We propose methods for testing hypothesis of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses...

In the standard consumption capital asset pricing model (CCAPM), the curvature of the investor's utility function captures two aspects of preferences: as the concavity of the function increases so does his aversion to risk as well as his desire to smooth consumption intertemporally. This...

In this paper, we characterize the asymmetries of the smile through multiple leverage effects in a stochastic dynamic asset pricing framework. The dependence between price movements and future volatility is introduced through a set of latent state variables. These latent variables can capture...

The risk-return trade-off being the very substance of finance, volatility has always been an essential parameter for portfolio management. Moreover, the generalization of the use of derivatives has placed in the forefront the concept of volatility risk: i.e. the model risk generated by treating...

Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time...

Financial risk model evaluation or backtesting is a key part of the internal model's approach to market risk management as laid out by the Basle Commitee on Banking Supervision (1996). However, existing backtesting methods such as those developed in Christoffersen (1998), have relatively small...

Dans cet article, nous proposons des tests sur la forme de la distribution des erreurs dans un modèle de régression linéaire multivarié (RLM). Les tests que nous développons sont fonction des résidus obtenus par moindres carrés multivariés, lesquels sont standardisés de façon à ce que...

In this paper, we consider a linear regression model with Gaussian autoregressive errors of order p = 2, which may be nonstationary. Exact inference methods (tests and confidence region) are developed for the autoregressive parameters and the regression coefficients. We generalize the method...