Handbook of the Equity Risk Premium docx

HANDBOOK OF THE
EQUITY RISK
PREMIUM
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HANDBOOKS
IN
FINANCE
Series Editor
WILLIAM T. ZIEMBA
Advisory Editors
KENNETH J. ARROW
GEORGE C. CONSTANTINIDES
B. ESPEN ECKBO
HARRY M. MARKOWITZ
ROBERT C. MERTON
STEWART C. MYERS
PAUL A. SAMUELSON
WILLIAM F. SHARPE
amsterdam • boston • heidelberg • london
new york • oxford • paris • san diego
san francisco • singapore • sydney • tokyo
HANDBOOK OF THE
EQUITY RISK
PREMIUM
By
Rajnish Mehra
amsterdam • boston • heidelberg • london
new york • oxford • paris • san diego
san francisco • singapore • sydney • tokyo
Elsevier

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First edition 2008
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Dedicated to my parents
to Jyoti and Ravi
to Neeru
and
to Chaitanya
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Contents

List of Contributors xvii
Preface xix
Introduction to the Series xxiii
1 The Equity Premium: ABCs 1
Rajnish Mehra (UCSB) and Edward C. Prescott (Arizona State)
1. Introduction 2
1.1. An Important Preliminary Issue 2
1.2. Data Sources 3
1.3. Estimates of the Equity Premium 6
1.4. Variation in the Equity Premium Over Time 9
2. Is the Equity Premium Due to a Premium for Bearing Non-Diversifiable Risk? 11
2.1. Standard Preferences 14
References 25
Appendix A 29
Appendix B 29
Appendix C 35
Appendix D 35
2 Risk-Based Explanations of the Equity Premium 37
John B. Donaldson (Columbia) and Rajnish Mehra (UCSB)
Introduction 39
1. Alternative Preference Structures 41
1.1. Preliminaries 41
1.2. Coincidence of Risk and Time Preferences in CRRA utility 44
1.3. Separating Risk and Time Preferences: Epstein–Zin and others 46
1.4. Variation in the CRRA and EIS 52
vii
viii Contents
1.5. Habit Formation 55
1.6. Behavioral Models 61
1.7. Beyond One Good and a Representative Agent 71

2. Production Economies 78
3. Disaster Events and Survivorship Bias 81
4. Market Incompleteness and Trading Frictions 86
4.1. Restricted Participation 86
5. Model Uncertainty 91
6. Concluding Comments 93
References 94
3 Non-Risk-based Explanations of the Equity Premium 101
Rajnish Mehra (UCSB) and Edward C. Prescott (Arizona State)
Introduction 102
1. The Inappropriateness of Using T-Bills as a Proxy for the Intertemporal
Marginal Rate of Substitution of Consumption 102
1.1. Liquidity 104
1.2. Transaction Balances 104
2. The Effect of Government Regulations and Rules 106
3. Taxes 107
4. Borrowing Constraints 110
5. The Impact of Agent Heterogeneity and Intermediation Costs 113
6. Concluding Comments 114
References 114
4 Equity Premia with Benchmark Levels of Consumption:
Closed-Form Results 117
Andrew B. Abel (Wharton)
1. Preferences 120
2. The Canonical Asset 126
2.1. The Price of the Canonical Asset 127
2.2. The Rate of Return on the Canonical Asset 129
3. Risk, Term, and Equity Premia 131
4. Log-Normality 134
5. Risk, Term, and Equity Premia Under Log-Normality with Consumption

Externalities and Without Habit Formation 135
6. Linear Approximations to Risk, Term, and Equity Premia 137
7. Second Moments 138
7.1. Linear Approximations to Second Moments 140
8. Correlation of Dividend-Price Ratio and the Rate of Return on Stock 142
8.1. Correlation of Dividend-Price Ratio and the Excess Rate of Return on Stock 144
Contents ix
9. Special Cases 146
9.1. Rational Expectations 146
9.2. Distorted Beliefs 151
10. Accuracy of Approximations 153
11. Summary 156
References 156
Discussion: Francisco Gomes (LBS) 158
1. Introduction 158
2. Preferences with Benchmark Levels of Consumption 159
3. Changing the “Benchmark Level” of the Explanation 161
3.1. Aggregate Moments 161
3.2. Micro-Economic Implications 162
3.3. Micro-Economic Foundations and Aggregation 163
4. Leverage, Correlation between Dividends and Consumption, and
distorted Beliefs 163
4.1. Levered Equity Claims and Correlation Between Dividends and
Consumption 163
4.2. Non-Rational Expectations 164
5. Final Remarks 165
References 165
5 Long-Run Risks and Risk Compensation in Equity Markets 167
Ravi Bansal (Duke)
1. Introduction 168

