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Profitability of the On-Balance Volume Indicator

Author

Listed:
  • William Wai Him Tsang

    (Department of Economics, The Chinese University of Hong Kong)

  • Terence Tai Leung Chong

    (Department of Economics, The Chinese University of Hong Kong)

Abstract

In the literature, there is a lack of empirical studies documenting the profitability of volume-based technical indicators. This paper evaluates the profitability of the On-Balance Volume (OBV) trading rule. Our result shows that the OBV trading rule is increasingly profitable and rewards investors with notable returns in the stock markets of Greater China.

Suggested Citation

  • William Wai Him Tsang & Terence Tai Leung Chong, 2009. "Profitability of the On-Balance Volume Indicator," Economics Bulletin, AccessEcon, vol. 29(3), pages 2424-2431.
    • Handle: RePEc:ebl:ecbull:eb-09-00423
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    File URL: http://www.accessecon.com/Pubs/EB/2009/Volume29/EB-09-V29-I3-P87.pdf
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    References listed on IDEAS

    as
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    2. Hudson, Robert & Dempsey, Michael & Keasey, Kevin, 1996. "A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 1121-1132, July.
    3. Chong, Terence Tai-Leung & Ip, Hugo Tak-Sang, 2009. "Do momentum-based strategies work in emerging currency markets?," Pacific-Basin Finance Journal, Elsevier, vol. 17(4), pages 479-493, September.
    4. Mills, Terence C, 1997. "Technical Analysis and the London Stock Exchange: Testing Trading Rules Using the FT30," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 2(4), pages 319-331, October.
    5. 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.
    6. Ben Marshall & Martin Young & Rochester Cahan, 2008. "Are candlestick technical trading strategies profitable in the Japanese equity market?," Review of Quantitative Finance and Accounting, Springer, vol. 31(2), pages 191-207, August.
    7. Thomas Shik & Terence Tai-Leung Chong, 2007. "A comparison of MA and RSI returns with exchange rate intervention," Applied Economics Letters, Taylor & Francis Journals, vol. 14(5), pages 371-383.
    8. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. "Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
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    Citations

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    Cited by:

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    2. Tidor-Vlad Pricope, 2021. "Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review," Papers 2106.00123, arXiv.org.
    3. Seung Hwan Jeong & Hee Soo Lee & Hyun Nam & Kyong Joo Oh, 2021. "Using a Genetic Algorithm to Build a Volume Weighted Average Price Model in a Stock Market," Sustainability, MDPI, vol. 13(3), pages 1-16, January.
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    5. Papa Ousseynou Diop, 2024. "An Econometric and Time Series Analysis of the USTC Depeg’s Impact on the LUNA Classic Price Crash During Spring 2022’s Crypto Market Turmoil," Commodities, MDPI, vol. 3(4), pages 1-29, December.

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    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G0 - Financial Economics - - General

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