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 revisits the study of Cochrane (2005), to estimate the risk and returns of venture capital investments while correcting for the selection bias. We use an up-to-date dataset and enhance it to account for missing firm valuations using machine learning. The model is able to infer, with a...

Researchers and practitioners who use Data Envelopment Analysis often want to incorporate several inputs and outputs in their model to consider as much relevant information as possible. However, too many inputs and outputs can result in the well-known dimensionality problem referred to as the...

This paper suggests a method of estimation of the implied volatility smile uncertainty of the observed options prices due to future risk-free rate uncertainty. The purpose is to quantify the range of uncertainty under different scenarios.We consider the setting where both the implied volatility...

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...

This study deals with the dynamic hedging of single-tranche collateralized debt obligations (STCDOs). As a first step, we specify a top-down affine factor model in which a catastrophic risk component is incorporated in order to capture the dynamics of super-senior tranches. Next, we derive the...

We propose an affi ne two-factor model for the pricing of single-tranche collateralized debt obligations by following the general top-down framework introduced in Filipovic et al. [2011]. Apart from being analytically tractable, this model has the feature that it incorporates a catastrophic risk...

This paper decomposes the risk premia of individual stocks into contributions from systematic and idiosyncratic risks. I introduce an affine jump-diffusion model, which accounts for both the factor structure of asset returns and that of the variance of idiosyncratic returns. The estimation is...