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 Nikkei Econophysics Symposium (2nd : 2002 : Tokyo, Japan)
 Tokyo : Springer Japan, 2004.
 Description
 Book — 1 online resource (x, 334 pages) : illustrations
 Summary

 Market properties: Basic statistics
 Predictability
 New methods
 Various markets
 Models
 Other topics: Income distribution
 Company's risks
 Theories.
 Palm, Günter.
 Paris, International Institute for Educational Planning, 1967.
 Description
 Book — iii, 12 p. 27 cm.
 Online
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370.9409 .F981 NO.19  Available 
 Workshop on Economics with Heterogeneous Interacting Agents (7th : 2002 : Trieste, Italy)
 New York : SpringerVerlag, 2003.
 Description
 Book — xv, 402 p. : ill. ; 24 cm.
 Summary

This book deals with the economy as a complex interactive system. The emphasis is on the direct interaction between agents rather than on the indirect and autonomous interaction through the market mechanism. Contributions from economists and physicists emphasise the consequences for aggregate behaviour of the interaction between agents with limited rationality. Models of financial markets which exhibit many of the stylised facts of empirical markets such as bubbles, herd behaviour and long memory are presented. This includes contributions on bargaining, buyerseller relations, the evolution of economic networks and several aspects of macroeconomic behaviour. This book will be of interest to all those interested in the foundations of collective social and economic behaviour and in particular, to those concerned with the dynamics of market behaviour and recent applications of physics to economics.
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 Online
 Workshop on Economics with Heterogeneous Interacting Agents (9th : 2004 : Kyoto University)
 Berlin ; New York : Springer, c2006.
 Description
 Book — xi, 347 p. : ill.
6. The complex networks of economic interactions : essays in agentbased economics and econophysics [2006]
 Workshop on Economics with Heterogeneous Interacting Agents (9th : 2004 : Kyoto University, Japan)
 Berlin ; [Great Britain] : Springer, c2006.
 Description
 Book — xi, 347 p. : ill. ; 24 cm.
 Summary

 Econophysics. Complex Economic Network. Economic Dynamics. AgentBased Modeling. Auction and TwoSided Matching. Minority Games and Collective Intelligence. GameTheoretic Approach.
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 Bellingham, Wash. : SPIE, c2008.
 Description
 Book — 1 v. (various pagings) : ill. ; 28 cm.
 New York : Nova Publishers, [2015]
 Description
 Book — 1 online resource.
 Summary

 COMPUTATIONAL DATA ANALYSIS TECHNIQUES IN ECONOMICS AND FINANCE; COMPUTATIONAL DATA ANALYSIS TECHNIQUES IN ECONOMICS AND FINANCE; Library of Congress CataloginginPublication Data; Contents; Preface;
 Chapter 1: Optimum Currency Areas within the US and Canada: A Data Analysis Approach; Abstract; 1. Introduction; 2. Methodology; 2.1. Correspondence Analysis; 2.2. Hierarchical Cluster Analysis; 2.3. Data; 3. Empirical Estimation; 3.1. Applying Correspondence Analysis; 3.2. Hierarchical Cluster Analysis; Conclusion; References.
 Chapter 2: Directional Forecasting in Financial Time Series Using Support Vector Machines: The USD/EURO Exchange RateAbstract; 1. Introduction; 2. Support Vector Machines; 2.1. Linear Separable Case; 2.2. Error Tolerant SVM; 2.3. Kernel Methods; 3. Data Analysis; 3.1. Data Collection and Kernel Selection; 3.2. Sensitivity Analysis; Acknowledgment; Conclusion; Appendix; References;
 Chapter 3: Inflation Forecasting in Greece Using a NeuroFuzzy System; Abstract; 1. Introduction; 1.1. Related Research; 2. Model Presentation; 2.1. ANFIS Architecture; 2.2. Learning Algorithm of ANFIS.
 2.3. Data and Model Parameters4. Model Performance Evaluations; Conclusion; References;
 Chapter 4: The Value of IPRs and Competitiveness Regarding FDI: Linear and NonLinear Analysis; Abstract; 1. Introduction; 2. FDI Background; 3. Competition Background; 4. IPR Background; 5. Competition Policy and the Exercise of Intellectual Property Rights; 6. Data and Methodology; 7. Empirical Results; 7.1. Linear Results; 7.2. NonLinear Results; Conclusion; Appendices; References; Cases;
 Chapter 5: The Modelling of Maintenance Cost: The Case of ContainerShips in DryDock; Abstract; 1. Introduction.
 2. Literature Review2.1. Prior Research on Operating and Maintenance Costs; 2.2. Containerships and Their Costs; 3. Hypotheses; 3.1. Age; 3.2. Size; 3.3. Stay Days; 3.4. Market Conditions; 3.5. Owners' Negotiating Capacity; 4. Data and Methodology; 4.1. Data Collected; 4.2. Methodology; 5. Discussion of Results; Conclusion; References;
 Chapter 6: Discounted Cash Flows through Expertons in Business Valuation Process; Abstract; 1. Introduction; 2. Preliminaries; 2.1. Literature Review in Business Valuation; 2.2. Fuzzy Methodology in Business Valuation; 3. Fuzzy Methodology for Uncertainty.
 3.1. Confidence Intervals3.2. Fuzzy Numbers; 3.3. Triangular Fuzzy Numbers; 3.4. Fuzzy Subsets; 3.5. Expertons; 4. Application on Business Valuation; 5. Discounted Cash Flows; 5.1. n Number of Years; 5.2. CF Cash Flow; 5.3. k Discount Rate; 5.4. Vn Residual Value; Result and Conclusion; References;
 Chapter 7: Leverage Premium in a Southern European Frame; Abstract; 1. Introduction; 2. Literature Review; 3. Data Collection and Sample Derivation; 4. Methodology; 4.1. Dependent Variable; 4.2. Independent Variables; 5. Empirical Results; 5.1. Full Sample Level; 5.1.1. One Factor Model.
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 Hainaut, Donatien.
 Cham, Switzerland : Springer, 2022.
 Description
 Book — 1 online resource
 Summary

 Preface. Acknowledgements. Notations.
 1. Switching Models: Properties and Estimation.
 2. Estimation of Continuous Time Processes by Markov Chain Monte Carlo.
 3. Particle Filtering and Estimation.
 4. Modeling of Spillover Effects in Stock Markets.
 5. NonMarkov Models for Contagion and Spillover.
 6. Fractional Brownian Motion.
 7. Gaussian Fields for Asset Prices.
 8. Levy Interest Rate Models With a Long Memory.
 9. Affine Volterra Processes and Rough Models.
 10. SubDiffusion for Illiquid Markets.
 11. A Fractional Dupire Equation for JumpDiffusions. References.
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10. A course on statistics for finance [2013]
 Sclove, Stanley L.
 Boca Raton, Fla. ; London : CRC Press, ©2013.
 Description
 Book — 1 online resource (xxvii, 245 pages) : illustrations
 Summary

 INTRODUCTORY CONCEPTS AND DEFINITIONS Review of Basic Statistics What Is Statistics? Characterizing Data Measures of Central Tendency Measures of Variability Higher Moments Summarizing Distributions Bivariate Data Three Variables TwoWay Tables
 Stock Price Series and Rates of Return Introduction Sharpe Ratio ValueatRisk Distributions for RORs
 Several Stocks and Their Rates of Return Introduction Review of Covariance and Correlation Two Stocks Three Stocks m Stocks
 REGRESSION Simple Linear Regression CAPM and Beta Introduction Simple Linear Regression Estimation Inference Concerning the Slope Testing Equality of Slopes of Two Lines through the Origin Linear Parametric Functions Variances Dependent upon X A Financial Application: CAPM and "Beta" Slope and Intercept
 Multiple Regression and Market Models Multiple Regression Models Market Models Models with Both Numerical and Dummy Explanatory Variables Model Building
 PORTFOLIO ANALYSIS MeanVariance Portfolio Analysis Introduction Two Stocks Three Stocks m Stocks m Stocks and a RiskFree Asset ValueatRisk Selling Short Market Models and Beta
 UtilityBased Portfolio Analysis Introduction SingleCriterion Analysis
 TIME SERIES ANALYSIS Introduction to Time Series Analysis Introduction Control Charts Moving Averages Need for Modeling Trend, Seasonality, and Randomness Models with Lagged Variables MovingAverage Models Identification of ARIMA Models Seasonal Data Dynamic Regression Models Simultaneous Equations Models
 Regime Switching Models Introduction Bull and Bear Markets
 Appendix A: Vectors and Matrices Appendix B: Normal Distributions Appendix C: Lagrange Multipliers Appendix D: Abbreviations and Symbols
 Index
 A Summary, Exercises, and Bibliography appear at the end of each chapter.
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11. Domestic finance [1997]
 Paris : Organisation for Economic Cooperation and Development ; [Washington, D.C. : OECD Washington Center, distributor], c1998.
 Description
 Book — 81 p. ; 27 cm.
 Online
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HG176 .D65 1998  Available 
 McCauley, Joseph L.
 Cambridge : Cambridge University Press, 2004.
 Description
 Book — 1 online resource (228 p.) : digital, PDF file(s).
 Summary

 Preface
 1. The moving target
 2. Neoclassical economic theory
 3. Probability and stochastic processes
 4. Scaling the ivory tower of finance
 5. Standard betting procedures in portfolio selection theory
 6. Dynamics of financial markets, volatility and option pricing
 7. Thermodynamic analogies vs. instability of markets
 8. Scaling, correlations and cascades in finance and turbulence
 9. What is complexity?
 References
 Index.
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 McCauley, Joseph L.
 2nd ed.  Cambridge, UK ; New York : Cambridge University Press, 2009.
 Description
 Book — xv, 270 p. : ill. ; 26 cm.
 Summary

 Preface
 1. Econophysics: why and what
 2. Neoclassical economic theory
 3. Probability and stochastic processes
 4. Introduction to financial economics
 5. Introduction to portfolio selection theory
 6. Scaling, pair correlations, and conditional densities
 7. Statistical ensembles: deducing dynamics from time series
 8. Martingale option pricing
 9. FX market globalization: evolution of the dollar to worldwide reserve currency
 10. Macroeconomics and econometrics: regression models vs. empirically based modeling
 11. Complexity
 Index.
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 McCauley, Joseph L.
 2nd ed.  Cambridge, UK ; New York : Cambridge University Press, 2009.
 Description
 Book — 1 online resource (xv, 270 pages) : illustrations
 Summary

 Preface
 1. Econophysics: why and what
 2. Neoclassical economic theory
 3. Probability and stochastic processes
 4. Introduction to financial economics
 5. Introduction to portfolio selection theory
 6. Scaling, pair correlations, and conditional densities
 7. Statistical ensembles: deducing dynamics from time series
 8. Martingale option pricing
 9. FX market globalization: evolution of the dollar to worldwide reserve currency
 10. Macroeconomics and econometrics: regression models vs. empirically based modeling
 11. Complexity
 Index.
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 EconophysKolkata (2nd : 2006 : Calcutta, India)
 Milan : SpringerVerlag Italia, c2006.
 Description
 Book — xiii, 253 p. : ill.
 Summary

 Markets and their Analysis. On StockPrice Fluctuations in the Periods of Booms and Stagnations. An Outlook on Correlations in Stock Prices. The Power (Law) of Indian Markets: Analysing NSE and BSE Trading Statistics. A Random Matrix Approach To Volatility In An Indian Financial Market. Why do Hurst Exponents of Traded Value Increase as the Logarithm of Company Size?. Statistical Distribution of Stock Returns Runs. Fluctuation Dynamics of Exchange Rates on Indian Financial Market. Noise Trading in an Emerging Market: Evidence and Analysis. How Random is the Walk: Efficiency of Indian Stock and Futures Markets. Markets and their Models. Models of Financial Market Information Ecology. Estimating Phenomenological Parameters in MultiAssets Markets. Agents Play Mixgame. Triangular Arbitrage as an Interaction in Foreign Exchange Markets. Modelling Limit Order Financial Markets. Two Fractal Overlap Time Series and Anticipation of Market Crashes. The Apparent Madness of Crowds: Irrational Collective Behavior Emerging from Interactions among Rational Agents. AgentBased Modelling with Wavelets and an Evolutionary Artificial Neural Network: Applications to CAC 40 Forecasting. Information Extraction in Scheduling Problems with NonIdentical Machines. Modelling Financial Time Series. Random Matrix Approach to Fluctuations and Scaling in Complex Systems. The Economic Efficiency of Financial Markets. Regional Inequality. Historical Notes. A Brief History of Economics: An Outsider's Account. The Nature and Future of Econophysics. Comments and Discussions. EconophysKolkata II Workshop Summary. Econophysics: Some Thoughts on Theoretical Perspectives. Comments on "Worrying Trends in Econophysics": Income Distribution Models.
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 EconophysKolkata (Workshop) (2nd : 2006 : Calcutta, India)
 Milan : SpringerVerlag Italia, ©2006.
 Description
 Book — 1 online resource (xiii, 253 pages) : illustrations Digital: text file.PDF.
 Summary

 Markets and their Analysis. On StockPrice Fluctuations in the Periods of Booms and Stagnations. An Outlook on Correlations in Stock Prices. The Power (Law) of Indian Markets: Analysing NSE and BSE Trading Statistics. A Random Matrix Approach To Volatility In An Indian Financial Market. Why do Hurst Exponents of Traded Value Increase as the Logarithm of Company Size?. Statistical Distribution of Stock Returns Runs. Fluctuation Dynamics of Exchange Rates on Indian Financial Market. Noise Trading in an Emerging Market: Evidence and Analysis. How Random is the Walk: Efficiency of Indian Stock and Futures Markets. Markets and their Models. Models of Financial Market Information Ecology. Estimating Phenomenological Parameters in MultiAssets Markets. Agents Play Mixgame. Triangular Arbitrage as an Interaction in Foreign Exchange Markets. Modelling Limit Order Financial Markets. Two Fractal Overlap Time Series and Anticipation of Market Crashes. The Apparent Madness of Crowds: Irrational Collective Behavior Emerging from Interactions among Rational Agents. AgentBased Modelling with Wavelets and an Evolutionary Artificial Neural Network: Applications to CAC 40 Forecasting. Information Extraction in Scheduling Problems with NonIdentical Machines. Modelling Financial Time Series. Random Matrix Approach to Fluctuations and Scaling in Complex Systems. The Economic Efficiency of Financial Markets. Regional Inequality. Historical Notes. A Brief History of Economics: An Outsider's Account. The Nature and Future of Econophysics. Comments and Discussions. EconophysKolkata II Workshop Summary. Econophysics: Some Thoughts on Theoretical Perspectives. Comments on "Worrying Trends in Econophysics": Income Distribution Models.
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 Japan ; New York : Springer, ©2002.
 Description
 Book — 1 online resource (x, 352 pages) : illustrations Digital: PDF.text file.
 Summary

 Part 1. Empirical Facts of Financial Market Fluctuations: Basic Market Statistics. CrossCorrelations. Market Anomalies
 Part 2. Various Approaches to Financial Markets: AgentBased Modeling. Stochastic Modeling. Prediction and Investment Strategy
 Part 3. Other Topics: Relation to Economic Theories. Corporate and Individual Statistics.
18. Essentials of Excel VBA, Python, and R. Volume I, Financial statistics and portfolio analysis [2022]
 Lee, John C. author.
 Second edition.  Cham : Springer, [2022]
 Description
 Book — 1 online resource (xvi, 696 pages) : illustrations (chiefly color)
 Summary

 Chapter 1. Introduction.
 Chapter 2. Data Collection, Presentation, and Yahoo Finance.
 Chapter 3. Histograms and the Rate of Returns of JPM and JNJ.
 Chapter 4. Numerical Summary Measures on Stock Rates of Return and Market Rates of Return.
 Chapter 5. Probability Concepts and their Analysis.
 Chapter 6. Discrete Random Variables and Probability Distributions.
 Chapter 7. The Normal and Lognormal Distributions.
 Chapter 8. Sampling Distributions and Central Limit Theorem.
 Chapter 9. Other Continuous Distributions.
 Chapter 10. Estimation.
 Chapter 11. Hypothesis Testing.
 Chapter 12. Analysis of Variance and ChiSquare Tests.
 Chapter 13. Simple Linear Regression and the Correlation Coefficient.
 Chapter 14. Simple Linear Regression and Correlation: Analyses and Applications.
 Chapter 15. Multiple Linear Regression.
 Chapter 16. Residual and Regression Assumption Analysis.
 Chapter 17. Nonparametric Statistics.
 Chapter 18. Time Series: Analysis, Model, and Forecasting.
 Chapter 19. Index Numbers and Stock Market Indexes.
 Chapter 20. Sampling Surveys: Methods and Applications.
 Chapter 21. Statistical Decision Theory.
 Chapter 22. Sources of Risks and their Determination.
 Chapter 23. RiskAversion, Capital Asset Allocation, and Markowitz Portfolio Selection Model.
 Chapter 24. Capital Asset Pricing Model and Beta Forecasting.
 Chapter 25. SingleIndex Models for Portfolio Selection.
 Chapter 26. Sharpe Performance Measure and Treynor Performance Measure Approach to Portfolio Analysis.
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 Lee, John C. author.
 Second edition.  Cham : Springer, [2023]
 Description
 Book — 1 online resource (xv, 523 pages) : illustrations (chiefly color)
 Summary

 Chapter 1. Introduction
 Chapter 2. Introduction to Excel Programming
 Chapter 3. Introduction to VBA Programming
 Chapter 4. Professional Techniques Used in Excel and Excel VBA Techniques
 Chapter 5. Decision Tree Approach for Binomial Option Pricing Model
 Chapter 6. Microsoft Excel Approach to Estimating Alternative Option Pricing Models
 Chapter 7. Alternative Methods to Estimate Implied Variances
 Chapter 8. Greek Letters and Portfolio Insurance
 Chapter 9. Portfolio Analysis and Option Strategies
 Chapter 10. Alternative Simulation Methods and Their Applications
 Chapter 11. Linear Models for Regression
 Chapter 12. Kernel Linear Model
 Chapter 13. Neural Networks and Deep Learning
 Chapter 14. Applications of Alternative Machine Learning Methods for Credit Card Default Forecasting
 Chapter 15. An Application of Deep Neural Networks for Predicting Credit Card Delinquencies
 Chapter 16. Binomial/Trinomial Tree Option Pricing Using Python
 Chapter 17. Financial Ratios and its Applications
 Chapter 18. Time Value Money Analysis
 Chapter 19. Capital Budgeting under Certainty and Uncertainty
 Chapter 20. Financial Planning and Forecasting
 Chapter 21. Hedge Ratios: Theory and Applications
 Chapter 22. Application of simultaneous equation in finance research: Methods and empirical results
 Chapter 23. Using R Program to Estimate Binomial Option Pricing Model and Black & Scholes Option Pricing Model.
 Borowiak, Dale, author.
 2nd edition.  Chapman and Hall/CRC, 2013.
 Description
 Book — 1 online resource (392 pages) Digital: text file.
 Summary

