Books and Edited Volumes
Classics old and new. In the interpretive introductory chapter I selectively survey several key strands of literature on financial risk measurement and management. I begin by showing why there's a need for financial risk measurement and management, and then I turn to relevant aspects of return distributions and volatility fluctuations, with implicit emphasis on market risk for equities. I then treat market risk for bonds, focusing on the yield curve, with its nuances and special structure. In addition to market risk measurement and management, I also discuss aspects of measuring credit risk, operational risk, systemic risk, and underlying business-cycle risk. I nevertheless also stress the limits of statistical analysis, and the associated importance of respecting the unknown and the unknowable.
Central banks manage huge forex portfolios. It would be socially irresponsible for them to manage those portfolios like aggressive and risky hedge funds, yet it would presumably be similarly socially irresponsible for them to settle for a risk-free return. So how should central banks manage their portfolios? This book grapples with that interesting question.
A collection of our papers in time-series macro-econometrics, with an interpretive introductions. Includes material on the analysis of business cycle durations, long memory, regime switching, leading indicators, turning points, and predictive accuracy comparisons.
My 1986 Ph.D. dissertation, written in 1984-1985, showing that ARCH effects are important in asset returns. Hard to believe from today's vantage point, but that was a very novel result at the time! Also contains work on testing for serial correlation in the presence of ARCH, Gaussian CLTs for ARCH processes (so that temporal aggregation reduces the fat tails in unconditional distributions), and multivariate latent-factor ARCH.
On the successes and failures of various parts of modern financial risk management, emphasizing the known (K), the unknown (u) and the unknowable (U). We illustrate a KuU-based perspective for conceptualizing financial risks and designing effective risk management strategies. Sometimes we focus on K, and sometimes on U, but most often our concerns blend aspects of K and u and U. Indeed K and U are extremes of a smooth spectrum, with many of the most interesting and relevant situations interior. Statistical issues emerge as central to risk measurement, and we push toward additional progress. But economic issues of incentives and strategic behavior emerge as central for risk management, as we illustrate in a variety of contexts.