Francis X. Diebold – författare

This is the most sophisticated and up-to-date econometric analysis of business cycles now available. Francis Diebold and Glenn Rudebusch have long been acknowledged as leading experts on business cycles. And here they present a highly integrative collection of their most important essays on the subject, along with a detailed introduction that draws together the book''s principal themes and findings. Diebold and Rudebusch use the latest quantitative methods to address five principal questions about the measurement, modeling, and forecasting of business cycles. They ask whether business cycles have become more moderate in the postwar period, concluding that recessions have, in fact, been shorter and shallower. They consider whether economic expansions and contractions tend to die of "old age." Contrary to popular wisdom, they find little evidence that expansions become more fragile the longer they last, although they do find that contractions are increasingly likely to end as they age. The authors discuss the defining characteristics of business cycles, focusing on how economic variables move together and on the timing of the slow alternation between expansions and contractions. They explore the difficulties of distinguishing between long-term trends in the economy and cyclical fluctuations. And they examine how business cycles can be forecast, looking in particular at how to predict turning points in cycles, rather than merely the level of future economic activity. They show here that the index of leading economic indicators is a poor predictor of future economic activity, and consider what we can learn from other indicators, such as financial variables. Throughout, the authors make use of a variety of advanced econometric techniques, including nonparametric analysis, fractional integration, and regime-switching models. Business Cycles is crucial reading for policymakers, bankers, and business executives.

A clear understanding of what we know, don''t know, and can''t know should guide any reasonable approach to managing financial risk, yet the most widely used measure in finance today--Value at Risk, or VaR--reduces these risks to a single number, creating a false sense of security among risk managers, executives, and regulators. This book introduces a more realistic and holistic framework called KuU --the K nown, the u nknown, and the U nknowable--that enables one to conceptualize the different kinds of financial risks and design effective strategies for managing them. Bringing together contributions by leaders in finance and economics, this book pushes toward robustifying policies, portfolios, contracts, and organizations to a wide variety of KuU risks. Along the way, the strengths and limitations of "quantitative" risk management are revealed. In addition to the editors, the contributors are Ashok Bardhan, Dan Borge, Charles N. Bralver, Riccardo Colacito, Robert H. Edelstein, Robert F. Engle, Charles A. E. Goodhart, Clive W. J. Granger, Paul R. Kleindorfer, Donald L. Kohn, Howard Kunreuther, Andrew Kuritzkes, Robert H. Litzenberger, Benoit B. Mandelbrot, David M. Modest, Alex Muermann, Mark V. Pauly, Til Schuermann, Kenneth E. Scott, Nassim Nicholas Taleb, and Richard J. Zeckhauser.

Understanding the dynamic evolution of the yield curve is critical to many financial tasks, including pricing financial assets and their derivatives, managing financial risk, allocating portfolios, structuring fiscal debt, conducting monetary policy, and valuing capital goods. Unfortunately, most yield curve models tend to be theoretically rigorous but empirically disappointing, or empirically successful but theoretically lacking. In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful. The first extension is the dynamic Nelson-Siegel model (DNS), while the second takes this dynamic version and makes it arbitrage-free (AFNS). Diebold and Rudebusch show how these two models are just slightly different implementations of a single unified approach to dynamic yield curve modeling and forecasting. They emphasize both descriptive and efficient-markets aspects, they pay special attention to the links between the yield curve and macroeconomic fundamentals, and they show why DNS and AFNS are likely to remain of lasting appeal even as alternative arbitrage-free models are developed. Based on the Econometric and Tinbergen Institutes Lectures, Yield Curve Modeling and Forecasting contains essential tools with enhanced utility for academics, central banks, governments, and industry.