Understand UptoDate Statistical Techniques for Financial and Actuarial ApplicationsSince the first edition was published, statistical techniques, such as reliability measurement, simulation, regression, and Markov chain modeling, have become more prominent in the financial and actuarial industries. Consequently, practitioners and students must ac.
 Borowiak, Dale S., 1952
 New York : Marcel Dekker, c2003.
 Description
 Book — xi, 330 p. : ill. ; 24 cm.
 Summary

 Statistical ConceptsFinancial Computational ModelsDeterministic Status ModelsFuture Lifetime Random VariableFuture Lifetime Models and TablesStochastic Status ModelsScenario and Simulation TestingFurther Statistical ConsiderationsAppendix: Standard Normal TablesReferencesIndex.
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 Online
Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
HG173 .B67 2003  Unknown 
23. Financial and insurance formulas [2010]
 Cipra, Tomas.
 Heidelberg ; New York : PhysicaVerlag, ©2010.
 Description
 Book — 1 online resource (xv, 418 pages) Digital: text file.PDF.
 Summary

 pt. 1. Financial formulas
 pt. 2. Insurance formulas
 pt. 3. Formulas of related disciplines.
 Fogler, H. Russell.
 Englewood Cliffs, N.J. : PrenticeHall, c1982.
 Description
 Book — xii, 212 p. : ill ; 24 cm.
 Online
Business Library
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HB139 .F63  Available 
25. Financial market complexity [2003]
 Johnson, Neil F., 1961
 Oxford ; New York : Oxford University Press, 2003.
 Description
 Book — x, 254 p. : ill. ; 25 cm.
 Summary

 1. Financial markets as complex systems
 2. Standard finance theory
 3. A complex walk down Wall Street
 4. Financial market models with global interactions
 5. Financial market models with local interactions
 6. Nonzero risk in the real world
 7. Deterministic dynamics, chaos and crashes.
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Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
HG176.5 .J64 2003  Unknown 
26. Financial mathematics for actuaries [2018]
 Chan, WaiSum, author.
 Second edition.  New Jersey : World Scientific, [2018]
 Description
 Book — xviii, 353 pages ; 25 cm
 Online
Science Library (Li and Ma)
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HF5691 .C345 2018  Unknown 
 Mandelbrot, Benoit B.
 New York : Springer, c1997.
 Description
 Book — x, 551 p. : ill. ; 25 cm.
 Summary

 List of Chapters. El Introduction (1996). E2 Discontinuity and scaling: scope and likely limitations (1996). E3 New methods in statistical economics (M 1963e). E4 Sources of inspiration and historical background (1996). E5 States of randomness from mild to wild, and concentration in the short, medium and long run (1996). E6 Selfsimilarity and panorama of selfaffinity (1996). E7 Ranksize plots, Zipf's law, and scaling (1996). E8 Proportional growth with or without diffusion, and other explanations of scaling (1996). * Appendices (M 1964o, M 1974d). E9 A case against the lognormal distribution (1996). E10 Lstable model for the distribution of income (M 1960i). * Appendices (M 1963i, M 1963j). E11 Lstability and multiplicative variation of income (M 1961e). E12 Scaling distributions and income maximization (M 1962q). E13 Industrial concentration and scaling (1996). E14 The variation of certain speculative prices (M 1963b). * Appendices (Fama & Blume 1966, M 1972b, M 1982c). E15 The variation of the price of cotton, wheat, and railroad stocks, and of some financial rates (M 1967j). E16 Mandelbrot on price variation (Fama 1963). E17 Comments by P. H. Cootner, E. Parzen & W. S. Morris (1960s), and responses (1996). E18 Computation of the Lstable distributions (1996). E19 Nonlinear forecasts, rational bubbles, and martingales (M 1966b). E20 Limitations of efficiency and martingales (M 1971e). E21 Selfaffine variation in fractal time (M & Taylor 1967, M 1973c). Cumulative Bibliography.
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HG176.5 .M36 1997  Available 
 Probability and finance
 Shafer, Glenn, 1946 author.
 Hoboken, NJ : John Wiley & Sons, Inc., 2019.
 Description
 Book — 1 online resource Digital: data file.
 Summary

Gametheoretic probability and finance come of age Glenn Shafer and Vladimir Vovk Probability and Finance, published in 2001, showed that perfectinformation games can be used to define mathematical probability. Based on fifteen years of further research, GameTheoretic Foundations for Probability and Finance presents a mature view of the foundational role game theory can play. Its account of probability theory opens the way to new methods of prediction and testing and makes many statistical methods more transparent and widely usable. Its contributions to finance theory include purely gametheoretic accounts of Ito stochastic calculus, the capital asset pricing model, the equity premium, and portfolio theory. GameTheoretic Foundations for Probability and Finance is a book of research. It is also a teaching resource. Each chapter is supplemented with carefully designed exercises and notes relating the new theory to its historical context. Praise from early readers ver since Kolmogorov's Grundbegriffe, the standard mathematical treatment of probability theory has been measuretheoretic. In this groundbreaking work, Shafer and Vovk give a gametheoretic foundation instead. While being just as rigorous, the gametheoretic approach allows for vast and useful generalizations of classical measuretheoretic results, while also giving rise to new, radical ideas for prediction, statistics and mathematical finance without stochastic assumptions. The authors set out their theory in great detail, resulting in what is definitely one of the most important books on the foundations of probability to have appeared in the last few decades. Peter Gr130 0Wiley series in probability and statisticsnwald, CWI and University of Leiden hafer and Vovk have thoroughly rewritten their 2001 book on the gametheoretic foundations for probability and for finance. They have included an account of the tremendous growth that has occurred since, in the gametheoretic and pathwise approaches to stochastic analysis and in their applications to continuoustime finance. This new book will undoubtedly spur a better understanding of the foundations of these very important fields, and we should all be grateful to its authors. Ioannis Karatzas, Columbia University.
 Probability and finance
 Shafer, Glenn, 1946 author.
 Hoboken, NJ : John Wiley & Sons, Inc., 2019.
 Description
 Book — 1 online resource Digital: data file.
 Summary

Gametheoretic probability and finance come of age Glenn Shafer and Vladimir Vovk Probability and Finance, published in 2001, showed that perfectinformation games can be used to define mathematical probability. Based on fifteen years of further research, GameTheoretic Foundations for Probability and Finance presents a mature view of the foundational role game theory can play. Its account of probability theory opens the way to new methods of prediction and testing and makes many statistical methods more transparent and widely usable. Its contributions to finance theory include purely gametheoretic accounts of Ito stochastic calculus, the capital asset pricing model, the equity premium, and portfolio theory. GameTheoretic Foundations for Probability and Finance is a book of research. It is also a teaching resource. Each chapter is supplemented with carefully designed exercises and notes relating the new theory to its historical context. Praise from early readers ver since Kolmogorov's Grundbegriffe, the standard mathematical treatment of probability theory has been measuretheoretic. In this groundbreaking work, Shafer and Vovk give a gametheoretic foundation instead. While being just as rigorous, the gametheoretic approach allows for vast and useful generalizations of classical measuretheoretic results, while also giving rise to new, radical ideas for prediction, statistics and mathematical finance without stochastic assumptions. The authors set out their theory in great detail, resulting in what is definitely one of the most important books on the foundations of probability to have appeared in the last few decades. Peter Gr130 0Wiley series in probability and statisticsnwald, CWI and University of Leiden hafer and Vovk have thoroughly rewritten their 2001 book on the gametheoretic foundations for probability and for finance. They have included an account of the tremendous growth that has occurred since, in the gametheoretic and pathwise approaches to stochastic analysis and in their applications to continuoustime finance. This new book will undoubtedly spur a better understanding of the foundations of these very important fields, and we should all be grateful to its authors. Ioannis Karatzas, Columbia University.
 New York, NY : SpringerReference, [2014]
 Description
 Book — 1 online resource (xxviii, 2903 pages) : illustrations (some color) Digital: text file; PDF.
 Summary

 Introduction to Financial Econometrics and Statistics. Experience, Information Asymmetry, and Rational Forecast Bias. An Overview of Modeling Dimensions for Performance Appraisal of Global Mutual Funds. Simulation as a Research Tool for Market Architects. Motivations for Issuing Putable Debt: An Empirical Analysis. Multi RiskPremia Model of U.S. Bank Returns: An Integration of CAPM and APT. NonParametric Bounds for European Option Prices. Can TimeVarying Copulas Improve MeanVariance Portfolio? Determinations of Corporate Earnings Forecast Accuracy: Taiwan Market Experience. MarketBased Accounting Research (MBAR) Models: A Test of ARIMAX Modeling. An Assessment of Copula Functions Approach in Conjunction with Factor Model in Portfolio Credit Risk Management. Assessing Importance of TimeSeries versus CrossSectional Changes in Panel Data: A Study of International Variations in ExAnte Equity Premia and Financial Architecture. Does Banking Capital Reduce Risk?: An Application of Stochastic Frontier Analysis and GMM Approach. Evaluating LongHorizon Event Study Methodology. Effect of Unexpected Volatility Shocks on Intertemporal RiskReturn Relation. Combinatorial Methods for Constructing Credit Risk Ratings. Dynamic Interactions in the Taiwan Stock Exchange: A Threshold VAR Model. Methods of Denoising Financial Data. Analysis of Financial TimeSeries using Wavelet Methods. Composite GoodnessofFit Tests for Left Truncated Loss Sample. Effect of Merger on the Credit Rating and Performance of Taiwan Security Firms. On/offtheRun Yield Spread Puzzle: Evidence from Chinese Treasury Markets. Factor Copula for Defaultable Basket Credit Derivatives. Panel Data Analysis and Bootstrapping: Application to China Mutual Funds. Market Segmentation and Pricing of Closedend Country Funds: An Empirical Analysis. A Comparison of Portfolios using Different Risk Measurements. Using Alternative Models and a Combining Technique in Credit Rating Forecasting: An Empirical Study. Can We Use the CAPM as an Investment Strategy?: An Intuitive CAPM and Efficiency Test. Group Decision Making Tools for Managerial Accounting and Finance Applications. Statistics Methods Applied in Employee Stock Options. Structural Change and Monitoring Tests. Consequences of Option Pricing of a Long Memory in Volatility. Seasonal aspects of Australian electricity market. Pricing Commercial Timberland Returns in the United States. Optimal Orthogonal Portfolios with Conditioning Information. MultiFactor, MultiIndicator Approach to Asset Pricing: Method and Empirical Evidence. Binomial OPM, BlackScholes OPM and Their Relationship: Decision Tree and Microsoft Excel Approach. Dividend Payments and Share Repurchases of U.S. Firms: An Econometric Approach. Term Structure Modeling and Forecasting Using the NelsonSiegel Model. The intertemporal relation between expected return and risk on currency. Quantile Regression and ValueatRisk. Earnings Quality and Board Structure: Evidence from South East Asia. Rationality and Heterogeneity of Survey Forecasts of the YenDollar Exchange Rate: A Reexamination. Stochastic Volatility Structures and IntraDay Asset Price Dynamics. Optimal Asset Allocation under VaR Criterion: Taiwan Stock Market. Applications of Switching Model in Finance and Accounting. Matched Sample Comparison Group Analysis. A QuasiMaximum Likelihood Estimation Strategy for ValueatRisk Forecasting: Application to Equity Index FuturesA Markets. Computer Technology for Financial Service. LongRun Stock Return and the Statistical Inference. ValueatRisk Estimation via a SemiParametric Approach: Evidence from the Stock Markets. Modeling Multiple Asset Returns by a TimeVarying t Copula Model. Internet Bubble Examination with MeanVariance Ratio. Quantile Regression in Risk Calibration. Strike Prices of Options for Overconfident Executives. Density and Conditional Distribution Based Specification Analysis. Assessing the Performance of Estimators Dealing with Measurement Errors. Realized Distributions of Dynamic Conditional Correlation and Volatility Thresholds in the Crude Oil, Gold and Dollar/Pound Currency Markets. PreIT Policy, PostIT Policy, and the Real Sphere in Turkey. Determination of Capital Structure: A LISREL Model Approach. Evaluating the Effectiveness of Futures Hedging. Evidence on Earning Management by Integrated Oil and Gas Companies. A Comparative Study of Two Models SV with MCMC Algorithm. Internal Control Material Weakness, Analysts Accuracy and Bias, and Brokerage Reputation. What Increases Banks Vulnerability to Financial Crisis: ShortTerm Financing or Illiquid Assets? Accurate Formulae for Evaluating Barrier Options with Dividends Payout and the Application in Credit Risk Valuation. Pension Funds: Financial Econometrics on the Herding Phenomenon in Spain and the United Kingdom. Estimating the Correlation of Asset Returns: A Quantile Dependence Perspective. MultiCriteria Decision Making for Evaluating Mutual Funds Investment Strategies. Econometric Analysis of Currency Carry Trade. Analytical Bounds for Treasury Bond Futures prices. Rating Dynamics of Fallen Angels and their Speculative GradeRated Peers: Static vs. Dynamic Approach. Creation and Control of Bubbles: Managers Compensation Schemes, Risk Aversion, and Wealth and Short Sale Constraints. Range Volatility: A Review of Models and Empirical Studies. Business Models: Applications to Capital Budgeting, Equity Value, and Return Attribution. VAR Models: Estimation, Inferences, and Applications. Model Selection for HighDimensional Problems. Hedonic Regression Models. Optimal Payout Ratio under Uncertainty and the Flexibility Hypothesis: Theory and Empirical Evidence. Modeling Asset Returns with Skewness, Kurtosis, and Outliers. Alternative Models for Estimating the Cost of Equity Capital for Property/Casualty Insurers: Combined Estimator Approach. A VGNGARCH Model for Impacts of Extreme Events on Stock Returns. RiskAverse Portfolio Optimization via Stochastic Dominance Constraints. Implementation Problems and Solutions in Stochastic Volatility Models of the Heston Type. Stochastic ChangePoint Models of Asset Returns and Their Volatilities. Unspanned Stochastic Volatilities and Interest Rate Derivatives Pricing. Alternative Equity Valuation Models. Time Series Models to Predict the Net Asset Value (NAV) of an Asset Allocation Mutual Fund VWELX. Discriminant Analysis and Factor Analysis: Theory And Method. Implied Volatility: Theory and Empirical Method. Measuring Credit Risk in a Factor Copula Model. Instantaneous Volatility Estimation by Nonparametric Fourier Transform Methods. A Dynamic CAPM with Supply Effect Theory and Empirical Results. A Generalized Model for Optimum Futures Hedge Ratio. Instrument Variable Approach to Correct for Endogeneity in Finance. Application of Poisson Mixtures in the Estimation of Probability of Informed Trading. CEO Stock Options and Analysts Forecast Accuracy and Bias. Option Pricing and Hedging Performance under Stochastic Volatility and Stochastic Interest Rates. THE LE CHATELIER PRINCIPLE OF THE CAPITAL MARKET EQUILIBRIUM. Econometric Measures of Liquidity.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 New Jersey : World Scientific, [2021]
 Description
 Book — 1 online resource
 Summary

This fourvolume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multivolume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.
(source: Nielsen Book Data)
32. Handbook of financial time series [2009]
 Berlin ; London : Springer, ©2009.
 Description
 Book — 1 online resource (xxix, 1050 pages) : illustrations
 Summary

 Recent Developments in GARCH Modeling. An Introduction to Univariate GARCH Models. Stationarity, Mixing, Distributional Properties and Moments of GARCH(p, q)Processes. ARCH( ) Models and Long Memory Properties. A Tour in the Asymptotic Theory of GARCH Estimation. Practical Issues in the Analysis of Univariate GARCH Models. Semiparametric and Nonparametric ARCH Modeling. Varying Coefficient GARCH Models. Extreme Value Theory for GARCH Processes. Multivariate GARCH Models. Recent Developments in Stochastic Volatility Modeling. Stochastic Volatility: Origins and Overview. Probabilistic Properties of Stochastic Volatility Models. MomentBased Estimation of Stochastic Volatility Models. Parameter Estimation and Practical Aspects of Modeling Stochastic Volatility. Stochastic Volatility Models with Long Memory. Extremes of Stochastic Volatility Models. Multivariate Stochastic Volatility. Topics in Continuous Time Processes. An Overview of AssetPrice Models. OrnsteinUhlenbeck Processes and Extensions. JumpType Levy Processes. LevyDriven ContinuousTime ARMA Processes. Continuous Time Approximations to GARCH and Stochastic Volatility Models. Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance. Parametric Inference for Discretely Sampled Stochastic Differential Equations. Realized Volatility. Estimating Volatility in the Presence of Market Microstructure Noise: A Review of the Theory and Practical Considerations. Option Pricing. An Overview of Interest Rate Theory. Extremes of ContinuousTime Processes.. Topics in Cointegration and Unit Roots. Cointegration: Overview and Development. Time Series with Roots on or Near the Unit Circle. Fractional Cointegration. Special Topics  Risk. Different Kinds of Risk. ValueatRisk Models. CopulaBased Models for Financial Time Series. Credit Risk Modeling. Special Topics  Time Series Methods. Evaluating Volatility and Correlation Forecasts. Structural Breaks in Financial Time Series. An Introduction to Regime Switching Time Series Models. Model Selection. Nonparametric Modeling in Financial Time Series. Modelling Financial High Frequency Data Using Point Processes. Special Topics  Simulation Based Methods. Resampling and Subsampling for Financial Time Series. Markov Chain Monte Carlo. Particle Filtering.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 First edition.  Amsterdam ; Boston : Elsevier, [2003]
 Description
 Book — 1 online resource (1 volume) : illustrations
 Summary

 Heavy tails in finance for independent or multifractal price increments / Benoit B. Mandelbrot
 Financial risk and heavy tails / Brendan O. Bradley and Murad S. Taqqu
 Modeling financial data with stable distributions / John P. Nolan
 Statistical issues in modeling multivariate stable portfolios / Tomasz J. Kozubowski, Anna K. Panorska and Svetlozar T. Rachev
 Jumpdiffusion models / Wolfgang J. Runggaldier
 Hyperbolic processes in finance / Bo Martin Bibby and Michael Sørensen
 Stable modeling of market and credit value at risk / Svetlozar T. Rachev, Eduardo S. Schwartz and Irina Khindanova
 Modelling dependence with copulas and applications to risk management / Paul Embrechts, Filip Lindskog and Alexander McNeil
 Prediction of financial downsiderisk with heavytailed conditional distributions / Stefan Mittnik and Marc S. Paolella
 Stable nonGaussian models for credit risk management / Bernhard Martin, Svetlozar T. Rachev and Eduardo S. Schwartz
 Multifactor stochastic variance models in risk management : maximum entropy approach and Lévy processes / Alexander Levin and Alexander Tchernitser
 Modelling the term structure of monetary rates / Luisa Izzi
 Asset liability management : a review and some new results in the presence of heavy tails / Yesim Tokat, Svetlozar T. Rachev and Eduardo S. Schwartz
 Portfolio choice theory with nonGaussian distributed returns / Sergio Ortobelli [and three others]
 Portfolio modeling with heavy tailed random vectors / Mark M. Meerschaert and HansPeter Scheffler
 Long range dependence in heavy tailed stochastic processes / Borjana RachevaIotova and Gennaday Samorodnitsky.
(source: Nielsen Book Data)
 Jansen, Stefan, author.
 Birmingham, UK : Packt Publishing, 2018.
 Description
 Book — 1 online resource (1 volume) : illustrations
 Summary

