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Using VIX data to enhance technical trading signals

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  • James Kozyra
  • Camillo Lento

Abstract

The purpose of this article is to provide new insights into the relationship between technical analysis and implied market volatility (VIX) by calculating technical trading rules with the VIX price data, as opposed to the stock prices. Three trending trading rule signals are calculated on the prices of three major US indices and the VIX prices. The results reveal that the trading signals calculated with the VIX level provide large, statistically significant profits that are in excess of the profits from the traditional computation. Sub-period analysis reveals that technical trading rules were most (least) profitable during the period with the highest (lowest) volatility levels.

Suggested Citation

  • James Kozyra & Camillo Lento, 2011. "Using VIX data to enhance technical trading signals," Applied Economics Letters, Taylor & Francis Journals, vol. 18(14), pages 1367-1370.
    • Handle: RePEc:taf:apeclt:v:18:y:2011:i:14:p:1367-1370
    DOI: 10.1080/13504851.2010.537623
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    Citations

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    Cited by:

    1. Day, Min-Yuh & Ni, Yensen & Huang, Paoyu, 2019. "Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 349-372.
    2. Jadhao, Gaurav & Chandra, Abhijeet, 2017. "Application of VIX and entropy indicators for portfolio rotation strategies," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1367-1371.
    3. Zhu, Sha & Liu, Qiuhong & Wang, Yan & Wei, Yu & Wei, Guiwu, 2019. "Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    4. Nazarova Jekaterina, 2015. "Investment Planning in the Context of Business Cycle Volatility," Economics and Business, Sciendo, vol. 27(1), pages 53-57, August.
    5. Imlak Shaikh & Puja Padhi, 2014. "The forecasting performance of implied volatility index: evidence from India VIX," Economic Change and Restructuring, Springer, vol. 47(4), pages 251-274, November.
    6. Camillo Lento & Nikola Gradojevic, 2022. "The Profitability of Technical Analysis during the COVID-19 Market Meltdown," JRFM, MDPI, vol. 15(5), pages 1-19, April.
    7. Tzu‐Pu Chang, 2021. "Buy Low and Sell High: The 52‐Week Price Range and Predictability of Returns," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 336-344, March.

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