The forward-looking nature of option market data allows one to derive economically-based and model-free risk measures. This article proposes an extensive analysis of the performances of option-implied VaR and CVaR, and compare them with classical risk measures for the S&P500 Index. Delivering...

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the degree of non-linearity of the instruments comprised in the portfolio and thewillingness to make restrictive assumptions on the underlying statistical distributions, a...

We extend the model presented in Bonollo et al. by introducing a multiscenario framework that allows for a richer and more realistic specification, including non-static (stochastic) probabilities of default and losses given default. Though more complex from a computational point of view, the...

This paper considers an institutional investor who is implementing a long-term portfolio allocation strategy using forecasts of financial returns. We compare the performance of two competing macro-finance models, an unrestricted Vector AutoRegression (VAR) and a fully structural Dynamic...

The objective of this paper is to combine a real options framework with portfolio optimization techniques and to apply this new framework to investments in the electricity sector. In particular, a real options model is used to assess the adoption decision of particular technologies under...

We study alternative specifications of conditional quantile models that are used to estimate Value at Risk (VaR). Our proposed specifications include the incorporation of a slow moving component in the quantile process, along with recent aggregate returns as regressors. We consider a range of...

Empirical evidence suggests that asset returns correlate more strongly in bear markets than conventional correlation estimates imply. We propose a method for determining complete tail-correlation matrices based on Value-at-Risk (VaR) estimates. We demonstrate how to obtain more effi cient...

In this paper, we propose a multivariate market model with returns assumed to follow a multivariate normal tempered stable distribution. This distribution, defined by a mixture of the multivariate normal distribution and the tempered stable subordinator, is consistent with two stylized facts...