Technical Analysis, Energy Cryptos and Energy Equity Markets
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 syst...
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| Format: | Article |
| Language: | English |
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EconJournals
2022-03-01
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| Series: | International Journal of Energy Economics and Policy |
| Subjects: | |
| Online Access: | https://econjournals.com/index.php/ijeep/article/view/11015 |
| _version_ | 1797914304154959872 |
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| author | Ikhlaas Gurrib |
| author_facet | Ikhlaas Gurrib |
| author_sort | Ikhlaas Gurrib |
| collection | DOAJ |
| description |
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.
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| first_indexed | 2024-04-10T12:24:40Z |
| format | Article |
| id | doaj.art-96c9e1c7e042471db4cbb4ee152e6a49 |
| institution | Directory Open Access Journal |
| issn | 2146-4553 |
| language | English |
| last_indexed | 2024-04-10T12:24:40Z |
| publishDate | 2022-03-01 |
| publisher | EconJournals |
| record_format | Article |
| series | International Journal of Energy Economics and Policy |
| spelling | doaj.art-96c9e1c7e042471db4cbb4ee152e6a492023-02-15T16:15:18ZengEconJournalsInternational Journal of Energy Economics and Policy2146-45532022-03-0112210.32479/ijeep.11015Technical Analysis, Energy Cryptos and Energy Equity MarketsIkhlaas Gurrib0Canadian University Dubai, Faculty of Management, School of Graduate Studies, United Arab Emirates 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. https://econjournals.com/index.php/ijeep/article/view/11015Energy CryptosEnergy StocksFibonacci RetracementsPerformance Evaluation |
| spellingShingle | Ikhlaas Gurrib Technical Analysis, Energy Cryptos and Energy Equity Markets International Journal of Energy Economics and Policy Energy Cryptos Energy Stocks Fibonacci Retracements Performance Evaluation |
| title | Technical Analysis, Energy Cryptos and Energy Equity Markets |
| title_full | Technical Analysis, Energy Cryptos and Energy Equity Markets |
| title_fullStr | Technical Analysis, Energy Cryptos and Energy Equity Markets |
| title_full_unstemmed | Technical Analysis, Energy Cryptos and Energy Equity Markets |
| title_short | Technical Analysis, Energy Cryptos and Energy Equity Markets |
| title_sort | technical analysis energy cryptos and energy equity markets |
| topic | Energy Cryptos Energy Stocks Fibonacci Retracements Performance Evaluation |
| url | https://econjournals.com/index.php/ijeep/article/view/11015 |
| work_keys_str_mv | AT ikhlaasgurrib technicalanalysisenergycryptosandenergyequitymarkets |