Market timing with moving averages for fossil fuel and renewable energy stocks

被引:12
作者
Chang, Chia-Lin [1 ,2 ,3 ]
Ilomaki, Jukka [4 ]
Laurila, Hannu [4 ]
McAleer, Michael [3 ,5 ,6 ,7 ,8 ,9 ]
机构
[1] Natl Chung Hsing Univ, Dept Appl Econ, Taichung, Taiwan
[2] Natl Chung Hsing Univ, Dept Finance, Taichung, Taiwan
[3] Asia Univ, Dept Finance, Taichung, Taiwan
[4] Tampere Univ, Fac Management & Business, Tampere, Finland
[5] Univ Sydney, Discipline Business Analyt, Business Sch, Sydney, NSW, Australia
[6] Erasmus Univ, Erasmus Sch Econ, Econometr Inst, Rotterdam, Netherlands
[7] Univ Complutense Madrid, Dept Econ Anal, Madrid, Spain
[8] Univ Complutense Madrid, ICAE, Madrid, Spain
[9] Yokohama Natl Univ, Inst Adv Sci, Yokohama, Kanagawa, Japan
基金
澳大利亚研究理事会;
关键词
Moving averages; Market timing; Energy sector; Fossil fuels; Renewable energy; Random timing; AUTOREGRESSIVE TIME-SERIES; OIL PRICES; CLEAN ENERGY; PERFORMANCE; RISK; HYPOTHESIS;
D O I
10.1016/j.egyr.2020.06.029
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The paper examines whether the Moving Average (MA) technique can outperform random market timing in the energy sector, compiled of fossil and renewable energy producers. According to the Capital Asset Pricing Model, random timing is a superior trading strategy in the long run. However, the MA technique may be more successful, if there are predictable stochastic trends in the price series. In the paper, eight representative firms are selected for both fossil and renewable portfolios with actually tradable stocks in order to create two Exchange-Traded Funds (ETF). The paper finds that MA timing outperforms random timing for the ETF of renewable energy companies, but not for the ETF of fossil energy companies. (C) 2020 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:1798 / 1810
页数:13
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