We examine how sensitive the new performance indexes incorporating high moments and disaster risk are to disaster risk …. The new performance indexes incorporating high moments and disaster risk are the Aumann-Serrano performance index and … underlying risk. We show, by numerical examples and empirical examples, how sensitive these indexes are to disaster risk …

Diversification of financial securities is considered a substantial element of portfolio risk. In this context, the … construction of an optimal portfolio is an ongoing concern for portfolio managers. This study measures the risk-reward tradeoffs … risk for DAX, MDAX, and CAC40 decreases from joining a common hypothetical stock market, while for FTSE100, FTSE MIB, and …

irrelevant for stocks with extremely high risk. This study finds that the SAI in India explains the variation in the excess …

situations it is better to renounce parameter estimation altogether and pursue some trivial strategy such as the totally risk … ; Naive diversification ; Out-ofsample performance ; Risk function ; Shrinkage estimation …In the present work I derive the risk functions of 5 standard estimators for expected asset returns which are …

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 …

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 …

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 …