A non-random walk down Wall Street /:
For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. C...
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| Main Authors: | , |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Princeton :
Princeton University Press,
2002.
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| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a sta. |
| Item Description: | Appendix A6: Proof of Theorems. |
| Physical Description: | 1 online resource (xxiii, 424 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 395-415) and index. |
| ISBN: | 9781400829095 1400829097 |
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| 100 | 1 | |a Lo, Andrew W. |q (Andrew Wen-Chuan), |e author. |0 http://id.loc.gov/authorities/names/no92001206 | |
| 245 | 1 | 2 | |a A non-random walk down Wall Street / |c Andrew W. Lo, A. Craig MacKinlay. |
| 264 | 1 | |a Princeton : |b Princeton University Press, |c 2002. | |
| 264 | 4 | |c ©1999 | |
| 300 | |a 1 online resource (xxiii, 424 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references (pages 395-415) and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover; Title Page; Copyright Page; Table of 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 SizeBased Portfolios; 2.2.3 Results for Individual Securities. | |
| 505 | 8 | |a 2.3 Spurious Autocorrelation Induced by Nontrading2.4 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. | |
| 505 | 8 | |a 3.4.1 The Variance Ratio Test for Large q3.4.2 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 Nontradin; 4.4.1 Daily Nontrading Probabilities Implicit in Autocorrelations; 4.4.2 Nontrading and Index Autocorrelations; 4.5 Extensions and Generalizations. | |
| 505 | 8 | |a Appendix A4: Proof of Propositions5. 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-Askspread; 5.4 An Empirical Appraisal of Overreaction; 5.5 Long Horizons Versus Short Horizons; 5.6 Conclusion; Appendix A5. | |
| 505 | 8 | |a 6. Long-Term Memory in Stock Market Prices6.1 Introduction; 6.2 Long-Rangeversus 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. | |
| 500 | |a Appendix A6: Proof of Theorems. | ||
| 520 | |a For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a sta. | ||
| 650 | 0 | |a Investments |x Mathematics. |0 http://id.loc.gov/authorities/subjects/sh85067719 | |
| 650 | 0 | |a Stocks |x Prices |x Mathematical models. | |
| 650 | 0 | |a Random walks (Mathematics) |0 http://id.loc.gov/authorities/subjects/sh85111357 | |
| 650 | 6 | |a Investissements |x Mathématiques. | |
| 650 | 6 | |a Actions (Titres de société) |x Prix |x Modèles mathématiques. | |
| 650 | 6 | |a Marches aléatoires (Mathématiques) | |
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| 700 | 1 | |a MacKinlay, Archie Craig, |d 1955- |e author. |0 http://id.loc.gov/authorities/names/n90703488 | |
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| author | Lo, Andrew W. (Andrew Wen-Chuan) MacKinlay, Archie Craig, 1955- |
| author_GND | http://id.loc.gov/authorities/names/no92001206 http://id.loc.gov/authorities/names/n90703488 |
| author_facet | Lo, Andrew W. (Andrew Wen-Chuan) MacKinlay, Archie Craig, 1955- |
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| contents | Cover; Title Page; Copyright Page; Table of 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 SizeBased Portfolios; 2.2.3 Results for Individual Securities. 2.3 Spurious Autocorrelation Induced by Nontrading2.4 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 q3.4.2 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 Nontradin; 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 Propositions5. 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-Askspread; 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 Prices6.1 Introduction; 6.2 Long-Rangeversus 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. |
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Craig MacKinlay.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Princeton :</subfield><subfield code="b">Princeton University Press,</subfield><subfield code="c">2002.</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©1999</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (xxiii, 424 pages) :</subfield><subfield code="b">illustrations</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references (pages 395-415) and index.</subfield></datafield><datafield tag="588" ind1="0" ind2=" "><subfield code="a">Print version record.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Cover; Title Page; Copyright Page; Table of 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 SizeBased Portfolios; 2.2.3 Results for Individual Securities.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">2.3 Spurious Autocorrelation Induced by Nontrading2.4 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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">3.4.1 The Variance Ratio Test for Large q3.4.2 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 Nontradin; 4.4.1 Daily Nontrading Probabilities Implicit in Autocorrelations; 4.4.2 Nontrading and Index Autocorrelations; 4.5 Extensions and Generalizations.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Appendix A4: Proof of Propositions5. 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-Askspread; 5.4 An Empirical Appraisal of Overreaction; 5.5 Long Horizons Versus Short Horizons; 5.6 Conclusion; Appendix A5.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">6. Long-Term Memory in Stock Market Prices6.1 Introduction; 6.2 Long-Rangeversus 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.</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Appendix A6: Proof of Theorems.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. 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| id | ZDB-4-EBA-ocn769342463 |
