We present several estimates of measures of risk amongst the most well-known, using both high and low frequency data. The aim of the article is to show which lower frequency measures can be an acceptable substitute to the high precision measures, when transaction data is unavailable for a long...

Researchers in finance very often rely on highly persistent Ñ nearly integrated Ñ explanatory variables to predict returns. This paper proposes to stand up to the usual problem of persistent regressor bias, by detrending the highly auto-correlated predictors. We find that the statistical...

We provide an economic valuation of the riskiness of risk models by directly measuring the impact of model risks (specification and estimation risks) on VaR estimates. We find that integrating the model risk into the VaR computations implies a substantial minimum correction of the order of...

The forecasting literature has identified three important and broad issues: the predictive content is unstable over time, in-sample and out-of-sample discordant results and the problematic statistical inference with highly persistent predictors. In this paper, we simultaneously address these...

This paper studies the role of fluctuations in the aggregate price-earning ratio at different time-scales, for predicting stock returns and exploring the channels through which returns are forecasted. Using U.S. quartely data, we find that cycles in the price-earning ratio are strong and better...

This paper generalizes the Bollerslev and Zhang (2003) approach for the estimation of loadings of asset pricing models using "realized" measures and co-measures of risk. We propose here to extend this approach by including higher-moments in asset pricing models. Estimations are conducted using...

This article proposes a non-parametric portfolio selection criterion for the static asset allocation problem in a robust higher-moment framework. Adopting the Shortage Function approach, we generalize the multi-objective optimization technique in a four-dimensional space using L-moments, and...

The objective of this paper is to provide a complete framework to aggregate different quantile and expectile models for obtaining more diversified Value-at-Risk and Expected Shortfall measures, by applying the diversification principle to model risk. Following Taylor (2008) and Gouriéroux and...

Controlling and managing potential losses is one of the main objectives of the Risk Management. Following Ben Ameur and Prigent (2007) and Chen et al. (2008), and extending the first results by Hamidi et al. (2009) when adopting a risk management approach for defining insurance portfolio...

In a Constant Proportion Portfolio Insurance (CPPI) framework, a constant risk exposure is defined by the multiple of the strategy. This article proposes an alternative conditional multiple estimation model, which is based on an autoregressive quantile regression dynamic approach. We estimate...