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Correlation estimation using components of Japanese candlesticks

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  • V. Popov

Abstract

Using the wick’s difference from the classical Japanese candlestick representation of daily open, high, low, close prices brings efficiency when estimating the correlation in a bivariate Brownian motion. An interpretation of the correlation estimator given in [Rogers, L.C.G. and Zhou, F., Estimating correlation from high, low, opening and closing prices. Ann. Appl. Probab., 2008, 18(2), 813–823] in the light of wicks’ difference allows us to suggest modifications, which lead to an increased efficiency and robustness over the baseline model. An empirical study of four major financial markets confirms the advantages of the modified estimator.

Suggested Citation

  • V. Popov, 2016. "Correlation estimation using components of Japanese candlesticks," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1615-1630, October.
    • Handle: RePEc:taf:quantf:v:16:y:2016:i:10:p:1615-1630
    DOI: 10.1080/14697688.2016.1157625
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    1. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
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    4. L. C. G. Rogers & Fanyin Zhou, 2008. "Estimating correlation from high, low, opening and closing prices," Papers 0804.0162, arXiv.org.
    5. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    6. Karim Bannouh & Dick van Dijk & Martin Martens, 2009. "Range-Based Covariance Estimation Using High-Frequency Data: The Realized Co-Range -super-," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 341-372, Fall.
    7. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
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    Cited by:

    1. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.

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