Madhu Kalimipalli
Dr. Kalimipalli joined Wilfrid Laurier's Business Faculty in the fall of 2000. His research is broadly in the areas of risk-management and fixed income markets. He teaches Derivatives and Risk Management (for undergraduates and MBAs) and Financial Management (for undergraduates).
Articles by this Author
Regime-Switching Stochastic Volatility and Short-term Interest Rates
- By Madhu Kalimipalli
- Published 12/21/2007
- Price modeling
- Unrated
Keywords: Short-term interest rates, stochastic volatility, regime switching, MCMCmethods, GARCH models.
Published in:
Publication year:
Co-author 1: Raul Susmel
In this paper, we introduce regime-switching in a two-factor stochastic volatility model to explain the behavior of short-term interest rates. The regime-switching stochastic volatility (RSV) process for interest rates is able to capture all possible exogenous shocks that could be either discrete, as occuring from possible changes in the underlying regime, or continuous in the form of 'market-news' events. We estimate the model using a Gibbs Sampling based Markov Chain Monte Carlo algorithm that is robust to complex non-linearities in the likelihood function. We compare the performance of our RSV model with the performance of other GARCH and stochastic volatility two-factor models. We evaluate all models with several in-sample and out-of-sample measures. Overall, our results show a superior performance of the RSV two-factor model.
Published in:
Publication year:
Co-author 1: Raul Susmel
In this paper, we introduce regime-switching in a two-factor stochastic volatility model to explain the behavior of short-term interest rates. The regime-switching stochastic volatility (RSV) process for interest rates is able to capture all possible exogenous shocks that could be either discrete, as occuring from possible changes in the underlying regime, or continuous in the form of 'market-news' events. We estimate the model using a Gibbs Sampling based Markov Chain Monte Carlo algorithm that is robust to complex non-linearities in the likelihood function. We compare the performance of our RSV model with the performance of other GARCH and stochastic volatility two-factor models. We evaluate all models with several in-sample and out-of-sample measures. Overall, our results show a superior performance of the RSV two-factor model.