Optimal Portfolio Choice Under Decision-Based Model Combinations

Arbeitspapier

We propose a novel Bayesian model combination approach where the combination weights depend on the past forecasting performance of the individual models entering the combination through a utility-based objective function. We use this approach in the context of stock return predictability and optimal portfolio decisions, and investigate its forecasting performance relative to a host of existing combination schemes. We find that our method produces markedly more accurate predictions than the existing model combinations, both in terms of statistical and economic measures of out-of-sample predictability. We also investigate the role of our model combination method in the presence of model instabilities, by considering predictive regressions that feature time-varying regression coe cients and stochastic volatility. We find that the gains from using our model combination method increase significantly when we allow for instabilities in the individual models entering the combination.

Angaben zum Objekt

• ISBN: 978-82-7553-835-0
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Working Paper ; No. 15/2014

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Bayesian Analysis: General ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Portfolio Choice; Investment Decisions ; Asset Pricing; Trading Volume; Bond Interest Rates
• Thema: Bayesian econometrics ; time-varying parameters ; model combinations ; portfolio choice

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Pettenuzzo, Davide ; Ravazzolo, Francesco
• Ereignis: Veröffentlichung
• (wer): Norges Bank
• (wo): Oslo
• (wann): 2014

Weitere Informationen

• Handle: http://hdl.handle.net/10419/210064
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