Empirical Asset Pricing: The Cross Section of Stock Returns by Bali, Turan G.

Description: "Bali, Engle, and Murray have produced a highly accessible introduction to the techniques and evidence of modern empirical asset pricing. This book should be read and absorbed by every serious student of the field, academic and professional." Eugene Fama, Robert R. McCormick Distinguished Service Professor of Finance, University of Chicago and 2013 Nobel Laureate in Economic Sciences "The empirical analysis of the cross-section of stock returns is a monumental achievement of half a century of finance research. Both the established facts and the methods used to discover them have subtle complexities that can mislead casual observers and novice researchers. Bali, Engle, and Murray's clear and careful guide to these issues provides a firm foundation for future discoveries." John Campbell, Morton L. and Carole S. Olshan Professor of Economics, Harvard University "Bali, Engle, and Murray provide clear and accessible descriptions of many of the most important empirical techniques and results in asset pricing." Kenneth R. French, Roth Family Distinguished Professor of Finance, Tuck School of Business, Dartmouth College "This exciting new book presents a thorough review of what we know about the cross-section of stock returns. Given its comprehensive nature, systematic approach, and easy-to-understand language, the book is a valuable resource for any introductory PhD class in empirical asset pricing." Lubos Pastor, Charles P. McQuaid Professor of Finance, University of Chicago Empirical Asset Pricing: The Cross Section of Stock Returns is a comprehensive overview of the most important findings of empirical asset pricing research. The book begins with thorough expositions of the most prevalent econometric techniques with in-depth discussions of the implementation and interpretation of results illustrated through detailed examples. The second half of the book applies these techniques to demonstrate the most salient patterns observed in stock returns. The phenomena documented form the basis for a range of investment strategies as well as the foundations of contemporary empirical asset pricing research. Empirical Asset Pricing: The Cross Section of Stock Returns also includes: * Discussions on the driving forces behind the patterns observed in the stock market * An extensive set of results that serve as a reference for practitioners and academics alike * Numerous references to both contemporary and foundational research articles Empirical Asset Pricing: The Cross Section of Stock Returns is an ideal textbook for graduate-level courses in asset pricing and portfolio management. The book is also an indispensable reference for researchers and practitioners in finance and economics. Turan G. Bali, PhD, is the Robert Parker Chair Professor of Finance in the McDonough School of Business at Georgetown University. The recipient of the 2014 Jack Treynor prize, he is the coauthor of Mathematical Methods for Finance: Tools for Asset and Risk Management, also published by Wiley. Robert F. Engle, PhD, is the Michael Armellino Professor of Finance in the Stern School of Business at New York University. He is the 2003 Nobel Laureate in Economic Sciences, Director of the New York University Stern Volatility Institute, and co-founding President of the Society for Financial Econometrics. Scott Murray, PhD, is an Assistant Professor in the Department of Finance in the J. Mack Robinson College of Business at Georgia State University. He is the recipient of the 2014 Jack Treynor prize. Turan G. Bali, PhD, is