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Optimal Portfolio Choice Under Decision‐Based Model Combinations
Author(s) -
Pettenuzzo Davide,
Ravazzolo Francesco
Publication year - 2016
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2502
Subject(s) - predictability , portfolio , econometrics , volatility (finance) , computer science , stock (firearms) , stochastic volatility , aggregate (composite) , mathematical optimization , economics , mathematics , statistics , financial economics , mechanical engineering , materials science , engineering , composite material
Summary We propose a density combination approach featuring combination weights that depend on the past forecast performance of the individual models entering the combination through a utility‐based objective function. We apply this model combination scheme to forecast stock returns, both at the aggregate level and by industry, and investigate its forecasting performance relative to a host of existing combination methods, both within the class of linear and time‐varying coefficients, stochastic volatility models. Overall, we find that our combination scheme produces markedly more accurate predictions than the existing alternatives, both in terms of statistical and economic measures of out‐of‐sample predictability. Copyright © 2016 John Wiley & Sons, Ltd.