 Table of Contents Machine Learning for Trading Market and Fundamental Data Alternative Data for Finance Alpha Factor Research Strategy Evaluation The Machine Learning Process Linear Models Time Series Models Bayesian Machine Learning Decision Trees and Random Forests Gradient Boosting Machines Unsupervised Learning Working with Text Data Topic Modeling Word Embeddings Next Steps.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Jansen, Stefan, author.
 Birmingham, UK : Packt Publishing, 2018.
 Description
 Book — 1 online resource (1 volume) : illustrations
 Summary

 Table of Contents Machine Learning for Trading Market and Fundamental Data Alternative Data for Finance Alpha Factor Research Strategy Evaluation The Machine Learning Process Linear Models Time Series Models Bayesian Machine Learning Decision Trees and Random Forests Gradient Boosting Machines Unsupervised Learning Working with Text Data Topic Modeling Word Embeddings Next Steps.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Ibragimov, Rustam.
 Singapore : World Scientific Publishing Co. Pte Ltd., c2017.
 Description
 Book — 1 online resource (303 p.) : ill.
 Summary

"This book offers a unified approach to the study of crises, large fluctuations, dependence and contagion effects in economics and finance. It covers important topics in statistical modeling and estimation, which combine the notions of copulas and heavy tails — two particularly valuable tools of today's research in economics, finance, econometrics and other fields — in order to provide a new way of thinking about such vital problems as diversification of risk and propagation of crises through financial markets due to contagion phenomena, among others. The aim is to arm today's economists with a toolbox suited for analyzing multivariate data with many outliers and with arbitrary dependence patterns. The methods and topics discussed and used in the book include, in particular, majorization theory, heavytailed distributions and copula functions — all applied to study robustness of economic, financial and statistical models, and estimation methods to heavy tails and dependence."Publisher's website.
 Ursone, Pierino, 1966
 1  Hoboken : Wiley, 2015.
 Description
 Book — 1 online resource.
 Summary

 Preface ix
 Chapter 1 Introduction 1
 Chapter 2 The Normal Probability Distribution 7 Standard deviation in a financial market 8 The impact of volatility and time on the standard deviation 8
 Chapter 3 Volatility 11 The probability distribution of the value of a Future after one year of trading 11 Normal distribution versus lognormal distribution 11 Calculating the annualised volatility traditionally 15 Calculating the annualised volatility without 17 Calculating the annualised volatility applying the 16% rule 19 Variation in trading days 20 Approach towards intraday volatility 20 Historical versus implied volatility 23
 Chapter 4 Put Call Parity 25 Synthetically creating a Future long position, the reversal 29 Synthetically creating a Future short position, the conversion 30 Synthetic options 31 Covered call writing 34 Short note on interest rates 35
 Chapter 5 Delta 37 Change of option value through the delta 38 Dynamic delta 40 Delta at different maturities 41 Delta at different volatilities 44 20 80 Delta region 46 Delta per strike 46 Dynamic delta hedging 47 The at the money delta 50 Delta changes in time 53
 Chapter 6 Pricing 55 Calculating the at the money straddle using Black and Scholes formula 57 Determining the value of an at the money straddle 59
 Chapter 7 Delta II 61 Determining the boundaries of the delta 61 Valuation of the at the money delta 64 Delta distribution in relation to the at the money straddle 65 Application of the delta approach, determining the delta of a call spread 68
 Chapter 8 Gamma 71 The aggregate gamma for a portfolio of options 73 The delta change of an option 75 The gamma is not a constant 76 Long term gamma example 77 Short term gamma example 77 Very short term gamma example 78 Determining the boundaries of gamma 79 Determining the gamma value of an at the money straddle 80 Gamma in relation to time to maturity, volatility and the underlying level 82 Practical example 85 Hedging the gamma 87 Determining the gamma of out of the money options 89 Derivatives of the gamma 91
 Chapter 9 Vega 93 Different maturities will display different volatility regime changes 95 Determining the vega value of at the money options 96 Vega of at the money options compared to volatility 97 Vega of at the money options compared to time to maturity 99 Vega of at the money options compared to the underlying level 99 Vega on a 3dimensional scale, vega vs maturity and vega vs volatility 101 Determining the boundaries of vega 102 Comparing the boundaries of vega with the boundaries of gamma 104 Determining vega values of out of the money options 105 Derivatives of the vega 108 Vomma 108
 Chapter 10 Theta 111 A practical example 112 Theta in relation to volatility 114 Theta in relation to time to maturity 115 Theta of at the money options in relation to the underlying level 117 Determining the boundaries of theta 118 The gamma theta relationship 120 Theta on a 3dimensional scale, theta vs maturity and theta vs volatility 125 Determining the theta value of an at the money straddle 126 Determining theta values of out of the money options 127
 Chapter 11 Skew 129 Volatility smiles with different times to maturity 131 Sticky at the money volatility 133
 Chapter 12 Spreads 135 Call spread (horizontal) 135 Put spread (horizontal) 137 Boxes 138 Applying boxes in the real market 139 The Greeks for horizontal spreads 140 Time spread 146 Approximation of the value of at the money spreads 148 Ratio spread 149
 Chapter 13 Butterfly 155 Put call parity 158 Distribution of the butterfly 159 Boundaries of the butterfly 161 Method for estimating at the money butterfly values 163 Estimating out of the money butterfly values 164 Butterfly in relation to volatility 165 Butterfly in relation to time to maturity 166 Butterfly as a strategic play 166 The Greeks of a butterfly 167 Straddle strangle or the Iron fly 171
 Chapter 14 Strategies 173 Call 173 Put 174 Call spread 175 Ratio spread 176 Straddle 177 Strangle 178 Collar (risk reversal, fence) 178 Gamma portfolio 179 Gamma hedging strategies based on Monte Carlo scenarios 180 Setting up a gamma position on the back of prevailing kurtosis in the market 190 Excess kurtosis 191 Benefitting from a platykurtic environment 192 The mesokurtic market 193 The leptokurtic market 193 Transition from a platykurtic environment towards a leptokurtic environment 194 Wrong hedging strategy: Killergamma 195 Vega convexity/Vomma 196 Vega convexity in relation to time/Veta 202 Index 205.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Ursone, Pierino, 1966 author.
 Chichester, West Sussex, United Kingdom : John Wiley & Sons, 2015.
 Description
 Book — 1 online resource (1 volume) : illustrations.
 Summary

 Preface ix
 Chapter 1 Introduction 1
 Chapter 2 The Normal Probability Distribution 7 Standard deviation in a financial market 8 The impact of volatility and time on the standard deviation 8
 Chapter 3 Volatility 11 The probability distribution of the value of a Future after one year of trading 11 Normal distribution versus lognormal distribution 11 Calculating the annualised volatility traditionally 15 Calculating the annualised volatility without 17 Calculating the annualised volatility applying the 16% rule 19 Variation in trading days 20 Approach towards intraday volatility 20 Historical versus implied volatility 23
 Chapter 4 Put Call Parity 25 Synthetically creating a Future long position, the reversal 29 Synthetically creating a Future short position, the conversion 30 Synthetic options 31 Covered call writing 34 Short note on interest rates 35
 Chapter 5 Delta 37 Change of option value through the delta 38 Dynamic delta 40 Delta at different maturities 41 Delta at different volatilities 44 20 80 Delta region 46 Delta per strike 46 Dynamic delta hedging 47 The at the money delta 50 Delta changes in time 53
 Chapter 6 Pricing 55 Calculating the at the money straddle using Black and Scholes formula 57 Determining the value of an at the money straddle 59
 Chapter 7 Delta II 61 Determining the boundaries of the delta 61 Valuation of the at the money delta 64 Delta distribution in relation to the at the money straddle 65 Application of the delta approach, determining the delta of a call spread 68
 Chapter 8 Gamma 71 The aggregate gamma for a portfolio of options 73 The delta change of an option 75 The gamma is not a constant 76 Long term gamma example 77 Short term gamma example 77 Very short term gamma example 78 Determining the boundaries of gamma 79 Determining the gamma value of an at the money straddle 80 Gamma in relation to time to maturity, volatility and the underlying level 82 Practical example 85 Hedging the gamma 87 Determining the gamma of out of the money options 89 Derivatives of the gamma 91
 Chapter 9 Vega 93 Different maturities will display different volatility regime changes 95 Determining the vega value of at the money options 96 Vega of at the money options compared to volatility 97 Vega of at the money options compared to time to maturity 99 Vega of at the money options compared to the underlying level 99 Vega on a 3dimensional scale, vega vs maturity and vega vs volatility 101 Determining the boundaries of vega 102 Comparing the boundaries of vega with the boundaries of gamma 104 Determining vega values of out of the money options 105 Derivatives of the vega 108 Vomma 108
 Chapter 10 Theta 111 A practical example 112 Theta in relation to volatility 114 Theta in relation to time to maturity 115 Theta of at the money options in relation to the underlying level 117 Determining the boundaries of theta 118 The gamma theta relationship 120 Theta on a 3dimensional scale, theta vs maturity and theta vs volatility 125 Determining the theta value of an at the money straddle 126 Determining theta values of out of the money options 127
 Chapter 11 Skew 129 Volatility smiles with different times to maturity 131 Sticky at the money volatility 133
 Chapter 12 Spreads 135 Call spread (horizontal) 135 Put spread (horizontal) 137 Boxes 138 Applying boxes in the real market 139 The Greeks for horizontal spreads 140 Time spread 146 Approximation of the value of at the money spreads 148 Ratio spread 149
 Chapter 13 Butterfly 155 Put call parity 158 Distribution of the butterfly 159 Boundaries of the butterfly 161 Method for estimating at the money butterfly values 163 Estimating out of the money butterfly values 164 Butterfly in relation to volatility 165 Butterfly in relation to time to maturity 166 Butterfly as a strategic play 166 The Greeks of a butterfly 167 Straddle strangle or the Iron fly 171
 Chapter 14 Strategies 173 Call 173 Put 174 Call spread 175 Ratio spread 176 Straddle 177 Strangle 178 Collar (risk reversal, fence) 178 Gamma portfolio 179 Gamma hedging strategies based on Monte Carlo scenarios 180 Setting up a gamma position on the back of prevailing kurtosis in the market 190 Excess kurtosis 191 Benefitting from a platykurtic environment 192 The mesokurtic market 193 The leptokurtic market 193 Transition from a platykurtic environment towards a leptokurtic environment 194 Wrong hedging strategy: Killergamma 195 Vega convexity/Vomma 196 Vega convexity in relation to time/Veta 202 Index 205.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Mantegna, Rosario N. (Rosario Nunzio), 1960
 Cambridge, UK ; New York : Cambridge University Press, 2000.
 Description
 Book — 1 online resource (ix, 148 pages) : illustrations Digital: data file.
 Summary

 Introduction
 Efficient market hypothesis
 Random walk
 Levy stochastic processes and limit theorems
 Scales in financial data
 Stationarity and time correlation
 Time correlation in financial time series
 Stochastic models of price dynamics
 Scaling and its breakdown
 ARCH and GARCH processes
 Financial markets and turbulence
 Correlation and anticorrelation between stocks
 Taxonomy of a stock portfolio
 Options in idealized markets
 Options in real markets.
(source: Nielsen Book Data)
 Mantegna, Rosario N. (Rosario Nunzio), 1960
 Cambridge, UK ; New York : Cambridge University Press, 2000.
 Description
 Book — 1 online resource (ix, 148 pages) : illustrations Digital: data file.
 Summary

 Introduction
 Efficient market hypothesis
 Random walk
 Levy stochastic processes and limit theorems
 Scales in financial data
 Stationarity and time correlation
 Time correlation in financial time series
 Stochastic models of price dynamics
 Scaling and its breakdown
 ARCH and GARCH processes
 Financial markets and turbulence
 Correlation and anticorrelation between stocks
 Taxonomy of a stock portfolio
 Options in idealized markets
 Options in real markets.
(source: Nielsen Book Data)
41. An introduction to econophysics [electronic resource] : correlations and complexity in finance [2000]
 Mantegna, Rosario N. (Rosario Nunzio), 1960
 Cambridge, UK ; New York : Cambridge University Press, 2000.
 Description
 Book — ix, 148 p. : ill.
 Summary

 Preface
 1. Introduction
 2. Efficient market hypothesis
 3. Random walk
 4. Levy stochastic processes and limit theorems
 5. Scales in financial data
 6. Stationarity and time correlation
 7. Time correlation in financial time series
 8. Stochastic models of price dynamics
 9. Scaling and its breakdown
 10. ARCH and GARCH processes
 11. Financial markets and turbulence
 12. Correlation and anticorrelation between stocks
 13. Taxonomy of a stock portfolio
 14. Options in idealized markets
 15. Options in real markets
 Appendix A: notation guide
 Appendix B: martingales
 References
 Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
42. An introduction to quantitative finance [2014]
 Blyth, Stephen, author.
 Oxford : Oxford University Press, 2014.
 Description
 Book — xvi, 175 pages : illustrations (black and white) ; 24 cm
 Summary

 I INTRODUCTION AND PRELIMINARIES
 II FORWARDS, SWAPS AND OPTIONS
 III REPLICATION, RISKNEUTRALITY AND THE FUNDAMENTAL THEOREM
 IV INTEREST RATE OPTIONS
 V THROUGH CONTINUOUS TIME.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
HG176.5 .B59 2014  Unknown 
43. Introduction to Quantitative Finance [2013]
 Blyth, Stephen.
 Oxford University Press, USA, 2013.
 Description
 Book — 1 online resource
 Summary

 Cover; Contents; PART I: PRELIMINARIES; 1 Preliminaries; 1.1 Interest rates and compounding; 1.2 Zero coupon bonds and discounting; 1.3 Annuities; 1.4 Daycount conventions; 1.5 An abridged guide to stocks, bonds and FX; 1.6 Exercises; PART II: FORWARDS, SWAPS AND OPTIONS; 2 Forward contracts and forward prices; 2.1 Derivative contracts; 2.2 Forward contracts; 2.3 Forward on asset paying no income; 2.4 Forward on asset paying known income; 2.5 Review of assumptions; 2.6 Value of forward contract; 2.7 Forward on stock paying dividends and on currency; 2.8 Physical versus cash settlement.
 2.9 Summary2.10 Exercises; 3 Forward rates and libor; 3.1 Forward zero coupon bond prices; 3.2 Forward interest rates; 3.3 Libor; 3.4 Forward rate agreements and forward libor; 3.5 Valuing floating and flxed cashflows; 3.6 Exercises; 4 Interest rate swaps; 4.1 Swap definition; 4.2 Forward swap rate and swap value; 4.3 Spotstarting swaps; 4.4 Swaps as difference between bonds; 4.5 Exercises; 5 Futures contracts; 5.1 Futures definition; 5.2 Futures versus forward prices; 5.3 Futures on libor rates; 5.4 Exercises; 6 Noarbitrage principle; 6.1 Assumption of noarbitrage.
 6.2 Monotonicity theorem6.3 Arbitrage violations; 6.4 Exercises; 7 Options; 7.1 Option definitions; 7.2 Putcall parity; 7.3 Bounds on call prices; 7.4 Call and put spreads; 7.5 Butterflies and convexity of option prices; 7.6 Digital options; 7.7 Options on forward contracts; 7.8 Exercises; PART III: REPLICATION, RISKNEUTRALITY AND THE FUNDAMENTAL THEOREM; 8 Replication and riskneutrality on the binomial tree; 8.1 Hedging and replication in the twostate world; 8.2 Riskneutral probabilities; 8.3 Multiple time steps; 8.4 General noarbitrage condition; 8.5 Exercises.
 9 Martingales, numeraires and the fundamental theorem9.1 Definition of martingales; 9.2 Numeraires and fundamental theorem; 9.3 Change of numeraire on binomial tree; 9.4 Fundamental theorem: a pragmatic example; 9.5 Fundamental theorem: summary; 9.6 Exercises; 10 Continuoustime limit and BlackScholes formula; 10.1 Lognormal limit; 10.2 Riskneutral limit; 10.3 BlackScholes formula; 10.4 Properties of BlackScholes formula; 10.5 Delta and vega; 10.6 Incorporating random interest rates; 10.7 Exercises; 11 Option price and probability duality.
 11.1 Digitals and cumulative distribution function11.2 Butterflies and riskneutral density; 11.3 Calls as spanning set; 11.4 Implied volatility; 11.5 Exercises; PART IV: INTEREST RATE OPTIONS; 12 Caps, floors and swaptions; 12.1 Caplets; 12.2 Caplet valuation and forward numeraire; 12.3 Swaptions and swap numeraire; 12.4 Summary; 12.5 Exercises; 13 Cancellable swaps and Bermudan swaptions; 13.1 European cancellable swaps; 13.2 Callable bonds; 13.3 Bermudan swaptions; 13.4 Bermudan swaption exercise criteria; 13.5 Bermudan cancellable swaps and callable bonds; 13.6 Exercises.
 Severini, Thomas A. (Thomas Alan), 1959, author.
 Boca Raton, FL : CRC Press, [2017]
 Description
 Book — 1 online resource
 Summary

 Returns.
 Random Walk Hypothesis.
 Portfolios.
 Efficient Portfolio Theory.
 Estimation.
 Capital Asset Pricing Model.
 The Market Model.
 The SingleIndex Model.
 Factor Models.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Cham : Springer, 2015.
 Description
 Book — 1 online resource Digital: text file.PDF.
 Summary

 Hagan, Lesniewski, Woodward: Probability Distribution in the SABR Model of Stochastic Volatility. Paulot: Asymptotic Implied Volatility at the Second Order with Application to the SABR Model. HenryLabordere: Unifying the BGM and SABR Models: A Short Ride in Hyperbolic Geometry. Ben Arous, Laurence: Second Order Expansion for Implied Volatility in Two Factor Localstochastic Volatility. Osajima: General Asymptotics of Wiener Functionals and Application to Implied Volatilities. Bayer, Laurence: Smalltime asymptotics for the atthemoney implied volatility in a multidimensional local volatility model. KellerRessel, Teichmann: A Remark on Gatheral's 'Mostlikely Path Approximation' of Implied Volatility. Gatheral, Wang: Implied volatility from local volatility: a path integral approach. Gerhold, Friz: Don't Stay Local  Extrapolation Analytics for Dupire's Local Volatility. Gulisashvili, Teichmann: Laplace Principle Expansions and Short Time Asymptotics for Affine Processes. Lorig, Pascucci, Pagliarani: Asymptotics for ddimensional Levytype Processes. Takahashi: An Asymptotic Expansion Approach in Finance. Baudoin, Ouyang: On small time asymptotics for rough differential equations driven by fractional Brownian motions. Lucic: On singularities in the Heston model. Bayer, Friz, Laurence: On the probability density function of baskets. Conforti, De Marco, Deuschel: On smallnoise equations with degenerate limiting system arising from volatility models. Pham: Long time asymptotic problems for optimal investment. Spiliopoulos: Systemic Risk and Default Clustering for Large Financial Systems. Jacod, Rosenbaum: Asymptotic Properties of a Volatility Estimator.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Jansen, Stefan.
 [S.l.] : Packt Publishing, 2020.
 Description
 Book — 1 online resource
 Summary

