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Market Timing with Moving Averages for Fossil Fuel and Renewable Energy Stocks

Chia-Lin Chang (), Jukka Ilomäki, Hannu Laurila and Michael McAleer

No EI2018-44, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: The paper examines whether the moving average (MA) technique can beat random market timing in traditional and newer branches of an industrial sector. The sector considered is the energy sector, divided into balanced stock portfolios of fossil and renewable energy companies. Eight representative firms are selected for both portfolios. The paper finds that MA timing outperforms random timing with the portfolio of renewable energy companies, whereas the result is less clear with the portfolio of fossil energy companies. Thus, there seems to be more forecastable stochastic trends in sunrise branches than in sunset branches.

Keywords: Moving averages; market timing; industrial sector; energy sector; fossil fuels; renewable; energy; random timing; sunrise branches; sunset branches (search for similar items in EconPapers)
JEL-codes: C22 C32 L71 L72 Q16 Q42 Q47 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ene and nep-env
Date: 2018-09-01
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https://repub.eur.nl/pub/111616/EI2018-44.pdf (application/pdf)

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Working Paper: Market Timing with Moving Averages for Fossil Fuel and Renewable Energy Stocks (2018) Downloads
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