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Index
Cover Page
Title Page
Copyright Page
Dedication Page
Contents
List of Figures
List of Tables
Preface
1 - Introduction
1.1 - The Random Walk and Efficient Markets
1.2 - The Current State of Efficient Markets
1.3 - Practical Implications
Part I
2 - Stock Market Prices Do not Follow Random Walks: Evidence from a Simple Specification Test
2.1 - The Specification Test
2.1.1 - Homoskedastic Increments
2.1.2 - Heteroskedastic Increments
2.2 - The Random Walk Hypothesis for Weekly Returns
2.2.1 - Results for Market Indexes
2.2.2 - Results for Size-Based Portfolios
2.2.3 - Results for Individual Securities
2.3 - Spurious Autocorrelation Induced by Nontrading
2.4 - The Mean-Reverting Alternative to the Random Walk
2.5 - Conclusion
Appendix A2: Proof of Theorems
3 - The Size and Power of the Variance Ratio Test in Finite Samples: A Monte Carlo Investigation
3.1 - Introduction
3.2 - The Variance Ratio Test
3.2.1 - The IID Gaussian Null Hypothesis
3.2.2 - The Heteroskedastic Null Hypothesis
3.2.3 - Variance Ratios and Autocorrelations
3.3 - Properties of the Test Statistic under the Null Hypotheses .
3.3.1 - The Gaussian IID Null Hypothesis
3.3.2 - A Heteroskedastic Null Hypothesis
3.4 - Power
3.4.1 - The Variance Ratio Test for Large q
3.4.2 - Power against a Stationary AR(1) Alternative
3.4.3 - Two Unit Root Alternatives to the Random Walk
3.5 - Conclusion
4 - An Econometric Analysis of Nonsynchronous Trading
4.1 - Introduction
4.2 - A Model of Nonsynchronous Trading
4.2.1 - Implications for Individual Returns
4.2.2 - Implications for Portfolio Returns
4.3 - Time Aggregation
4.4 - An Empirical Analysis of Nontrading
4.4.1 - Daily Nontrading Probabilities Implicit in Autocorrelations
4.4.2 - Nontrading and Index Autocorrelations
4.5 - Extensions and Generalizations
Appendix A4: Proof of Propositions
5 - When are Contrarian Profits Due to Stock Market Overreaction?
5.1 - Introduction
5.2 - A Summary of Recent Findings
5.3 - Analysis of Contrarian Profitability
5.3.1 - The Independently and Identically Distributed Benchmark
5.3.2 - Stock Market Overreaction and Fads
5.3.3 - Trading on White Noise and Lead-Lag Relations
5.3.4 - Lead-Lag Effects and Nonsynchronous Trading
5.3.5 - A Positively Dependent Common Factor and the Bid-Ask Spread
5.4 - An Empirical Appraisal of Overreaction
5.5 - Long Horizons versus Short Horizons
5.6 - Conclusion
Appendix A5
6 - Long-Term Memory in Stock Market Prices
6.1 - Introduction
6.2 - Long-Range versus Short-Range Dependence
6.2.1 - The Null Hypothesis
6.2.2 - Long-Range Dependent Alternatives
6.3 - The Rescaled Range Statistic
6.3.1 - The Modified R/S Statistic
6.3.2 - The Asymptotic Distribution of Qn
6.3.3 - The Relation between Qn and Qn
6.3.4 - The Behavior of Qn under Long Memory Alternatives
6.4 - R/S Analysis for Stock Market Returns
6.4.1 - The Evidence for Weekly and Monthly Returns
6.5 - Size and Power
6.5.1 - The Size of the R/S Test
6.5.2 - Power Against Fractionally-Differenced Alternatives
6.6 - Conclusion
Appendix A6: Proof of Theorems
Part II
7 - Multifactor Models Do not Explain Deviations from the CAPM
7.1 - Introduction
7.2 - Linear Pricing Models, Mean-Variance Analysis, and the Optimal Orthogonal Portfolio
