Bossaerts, Peter. 　著

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Preface ix 1. Principles of Asset-Pricing Theory Wherein we review thebasics of asset-pricing theory, starting from dynamic programming (pointingout some of the surprising simplifications when applied to portfolioanalysis), introducing the notion of equilibrium,and then narrowingeverything down to arrive at the Capital Asset-Pricing Model (CAPM). Theemphasis is on the features that the CAPM shares with virtually all otherasset-pricing models,namely, in equilibrium, prices are set so that expectedexcess returns are proportional to covariance with aggregate risk. 1.1Introduction 1 1.2 Stochastic Dynamic Programming 2 1.3 An Application to aSimple Investment-Consumption Problem 8 1.4 A Nontrivial Portfolio Problem10 1.5 Portfolio Separation 11 1.6 Toward the First Asset-Pricing Model 151.7 Consumption-Based Asset-Pricing Models 17 1.8 Asset-Pricing Theory: TheBottom Line 21 1.9 Arrow-Debreu Securities Pricing 22 1.10 Roll's Critique23 1.11 Time Nonseparable Preferences 24 1.12 Existence of Equilibrium 261.13 Price Discovery 28 Exercises 36 2. Empirical Methodology Empiricaltests of asset-pricing theory require the researcher to make auxiliaryassumptions that are not necessarily an integral part of the theory. Mostprominent is the assumption that ties ex-ante beliefs (which determineprices) to the ex-post frequencies of the payoffs, which has become known asthe efficient markets hypothesis (EMH). EMH dramatically simplifies empiricalmethodology. We review three important types of tests that it generated: (1)Tests of the mean-variance efficiency of benchmark portfolio(s);(2)stochastic Euler equation tests; and (3) variance bounds tests. 2.1Introduction 39 2.2 The Efficient Markets Hypothesis (EMH) 42 2.3Violations of the Stationarity Assumption 46 2.4 Inference in aNonstationary World 53 2.5 Testing the CAPM 55 2.5.1 A Linear Test 562.5.2 A Nonlinear Test 57 2.5.3 The Fama-MacBeth Procedure 58 2.5.4 Can OneCondition on Less than the Entire State Vector in Tests of the CAPM? 59 2.6Testing Consumption-Based Asset-Pricing Models 63 2.7 Diagnostics: VarianceBounds 66 Exercises 69 3. The Empirical Evidence in a Nutshell Ananthology of the extensive literature on tests of asset-pricing modelsenables us to form a fairly comprehensive image of the empirical evidence.Few would be encouraged by the results. 3.1 Introduction 71 3.2 EmpiricalEvidence on the CAPM 72 3.3 Hansen-Jagannathan Bounds 83 3.4 GMM Tests ofConsumption-Based Models 89 3.5 Cross-Sectional Tests 95 3.6 Conclusion 100Exercises 101 4. The Experimental Evidence But perhaps we are demandingtoo much from empirical studies of historical data from field markets. Whatabout the evidence from simple, purposely built experimental markets? Someprinciples emerge well and alive (e.g., the CAPM), others can be rejectedoutright (e.g., instantaneous equilibration). The lab also allows us todiscover things that are fundamental to economic theory but difficult todetect in historical data, such as the ranking of Arrow-Debreu securitiesprices. At the same time, we experience how hard it is to control beliefs.4.1 Introduction 103 4.2 A Typical Asset-Pricing Experiment 107 4.3Theoretical Predictions 110 4.4 Experimental Results 111 4.5 Announced andPerceived Uncertainty 116 4.6 The Scale of Experimentation 122 4.7 FormalTests 124 4.7.1 The CAPM 124 4.7.2 The Arrow-Debreu Model 126 4.8Conclusion 128 5. From EMH to Merely Efficient Learning Although weobviously do not yet understand how to extrapolate lab results to the giantand complex field markets, we can investigate whether our econometricmethodology has not been the cause of the empirical failure of asset-pricingtheory. The first suspect is EMH. The criticism will be constructive, bydemonstrating that EMH is unnecessarily strong: much of the simplicity of theEMH-based empirical methodology can be retained even if one cuts out the mostobjectionable part. We develop a new methodology for testing asset-pricingmodels that allows the market to hold mistaken expectations at times, butstill requires it to learn as under EMH. We will call it the hypothesis ofefficiently learning markets (ELM). 5.1 Introduction 131 5.2 BayesianLearning 137 5.3 Digital Option Prices under ELM 140 5.4 Limited LiabilitySecurity Prices under ELM 142 5.5 Revisiting an Earlier Example 147 5.6Conclusion 151 Exercises 152 6. Revisiting the Historical Record Armedwith new tools, we can revisit historical data. We investigate theaftermarket performance of almost five thousand U.S. initial public offerings(IPOs) in the period 1975-95. Although not perfect, we find far more supportfor the theory. The example suggests that we may want to substitute ELM forEMH in future studies of historical data from field markets. 6.1Introduction 153 6.2 U.S. IPO Aftermarket Performance 154 6.3 Conclusion162 References 163 Index 169