1  20
Next
 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.
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(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.
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5. 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.
 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.
 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.
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8. Statistics and finance : an introduction [2004]
 Ruppert, David, 1948 author.
 New York : Springer, [2004]
 Description
 Book — 1 online resource (xx, 473 pages) : illustrations
 Summary

 Introduction. Probability and Statistical Models. Returns. Time Series Models. Portfolio Theory. Regression. The Capital Asset Pricing Model. Options Pricing. Fixed Income Securities. Resampling. ValueatRisk. GARCH models. Nonparametric Regression and Splines. Behavioral Finance.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 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
 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 
 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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(source: Nielsen Book Data)
12. 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.
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(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)
15. 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)
16. 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.
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(source: Nielsen Book Data)
 Lee, Cheng F.
 Dordrecht : Springer, 2012.
 Description
 Book — 1 online resource (1237 pages)
 Summary

 Introduction and Descriptive Statistics. Probability and Important Distributions. Statistical Inferences Based on Samples. Regression and Correlation: Relating Two or More Variables. Selected Topics in Statistical Analysis for Business and Economics. Appendices. Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
18. 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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(source: Nielsen Book Data)
 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.
20. 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.
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