This paper addresses the problem of nonparametric estimation of the conditional expected shortfall (CES) that has gained popularity in financial risk management. We propose a new nonparametric estimator of the CES. The proposed estimator is defined as a conditional counterpart of the sample...

This paper considers spot variance path estimation from datasets of intraday high-frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects, and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...

This article introduces a new class of stochastic volatility models which allows for stochastic volatility of volatility (SVV): Volatility modulated non-Gaussian Ornstein--Uhlenbeck (VMOU) processes. Various probabilistic properties of (integrated) VMOU processes are presented. Further we study...

In this paper, we analyze five of the most popular models proposed to represent conditional heteroscedasticity with leverage effect, namely, GQARCH, TGARCH, GJR, EGARCH, and APARCH. We show that when the parameters satisfy the positivity, stationarity, and finite kurtosis conditions, the...

We present a new estimation approach that allows us to extract from spreads in synthetic credit markets the contribution of systematic and idiosyncratic default risk to total default risk. Using an extensive dataset of 90,600 credit default swap and collateralized debt obligation (CDO) tranche...

This paper proposes a parsimonious approach to test nonlinear dependence on the conditional mean and variance of hedge funds with respect to several market factors. My approach introduces nonlinear dependence by means of empirically relevant polynomial functions of the factors. For comparison...