 Table of Contents Machine Learning for Trading  From Idea to Execution Market and Fundamental Data  Sources and Techniques Alternative Data for Finance  Categories and Use Cases Financial Feature Engineering  How to Research Alpha Factors Portfolio Optimization and Performance Evaluation The Machine Learning Process Linear Models  From Risk Factors to Return Forecasts The ML4T Workflow  From Model to Strategy Backtesting (N.B. Please use the Look Inside option to see further chapters).
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Jansen, Stefan, author.
 Second edition.  Birmingham, UK : Packt Publishing, 2020.
 Description
 Book — 1 online resource (1 volume) : illustrations
 Summary

 Table of Contents Machine Learning for Trading  From Idea to Execution Market and Fundamental Data  Sources and Techniques Alternative Data for Finance  Categories and Use Cases Financial Feature Engineering  How to Research Alpha Factors Portfolio Optimization and Performance Evaluation The Machine Learning Process Linear Models  From Risk Factors to Return Forecasts The ML4T Workflow  From Model to Strategy Backtesting (N.B. Please use the Look Inside option to see further chapters).
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 MAF 2010 (2010 : Salerno, Italy)
 Milan ; New York : Springer, ©2012.
 Description
 Book — 1 online resource (xii, 408 pages) Digital: text file.PDF.
 Summary

 On the estimation in continuous limit of GARCH processes / Giuseppina Albano, Francesco Giordano and Cira Perna
 Variable selection in forecasting models for default risk / Alessandra Amendola, Marialuisa Restaino and Luca Sensini
 Capital structure with firm's net cash payouts / Flavia Barsotti, Maria Elvira Mancino and Monique Pontier
 Convex ordering of Esscher and minimal entropy martingale measures for discrete time models / Fabio Bellini and Carlo Sgarra
 On hyperbolic iterated distortions for the adjustment of survival functions / Alexis Bienvenüe and Didier Rullière
 Beyond Basel2: Modeling loss given default through survival analysis / Stefano Bonini and Giuliana Caivano
 Initial premium, aggregate claims and distortion risk measures in XL reinsurance with reinstatements / Antonella Campana and Paola Ferretti
 Population dynamics in a spatial Solow model with a convexconcave production function / Vincenzo Capasso, Ralf Engbers and Davide La Torre
 Population dynamics in a patch growth model with Sshaped production functions and migration effects / Vincenzo Capasso, Herb E. Kunze and Davide La Torre
 An ordinal approach to risk measurement / Marta Cardin and Miguel Couceiro
 Piecewise linear dynamic systems for own risk solvency assessment / Rocco Roberto Cerchiara and Fabio Lamantia
 Valuation of the conditional indexation option in asset and liability management of defined benefit pension funds / Rosa Cocozza, Angela Gallo and Giuseppe Xella
 Conditional performance attribution for equity portfolio / Claudio Conversano and Alessio Lizzeri
 Capital requirements for aggregate risks in long term living products: A stochastic approach / Mariarosaria Coppola, Albina Orlando and Massimiliano Politano
 Portfolio selection with an alternative measure of risk: Computational performances of particle swarm optimization and genetic algorithms / Marco Corazza, Giovanni Fasano and Riccardo Gusso
 Interdependence and contagion in international stock markets: A latent Markov model approach / Michele Costa, Luca De Angelis and Leonard J. Paas.
 Valuation of portfolio loss derivatives in an infectious model / Areski Cousin, Diana Dorobantu and Didier Rullière
 Internal risk control by solvency measures / Valeria D'Amato, Emilia Di Lorenzo, Maria Russolillo and Marilena Sibillo
 Measuring mortality heterogeneity in pension annuities / Valeria D'Amato, Gabriella Piscopo and Maria Russolillo
 Is technical analysis able to beat market inefficiency? / Elisa Daniotti
 On the damped geometric telegrapher's process / Antonio Di Crescenzo, Barbara Martinucci and Shelemyahu Zacks
 Risk measures and Pareto style tails / Anna Maria Fiori, Emanuela Rosazza Gianin and Anna Spasova
 Credit risk and incomplete information: A filtering framework for pricing and risk management / Claudio Fontana
 Claims reserving uncertainty in the development of internal risk models / Salvatore Forte, Matteo Ialenti and Marco Pirra
 Some inequalities between measures of multivariate kurtosis, with application to financial returns / Cinzia Franceschini and Nicola Loperfido
 The generalized trapezoidal model in financial data analysis / Manuel Franco, Johan René van Dorp and JuanaMaría Vivo
 Nonparametric estimation of volatility functions: Some experimental evidences / Francesco Giordano, Michele La Rocca and Cira Perna
 Investigating and modelling the perception of economic security in the Survey of Household Income and Wealth / Maria Iannario and Domenico Piccolo
 On ruin probabilities in risk models with interest rate / Nino Kordzakhia, Alexander Novikov and Gurami Tsitsiashvili
 On longevity risk securitization and solvency capital requirements in life annuities / Susanna Levantesi, Massimiliano Menzietti and Tiziana Torri.
 Modelling the share prices as a hidden random walk on the lamplighter group / Xiaojuan Ma and Sergey Utev
 Multivariate jump arrivals: The variance gamma case / Roberto Marfè
 Modelling the skewed exponential power distribution in finance / J. Miguel Marín and Genaro Sucarrat
 Composite indicators: A sectorial perspective / Marco Marozzi
 Dynamic model of pension savings management with stochastic interest rates and stock returns / Igor Melicherčík and Daniel Ševčovič
 Financial and demographic risks impact on a payasyougo pension fund / Roberta Melis and Alessandro Trudda
 Extracting implied dividends from options prices: Some applications to the Italian derivatives market / Martina Nardon and Paolo Pianca
 Generalization of some linear time series property to nonlinear domain / Marcella Niglio and Cosimo Damiano Vitale
 Evaluating the behavior of a function in kernel based regression / Maria Lucia Parrella
 Optimal trading rules at hourly frequency in the foreign exchange markets / Danilo Pelusi and Massimo Tivegna
 The influence of correlation and loading on MV efficient retentions in variable quota share proportional reinsurance / Flavio Pressacco and Laura Ziani
 Good and bad banks / Luca Regis
 Tail diversification strategy. An application to MSCI World Sector Indices / Giorgia Rivieccio
 Marginalization and aggregation of exponential smoothing models in forecasting portfolio volatility / Giacomo Sbrana and Andrea Silvestrini
 Generalization of stratified variance reduction methods for Monte Carlo exchange options pricing / Giovanni Villani
 Price discovery in a dynamic structural model / Lei Wu and Hans van der Weide.
 International Conference MAF (2008 : Venice, Italy)
 Dordrecht ; New York : Springer Verlag, ©2010.
 Description
 Book — 1 online resource (xv, 314 pages) : illustrations
 Summary

 Impact of interest rate risk on the Spanish banking sector. Tracking error with minimum guarantee constraints. Energy markets: crucial relationship between prices. Tempered stable distributions and processes in finance: numerical analysis. Transformation kernel estimation of insurance claim cost distributions. What do distortion risk measures tell us on excess of loss reinsurance with reinstatements?. Some classes of multivariate risk measures. Assessing risk perception by means of ordinal models. A financial analysis of surplus dynamics for deferred life schemes. Checking financial markets via Benford's law: the S&P 500 case. Empirical likelihood based nonparametric testing for CAPM. LeeCarter error matrix simulation: heteroschedasticity impact on actuarial valuations. Estimating the volatility term structure. Exact and approximated option pricing in a stochastic volatility jumpdiffusion model. A skewed GARCHtype model for multivariate financial time series. Financial time series and neural networks in a minority game context. Robust estimation of style analysis coefficients. Managing demographic risk in enhanced pensions. Clustering mutual funds by return and risk levels. Multivariate Variance Gamma and Gaussian Dependence: a study with copulas. A simple dimension reduction procedure for corporate finance composite indicators. The relation between implied and realised volatility in the DAX index options market. Binomial algorithms for the evaluation of options on stocks with fixed per share dividends. Nonparametric prediction in time series analysis: some empirical results. On efficient optimisation of the CVaR and related LP computable risk measures for portfolio selection. A pattern recognition algorithm for optimal profits in currency trading. Nonlinear cointegration in financial time series. Optimal dynamic asset allocation in a nonGaussian world. Fair costs of guaranteed minimum death benefit contracts. Solvency evaluation of the guaranty fund at a large financial cooperative. A Monte Carlo approach to value exchange options using a single stochastic factor.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 MAF (Conference) (7th : 2016 : Paris, France) author.
 Cham, Switzerland : Springer, 2017.
 Description
 Book — 1 online resource Digital: PDF.text file.
 Summary

 1 The effects of credit rating announcements on bond liquidity: An event study. 2 The effect of credit rating events on the emerging CDS market. 3 A generalised linear model approach to predict the result of research evaluation. 4 Projecting dynamic life tables using Data Cloning. 5 Markov switching GARCH models: Filtering, approximations and duality. 6 A network approach to risk theory and portfolio selection. 7 A PSObased approach for improving simple trading systems. 8 Provisions for outstanding claims with distancebased generalized linear models. 9 Profitability vs. attractiveness within a performance analysis of a life annuity business. 10 Uncertainty in historical ValueatRisk: an alternative quantilebased risk measure. 11 Modeling volatility risk premium. 12 Covered call writing and framing: A cumulative prospect theory approach. 13 Optimal portfolio selection for an investor with asymmetric attitude to gains and losses.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 MAF (Conference) (2018 : Madrid, Spain)
 Cham : Springer, 2018.
 Description
 Book — 1 online resource Digital: text file.PDF.
 Summary

 Intro; Preface; Contents; About the Editors; The Effect of Rating Contingent Guidelines and Regulation Around Credit Rating News; 1 Introduction; 2 RatingBased Investment Guidelines; 3 Data and Analysis Implementation; 4 Results; 5 Concluding Remarks; References; Practical Problems with Tests of Cointegration Rank with Strong Persistence and HeavyTailed Errors; 1 Introduction; 2 Power of Tests in the Heteroskedastic VAR Model with HeavyTailed Errors; 3 Empirical Results; 4 Conclusions; References; Inference in a NonHomogeneous Vasicek Type Model; 1 Introduction and Background; 2 The Model
 3 Fitting the Model4 A Simulation Study; References; Small Sample Analysis in Diffusion Processes: A Simulation Study; 1 Introduction; 2 ML Estimation and Bootstrap Correction; 3 Simulation Experiment and Results; References; Using Deepest Dependency Paths to Enhance Life ExpectancyEstimation; 1 Introduction; 2 Methodology; 3 Results; References; The Optimal Investment and Consumption for Financial Markets Generated by the Spread of Risky Assets for the Power Utility; 1 Market Model; 2 Stochastic Programming Method; 3 Main Results; References; Combining Multivariate Volatility Models
 1 Introduction2 MCS Combination Strategy; 3 Empirical Analysis; References; Automatic Detection and Imputation of Outliers in Electricity Price Time Series; 1 Introduction; 2 Time Series Outlier Detection and Imputation; 3 Results and Discussion; References; Bayesian Factorization Machines for Risk Management and Robust Decision Making; 1 Introduction; 2 Prediction; 3 Multiobjective Optimization; References; Improving LeeCarter Forecasting: Methodology and Some Results; 1 Introduction and Literature; 2 Mathematical Framework and Empirical Methodology
 3 Graphical Assessment of the Predictive Accuracy of the ``mLC'' Model4 Concluding Remarks; References; The Bank Tailored Integrated Rating; 1 Motivation and Methodology; 2 Stylized Mathematical Approach; 3 Summaries and Future Developments; Appendix; References; A Single Factor Model for Constructing Dynamic Life Tables; 1 Single Factor Model; 1.1 Adjusting a Sensitivity Function to bx, x*; 1.2 Forecasting Mortality Rates; 2 LeeCarter (1992) Model; 3 Comparison Between the Single Factor Model and the LeeCarter Model; References; Variable Annuities with StateDependent Fees; 1 Introduction
 2 The Structure of the Contract3 Valuation Framework; 3.1 The Static Approach; 3.2 The Mixed Approach; 4 Numerical Implementation; References; Dynamic Policyholder Behavior and Surrender Option Evaluation for Life Insurance; 1 Introduction; 2 A Model for the Lapse Rate Estimation According to Policyholder Behavior; 2.1 Step 1; 2.2 Step 2; 3 Some Numerical Results; References; Classification Ratemaking via Quantile Regression and a Comparison with Generalized Linear Models; 1 Introduction; 2 A Quantile Premium Principle Based on a TwoPart Model
(source: Nielsen Book Data)
 MAF (Conference) (2022 : Solerno, Italy)
 Cham, Switzerland : Springer, 2022.
 Description
 Book — 1 online resource (1 volume) : illustrations (black and white, and color).
 Summary

 The book chapters will be the scientific contributes submitted by the Authors and accepted for publication after peer review. The book will contain about 70 chapters.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 1st ed.  New York : Springer, ©2008.
 Description
 Book — 1 online resource (xiv, 208 pages : illustrations
 Summary

 Least Squares Predictors for Threshold Models: Properties and Forecast Evaluation
 Estimating Portfolio Conditional Returns Distribution Through Style Analysis Models
 A Full Monte Carlo Approach to the Valuation of the Surrender Option Embedded in Life Insurance Contracts
 Spatial Aggregation in Scenario Tree Reduction
 Scaling Laws in Stock Markets. An Analysis of Prices and Volumes
 Bounds for Concave Distortion Risk Measures for Sums of Risks
 Characterization of Convex Premium Principles
 FFT, Extreme Value Theory and Simulation to Model NonLife Insurance Claims Dependences
 Dynamics of Financial Time Series in an Inhomogeneous Aggregation Framework
 A Liability Adequacy Test for Mathematical Provision
 Iterated Function Systems, Iterated Multifunction Systems, and Applications
 Remarks on Insured Loan Valuations
 Exploring the Copula Approach for the Analysis of Financial Durations
 Analysis of Economic Fluctuations: A Contribution from Chaos Theory
 Generalized Influence Functions and Robustness Analysis
 Neural Networks for Bandwidth Selection in NonParametric Derivative Estimation
 Comparing Mortality Trends via LeeCarter Method in the Framework of Multidimensional Data Analysis
 Decision Making in Financial Markets Through Multivariate Ordering Procedure
 A Biometric Risks Analysis in Long Term Care Insurance
 Clustering Financial Data for Mutual Fund Management
 Modeling UltraHighFrequency Data: The S & P 500 Index Future
 Simulating a Generalized Gaussian Noise with Shape Parameter 1/2
 Further Remarks on Risk Profiles for Life Insurance Participating Policies
 Classifying Italian Pension Funds via GARCH Distance
 The Analysis of Extreme Events
 Some Forecasting Approaches.
 1st ed.  New York : Springer, c2008.
 Description
 Book — xiv, 208 p. : ill.
 1st ed.  New York : Springer, c2008.
 Description
 Book — 1 online resource (xiv, 208 p. : ill.)
56. The mathematics of derivatives securities with applications in MATLAB [electronic resource] [2012]
 Cerrato, Mario.
 Hoboken : John Wiley & Sons Inc., 2012.
 Description
 Book — xii, 236 pages : illustrations ; 24 cm
 Summary

