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Market Momentum: Theory and Practice is a thorough, how-to reference guide for a full range of financial professionals and students. It examines the behavioral and statistical causes of market momentum while also exploring the practical side of implementing related strategies.
The phenomenon of momentum in finance occurs when past high returns are followed by subsequent high returns, and past low returns are followed by subsequent low returns. Market Momentum provides a detailed introduction to the financial topic, while examining existing literature. Recent academic and practitioner research is included, offering a more up-to-date perspective.
What type of book is Market Momentum and how does it serve a range of readers' interests and needs?
* A holistic market momentum guide for industry professionals, asset managers, risk managers, firm managers, plus hedge fund and commodity trading advisors
* Advanced text to help graduate students in finance, economics, and mathematics further develop their funds management skills
* Useful resource for financial practitioners who want to implement momentum trading strategies
* Reference book providing behavioral and statistical explanations for market momentum
Due to claims that the phenomenon of momentum goes against the Efficient Markets Hypothesis, behavioral economists have studied the topic in-depth. However, many books published on the subject are written to provide advice on how to make money. In contrast, Market Momentum offers a comprehensive approach to the topic, which makes it a valuable resource for both investment professionals and higher-level finance students. The contributors address momentum theory and practice, while also offering trading strategies that practitioners can study.
Market Momentum: Theory and Practice is a thorough, how-to reference guide for a full range of financial professionals and students. It examines the behavioral and statistical causes of market momentum while also exploring the practical side of implementing related strategies.
The phenomenon of momentum in finance occurs when past high returns are followed by subsequent high returns, and past low returns are followed by subsequent low returns. Market Momentum provides a detailed introduction to the financial topic, while examining existing literature. Recent academic and practitioner research is included, offering a more up-to-date perspective.
What type of book is Market Momentum and how does it serve a range of readers' interests and needs?
* A holistic market momentum guide for industry professionals, asset managers, risk managers, firm managers, plus hedge fund and commodity trading advisors
* Advanced text to help graduate students in finance, economics, and mathematics further develop their funds management skills
* Useful resource for financial practitioners who want to implement momentum trading strategies
* Reference book providing behavioral and statistical explanations for market momentum
Due to claims that the phenomenon of momentum goes against the Efficient Markets Hypothesis, behavioral economists have studied the topic in-depth. However, many books published on the subject are written to provide advice on how to make money. In contrast, Market Momentum offers a comprehensive approach to the topic, which makes it a valuable resource for both investment professionals and higher-level finance students. The contributors address momentum theory and practice, while also offering trading strategies that practitioners can study.
ANDREW GRANT is a Senior Lecturer in Finance at the University of Sydney. His main areas of expertise are behavioural finance, individual investor decision making, and betting markets. He has also been engaged with industry in the Asia-Pacific region. Andrew is a frequent speaker at conferences and seminars.
STEPHEN SATCHELL is Fellow of Economics, Trinity College Cambridge, UK. He also works as an advisor to financial institutions and as a quantitative facilitator bringing clients together. Stephen lectures frequently at finance industry seminars and is on the committees for several leading quantitative research groups.
Contributors xvii
Introduction xxiii
Chapter 1 Behavioural Finance and Momentum 1
1.1 Introduction 1
1.2 The failure of risk-based explanations 3
1.3 Behavioural models of momentum 3
1.4 Slow information diffusion 5
1.5 Patterns in information arrival 6
1.6 The 52-week high and capital gains overhang 8
1.7 Institutional trading and momentum profits 10
1.8 Sentiment and momentum 11
