An extended history of market returns reveals aspects of financial risk that are not evident over short timescales. The most enduring risk measure is variance, which quantifies short-term regularities in return dispersion. An alternative measure, shortfall, quantifies the risk of extreme market...

Risk analysis involves gaining deeper insight into the sources of risk, and evaluating whether these risks accurately reflect the views of the portfolio manager. In this paper, we show how to extend standard volatility analytics to shortfall, a measure of extreme risk. Using two examples, we...

Systematic model bias has been implicated in the global recession that began in 2007, and this bias can be traced back to assumptions about the normality of data. Nonetheless, the normal distribution continues to play a foundational role in quantitative finance. One reason for this is that the...

A nonparametric analysis of player plate appearances (PA) in the 2018 Major League Baseball (MLB) season provides no evidence of a batter hot hand. Players with more than 100 PAs in the 2018 season are analyzed using one-sided permutation tests stratified by player. Based on recent literature,...

Portfolio risk forecasts are commonly evaluated using test statistics that are sums of random variables. We study the distributional properties of these test statistics for value at risk, expected shortfall, and volatility. For a diverse collection of 74 US equity portfolios, risk forecasts...

We develop a portfolio risk model that uses high-frequency data to forecast the loss surface, which is the set of loss distributions at future time horizons. Our model uses a fully automated, semi-parametric fitting procedure that has its basis in extreme value statistics. We take account of...

We examine the efficacy of the I-squared incomplete information credit model in a broad context that is relevant to fund and asset managers.Using a rigorous statistical analysis, we show that I-squared is a powerful forecaster of the following events:- Rating agency downgrades- Investment grade...

Extreme value statistics provides a practical, flexible, mathematically elegant framework in which to develop financial risk management tools that are consistent with empirical data. In this introductory survey, we discuss some of the basic tools including power law distributions, the peaks over...

We propose a multi-firm first-passage credit model in which investors have incomplete information. In this model, investors observe neither a firm's value nor its default barrier. The model accounts for the short term risk inherent in default events, the market-wide impact of defaults on...

Given a collection of single-market covariance matrix forecasts for different markets, we describe how to embed them into a global forecast of total risk.We do this by starting with any global covariance matrix forecast that contains information about cross-market correlations, and revising it...