 Preface xi 1 An Introduction to Probability Theory 1 1.1 The Notion of a Set and a Sample Space 1 1.2 Sigma Algebras or Field 2 1.3 Probability Measure and Probability Space 2 1.4 Measurable Mapping 3 1.5 Cumulative Distribution Functions 4 1.6 Convergence in Distribution 5 1.7 Random Variables 5 1.8 Discrete Random Variables 6 1.9 Example of Discrete Random Variables: The Binomial Distribution 6 1.10 Hypergeometric Distribution 7 1.11 Poisson Distribution 8 1.12 Continuous Random Variables 9 1.13 Uniform Distribution 9 1.14 The Normal Distribution 9 1.15 Change of Variable 11 1.16 Exponential Distribution 12 1.17 Gamma Distribution 12 1.18 Measurable Function 13 1.19 Cumulative Distribution Function and Probability Density Function 13 1.20 Joint, Conditional and Marginal Distributions 17 1.21 Expected Values of Random Variables and Moments of a Distribution 19 2 Stochastic Processes 25 2.1 Stochastic Processes 25 2.2 Martingales Processes 26 2.3 Brownian Motions 29 2.4 Brownian Motion and the Reflection Principle 32 2.5 Geometric Brownian Motions 35 3 Ito Calculus and Ito Integral 37 3.1 Total Variation and Quadratic Variation of Differentiable Functions 37 3.2 Quadratic Variation of Brownian Motions 39 3.3 The Construction of the Ito Integral 40 3.4 Properties of the Ito Integral 41 3.5 The General Ito Stochastic Integral 42 3.6 Properties of the General Ito Integral 43 3.7 Construction of the Ito Integral with Respect to SemiMartingale Integrators 44 3.8 Quadratic Variation of a General Bounded Martingale 46 4 The Black and Scholes Economy 55 4.1 Introduction 55 4.2 Trading Strategies and Martingale Processes 55 4.3 The Fundamental Theorem of Asset Pricing 56 4.4 Martingale Measures 58 4.5 Girsanov Theorem 59 4.6 RiskNeutral Measures 62 5 The Black and Scholes Model 67 5.1 Introduction 67 5.2 The Black and Scholes Model 67 5.3 The Black and Scholes Formula 68 5.4 Black and Scholes in Practice 70 5.5 The FeynmanKac Formula 71 6 Monte Carlo Methods 79 6.1 Introduction 79 6.2 The Data Generating Process (DGP) and the Model 79 6.3 Pricing European Options 80 6.4 Variance Reduction Techniques 81 7 Monte Carlo Methods and American Options 91 7.1 Introduction 91 7.2 Pricing American Options 91 7.3 Dynamic Programming Approach and American Option Pricing 92 7.4 The Longstaff and Schwartz Least Squares Method 93 7.5 The Glasserman and Yu Regression Later Method 95 7.6 Upper and Lower Bounds and American Options 96 8 American Option Pricing: The Dual Approach 101 8.1 Introduction 101 8.2 A General Framework for American Option Pricing 101 8.3 A Simple Approach to Designing Optimal Martingales 104 8.4 Optimal Martingales and American Option Pricing 104 8.5 A Simple Algorithm for American Option Pricing 105 8.6 Empirical Results 106 8.7 Computing Upper Bounds 107 8.8 Empirical Results 109 9 Estimation of Greeks using Monte Carlo Methods 113 9.1 Finite Difference Approximations 113 9.2 Pathwise Derivatives Estimation 114 9.3 Likelihood Ratio Method 116 9.4 Discussion 118 10 Exotic Options 121 10.1 Introduction 121 10.2 Digital Options 121 10.3 Asian Options 122 10.4 Forward Start Options 123 10.5 Barrier Options 123 10.5.1 Hedging Barrier Options 125 11 Pricing and Hedging Exotic Options 129 11.1 Introduction 129 11.2 Monte Carlo Simulations and Asian Options 129 11.3 Simulation of Greeks for Exotic Options 130 11.4 Monte Carlo Simulations and Forward Start Options 131 11.5 Simulation of the Greeks for Exotic Options 132 11.6 Monte Carlo Simulations and Barrier Options 132 12 Stochastic Volatility Models 137 12.1 Introduction 137 12.2 The Model 137 12.3 Square Root Diffusion Process 138 12.4 The Heston Stochastic Volatility Model (HSVM) 139 12.5 Processes with Jumps 143 12.6 Application of the Euler Method to Solve SDEs 143 12.7 Exact Simulation Under SV 144 12.8 Exact Simulation of Greeks Under SV 146 13 Implied Volatility Models 151 13.1 Introduction 151 13.2 Modelling Implied Volatility 152 13.3 Examples 153 14 Local Volatility Models 157 14.1 An Overview 157 14.2 The Model 159 14.3 Numerical Methods 161 15 An Introduction to Interest Rate Modelling 167 15.1 A General Framework 167 15.2 Affine Models (AMs) 169 15.3 The Vasicek Model 171 15.4 The Cox, Ingersoll and Ross (CIR) Model 173 15.5 The Hull and White (HW) Model 174 15.6 The Black Formula and Bond Options 175 16 Interest Rate Modelling 177 16.1 Some Preliminary Definitions 177 16.2 Interest Rate Caplets and Floorlets 178 16.3 Forward Rates and Numeraire 180 16.4 Libor Futures Contracts 181 16.5 Martingale Measure 183 17 Binomial and Finite Difference Methods 185 17.1 The Binomial Model 185 17.2 Expected Value and Variance in the Black and Scholes and Binomial Models 186 17.3 The CoxRossRubinstein Model 187 17.4 Finite Difference Methods 188
 Appendix 1 An Introduction to MATLAB 191 A1.1 What is MATLAB? 191 A1.2 Starting MATLAB 191 A1.3 Main Operations in MATLAB 192 A1.4 Vectors and Matrices 192 A1.5 Basic Matrix Operations 194 A1.6 Linear Algebra 195 A1.7 Basics of Polynomial Evaluations 196 A1.8 Graphing in MATLAB 196 A1.9 Several Graphs on One Plot 197 A1.10 Programming in MATLAB: Basic Loops 199 A1.11 MFile Functions 200 A1.12 MATLAB Applications in Risk Management 200 A1.13 MATLAB Programming: Application in Financial Economics 202
 Appendix 2 Mortgage Backed Securities 205 A2.1 Introduction 205 A2.2 The Mortgage Industry 206 A2.3 The Mortgage Backed Security (MBS) Model 207 A2.4 The Term Structure Model 208 A2.5 Preliminary Numerical Example 210 A2.6 Dynamic Option Adjusted Spread 210 A2.7 Numerical Example 212 A2.8 Practical Numerical Examples 213 A2.9 Empirical Results 214 A2.10 The PrePayment Model 215
 Appendix 3 Value at Risk 217 A3.1 Introduction 217 A3.2 Value at Risk (VaR) 217 A3.3 The Main Parameters of a VaR 218 A3.4 VaR Methodology 219 A3.5 Empirical Applications 222 A3.6 Fat Tails and VaR 224 Bibliography 227 References 229 Index 233.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
The book is divided into two parts  the first part introduces probability theory, stochastic calculus and stochastic processes before moving on to the second part which instructs readers on how to apply the content learnt in part one to solve complex financial problems such as pricing and hedging exotic options, pricing American derivatives, pricing and hedging under stochastic volatility, and interest rate modelling. Each chapter provides a thorough discussion of the topics covered with practical examples in MATLAB so that readers will build up to an analysis of modern cutting edge research in finance, combining probabilistic models and cutting edge finance illustrated by MATLAB applications.Most books currently available on the subject require the reader to have some knowledge of the subject area and rarely consider computational applications such as MATLAB. This book stands apart from the rest as it covers complex analytical issues and complex financial instruments in a way that is accessible to those without a background in probability theory and finance, as well as providing detailed mathematical explanations with MATLAB code for a variety of topics and real world case examples.
(source: Nielsen Book Data)
57. The mathematics of financial models : solving realworld problems with quantitative methods [2014]
 Ravindran, Kannoo, author.
 Hoboken, New Jersey : John Wiley & Sons, [2014]
 Description
 Book — 1 online resource (1 volume) : illustrations
 Summary

 Preface ix Acknowledgments xi CHAPTER 1 Setting the Stage 1 Why Is This Book Different? 2 Road Map of the Book 3 References 5 CHAPTER 2 Building Zero Curves 7 Market Instruments 8 Linear Interpolation 16 Cubic Splining 25 Appendix: Finding Swap Rates Using a Floating Coupon Bond Approach 41 References 43 CHAPTER 3 Valuing Vanilla Options 45 BlackScholes Formulae 47 Adaptations of the BlackScholes Formulae 53 Limitations of the BlackScholes Formulae 70 Application in Currency Risk Management 74 Appendix 78 References 80 CHAPTER 4 Simulations 81 Uniform Number Generation 82 NonUniform Number Generation 86 Applications of Simulations 93 Variance Reduction Techniques 100 References 104 CHAPTER 5 Valuing Exotic Options 107 Valuing PathIndependent, EuropeanStyle Options on a Single Variable 108 Valuing PathDependent, EuropeanStyle Options on a Single Variable 114 Valuing PathIndependent, EuropeanStyle Options on Two Variables 135 Valuing PathDependent, EuropeanStyle Options on Multiple Variables 152 References 157 CHAPTER 6 Estimating Model Parameters 159 Calibration of Parameters in the BlackScholes Model 161 Using Implied BlackScholes Volatility Surface and Zero Rate Term Structure to Value Options 169 Using Volatility Surface 178 Calibration of Interest Rate Option Model Parameters 190 Statistical Estimation 196 References 203 CHAPTER 7 The Effectiveness of Hedging Strategies 205 Delta Hedging 206 Assumptions Underlying Delta Hedging 216 Beyond Delta Hedging 223 Testing Hedging Strategies 230 Analysis Associated with the Hedging of a EuropeanStyle Vanilla Put Option 235 References 244 CHAPTER 8 Valuing Variable Annuity Guarantees 245 Basic GMDB 246 Death Benefit Riders 261 Other Details Associated with GMDB Products 269 Improving Modeling Assumptions 273 Living Benefit Riders 276 References 279 CHAPTER 9 Real Options 281
 Surrendering a GMAB Rider 282 Adding Servers in a Queue 300 References 314 CHAPTER 10 Parting Thoughts 315 About the Author 317 About the Website 319 Index 321.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
58. The mathematics of financial models : solving realworld problems with quantitative methods [2014]
 Ravindran, Kannoo, author.
 Hoboken, New Jersey : John Wiley & Sons, Inc., [2014]
 Description
 Book — 1 online resource (xi, 331 pages).
 Summary

 Preface ix Acknowledgments xi CHAPTER 1 Setting the Stage 1 Why Is This Book Different? 2 Road Map of the Book 3 References 5 CHAPTER 2 Building Zero Curves 7 Market Instruments 8 Linear Interpolation 16 Cubic Splining 25 Appendix: Finding Swap Rates Using a Floating Coupon Bond Approach 41 References 43 CHAPTER 3 Valuing Vanilla Options 45 BlackScholes Formulae 47 Adaptations of the BlackScholes Formulae 53 Limitations of the BlackScholes Formulae 70 Application in Currency Risk Management 74 Appendix 78 References 80 CHAPTER 4 Simulations 81 Uniform Number Generation 82 NonUniform Number Generation 86 Applications of Simulations 93 Variance Reduction Techniques 100 References 104 CHAPTER 5 Valuing Exotic Options 107 Valuing PathIndependent, EuropeanStyle Options on a Single Variable 108 Valuing PathDependent, EuropeanStyle Options on a Single Variable 114 Valuing PathIndependent, EuropeanStyle Options on Two Variables 135 Valuing PathDependent, EuropeanStyle Options on Multiple Variables 152 References 157 CHAPTER 6 Estimating Model Parameters 159 Calibration of Parameters in the BlackScholes Model 161 Using Implied BlackScholes Volatility Surface and Zero Rate Term Structure to Value Options 169 Using Volatility Surface 178 Calibration of Interest Rate Option Model Parameters 190 Statistical Estimation 196 References 203 CHAPTER 7 The Effectiveness of Hedging Strategies 205 Delta Hedging 206 Assumptions Underlying Delta Hedging 216 Beyond Delta Hedging 223 Testing Hedging Strategies 230 Analysis Associated with the Hedging of a EuropeanStyle Vanilla Put Option 235 References 244 CHAPTER 8 Valuing Variable Annuity Guarantees 245 Basic GMDB 246 Death Benefit Riders 261 Other Details Associated with GMDB Products 269 Improving Modeling Assumptions 273 Living Benefit Riders 276 References 279 CHAPTER 9 Real Options 281
 Surrendering a GMAB Rider 282 Adding Servers in a Queue 300 References 314 CHAPTER 10 Parting Thoughts 315 About the Author 317 About the Website 319 Index 321.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Duffie, Darrell.
 Oxford : Oxford University Press, 2011.
 Description
 Book — 1 online resource (viii, 109 p.) : ill.
 Summary

 1. Objectives and Scope
 2. Survival Modeling
 3. How to Estimate Default Intensity Processes
 4. The Default Intensities of Public Corporations
 5. Default Correlation
 6. FrailtyInduced Correlation
 7. Empirical Evidence of Frailty
 A. TimeSeries Parameter Estimates
 B. Residual Gaussian Copula Correlation
 C. Additional Tests for MisSpecified Intensities
 D. Applying the Gibbs Sampler with Frailty
 E. Testing for Frailty
 F. Unobserved Heterogeneity
 G. NonLinearity Check
 H. Bayesian Frailty Dynamics
 I. RiskNeutral Default Probabilities.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Paris : Organisation for Economic Cooperation and Development, c1981.
 Description
 Book — 353 p. ; 24 cm.
 Online
SAL3 (offcampus storage)
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HJ9105 .M4  Available 
 Washington, D.C. : International Monetary Fund, 2017.
 Description
 Book — 1 online resource (450 pages)
 Summary

This edition of Monetary and Financial Statistics Manual and Compilation Guide (Manual) updates and merges into one volume methodological and practical aspects of the compilation process of monetary statistics. The Manual is aimed at compilers and users of monetary data, offering guidance for the collection and analytical presentation of monetary statistics. The Manual includes standardized report forms, providing countries with a tool for compiling and reporting harmonized data for the central bank, other depository corporations, and other financial corporations.
 Bellingham, Wash. : SPIE, c2005.
 Description
 Book — xxxviii, 348 p. : ill. ; 28 cm.
 [Bellingham, Wash. : SPIE, 2007]
 Description
 Book
64. Nonparametric finance [2018]
 Klemelä, Jussi, 1965 author.
 Hoboken, NJ : John Wiley & Sons, Inc., [2018]
 Description
 Book — 1 online resource.
 Summary

 Cover; Title Page; Copyright; Contents; Preface;
 Chapter 1 Introduction; 1.1 Statistical Finance; 1.2 Risk Management; 1.3 Portfolio Management; 1.4 Pricing of Securities; Part I Statistical Finance;
 Chapter 2 Financial Instruments; 2.1 Stocks; 2.1.1 Stock Indexes; 2.1.1.1 Definition of a Stock Index; 2.1.1.2 Uses of Stock Indexes; 2.1.1.3 Examples of Stock Indexes; 2.1.2 Stock Prices and Returns; 2.1.2.1 Initial Price Data; 2.1.2.2 Sampling of Prices; 2.1.2.3 Stock Returns; 2.2 Fixed Income Instruments; 2.2.1 Bonds; 2.2.2 Interest Rates; 2.2.2.1 Definitions of Interest Rates.
 2.2.2.2 The Risk Free Rate2.2.3 Bond Prices and Returns; 2.3 Derivatives; 2.3.1 Forwards and Futures; 2.3.1.1 Forwards; 2.3.1.2 Futures; 2.3.2 Options; 2.3.2.1 Calls and Puts; 2.3.2.2 Applications of Options; 2.3.2.3 Exotic Options; 2.4 Data Sets; 2.4.1 Daily S & P 500 Data; 2.4.2 Daily S & P 500 and Nasdaqâ#x80; #x90; 100 Data; 2.4.3 Monthly S & P 500, Bond, and Bill Data; 2.4.4 Daily US Treasury 10 Year Bond Data; 2.4.5 Daily S & P 500 Components Data;
 Chapter 3 Univariate Data Analysis; 3.1 Univariate Statistics; 3.1.1 The Center of a Distribution; 3.1.1.1 The Mean and the Conditional Mean.
 3.1.1.2 The Median and the Conditional Median3.1.1.3 The Mode and the Conditional Mode; 3.1.2 The Variance and Moments; 3.1.2.1 The Variance and the Conditional Variance; 3.1.2.2 The Upper and Lower Partial Moments; 3.1.2.3 The Upper and Lower Conditional Moments; 3.1.3 The Quantiles and the Expected Shortfalls; 3.1.3.1 The Quantiles and the Conditional Quantiles; 3.1.3.2 The Expected Shortfalls; 3.2 Univariate Graphical Tools; 3.2.1 Empirical Distribution Function Based Tools; 3.2.1.1 The Empirical Distribution Function; 3.2.1.2 The Tail Plots; 3.2.1.3 Regression Plots of Tails.
 3.2.1.4 The Empirical Quantile Function3.2.2 Density Estimation Based Tools; 3.2.2.1 The Histogram; 3.2.2.2 The Kernel Density Estimator; 3.3 Univariate Parametric Models; 3.3.1 The Normal and Logâ#x80; #x90; normal Models; 3.3.1.1 The Normal and Logâ#x80; #x90; normal Distributions; 3.3.1.2 Modeling Stock Prices; 3.3.2 The Student Distributions; 3.3.2.1 Properties of Student Distributions; 3.3.2.2 Estimation of the Parameters of a Student Distribution; 3.4 Tail Modeling; 3.4.1 Modeling and Estimating Excess Distributions; 3.4.1.1 Modeling Excess Distributions; 3.4.1.2 Estimation.
 3.4.2 Parametric Families for Excess Distributions3.4.2.1 The Exponential Distributions; 3.4.2.2 The Pareto Distributions; 3.4.2.3 The Gamma Distributions; 3.4.2.4 The Generalized Pareto Distributions; 3.4.2.5 The Weibull Distributions; 3.4.2.6 A Three Parameter Family; 3.4.3 Fitting the Models to Return Data; 3.4.3.1 S & P 500 Daily Returns: Maximum Likelihood; 3.4.3.2 Tail Index Estimation for S & P 500 Components; 3.5 Asymptotic Distributions; 3.5.1 The Central Limit Theorems; 3.5.1.1 Sums of Independent Random Variables; 3.5.1.2 Sums of Independent and Identically Distributed Random Variables.
(source: Nielsen Book Data)
65. Nonparametric finance [2018]
 Klemelä, Jussi, 1965 author.
 Hoboken, NJ : John Wiley & Sons, Inc., [2018]
 Description
 Book — 1 online resource Digital: data file.
 Summary

 Preface xxiii
 1 Introduction 1 1.1 Statistical Finance 2 1.2 Risk Management 3 1.3 Portfolio Management 5 1.4 Pricing of Securities 6 Part I Statistical Finance 11
 2 Financial Instruments 13 2.1 Stocks 13 2.2 Fixed Income Instruments 19 2.3 Derivatives 23 2.4 Data Sets 27
 3 Univariate Data Analysis 33 3.1 Univariate Statistics 34 3.2 Univariate Graphical Tools 42 3.3 Univariate ParametricModels 55 3.4 Tail Modeling 61 3.5 Asymptotic Distributions 83 3.6 Univariate Stylized Facts 91
 4 Multivariate Data Analysis 95 4.1 Measures of Dependence 95 4.2 Multivariate Graphical Tools 103 4.3 Multivariate ParametricModels 107 4.4 Copulas 111
 5 Time Series Analysis 121 5.1 Stationarity and Autocorrelation 122 5.2 Model Free Estimation 128 5.3 Univariate Time Series Models 135 5.4 Multivariate Time Series Models 157 5.5 Time Series Stylized Facts 160
 6 Prediction 163 6.1 Methods of Prediction 164 6.2 Forecast Evaluation 170 6.3 Predictive Variables 175 6.4 Asset Return Prediction 182 Part II Risk Management 193
 7 Volatility Prediction 195 7.1 Applications of Volatility Prediction 197 7.2 Performance Measures for Volatility Predictors 199 7.3 Conditional Heteroskedasticity Models 200 7.4 Moving Average Methods 205 7.5 State Space Predictors 211
 8 Quantiles and ValueatRisk 219 8.1 Definitions of Quantiles 220 8.2 Applications of Quantiles 223 8.3 Performance Measures for Quantile Estimators 227 8.4 Nonparametric Estimators of Quantiles 233 8.5 Volatility Based Quantile Estimation 240 8.6 Excess Distributions in Quantile Estimation 258 8.7 Extreme ValueTheory in Quantile Estimation 288 8.8 Expected Shortfall 292 Part III Portfolio Management 297
 9 Some Basic Concepts of Portfolio Theory 299 9.1 Portfolios and Their Returns 300 9.2 Comparison of Return andWealth Distributions 312 9.3 Multiperiod Portfolio Selection 326
 10 Performance Measurement 337 10.1 The Sharpe Ratio 338 10.2 Certainty Equivalent 346 10.3 Drawdown 347 10.4 Alpha and Conditional Alpha 348 10.5 Graphical Tools of Performance Measurement 356
 11 Markowitz Portfolios 367 11.1 Variance Penalized Expected Return 369 11.2 Minimizing Variance under a Sufficient Expected Return 372 11.3 Markowitz Bullets 375 11.4 Further Topics in Markowitz Portfolio Selection 381 11.5 Examples of Markowitz Portfolio Selection 383
 12 Dynamic Portfolio Selection 385 12.1 Prediction in Dynamic Portfolio Selection 387 12.2 Backtesting Trading Strategies 393 12.3 One Risky Asset 394 12.4 Two Risky Assets 405 Part IV Pricing of Securities 419
 13 Principles of Asset Pricing 421 13.1 Introduction to Asset Pricing 422 13.2 Fundamental Theorems of Asset Pricing 430 13.3 Evaluation of Pricing and Hedging Methods 456
 14 Pricing by Arbitrage 459 14.1 Futures and the PutCall Parity 460 14.2 Pricing in Binary Models 466 14.3 BlackScholes Pricing 485 14.4 BlackScholes Hedging 505 14.5 BlackScholes Hedging and Volatility Estimation 515
 15 Pricing in IncompleteModels 521 15.1 Quadratic Hedging and Pricing 522 15.2 Utility Maximization 523 15.3 Absolutely Continuous Changes of Measures 530 15.4 GARCH Market Models 534 15.5 Nonparametric Pricing Using Historical Simulation 545 15.6 Estimation of the RiskNeutral Density 551 15.7 Quantile Hedging 555
 16 Quadratic and Local Quadratic Hedging 557 16.1 Quadratic Hedging 558 16.2 Local Quadratic Hedging 583 16.3 Implementations of Local Quadratic Hedging 595
 17 Option Strategies 615 17.1 Option Strategies 616 17.2 Profitability of Option Strategies 625
 18 Interest Rate Derivatives 649 18.1 Basic Concepts of Interest Rate Derivatives 650 18.2 Interest Rate Forwards 659 18.3 Interest Rate Options 666 18.4 Modeling Interest Rate Markets 669 References 673 Index 681.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
66. Numerical methods in finance and economics [electronic resource] : a MATLABbased introduction [2006]
 Brandimarte, Paolo.
 2nd ed.  Hoboken, N.J. : WileyInterscience, c2006.
 Description
 Book — xxiv, 669 p. : ill. ; 25 cm.
 Summary

