We propose a dynamic APT multi-factor model with time-varying volatility for currency, bond and stock returns for ten European countries over the period 1977-1997. We exploit the cross-sectional dimension of the model to construct world portfolios, which, when added to the original list of...

This article discusses the application of the EM algorithm to factor models with dynamic heteroscedasticity in the common factors. It demonstrates that the EM algorithm reduces the computational burden so much that researchers can estimate such models with many series. Two empirical applications...

The authors investigate whether the degree of autocorrelation shown by high frequency stock returns changes with volatility. This may result from nontrading effects, feedback trading strategies, or variable risk aversion. The authors' results indicate that when volatility is low, daily (and...

We show that the distribution of any portfolio whose components jointly follow a location-scale mixture of normals can be characterised solely by its mean, variance and skewness. Under this distributional assumption, we derive the mean-variance-skewness frontier in closed form, and show that it...

Regression and SDF approaches with centered or uncentered moments and symmetric or asymmetric normalizations are commonly used to empirically evaluate linear factor pricing models. We show that unlike two-step or iterated GMM procedures, single-step estimators such as continuously updated GMM...

We compare Semi-Nonparametric expansions of the Gamma distribution with alternative Laguerre expansions, showing that they substantially widen the range of feasible moments of positive random variables. Then, we combine those expansions with a component version of the Multiplicative Error Model...

We compare Semi-Nonparametric expansions of the Gamma distribution with alternative Laguerre expansions, showing that they substantially widen the range of feasible moments of positive random variables. Then, we combine those expansions with a component version of the Multiplicative Error Model...

We derive the likelihood function and score of factor models with dynamic heteroskedasticity, and the Kuhn-Tucker conditions defining the inequality restricted maximum likelihood estimators that guarantee a positive definite convariance matrix. We present three methods to compute the likelihood...

In this paper, I first provide a unifying approach to Mean-Variance analysis and Value at Risk, which highlights both their similarities and differences. Then I use it to explain how fund managers can take investment decisions within the well-known Mean-Variance allocation framework that satisfy...

We analyse the Generalised Hyperbolic distribution as a model for fat tails and asymmetries in multivariate conditionally heteroskedastic dynamic regression models. We provide a standardised version of this distribution, obtain analytical expressions for the log-likelihood score, and explain how...