Empirical Asset Pricing: The Cross Section of Stock Returns

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“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. 

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 ΔIVolC and ΔIVolP 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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