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.
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