This paper revisits the performance of frequently used risk forecasting methods, such as the Value-at-Risk models. The aim is to analyze its performance, and mitigate its pitfalls by incorporating conditional variance estimates, as generated by a GARCH model. Notably, this paper tests several...

Risk transmission among financial markets and their participants is time- evolving, especially for the extreme risk scenarios. Possibly sudden time variation of such risk structures ask for quantitative technology that is able to cope with such situations. Here we present a novel localized...

We modify Adrian and Brunnermeier's (2011) CoVaR, the Value-at-Risk (VaR) of the financial system conditional on an institution being in financial distress. We change the definition of financial distress from an institution being exactly at its VaR to being at most at its VaR. This change allows...

We study the intra-horizon value at risk (iVaR) in a general jump diffusion setup and propose a new model of asset returns called displaced mixed-exponential model, which can arbitrarily closely approximate finite-activity jump-diffusions and completely monotone Levy processes. We derive...

Can a major financial crisis trigger changes in a bank’s risk-taking behavior? Using the 2008 Global Financial Crisis as a quasi-natural experiment and a difference-in-differences approach, I examine whether the worst crisis-hit Russian banks – the banks that have strong incentives to...

We propose a market-based framework that exploits time-varying parameter vector autoregressions to estimate the dynamic network of financial spillover effects. We apply it to financials in the Standard & Poor's 500 index and estimate interconnectedness at the sector and institution level. At the...