the Robert Parker Chair Professor of Finance in the McDonough School of Business at Georgetown University. The recipient of the 2014 Jack Treynor prize, he is the coauthor of Mathematical Methods for Finance: Tools for Asset and Risk Management, also published by Wiley. Robert F. Engle, PhD, is the Michael Armellino Professor of Finance in the Stern School of Business at New York University. He is the 2003 Nobel Laureate in Economic Sciences, Director of the New York University Stern Volatility Institute, and co-founding President of the Society for Financial Econometrics. Scott Murray, PhD, is an Assistant Professor in the Department of Finance in the J. Mack Robinson College of Business at Georgia State University. He is the recipient of the 2014 Jack Treynor prize. PREFACE xv PART I STATISTICAL METHODOLOGIES 1 1 Preliminaries 3 1.1 Sample 3 1.2 Winsorization and Truncation 5 1.3 Newey and West (1987) Adjustment 6 1.4 Summary 8 References 8 2 Summary Statistics 9 2.1 Implementation 10 2.1.1 Periodic Cross-Sectional Summary Statistics 10 2.1.2 Average Cross-Sectional Summary Statistics 12 2.2 Presentation and Interpretation 12 2.3 Summary 16 3 Correlation 17 3.1 Implementation 18 3.1.1 Periodic Cross-Sectional Correlations 18 3.1.2 Average Cross-Sectional Correlations 19 3.2 Interpreting Correlations 20 3.3 Presenting Correlations 23 3.4 Summary 24 References 24 4 Persistence Analysis 25 4.1 Implementation 26 4.1.1 Periodic Cross-Sectional Persistence 26 4.1.2 Average Cross-Sectional Persistence 28 4.2 Interpreting Persistence 28 4.3 Presenting Persistence 31 4.4 Summary 32 References 32 5 Portfolio Analysis 33 5.1 Univariate Portfolio Analysis 34 5.1.1 Breakpoints 34 5.1.2 Portfolio Formation 37 5.1.3 Average Portfolio Values 39 5.1.4 Summarizing the Results 41 5.1.5 Interpreting the Results 43 5.1.6 Presenting the Results 45 5.1.7 Analyzing Returns 47 5.2 Bivariate Independent-Sort Analysis 52 5.2.1 Breakpoints 52 5.2.2 Portfolio Formation 54 5.2.3 Average Portfolio Values 57 5.2.4 Summarizing the Results 60 5.2.5 Interpreting the Results 64 5.2.6 Presenting the Results 66 5.3 Bivariate Dependent-Sort Analysis 71 5.3.1 Breakpoints 71 5.3.2 Portfolio Formation 74 5.3.3 Average Portfolio Values 76 5.3.4 Summarizing the Results 80 5.3.5 Interpreting the Results 80 5.3.6 Presenting the Results 81 5.4 Independent Versus Dependent Sort 85 5.5 Trivariate-Sort Analysis 87 5.6 Summary 87 References 88 6 Fama and Macbeth Regression Analysis 89 6.1 Implementation 90 6.1.1 Periodic Cross-Sectional Regressions 90 6.1.2 Average Cross-Sectional Regression Results 91 6.2 Interpreting FM Regressions 95 6.3 Presenting FM Regressions 98 6.4 Summary 99 References 99 PART II THE CROSS SECTION OF STOCK RETURNS 101 7 The CRSP Sample and Market Factor 103 7.1 The U.S. Stock Market 103 7.1.1 The CRSP U.S.-Based Common Stock Sample 104 7.1.2 Composition of the CRSP Sample 105 7.2 Stock Returns and Excess Returns 111 7.2.1 CRSP Sample (1963-2012) 115 7.3 The Market Factor 115 7.4 The CAPM Risk Model 120 7.5 Summary 120 References 121 8 Beta 122 8.1 Estimating Beta 123 8.2 Summary Statistics 126 8.3 Correlations 128 8.4 Persistence 129 8.5 Beta and Stock Returns 131 8.5.1 Portfolio Analysis 132 8.5.2 Fama-MacBeth Regression Analysis 140 8.6 Summary 143 References 144 9 The Size Effect 146 9.1 Calculating Market Capitalization 147 9.2 Summary Statistics 150 9.3 Correlations 152 9.4 Persistence 154 9.5 Size and Stock Returns 155 9.5.1 Univariate Portfolio Analysis 155 9.5.2 Bivariate Portfolio Analysis 162 9.5.3 Fama-MacBeth Regression Analysis 168 9.6 The Size Factor 171 9.7 Summary 173 