Forecasting stock returns under economic constraints

• 成果类型: Article
• 署名作者: Pettenuzzo, Davide; Timmermann, Allan; Valkanov, Rossen
• 署名单位: Brandeis University; University of California System; University of California San Diego; Centre for Economic Policy Research - UK; CREATES
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2014.07.015
• 发表日期: 2014
• 页码: 517-553
• 关键词: Economic constraints; Sharpe ratio; Equity premium predictions

摘要

We propose a new approach to imposing economic constraints on time series forecasts of the equity premium. Economic constraints are used to modify the posterior distribution of the parameters of the predictive return regression in a way that better allows the model to learn from the data. We consider two types of constraints: non-negative equity premia and bounds on the conditional Sharpe ratio, the latter of which incorporates time-varying volatility in the predictive regression framework. Empirically, we find that economic constraints systematically reduce uncertainty about model parameters, reduce the risk of selecting a poor forecasting model, and improve both statistical and economic measures of out-of-sample forecast performance. (C) 2014 Elsevier B.V. All rights reserved.