1.9 Discussion 12
Chapter 2 A Taxonomy of Momentum Strategies 16
2.1 Introduction 16
2.2 Relative strength strategies 17
2.3 Time-series momentum strategies 18
2.4 Cross-sectional momentum strategies 20
2.5 Cross-asset momentum 27
Chapter 3 Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations 30
3.1 Data Description 34
3.2 Methodology 39
3.3 Turnover Reduction 42
3.4 The Recent Underperformance of Time-series Momentum Strategies and the Effect of Pairwise Correlations 52
3.5 Trading Costs Implications 58
3.6 Concluding Remarks 63
Chapter 4 Risk and Return of Momentum in Developed Equity Markets 68
4.1 Introduction 68
4.2 Definition of momentum 69
4.3 Simple factor portfolios 71
4.4 Multifactor structure 73
4.5 Pure factor portfolios 75
4.6 Empirical results: momentum performance 76
4.7 Empirical results: momentum risk 80
4.8 Diversification benefits 83
4.9 Summary 84
Chapter 5 Momentum Across Asset Classes 86
5.1 Measuring momentum 87
5.2 Framework: equity momentum and corporate credit risk 87
5.3 Empirical studies: momentum and credit risk 89
5.4 Our research on equity momentum and bond returns 91
5.5 Geographically bound assets 92
5.6 Momentum in other illiquid assets 94
5.7 Cross-asset class effects of commodities 95
5.8 Momentum effects and taxable investors 95
5.9 Active management and momentum effects 96
5.10 Conclusions 98
Chapter 6 Momentum in Momentum ETFs 103
6.1 Introduction 103
6.2 Why are momentum ETFs so popular? 104
6.3 What is in a momentum ETF? 112
6.4 Which factors drive active risk for momentum ETFs? 114
6.5 From constrained to unconstrained strategies 117
6.6 Conclusions 119
Chapter 7 CTA Momentum 120
7.1 Introduction 120
7.2 Time-series momentum (TSM) 121
7.3 Strategy return models 127
7.4 Time-series momentum 131
7.5 TSM meets CSM with two instruments 133
7.6 Conclusions 135
7.A.1 Appendix A: Correlation parameter restrictions 136
7.A.2 Appendix B: Proofs of variances and covariance 138
Chapter 8 Overreaction and Faint Praise - Short-Term Momentum in Contemporary Art 141
8.1 Introduction 141
8.2 Contemporary art market ecosystem 144
8.3 ArtForecaster data 145
8.4 Systematic forecasting strategies 149
8.5 Conclusions 157
Chapter 9 Volatility-Managed Momentum 160
9.1 Introduction 160
9.2 Data and momentum portfolio construction 161
9.3 Volatility-managed momentum strategies 162
9.4 Some potential practical issues 166
9.5 The best volatility measure for momentum? 170
9.6 Concluding remarks 172
Chapter 10 Theoretical Analysis of the Fama-French Portfolios 174
10.1 Introduction 174
10.2 Strategies, notation and preliminaries 179
10.3 Distribution of Fama-French factors 182
10.4 Fama-French factors with sequential sorting 189
10.5 Conclusion 194
10.A.1 Proof of Lemma 1 194
10.A.2 Proof of Theorem 3 195
10.A.3 Proof of Theorem 4 196
Chapter 11 Exploiting the Countercyclical Properties of Momentum and other Factor Premia - A Cross-Country Perspective 199
11.1 Introduction 199
11.2 Methodology 200
11.3 Alternative investment strategies 206
11.4 Quantifying the utility of risk premia strategies 211
11.5 Summary and conclusions 215
Chapter 12 Time-Series Variation in Factor Premia: The Influence of the Business Cycle 218
12.1 Introduction 218
12.2 Factors and factor rotation 219
12.3 Factors and the business cycle 220
12.4 Data and summary statistics 222
12.5 Empirical results 224
12.6 Conclusions 234
12.A.1 Derivation of cash-flow news series 234
12.A.2 US leading economic indicator and global risk appetite indicator 236
12.A.3 Dynamic multifactor strategy: extension to other market segments and regions 236
Chapter 13 Where Goes Momentum? 243
13.1 Introduction 243
13.2 Momentum strategies 245
13.3 Data 246
13.4 Method 247
13.5 Results 252
13.6 Risk-adjusted after-transaction costs performance of time-series and cross-sectional momentum strategies 260
13.7 Conclusions 269
Chapter 14 Time-Series Momentum in Credit: Machine Learning Approach 273
14.1 Introduction 273
14.2 The philosophy of artificial intelligence 274
14.3 Vanilla time-series momentum 277
14.4 Generalized linear models (GLM) - Lasso, Ridge and Elastic Net 280
14.5 Determining optimal hyper-parameters via cross-validation 283
14.6 Results: generalized linear models 284
14.7 Random forests 284
14.8 Neural networks 289
14.9 Results and comments 291
14.10 Conclusion 293
Chapter 15 Momentum and Business Cycles 297
15.1 Introduction 297
15.2 Momentum, business cycles and realised market return 298
15.3 Momentum and expected market risk premiums 301
15.4 Momentum, overconfidence and sentiment 309
15.5 Summary and conclusions 311
