Modeling and Forecasting Interval Time Series with Threshold Models: An Application to S&P500 Index Returns
Over recent years several methods to deal with high-frequency data (economic, financial and other) have been proposed in the literature. An interesting example is for instance interval valued time series described by the temporal evolution of high and low prices of an asset. In this paper a new class of threshold models capable of capturing asymmetric e¤ects in interval-valued data is introduced as well as new forecast loss functions and descriptive statistics of the forecast quality proposed. Least squares estimates of the threshold parameter and the regression slopes are obtained; and forecasts based on the proposed threshold model computed. A new forecast procedure based on the combination of this model with the k nearest neighbors method is introduced. To illustrate this approach, we report an application to a weekly sample of S&P500 index returns. The results obtained are encouraging and compare very favorably to available procedures.
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- Hansen, Bruce E, 1996.
"Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis,"
Econometric Society, vol. 64(2), pages 413-30, March.
- Hansen, B.E., 1991. "Inference when a Nuisance Parameter is Not Identified Under the Null Hypothesis," RCER Working Papers 296, University of Rochester - Center for Economic Research (RCER).
- Tom Doan, . "TAR: RATS procedure to estimate a threshold autoregression, tests for threshold effect," Statistical Software Components RTS00209, Boston College Department of Economics.
- Tom Doan, . "RATS programs to replicate Hansen's threshold estimation and testing results," Statistical Software Components RTZ00091, Boston College Department of Economics.
- Clements, M.P. & Smith J., 1998. "Evaluating The Forecast of Densities of Linear and Non-Linear Models: Applications to Output Growth and Unemployment," The Warwick Economics Research Paper Series (TWERPS) 509, University of Warwick, Department of Economics.
- Clements, Michael P. & Smith, Jeremy, 1997. "The performance of alternative forecasting methods for SETAR models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 463-475, December.
- Michael Dueker & Martin Sola & Fabio Spagnolo, 2007.
"Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting,"
5_2007, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
- Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
- Michael J. Dueker & Martin Sola & Fabio Spagnolo, 2006. "Contemporaneous threshold autoregressive models: estimation, testing and forecasting," Working Papers 2003-024, Federal Reserve Bank of St. Louis.
- Michael Dueker & Martin Sola & Fabio Spagnolo, 2006. "Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting," Department of Economics Working Papers 2006-04, Universidad Torcuato Di Tella.
- Billard L. & Diday E., 2003. "From the Statistics of Data to the Statistics of Knowledge: Symbolic Data Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 470-487, January.
- Francis X. Diebold & Jose A. Lopez, 1996.
"Forecast Evaluation and Combination,"
NBER Technical Working Papers
0192, National Bureau of Economic Research, Inc.
- Clements, Michael P & Smith, Jeremy, 1999.
"A Monte Carlo Study of the Forecasting Performance of Empirical SETAR Models,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 14(2), pages 123-41, March-Apr.
- Clements, Michael P & Smith, Jeremy, 1996. "A Monte Carlo Study of the Forecasting Performance of Empirical Setar Models," The Warwick Economics Research Paper Series (TWERPS) 464, University of Warwick, Department of Economics.
- Simon M. Potter, 1993.
"A Nonlinear Approach to U.S. GNP,"
UCLA Economics Working Papers
693, UCLA Department of Economics.
- Bruce E. Hansen, 2000.
"Sample Splitting and Threshold Estimation,"
Econometric Society, vol. 68(3), pages 575-604, May.
- Yin-Wong Cheung, 2007.
"An empirical model of daily highs and lows,"
International Journal of Finance & Economics,
John Wiley & Sons, Ltd., vol. 12(1), pages 1-20.
- Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
- Chou, Ray Yeutien, 2005. "Forecasting Financial Volatilities with Extreme Values: The Conditional Autoregressive Range (CARR) Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 561-82, June.
- Philip Rothman, 1998.
"Forecasting Asymmetric Unemployment Rates,"
The Review of Economics and Statistics,
MIT Press, vol. 80(1), pages 164-168, February.
- García-Ascanio, Carolina & Maté, Carlos, 2010. "Electric power demand forecasting using interval time series: A comparison between VAR and iMLP," Energy Policy, Elsevier, vol. 38(2), pages 715-725, February.
- J. Barkley Rosser, 2009. "Introduction," Chapters, in: Handbook of Research on Complexity, chapter 1 Edward Elgar.
- De Gooijer, Jan G. & Kumar, Kuldeep, 1992. "Some recent developments in non-linear time series modelling, testing, and forecasting," International Journal of Forecasting, Elsevier, vol. 8(2), pages 135-156, October.
- Zellner, Arnold & Tobias, Justin, 2004.
"A Note on Aggregation, Disaggregation and Forecasting Performance,"
Staff General Research Papers
12371, Iowa State University, Department of Economics.
- Tobias, Justin & Zellner, Arnold, 2000. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers 12024, Iowa State University, Department of Economics.
- Fiess, Norbert M & MacDonald, Ronald, 2002. "Towards the fundamentals of technical analysis: analysing the information content of High, Low and Close prices," Economic Modelling, Elsevier, vol. 19(3), pages 353-374, May.
- De Gooijer, Jan G. & De Bruin, Paul T., 1998. "On forecasting SETAR processes," Statistics & Probability Letters, Elsevier, vol. 37(1), pages 7-14, January.
- Henry, Olan T & Olekalns, Nilss & Summers, Peter M, 2001. "Exchange Rate Instability: A Threshold Autoregressive Approach," The Economic Record, The Economic Society of Australia, vol. 77(237), pages 160-66, June.
- Beckers, Stan, 1983. "Variances of Security Price Returns Based on High, Low, and Closing Prices," The Journal of Business, University of Chicago Press, vol. 56(1), pages 97-112, January.
- Lima Neto, Eufrásio de A. & de Carvalho, Francisco de A.T., 2010. "Constrained linear regression models for symbolic interval-valued variables," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 333-347, February.
- Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range-Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, 06.
- Makridakis, Spyros, 1989. "Why combining works?," International Journal of Forecasting, Elsevier, vol. 5(4), pages 601-603.
- Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
- G�ran Therborn & K.C. Ho, 2009. "Introduction," City, Taylor & Francis Journals, vol. 13(1), pages 53-62, March.
- Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt’s exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759.
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