 Preface to the Second Edition. From the Preface to the First Edition. PART I. BACKGROUND.
 1. Motivation.
 2. Financial Theory. PART II. NUMERICAL METHODS.
 3. Basics of Numerical Analysis.
 4. Numerical Integration: Deterministic and Monte Carlo Methods.
 5. Finite Difference Methods for Partial Differential Equations.
 6. Convex Optimization. PART III. PRICING EQUITY OPTIONS.
 7. Option Pricing by Binomial and Trinomial Lattices.
 8. Option Pricing by Monte Carlo Methods.
 9. Option Pricing by Finite Difference Methods. PART IV. ADVANCED OPTMIZATION MODELS AND METHODS.
 10. Dynamic Programming.
 11. Linear Stochastic Programming Models with Recourse.
 12. NonConvex Optimization. PART V. APPENDICES. Appendix A. Introduction to MATLAB Programming. Appendix B. Refresher on Probability theory and Statistics. Appendix C. Introduction to AMPL. Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
67. OECD financial statistics. Methodological supplement = Statistiques financières de l'OCDE. Supplément méthodologique [1981  1992]
 [Paris] : Organisation for Economic Cooperation and Development, 19811992.
 Description
 Journal/Periodical — v. ; 27 cm.
 Online
Green Library, SAL3 (offcampus storage)
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HG176.5 .O38 1990  Available 
HG176.5 .O38 19871989  Available 
HG176.5 .O38 1985/1986  Available 
HG176.5 .O38 1983/1984  Available 
HG176.5 .O38 1981/1982  Available 
68. OECD financial statistics. Methodological supplement = Statistiques financières de l'OCDE. Supplément méthodologique [1981 ]
 [Paris] : Organisation for Economic Cooperation and Development, 1981
 Description
 Journal/Periodical — v. ; 27 cm.
 Online
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BOUND WITH: OECD financial statistcs. Part 3, Non 
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HG176.5 .O38 1991/1992  Available 
BUS45793 1989  Available 
BUS45793 1988  Available 
BUS45793 19861987  Available 
BUS45793 19841985  Available 
BUS45793 1983  Available 
BUS45793 1982  Available 
BUS45793 1981  Available 
 Taniguchi, Masanobu.
 Boca Raton, FL : Chapman & Hall/CRC, c2008.
 Description
 Book — xii, 366 p. : ill. ; 25 cm.
 Summary

 PREFACE INTRODUCTION ELEMENTS OF PROBABILITY Probability and Probability Distribution Vector Random Variable and Independence Expectation and Conditional Distribution Convergence and Central Limit Theorems STATISTICAL INFERENCE Sufficient Statistics Unbiased Estimators Efficient Estimators Asymptotically Efficient Estimators VARIOUS STATISTICAL METHODS Interval Estimation Most Powerful Test Various Tests Discriminant Analysis STOCHASTIC PROCESSES Elements of Stochastic Processes Spectral Analysis Ergodicity, Mixing, and Martingale Limit Theorems for Stochastic Processes Exercise TIME SERIES ANALYSIS Time Series Model Estimation of Time Series Models Model Selection Problems Nonparametric Estimation Prediction of Time Series Regression for Time Series Long Memory Processes Local Whittle Likelihood Approach Nonstationary Processes Semiparametric Estimation Discriminant Analysis for Time Series INTRODUCTION TO STATISTICAL FINANCIAL ENGINEERING Option Pricing Theory Higher Order Asymptotic Option Valuation for NonGaussian Dependent Returns Estimation of Portfolio ValueatRisk (VaR) Problems TERM STRUCTURE Spot Rates and Discount Bonds Estimation Procedures for Term Structure CREDIT RATING Parametric Clustering for Financial Time Series Nonparametric Clustering for Financial Time Series Credit Rating Based on Financial Time Series APPENDIX REFERENCES INDEX.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
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Stacks  Request (opens in new tab) 
QA276 .T27 2008  Available 
 Nikkei Econophysics Symposium (3rd : 2004 : Tokyo, Japan)
 Tokyo : Springer, c2006.
 Description
 Book — xii, 390 p. : ill. (1 col.)
 Summary

 1. Market's Basic Properties
 Correlated Randomeness: Rare and Notsorare Events in Finance
 Nontrivial scaling of fluctuations in the trading activity of NYSE
 Dynamics and predictability of fluctuations in dollaryen exchange rates
 Temporal characteristics of moving average of foreign exchange markets
 Characteristic market behaviors caused by intervention in a foreign exchange market
 Apples and Oranges: the difference between the Reaction of the Emerging and Mature Markets to Crashes
 Scaling and Memory in Return Loss Intervals: Application to Risk Estimation
 Recurrence analysis near the NASDAQ crash of April 2000
 Modeling a foreign exchange rate using moving average of YenDollar market data
 Systematic tuning of optimal weightedmovingaverage of yendollar market data
 Power law and its transition in the slow convergence to a Gaussian in the S&P500 index
 Empirical study of the market impact in the Tokyo Stock Exchange
 Econophysics to unravel the hidden dynamics of commodity markets
 A characteristic time scale of tick quotes on foreign currency markets
 2. Predictability of Markets
 Order book dynamics and price impact
 Prediction oriented variant of financial logperiodicity and speculating about the stock market development until 2010
 Quantitative Forecasting and Modeling Stock Price Fluctuations
 Time series of stock price and of two fractal overlaps: Anticipating market crashes ?
 Short Time Segment Price Forecasts Using Spline Fit Interactions
 Successful Price Cycle Forecasts for S&P Futures Using TF3  a Pattern Recognition Algorithms Based on the KNN Method
 The Hurst's exponent in technical analysis signals
 Financial Markets Dynamic Distribution Function, Predictability and Investment DecisionMaking (FMDDF)
 Market Cycle Turning Point Forecasts by a TwoParameter Learning Algorithm as a Trading Tool for S&P Futures
 3. Mathematical models
 The CTRWs in finance: the mean exit time
 Discretized ContinuousTime Hierarchical Walks and Flights as possible bases of the nonlinear longterm autocorrelations observed in highfrequency financial timeseries
 Evidence for Superdiffusion and "Momentum" in Stock Price Changes
 Beyond the Third Dimension: Searching for the Price Equation
 An agentbased model of financial returns in a limit order market
 Stock price process and the longrange percolation
 What information is hidden in chaotic time series?
 Analysis of Evolution of Stock Prices in Terms of Oscillation Theory
 Simple stochastic modeling for fat tails in financial markets
 Agent Based Simulation Design Principles ? Applications to Stock Market
 Heterogeneous agents model for stock market dynamics: role of market leaders and fundamental prices
 Dynamics of Interacting Strategies
 Emergence of twophase behavior in markets through interaction and learning in agents with bounded rationality
 Explanation of binarized tick data using investor sentiment and genetic learning
 A Gametheoretic Stochastic Agents Model for Enterprise Risk Management
 4. Correlation and Risk Management
 Blackouts, risk, and fattailed distributions
 Portfolio Selection in a Noisy Environment Using Absolute Deviation as a Risk Measure
 Application of PCA and Random Matrix Theory to Passive Fund Management
 Testing Methods to Reduce Noise in Financial Correlation Matrices
 Application of noise level estimation for portfolio optimization
 Method of Analyzing Weather Derivatives Based on Longrange Weather Forecasts
 Investment horizons : A timedependent measure of asset performance
 Clustering financial time series
 Risk portofolio management under Zipf analysis based strategies
 Macroplayers in stock markets
 Conservative Estimation of Default Rate Correlations
 Are Firm Growth Rates Random? Evidence from Japanese Small Firms
 Trading Volume and Information Dynamics of Financial Markets
 Random Matrix Theory Applied to Portfolio Optimization in Japanese Stock Market
 Growth and Fluctuations for SmallBusiness Firms
 5. Networks and Wealth Distributions
 The skeleton of the Shareholders Networks
 Financial Market  A Network Perspective
 Change of ownership networks in Japan
 G7 country Gross Domestic Product (GDP) time correlations  A graph network analysis
 Dependence of Distribution and Velocity of Money on Required Reserve Ratio
 Prospects for Money Transfer Models
 Inequalities of Wealth Distribution in a Society with Social Classes
 Analyzing money distributions in 'ideal gas' models of markets
 Unstable periodic orbits and chaotic transitions among growth patterns of an economy
 Powerlaw behaviors in high income distribution
 The powerlaw exponent and the competition rule of the high income model
 6. New Ideas
 Personal versus economic freedom
 Complexity in an Interacting System of Production
 Four Ingredients for New Approaches to Macroeconomic Modeling
 Competition phase space: theory and practice
 Analysis of Retail Spatial Market System by the Constructive Simulation Method
 QuantumMonadology Approach to Economic Systems
 Visualization of microstructures of economic flows and adaptive control.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
71. Practical fruits of Econophysics : proceedings of the third Nikkei Econophysics Symposium [2006]
 Nikkei Econophysics Symposium (3rd : 2004 : Tokyo, Japan)
 Tokyo ; New York : Springer, ©2006.
 Description
 Book — 1 online resource (xii, 390 pages) : illustrations Digital: text file.PDF.
 Summary

 1. Market's Basic Properties
 Correlated Randomeness: Rare and Notsorare Events in Finance
 Nontrivial scaling of fluctuations in the trading activity of NYSE
 Dynamics and predictability of fluctuations in dollaryen exchange rates
 Temporal characteristics of moving average of foreign exchange markets
 Characteristic market behaviors caused by intervention in a foreign exchange market
 Apples and Oranges: the difference between the Reaction of the Emerging and Mature Markets to Crashes
 Scaling and Memory in Return Loss Intervals: Application to Risk Estimation
 Recurrence analysis near the NASDAQ crash of April 2000
 Modeling a foreign exchange rate using moving average of YenDollar market data
 Systematic tuning of optimal weightedmovingaverage of yendollar market data
 Power law and its transition in the slow convergence to a Gaussian in the S&P500 index
 Empirical study of the market impact in the Tokyo Stock Exchange
 Econophysics to unravel the hidden dynamics of commodity markets
 A characteristic time scale of tick quotes on foreign currency markets
 2. Predictability of Markets
 Order book dynamics and price impact
 Prediction oriented variant of financial logperiodicity and speculating about the stock market development until 2010
 Quantitative Forecasting and Modeling Stock Price Fluctuations
 Time series of stock price and of two fractal overlaps: Anticipating market crashes ?
 Short Time Segment Price Forecasts Using Spline Fit Interactions
 Successful Price Cycle Forecasts for S&P Futures Using TF3  a Pattern Recognition Algorithms Based on the KNN Method
 The Hurst's exponent in technical analysis signals
 Financial Markets Dynamic Distribution Function, Predictability and Investment DecisionMaking (FMDDF)
 Market Cycle Turning Point Forecasts by a TwoParameter Learning Algorithm as a Trading Tool for S&P Futures
 3. Mathematical models
 The CTRWs in finance: the mean exit time
 Discretized ContinuousTime Hierarchical Walks and Flights as possible bases of the nonlinear longterm autocorrelations observed in highfrequency financial timeseries
 Evidence for Superdiffusion and "Momentum" in Stock Price Changes
 Beyond the Third Dimension: Searching for the Price Equation
 An agentbased model of financial returns in a limit order market
 Stock price process and the longrange percolation
 What information is hidden in chaotic time series?
 Analysis of Evolution of Stock Prices in Terms of Oscillation Theory
 Simple stochastic modeling for fat tails in financial markets
 Agent Based Simulation Design Principles ? Applications to Stock Market
 Heterogeneous agents model for stock market dynamics: role of market leaders and fundamental prices
 Dynamics of Interacting Strategies
 Emergence of twophase behavior in markets through interaction and learning in agents with bounded rationality
 Explanation of binarized tick data using investor sentiment and genetic learning
 A Gametheoretic Stochastic Agents Model for Enterprise Risk Management
 4. Correlation and Risk Management
 Blackouts, risk, and fattailed distributions
 Portfolio Selection in a Noisy Environment Using Absolute Deviation as a Risk Measure
 Application of PCA and Random Matrix Theory to Passive Fund Management
 Testing Methods to Reduce Noise in Financial Correlation Matrices
 Application of noise level estimation for portfolio optimization
 Method of Analyzing Weather Derivatives Based on Longrange Weather Forecasts
 Investment horizons : A timedependent measure of asset performance
 Clustering financial time series
 Risk portofolio management under Zipf analysis based strategies
 Macroplayers in stock markets
 Conservative Estimation of Default Rate Correlations
 Are Firm Growth Rates Random? Evidence from Japanese Small Firms
 Trading Volume and Information Dynamics of Financial Markets
 Random Matrix Theory Applied to Portfolio Optimization in Japanese Stock Market
 Growth and Fluctuations for SmallBusiness Firms
 5. Networks and Wealth Distributions
 The skeleton of the Shareholders Networks
 Financial Market  A Network Perspective
 Change of ownership networks in Japan
 G7 country Gross Domestic Product (GDP) time correlations  A graph network analysis
 Dependence of Distribution and Velocity of Money on Required Reserve Ratio
 Prospects for Money Transfer Models
 Inequalities of Wealth Distribution in a Society with Social Classes
 Analyzing money distributions in 'ideal gas' models of markets
 Unstable periodic orbits and chaotic transitions among growth patterns of an economy
 Powerlaw behaviors in high income distribution
 The powerlaw exponent and the competition rule of the high income model
 6. New Ideas
 Personal versus economic freedom
 Complexity in an Interacting System of Production
 Four Ingredients for New Approaches to Macroeconomic Modeling
 Competition phase space: theory and practice
 Analysis of Retail Spatial Market System by the Constructive Simulation Method
 QuantumMonadology Approach to Economic Systems
 Visualization of microstructures of economic flows and adaptive control.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Neapolitan, Richard E.
 San Fransisco, CA : Morgan Kaufmann Publishers, ©2007.
 Description
 Book — 1 online resource (viii, 413 pages) : illustrations Digital: text file.
 Summary

 I: Informatics and Baysesian Networks
 Introduction to Informatics
 Basics of Probability and Statistics
 Algorithms for Bayesian Networks
 Decision Trees and Influence Diagrams. II: Business Informatics: Collaborative Filtering
 Targeted Advertising
 Market Basket Analysis
 Venture Capital Decision Making
 Measuring Operational Risk
 Credit Scoring
 Applications to Investment Science. Appendices.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Neapolitan, Richard E.
 San Fransisco, CA : Morgan Kaufmann Publishers, ©2007.
 Description
 Book — 1 online resource (viii, 413 pages) : illustrations Digital: text file.
 Summary

 I: Informatics and Baysesian Networks
 Introduction to Informatics
 Basics of Probability and Statistics
 Algorithms for Bayesian Networks
 Decision Trees and Influence Diagrams. II: Business Informatics: Collaborative Filtering
 Targeted Advertising
 Market Basket Analysis
 Venture Capital Decision Making
 Measuring Operational Risk
 Credit Scoring
 Applications to Investment Science. Appendices.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Neapolitan, Richard E.
 San Fransisco, CA : Morgan Kaufmann Publishers, c2007.
 Description
 Book — viii, 413 p. : ill. ; 24 cm.
 Summary

 I: Informatics and Baysesian Networks
 Introduction to Informatics
 Basics of Probability and Statistics
 Algorithms for Bayesian Networks
 Decision Trees and Influence Diagrams. II: Business Informatics: Collaborative Filtering
 Targeted Advertising
 Market Basket Analysis
 Venture Capital Decision Making
 Measuring Operational Risk
 Credit Scoring
 Applications to Investment Science. Appendices.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
75. Probability and statistics for finance [2010]
 Hoboken, N.J. : John Wiley & Sons, ©2010.
 Description
 Book — 1 online resource (xviii, 654 pages) : illustrations
 Summary