2. Long-Run Risks Model 170
2.1. Preferences and the Environment 170
2.2. Long-Run Growth Rate Risks 171
2.3. Long-Run Growth and Uncertainty Risks 174
2.4. Data and Model Implications 176
3. Cross-Sectional Implications 185
3.1. Value, Momentum, Size, and the Cross-Sectional Puzzle 185
4. Conclusion 191
References 191
Discussion: John C. Heaton (Chicago) 194
1. Summary 194
2. A Low-Frequency Component in Consumption? 194
3. Preferences 195
4. Returns and Long-Run Cash Flows 197
5. Conclusion 198
References 198
x Contents
6 The Loss Aversion/Narrow Framing Approach to the Equity Premium Puzzle 199
Nicholas Barberis (Yale) and Ming Huang (Cornell)
1. Introduction 201
2. Loss Aversion and Narrow Framing 203
3. The Equity Premium 207
3.1. Modeling Loss Aversion and Narrow Framing 207
3.2. Quantitative Implications 212
3.3. Attitudes to Large Monetary Gambles 216
3.4. Attitudes to Small Monetary Gambles 218
3.5. The Importance of Narrow Framing 220
4. Other Applications 224
5. Further Extensions 225
5.1. Dynamic Aspects of Loss Aversion 225

5.2. Other Forms of Narrow Framing 226
6. Conclusion and Future Directions 227
References 228
Discussion: Xavier Gabaix (New York) 230
1. Work Out More Systematically the Preferences of PT vs. EU
Investors—The “Equity Protection Puzzle” 230
2. Make Quantitative Predictions, Particularly About Equilibrium
Market Phenomena, Rather than Just about Individual Trading Behavior 232
3. Do a Version of the Model in Continuous Time 233
References 234
Discussion: Ravi Jagannathan (Northwestern) 235
7 Financial Markets and the Real Economy 237
John H. Cochrane (Chicago)
1. Introduction 239
1.1. Risk Premia 239
1.2. Who Cares? 242
1.3. The Mimicking Portfolio Theorem and the Division of Labor 243
2. Facts: Time Variation and Business Cycle Correlation of Expected Returns 244
2.1. Variation over Time 244
2.2. Variation Across Assets 245
2.3. Return Forecasts—Variation over Time 246
2.4. The Cross Section of Returns—Variation Across Assets 251
3. Equity Premium 257
3.1. Mehra and Prescott and the Puzzle 261
3.2. The Future of the Equity Premium 266
Contents xi
4. Consumption Models 267
4.1. Hansen and Singleton; Power Utility 267
4.2. New Utility Functions 270
4.3. Empirics with New Utility Functions 273

4.4. Consumption and Factor Models 286
5. Production, Investment, and General Equilibrium 290
5.1. “Production-Based Asset Pricing” 290
5.2. General Equilibrium 294
6. Labor Income and Idiosyncratic Risk 302
6.1. Labor and Outside Income 302
6.2. Idiosyncratic Risk, Stockholding, and Micro Data 307
7. Challenges for the Future 314
References 314
Appendix 322
Discussion: Lars Peter Hansen (Chicago) 326
References 329
8 Understanding the Equity Risk Premium Puzzle 331
George M. Constantinides (Chicago)
1. Introduction 332
2. Habit Persistence 337
3. Limited Stock Market Participation and Per Capita Consumption 345
4. Incomplete Markets and Idiosyncratic Income Shocks 349
5. Concluding Remarks 355
References 356
Discussion: Hanno Lustig (UCLA) 360
1. Introduction 360
1.1. Environment 361
1.2. Preferences and Endowments 361
2. Complete Markets 362
2.1. Equilibrium 363
2.2. Equity Premium Puzzle 364
3. Missing Markets 364
3.1. Equilibrium 365
3.2. Mankiw’s Recipe for Generating Risk Premia 365

