A non-random walk down Wall Street:
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Princeton, NJ [u.a.]
Princeton Univ. Pr.
2002
|
| Edition: | 5. print., and 1. paperback print. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXIII, 424 S. graph. Darst. |
| ISBN: | 9780691092560 0691092567 |
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MARC
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| 245 | 1 | 0 | |a A non-random walk down Wall Street |c Andrew W. Lo ; A. Craig MacKinlay |
| 250 | |a 5. print., and 1. paperback print. | ||
| 264 | 1 | |a Princeton, NJ [u.a.] |b Princeton Univ. Pr. |c 2002 | |
| 300 | |a XXIII, 424 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 650 | 4 | |a Random walks (Mathematics) | |
| 650 | 4 | |a Stocks - Prices - Mathematical models | |
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| 650 | 4 | |a prisfastsættelse | |
| 650 | 4 | |a random walk | |
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Record in the Search Index
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|---|---|
| adam_text | Titel: A non-random walk down Wall Street
Autor: Lo, Andrew W
Jahr: 2002
Contents
List of Figures xiii
List of Tables xv
Préface xxi
1 Introduction 3
1.1 The Random Walk and Efficient Markets.......... 4
1.2 The Current State of Efficient Markets........... 6
1.3 Practical Implications..................... 8
Parti 13
2 Stock Market Priées Do Not Follow Random Walks: Evidence from
a Simple Spécification Test 17
2.1 The Spécification Test.................... 19
2.1.1 Homoskedastic Incréments ............. 20
2.1.2 Heteroskedastic Incréments............. 24
2.2 The Random Walk Hypothesis for Weekly Returns..... 26
2.2.1 Results for Market Indexes.............. 27
2.2.2 Results for Size-Based Portfolios........... 30
2.2.3 Results for Individual Securities........... 32
2.3 Spurious Autocorrélation Induced by Nontrading..... 34
2.4 The Mean-Reverting Alternative to the Random Walk ... 38
2.5 Conclusion.......................... 39
Appendix A2: Proof of Theorems 41
vu
viii Contents
3 The Size and Power of the Variance Ratio Test in Finite Samples:
A Monte Carlo Investigation 47
3.1 Introduction ......................... 47
3.2 The Variance Ratio Test................... 49
3.2.1 The IID Gaussian Null Hypothesis.......... 49
3.2.2 The Heteroskedastic Null Hypothesis........ 52
3.2.3 Variance Ratios and Autocorrélations........ 54
3.3 Properties of the Test Statistic under the Null Hypothèses . 55
3.3.1 The Gaussian IID Null Hypothesis.......... 55
3.3.2 A Heteroskedastic Null Hypothesis......... 61
3.4 Power............................. 68
3.4.1 The Variance Ratio Test for Large q......... 69
3.4.2 Power against a StationaryAR(l) Alternative .... 70
3.4.3 Two Unit Root Alternatives to the Random Walk . . 73
3.5 Conclusion.......................... 81
4 An Econometric Analysis of Nonsynchronous Trading 85
4.1 Introduction ......................... 85
4.2 A Model of Nonsynchronous Trading............ 88
4.2.1 Implications for Individual Returns......... 90
4.2.2 Implications for Portfolio Returns.......... 93
4.3 Time Aggregation ...................... 95
4.4 An Empirical Analysis of Nontrading............ 99
4.4.1 Daily Nontrading Probabilities Implicit in Auto-
corrélations ....................... 101
4.4.2 Nontrading and Index Autocorrélations...... 104
4.5 Extensions and Generalizations............... 105
Appendix A4: Proof of Propositions 108
5 When Are Contrarian Profits Due to Stock Market Overreaction? 115
5.1 Introduction ......................... 115
5.2 A Summary of Récent Findings............... 118
5.3 Analysis of Contrarian Profitability............. 121
5.3.1 The Independendy and Identically Distributed Bench-
mark........................... 124
5.3.2 Stock Market Overreaction and Fads........ 124
5.3.3 Trading on White Noise and Lead-Lag Relations . 126
5.3.4 Lead-Lag Effects and Nonsynchronous Trading . . 127
5.3.5 A Positively Dépendent Common Factor and the
Bid-Ask Spread..................... 130
5.4 An Empirical Appraisal of Overreaction .......... 132
Contents ix
