Markov-Switching and Stochastic Volatility Diffusion Models of Short-Term Interest Rates
实证比较了短期利率的马尔可夫转换和随机波动扩散模型，发现马尔可夫转换模型拟合更好、参数更合理，且波动率依赖于利率水平，该模型预测效果最佳。
AbstractThis article empirically compares the Markov-switching and stochastic volatility diffusion models of the short rate. The evidence supports the Markov-switching diffusion model. Estimates of the elasticity of volatility parameter for single-regime models unanimously indicate an explosive volatility process, whereas the Markov-switching models estimates are reasonable. Itis found that either Markov switching or stochastic volatility, but not both, is needed to adequately fit the data. A robust conclusion is that volatility depends on the level of the short rate. Finally, the Markov-switching model is the best for forecasting. A technical contribution of this article is a presentation of quasi-maximum likelihood estimation techniques for the Markov-switching stochastic-volatility model.KEY WORDS : Quasi-maximum likelihood estimationShort rateTerm structure