3.3. Constantinides and Duffie 366
3.4. Independence of Idiosyncratic Shocks from Aggregate Conditions 368
4. Missing Markets and State-Dependent Solvency Constraints 370
4.1. Incomplete Markets 370
4.2. Complete Markets 371
xii Contents
5. Conclusion 372
References 372
A. Second-Order Taylor Expansion 373
B. Constantinides and Duffie 374
9 Cash Flow Risk, Discounting Risk, and the Equity Premium Puzzle 377
Gurdip Bakshi (Maryland) and Zhiwu Chen (Yale)
1. Introduction 379
2. Economic Determinants of Equity Premium 381
2.1. Cash Flow Process 381
2.2. The Discounting Process 382
2.3. Dynamics of the Market Portfolio 383
2.4. Dynamics of the Equity Premium 385
3. Time-Series Data on S&P500 EPS, EPS Growth, and the Interest Rate 387
4. Implications of the Model for Equity Premium 389
4.1. How Large Is the Interest-Rate Risk Premium? 389
4.2. Maximum-Likelihood Estimation of the (Physical) G
t
Process 391
4.3. Compensation for Cash Flow Risk and the Equity Premium 392
5. Concluding Remarks and Extensions 396
Appendix 398
References 400
Discussion: Vito D. Gala (LBS) 403
1. Discussion 403

1.1. Calibration and Estimation 404
1.2. Where Is the Equity Premium Puzzle? 405
References 407
Discussion: Lior Menzly (Proxima) 409
1. Introduction 410
2. The Model 410
2.1. Pricing Kernel 410
2.2. Cash Flow Process 411
2.3. The Model—Solutions 411
3. Calibration 412
3.1. Calibrating the Model 412
3.2. Estimation Results 412
4. Two-Stage Procedure—An Empirical Concern 412
5. Conclusion 414
References 414
Contents xiii
10 Distribution Risk and Equity Returns 415
Jean-Pierre Danthine (Lausanne), John B. Donaldson (Columbia), and Paolo Siconolfi
(Columbia)
1. Introduction 417
2. The Business Cycle and the Labor Market 418
2.1. The Stylized Facts of the Business Cycle 418
2.2. The Labor Market 421
3. The Model Economy 423
3.1. Workers 423
3.2. Shareholders 424
3.3. The Firm 425
3.4. Equilibrium 427
3.5. Numerical Procedures and Calibration 429
4. An Economy with Distribution Risk Only 430

5. Adding Aggregate Uncertainty 432
6. Comparative Dynamics and Welfare Assessment 436
6.1. Changes in the Correlation of Productivity and Distribution Shocks 437
6.2. Changes in Risk Aversion and the Conditional Mean Distribution Shock 438
6.3. Other Comparative Dynamic Tests 440
6.4. Welfare Considerations 441
6.5. Explaining the Market Value to National Income Ratio 442
7. Technology-Driven Variations in Factor Shares 443
8. Robustness 446
9. An Alternative Interpretation of the Sharing Mechanism 448
10. Related Literature 452
11. Concluding Comments 459
References 460
Discussion: Urban J. Jermann (Wharton) 463
References 466
11 The Worldwide Equity Premium: A Smaller Puzzle 467
Elroy Dimson (LBS), Paul Marsh (LBS), and Mike Stauhton (LBS)
1. Introduction 469
2. Prior Estimates of the Equity Premium 471
2.1. Expert Opinion 472
3. Long-Run International Data 474
3.1. The DMS Global Database: Composition and Start Date 475
3.2. The DMS Global Database: General Methodology and Guiding Principles 477
4. Long-Run Historical Rates of Return 479
4.1. Extremes of History 480
4.2. The Long-Run Perspective 483
xiv Contents
5. New Global Evidence on the Equity Premium 486
5.1. The Equity Premium Around the World 487
5.2. A Smaller Risk Premium 489

