A General Stochastic Volatility Model For The Pricing And Forecasting Of Interest Rate Derivatives
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A General Stochastic Volatility Model for the Pricing and Forecasting of Interest Rate Derivatives
We develop a tractable and flexible stochastic volatility multi-factor model of the term structure of interest rates. It features correlations between innovations to forward rates and volatilities, quasi-analytical prices of zero-coupon bond options and dynamics of the forward rate curve, under both the actual and risk-neutral measure, in terms of a finite-dimensional affine state vector. The model has a very good fit to an extensive panel data set of interest rates, swaptions and caps. In particular, the model matches the implied cap skews and the dynamics of implied volatilities. The model also performs well in forecasting interest rates and derivatives.
Yield Curve Modeling and Forecasting
Author: Francis X. Diebold
language: en
Publisher: Princeton University Press
Release Date: 2013-01-15
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.
Advances in Investment Analysis and Portfolio Management (New Series) Vol．5
Author: Cheng F. Lee
language: en
Publisher: Center for PBBEFR & Airiti Press
Release Date: 2012-04-01
Advances in Investment Analysis and Portfolio Management (New Series) is an annual publication designed to disseminate developments in the area of investment analysis and portfolio management. The publication is a forum for statistical and quantitative analyses of issues in security analysis, portfolio management, options, futures, and other related issues. The objective is to promote interaction between academic research in finance, economics, and accounting and applied research in the financial community.