stockholders' consumption risk has strong predictive power for market returns with 39% in-sample and 19% out-of-sample R …' consumption risk explains 40% of the cross-sectional average returns. Stockholders' consumption risk also partially explains the …' consumption risk reverses the findings in the literature using aggregate consumption risk: stockholders' consumption risk varies …

Considerable literature has been devoted to developing statistical inferential results for risk measures, especially … a number of risk measures that are of the form of ratios, or even more complex combinations, of two L-functionals. In … the present paper we call such combinations ‘coupled risk measures' and develop a statistical inferential theory for them …

We describe characteristics of various risk measures (Value-at-Risk, Expected Shortfall, etc.) that are used to analyze … and quantify the tail risk exposure, and discuss their relative strengths and weaknesses. Emphasis is placed on presenting … and comparing methodologies to compute and backtest estimates for these risk measures, from a practical perspective. We …

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the … Garman [1996a, 1997a] under the assumption that returns are drawnfrom a multivariate normal distribution. For many portfolios … to cause seriousdistortions in VaR calculations, one has to resort to either alternative distribution specifications …

algorithm is at least $\Omega (n^{-1/2})$ away from the optimal distortion for some distribution on a bounded subset of ${\cal R …

endpoint of the speed distribution is estimated. The corresponding time can be interpreted as the estimated ultimate world …