Proper measurement of volatility is vital in financial decisions. Estimating volatility accurately also requires properly capturing the conditional distribution, fat tails and price spikes. In this study, we model the volatility of Natural Gas Futures, Brent Oil Futures and Heating Oil Futures...

We provide evidence suggesting that the assumption on the probability distribution for return innovations is more influential for Value at Risk (VaR) performance than the conditional volatility specification. We also show that some recently proposed asymmetric probability distributions and the...

In this paper we consider daily financial data from various sources (stock market indices, foreign exchange rates and bonds) and analyze their multi-scaling properties by estimating the parameters of a Markov-switching multifractal model (MSM) with Lognormal volatility components. In order to...

A general model is proposed for flexibly estimating the density of a continuous response variable conditional on a possibly high-dimensional set of covariates. The model is a finite mixture of asymmetric student-t densities with covariate dependent mixture weights. The four parameters of the...

In this paper, we extend the concept of News Impact Curve developed by Engle and Ng (1993) to the higher moments of the multivariate returns' distribution, thereby providing a tool to investigate the impact of shocks on the characteristics of the subsequent distribution. For this purpose, we...