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 …

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model …

fairly priced stocks. Thus, our results support the mispricing and arbitrage risk hypotheses that the positive (negative …

Risk forecasting is crucial for informed investment decision-making. Moreover, the salience of investment risk … increases during economically uncertain times. In this paper, we study how sell-side analysts form expectations of firm risk … use of quantitative/qualitative information improves their forecasts as predictors of firm risk. Together, our results …

This paper introduces an alternate measure of idiosyncratic risk leveraged from the decomposition method to further … eliminate the residual systematic risk inherent in the factor asset pricing model. Combining both complementary techniques … contributes to a more comprehensive firm-level idiosyncratic risk that is crucial in both portfolio diversification and alpha …

The paper is an empirical research work wherein the principle of Modern Portfolio Theory along with aspects of … geographical diversification have been subjected to test. The validation of the said theory has been made via hypothesis testing in … diversifying risk …

The paper proposes a new approach to model risk measurement based on the Wasserstein distance between two probability … measures. It formulates the theoretical motivation resulting from the interpretation of fictitious adversary of robust risk … nominal model. The Wasserstein approach suits for all types of model risk problems, ranging from the single-asset hedging risk …

In this work, we have found a risk model that improves the performance of Risk Targeting. Risk Targeting in portfolio … construction is implemented to improve capital utilization in growing markets and systematically step away from risk scenarios …. However, the performance of risk targeting varies with different implementations of risk estimation. Risk Targeting using …

We propose a novel risk matrix to characterize the optimal portfolio choice of an investor with tail concerns. The … diagonal of the matrix contains the Value-at-Risk of each asset in the portfolio and the off-diagonal the pairwise Delta …-CoVaR measures reflecting tail connections between assets. First, we derive the conditions under which the associated quadratic risk …