these options. The signs of the estimated risk premia are consistent with theory, their economic magnitudes show that a long …

Risk evaluation is a forecast, and its validity must be backtested. Probability distribution forecasts are used in this … correlation), and that the bivariate forecasts provided by a risk methodology based on historical innovations performs correctly …

The Euler allocation scheme is a well-suited risk management tool that meets the three axioms of capital allocation …: diversification, continuity, and RORAC compatible. However, the Euler allocation scheme of the risk measure VaR meets the desirable … property of portfolio-invariance only under the asymptotically single-risk-factor model (ASRF) framework. Without portfolio …

In aftermath of the Financial Crisis, some risk management practitioners advocate wider adoption of Bayesian inference … to replace Value-at-Risk (VaR) models for minimizing risk failures (Borison & Hamm, 2010). They claim reliance of …-Bayesian and [increasingly] Bayesian – continues to be a key methodological foundation of risk management and regulation related …

[Update: Within four weeks of the original publication of this research report, Risk Magazine reported in its 28th … February 2012 issue story titled 'Goodbye VaR? Basel to Consider Other Risk Metrics': "A review of trading book capital rules …, due to be launched in March by the Basel Committee on Banking Supervision, will consider ditching value-at-risk as the …

In the aftermath of the Global Financial Crisis, some risk management practitioners have advocated wider adoption of … Bayesian inference to replace Value- at-Risk (VaR) models in order to minimize risk failures. Despite its limitations, the … [increasingly] Bayesian—continues to be a key methodological foundation of risk management and regulation-related risk modeling …

extreme downside return risk and is mainly driven by more recent years. There is no premium for stocks whose liquidity is …We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside … same time when the market liquidity (return) is lowest. This effect is not driven by linear or downside liquidity risk or …

Tail risk refers to the possibility that a rare event would adversely affect the value of a portfolio in a significant … manner. It became much more relevant due to recent periods of strong market turbulence.We describe how to quantify such risk …, which tail risk protection strategies were considered in the literature, their effectiveness and associated costs. We also …

model with heterogeneous agents, we reveal the existence of an extreme weather risk premium in the cross-section of stock … returns. In the period from 1995 to 2019, domestic U.S. stocks with the most negative sensitivity to thunderstorm losses … risk factors from standard asset pricing models nor by firm characteristics. Our results reveal a novel link between …