Linear Factor Models in Finance -- Contents -- List of contributors -- Introduction -- 1 Review of literature on multifactor asset pricing models -- 1.1 Theoretical reasons for existence of multiple factors -- 1.2 Empirical evidence of existence of multiple factors -- 1.3 Estimation of factor pricing models -- Bibliography -- 2 Estimating UK factor models using the multivariate skew normal distribution -- 2.1 Introduction -- 2.2 The multivariate skew normal distribution and some of its properties -- 2.3 Conditional distributions and factor models -- 2.4 Data model choice and estimation -- 2.5 Empirical study -- 2.5.1 Basic return statistics -- 2.5.2 Overall model fit -- 2.5.3 Comparison of parameter estimates -- 2.5.4 Skewness parameters -- 2.5.5 Tau and time-varying conditional variance -- 2.6 Conclusions -- Acknowledgement -- References -- 3 Misspecification in the linear pricing model -- 3.1 Introduction -- 3.2 Framework -- 3.2.1 Arbitrage Pricing Theory -- 3.2.2 Multivariate F test used in linear factor model -- 3.2.3 Average F test used in linear factor model -- 3.3 Distribution of the multivariate F test statistics under misspecification -- 3.3.1 Exclusion of a set of factors from estimation -- 3.3.2 Time-varying factor loadings -- 3.4 Simulation study -- 3.4.1 Design -- 3.4.2 Factors serially independent -- 3.4.3 Factors autocorrelated -- 3.4.4 Time-varying factor loadings -- 3.4.5 Simulation results -- 3.5 Conclusion -- Appendix: Proof of proposition 3.1 and proposition 3.2 -- 4 Bayesian estimation of risk premia in an APT context -- 4.1 Introduction -- 4.2 The general APT framework -- 4.2.1 The excess return generating process (when factors are traded portfolios) -- 4.2.2 The excess return generating process (when factors are macroeconomic variables or non-traded portfolios) -- 4.2.3 Obtaining the (K x 1) vector of risk premia l.

4.3 Introducing a Bayesian framework using a Minnesota prior (Litterman's prior) -- 4.3.1 Prior estimates of the risk premia -- 4.3.2 Posterior estimates of the risk premia -- 4.4 An empirical application -- 4.4.1 Data -- 4.4.2 Results -- 4.5 Conclusion -- References -- Appendix -- 5 Sharpe style analysis in the MSCI sector portfolios: a Monte Carlo integration approach -- 5.1 Introduction -- 5.2 Methodology -- 5.2.1 A Bayesian decision-theoretic approach -- 5.2.2 Estimation by Monte Carlo integration -- 5.3 Style analysis in the MSCI sector portfolios -- 5.4 Conclusions -- References -- 6 Implication of the method of portfolio formation on asset pricing tests -- 6.1 Introduction -- 6.2 Models -- 6.2.1 Asset pricing frameworks -- 6.2.2 Specifications to be tested -- 6.3 Implementation -- 6.3.1 Multivariate F test -- 6.3.2 Average F test -- 6.3.3 Stochastic discount factor using GMM with Hansen and Jagannathan distance -- 6.3.4 A look at the pricing errors under different tests -- 6.4 Variables construction and data sources -- 6.4.1 Data sources -- 6.4.2 Independent variables: excess market return, size return factor and book-to-market return factor -- 6.4.3 Dependent variables: size-sorted portfolios, beta-sorted portfolios and individual assets -- 6.5 Result and discussion -- 6.5.1 Formation of WT -- 6.5.2 Model 1 -- 6.5.3 Model 2 -- 6.5.4 Model 3 -- 6.6 Simulation -- 6.7 Conclusion and implication -- References -- 7 The small noise arbitrage pricing theory and its welfare implications -- 7.1 Introduction -- 7.2 -- 7.3 -- References -- List of symbols -- 8 Risk attribution in a global country-sector model -- 8.1 Introduction -- 8.2 Recent trends in the 'globalization' of equity markets -- 8.2.1 'Home bias' -- 8.2.2 The rise and rise of the multinational corporation -- 8.2.3 Increases in market concentration -- 8.3 Modelling country and sector risk.

8.4 The estimated country and sector indices -- 8.5 Stock and portfolio risk attribution -- 8.6 Conclusions -- 8.7 Further issues and applications -- 8.7.1 Accounting for currency risk -- 8.7.2 Additional applications for this research -- References -- Appendix A: A detailed description of the identifying restrictions -- Appendix B: The optimization algorithm -- Appendix C: Getting the hedge right -- 9 Predictability of fund of hedge fund returns using DynaPorte -- 9.1 Introduction -- 9.2 Literature review -- 9.3 Methodology and data -- 9.4 Empirical results -- 9.5 Discussion -- 9.6 Conclusion -- References -- 10 Estimating a combined linear factor model -- 10.1 Introduction -- 10.2 A combined linear factor model -- 10.3 An extended model -- 10.4 Model estimation -- 10.5 Conditional maximization -- 10.6 Heterogeneous errors -- 10.7 Estimating the extended model -- 10.8 Discussion -- 10.9 Some simulation evidence -- 10.10 Model extensions -- 10.11 Conclusion -- References -- 11 Attributing investment risk with a factor analytic model -- 11.1 Introduction -- 11.2 The case for factor analytic models -- 11.2.1 Types of linear factor model -- 11.2.2 Estimation issues -- 11.3 Attributing investment risk with a factor analytic model -- 11.3.1 Which attributes can we consider? -- 11.4 Valuation attributes -- 11.4.1 Which attributes should we consider? -- 11.4.2 Attributing risk with valuation attributes -- 11.5 Category attributes -- 11.5.1 Which categories should we consider? -- 11.5.2 Attributing risk with categories -- 11.6 Sensitivities to macroeconomic time series -- 11.6.1 Which time series should we consider? -- 11.6.2 Attributing risk with macroeconomic time series -- 11.7 Reporting risk - relative marginals -- 11.7.1 Case study: Analysis of a UK portfolio -- 11.8 Conclusion -- References -- Appendix.

12 Making covariance-based portfolio risk models sensitive to the rate at which markets reflect new information -- 12.1 Introduction -- 12.2 Review -- 12.3 Discussion -- 12.4 The model -- 12.5 A few examples -- 12.6 Conclusions -- References -- 13 Decomposing factor exposure for equity portfolios -- 13.1 Introduction -- 13.2 Risk decomposition: cross-sectional characteristics -- 13.3 Decomposition and misspecification in the cross-sectional model: a simple example -- 13.3.1 Industry classification projected onto factor exposures -- 13.3.2 Incorporating expected return information -- 13.4 Summary and discussion -- References -- Index.