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...

We derive Lagrange multiplier and likelihood ratio specification tests for the null hypotheses of multivariate normal and Student-t innovations using the generalized hyperbolic distribution as our alternative hypothesis. We decompose the corresponding Lagrange multiplier-type tests into skewness...

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...

The factor GARCH model of Engle (1987) and the latent factor ARCH model of Diebold and Nerlove (1989) have become rather popular multivariate volatility parametriza-tions due to their parsimony, and the commonality in volatility movements across different financial series. Nevertheless, there is...

The authors attempt to account for the covariances between stock markets and to assess their integration. They estimate a factor model for sixteen national stock market returns whose volatility is induced by changing volatility in the factors. Unanticipated returns depend on innovations in...

The empirical objective of this study is to account for the time-variation the covariances between markets. Using data on sixteen national stock markets, we estimate a multivariate factor model in which the volatility of returns is induced by changing volatility in the orthogonal factors. Excess...

We derive the statistical properties of the SNP densities of Gallant and Nychka (1987). We show that these densities, which are always positive, are more flexible than truncated Gram-Charlier expansions with positivity restrictions. We use the SNP densities for financial derivatives valuation....