Central to the ongoing development of practical financial risk management methods is recognition of the fact that asset return volatility is often forecastable. Although there is no single horizon relevant for financial risk management, most would agree that in many situations the relevant...

Recent literature has trumpeted the claim that extreme value theory (EVT) holds promise for accurate estimation of extreme quantiles and tail probabilities of financial asset returns, and hence holds promise for advances in the management of extreme financial risks. Our view, based on a...

The turmoil in the capital markets in 1997 and 1998 has highlighted the need for systematic stress testing of banks' portfolios, including both their trading and lending books. We propose that underlying macroeconomic volatility is a key part of a useful conceptual framework for stress testing...

Market risk management under normal conditions traditionally has focussed on the distribution of portfolio value changes resulting from moves in the mid-price. Hence the market risk is really in a "pure" form: risk in an idealized market with no "friction" in obtaining the fair price. However,...

We show that the common practice of converting 1-day volatility estimates to h-day estimates by scaling by the sqaure root of h is inappropriate and produces overestimates of the variability of long-horizon volatility. We conclude that volatility models are best tailored to tasks: if interest...

Recent literature has trumpeted the claim that extreme value theory (EVT) holds promise for accurate estimation of extreme quantiles and tail probabilities of financial asset returns, and hence hold promise for advances in the management of extreme financial risks. Our view, based on a...

Extreme value theory (EVT) holds promise for advancing the assessment and management of extreme financial risks. Recent literature suggests that the application of EVT generally results in more precise estimates of extreme quantiles and tail probabilities of financial asset returns. This article...