Local Adaptive Multiplicative Error Models for High-Frequency Forecasts
AbstractWe propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time. Analyzing one-minute cumulative trading volumes of five large NASDAQ stocks in 2008, we show that local windows of approximately 3 to 4 hours are reasonable to capture parameter variations while balancing modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM where local estimation windows are fixed on an ad hoc basis.
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Bibliographic InfoPaper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2012-031.
Length: 32 pages
Date of creation: Apr 2012
Date of revision:
multiplicative error model; local adaptive modelling; high-frequency processes; trading volume; forecasting;
Find related papers by JEL classification:
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-05-08 (All new papers)
- NEP-ECM-2012-05-08 (Econometrics)
- NEP-ETS-2012-05-08 (Econometric Time Series)
- NEP-FOR-2012-05-08 (Forecasting)
- NEP-MST-2012-05-08 (Market Microstructure)
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- Hautsch, Nikolaus & Malec, Peter & Schienle, Melanie, 2010.
"Capturing the zero: A new class of zero-augmented distributions and multiplicative error processes,"
CFS Working Paper Series
2010/19, Center for Financial Studies (CFS).
- Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(1), pages 89-121, December.
- Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2010. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2010-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Hautsch, Nikolaus & Malec, Peter & Schienle, Melanie, 2011. "Capturing the zero: A new class of zero-augmented distributions and multiplicative error processes," CFS Working Paper Series 2011/25, Center for Financial Studies (CFS).
- Meitz, Mika & Terasvirta, Timo, 2006.
"Evaluating Models of Autoregressive Conditional Duration,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 24, pages 104-124, January.
- Meitz, Mika & Teräsvirta, Timo, 2004. "Evaluating models of autoregressive conditional duration," Working Paper Series in Economics and Finance 557, Stockholm School of Economics, revised 13 Dec 2004.
- Diebold, Francis X & Mariano, Roberto S, 1995.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 13(3), pages 253-63, July.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- P. Č�žek & W. H�rdle & V. Spokoiny, 2009. "Adaptive pointwise estimation in time-inhomogeneous conditional heteroscedasticity models," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 248-271, 07.
- Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2009.
"Intra-daily Volume Modeling and Prediction for Algorithmic Trading,"
Econometrics Working Papers Archive
wp2009_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(3), pages 489-518, Summer.
- Ying Chen & Wolfgang Härdle & Uta Pigorsch, 2009.
"Localized Realized Volatility Modelling,"
SFB 649 Discussion Papers
SFB649DP2009-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
- Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
- Manganelli, Simone, 2005.
"Duration, volume and volatility impact of trades,"
Journal of Financial Markets,
Elsevier, vol. 8(4), pages 377-399, November.
- Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
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