Comparing Estimation Procedures For Stochastic Volatility Models Of Short Term Interest Rates

Download or read book Comparing Estimation Procedures for Stochastic Volatility Models of Short-Term Interest Rates written by Ramaprasad Bhar and published by . This book was released on 2009 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper compares the performance of three maximum likelihood estimation procedures -quasi-maximum likelihood, Monte Carlo likelihood and the particle filter to estimate stochastic volatility models of short term interest rates. The procedures are compared in an empirical study of interest rate volatility where a number of diagnostic tests in- and out-of-sample are utilized to evaluate both model specification and estimation procedure. Empirically, the results suggest interest rates follow the Cox-Ingersoll-Ross model with stochastic volatility and that volatility increases after Federal Open Market Committee meetings. Overall, the Monte Carlo likelihood procedure provided the best results.