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Technical Analysis, Energy Cryptos and Energy Equity Markets

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  • Ikhlaas Gurrib

    (Canadian University Dubai, Faculty of Management, School of Graduate Studies, United Arab Emirates)

Abstract

The aim of this study is to investigate if Fibonacci retracements levels, as a popular technical analysis indicator, can serve to predict stock prices of leading US energy companies and energy crypto currencies. The methodology centers on the application of Fibonacci retracements as a trading system. Daily stock prices from the top ten constituents of the S&P Composite 1500 Energy Index are sourced, spanning from 21st November 2017 to 17th January 2020. The performance of the Fibonacci's tool is captured using the Sharpe measure. The model is also benchmarked against the naïve buy-and-hold strategy. We also tested if the use of Fibonacci retracements, coupled with a price crossover strategy results into higher return per unit of risk. Findings support the Fibonacci retracement tool captures the price movements of energy stocks better than energy cryptos. Further, price violations tend occur more during downtrends compared to uptrends, suggesting the Fibonacci tool does not capture price increases during downtrends as well as price decreases during uptrends. Less consecutive retracement breaks occurred as we move from 1 to 3 days prior. While a Fibonacci based strategy resulted in superior returns to a naïve buy and hold model, the Sharpe and Sharpe per trade values were low. Complementing the Fibonacci tool with a price cross strategy did not improve the results significantly, and resulted in fewer or no trades for some constituents.

Suggested Citation

  • Ikhlaas Gurrib, 2022. "Technical Analysis, Energy Cryptos and Energy Equity Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 249-267, March.
    • Handle: RePEc:eco:journ2:2022-02-28
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    References listed on IDEAS

    as
    1. Neely, Christopher J. & Weller, Paul A. & Ulrich, Joshua M., 2009. "The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(2), pages 467-488, April.
    2. Shashi Gupta & Himanshu Choudhary & D.R. Agarwal, 2017. "Hedging Efficiency of Indian Commodity Futures," Paradigm, , vol. 21(1), pages 1-20, June.
    3. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    4. Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: What gain for investors?," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3878-3889.
    5. Lui, Yu-Hon & Mole, David, 1998. "The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 535-545, June.
    6. Ikhlaas Gurrib & Qian Long Kweh & Davide Contu & Firuz Kamalov, 2021. "COVID-19, Short-selling Ban and Energy Stock Prices," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 1(1), pages 1-4.
    7. Shynkevich, Andrei, 2016. "Predictability in bond returns using technical trading rules," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 55-69.
    8. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
    9. Anna Creti & Duc Khuong Nguyen, 2015. "Energy markets׳ financialization, risk spillovers, and pricing models," Post-Print hal-01517413, HAL.
    10. Szakmary, Andrew C. & Shen, Qian & Sharma, Subhash C., 2010. "Trend-following trading strategies in commodity futures: A re-examination," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 409-426, February.
    11. Ikhlaas Gurrib & Firuz Kamalov, 2019. "The implementation of an adjusted relative strength index model in foreign currency and energy markets of emerging and developed economies," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 12(2), pages 105-123, May.
    12. repec:dau:papers:123456789/14774 is not listed on IDEAS
    13. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    14. Olson, Dennis, 2004. "Have trading rule profits in the currency markets declined over time?," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 85-105, January.
    15. Fama, Eugene F, 1972. "Components of Investment Performance," Journal of Finance, American Finance Association, vol. 27(3), pages 551-567, June.
    16. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
    17. Wing-Keung Wong & Meher Manzur & Boon-Kiat Chew, 2003. "How rewarding is technical analysis? Evidence from Singapore stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 543-551.
    18. Sukanto Bhattacharya & Kuldeep Kumar, 2006. "A Computational Exploration of the Efficacy of Fibonacci Sequences in Technical Analysis and Trading," Annals of Economics and Finance, Society for AEF, vol. 7(1), pages 185-196, May.
    19. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    20. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    21. Ikhlaas Gurrib, 2018. "Can an Energy Futures Index Predict US Stock Market Index Movements?," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 230-240.
    22. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    23. Czudaj, Robert L., 2019. "Crude oil futures trading and uncertainty," Energy Economics, Elsevier, vol. 80(C), pages 793-811.
    24. Ioannis Psaradellis & Jason Laws & Athanasios A. Pantelous & Georgios Sermpinis, 2019. "Performance of technical trading rules: evidence from the crude oil market," The European Journal of Finance, Taylor & Francis Journals, vol. 25(17), pages 1793-1815, November.
    25. Smith, David M. & Wang, Na & Wang, Ying & Zychowicz, Edward J., 2016. "Sentiment and the Effectiveness of Technical Analysis: Evidence from the Hedge Fund Industry," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(6), pages 1991-2013, December.
    26. Gencay, Ramazan, 1999. "Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules," Journal of International Economics, Elsevier, vol. 47(1), pages 91-107, February.
    27. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
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    More about this item

    Keywords

    Energy Cryptos; Energy Stocks; Fibonacci Retracements; Performance Evaluation;
    All these keywords.

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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