Assessing the profitability of intraday opening range breakout strategies
AbstractIs 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Umeå University, Department of Economics in its series Umeå Economic Studies with number 845.
Length: 11 pages
Date of creation: 23 Aug 2012
Date of revision:
Contact details of provider:
Postal: Department of Economics, Umeå University, S-901 87 Umeå, Sweden
Phone: 090 - 786 61 42
Fax: 090 - 77 23 02
Web page: http://www.econ.umu.se/
More information through EDIRC
Bootstrap; Crude oil futures; Contraction-Expansion principle; Efficient market hypothesis; Martingales; Technical Analysis;
Other versions of this item:
- Holmberg, Ulf & Lönnbark, Carl & Lundström, Christian, 2013. "Assessing the profitability of intraday opening range breakout strategies," Finance Research Letters, Elsevier, vol. 10(1), pages 27-33.
- C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-09-03 (All new papers)
- NEP-ENE-2012-09-03 (Energy Economics)
- NEP-MST-2012-09-03 (Market Microstructure)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Brock, W. & Lakonishok, J. & Lebaron, B., 1991.
"Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns,"
90-22, Wisconsin Madison - Social Systems.
- 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 1731-64, December.
- Schulmeister, Stephan, 2006.
"The interaction between technical currency trading and exchange rate fluctuations,"
Finance Research Letters,
Elsevier, vol. 3(3), pages 212-233, September.
- Stephan Schulmeister, 2005. "The Interaction between Technical Currency Trading and Exchange Rate Fluctuations," Finance 0512033, EconWPA.
- Stephan Schulmeister, 2005. "The Interaction between Technical Currency Trading and Exchange Rate Fluctuations," WIFO Working Papers 264, WIFO.
- 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.
- Stephan Schulmeister, 2008.
"Profitability of Technical Stock Trading: Has it Moved from Daily to Intraday Data?,"
WIFO Working Papers
- Schulmeister, Stephan, 2009. "Profitability of technical stock trading: Has it moved from daily to intraday data?," Review of Financial Economics, Elsevier, vol. 18(4), pages 190-201, October.
- 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.
- 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.
- Nicholas Barberis & Andrei Shleifer & Robert W. Vishny, 1997.
"A Model of Investor Sentiment,"
NBER Working Papers
5926, National Bureau of Economic Research, Inc.
- 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.
- 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.
- Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kjell-Göran Holmberg).
If references are entirely missing, you can add them using this form.