In this study we consider the risk estimation as a stochastic process based on the Sample Quantile Process (SQP) - which is a generalization of the Value-at-Risk calculated on a rolling sample. Using SQP's, we are able to show and quantify the pro-cyclicality of the current way financial...

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...

This study examines the sensitivity of VaR estimates obtained with Monte Carlo technique using the data set of Benninga and Wiener (1998) and applies the Kupiec test either by assuming large sample properties or by obtaining p-values through simulation process.

Under the internal model approach (IMA) stipulated by Basel II, financial institutions are allowed to develop and employ proprietary internal models to evaluate various risk. However, the flexibility to develop a proprietary model leads to the question of which computing method delivers the most...

Operational risk management remains a major concern for financial institutions. Indeed, institutions are bound to manage their own funds to hedge this risk. In this paper, we propose an approach to allocate one's own funds based on a combination of historical data and expert opinion using the...

This paper shows that the presence of conditional staging in R&D (Research & Development) has a critical impact on portfolio risk, and changes diversification arguments when a portfolio is constructed. When R&D projects exhibit option-like characteristics, correlation between projects plays a...