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Regime Switching Stochastic Volatility and Short-Term Interest Rates

Regime Switching Stochastic Volatility and Short-Term Interest Rates
Author: Madhu Kalimipalli
Publisher:
Total Pages:
Release: 2003
Genre:
ISBN:

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In this paper, we introduce regime-switching in a two-factor stochastic volatility (SV) model to explain the behavior of short-term interest rates. We model the volatility of short-term interest rates as a stochastic volatility process whose mean is subject to shifts in regime. We estimate the regime-switching stochastic volatility (RSV) model using a Gibbs Sampling-based Markov Chain Monte Carlo algorithm. In-sample results strongly favor the RSV model in comparison to the single-state SV model and GARCH family of models. Out-of-sample results are mixedand, overall, provide weak support for the RSV model.


Modeling, Stochastic Control, Optimization, and Applications

Modeling, Stochastic Control, Optimization, and Applications
Author: George Yin
Publisher: Springer
Total Pages: 599
Release: 2019-07-16
Genre: Mathematics
ISBN: 3030254984

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This volume collects papers, based on invited talks given at the IMA workshop in Modeling, Stochastic Control, Optimization, and Related Applications, held at the Institute for Mathematics and Its Applications, University of Minnesota, during May and June, 2018. There were four week-long workshops during the conference. They are (1) stochastic control, computation methods, and applications, (2) queueing theory and networked systems, (3) ecological and biological applications, and (4) finance and economics applications. For broader impacts, researchers from different fields covering both theoretically oriented and application intensive areas were invited to participate in the conference. It brought together researchers from multi-disciplinary communities in applied mathematics, applied probability, engineering, biology, ecology, and networked science, to review, and substantially update most recent progress. As an archive, this volume presents some of the highlights of the workshops, and collect papers covering a broad range of topics.


Regime Switches in Interest Rates

Regime Switches in Interest Rates
Author: Andrew Ang
Publisher:
Total Pages: 41
Release: 1998
Genre: Interest rates
ISBN:

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Regime-switching models are well suited to capture the non-linearities in interest rates. This paper examines the econometric performance of regime-switching models for interest rate data from the US, Germany and the UK. There is strong evidence supporting the presence of regime switches but univariate models are unlikely to yield consistent estimates of the model parameters. Regime-switching models incorporating international short rate and term spread information forecast better, match sample moments better, and classify regimes better than univariate models. We show that the regimes in interest rates correspond reasonably well with business cycles, at least in the US. This may explain why regime-switching models forecast interest rates better than single regime models. Finally, the non-linear interest rate dynamics implied by regime-switching models have potentially important implications for the macroeconomic literature documenting the effects of monetary policy shocks on economic aggregates. Moreover, the implied volatility and drift functions are rich enough to resemble those recently estimated using non-parametric techniques.


Missing Data Methods

Missing Data Methods
Author: David M. Drukker
Publisher: Emerald Group Publishing
Total Pages: 262
Release: 2011-11-30
Genre: Business & Economics
ISBN: 1780525265

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Part of the "Advances in Econometrics" series, this title contains chapters covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.


Nonlinear Drift and Stochastic Volatility

Nonlinear Drift and Stochastic Volatility
Author: Licheng Sun
Publisher:
Total Pages:
Release: 2002
Genre:
ISBN:

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In this article I provide new evidence on the role of nonlinear drift and stochastic volatility in interest rate modeling. I compare various model specifications for the short-term interest rate using the data from five countries. I find that modeling the stochastic volatility in the short rate is far more important than specifying the shape of the drift function. The empirical support for nonlinear drift is weak with or without the stochastic volatility factor. Although a linear drift stochastic volatility model fits the international data well, I find that the level effect differs across countries.


Stochastic Volatility and Jumps in Interest Rates

Stochastic Volatility and Jumps in Interest Rates
Author: Ren-Raw Chen
Publisher:
Total Pages: 43
Release: 2010
Genre:
ISBN:

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In this paper, we examine possible stochastic volatility and jumps in short-term interest rates for four major countries: US, UK, Germany and Japan. An econometric model with stochastic volatility and jumps in both rates and volatility is derived and fit to the daily data for futures interest rates in four major currencies and the model provides a better fit for the empirical distributions. The distributions for changes in Eurocurrency interest rate futures are leptokurtic with fat tails and an unusually large percentage of observations concentrated at zero. The implied volatilities for at-the-money options on interest rate futures reveal evidence of stochastic volatility, as well as jumps in volatility.