A Non-Random Walk Down Wall Street-猫眼课题宝

DOI：

10.5860/choice.37-2272

发表时间：

1999

期刊：

影响因子：

通讯作者：

中科院分区：

其他

文献类型：

作者：

A. Lo;A. Mackinlay

表格列表序言清单1简介1.1随机步行和高效市场1.2当前有效市场的状态1.3实际意义1第I部分股票市场价格不遵循随机步行：简单规格测试2.1规范测试2.1的证据。 1同性恋增量2.1.2异性恋增量2.2每周收益的随机步行假设2.2.1市场索引的结果2.2.2基于尺寸的投资组合的结果2.2.3单个证券的结果2.3替代随机步行2.5结论附录A2：定理的证明3有限样本中方差比测试的大小和功率：蒙特卡洛研究3.1简介3.2方差比测试3.2.1 IID高斯无效假设3.2.2杂菌性无效假设3.2.3方差比和自相关3.3 null假设下测试统计量的特性3.3.1高斯IID无效假设3.3.2杂质无效的无效假设3.4功率3.4功率3.4.1大型Q 3.4.2的方差比测试对固定AR的功率（1）替代3.4.3随机步行3.5结论的两个单位根替代方案4非同步交易的计量经济分析4.1简介4.2非同步交易的模型4.2.1对单个收益的影响4.2.2对投资组合的影响4.2.2收益4.3时间汇总4.4非交易4.4.1每日非交易概率的经验分析在自相关中隐含的4.4.2非交易和索引自相关4.5扩展和概括附录A4：命题证明5何时是由于股票市场过度差异吗？ 5.1简介5.2最新发现的摘要5.3对逆势盈利能力的分析5.3.1独立和相同分布的基准5.3.2股票市场过度反应和FADS 5.3.3在白噪声和铅滞后关系5.3.4铅滞后效应和铅滞后效应5.3.3非同步交易5.3.5 5.3.5肯定依赖的共同因素和出价差异5.4对过度反应的经验评估5.5长距离与短范围5.6结论附录A5 6股票市场的长期记忆6.1简介6.2长期与短期和短期和短期 - 范围依赖性6.2.1零假设6.2.2远程依赖性替代方案6.3重新缩放范围统计量6.3.1修改后的R/S统计量6.3.2 QN 6.3.3的渐近分布Qn 6.3.3 Qn和[tilde] Qn之间的关系6.3.4长期内存替代方案QN的行为6.4 R/s股票市场的分析6.4.1每周和每月收益的证据6.5尺寸和功率6.5.1 R/S测试的大小6.5.2功率6.5.2电源分数差异的替代方案6.6结论附录A6：定理第II部分7多因素模型的证明不会解释CAPM 7.1简介7.2线性定价模型，均值差异分析和最佳正交投资组合和最佳正交投资组合7.4 Spare Spare-Spare Spare-7.4含义7.4含义7.4基于基于非风险的替代方案7.4.1零拦截F检验7.4.2测试方法7.4.3估计方法7.5有限经济体中的渐近套利7.6结论8在金融资产定价模型的测试中，数据解决偏见8.1量化数据 - 努力偏见的偏见具有诱导的订单统计8.1.1诱导顺序统计的渐近性能8.1.2基于单个证券的测试偏差8.1.3基于证券投资组合的测试偏差8.1.4将数据解决偏见解释为功率8.2 Monte Carlo Resultes 8.2。 1 [theta] p 8.2.2诱导排序对f检验的影响8.2.3 f检验的仿真结果具有横截面依赖性8.3两个经验示例8.3.1通过beta 8.3.2按大小8.4分类数据如何分类数据。侦听8.5结论9股票和债券市场的可预测性9.1简介9.2动机9.2.1预测因素与预测回报9.2.2数值插图9.2.3经验说明9.3最大化可预测性9.3.1最大可预测的投资组合9.3.2示例：9.3.2示例：9.3.2：单因素模型9.4经验实施9.4.1条件因子9.4.2估计条件因子模型9.4.3最大化可预测性9.4.4最大预测的投资组合9.5最大R2的统计推断最大R2 R2 9.5.1 Monte Carlo Anallysis 9.6 Thrime 9.6 Thrim可预测性的样本外9.6.1幼稚与条件预测9.6.2默顿的市场时机衡量标准9.6.3可预测性的盈利能力9.7结论第三部分第三部分交易股价的订购概率分析10.1简介10.2订购的概率10.2模型10.2.1其他离散度的模型10.2.2可能性函数10.3数据10.3.1样本统计10.4经验规范10.5最大似然估计10.5.1诊断10.5.2 [delta] TK和IBSK和IBSK的内生性性。 1订单流依赖性10.6.2测量每单位交易量的价格影响10.6.3离散性很重要吗？ 10.7较大的样本10.8结论11指数套件套利和股票指数期货价格的行为11.1套利策略和股票指数期货价格的行为11.1.1.1股票指数的远期合同（无交易成本）11.1.2交易的影响成本11.2经验证据11.2.1数据11.2.2期货和指数系列的行为11.2.3错误定价系列的行为11.2.4错误定价的路径依赖性11.3结论12阶订单不平衡和股票价格运动，1987年10月19日和20日12.1 12.1 12.1一些初步的12.1.1数据来源12.1.2已发表的标准和穷人指数12.2构造的索引12.3买卖压力12.3.1订单不平衡的量度不平衡12.3.2时间序列结果12.3.3.3.3.3.3.3.3.3.3.3.3.3 12.3.4返回反向12.4结论附录A12 A12.1索引级别A12.2 15分钟索引返回参考索引

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 [tilde]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 [theta]p 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 [Delta]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 A12.1 Index Levels A12.2 Fifteen-Minute Index Returns References Index

A Non-Random Walk Down Wall Street

文献摘要

被引文献

相似文献