Details

Market Momentum


Market Momentum

Theory and Practice
The Wiley Finance Series 1. Aufl.

von: Stephen Satchell, Andrew Grant

61,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 15.09.2020
ISBN/EAN: 9781119599470
Sprache: englisch
Anzahl Seiten: 432

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Beschreibungen

<p><b>A one-of-a-kind reference guide covering the behavioral and statistical explanations for market momentum and the implementation of momentum trading strategies</b></p> <p><i>Market Momentum: Theory and Practice</i> 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.</p> <p>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. <i>Market Momentum </i>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.</p> <p>What type of book is <i>Market Momentum </i>and how does it serve a range of readers’ interests and needs?</p> <ul> <li>A holistic market momentum guide for industry professionals, asset managers, risk managers, firm managers, plus hedge fund and commodity trading advisors</li> <li>Advanced text to help graduate students in finance, economics, and mathematics further develop their funds management skills</li> <li>Useful resource for financial practitioners who want to implement momentum trading strategies</li> <li>Reference book providing behavioral and statistical explanations for market momentum</li> </ul> <p>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, <i>Market Momentum</i> offers a comprehensive approach to the topic, which makes it a valuable resource for both investment professionals and higher-level finance students.</p> The contributors address momentum theory and practice, while also offering trading strategies that practitioners can study.
<p>Contributors xvii</p> <p>Introduction xxiii</p> <p><b>Chapter 1 Behavioural Finance and Momentum 1</b></p> <p>1.1 Introduction 1</p> <p>1.2 The failure of risk-based explanations 3</p> <p>1.3 Behavioural models of momentum 3</p> <p>1.4 Slow information diffusion 5</p> <p>1.5 Patterns in information arrival 6</p> <p>1.6 The 52-week high and capital gains overhang 8</p> <p>1.7 Institutional trading and momentum profits 10</p> <p>1.8 Sentiment and momentum 11</p> <p>1.9 Discussion 12</p> <p><b>Chapter 2 A Taxonomy of Momentum Strategies 16</b></p> <p>2.1 Introduction 16</p> <p>2.2 Relative strength strategies 17</p> <p>2.3 Time-series momentum strategies 18</p> <p>2.4 Cross-sectional momentum strategies 20</p> <p>2.5 Cross-asset momentum 27</p> <p><b>Chapter 3 Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations 30</b></p> <p>3.1 Data Description 34</p> <p>3.2 Methodology 39</p> <p>3.3 Turnover Reduction 42</p> <p>3.4 The Recent Underperformance of Time-series Momentum Strategies and the Effect of Pairwise Correlations 52</p> <p>3.5 Trading Costs Implications 58</p> <p>3.6 Concluding Remarks 63</p> <p><b>Chapter 4 Risk and Return of Momentum in Developed Equity Markets 68</b></p> <p>4.1 Introduction 68</p> <p>4.2 Definition of momentum 69</p> <p>4.3 Simple factor portfolios 71</p> <p>4.4 Multifactor structure 73</p> <p>4.5 Pure factor portfolios 75</p> <p>4.6 Empirical results: momentum performance 76</p> <p>4.7 Empirical results: momentum risk 80</p> <p>4.8 Diversification benefits 83</p> <p>4.9 Summary 84</p> <p><b>Chapter 5 Momentum Across Asset Classes 86</b></p> <p>5.1 Measuring momentum 87</p> <p>5.2 Framework: equity momentum and corporate credit risk 87</p> <p>5.3 Empirical studies: momentum and credit risk 89</p> <p>5.4 Our research on equity momentum and bond returns 91</p> <p>5.5 Geographically bound assets 92</p> <p>5.6 Momentum in other illiquid assets 94</p> <p>5.7 Cross-asset class effects of commodities 95</p> <p>5.8 Momentum effects and taxable investors 95</p> <p>5.9 Active management and momentum effects 96</p> <p>5.10 Conclusions 98</p> <p><b>Chapter 6 Momentum in Momentum ETFs 103</b></p> <p>6.1 Introduction 103</p> <p>6.2 Why are momentum ETFs so popular? 