Chapter 16 Momentum as a Fundamental Risk Factor 314
16.1 Introduction 314
16.2 Defining momentum as a strategy 316
16.3 A new framework 318
16.4 From realised returns to forecast returns 319
16.5 Examining behaviour 319
16.6 The momentum trader as a bystander 323
16.7 Extending the model 325
16.8 Short-term versus long-term investors 326
16.9 The impact of the short-term investor 330
16.10 The momentum risk premium 332
16.11 The Apollo asset pricing model 334
16.12 Momentum alpha 335
16.13 Beta momentum 339
16.14 Beta signal 340
16.15 Momentum strategies 341
16.16 Results 347
16.17 Analysis of results 353
16.18 Conclusions 355
Chapter 17 Momentum, Value and Carry Commodity Factors for Multi-Asset Portfolios 359
17.1 Introduction 359
17.2 Methodology and key research questions 361
17.3 Commodity factors - insights from the historical data 362
17.4 Wealth accumulation strategies and rebalancing considerations 366
17.5 Wealth decumulation strategies 373
17.6 Long/short versus long only strategies 375
17.7 Completion portfolios versus maximum Sharpe ratio portfolios 379
17.8 Conclusions 380
17.A.1 Momentum factor 381
17.A.2 Carry factor 381
17.A.3 Value factor 382
17.A.4 From commodity factors to factor portfolios 383
17.A.5 Factor construction 383
Index 387
| Erscheinungsjahr: | 2020 |
|---|---|
| Fachbereich: | Betriebswirtschaft |
| Genre: | Importe, Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Buch |
| Inhalt: | 432 S. |
| ISBN-13: | 9781119599326 |
| ISBN-10: | 1119599326 |
| Sprache: | Englisch |
| Einband: | Gebunden |
| Autor: |
Satchell, Stephen
Grant, Andrew |
| Hersteller: | Wiley |
| Maße: | 247 x 173 x 34 mm |
| Von/Mit: | Stephen Satchell (u. a.) |
| Erscheinungsdatum: | 02.12.2020 |
| Gewicht: | 0,944 kg |
ANDREW GRANT is a Senior Lecturer in Finance at the University of Sydney. His main areas of expertise are behavioural finance, individual investor decision making, and betting markets. He has also been engaged with industry in the Asia-Pacific region. Andrew is a frequent speaker at conferences and seminars.
STEPHEN SATCHELL is Fellow of Economics, Trinity College Cambridge, UK. He also works as an advisor to financial institutions and as a quantitative facilitator bringing clients together. Stephen lectures frequently at finance industry seminars and is on the committees for several leading quantitative research groups.
Contributors xvii
Introduction xxiii
Chapter 1 Behavioural Finance and Momentum 1
1.1 Introduction 1
1.2 The failure of risk-based explanations 3
1.3 Behavioural models of momentum 3
1.4 Slow information diffusion 5
1.5 Patterns in information arrival 6
1.6 The 52-week high and capital gains overhang 8
1.7 Institutional trading and momentum profits 10
1.8 Sentiment and momentum 11
1.9 Discussion 12
Chapter 2 A Taxonomy of Momentum Strategies 16
2.1 Introduction 16
2.2 Relative strength strategies 17
2.3 Time-series momentum strategies 18
2.4 Cross-sectional momentum strategies 20
2.5 Cross-asset momentum 27
Chapter 3 Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations 30
3.1 Data Description 34
3.2 Methodology 39
3.3 Turnover Reduction 42
3.4 The Recent Underperformance of Time-series Momentum Strategies and the Effect of Pairwise Correlations 52
3.5 Trading Costs Implications 58
3.6 Concluding Remarks 63
Chapter 4 Risk and Return of Momentum in Developed Equity Markets 68
4.1 Introduction 68
4.2 Definition of momentum 69
4.3 Simple factor portfolios 71
4.4 Multifactor structure 73
4.5 Pure factor portfolios 75
4.6 Empirical results: momentum performance 76
4.7 Empirical results: momentum risk 80
4.8 Diversification benefits 83
4.9 Summary 84
Chapter 5 Momentum Across Asset Classes 86
5.1 Measuring momentum 87
5.2 Framework: equity momentum and corporate credit risk 87
5.3 Empirical studies: momentum and credit risk 89
5.4 Our research on equity momentum and bond returns 91
5.5 Geographically bound assets 92
5.6 Momentum in other illiquid assets 94
5.7 Cross-asset class effects of commodities 95
5.8 Momentum effects and taxable investors 95
5.9 Active management and momentum effects 96
5.10 Conclusions 98
Chapter 6 Momentum in Momentum ETFs 103
6.1 Introduction 103
6.2 Why are momentum ETFs so popular? 104
6.3 What is in a momentum ETF? 112
6.4 Which factors drive active risk for momentum ETFs? 114
6.5 From constrained to unconstrained strategies 117
6.6 Conclusions 119
Chapter 7 CTA Momentum 120
7.1 Introduction 120
7.2 Time-series momentum (TSM) 121
7.3 Strategy return models 127
7.4 Time-series momentum 131
7.5 TSM meets CSM with two instruments 133
