TY - JOUR
T1 - Extended switching regression models with time-varying probabilities for combining forecasts
AU - Preminger, Arie
AU - Ben-Zion, Uri
AU - Wettstein, David
N1 - Funding Information:
We are grateful for several comments from seminar participants at the FFM 2003 conference, Tel Aviv University and the Technion – Israel institute of Technology. We thank Ezra Einy for several insightful comments and suggestions. We also thank two anonymous referees and an editor for several important questions and suggestions. We are grateful to the Federal Reserve Bank of St. Louis and BIS for providing access to their databases. Preminger gratefully acknowledges research support from the Kreitman Foundation.
PY - 2006/10/1
Y1 - 2006/10/1
N2 - This paper introduces a new methodology, which extends the well-known switching regression model. The extension is via the introduction of several latent state variables, each one of which influencing a disjoint set of the model parameters. Furthermore, the probability distribution of the state variables is allowed to vary over time. This model is called the time varying extended switching regression (TV-ESR) model. The model is used to combine volatility forecasts of several currencies (JPY/USD, GBP/USD, and CHF/USD). A detailed comparison of the forecasts generated by the TV-ESR approach is made with those of traditional linear combining procedures and other methods for combining forecasts derived from the switching regression model. On the basis of out-of-sample forecast encompassing tests as well as other measures for forecasting accuracy, results indicate that the use of this new method yields overall better forecasts than those generated by competing models.
AB - This paper introduces a new methodology, which extends the well-known switching regression model. The extension is via the introduction of several latent state variables, each one of which influencing a disjoint set of the model parameters. Furthermore, the probability distribution of the state variables is allowed to vary over time. This model is called the time varying extended switching regression (TV-ESR) model. The model is used to combine volatility forecasts of several currencies (JPY/USD, GBP/USD, and CHF/USD). A detailed comparison of the forecasts generated by the TV-ESR approach is made with those of traditional linear combining procedures and other methods for combining forecasts derived from the switching regression model. On the basis of out-of-sample forecast encompassing tests as well as other measures for forecasting accuracy, results indicate that the use of this new method yields overall better forecasts than those generated by competing models.
KW - Forecast combining
KW - TV-ESR models
KW - Volatility modelling
UR - http://www.scopus.com/inward/record.url?scp=33748775738&partnerID=8YFLogxK
U2 - 10.1080/13518470500039360
DO - 10.1080/13518470500039360
M3 - Article
AN - SCOPUS:33748775738
SN - 1351-847X
VL - 12
SP - 455
EP - 472
JO - European Journal of Finance
JF - European Journal of Finance
IS - 6-7
ER -