5.3. Survivorship of Markets 490
5.4. Survivorship Bias Is Negligible 492
6. Decomposing the Historical Equity Premium 493
6.1. Unanticipated Success 493
6.2. Decomposition of the Equity Premium 495
6.3. From the Past to the Future 497
7. Conclusion 500
References 501
Appendix 1: Decomposition of the Equity Premium 505
Appendix 2: Data Sources for the DMS Database 507
12 History and the Equity Risk Premium 515
William N. Goetzmann (Yale) and Roger G. Ibbotson (Yale)
1. Introduction 516
2. Historical Conception and Measurement of the Equity Risk Premium 517
3. Stocks, Bonds, Bills, and Inflation 521
4. History as Written by the Winners? 523
5. The Equity Premium Over the Very Long Term 524
6. Conclusion 527
References 528
Discussion: Stephen F. LeRoy (UCSB) 530
References 534
13 Can Heterogeneity, Undiversified Risk, and Trading Frictions Solve the
Equity Premium Puzzle 535
John C. Heaton (Chicago) and Deborah Lucas (Northwestern)
1. Introduction 537
2. Labor Income as Background Risk 539
2.1. Calibrating the Income Process 544
2.2. Adding Trading Frictions 547
3. Entrepreneurial Income as Background Risk 552
4. Limited Participation and Limited Diversification 555

5. Conclusions 556
References 556
Discussion: Kjetil Storesletten (U Oslo) 558
1. Introduction 558
2. Labor Income Risk 559
Contents xv
3. Transaction Costs 560
4. Concentrating Aggregate Risk on Fewer Hands 560
4.1. Entrepreneurial Risk 560
4.2. Limited Participation 561
5. Conclusion 562
References 563
14 Asset Prices and Intergenerational Risk Sharing: The Role of
Idiosyncratic Earnings Shocks 565
Kjetil Storesletten (U Oslo), Chris Telmer (CMU), and Amir Yaron (Wharton)
1. Introduction 567
2. An Analytical Example of the Constantinides–Duffie Model 569
2.1. Calibration of the Constantinides–Duffie Economy 570
2.2. Model Implications 571
3. Incorporating the Life Cycle 573
3.1. Calibration 576
4. Quantitative Results 577
4.1. Asset Pricing Implications 580
4.2. Sensitivity Analysis 581
5. Conclusions 581
References 584
A. Calibration Appendix 587
B. Asset Pricing 590
Discussion: Darrell Duffie (Stanford) 591
References 592

Index 593
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List of Contributors
Andrew B. Abel, Department of Finance, 2315 Steinberg Hall-Dietrich Hall, The
Wharton School, University of Pennsylvania, 3620 Locust Walk, Philadelphia, PA
19104-6367, USA
Gurdip Bakshi, Department of Finance, Smith School of Business, University of
Maryland, College Park, MD 20742, USA
Ravi Bansal, Fuqua School of Business, Duke University, 1 Towerview Drive, Durham,
NC 27708, USA
Nicholas Barberis, Yale School of Management, 135 Prospect Street, New Haven
CT 06511, USA
Zhiwu Chen, Yale School of Management, 135 Prospect Street, New Haven,
CT 06520, USA
John H. Cochrane, Graduate School of Business, University of Chicago, 5807
S. Woodlawn, Chicago IL 60637, USA
George M. Constantinides, Graduate School of Business, The University of Chicago,
5807 South Woodlawn Avenue, Chicago IL 60637, USA
Jean-Pierre Danthine, University of Lausanne, Bldg Extranef, Dorigny, CH-1015
Lausanne, Switzerland
Elroy Dimson, London Business School, Regents Park, London NW1 4SA, UK
John B. Donaldson, Graduate School of Business, Columbia University, 3022 Broad-
way, New York, NY 10027-6989, USA
Darrell Duffie, Graduate School of Business, Stanford University, 518 Memorial Way,
Stanford, CA 94305-5015, USA
Xavier Gabaix, Department of Finance, Stern School of Business, New York Univer-
sity, 44 West 4th Street, Suite 9-190, New York, NY 10012, USA
Vito Gala, London Business School, Regent’s Park, London, NW1 4SA, UK
xvii
xviii List of Contributors