7.3 - Squared Sharpe Measures
7.4 - Implications for Risk-Based versus Nonrisk-Based Alternatives
7.4.1 - Zero Intercept F-Test
7.4.2 - Testing Approach
7.4.3 - Estimation Approach
7.5 - Asymptotic Arbitrage in Finite Economies
7.6 - Conclusion
8 - Data-Snooping Biases in Tests of Financial Asset Pricing Models
8.1 - Quantifying Data-Snooping Biases with Induced Order Statistics
8.1.1 - Asymptotic Properties of Induced Order Statistics
8.1.2 - Biases of Tests Based on Individual Securities
8.1.3 - Biases of Tests Based on Portfolios of Securities
8.1.4 - Interpreting Data-Snooping Bias as Power
8.2 - Monte Carlo Results
8.2.1 - Simulation Results for θp
8.2.2 - Effects of Induced Ordering on F-Tests
8.2.3 - F-Tests with Cross-Sectional Dependence
8.3 - Two Empirical Examples
8.3.1 - Sorting by Beta
8.3.2 - Sorting by Size
8.4 - How the Data Get Snooped
8.5 - Conclusion
9 - Maximizing Predictability in the Stock and Bond Markets
9.1 - Introduction
9.2 - Motivation
9.2.1 - Predicting Factors vs. Predicting Returns
9.2.2 - Numerical Illustration
9.2.3 - Empirical Illustration
9.3 - Maximizing Predictability
9.3.1 - Maximally Predictable Portfolio
9.3.2 - Example: One-Factor Model
9.4 - An Empirical Implementation
9.4.1 - The Conditional Factors
9.4.2 - Estimating the Conditional-Factor Model
9.4.3 - Maximizing Predictability
9.4.4 - The Maximally Predictable Portfolios
9.5 - Statistical Inference for the Maximal R2
9.5.1 - Monte Carlo Analysis
9.6 - Three Out-of-Sample Measures of Predictability
9.6.1 - Naive vs. Conditional Forecasts
9.6.2 - Merton's Measure of Market Timing
9.6.3 - The Profitability of Predictability
9.7 - Conclusion
Part III
10 - An Ordered Probit Analysis of Transaction Stock Prices
10.1 - Introduction
10.2 - The Ordered Probit Model
10.2.1 - Other Models of Discreteness
10.2.2 - The Likelihood Function
10.3 - The Data
10.3.1 - Sample Statistics
10.4 - The Empirical Specification
10.5 - The Maximum Likelihood Estimates
10.5.1 - Diagnostics
10.5.2 - Endogeneity of ∆ tk and IBSk
10.6 - Applications
10.6.1 - Order-Flow Dependence
10.6.2 - Measuring Price Impact Per Unit Volume of Trade .
10.6.3 - Does Discreteness Matter?
10.7 - A Larger Sample
10.8 - Conclusion
11 - Index-Futures Arbitrage and the Behavior of Stock Index Futures Prices
11.1 - Arbitrage Strategies and the Behavior of Stock Index Futures Prices
11.1.1 - Forward Contracts on Stock Indexes (No Transaction Costs)
11.1.2 - The Impact of Transaction Costs
11.2 - Empirical Evidence
11.2.1 - Data
11.2.2 - Behavior of Futures and Index Series
11.2.3 - The Behavior of the Mispricing Series
11.2.4 - Path Dependence of Mispricing
11.3 - Conclusion
12 - Order Imbalances and Stock Price Movements on October 19 and 20, 1987
12.1 - Some Preliminaries
12.1.1 - The Source of the Data
12.1.2 - The Published Standard and Poor's Index
12.2 - The Constructed Indexes
12.3 - Buying and Selling Pressure
12.3.1 - A Measure of Order Imbalance
12.3.2 - Time-Series Results
12.3.3 - Cross-Sectional Results
12.3.4 - Return Reversals
12.4 - Conclusion
Appendix A12
Al2.1 - Index Levels
A12.2 - Fifteen-Minute Index Returns
References
Index
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