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Testing the Empirical Performance of Stochastic Volatility Models of the Short-Term Interest Rate

Turan G. Bali
The Journal of Financial and Quantitative Analysis
Vol. 35, No. 2 (Jun., 2000), pp. 191-215
DOI: 10.2307/2676190
Stable URL: http://www.jstor.org/stable/2676190
Page Count: 25
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Testing the Empirical Performance of Stochastic Volatility Models of the Short-Term Interest Rate
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Abstract

I introduce two-factor discrete time stochastic volatility models of the short-term interest rate to compare the relative performance of existing and alternative empirical specifications. I develop a nonlinear asymmetric framework that allows for comparisons of non-nested models featuring conditional heteroskedasticity and sensitivity of the volatility process to interest rate levels. A new class of stochastic volatility models with asymmetric drift and nonlinear asymmetric diffusion process is introduced in discrete time and tested against the popular continuous time and symmetric and asymmetric GARCH models. The existing models are rejected in favor of the newly proposed models because of the asymmetric drift of the short rate, and the presence of nonlinearity, asymmetry, GARCH, and level effects in its volatility. I test the predictive power of nested and non-nested models in capturing the stochastic behavior of the risk-free rate. Empirical evidence on three-, six-, and 12-month U.S. Treasury bills indicates that two-factor stochastic volatility models are better than diffusion and GARCH models in forecasting the future level and volatility of interest rate changes.

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