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Testing The Empirical Performance Of Stochastic Volatility Models Of The Short Term Interest Rate
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Book Synopsis Testing the Empirical Performance of Stochastic Volatility Models of the Short Term Interest Rate by : Turan G. Bali
Download or read book Testing the Empirical Performance of Stochastic Volatility Models of the Short Term Interest Rate written by Turan G. Bali and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Comparing Estimation Procedures for Stochastic Volatility Models of Short-Term Interest Rates by : Ramaprasad Bhar
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.
Book Synopsis Nonlinear Drift and Stochastic Volatility by : Licheng Sun
Download or read book Nonlinear Drift and Stochastic Volatility written by Licheng Sun and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis An Empirical Comparison of the Short Term Interest Rate Models by : Mona Ben Salah
Download or read book An Empirical Comparison of the Short Term Interest Rate Models written by Mona Ben Salah and published by . This book was released on 2014 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article attempts to identify the best model of the short term interest rates that can predict its stochastic process over time.We studied eight different models of interest rates in the short term. The choice of these models was the aim of analyzing the relevance of certain specifications of the stochastic process of the short term interest rates, the effect of mean reversion and the sensitivity of the volatility to the level of interest rate.The yield on three months treasury bills is used as a proxy for the short term interest rates. The parameters of the different stochastic process are estimated using the generalized method of moments. The results show that the effect of mean reversion is not statistically significant and that volatility is highly sensitive to the level of interest rates.To further study the performance prediction of the intertemporal behavior of the short term interest rate of the various models; we simulated their stochastic process for different periods.The results show that none of the studied models reproduce the actual path of the short term interest rates. The problem lies in the parametric specification of the mean and volatility of the diffusion process.
Book Synopsis The Stochastic Volatility of Short-term Interest Rates by : Clifford A. Ball
Download or read book The Stochastic Volatility of Short-term Interest Rates written by Clifford A. Ball and published by . This book was released on 1998 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Stochastic Volatility and Realized Stochastic Volatility Models by : Makoto Takahashi
Download or read book Stochastic Volatility and Realized Stochastic Volatility Models written by Makoto Takahashi and published by Springer Nature. This book was released on 2023-04-18 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns. The modeling of financial time series volatility constitutes a crucial aspect of finance, as it plays a vital role in predicting return distributions and managing risks. Among the various econometric models available, the stochastic volatility model has been a popular choice, particularly in comparison to other models, such as GARCH models, as it has demonstrated superior performance in previous empirical studies in terms of fit, forecasting volatility, and evaluating tail risk measures such as Value-at-Risk and Expected Shortfall. The book also explores an extension of the basic stochastic volatility model, incorporating a skewed return error distribution and a realized volatility measurement equation. The concept of realized volatility, a newly established estimator of volatility using intraday returns data, is introduced, and a comprehensive description of the resulting realized stochastic volatility model is provided. The text contains a thorough explanation of several efficient sampling algorithms for latent log volatilities, as well as an illustration of parameter estimation and volatility prediction through empirical studies utilizing various asset return data, including the yen/US dollar exchange rate, the Dow Jones Industrial Average, and the Nikkei 225 stock index. This publication is highly recommended for readers with an interest in the latest developments in stochastic volatility models and realized stochastic volatility models, particularly in regards to financial risk management.
Book Synopsis Empirical Performance of Non-Affine Stochastic Volatility Models by : Øystein Sivertsen Jensen
Download or read book Empirical Performance of Non-Affine Stochastic Volatility Models written by Øystein Sivertsen Jensen and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis aims to test the empirical performance of 5 different non-affine specifications of the stochastic volatility model. The performance of the common affine square-root (SQR) specification is also investigated. The analysis is carried out by calibrating each model to option data by fitting the model-implied Black-Scholes volatilities to the marked-implied Black-Scholes volatilities. The data is collected from three months of very different financial climates; January 2007, October 2008, and July 2010. Three assets are considered; the S&P500 index, Apple Inc. and ExxonMobil Corporation. The findings confirm that model fit can be improved by choosing a non-affine model specification. The VAR model stands out as the best specification across all performance measures. The 3/2N model also consistently outperforms the SQR model. A separate estimation exercise based on maximum likelihood is also performed, confirming the better performance of the non-affine model specifications. The estimated parameters from the two estimation exercises show little sign of consistency, which indicates that all models are misspecified.
Book Synopsis A Model of the Short-term Interest Rate with Stochastic Volatility and Jumps by : Ravikumar Balasubramanian
Download or read book A Model of the Short-term Interest Rate with Stochastic Volatility and Jumps written by Ravikumar Balasubramanian and published by . This book was released on 1998 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Comparison of Alternative Models of the Short-term Interest Rate by : Xin Bo
Download or read book Comparison of Alternative Models of the Short-term Interest Rate written by Xin Bo and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper proposes a procedure for testing the alternative continuous time models of short term riskless interest rates. Parameters estimation and models comparison are presented using the Generalized Method of Moments. An empirical research to LIBOR in US dollar is given and found that the volatility of interest rate changes is to be less sensitive to the interest rate levels in contrast to previous findings. In addition the Brennan-Schwartz model is suggested to be superior to the others in term of data fit under daily observations, and CIR SR model cannot be rejected.