5.5 Long Horizons Versus Short Horizons........... 140
5.6 Conclusion.......................... 142
Appendix A5 143
6 Long-Term Memory in Stock Market Priées 147
6.1 Introduction ......................... 147
6.2 Long-Range Versus Short-Range Dependence....... 149
6.2.1 The Null Hypothesis................. 149
6.2.2 Long-Range Dépendent Alternatives........ 152
6.3 The Rescaled Range Statistic................. 155
6.3.1 The Modified R/S Statistic.............. 158
6.3.2 The Asymptotic Distribution ofJ??.......... 160
6.3.3 The Relation Between Q» and Q^.......... 161
6.3.4 The Behavior of Q^ Under Long Memory
Alternatives....................... 163
6.4 R/S Analysis for Stock Market Returns........... 165
6.4.1 The Evidence for Weekly and Monthly Returns . . . 166
6.5 Size and Power........................ 171
6.5.1 The Size of the R/S Test............... 171
6.5.2 Power Against Fractionally-Differenced Alternatives 174
6.6 Conclusion.......................... 179
Appendix A6: Proof of Theorems 181
Part II 185
7 Multifactor Models Do Not Explain Déviations from the CAPM 189
7.1 Introduction .......................... 189
7.2 Linear Pricing Models, Mean-Variance Analysis,
and the Optimal Orthogonal Portfolio............192
7.3 Squared Sharpe Measures.................. 195
7.4 Implications for Risk-Based Versus Nonrisk-Based
Alternatives...........................196
7.4.1 Zéro Intercept F-Test................. 197
7.4.2 Testing Approach................... 198
7.4.3 Estimation Approach................. 206
7.5 Asymptotic Arbitrage in Finite Economies......... 208
7.6 Conclusion.......................... 212
8 Data-Snooping Biases in Tests of Financial Asset Pricing Models 213
8.1 Quantifying Data-Snooping Biases With Induced Order
Statistics.............................215
8.1.1 Asymptotic Properties of Induced Order Statistics . 216
8.1.2 Biases of Tests Based on Individual Securities . . . . 219
x Contents
8.1.3 Biases of Tests Based on Portfolios of Securities . . 224
8.1.4 Interpreting Data-Snooping Bias as Power..... 228
8.2 Monte Carlo Results..................... 230
8.2.1 Simulation Results for Ôp............... 231
8.2.2 Effects of Induced Ordering on f-Tests....... 231
8.2.3 i^-Tests With Cross-Sectional Dependence...... 236
8.3 Two Empirical Examples................... 238
8.3.1 Sorting By Beta.................... 238
8.3.2 Sorting By Size .................... 240
8.4 How the Data Get Snooped................. 243
8.5 Conclusion.......................... 246
9 Maximizing Predictability in the Stock and Bond Markets 249
9.1 Introduction ......................... 249
9.2 Motivation........................... 252
9.2.1 Predicting Factors vs. Predicting Returns...... 252
9.2.2 Numerical Illustration ................ 254
9.2.3 Empirical Illustration................. 256
9.3 Maximizing Predictability.................. 257
9.3.1 Maximally Predictable Portfolio........... 258
9.3.2 Example: One-Factor Model............. 259
9.4 An Empirical Implementation................ 260
9.4.1 The Conditional Factors............... 261
9.4.2 Estimating the Conditional-Factor Model...... 262
9.4.3 Maximizing Predictability .............. 269
9.4.4 The Maximally Predictable Portfolios........ 271
9.5 Statistical Inference for the Maximal R2........... 273
9.5.1 Monte Carlo Analysis................. 273
9.6 Three Out-of-Sample Measures of Predictability...... 276
9.6.1 Naive vs. Conditional Forecasts ........... 276
9.6.2 Merton s Measure of Market Timing ........ 279
9.6.3 The Profitability of Predictability .......... 281
9.7 Conclusion.......................... 283
Part III 285
10 An Ordered Probit Analysis of Transaction Stock Prices 287
10.1 Introduction ......................... 287
10.2 The Ordered Probit Model ................. 290
10.2.1 Other Models of Discreteness............ 294
10.2.2 The Likelihood Function............... 294
10.3 The Data ........................... 295
10.3.1 Sample Statistics.................... 297
10.4 The Empirical Spécification................. 307
Contents xi
10.5 The Maximum Likelihood Estimâtes............ 310
10.5.1 Diagnostics ...................... 316
