Yield Curve Modeling and Forecasting: The Dynamic Nelson-Siegel Approach (The Econometric and Tinbergen Institutes Lectures)

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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.

Publisher ‏ : ‎ Princeton University Press (January 15, 2013)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 224 pages
ISBN-10 ‏ : ‎ 0691146802
ISBN-13 ‏ : ‎ 978-0691146805
Item Weight ‏ : ‎ 13.6 ounces
Dimensions ‏ : ‎ 0.1 x 0.1 x 0.1 inches

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4 reviews for Yield Curve Modeling and Forecasting: The Dynamic Nelson-Siegel Approach (The Econometric and Tinbergen Institutes Lectures)

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  1. selwyn daniel

    This book was able to formulate in my mind the premise of the curve.
    A substantially high level of math is required to interpret and apply these concepts. I was unaware of this when i bought this book and thought that my current masters level calculus and statistics would suffice. However I was wrong and I am currently attempting to return to my mathematical root and advance my mathematical acumen before proceeding further with this book. I do believe however from what i was able to gleam from my reading that once one able to acquire the necessary mathematical acumen, it would provide and advantage with respect to application, as opposed to a conceptual understanding.

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  2. Julio

    Basic
    It includes online the basics

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  3. Ho Yan Chan

    great

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  4. Mike

    nothing more than that, it’s a summary of his papers, but it’s very detail, and very broad introduction to Nelson Siegel Type Models

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