volatility measures, and the VaRs are tested and compared. La valeur exposée au risque (value at risk - VaR) est devenue un outil …

Discrete time stochastic volatility models (hereafter SVOL) are noticeably harder to estimate than the successful ARCH …(volatilities/ parameters) and p(parameters). This hierarchy provides a natural environment for the construction of stochastic volatility models …, therefore, provides a general perspective on specification and implementation of stochastic volatility models. We apply various …

can be summarized as follows. First, while our version of calibration is better than naive estimation, both are dominated …'apprentisage par moyen d'estimation. …

Using realized volatility to estimate daily conditional volatility of financial returns, we compare forecasts of daily … volatility from standard QML-estimated GARCH models, and from projections on past realized volatilities obtained from high … variance of daily returns treated as a daily volatility forecast, allowing us to estimate the maximum horizon at which the …

multivariate modeling framework with Swiss current account data using Bayesian econometric methods for estimation and inference. …

much interrelated, and we explore the relationships in detail. Among other things, we show that: (1) Volatility dependence … overwhelming evidence of volatility dependence. (2) The standard finding of little or no conditional mean dependence is entirely … consistent with a significant degree of sign dependence and volatility dependence. In particular, sign dependence does not imply …