Empirical Asset Pricing
The Cross Section of Stock Returns
1. Edition April 2016
512 Pages, Hardcover
Wiley & Sons Ltd
Short Description
Written by two experts in the field (including a renowned Nobel Prize Laureate), this book represents an up-to-date compilation of empirical asset pricing theory and their techniques and application--keeping emphasis throughout on empirical research and findings. Covering topics such as the mean-variance portfolio theory, the capital asset pricing model, and the arbitrage pricing theory, this is an ideal text for courses on asset pricing as well as on portfolio/risk management/finance, stocks and bonds, and arbitrage
"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.
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
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.