10.5.2 Endogeneity of Atk and IBSk............. 318
10.6 Applications.......................... 320
10.6.1 Order-Flow Dependence............... 321
10.6.2 Measuring Price Impact Per Unit Volume of Trade . 322
10.6.3 Does Discreteness Matter?.............. 331
10.7 A Larger Sample....................... 338
10.8 Conclusion.......................... 344
11 Index-Futures Arbitrage and the Behavior of Stock Index Futures
Priées 347
11.1 Arbitrage Stratégies and the Behavior of Stock Index
Futures Priées..........................348
11.1.1 Forward Contracta on Stock Indexes (No Transac-
tion Costs) ....................... 349
11.1.2 The Impact of Transaction Costs........... 350
11.2 Empirical Evidence...................... 352
11.2.1 Data.......................... 353
11.2.2 Behavior of Futures and Index Séries........ 354
11.2.3 The Behavior of the Mispricing Séries........ 360
11.2.4 Path Dependence ofMispricing........... 364
11.3 Conclusion.......................... 367
12 Order Imbalances and Stock Price Movements on October 19 and
20,1987 369
12.1 Some Preliminaries...................... 370
12.1.1 The Source of the Data................ 371
12.1.2 The Published Standard and Poor s Index..... 372
12.2 The Constructed Indexes .................. 373
12.3 Buying and Selling Pressure................. 378
12.3.1 A Measureof Order Imbalance........... 378
12.3.2 Time-Series Results.................. 380
12.3.3 Cross-Sectional Results................ 381
12.3.4 Return Reversais ................... 385
12.4 Conclusion.......................... 387
Appendix Al 2 389
A12.1 Index Levels.......................... 389
Al2.2 Fifteen-Minute Index Returns................ 393
Références 395
Index 417
|
| any_adam_object | 1 |
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| indexdate | 2024-07-09T19:13:13Z |
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| language | English |
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| physical | XXIII, 424 S. graph. Darst. |
| publishDate | 2002 |
| publishDateSearch | 2002 |
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| publisher | Princeton Univ. Pr. |
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| spelling | Lo, Andrew W. 1960- Verfasser (DE-588)124791433 aut A non-random walk down Wall Street Andrew W. Lo ; A. Craig MacKinlay 5. print., and 1. paperback print. Princeton, NJ [u.a.] Princeton Univ. Pr. 2002 XXIII, 424 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Random walks (Mathematics) Stocks - Prices - Mathematical models aktier prisfastsættelse random walk Irrfahrtsproblem (DE-588)4162442-7 gnd rswk-swf Aktienkurs (DE-588)4141736-7 gnd rswk-swf Aktienkurs (DE-588)4141736-7 s Irrfahrtsproblem (DE-588)4162442-7 s DE-604 MacKinlay, Archie Craig 1955- Verfasser (DE-588)124791476 aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010289779&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Lo, Andrew W. 1960- MacKinlay, Archie Craig 1955- A non-random walk down Wall Street Random walks (Mathematics) Stocks - Prices - Mathematical models aktier prisfastsættelse random walk Irrfahrtsproblem (DE-588)4162442-7 gnd Aktienkurs (DE-588)4141736-7 gnd |
| subject_GND | (DE-588)4162442-7 (DE-588)4141736-7 |
| title | A non-random walk down Wall Street |
| title_auth | A non-random walk down Wall Street |
| title_exact_search | A non-random walk down Wall Street |
| title_full | A non-random walk down Wall Street Andrew W. Lo ; A. Craig MacKinlay |
| title_fullStr | A non-random walk down Wall Street Andrew W. Lo ; A. Craig MacKinlay |
| title_full_unstemmed | A non-random walk down Wall Street Andrew W. Lo ; A. Craig MacKinlay |
| title_short | A non-random walk down Wall Street |
| title_sort | a non random walk down wall street |
| topic | Random walks (Mathematics) Stocks - Prices - Mathematical models aktier prisfastsættelse random walk Irrfahrtsproblem (DE-588)4162442-7 gnd Aktienkurs (DE-588)4141736-7 gnd |
| topic_facet | Random walks (Mathematics) Stocks - Prices - Mathematical models aktier prisfastsættelse random walk Irrfahrtsproblem Aktienkurs |
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