A Bayesian Analysis of Stur Models

• Autorzy: Jacek Kwiatkowski
• Języki publikacji: EN

Abstrakty

EN

Chapter 2 is a study on stochastic unit root models (STUR) under the Bayesian estimation and testing. The Gibbs sampling algorithm is used. The parameters of the model follow an autoregressive mechanism. It has been specified that the series tend to possess one unit root in the long run, while in the short run the roots may be stationary or explosive. An application for the stock returns, for weekly sampling frequencies, has shown that three of ten series exhibit symptoms of time-varying unit root. (fragment of text)

Słowa kluczowe

EN

Stochastic models; Bayesian estimation; Autoregression models

PL

Modele stochastyczne; Estymacja bayesowska; Modele autoregresji

• Czasopismo: FindEcon Monograph Series : advances in financial market analysis
• Rocznik: 2006
• Numer: nr 2 Financial markets : principles of modeling forecasting and decision-making
• Strony: 37--48

Twórcy

autor

Jacek Kwiatkowski

• Nicolaus Copernicus University in Toruń, Poland

Bibliografia

• Box G. E. P., Jenkins G. M. (1976), Time Series Analysis: Forecasting and Control, San Francisco: Holden-Day.
• Carlin B. P., Louis T. A. (2000), Bayes and Empirical Bayes Methods for Data Analysis, New York: Chapman & Hall.
• Gelman A., Carlin J., Stern H., Rubin D. (1997), Bayesian Data Analysis, London: Chapman & Hall.
• Granger C. W. J., Swanson N. R. (1997), "An Introduction to Stochastic Unit-root Process", Journal of Econometrics, 80, 35-62.
• Jones C. R., Marriott J. M. (1999), "A Bayesian Analysis of Stochastic Unit Root Models", Bayesian Statistics, 6, 785-794.
• Jostova G., Philipov A. (2004), "Bayesian Analysis of Stochastic Betas", Journal of Financial and Quantitative Analysis (forthcoming).
• Kwiatkowski J. (2004), "Maximum Likelihood Estimation of Stochastic Unit Root Models with GARCH Disturbances", working paper version.
• Kwiatkowski J., Osińska M. (2004), "Forecasting STUR Processes. A Comparison to Threshold and GARCH Models", working paper version.
• Leybourne S. J., McCabe B. P. M., Mills T. C. (1996), "Randomized Unit Root Processes for Modelling and Forecasting Financial Time Series: Theory and Applications", Journal of Forecasting, 15, 253-270.
• Leybourne S. J., McCabe B. P. M., Tremayne A. R (1996), "Can Economic Time Series Be Differenced to Stationarity?", Journal of Business and Economic Statistics, 14, 435-446.
• Newton, M. A., Raftery A. E. (1994), "Approximate Bayesian Inference by the Weighted Likelihood Bootstrap (with Discussion)", Journal of the Royal Statistical Society, B, 56, 3-48.
• Osiewalski J., Pipien M. (2004), "Bayesian Comparison of Bivariate ARCH-type Models for Main Exchange Rates in Poland", Journal of Econometrics, 123, 371-391.
• Sollis R., Leybourne S. J., Newbold P. (2000), "Stochastic Unit Roots Modelling of Stock Price Indices", Applied Financial Economics, 10, 311-315.