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 this paper, we extend the standard Gaussian stochastic-volatility Bayesian VAR by employing the generalized hyperbolic skew Student's t distribution for the innovations. Allowing the skewness parameter to vary over time, our specification permits flexible modelling of innovations in terms of...

We investigate the effect of inflation uncertainty on inflation from January 1982 through March 2016 for Turkey by using the Stochastic Volatility in Mean model with time-varying parameters. Our empirical evidence from consumer price index (CPI) inflation suggests that the observed positive...

Risk estimation or volatility estimation at financial markets, particularly stock exchange markets, is complex issue of great importance to theorists and practitioners. Models used to estimate volatility forecasts are translated into better pricing of stocks and better risk management. The aim...

As common practice, oil studies in the economic literature are carried out by taking the correct specification of a model as given, and ignoring the problem of estimating overly optimistic confidence sets. This means that model uncertainty is pervasive in the empirical results. In this work I...

Using equations that arise in quantum mechanics, this paper describes a way to more accurately and efficiently represent non-Gaussian return distributions than the standard method of invoking skewness and kurtosis. Then, it provides a new single intuitive number, defined here as the “crash...

Understanding uncertainty in estimating risk measures is important in modern financial risk management. In this paper we consider a nonparametric framework that incorporates auxiliary information available in covariates, and propose a family of inferential methods for the value at risk, expected...