104</p> <p>6.3 What is in a momentum ETF? 112</p> <p>6.4 Which factors drive active risk for momentum ETFs? 114</p> <p>6.5 From constrained to unconstrained strategies 117</p> <p>6.6 Conclusions 119</p> <p><b>Chapter 7 CTA Momentum 120</b></p> <p>7.1 Introduction 120</p> <p>7.2 Time-series momentum (TSM) 121</p> <p>7.3 Strategy return models 127</p> <p>7.4 Time-series momentum 131</p> <p>7.5 TSM meets CSM with two instruments 133</p> <p>7.6 Conclusions 135</p> <p>7.A.1 Appendix A: Correlation parameter restrictions 136</p> <p>7.A.2 Appendix B: Proofs of variances and covariance 138</p> <p><b>Chapter 8 Overreaction and Faint Praise – Short-Term Momentum in Contemporary Art 141</b></p> <p>8.1 Introduction 141</p> <p>8.2 Contemporary art market ecosystem 144</p> <p>8.3 ArtForecaster data 145</p> <p>8.4 Systematic forecasting strategies 149</p> <p>8.5 Conclusions 157</p> <p><b>Chapter 9 Volatility-Managed Momentum 160</b></p> <p>9.1 Introduction 160</p> <p>9.2 Data and momentum portfolio construction 161</p> <p>9.3 Volatility-managed momentum strategies 162</p> <p>9.4 Some potential practical issues 166</p> <p>9.5 The best volatility measure for momentum? 170</p> <p>9.6 Concluding remarks 172</p> <p><b>Chapter 10 Theoretical Analysis of the Fama-French Portfolios 174</b></p> <p>10.1 Introduction 174</p> <p>10.2 Strategies, notation and preliminaries 179</p> <p>10.3 Distribution of Fama-French factors 182</p> <p>10.4 Fama-French factors with sequential sorting 189</p> <p>10.5 Conclusion 194</p> <p>10.A.1 Proof of Lemma 1 194</p> <p>10.A.2 Proof of Theorem 3 195</p> <p>10.A.3 Proof of Theorem 4 196</p> <p><b>Chapter 11 Exploiting the Countercyclical Properties of Momentum and other Factor Premia – A Cross-Country Perspective 199</b></p> <p>11.1 Introduction 199</p> <p>11.2 Methodology 200</p> <p>11.3 Alternative investment strategies 206</p> <p>11.4 Quantifying the utility of risk premia strategies 211</p> <p>11.5 Summary and conclusions 215</p> <p><b>Chapter 12 Time-Series Variation in Factor Premia: The Influence of the Business Cycle 218</b></p> <p>12.1 Introduction 218</p> <p>12.2 Factors and factor rotation 219</p> <p>12.3 Factors and the business cycle 220</p> <p>12.4 Data and summary statistics 222</p> <p>12.5 Empirical results 224</p> <p>12.6 Conclusions 234</p> <p>12.A.1 Derivation of cash-flow news series 234</p> <p>12.A.2 US leading economic indicator and global risk appetite indicator 236</p> <p>12.A.3 Dynamic multifactor strategy: extension to other market segments and regions 236</p> <p><b>Chapter 13 Where Goes Momentum? 243</b></p> <p>13.1 Introduction 243</p> <p>13.2 Momentum strategies 245</p> <p>13.3 Data 246</p> <p>13.4 Method 247</p> <p>13.5 Results 252</p> <p>13.6 Risk-adjusted after-transaction costs performance of time-series and cross-sectional momentum strategies 260</p> <p>13.7 Conclusions 269</p> <p><b>Chapter 14 Time-Series Momentum in Credit: Machine Learning Approach 273</b></p> <p>14.1 Introduction 273</p> <p>14.2 The philosophy of artificial intelligence 274</p> <p>14.3 Vanilla time-series momentum 277</p> <p>14.4 Generalized linear models (GLM) – Lasso, Ridge and Elastic Net 280</p> <p>14.5 Determining