 Preface. About the Authors.
 CHAPTER 1 Introduction. Probability Versus Statistics. Overview of the Book. PART ONE Descriptive Statistics.
 CHAPTER 2 Basic Data Analysis. Data Types. Frequency Distributions. Empirical Cumulative Frequency Distribution. Data Classes. Cumulative Frequency Distributions. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 3 Measures of Location and Spread. Parameters versus Statistics. Center and Location. Variation. Measures of the Linear Transformation. Summary of Measures. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 4 Graphical Representation of Data. Pie Charts. Bar Chart. Stem and Leaf Diagram. Frequency Histogram. Ogive Diagrams. Box Plot. QQ Plot. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 5 Multivariate Variables and Distributions. Data Tables and Frequencies. Class Data and Histograms. Marginal Distributions. Graphical Representation. Conditional Distribution. Conditional Parameters and Statistics. Independence. Covariance. Correlation. Contingency Coefficient. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 6 Introduction to Regression Analysis. The Role of Correlation. Regression Model: Linear Functional Relationship Between Two Variables. Distributional Assumptions of the Regression Model. Estimating the Regression Model. Goodness of Fit of the Model. Linear Regression of Some NonLinear Relationship. Two Applications in Finance. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 7 Introduction to Time Series Analysis. What Is Time Series? Decomposition of Time Series. Representation of Time Series with Difference Equations. Application: The Price Process. Concepts Explained in this Chapter (In Order of Presentation). PART TWO Basic Probability Theory.
 CHAPTER 8 Concepts of Probability Theory. Historical Development of Alternative Approaches to Probability. Set Operations and Preliminaries. Probability Measure. Random Variable. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 9 Discrete Probability Distributions. Discrete Law. Bernoulli Distribution. Binomial Distribution. Hypergeometric Distribution. Multinomial Distribution. Poisson Distribution Discrete Uniform Distribution. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 10 Continuous Probability Distributions. Continuous Probability Distribution Described. Distribution Function. Density Function. Continuous Random Variable. Computing Probabilities from the Density Function. Location Parameters. Dispersion Parameters. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 11 Continuous Probability Distributions with Appealing Statistical Properties. Normal Distribution. ChiSquare Distribution. Student's t Distribution. F Distribution. Exponential Distribution. Rectangular Distribution. Gamma Distribution. Beta Distribution. LogNormal Distribution. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 12 Continuous Probability Distributions Dealing with Extreme Events. Generalized Extreme Value Distribution. Generalized Pareto Distribution. Normal Inverse Gaussian Distribution. aStable Distribution. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 13 Parameters of Location and Scale of Random Variables. Parameters of Location. Parameters of Scale. Concepts Explained in this Chapter (In Order of Presentation). Appendix: Parameters for Various Distribution Functions.
 CHAPTER 14 Joint Probability Distributions. Higher Dimensional Random Variables. Joint Probability Distribution. Marginal Distributions. Dependence. Covariance and Correlation. Selection of Multivariate Distributions. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 15 Conditional Probability and Bayes' Rule. Conditional Probability. Independent Events. Multiplicative Rule of Probability. Bayes' Rule. Conditional Parameters. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 16 Copula and Dependence Measures. Copula. Alternative Dependence Measures. Concepts Explained in this Chapter (In Order of Presentation). PART THREE Inductive Statistics.
 CHAPTER 17 Point Estimators. Sample, Statistic, and Estimator. Quality Criteria of Estimators. Large Sample Criteria. Maximum Likehood Estimator. Exponential Family and Sufficiency. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 18 Confidence Intervals. Confidence Level and Confidence Interval. Confidence Interval for the Mean of a Normal Random Variable. Confidence Interval for the Mean of a Normal Random Variable with Unknown Variance. Confidence Interval for the Parameter p of a Binomial Distribution. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 19 Hypothesis Testing. Hypotheses. Error Types. Quality Criteria of a Test. Examples. Concepts Explained in this Chapter (In Order of Presentation). PART FOUR Multivariate Linear Regression Analysis.
 CHAPTER 20 Estimates and Diagnostics for Multivariate Linear Regression Analysis. The Multivariate Linear Regression Model. Assumptions of the Multivariate Linear Regression Model. Estimation of the Model Parameters. Designing the Model. Diagnostic Check and Model Significance. Applications to Finance. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 21 Designing and Building a Multivariate Linear Regression Model. The Problem of Multicollinearity. Incorporating Dummy Variables as Independent Variables. Model Building Techniques 561 Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 22 Testing the Assumptions of the Multivariate Linear Regression Model. Tests for Linearity. Assumed Statistical Properties About the Error Term. Tests for the Residuals Being Normally Distributed. Tests for Constant Variance of the Error Term (Homoskedasticity). Absence of Autocorrelation of the Residuals. Concepts Explained in this Chapter (In Order of Presentation). APPENDIX A Important Functions and Their Features. Continuous Function. Indicator Function. Derivatives. Monotonic Function. Integral. Some Functions. APPENDIX B Fundamentals of Matrix Operations and Concepts. The Notion of Vector and Matrix. Matrix Multiplication. Particular Matrices. Positive Semidefinite Matrices. APPENDIX C Binomial and Multinomial Coefficients. Binomial Coefficient. Multinomial Coefficient. APPENDIX D Application of the LogNormal Distribution to the Pricing of Call Options. Call Options. Deriving the Price of a European Call Option. Illustration. REFERENCES. INDEX.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
76. Probability and statistics for finance [2010]
 Hoboken, N.J. : John Wiley & Sons, ©2010.
 Description
 Book — 1 online resource (xviii, 654 pages) : illustrations.
 Summary

 Preface xv About the Authors xvii
 CHAPTER 1 Introduction 1 Probability vs. Statistics 4 Overview of the Book 5 Part One Descriptive Statistics 15
 Chapter 2 Basic Data Analysis 17 Data Types 17 Frequency Distributions 22 Empirical Cumulative Frequency Distribution 27 Data Classes 32 Cumulative Frequency Distributions 41 Concepts Explained in this
 Chapter 43
 Chapter 3 Measures of Location and Spread 45 Parameters vs. Statistics 45 Center and Location 46 Variation 59 Measures of the Linear Transformation 69 Summary of Measures 71 Concepts Explained in this
 Chapter 73
 Chapter 4 Graphical Representation of Data 75 Pie Charts 75 Bar Chart 78 Stem and Leaf Diagram 81 Frequency Histogram 82 Ogive Diagrams 89 Box Plot 91 QQ Plot 96 Concepts Explained in this
 Chapter 99
 CHAPTER 5 Multivariate Variables and Distributions 101 Data Tables and Frequencies 101 Class Data and Histograms 106 Marginal Distributions 107 Graphical Representation 110 Conditional Distribution 113 Conditional Parameters and Statistics 114 Independence 117 Covariance 120 Correlation 123 Contingency Coefficient 124 Concepts Explained in this
 Chapter 126
 CHAPTER 6 Introduction to Regression Analysis 129 The Role of Correlation 129 Regression Model: Linear Functional Relationship Between Two Variables 131 Distributional Assumptions of the Regression Model 133 Estimating the Regression Model 134 Goodness of Fit of the Model 138 Linear Regression of Some Nonlinear Relationship 140 Two Applications in Finance 142 Concepts Explained in this
 Chapter 149
 CHAPTER 7 Introduction to Time Series Analysis 153 What Is Time Series? 153 Decomposition of Time Series 154 Representation of Time Series with Difference Equations 159 Application: The Price Process 159 Concepts Explained in this
 Chapter 163 Part Two Basic Probability Theory 165
 CHAPTER 8 Concepts of Probability Theory 167 Historical Development of Alternative Approaches to Probability 167 Set Operations and Preliminaries 170 Probability Measure 177 Random Variable 179 Concepts Explained in this
 Chapter 185
 Chapter 9 Discrete Probability Distributions 187 Discrete Law 187 Bernoulli Distribution 192 Binomial Distribution 195 Hypergeometric Distribution 204 Multinomial Distribution 211 Poisson Distribution 216 Discrete Uniform Distribution 219 Concepts Explained in this
 Chapter 221
 CHAPTER 10 Continuous Probability Distributions 229 Continuous Probability Distribution Described 229 Distribution Function 230 Density Function 232 Continuous Random Variable 237 Computing Probabilities from the Density Function 238 Location Parameters 239 Dispersion Parameters 239 Concepts Explained in this
 Chapter 245
 CHAPTER 11 Continuous Probability Distributions with Appealing Statistical Properties 247 Normal Distribution 247 ChiSquare Distribution 254 Student s tDistribution 256 FDistribution 260 Exponential Distribution 262 Rectangular Distribution 266 Gamma Distribution 268 Beta Distribution 269 LogNormal Distribution 271 Concepts Explained in this
 Chapter 275
 CHAPTER 12 Continuous Probability Distributions Dealing with Extreme Events 277 Generalized Extreme Value Distribution 277 Generalized Pareto Distribution 281 Normal Inverse Gaussian Distribution 283 Stable Distribution 285 Concepts Explained in this
 Chapter 292
 CHAPTER 13 Parameters of Location and Scale of Random Variables 295 Parameters of Location 296 Parameters of Scale 306 Concepts Explained in this
 Chapter 321 Appendix: Parameters for Various Distribution Functions 322
 Chapter 14 Joint Probability Distributions 325 Higher Dimensional Random Variables 326 Joint Probability Distribution 328 Marginal Distributions 333 Dependence 338 Covariance and Correlation 341 Selection of Multivariate Distributions 347 Concepts Explained in this
 Chapter 358
 Chapter 15 Conditional Probability and Bayes Rule 361 Conditional Probability 362 Independent Events 365 Multiplicative Rule of Probability 367 Bayes Rule 372 Conditional Parameters 374 Concepts Explained in this
 Chapter 377
 CHAPTER 16 Copula and Dependence Measures 379 Copula 380 Alternative Dependence Measures 406 Concepts Explained in this
 Chapter 412 Part Three Inductive Statistics 413
 Chapter 17 Point Estimators 415 Sample, Statistic, and Estimator 415 Quality Criteria of Estimators 428 Large Sample Criteria 435 Maximum Likehood Estimator 446 Exponential Family and Sufficiency 457 Concepts Explained in this
 Chapter 461
 Chapter 18 Confidence Intervals 463 Confidence Level and Confidence Interval 463 Confidence Interval for the Mean of a Normal Random Variable 466 Confidence Interval for the Mean of a Normal Random Variable with Unknown Variance 469 Confidence Interval for the Variance of a Normal Random Variable 471 Confidence Interval for the Variance of a Normal Random Variable with Unknown Mean 474 Confidence Interval for the Parameter p of a Binomial Distribution 475 Confidence Interval for the Parameter of an Exponential Distribution 477 Concepts Explained in this
 Chapter 479
 Chapter 19 Hypothesis Testing 481 Hypotheses 482 Error Types 485 Quality Criteria of a Test 490 Examples 496 Concepts Explained in this
 Chapter 518 Part Four Multivariate Linear Regression Analysis 519
 CHAPTER 20 Estimates and Diagnostics for Multivariate Linear Regression Analysis 521 The Multivariate Linear Regression Model 522 Assumptions of the Multivariate Linear Regression Model 523 Estimation of the Model Parameters 523 Designing the Model 526 Diagnostic Check and Model Significance 526 Applications to Finance 531 Concepts Explained in this
 Chapter 543
 CHAPTER 21 Designing and Building a Multivariate Linear Regression Model 545 The Problem of Multicollinearity 545 Incorporating Dummy Variables as Independent Variables 548 Model Building Techniques 561 Concepts Explained in this
 Chapter 565
 CHAPTER 22 Testing the Assumptions of the Multivariate Linear Regression Model 567 Tests for Linearity 568 Assumed Statistical Properties about the Error Term 570 Tests for the Residuals Being Normally Distributed 570 Tests for Constant Variance of the Error Term (Homoskedasticity) 573 Absence of Autocorrelation of the Residuals 576 Concepts Explained in this
 Chapter 581 Appendix A Important Functions and Their Features 583 Continuous Function 583 Indicator Function 586 Derivatives 587 Monotonic Function 591 Integral 592 Some Functions 596 Appendix B Fundamentals of Matrix Operations and Concepts 601 The Notion of Vector and Matrix 601 Matrix Multiplication 602 Particular Matrices 603 Positive Semidefinite Matrices 614 APPENDIX C Binomial and Multinomial Coefficients 615 Binomial Coefficient 615 Multinomial Coefficient 622 APPENDIX D Application of the LogNormal Distribution to the Pricing of Call Options 625 Call Options 625 Deriving the Price of a European Call Option 626 Illustration 631 References 633 Index 635.
 (source: Nielsen Book Data)
 Preface. About the Authors.
 CHAPTER 1 Introduction. Probability Versus Statistics. Overview of the Book. PART ONE Descriptive Statistics.
 CHAPTER 2 Basic Data Analysis. Data Types. Frequency Distributions. Empirical Cumulative Frequency Distribution. Data Classes. Cumulative Frequency Distributions. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 3 Measures of Location and Spread. Parameters versus Statistics. Center and Location. Variation. Measures of the Linear Transformation. Summary of Measures. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 4 Graphical Representation of Data. Pie Charts. Bar Chart. Stem and Leaf Diagram. Frequency Histogram. Ogive Diagrams. Box Plot. QQ Plot. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 5 Multivariate Variables and Distributions. Data Tables and Frequencies. Class Data and Histograms. Marginal Distributions. Graphical Representation. Conditional Distribution. Conditional Parameters and Statistics. Independence. Covariance. Correlation. Contingency Coefficient. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 6 Introduction to Regression Analysis. The Role of Correlation. Regression Model: Linear Functional Relationship Between Two Variables. Distributional Assumptions of the Regression Model. Estimating the Regression Model. Goodness of Fit of the Model. Linear Regression of Some NonLinear Relationship. Two Applications in Finance. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 7 Introduction to Time Series Analysis. What Is Time Series? Decomposition of Time Series. Representation of Time Series with Difference Equations. Application: The Price Process. Concepts Explained in this Chapter (In Order of Presentation). PART TWO Basic Probability Theory.
 CHAPTER 8 Concepts of Probability Theory. Historical Development of Alternative Approaches to Probability. Set Operations and Preliminaries. Probability Measure. Random Variable. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 9 Discrete Probability Distributions. Discrete Law. Bernoulli Distribution. Binomial Distribution. Hypergeometric Distribution. Multinomial Distribution. Poisson Distribution Discrete Uniform Distribution. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 10 Continuous Probability Distributions. Continuous Probability Distribution Described. Distribution Function. Density Function. Continuous Random Variable. Computing Probabilities from the Density Function. Location Parameters. Dispersion Parameters. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 11 Continuous Probability Distributions with Appealing Statistical Properties. Normal Distribution. ChiSquare Distribution. Student's t Distribution. F Distribution. Exponential Distribution. Rectangular Distribution. Gamma Distribution. Beta Distribution. LogNormal Distribution. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 12 Continuous Probability Distributions Dealing with Extreme Events. Generalized Extreme Value Distribution. Generalized Pareto Distribution. Normal Inverse Gaussian Distribution. aStable Distribution. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 13 Parameters of Location and Scale of Random Variables. Parameters of Location. Parameters of Scale. Concepts Explained in this Chapter (In Order of Presentation). Appendix: Parameters for Various Distribution Functions.
 CHAPTER 14 Joint Probability Distributions. Higher Dimensional Random Variables. Joint Probability Distribution. Marginal Distributions. Dependence. Covariance and Correlation. Selection of Multivariate Distributions. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 15 Conditional Probability and Bayes' Rule. Conditional Probability. Independent Events. Multiplicative Rule of Probability. Bayes' Rule. Conditional Parameters. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 16 Copula and Dependence Measures. Copula. Alternative Dependence Measures. Concepts Explained in this Chapter (In Order of Presentation). PART THREE Inductive Statistics.
 CHAPTER 17 Point Estimators. Sample, Statistic, and Estimator. Quality Criteria of Estimators. Large Sample Criteria. Maximum Likehood Estimator. Exponential Family and Sufficiency. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 18 Confidence Intervals. Confidence Level and Confidence Interval. Confidence Interval for the Mean of a Normal Random Variable. Confidence Interval for the Mean of a Normal Random Variable with Unknown Variance. Confidence Interval for the Parameter p of a Binomial Distribution. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 19 Hypothesis Testing. Hypotheses. Error Types. Quality Criteria of a Test. Examples. Concepts Explained in this Chapter (In Order of Presentation). PART FOUR Multivariate Linear Regression Analysis.
 CHAPTER 20 Estimates and Diagnostics for Multivariate Linear Regression Analysis. The Multivariate Linear Regression Model. Assumptions of the Multivariate Linear Regression Model. Estimation of the Model Parameters. Designing the Model. Diagnostic Check and Model Significance. Applications to Finance. Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 21 Designing and Building a Multivariate Linear Regression Model. The Problem of Multicollinearity. Incorporating Dummy Variables as Independent Variables. Model Building Techniques 561 Concepts Explained in this Chapter (In Order of Presentation).
 CHAPTER 22 Testing the Assumptions of the Multivariate Linear Regression Model. Tests for Linearity. Assumed Statistical Properties About the Error Term. Tests for the Residuals Being Normally Distributed. Tests for Constant Variance of the Error Term (Homoskedasticity). Absence of Autocorrelation of the Residuals. Concepts Explained in this Chapter (In Order of Presentation). APPENDIX A Important Functions and Their Features. Continuous Function. Indicator Function. Derivatives. Monotonic Function. Integral. Some Functions. APPENDIX B Fundamentals of Matrix Operations and Concepts. The Notion of Vector and Matrix. Matrix Multiplication. Particular Matrices. Positive Semidefinite Matrices. APPENDIX C Binomial and Multinomial Coefficients. Binomial Coefficient. Multinomial Coefficient. APPENDIX D Application of the LogNormal Distribution to the Pricing of Call Options. Call Options. Deriving the Price of a European Call Option. Illustration. REFERENCES. INDEX.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Hong Kong International Workshop on Statistics and Finance (1999 : Centre of Financial Time Series, University of Hong Kong)
 London : Imperial College Press ; River Edge, NJ : Distributed by World Scientific Pub., ©2000.
 Description
 Book — 1 online resource (x, 384 pages) : illustrations
 Summary

 pt. I. Time series methodology. Heavytailed and nonlinear continuoustime ARMA models for financial time series / P.J. Brockwell
 Nonlinear state space model approach to financial time series with timevarying variance / G. Kitagawa and S. Sato
 Nonparametric estimation and bootstrap for financial time series / J.P. Kreif[symbol]
 Comparison of two discretization methods for estimating continuoustime autoregressive models / H. Tsai and K.S. Chan
 A note on kernel estimation in integrated time series / Y.C. Xia, W.K. Li and H. Tong
 pt. II. Long memory and value at risk. Stylized facts on the temporal and distributional properties of absolute returns: an update / C.W.J. Granger, S. Spear and Z.X. Ding
 Volatility computed by time series operators at high frequency / U.A. Müller
 Missing values in ARFIMA models / W. Palma
 Second order tail effects / C.G. de Vries
 pt. III. Volatility. Recent developments in heteroskedastic time series / N.H. Chan and G. Petris
 Bayesian estimation of stochastic volatility model via scale mixtures distributions / S.T.B. Choy and C.M. Chan
 On a smooth transition double threshold model / Y.N. Lee and W.K. Li
 Testing GARCH versus EGARCH / S. Ling and M. McAleer
 pt. IV. Forecasting. Interval prediction of financial time series / B. Cheng and H. Tong
 A decision theoretic approach to forecast evaluation / C.W.J. Granger and M.H. Pesaran
 Learning and forecasting with stochastic neural networks / T.L. Lai and S.P.S. Wong
 pt. V. Applications. The overreacting behavior of real exchange rate dynamics / Y.W. Cheung and K.S. Lai
 Portfolio management and market risk quantification using neural networks / J. Franke
 Optimal asset allocation under GARCH model / W.C. Hui, H. Yang and K.C. Yuen
 Statistical modelling of the Jcurve effect in trade balance: a case study / W.C. Ip [and others]
 Ruin theory with interest incomes / H. Yang and L. Zhang
 Detecting structural changes using genetic programming with an application to the greaterChina stock markets / X.B. Zhang, Y.K. Tse and W.S. Chan.
 Hong Kong International Workshop on Statistics and Finance (1999 : Centre of Financial Time Series, University of Hong Kong)
 London : Imperial College Press ; River Edge, NJ : Distributed by World Scientific Pub., ©2000.
 Description
 Book — 1 online resource (x, 384 pages) : illustrations
 Summary

 pt. I. Time series methodology. Heavytailed and nonlinear continuoustime ARMA models for financial time series / P.J. Brockwell
 Nonlinear state space model approach to financial time series with timevarying variance / G. Kitagawa and S. Sato
 Nonparametric estimation and bootstrap for financial time series / J.P. Kreif[symbol]
 Comparison of two discretization methods for estimating continuoustime autoregressive models / H. Tsai and K.S. Chan
 A note on kernel estimation in integrated time series / Y.C. Xia, W.K. Li and H. Tong
 pt. II. Long memory and value at risk. Stylized facts on the temporal and distributional properties of absolute returns: an update / C.W.J. Granger, S. Spear and Z.X. Ding
 Volatility computed by time series operators at high frequency / U.A. Müller
 Missing values in ARFIMA models / W. Palma
 Second order tail effects / C.G. de Vries
 pt. III. Volatility. Recent developments in heteroskedastic time series / N.H. Chan and G. Petris
 Bayesian estimation of stochastic volatility model via scale mixtures distributions / S.T.B. Choy and C.M. Chan
 On a smooth transition double threshold model / Y.N. Lee and W.K. Li
 Testing GARCH versus EGARCH / S. Ling and M. McAleer
 pt. IV. Forecasting. Interval prediction of financial time series / B. Cheng and H. Tong
 A decision theoretic approach to forecast evaluation / C.W.J. Granger and M.H. Pesaran
 Learning and forecasting with stochastic neural networks / T.L. Lai and S.P.S. Wong
 pt. V. Applications. The overreacting behavior of real exchange rate dynamics / Y.W. Cheung and K.S. Lai
 Portfolio management and market risk quantification using neural networks / J. Franke
 Optimal asset allocation under GARCH model / W.C. Hui, H. Yang and K.C. Yuen
 Statistical modelling of the Jcurve effect in trade balance: a case study / W.C. Ip [and others]
 Ruin theory with interest incomes / H. Yang and L. Zhang
 Detecting structural changes using genetic programming with an application to the greaterChina stock markets / X.B. Zhang, Y.K. Tse and W.S. Chan.
 Hong Kong International Workshop on Statistics and Finance (1999 : Centre of Financial Time Series, University of Hong Kong)
 London : Imperial College Press ; Singapore : Distributed by World Scientific Pub. Co., c2000.
 Description
 Book — x, 384 p. : ill.
 Summary

