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 …

idiosyncratic volatility and stock returns is parabolic. The high idiosyncratic risk is associated with high (low) excess returns at …The relation between idiosyncratic risk and stock returns is currently a topic of debate in the academic literature. So … idiosyncratic risk and stock returns in the Indian stock market employing quantile regressions. Using quantile regressions, this …

risk and market dynamics. This paper demonstrates how macroeconomic factor models, based on Bayesian model averaging (BMA …), can help address the challenges in some specific investment analytic tasks from three perspectives: (1) selecting risk … factors and estimating risk factor exposure in risk allocation, (2) modeling the dynamic exposure of multiple asset classes to …

historical periods in which uncertainty and risk premia were elevated because of news shocks. …

The relationship between risk and return is one of the most studied topics in finance. The majority of the literature … is based on a linear, parametric relationship between expected returns and conditional volatility. However, there is no … weights and arguments. We find strong robust evidence of volatility feedback in monthly data. Once volatility feedback is …

volatility variable, when included into the training sample, boosts the predictive power of the model significantly …

volatility variable, when included into the training sample, boosts the predictive power of the model significantly. -- CART …

In this paper we show that the long-run stock and bond volatility and the long-run stock-bond correlation depend on … macroeconomic uncertainty. We use the mixed data sampling (MIDAS) econometric approach. The findings are in accordance with the …

12 years of high-frequency data from U.S. and German sovereign bond markets. We detect realized volatility and realized …

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …