Energy crypto currencies and leading U.S. energy stock prices: are Fibonacci retracements profitable?

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Springer Science and Business Media Deutschland GmbH
This paper investigates the role of Fibonacci retracements levels, a popular technical analysis indicator, in predicting stock prices of leading U.S. energy companies and energy cryptocurrencies. The study methodology focuses on applying Fibonacci retracements as a system compared with the buy-and-hold strategy. Daily crypto and stock prices were obtained from the Standard & Poor's composite 1500 energy index and CoinMarketCap between November 2017 and January 2020. This study also examined if the combined Fibonacci retracements and the price crossover strategy result in a higher return per unit of risk. Our findings revealed that Fibonacci retracement captures energy stock price changes better than cryptos. Furthermore, most price violations were frequent during price falls compared to price increases, supporting that the Fibonacci instrument does not capture price movements during up and downtrends, respectively. Also, fewer consecutive retracement breaks were observed when the price violations were examined 3 days before the current break. Furthermore, the Fibonacci-based strategy resulted in higher returns relative to the naïve buy-and-hold model. Finally, complementing Fibonacci with the price cross strategy did not improve the results and led to fewer or no trades for some constituents. This study’s overall findings elucidate that, despite significant drops in oil prices, speculators (traders) can implement profitable strategies when using technical analysis indicators, like the Fibonacci retracement tool, with or without price crossover rules. © 2022, The Author(s).
This article is licensed under Creative Commons License and full text is openly accessible in CUD Digital Repository. The version of the scholarly record of this article is published in Financial Innovation (2022), available online at:
Energy cryptos, Energy stocks, Fibonacci retracements, Performance evaluation
Gurrib, I., Nourani, M., & Bhaskaran, R. K. (2022). Energy crypto currencies and leading U.S. energy stock prices: Are fibonacci retracements profitable? Financial Innovation, 8(1)