William N. Goetzmann, Yale School of Management, 135 Prospect Street, New Haven,
CT 06511-3729, USA
Francisco Gomes, Department of Finance, London Business School, Regent’s Park,
London NW1 4SA, UK
Lars Peter Hansen, Department of Economics, University of Chicago, 1126 East 59th
St., Chicago, Illinois. 60637, USA
John C. Heaton, The University of Chicago, Graduate School of Business, 5807 South
Woodlawn Avenue, Chicago, IL 60637, USA
Ming Huang, Johnson Graduate School of Management, Cornell University, 319 Sage
Hall, Ithaca, NY 14853-6201, USA
Roger G. Ibbotson, Yale School of Management, 135 Prospect Street, New Haven, CT
06511-3729, USA
Ravi Jagannathan, Kellogg School of Management, Northwestern University, 2001
Sheridan Rd, Evanston, IL 60208, USA
Urban J. Jermann, Department of Finance, The Wharton School of the University of
Pennsylvania, 3620 Locust Walk, Philadelphia, PA 19104-6367, USA
Stephen F. LeRoy, Department of Economics, University of California, Santa Barbara,
CA 93106, USA
Deborah Lucas, Kellogg School of Management, 2001 Sheridan Rd, Evanston, IL
60208, USA
Hanno Lustig, Department of Economics, University of California at Los Angeles,
Bunche Hall 8357, Box 951477, Los Angeles, CA 90095-1477, USA
Paul Marsh, London Business School, Regents Park, London NW1 4SA, UK
Rajnish Mehra, Department of Economics, 3014 North Hall, University of California,
Santa Barbara, CA 93106-9210, USA
Lior Menzly, Director of Quantitative Research and Risk Management, Proxima Alfa
Investment (USA), 623 Fifth Ave, 14th Floor, New York, NY 10022, USA
Edward C. Prescott, Department of Economics, W. P. Carey School of Business,
Arizona State University, Tempe, AZ 85287-3806, USA
Paolo Siconolfi, Columbia Business School, 3022 Broadway, Uris Hall 820, New York,

NY 10027, USA
Mike Staunton, London Business School, Regents Park, London NW1 4SA, UK
Kjetil Storesletten, Department of Economics, University of Oslo, PO Box 1095
Blindern, N-0317 Oslo, Norway
Chris Telmer, Tepper School of Business, Carnegie Mellon University, Posner Hall,
Room 350, Tech and Frew Streets, Pittsburgh, PA 15213, USA
Amir Yaron, The Wharton School, University of Pennsylvania, 2325 Steinberg
Hall-Dietrich Hall, 3620 Locust Walk, Philadelphia, PA 19104-6367, USA
Preface
Historical data provide a wealth of evidence documenting that for more than a century,
U.S. stock returns have been considerably higher than the returns for Treasury bills.
The average annual real return (that is, the inflation-adjusted return) on the U.S. stock
market for the past 110 years has been about 7.9 percent. In the same period, the real
return on a relatively riskless security was a paltry 1.0 percent. The difference between
these two returns, 6.9 percentage points, is the equity premium.
The generally accepted tenet of the neoclassical paradigm has been that the observed
differences in the rates of return to financial assets, in particular, the large difference
between the average returns on corporate equity and T-bills, is a premium for bear-
ing non-diversifiable aggregate risk. What came as a surprise to many economists and
researchers in finance was the conclusion of a research paper that Edward Prescott and
I wrote in 1979. We found that stocks and bonds pay off in approximately the same
states of nature or economic scenarios and hence, they should command approximately
the same rate of return. The historical U.S. equity premium was an order of magnitude
greater than could be rationalized in the context of the standard neoclassical paradigm
of financial economics.
In fact, using standard theory to estimate risk-adjusted returns, we found that stocks
on average should command, at most, a 1 percent return premium over bills. Since, for
as long as we had reliable data, (about a hundred years), the mean premium on stocks
over bills was considerably and consistently higher, we realized that we had a puzzle on
our hands.

It took us six more years to convince a skeptical profession and for “The Equity
Premium: A Puzzle” to be published. I want to emphasize that the equity premium
puzzle is a quantitative puzzle; standard theory is consistent with our notion of risk
that, on average, stocks should return more than bonds. The puzzle cannot be dismissed
lightly because much of our economic intuition is based on the very class of models that
fall short so dramatically when confronted with financial data. It underscores the failure
of paradigms central to financial and economic modelling to capture the characteristic
that appears to make stocks comparatively riskier. Hence, the viability of using this
class of models for any quantitative assessment—for instance, to gauge the welfare
implications of alternative stabilization policies—is thrown open to question.
xix
xx Preface
Creative research emerges at the fault lines where theory confronts observations.
Over the past two decades, attempts to resolve the puzzle have become a major
research impetus in finance and economics. Several generalizations of key features of
the Mehra–Prescott (1985) model have been proposed to reconcile observation with
theory. Consequently, we have a deeper understanding of the role and importance of the
abstractions that contribute to the puzzle. While no single explanation has fully resolved
the anomaly, considerable progress has been made and the equity premium is a lesser
puzzle today than it was twenty years ago.
This Handbook brings together fourteen papers by key researchers that span the spec-
trum of research efforts to resolve the Equity Premium Puzzle. I designed this volume
to be a collection of essays by experts in the field, discussing their own work and con-
tribution to the Equity Premium literature. My motivation is to give the profession a
critical look at the subject through the eyes of the researchers that have made funda-
mental contributions to the field. Each essay is followed by an expert commentary. The
expository style is intended to make the material accessible to doctoral students and
beginning researchers in the field. In this spirit, individual chapters are self-contained
and can be read independently.
The three introductory chapters provide a summary and overview of research over