 pt. I. Time series methodology. Heavytailed and nonlinear continuoustime ARMA models for financial time series / P.J. Brockwell
 Nonlinear state space model approach to financial time series with timevarying variance / G. Kitagawa and S. Sato
 Nonparametric estimation and bootstrap for financial time series / J.P. Kreif[symbol]
 Comparison of two discretization methods for estimating continuoustime autoregressive models / H. Tsai and K.S. Chan
 A note on kernel estimation in integrated time series / Y.C. Xia, W.K. Li and H. Tong
 pt. II. Long memory and value at risk. Stylized facts on the temporal and distributional properties of absolute returns: an update / C.W.J. Granger, S. Spear and Z.X. Ding
 Volatility computed by time series operators at high frequency / U.A. Müller
 Missing values in ARFIMA models / W. Palma
 Second order tail effects / C.G. de Vries
 pt. III. Volatility. Recent developments in heteroskedastic time series / N.H. Chan and G. Petris
 Bayesian estimation of stochastic volatility model via scale mixtures distributions / S.T.B. Choy and C.M. Chan
 On a smooth transition double threshold model / Y.N. Lee and W.K. Li
 Testing GARCH versus EGARCH / S. Ling and M. McAleer
 pt. IV. Forecasting. Interval prediction of financial time series / B. Cheng and H. Tong
 A decision theoretic approach to forecast evaluation / C.W.J. Granger and M.H. Pesaran
 Learning and forecasting with stochastic neural networks / T.L. Lai and S.P.S. Wong
 pt. V. Applications. The overreacting behavior of real exchange rate dynamics / Y.W. Cheung and K.S. Lai
 Portfolio management and market risk quantification using neural networks / J. Franke
 Optimal asset allocation under GARCH model / W.C. Hui, H. Yang and K.C. Yuen
 Statistical modelling of the Jcurve effect in trade balance: a case study / W.C. Ip ... [et al.]
 Ruin theory with interest incomes / H. Yang and L. Zhang
 Detecting structural changes using genetic programming with an application to the greaterChina stock markets / X.B. Zhang, Y.K. Tse and W.S. Chan.
80. Python for finance [2015]
 Hilpisch, Yves J. author.
 First edition.  Sebastopol, CA : O'Reilly Media, 2014.
 Description
 Book — xv, 586 pages : illustrations ; 24 cm
 Summary

The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This handson guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a fullfledged framework for Monte Carlo simulationbased derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, ValueatRisk, and CreditValueatRisk calculations; statistics for normality tests, meanvariance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies.
(source: Nielsen Book Data)
 Hilpisch, Yves J., author.
 Second edition.  Sebastopol, CA : O'Reilly Media, [2019]
 Description
 Book — 1 online resource (1 volume) : illustrations
 Summary

 Part I. Python and Finance; Part II. Mastering the Basics; Part III. Financial Data Science; Part IV. Algorithmic Trading; Part V. Derivatives Analytics; Appendix A. Dates and Times; Appendix B. BSM Option Class.
82. Random processes in physics and finance [2006]
 Lax, Melvin J.
 Oxford ; New York : Oxford University Press, 2006.
 Description
 Book — xiii, 327 p. : ill. ; 25 cm.
 Summary

 1. Review of Probability
 2. What is a Random Process
 3. Examples of Markovian Processes
 4. Spectral Measurement and Correlation
 5. Thermal Noise
 6. Shot Noise
 7. The FluctuationDissipation Theorem
 8. Generalized FokkerPlanck Equation of Markov Process
 9. Langevin Process
 10. Langevin Treatment of the FokkerPlanck Process
 11. The Rotating Wave Van Del Pol Oscillator (RWVP)
 12. Noise in Homogeneous Semiconductors
 13. Random Walk of Light in Turbid Media
 14. Analytical Solution of the Elastic Boltzmann Transport Equation
 15. Signal Extraction in the Presence of Smoothing and Noise
 16. Stochastic Methods to Investment Decision
 17. Spectral Analysis of Economic Time Series.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
SAL3 (offcampus storage)
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Stacks  Request (opens in new tab) 
QC20.7 .S8 L39 2006  Available 
 Lax, Melvin J.
 Oxford ; New York : Oxford University Press, 2006.
 Description
 Book — xiii, 327 p. : ill.
 Frees, Edward W.
 Cambridge ; New York : Cambridge University Press, 2010.
 Description
 Book — 1 online resource (xvii, 565 pages) : illustrations Digital: text file.
 Summary

 1. Regression and the normal distribution
 Part I. Linear Regression: 2. Basic linear regression
 3. Multiple linear regression  I
 4. Multiple linear regression  II
 5. Variable selection
 6. Interpreting regression results
 Part II. Topics in Time Series: 7. Modeling trends
 8. Autocorrelations and autoregressive models
 9. Forecasting and time series models
 10. Longitudinal and panel data models
 Part III. Topics in Nonlinear Regression: 11. Categorical dependent variables
 12. Count dependent variables
 13. Generalized linear models
 14. Survival models
 15. Miscellaneous regression topics
 Part IV. Actuarial Applications: 16. Frequencyseverity models
 17. Fattailed regression models
 18. Credibility and bonusmalus
 19. Claims triangles
 20. Report writing: communicating data analysis results
 21. Designing effective graphs
 Appendix 1: basic statistical inference
 Appendix 2: matrix algebra
 Appendix 3: probability tables.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Frees, Edward W.
 Cambridge : Cambridge University Press, 2009.
 Description
 Book — 1 online resource (584 p.) : digital, PDF file(s).
 Summary

 1. Regression and the normal distribution
 Part I. Linear Regression: 2. Basic linear regression
 3. Multiple linear regression  I
 4. Multiple linear regression  II
 5. Variable selection
 6. Interpreting regression results
 Part II. Topics in Time Series: 7. Modeling trends
 8. Autocorrelations and autoregressive models
 9. Forecasting and time series models
 10. Longitudinal and panel data models
 Part III. Topics in Nonlinear Regression: 11. Categorical dependent variables
 12. Count dependent variables
 13. Generalized linear models
 14. Survival models
 15. Miscellaneous regression topics
 Part IV. Actuarial Applications: 16. Frequencyseverity models
 17. Fattailed regression models
 18. Credibility and bonusmalus
 19. Claims triangles
 20. Report writing: communicating data analysis results
 21. Designing effective graphs
 Appendix 1: basic statistical inference
 Appendix 2: matrix algebra
 Appendix 3: probability tables.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Washington, D.C. : International Monetary Fund, 1992.
 Description
 Book — viii, 97 p. ; 28 cm.
 Online
SAL3 (offcampus storage)
SAL3 (offcampus storage)  Status 

Stacks  Request (opens in new tab) 
HG3891 .B33 1992  Available 
 Washington, D.C. : International Monetary Fund, 1992.
 Description
 Book — 1 online resource (viii, 97 pages)
 Summary

The Background Papers gathers together a number of studies that were prepared as research to the final report. Although not a part of the report itself, these papers provide detail on a number of issues grouped together here by general topic; data sources and methodology, direct investment, portfolio investment, international banking statistics, and other capital flows.
 [Place of publication not identified] : WORLD SCIENTIFIC, 2017.
 Description
 Book — 1 online resource.
 Summary

with an autobiography from Ragnar NorbergThe Risk and Stochastics Conference, held at the Royal Statistical Society in April 2015, brought together academics from the worlds of actuarial science, stochastic calculus, finance and statistics to celebrate the achievements of Professor Ragnar Norberg as he turned 70. After the conference, Ragnar Norberg suddenly fell very ill and passed away; this book honours his life and work.This collection of articles is written by speakers of the conference, themselves respected academics who have influenced and been influenced by the life and work of Professor Norberg. His professional and academic achievements are celebrated here, most significantly the instrumental work he put into setting up the worldrenowned Risk and Stochastics Enterprise at the London School of Economics (LSE). Subjects covered include discussion of risk measurements, ruin constraint, supporting stable pensions, filtration in discrete time, Riesz means and Beurling moving averages and orthonormal polynomial expansions. Also featured are notes from contributors giving account of their personal relations with Professor Norberg, as well as an autobiographical chapter from the man himself.Aimed at graduate level students and researchers interested in the life and work of Ragnar Norberg, this book provides a unique opportunity to reflect on and understand key findings and groundbreaking research in modern actuarial and financial mathematics and their interface, while giving intimate insights into the life of a leading academic mind.
(source: Nielsen Book Data)
89. Smallarea estimates of schoolage children in poverty : evaluation of current methodology [2000]
 National Research Council (U.S.). Panel on Estimates of Poverty for Small Geographic Areas.
 Washington, D.C. : National Academy Press, ©2000.
 Description
 Book — 1 online resource (xi, 256 pages) : illustrations Digital: data file.
 Summary

 Introduction and overview
 Title I allocation procedures
 Data sources for county estimates
 Estimation procedure for counties
 Alternative county models
 Evaluations of county estimates
 School district estimates
 Population estimates
 Research and development priorities
 Appendix A: Models for county and state poverty estimates
 Appendix B: Regression diagnostics on alternative county regression models
 Appendix C: County model comparisons with 1990 census estimates
 Appendix D: Use of school lunch data in New York state for the estimation of schoolage children in poverty: an analysis / James H. Wyckoff and Frank Papa
 Appendix E: Special case: estimates for Puerto Rico.
90. Smallarea estimates of schoolage children in poverty : evaluation of current methodology [2000]
 National Research Council (U.S.). Panel on Estimates of Poverty for Small Geographic Areas.
 Washington, D.C. : National Academy Press, c2000.
 Description
 Book — xi, 256 p. : ill ; 23 cm.
SAL3 (offcampus storage)
SAL3 (offcampus storage)  Status 

Stacks  Request (opens in new tab) 
HQ792 .U5 N375 2000  Available 
 National Research Council (U.S.). Panel on Estimates of Poverty for Small Geographic Areas.
 Washington, D.C. : National Academy Press, 1998.
 Description
 Book — 1 online resource (x, 173 pages) : illustrations.
 Summary

 1 FRONT MATTER
 2 EXECUTIVE SUMMARY
 3 1. INTRODUCTION
 4 2. CENSUS BUREAU ESTIMATION PROCEDURE
 5 3. ALTERNATIVE COUNTY MODELS
 6 4. EVALUATIONS
 7 5. RECOMMENDATION FOR TITLE I ALLOCATIONS FOR THE 19981999 SCHOOL YEAR
 8 6. FUTURE RESEARCH AND DEVELOPMENT FOR COUNTY ESTIMATES
 9 APPENDIX A. MODELS FOR COUNTY AND STATE POVERTY ESTIMATES
 10 APPENDIX B. POPULATION ESTIMATES
 11 APPENDIX C. REGRESSION DIAGNOSTICS ON ALTERNATIVE COUNTY REGRESSION MODELS
 12 APPENDIX D. COUNTY MODEL COMPARISONS WITH 1990 CENSUS ESTIMATES
 13 REFERENCES
 14 BIOGRAPHICAL SKETCHES, PANEL MEMBERS AND STAFF.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 National Research Council (U.S.). Panel on Estimates of Poverty for Small Geographic Areas.
 Washington, D.C. : National Academy Press, 1999.
 Description
 Book — viii, 124 p. : ill. ; 23 cm.
 Summary

 1 Front Matter
 2 Executive Summary
 3 1 Introduction
 4 2 County Estimates
 5 3 School District Estimates
 6 4 Recommendations for Title I Allocations for the 19992000 School Year
 7 5 Future Research and Development
 8 Appendix
 9 References and Bibliography
 10 Biographical Sketches of Panel Members and Staff.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
SAL3 (offcampus storage)
SAL3 (offcampus storage)  Status 

Stacks  Request (opens in new tab) 
HQ792 .U5 N373 1999  Available 
 National Research Council (U.S.). Panel on Estimates of Poverty for Small Geographic Areas.
 Washington, D.C. : National Academy Press, 1999.
 Description
 Book — 1 online resource (viii, 124 pages) : illustrations.
 Summary

 1 Front Matter
 2 Executive Summary
 3 1 Introduction
 4 2 County Estimates
 5 3 School District Estimates
 6 4 Recommendations for Title I Allocations for the 19992000 School Year
 7 5 Future Research and Development
 8 Appendix
 9 References and Bibliography
 10 Biographical Sketches of Panel Members and Staff.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 National Research Council (U.S.). Panel on Estimates of Poverty for Small Geographic Areas.
 Washington, D.C. : National Academy Press, 1997.
 Description
 Book — 1 online resource (viii, 88 pages)
 Summary

 1 FRONT MATTER
 2 EXECUTIVE SUMMARY
 3 1. INTRODUCTION
 4 2. POVERTY ESTIMATES BASED ON CENSUS AND CPS DATA
 5 3. MODELBASED ESTIMATES OF POOR SCHOOLAGE CHILDREN
 6 4. PANEL ASSESSMENT OF THE METHODOLOGY
 7 5. RECOMMENDATION FOR TITLE I ALLOCATIONS
 8 6. NEXT STEPS
 9 A. THE TITLE I ALLOCATION PROCESS
 10 B. COMPARISON OF CENSUS AND CPS ESTIMATES OF POVERTY
 11 C. CENSUS BUREAU'S METHODOLOGY FOR MODELBASED ESTIMATES
 12 D. POPULATION ESTIMATES
 13 E. FUTURE RESEARCH
 14 F. SPECIAL CASE: ESTIMATES FOR PUERTO RICO
 15 REFERENCES
 16 BIOGRAPHICAL SKETCHES, PANEL MEMBERS AND STAFF.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Voit, Johannes, 1957
 3rd ed.  Berlin ; New York : Springer, c2005.
 Description
 Book — xv, 378 p. : ill. ; 25 cm.
 Summary

This highly praised introductory treatment describes the parallels between statistical physics and finance  both those established in the 100year long interaction between these disciplines, as well as new research results on financial markets. The randomwalk technique, well known in physics, is also the basic model in finance, upon which are built, for example, the BlackScholes theory of option pricing and hedging, plus methods of portfolio optimization. Here the underlying assumptions are assessed critically. Using empirical financial data and analogies to physical models such as fluid flows, turbulence, or superdiffusion, the book develops a more accurate description of financial markets based on random walks. With this approach, novel methods for derivative pricing and risk management can be formulated. Computer simulations of interactingagent models provide insight into the mechanisms underlying unconventional price dynamics. It is shown that stock exchange crashes can be modelled in ways analogous to phase transitions and earthquakes, and sometimes have even been predicted successfully. This third edition of "The Statistical Mechanics of Financial Markets" especially stands apart from other treatments because it offers new chapters containing a practitioner's treatment of two important current topics in banking: the basic notions and tools of risk management and capital requirements for financial institutions, including an overview of the new Basel II capital framework which may well set the risk management standards in scores of countries for years to come.
(source: Nielsen Book Data)
 Online
Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
HG176.5 .V64 2005  Unknown 
 Voit, Johannes, 1957
 3rd ed.  Berlin ; New York : Springer, ©2005.
 Description
 Book — 1 online resource (xv, 378 pages) : illustrations Digital: text file.PDF.
 Summary

 Basic Information on Capital Markets
 Random Walks in Finance and Physics
 The BlackScholes Theory of Option Prices
 Scaling in Financial Data and in Physics
 Turbulence and Foreign Exchange Markets
 Derivative Pricing Beyond BlackScholes
 Microscopic Market Models
 Theory of Stock Exchange Crashes
 Risk Management
 Economic and Regulatory Capital for Financial Institutions.
 Voit, Johannes, 1957
 Berlin ; New York : Springer, [2001]
 Description
 Book — 1 online resource (xii, 220 pages) : illustrations Digital: text file.PDF.
 Summary

 1. Introduction
 2. Basic Information on Capital Markets
 3. Random Walks in Finance and Physics
 4. The BlackScholes Theory of Option Prices
 5. Scaling in Financial Data and in Physics
 6. Turbulence and Foreign Exchange Markets
 7. Risk Control and Derivative Pricing in NonGaussian Markets
 8. Microscopic Market Models
 9. Theory of Stock Exchange Crashes.
 Voit, Johannes, 1957
 3rd ed.  Berlin ; New York : Springer, c2005.
 Description
 Book — xv, 378 p. : ill. .
 Switzerland : Springer, 2016.
 Description
 Book — 1 online resource (viii, 225 pages) : illustrations (some color)
 Summary

 1 Frederi Viens: A didactic introduction to risk management via hedging in discrete and continuous time
 2 M'hamed Eddahbi and Sidi Mohamed Lalaoui Ben Cherif: Sensitivity analysis for timeinhomogeneous Ĺevy process: A Malliavin calculus approach and numeric
 3 Nicolas Privault and Dichuan Yang: VarianceGGC asset price models and their sensitivity analysis
 4 Josep Vives: Decomposition of the pricing formula for stochastic volatility models based on MalliavinSkorohod type calculus
 5 Boualem Djehiche: Statistical estimation techniques in life and disability insurance A short overview
 6 AbdulRahman AlHussein: Necessary and sufficient conditions of optimal control for infinite dimensional SDEs
 7 AbdulRahman AlHussein and Boulakhras Gherbal: Sufficient conditions of optimality for forwardbackward doubly SDEs with jumps
 8 Mohsine Benabdallah, Siham Bouhadou, Youssef Ouknine: On the pathwise uniqueness of solutions of onedimensional stochastic differential equations with jumps
 9 E.H. Essaky and M. Hassani: BSDE Approach for Dynkin Game and American Game Option.
100. Statistical methods for financial engineering [2013]
 Rémillard, Bruno, author.
 Boca Raton, Fla. : CRC Press, 2013
 Description
 Book — 1 online resource (xxxiii, 462 pages)
 Summary

 1. BlackScholes model
 2. Multivariate BlackScholes model
 3. Discussion of the BlackScholes model
 4. Measures of risk and performance
 5. Modeling interest rates
 6. Levy models
 7. Stochastic volatility models
 8. Copulas and applications
 9. Filtering
 10. Applications of filtering
 A. Probability distributions
 B. Estimation of parameters
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