| illustrated | Illustrated |
| indexdate | 2025-04-11T08:37:31Z |
| institution | BVB |
| isbn | 9781400829095 1400829097 |
| language | English |
| oclc_num | 769342463 |
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| publishDate | 2002 |
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| publisher | Princeton University Press, |
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| spelling | Lo, Andrew W. (Andrew Wen-Chuan), author. http://id.loc.gov/authorities/names/no92001206 A non-random walk down Wall Street / Andrew W. Lo, A. Craig MacKinlay. Princeton : Princeton University Press, 2002. ©1999 1 online resource (xxiii, 424 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references (pages 395-415) and index. Print version record. Cover; Title Page; Copyright Page; Table of 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 SizeBased Portfolios; 2.2.3 Results for Individual Securities. 2.3 Spurious Autocorrelation Induced by Nontrading2.4 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 q3.4.2 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 Nontradin; 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 Propositions5. 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-Askspread; 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 Prices6.1 Introduction; 6.2 Long-Rangeversus 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. For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a sta. Investments Mathematics. http://id.loc.gov/authorities/subjects/sh85067719 Stocks Prices Mathematical models. Random walks (Mathematics) http://id.loc.gov/authorities/subjects/sh85111357 Investissements Mathématiques. Actions (Titres de société) Prix Modèles mathématiques. Marches aléatoires (Mathématiques) BUSINESS & ECONOMICS Investments & Securities Stocks. bisacsh BUSINESS & ECONOMICS Investments & Securities General. bisacsh Investments Mathematics fast Random walks (Mathematics) fast Stocks Prices Mathematical models fast MacKinlay, Archie Craig, 1955- author. http://id.loc.gov/authorities/names/n90703488 has work: A non-random walk down Wall Street (Text) https://id.oclc.org/worldcat/entity/E39PCFXwdYr9cPYTkyxp7JbjYd https://id.oclc.org/worldcat/ontology/hasWork Print version: Lo, Andrew W. (Andrew Wen-Chuan). Non-random walk down Wall Street. Princeton, N.J. : Princeton University Press, 2002 0691092567 (OCoLC)48110037 |
| spellingShingle | Lo, Andrew W. (Andrew Wen-Chuan) MacKinlay, Archie Craig, 1955- A non-random walk down Wall Street / Cover; Title Page; Copyright Page; Table of 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 SizeBased Portfolios; 2.2.3 Results for Individual Securities. 2.3 Spurious Autocorrelation Induced by Nontrading2.4 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 q3.4.2 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 Nontradin; 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 Propositions5. 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-Askspread; 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 Prices6.1 Introduction; 6.2 Long-Rangeversus 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. Investments Mathematics. http://id.loc.gov/authorities/subjects/sh85067719 Stocks Prices Mathematical models. Random walks (Mathematics) http://id.loc.gov/authorities/subjects/sh85111357 Investissements Mathématiques. Actions (Titres de société) Prix Modèles mathématiques. Marches aléatoires (Mathématiques) BUSINESS & ECONOMICS Investments & Securities Stocks. bisacsh BUSINESS & ECONOMICS Investments & Securities General. bisacsh Investments Mathematics fast Random walks (Mathematics) fast Stocks Prices Mathematical models fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85067719 http://id.loc.gov/authorities/subjects/sh85111357 |
| 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 | non random walk down wall street |
| topic | Investments Mathematics. http://id.loc.gov/authorities/subjects/sh85067719 Stocks Prices Mathematical models. Random walks (Mathematics) http://id.loc.gov/authorities/subjects/sh85111357 Investissements Mathématiques. Actions (Titres de société) Prix Modèles mathématiques. Marches aléatoires (Mathématiques) BUSINESS & ECONOMICS Investments & Securities Stocks. bisacsh BUSINESS & ECONOMICS Investments & Securities General. bisacsh Investments Mathematics fast Random walks (Mathematics) fast Stocks Prices Mathematical models fast |
| topic_facet | Investments Mathematics. Stocks Prices Mathematical models. Random walks (Mathematics) Investissements Mathématiques. Actions (Titres de société) Prix Modèles mathématiques. Marches aléatoires (Mathématiques) BUSINESS & ECONOMICS Investments & Securities Stocks. BUSINESS & ECONOMICS Investments & Securities General. Investments Mathematics Stocks Prices Mathematical models |
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