Local adaptive multiplicative error models for high-frequency forecasts

Arbeitspapier

We 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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: SFB 649 Discussion Paper ; No. 2012-031

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Duration Analysis; Optimal Timing Strategies ; Model Construction and Estimation ; Forecasting Models; Simulation Methods ; Asset Pricing; Trading Volume; Bond Interest Rates ; Financial Forecasting and Simulation
• Thema: multiplicative error model ; local adaptive modelling ; high-frequency processes ; trading volume ; forecasting ; Statistische Bestandsanalyse ; Prognoseverfahren ; Theorie ; Schätzung ; Börsenkurs ; USA

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Härdle, Wolfgang Karl ; Hautsch, Nikolaus ; Mihoci, Andrija
• Ereignis: Veröffentlichung
• (wer): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (wo): Berlin
• (wann): 2012

Weitere Informationen

• Handle: http://hdl.handle.net/10419/79578
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