A course on statistics for finance / 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 revi...
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Boca Raton, Fla. ; London :
CRC Press,
©2013.
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MARC
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| 100 | 1 | |a Sclove, Stanley L. | |
| 245 | 1 | 2 | |a A course on statistics for finance / |c Stanley L. Sclove. |
| 260 | |a Boca Raton, Fla. ; |a London : |b CRC Press, |c ©2013. | ||
| 300 | |a 1 online resource (xxvii, 245 pages) : |b illustrations | ||
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| 588 | 0 | |a Print version record. | |
| 504 | |a Includes bibliographical references. | ||
| 505 | 0 | |a 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; Two-Way Tables Stock Price Series and Rates of Return; Introduction; Sharpe Ratio; Value-at-Risk; 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. | |
| 505 | 0 | |a 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; Mean-Variance Portfolio Analysis; Introduction; Two Stocks; Three Stocks; m Stocks; m Stocks and a Risk-Free Asset; Value-at-Risk; Selling Short; Market Models and Beta Utility-Based Portfolio Analysis; Introduction; Single-Criterion Analysis TIME SERIES ANALYSIS; Introduction to Time Series Analysis; Introduction; Control Charts; Moving Averages; Need for Modeling; Trend, Seasonality, | |
| 505 | 0 | |a And Randomness; Models with Lagged Variables; Moving-Average 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. | |
| 520 | 3 | |a 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. | |
| 650 | 0 | |a Finance |x Statistical methods. | |
| 650 | 0 | |a Investment analysis |x Statistical methods. | |
| 650 | 7 | |a Finance |x Statistical methods |2 fast | |
| 650 | 7 | |a Investment analysis |x Statistical methods |2 fast | |
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