Forecasting Expected Returns in the Financial Markets

Forecasting Expected Returns in the Financial Markets

by Stephen Satchell
Released August 2007
Publisher(s): Academic Press
ISBN: 9780080550671

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Book description

Forecasting returns is as important as forecasting volatility in multiple areas of finance. This topic, essential to practitioners, is also studied by academics. In this new book, Dr Stephen Satchell brings together a collection of leading thinkers and practitioners from around the world who address this complex problem using the latest quantitative techniques.

*Forecasting expected returns is an essential aspect of finance and highly technical
*The first collection of papers to present new and developing techniques
*International authors present both academic and practitioner perspectives

Table of contents

  1. Front Cover
  2. Forecasting Expected Returns in the Financial Markets
  3. Copyright Page
  4. Table of Contents
  5. List of contributors
  6. Introduction
  7. Chapter 1 Market efficiency and forecasting
    1. 1.1 Introduction
    2. 1.2 A modern view of market efficiency and predictability
    3. 1.3 Weak-form predictability
    4. 1.4 Semi-strong form predictability
    5. 1.5 Methodological issues
    6. 1.6 Perspective
    7. 1.7 Conclusion
    8. References
  8. Chapter 2 A step-by-step guide to the Black–Litterman model
    1. 2.1 Introduction
    2. 2.2 Expected returns
    3. 2.3 The Black–Litterman model (1/3)
    4. 2.3 The Black–Litterman model (2/3)
    5. 2.3 The Black–Litterman model (3/3)
    6. 2.4 A new method for incorporating user-specified confidence levels
    7. 2.5 Conclusion
    8. References
  9. Chapter 3 A demystification of the Black–Litterman model: managing quantitative and traditional portfolio construction
    1. 3.1 Introduction
    2. 3.2 Workings of the model
    3. 3.3 Examples
    4. 3.4 Alternative formulations
    5. 3.5 Conclusion
    6. Appendix
    7. References
  10. Chapter 4 Optimal portfolios from ordering information
    1. 4.1 Introduction
    2. 4.2 Efficient portfolios (1/3)
    3. 4.2 Efficient portfolios (2/3)
    4. 4.2 Efficient portfolios (3/3)
    5. 4.3 Optimal portfolios (1/2)
    6. 4.3 Optimal portfolios (2/2)
    7. 4.4 A variety of sorts
    8. 4.5 Empirical tests (1/3)
    9. 4.5 Empirical tests (2/3)
    10. 4.5 Empirical tests (3/3)
    11. 4.6 Conclusion
    12. Appendix A
    13. Appendix B
    14. References
  11. Chapter 5 Some choices in forecast construction
    1. 5.1 Introduction
    2. 5.2 Linear factor models
    3. 5.3 Approximating risk with a mixture of normals
    4. 5.4 Practical problems in the model-building process
    5. 5.5 Optimization with non-normal return expectations
    6. 5.6 Conclusion
    7. References
  12. Chapter 6 Bayesian analysis of the Black–Scholes option price
    1. 6.1 Introduction
    2. 6.2 Derivation of the prior and posterior densities (1/3)
    3. 6.2 Derivation of the prior and posterior densities (2/3)
    4. 6.2 Derivation of the prior and posterior densities (3/3)
    5. 6.3 Numerical evaluation
    6. 6.4 Results (1/2)
    7. 6.4 Results (2/2)
    8. 6.5 Concluding remarks and issues for further research
    9. Appendix (1/2)
    10. Appendix (2/2)
    11. References
  13. Chapter 7 Bayesian forecasting of options prices: a natural framework for pooling historical and implied volatility information
    1. 7.1 Introduction
    2. 7.2 A classical framework for option pricing
    3. 7.3 A Bayesian framework for option pricing (1/2)
    4. 7.3 A Bayesian framework for option pricing (2/2)
    5. 7.4 Empirical implementation (1/2)
    6. 7.4 Empirical implementation (2/2)
    7. 7.5 Conclusion
    8. Appendix
    9. References
  14. Chapter 8 Robust optimization for utilizing forecasted returns in institutional investment
    1. 8.1 Introduction
    2. 8.2 Notions of robustness
    3. 8.3 Case study: an implementation of robustness via forecast errors and quadratic constraints
    4. 8.4 Extensions to the theory
    5. 8.5 Conclusion
    6. References
  15. Chapter 9 Cross-sectional stock returns in the UK market: the role of liquidity risk
    1. 9.1 Introduction
    2. 9.2 Hypotheses and calculating factors
    3. 9.3 Empirical results (1/3)
    4. 9.3 Empirical results (2/3)
    5. 9.3 Empirical results (3/3)
    6. 9.4 Conclusions
    7. References
  16. Chapter 10 The information horizon – optimal holding period, strategy aggression and model combination in a multi-horizon framework
    1. 10.1 The information coefficient and information decay
    2. 10.2 Returns and information decay in the single model case
    3. 10.3 Model combination
    4. 10.4 Information decay in models
    5. 10.5 Models – optimal horizon, aggression and model combination
    6. Reference
  17. Chapter 11 Optimal forecasting horizon for skilled investors
    1. 11.1 Introduction
    2. 11.2 Analysis of the single model problem
    3. 11.3 Closed-form solutions
    4. 11.4 Multi-model horizon framework
    5. 11.5 An alternative formulation of the multi-model problem
    6. 11.6 Conclusions
    7. Appendix A
    8. Appendix B
    9. References
  18. Chapter 12 Investments as bets in the binomial asset pricing model
    1. 12.1 Introduction
    2. 12.2 Actual versus risk-neutral probabilities
    3. 12.3 Replicating investments with bets
    4. 12.4 Log optimal (Kelly) betting
    5. 12.5 Replicating Kelly bets with puts and calls
    6. 12.6 Options on Kelly bets
    7. 12.7 Conclusion
    8. References
  19. Chapter 13 The hidden binomial economy and the role of forecasts in determining prices
    1. 13.1 Introduction
    2. 13.2 General set-up
    3. 13.3 Power utility
    4. 13.4 Exponential utility, loss aversion and mixed equilibria
    5. 13.5 Conclusions
    6. Appendix
    7. References
  20. Index (1/2)
  21. Index (2/2)

Product information

  • Title: Forecasting Expected Returns in the Financial Markets
  • Author(s): Stephen Satchell
  • Release date: August 2007
  • Publisher(s): Academic Press
  • ISBN: 9780080550671