| Description |
1 online resource (x, 286 pages) : illustrations. |
| Physical Medium |
polychrome |
| Description |
text file |
| Series |
Quantitative finance series
|
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Quantitative finance series.
|
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Cover -- Contents -- List of contributors -- Introduction -- Chapter 1 Market efficiency and forecasting -- 1.1 Introduction -- 1.2 A modern view of market efficiency and predictability -- 1.3 Weak-form predictability -- 1.4 Semi-strong form predictability -- 1.5 Methodological issues -- 1.6 Perspective -- 1.7 Conclusion -- References -- Chapter 2 A step-by-step guide to the Black-Litterman model -- 2.1 Introduction -- 2.2 Expected returns -- 2.3 The Black-Litterman model -- 2.4 A new method for incorporating user-specified confidence levels -- 2.5 Conclusion -- References -- Chapter 3 A demystification of the Black-Litterman model: managing quantitative and traditional portfolio construction -- 3.1 Introduction -- 3.2 Workings of the model -- 3.3 Examples -- 3.4 Alternative formulations -- 3.5 Conclusion -- Appendix -- References -- Chapter 4 Optimal portfolios from ordering information -- 4.1 Introduction -- 4.2 Efficient portfolios -- 4.3 Optimal portfolios -- 4.4 A variety of sorts -- 4.5 Empirical tests -- 4.6 Conclusion -- Appendix A -- Appendix B -- References -- Chapter 5 Some choices in forecast construction -- 5.1 Introduction -- 5.2 Linear factor models -- 5.3 Approximating risk with a mixture of normals -- 5.4 Practical problems in the model-building process -- 5.5 Optimization with non-normal return expectations -- 5.6 Conclusion -- References -- Chapter 6 Bayesian analysis of the Black-Scholes option price -- 6.1 Introduction -- 6.2 Derivation of the prior and posterior densities -- 6.3 Numerical evaluation -- 6.4 Results -- 6.5 Concluding remarks and issues for further research -- Appendix -- References -- Chapter 7 Bayesian forecasting of options prices: a natural framework for pooling historical and implied volatility information -- 7.1 Introduction -- 7.2 A classical framework for option pricing -- 7.3 A Bayesian framework for option pricing -- 7.4 Empirical implementation -- 7.5 Conclusion -- Appendix -- References -- Chapter 8 Robust optimization for utilizing forecasted returns in institutional investment -- 8.1 Introduction -- 8.2 Notions of robustness -- 8.3 Case study: an implementation of robustness via forecast errors and quadratic constraints -- 8.4 Extensions to the theory -- 8.5 Conclusion -- References -- Chapter 9 Cross-sectional stock returns in the UK market: the role of liquidity risk -- 9.1 Introduction -- 9.2 Hypotheses and calculating factors -- 9.3 Empirical results -- 9.4 Conclusions -- References -- Chapter 10 The information horizon -- optimal holding period, strategy aggression and model combination in a multi-horizon framework -- 10.1 The information coefficient and information decay -- 10.2 Returns and information decay in the single model case -- 10.3 Model combination -- 10.4 Information decay in models -- 10.5 Models -- optimal horizon, aggression and model combination -- Reference -- Chapter 11 Optimal forecasting horizon for skilled investo. |
| Summary |
Dr Stephen Satchell brings together a collection of leading thinkers from around the world to address this complex and central challenge in portfolio management. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Stock price forecasting.
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Stock price forecasting. |
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Stock price forecasting -- Mathematical models.
|
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Stock price forecasting -- Mathematical models. |
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Investment analysis.
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Investment analysis. |
| Genre/Form |
Electronic books.
|
| Added Author |
Satchell, Stephen, 1949-
|
| Other Form: |
Print version: Forecasting expected returns in the financial markets. Oxford : Elsevier/AP, 2007 9780750683210 075068321X (OCoLC)166314253 |
| ISBN |
9780080550671 (electronic book) |
|
0080550673 (electronic book) |
|
1281057657 |
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9781281057655 |
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075068321X (Cloth) |
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9780750683210 |
|