optimal hyper-parameters via cross-validation 283</p> <p>14.6 Results: generalized linear models 284</p> <p>14.7 Random forests 284</p> <p>14.8 Neural networks 289</p> <p>14.9 Results and comments 291</p> <p>14.10 Conclusion 293</p> <p><b>Chapter 15 Momentum and Business Cycles 297</b></p> <p>15.1 Introduction 297</p> <p>15.2 Momentum, business cycles and realised market return 298</p> <p>15.3 Momentum and expected market risk premiums 301</p> <p>15.4 Momentum, overconfidence and sentiment 309</p> <p>15.5 Summary and conclusions 311</p> <p><b>Chapter 16 Momentum as a Fundamental Risk Factor 314</b></p> <p>16.1 Introduction 314</p> <p>16.2 Defining momentum as a strategy 316</p> <p>16.3 A new framework 318</p> <p>16.4 From realised returns to forecast returns 319</p> <p>16.5 Examining behaviour 319</p> <p>16.6 The momentum trader as a bystander 323</p> <p>16.7 Extending the model 325</p> <p>16.8 Short-term versus long-term investors 326</p> <p>16.9 The impact of the short-term investor 330</p> <p>16.10 The momentum risk premium 332</p> <p>16.11 The Apollo asset pricing model 334</p> <p>16.12 Momentum alpha 335</p> <p>16.13 Beta momentum 339</p> <p>16.14 Beta signal 340</p> <p>16.15 Momentum strategies 341</p> <p>16.16 Results 347</p> <p>16.17 Analysis of results 353</p> <p>16.18 Conclusions 355</p> <p><b>Chapter 17 Momentum, Value and Carry Commodity Factors for Multi-Asset Portfolios 359</b></p> <p>17.1 Introduction 359</p> <p>17.2 Methodology and key research questions 361</p> <p>17.3 Commodity factors – insights from the historical data 362</p> <p>17.4 Wealth accumulation strategies and rebalancing considerations 366</p> <p>17.5 Wealth decumulation strategies 373</p> <p>17.6 Long/short versus long only strategies 375</p> <p>17.7 Completion portfolios versus maximum Sharpe ratio portfolios 379</p> <p>17.8 Conclusions 380</p> <p>17.A.1 Momentum factor 381</p> <p>17.A.2 Carry factor 381</p> <p>17.A.3 Value factor 382</p> <p>17.A.4 From commodity factors to factor portfolios 383</p> <p>17.A.5 Factor construction 383</p> <p>Index 387</p>
<p><b>ANDREW GRANT</b> 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. <p><b>STEPHEN SATCHELL</b> 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.
<p><b>A THOROUGH, HOLISTIC INTRODUCTION TO A COVETED INVESTMENT STRATEGY</b> <p>Momentum investing is a topic of rigorous debate and endless study—with good reason. Returns on the order of 12% annually have been recorded by investors following short-to-medium-term market trends. Quantitative investment professionals and students of finance and economics require a solid understanding of the mechanisms underlying this fascinating strategy. <p><b>Written by top quants in business and academia, <i>Market Momentum</i> addresses key questions such as:</b> <ul> <b><li>What are the important momentum investment strategies across asset classes?</b></li> <b><li>What are the theoretical explanations of market momentum, from behavioural and mathematical viewpoints?</b></li> <b><li>How are risk and return structured in momentum investing?</b></li> <b><li>What have been the characteristics of effective real-world momentum portfolios?</b></li> <b><li>Which statistical techniques and machine-learning applications are suited to the strategy and in which markets?</b></li> </ul> <p><i>Market Momentum</i> goes well beyond the extant, practitioner-oriented literature to provide a thorough introduction to the strategy, incorporating the latest research to bring the subject fully up to date.

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