Forecasting commodity prices out-of-sample: Can technical indicators help?

被引:59
作者
Wang, Yudong [1 ]
Liu, Li [2 ]
Wu, Chongfeng [3 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Econ & Management, Nanjing, Peoples R China
[2] Nanjing Audit Univ, Sch Finance, Nanjing, Peoples R China
[3] Antai Coll Econ & Management, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Forecasting; Commodity price; Technical indicators; Predictive regression; Forecast combination; EQUITY PREMIUM PREDICTION; EXCESS CO-MOVEMENT; CRUDE-OIL PRICES; COMBINATION FORECASTS; MOMENTUM STRATEGIES; DENSITY FORECASTS; REAL PRICE; RETURNS; MARKETS; RISK;
D O I
10.1016/j.ijforecast.2019.08.004
中图分类号
F [经济];
学科分类号
02 ;
摘要
Economic variables are often used for forecasting commodity prices, but technical indicators have received much less attention in the literature. This paper demonstrates the predictability of commodity price changes using many technical indicators. Technical indicators are stronger predictors than economic indicators, and their forecasting performances are not affected by the problems of data mining or time changes. An investor with mean-variance preference receives utility gains of between 104.4 and 185.5 basis points from using technical indicators. Further analysis shows that technical indicators also perform better than economic variables for forecasting the density of commodity price changes. (C) 2019 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:666 / 683
页数:18
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