References 174 10 The Value Premium 175 10.1 Calculating Book-to-Market Ratio 177 10.2 Summary Statistics 181 10.3 Correlations 183 10.4 Persistence 184 10.5 Book-to-Market Ratio and Stock Returns 185 10.5.1 Univariate Portfolio Analysis 185 10.5.2 Bivariate Portfolio Analysis 190 10.5.3 Fama-MacBeth Regression Analysis 198 10.6 The Value Factor 200 10.7 The Fama and French Three-Factor Model 202 10.8 Summary 203 References 203 11 The Momentum Effect 206 11.1 Measuring Momentum 207 11.2 Summary Statistics 208 11.3 Correlations 210 11.4 Momentum and Stock Returns 211 11.4.1 Univariate Portfolio Analysis 211 11.4.2 Bivariate Portfolio Analysis 220 11.4.3 Fama-MacBeth Regression Analysis 234 11.5 The Momentum Factor 236 11.6 The Fama French and Carhart Four-Factor Model 238 11.7 Summary 239 References 239 12 Short-Term Reversal 242 12.1 Measuring Short-Term Reversal 243 12.2 Summary Statistics 243 12.3 Correlations 243 12.4 Reversal and Stock Returns 244 12.4.1 Univariate Portfolio Analysis 244 12.4.2 Bivariate Portfolio Analyses 249 12.5 Fama-MacBeth Regressions 263 12.6 The Reversal Factor 268 12.7 Summary 270 References 271 13 Liquidity 272 13.1 Measuring Liquidity 274 13.2 Summary Statistics 276 13.3 Correlations 277 13.4 Persistence 280 13.5 Liquidity and Stock Returns 281 13.5.1 Univariate Portfolio Analysis 281 13.5.2 Bivariate Portfolio Analysis 288 13.5.3 Fama-MacBeth Regression Analysis 300 13.6 Liquidity Factors 308 13.6.1 Stock-Level Liquidity 309 13.6.2 Aggregate Liquidity 310 13.6.3 Liquidity Innovations 312 13.6.4 Traded Liquidity Factor 312 13.7 Summary 316 References 316 14 Skewness 319 14.1 Measuring Skewness 321 14.2 Summary Statistics 323 14.3 Correlations 326 14.3.1 Total Skewness 326 14.3.2 Co-Skewness 329 14.3.3 Idiosyncratic Skewness 330 14.3.4 Total Skewness Co-Skewness and Idiosyncratic Skewness 331 14.3.5 Skewness and Other Variables 333 14.4 Persistence 336 14.4.1 Total Skewness 336 14.4.2 Co-Skewness 338 14.4.3 Idiosyncratic Skewness 339 14.5 Skewness and Stock Returns 341 14.5.1 Univariate Portfolio Analysis 341 14.5.2 Fama-MacBeth Regressions 350 14.6 Summary 359 References 360 15 Idiosyncratic Volatility 363 15.1 Measuring Total Volatility 365 15.2 Measuring Idiosyncratic Volatility 366 15.3 Summary Statistics 367 15.4 Correlations 370 15.5 Persistence 380 15.6 Idiosyncratic Volatility and Stock Returns 381 15.6.1 Univariate Portfolio Analysis 382 15.6.2 Bivariate Portfolio Analysis 389 15.6.3 Fama-MacBeth Regression Analysis 402 15.6.4 Cumulative Returns of IdioVolFF,1M Portfolio 407 15.7 Summary 409 References 410 16 Liquid Samples 412 16.1 Samples 413 16.2 Summary Statistics 414 16.3 Correlations 418 16.3.1 CRSP Sample and Price Sample 418 16.3.2 Price Sample and Size Sample 420 16.4 Persistence 421 16.5 Expected Stock Returns 424 16.5.1 Univariate Portfolio Analysis 425 16.5.2 Fama-MacBeth Regression Analysis 435 16.6 Summary 438 References 439 17 Option-Implied Volatility 441 17.1 Options Sample 443 17.2 Option-Based Variables 444 17.2.1 Predictive Variables 444 17.2.2 Option Returns 447 17.2.3 Additional Notes 448 17.3 Summary Statistics 449 17.4 Correlations 451 17.5 Persistence 453 17.6 Stock Returns 455 17.6.1 IVolSpread IVolSkew and Vol1M . IVol 456 17.6.2 DeltaIVolC and DeltaIVolP 460 17.7 Option Returns 469 17.8 Summary 474 References 474 18 Other Stock Return Predictors 477 18.1 Asset Growth 478 18.2 Investor Sentiment 479 18.3 Investor Attention 481 18.4 Differences of Opinion 482 18.5 Profitability and Investment 482 18.6 Lottery Demand 483 References 484 INDEX 489

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