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The implementation of an adjusted relative strength index model in foreign currency and energy markets of emerging and developed economies

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  • Ikhlaas Gurrib
  • Firuz Kamalov

Abstract

This study proposes refinements to some weaknesses in the Relative Strength Index (RSI) model and tests its predictability over pre and post crisis periods for the most active USD based currency pairs, including two energy markets. A new model (AdRSI) is tested using daily data over 2001–2015. Benchmarked against RSI and buy-and-hold models, findings support an inverse relationship between energy and currency markets. While energy markets had relatively higher risk, Chinese yuan had the lowest annualized risk. AdRSI produced higher annualized returns, lower number of trades and higher annualized risk. Overall, the buy-and-hold model was superior with higher reward-to-volatility.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:macfem:v:12:y:2019:i:2:p:105-123
    DOI: 10.1080/17520843.2019.1574852
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    Citations

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    Cited by:

    1. Ikhlaas Gurrib & Mohammad Nourani & Rajesh Kumar Bhaskaran, 2022. "Energy crypto currencies and leading U.S. energy stock prices: are Fibonacci retracements profitable?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-27, December.
    2. Ikhlaas Gurrib & Firuz Kamalov & Elgilani Elshareif, 2021. "Can the Leading US Energy Stock Prices be Predicted using the Ichimoku Cloud?," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 41-51.
    3. 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.
    4. Firuz Kamalov & Linda Smail & Ikhlaas Gurrib, 2021. "Stock price forecast with deep learning," Papers 2103.14081, arXiv.org.
    5. Firuz Kamalov, 2019. "Forecasting significant stock price changes using neural networks," Papers 1912.08791, arXiv.org.
    6. Ikhlaas Gurrib, 2023. "Momentum in Low Carbon and Fossil Fuel Free Equity Investing," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 461-471, September.
    7. Guohua Zeng & Peiying Wu & Xinxin Yuan, 2023. "Has the Development of the Digital Economy Reduced the Regional Energy Intensity—From the Perspective of Factor Market Distortion, Industrial Structure Upgrading and Technological Progress?," Sustainability, MDPI, vol. 15(7), pages 1-19, March.
    8. Ikhlaas Gurrib & Firuz Kamalov & Olga Starkova & Adham Makki & Anita Mirchandani & Namrata Gupta, 2023. "Performance of Equity Investments in Sustainable Environmental Markets," Sustainability, MDPI, vol. 15(9), pages 1-28, May.
    9. Firuz Kamalov & Ho Hon Leung, 2020. "Outlier Detection in High Dimensional Data," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-16, March.

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