7.6 Conclusions 135
7.A.1 Appendix A: Correlation parameter restrictions 136
7.A.2 Appendix B: Proofs of variances and covariance 138
Chapter 8 Overreaction and Faint Praise - Short-Term Momentum in Contemporary Art 141
8.1 Introduction 141
8.2 Contemporary art market ecosystem 144
8.3 ArtForecaster data 145
8.4 Systematic forecasting strategies 149
8.5 Conclusions 157
Chapter 9 Volatility-Managed Momentum 160
9.1 Introduction 160
9.2 Data and momentum portfolio construction 161
9.3 Volatility-managed momentum strategies 162
9.4 Some potential practical issues 166
9.5 The best volatility measure for momentum? 170
9.6 Concluding remarks 172
Chapter 10 Theoretical Analysis of the Fama-French Portfolios 174
10.1 Introduction 174
10.2 Strategies, notation and preliminaries 179
10.3 Distribution of Fama-French factors 182
10.4 Fama-French factors with sequential sorting 189
10.5 Conclusion 194
10.A.1 Proof of Lemma 1 194
10.A.2 Proof of Theorem 3 195
10.A.3 Proof of Theorem 4 196
Chapter 11 Exploiting the Countercyclical Properties of Momentum and other Factor Premia - A Cross-Country Perspective 199
11.1 Introduction 199
11.2 Methodology 200
11.3 Alternative investment strategies 206
11.4 Quantifying the utility of risk premia strategies 211
11.5 Summary and conclusions 215
Chapter 12 Time-Series Variation in Factor Premia: The Influence of the Business Cycle 218
12.1 Introduction 218
12.2 Factors and factor rotation 219
12.3 Factors and the business cycle 220
12.4 Data and summary statistics 222
12.5 Empirical results 224
12.6 Conclusions 234
12.A.1 Derivation of cash-flow news series 234
12.A.2 US leading economic indicator and global risk appetite indicator 236
12.A.3 Dynamic multifactor strategy: extension to other market segments and regions 236
Chapter 13 Where Goes Momentum? 243
13.1 Introduction 243
13.2 Momentum strategies 245
13.3 Data 246
13.4 Method 247
13.5 Results 252
13.6 Risk-adjusted after-transaction costs performance of time-series and cross-sectional momentum strategies 260
13.7 Conclusions 269
Chapter 14 Time-Series Momentum in Credit: Machine Learning Approach 273
14.1 Introduction 273
14.2 The philosophy of artificial intelligence 274
14.3 Vanilla time-series momentum 277
14.4 Generalized linear models (GLM) - Lasso, Ridge and Elastic Net 280
14.5 Determining optimal hyper-parameters via cross-validation 283
14.6 Results: generalized linear models 284
14.7 Random forests 284
14.8 Neural networks 289
14.9 Results and comments 291
14.10 Conclusion 293
Chapter 15 Momentum and Business Cycles 297
15.1 Introduction 297
15.2 Momentum, business cycles and realised market return 298
15.3 Momentum and expected market risk premiums 301
15.4 Momentum, overconfidence and sentiment 309
15.5 Summary and conclusions 311
Chapter 16 Momentum as a Fundamental Risk Factor 314
16.1 Introduction 314
16.2 Defining momentum as a strategy 316
16.3 A new framework 318
16.4 From realised returns to forecast returns 319
16.5 Examining behaviour 319
16.6 The momentum trader as a bystander 323
16.7 Extending the model 325
16.8 Short-term versus long-term investors 326
16.9 The impact of the short-term investor 330
16.10 The momentum risk premium 332
16.11 The Apollo asset pricing model 334
16.12 Momentum alpha 335
16.13 Beta momentum 339
16.14 Beta signal 340
16.15 Momentum strategies 341
16.16 Results 347
16.17 Analysis of results 353
16.18 Conclusions 355
Chapter 17 Momentum, Value and Carry Commodity Factors for Multi-Asset Portfolios 359
17.1 Introduction 359
17.2 Methodology and key research questions 361
17.3 Commodity factors - insights from the historical data 362
17.4 Wealth accumulation strategies and rebalancing considerations 366
17.5 Wealth decumulation strategies 373
17.6 Long/short versus long only strategies 375
17.7 Completion portfolios versus maximum Sharpe ratio portfolios 379
17.8 Conclusions 380
17.A.1 Momentum factor 381
17.A.2 Carry factor 381
17.A.3 Value factor 382
17.A.4 From commodity factors to factor portfolios 383
17.A.5 Factor construction 383
Index 387
| Erscheinungsjahr: | 2020 |
|---|---|
| Fachbereich: | Betriebswirtschaft |
| Genre: | Importe, Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Buch |
| Inhalt: | 432 S. |
| ISBN-13: | 9781119599326 |
| ISBN-10: | 1119599326 |
| Sprache: | Englisch |
| Einband: | Gebunden |
| Autor: |
Satchell, Stephen
Grant, Andrew |
| Hersteller: | Wiley |
| Maße: | 247 x 173 x 34 mm |
| Von/Mit: | Stephen Satchell (u. a.) |
| Erscheinungsdatum: | 02.12.2020 |
| Gewicht: | 0,944 kg |
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