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...

The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution...

This paper examines the relationship between oil price movements and systemic risk of many financial institutions in major petroleum-based economies. We estimate ΔCoVaR for those institutions and thereby observe the presence of elevated increases in the levels corresponding to the subprime and...

We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside liquidity (EDL) risks. The cross-section of stock returns reflects a premium if a stock's return (liquidity) is lowest at the same time when the market liquidity (return) is lowest....

Value-at-risk (VaR) is an important risk measure now widely used by financial institutions and regulators to quantify market risk and compute regulatory capital charge. The performance of VaR model can be examined by back-testing. Based on back-testing information, this paper develops a Machine...

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...

I provide a measure of time-varying tail risk in credit markets based on a dynamic power-law model. Credit tail risk is estimated from extreme price fluctuations of credit default swaps (CDS) on government debt. Tail returns are described by a power-law for core and peripheral countries within...