Description
Taylor & Francis Ltd A Course On Statistics For Finance 2013 Edition by Stanley L. Sclove
Taking a data-driven approach, A Course on Statistics for Finance presents statistical methods for financial investment analysis. The author introduces regression analysis, time series analysis, and multivariate analysis step by step using models and methods from finance.The book begins with a review of basic statistics, including descriptive statistics, kinds of variables, and types of data sets. It then discusses regression analysis in general terms and in terms of financial investment models, such as the capital asset pricing model and the Fama/French model. It also describes mean-variance portfolio analysis and concludes with a focus on time series analysis.Providing the connection between elementary statistics courses and quantitative finance courses, this text helps both existing and future quants improve their data analysis skills and better understand the modeling process. INTRODUCTORY CONCEPTS AND DEFINITIONS Review of Basic Statistics What Is Statistics?Characterizing DataMeasures of Central TendencyMeasures of VariabilityHigher Moments Summarizing DistributionsBivariate DataThree VariablesTwo-Way TablesStock Price Series and Rates of Return IntroductionSharpe RatioValue-at-RiskDistributions for RORsSeveral Stocks and Their Rates of Return Introduction Review of Covariance and Correlation Two StocksThree Stocksm StocksREGRESSION Simple Linear Regression; CAPM and Beta Introduction Simple Linear RegressionEstimationInference 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 InterceptMultiple Regression and Market Models Multiple Regression Models Market Models Models with Both Numerical and Dummy Explanatory VariablesModel BuildingPORTFOLIO ANALYSIS Mean-Variance Portfolio Analysis Introduction Two StocksThree Stocks m Stocks m Stocks and a Risk-Free Asset Value-at-RiskSelling Short Market Models and BetaUtility-Based Portfolio AnalysisIntroduction Single-Criterion AnalysisTIME SERIES ANALYSIS Introduction to Time Series Analysis Introduction Control Charts Moving AveragesNeed for Modeling Trend, Seasonality, and Randomness Models with Lagged VariablesMoving-Average ModelsIdentification of ARIMA ModelsSeasonal Data Dynamic Regression Models Simultaneous Equations ModelsRegime Switching Models Introduction Bull and Bear MarketsAppendix A: Vectors and MatricesAppendix B: Normal DistributionsAppendix C: Lagrange MultipliersAppendix D: Abbreviations and SymbolsIndexA Summary, Exercises, and Bibliography appear at the end of each chapter.