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

Chia Lin Chang; Jukka Ilomäki; Hannu Laurila; Michael McAleer

doi:10.1016/j.egyr.2020.06.029

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

Chia Lin Chang, Jukka Ilomäki, Hannu Laurila, Michael McAleer^*

^*Corresponding author for this work

Econometrics

Research output: Contribution to journal › Article › Academic › peer-review

11 Citations (Scopus)

24 Downloads (Pure)

Abstract

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.

Original language	English
Pages (from-to)	1798-1810
Number of pages	13
Journal	Energy Reports
Volume	6
DOIs	https://doi.org/10.1016/j.egyr.2020.06.029
Publication status	Published - Nov 2020

Bibliographical note

Funding Information:
The authors are most grateful to two reviewers for very helpful comments and suggestions. For financial support, the first author wishes to acknowledge the Ministry of Science and Technology (MOST) , Taiwan, and the fourth author is grateful to the Australian Research Council and Ministry of Science and Technology (MOST) , Taiwan.

Publisher Copyright:
© 2020 The Authors

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.egyr.2020.06.029

1-s2.0-S2352484720300755-mainFinal published version, 1.35 MBLicence: CC BY-NC-ND

Cite this

@article{b00956190456404c8fda26a9a47a691e,

title = "Market timing with moving averages for fossil fuel and renewable energy stocks",

abstract = "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.",

author = "Chang, {Chia Lin} and Jukka Ilom{\"a}ki and Hannu Laurila and Michael McAleer",

note = "Funding Information: The authors are most grateful to two reviewers for very helpful comments and suggestions. For financial support, the first author wishes to acknowledge the Ministry of Science and Technology (MOST) , Taiwan, and the fourth author is grateful to the Australian Research Council and Ministry of Science and Technology (MOST) , Taiwan. Publisher Copyright: {\textcopyright} 2020 The Authors",

year = "2020",

month = nov,

doi = "10.1016/j.egyr.2020.06.029",

language = "English",

volume = "6",

pages = "1798--1810",

journal = "Energy Reports",

issn = "2352-4847",

publisher = "Elsevier Ltd.",

}

TY - JOUR

T1 - Market timing with moving averages for fossil fuel and renewable energy stocks

AU - Chang, Chia Lin

AU - Ilomäki, Jukka

AU - Laurila, Hannu

AU - McAleer, Michael

N1 - Funding Information: The authors are most grateful to two reviewers for very helpful comments and suggestions. For financial support, the first author wishes to acknowledge the Ministry of Science and Technology (MOST) , Taiwan, and the fourth author is grateful to the Australian Research Council and Ministry of Science and Technology (MOST) , Taiwan. Publisher Copyright: © 2020 The Authors

PY - 2020/11

Y1 - 2020/11

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85087590114&partnerID=8YFLogxK

U2 - 10.1016/j.egyr.2020.06.029

DO - 10.1016/j.egyr.2020.06.029

M3 - Article

AN - SCOPUS:85087590114

SN - 2352-4847

VL - 6

SP - 1798

EP - 1810

JO - Energy Reports

JF - Energy Reports

ER -

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

Abstract

Bibliographical note

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this