Book Synopsis Comparison of Alternative Models of the Short-term Interest Rate by : Xin Bo
Download or read book Comparison of Alternative Models of the Short-term Interest Rate written by Xin Bo and published by . This book was released on 2006 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper proposes a procedure for testing the alternative continuous time models of short term riskless interest rates. Parameters estimation and models comparison are presented using the Generalized Method of Moments. An empirical research to LIBOR in US dollar is given and found that the volatility of interest rate changes is to be less sensitive to the interest rate levels in contrast to previous findings. In addition the Brennan-Schwartz model is suggested to be superior to the others in term of data fit under daily observations, and CIR SR model cannot be rejected.
Book Synopsis Another Look at Models of the Short-Term Interest Rate by : Robin J. Brenner
Download or read book Another Look at Models of the Short-Term Interest Rate written by Robin J. Brenner and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The short-term rate of interest is fundamental to much of theoretical and empirical finance. Yet no consensus has emerged on the dynamics of its volatility. We show that models which parameterize volatility only as a function of interest rate levels tend to over-emphasize the sensitivity of volatility to levels and fail to model adequately the serial correlation in conditional variances. On the other hand, serial correlation-based models like GARCH models fail to capture adequately the relationship between interest rate levels and volatility. We introduce and test a new class of models for the dynamics of short- term interest rate volatility which allows volatility to depend on both interest rate levels and information shocks. Two important conclusions emerge. First, the sensitivity of interest rate volatility to interest rate levels has been overstated in the literature. While this relationship is important, adequately modeling volatility as a function of unexpected information shocks is also important. Second, we conclude that the volatility processes in many existing theoretical models of interest rates are misspecified, and suggest new paths toward improving the theory.
Book Synopsis Proceedings of the Thirteenth International Conference on Management Science and Engineering Management by : Jiuping Xu
Download or read book Proceedings of the Thirteenth International Conference on Management Science and Engineering Management written by Jiuping Xu and published by Springer. This book was released on 2019-06-19 with total page 837 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 13th International Conference on Management Science and Engineering Management (ICMSEM 2019), which was held at Brock University, Ontario, Canada on August 5–8, 2019. Exploring the latest ideas and pioneering research achievements in management science and engineering management, the respective contributions highlight both theoretical and practical studies on management science and computing methodologies, and present advanced management concepts and computing technologies for decision-making problems involving large, uncertain and unstructured data. Accordingly, the proceedings offer researchers and practitioners in related fields an essential update, as well as a source of new research directions.
Book Synopsis Stochastic Volatility and Jumps in Interest Rates by : Ren-Raw Chen
Download or read book Stochastic Volatility and Jumps in Interest Rates written by Ren-Raw Chen and published by . This book was released on 2010 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Long Memory Models of Interest Rates, the Term Structure, and Variance Bounds Tests by : Gary S. Shea
Download or read book Long Memory Models of Interest Rates, the Term Structure, and Variance Bounds Tests written by Gary S. Shea and published by . This book was released on 1985 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Regime Switching Stochastic Volatility and Short-Term Interest Rates by : Madhu Kalimipalli
Download or read book Regime Switching Stochastic Volatility and Short-Term Interest Rates written by Madhu Kalimipalli and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis A Simple Approach to the Estimation of Continuous Time CEV Stochastic Volatility Models of the Short-term Rate by : Fabio Fornari
Download or read book A Simple Approach to the Estimation of Continuous Time CEV Stochastic Volatility Models of the Short-term Rate written by Fabio Fornari and published by . This book was released on 2001 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Stochastic Volatility Model and Inference for the Term Structure of Interest by :
Download or read book A Stochastic Volatility Model and Inference for the Term Structure of Interest written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis builds a stochastic volatility model for the term structure of interest rates, which is also known as the dynamics of the yield curve. The main purpose of the model is to propose a parsimonious and plausible approach to capture some characteristics that conform to some empirical evidences and conventions. Eventually, the development reaches a class of multivariate stochastic volatility models, which is flexible, extensible, providing the existence of an inexpensive inference approach. The thesis points out some inconsistency among conventions and practice. First, yield curves and its related curves are conventionally smooth. But in the literature that these curves are modeled as random functions, the co-movement of points on the curve are usually assumed to be governed by some covariance structures that do not generate smooth random curves. Second, it is commonly agreed that the constant volatility is not a sound assumption, but stochastic volatilities have not been commonly considered in related studies. Regarding the above problems, we propose a multiplicative factor stochastic volatility model, which has a relatively simple structure. Though it is apparently simple, the inference is not, because of the presence of stochastic volatilities. We first study the sequential-Monte-Carlo-based maximum likelihood approach, which extends the perspectives of Gaussian linear state-space modeling. We propose a systematic procedure that guides the inference based on this approach. In addition, we also propose a saddlepoint approximation approach, which integrates out states. Then the state propagates by an exact Gaussian approximation. The approximation works reasonably well for univariate models. Moreover, it works even better for the multivariate model that we propose. Because we can enjoy the asymptotic property of the saddlepoint approximation.