the past 20 years. The first chapter explains why the equity premium is a puzzle. Chapter
two is an extended survey of the risk-based explanations of the equity premium while
chapter three surveys non-risk based explanations. The remaining chapters are arranged
alphabetically by author. Each chapter has a descriptive title and an abstract. There is
little value added in summarizing them here.
This volume has taken the better part of four years to bring to press, as many essays
went through two rounds of refereeing. I am grateful to the anonymous referees for
their detailed comments, to the authors and discussants for their willingness to incor-
porate suggestions and for their diligence in adhering to our guidelines in preparing
their contributions to this volume. Thanks are due to Francisco Azeredo, Alok Khare
and Chaitanya Mehra, who contributed to this volume’s accessibility by reading and
critiquing the chapters from a student’s perspective.
Most of the papers were presented and discussed at “The Equity Premium Puzzle
Conference,” held in October 2005 at the University of California, Santa Barbara, to
commemorate the twentieth anniversary of the publication of “The Equity Premium:
A Puzzle.” The conference was sponsored by the Laboratory for Aggregate Economics
and Finance at UCSB and North Holland. I thank Finn Kydland, the director of LAEF,
Scott Bentley, the executive editor and David Clark, the publishing director at North
Holland for their generous support. Special thanks are due to Vijaisarath Parthasarathy,
at Elsevier, Chennai, where this issue was typeset, for the patience and grace with which
he handled the innumerable iterations involved in bringing this volume to press.
The equity premium puzzle has its genesis in the research program initiated by
Robert Lucas and Edward Prescott at Carnegie Mellon in the mid 70s, a program that
transformed dynamic economics. I was fortunate to have learned economics from them,
and to have witnessed that paradigmatic shift. I want to take this opportunity to express
my gratitude to both of them.
Preface xxi
With Ed Prescott, our association has evolved from his role as mentor to that of
co-author and colleague. The famous mathematician, Mark Kac, once made a distinc-
tion between two kinds of geniuses: the “ordinary” and the “magicians”. An ordinary

genius is a fellow that you and I would be just as good as, if we were only many times
better. It is different with magicians. The working of their minds is mysterious and
profound and even after we understand what they have done, the creative process by
which they have done it, is impossible to emulate. The last 30 odd years of collaborating
with Ed Prescott have convinced me that he is, truly, a magician.
It was at Carnegie too that I met John Donaldson and George Constantinides; over
the years, they have been generous with their time and advice and have served as a
sounding board for ideas. Both of them contributed immeasurably to this volume by
their meticulous reading of and comments on many of the papers collected here.
Finally, I thank my wife, Neeru, for editorial assistance. Her insightful comments and
recommendations reflect her passion for words, versatility of expression and command
of the language.
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Introduction to the Series
Advisory Editors:
Kenneth J. Arrow, Stanford University; George C. Constantinides, University of
Chicago; B. Espen Eckbo, Dartmouth College; Harry M. Markowitz, University of
California, San Diego; Robert C. Merton, Harvard University; Stewart C. Myers,
Massachusetts Institute of Technology; Paul A. Samuelson, Massachusetts Institute
of Technology; and William F. Sharpe, Stanford University.
The Handbooks in Finance are intended to be a definitive source for compre-
hensive and accessible information. Each volume in the series presents an accurate,
self-contained survey of a sub-field of finance, suitable for use by finance and economics
professors and lecturers, professional researchers, graduate students and as a teaching
supplement. The goal is to have a broad group of outstanding volumes in various areas
of finance.
William T. Ziemba
University of British Columbia
xxiii
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