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 Bayesian methodology has significant advantages. Just...

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 inference on subjective judgment, the key limitation...

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...

This paper derives and tests the cross-sectional predictions of an intertemporal equilibrium asset pricing model with generalized disappointment aversion and time-varying macroeconomic uncertainty. To the contrary of the existing literature, disappointment may result not only from a fall in the...

We propose a conditional model of asset returns in the presence of common factors and downside risk. Specifically, we generalize existing latent factor models in three ways: we show how to estimate the threshold which identifies the 'disappointment' event triggering the bad state of the world; we...

The forecasting uncertainty around point macroeconomic forecasts is usually measured by the historical performance of the forecasting model, using measures such as root mean squared forecasting errors (RMSE). This measure, however, has the major drawback that it is constant over time and hence...

Goal: ISO 31000 Risk Management (RM) recently re-defined risk as the effect of uncertainty on an organization's ability to meet the objectives. Earlier, it defined risk as a combination of the probability and scope of the (predicted) consequences. The revised ISO Risk advances beyond a static...

Risk evaluation is a forecast, and its validity must be backtested. Probability distribution forecasts are used in this work and allow for more powerful validations compared to point forecasts. Our aim is to use bivariate copulas in order to characterize the in-sample copulas and to validate...

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A...