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Assessing the profitability of intraday opening range breakout strategies

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  • Holmberg, Ulf
  • Lönnbark, Carl
  • Lundström, Christian

Abstract

Is it possible to beat the market by mechanical trading rules based on historical and publicly known information? Such rules have long been used by investors and in this paper, we test the success rate of trades and profitability of the Open Range Breakout (ORB) strategy. An investor that trades on the ORB strategy seeks to identify large intraday price movements and trades only when the price moves beyond some predetermined threshold. We present an ORB strategy based on normally distributed returns to identify such days and find that our ORB trading strategy result in significantly higher returns than zero as well as an increased success rate in relation to a fair game. The characteristics of such an approach over conventional statistical tests is that it involves the joint distribution of low, high, open and close over a given time horizon.

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Bibliographic Info

Article provided by Elsevier in its journal Finance Research Letters.

Volume (Year): 10 (2013)
Issue (Month): 1 ()
Pages: 27-33

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Handle: RePEc:eee:finlet:v:10:y:2013:i:1:p:27-33

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Web page: http://www.elsevier.com/locate/frl

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Keywords: Bootstrap; Crude oil futures; Contraction–Expansion principle; Efficient market hypothesis; Martingales; Technical analysis;

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  1. Schulmeister, Stephan, 2006. "The interaction between technical currency trading and exchange rate fluctuations," Finance Research Letters, Elsevier, vol. 3(3), pages 212-233, September.
  2. Brock, W. & Lakonishok, J. & Lebaron, B., 1991. "Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns," Working papers 90-22, Wisconsin Madison - Social Systems.
  3. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. " Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
  4. Nicholas Barberis & Andrei Shleifer & Robert W. Vishny, 1997. "A Model of Investor Sentiment," NBER Working Papers 5926, National Bureau of Economic Research, Inc.
  5. Stephan Schulmeister, 2008. "Profitability of Technical Stock Trading: Has it Moved from Daily to Intraday Data?," WIFO Working Papers 323, WIFO.
  6. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
  7. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December.
  8. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
  9. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
  10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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Cited by:
  1. Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2013. "On the predictability of stock prices: A case for high and low prices," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5132-5146.
  2. Kuo, Wei-Yu & Lin, Tse-Chun, 2013. "Overconfident individual day traders: Evidence from the Taiwan futures market," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3548-3561.

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