IDEAS home Printed from https://ideas.repec.org/p/hhs/umnees/0948.html
   My bibliography  Save this paper

On the Returns of Trend-Following Trading Strategies

Author

Listed:

Abstract

Paper [I] tests the success rate of trades and the returns of the Opening Range Breakout (ORB) strategy. A trader 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. Paper [II] measures the returns of a popular day trading strategy; the Opening Range Breakout strategy (ORB); across volatility states. We calculate the average daily returns of the ORB strategy for each volatility state of the underlying asset when applied on long time series of crude oil and S&P 500 futures contracts. We find an average difference in returns between the highest and the lowest volatility state of around 200 basis points per day for crude oil; and of around 150 basis points per day for the S&P 500. This finding suggests that the success in day trading can depend to a large extent on the volatility of the underlying asset. Paper [III] performs empirical analysis on short-term and long-term Commodity Trading Advisor (CTA) strategies regarding their exposures to unanticipated risk shocks. Previous research documents that CTA strategies offer diversification opportunities during equity market crisis situations when evaluated as a group; but do not separate between short-term and long-term CTA strategies. When separating between short-term and long-term CTA strategies; this paper finds that only short-term CTA strategies provide a significant; and consistent; exposure to unanticipated risk shocks while long-term CTA strategies do not. For the purpose of diversifying a portfolio during equity market crisis situations; this result suggests that an investor should allocate to short-term CTA strategies rather than to long-term CTA strategies.

Suggested Citation

  • Lundström, Christian, 2017. "On the Returns of Trend-Following Trading Strategies," Umeå Economic Studies 948, Umeå University, Department of Economics.
    • Handle: RePEc:hhs:umnees:0948
    as

    Download full text from publisher

    File URL: http://www.usbe.umu.se/digitalAssets/195/195397_ues948.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marklund, Per-Olov, 2004. "Essays on Productive Efficiency, Shadow Prices, and Human Capital. PhD Thesis," Umeå Economic Studies 621, Umeå University, Department of Economics.
    2. Ankarhem, Mattias, 2005. "Bioenergy, Pollution, and Economic Growth," Umeå Economic Studies 661, Umeå University, Department of Economics.
    3. Ghalwash, Tarek, 2006. "Income, Energy Taxation, and the Environment: An Econometric Analysis," Umeå Economic Studies 678, Umeå University, Department of Economics.
    4. Widerstedt, Barbro, 1998. "Moving or Staying? Job Mobility as a Sorting Process," Umeå Economic Studies 464, Umeå University, Department of Economics.
    5. Hakobyan, Lilit, 2014. "Essays on Growth and Political Transition," Umeå Economic Studies 893, Umeå University, Department of Economics.
    6. Rashid, Saman, 2004. "Immigrants' Income and Family Migration," Umeå Economic Studies 625, Umeå University, Department of Economics.
    7. Fung, William & Hsieh, David A, 2001. "The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 313-341.
    8. Vredin Johansson, Maria, 1999. "Economics without markets. Four papers on the Contingent Valuation and Stated Preference Methods," Umeå Economic Studies 517, Umeå University, Department of Economics.
    9. Hossein Kazemi & Ying Li, 2009. "Market timing of CTAs: An examination of systematic CTAs vs. discretionary CTAs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(11), pages 1067-1099, November.
    10. Heidrich, Stefanie, 2016. "Essays on Intergenerational Income Mobility, Geographical Mobility, and Education," Umeå Economic Studies 932, Umeå University, Department of Economics.
    11. Persson, Lars, 2008. "Environmental Policy and Transboundary Externalities - Coordination and Commitment in Open Economies," Umeå Economic Studies 755, Umeå University, Department of Economics.
    12. Brockwell, Erik, 2014. "State and Industrial Actions to Influence Consumer Behavior," Umeå Economic Studies 894, Umeå University, Department of Economics.
    13. Office of Health Economics, 2007. "The Economics of Health Care," For School 001490, Office of Health Economics.
    14. Liu, Yuna, 2016. "Essays on Stock Market Integration - On Stock Market Efficiency, Price Jumps and Stock Market Correlations," Umeå Economic Studies 926, Umeå University, Department of Economics.
    15. Selander, Carina, 2006. "Chartist Trading in Exchange Rate Theory," Umeå Economic Studies 698, Umeå University, Department of Economics.
    16. Cialani, Catia, 2014. "Essays on Growth and Environment," Umeå Economic Studies 875, Umeå University, Department of Economics.
    17. Raattamaa, Tomas, 2016. "Essays on Delegated Search and Temporary Work Agencies," Umeå Economic Studies 935, Umeå University, Department of Economics.
    18. Zetterdahl, Emma, 2015. "Take a Risk - Social Interaction, Gender Identity, and the Role of Family Ties in Financial Decision-Making," Umeå Economic Studies 908, Umeå University, Department of Economics.
    19. Westerberg, Thomas, 2006. "Two Papers On Fertility - The Case Of Sweden," Umeå Economic Studies 683, Umeå University, Department of Economics.
    20. Vesterberg, Mattias, 2017. "Power to the people: Electricity demand and household behavior," Umeå Economic Studies 942, Umeå University, Department of Economics.
    21. Quoreshi, Shahiduzzaman, 2006. "Time Series Modelling Of High Frequency Stock Transaction Data," Umeå Economic Studies 675, Umeå University, Department of Economics.
    22. Humavindu, Michael N, 2008. "Essays on the Namibian Economy," Umeå Economic Studies 745, Umeå University, Department of Economics.
    23. Tano, Sofia, 2014. "Migration and Regional Sorting of Skills," Umeå Economic Studies 882, Umeå University, Department of Economics.
    24. Sandberg, Krister, 2004. "Hedonic Prices, Economic Growth, and Spatial Dependence," Umeå Economic Studies 631, Umeå University, Department of Economics.
    25. Bask, Mikael, 1998. "Essays on Exchange Rates: Deterministic Chaos and Technical Analysis," Umeå Economic Studies 465, Umeå University, Department of Economics.
    26. Eriksson, Mathilda, 2016. "The Role of the Forest in Climate Policy," Umeå Economic Studies 927, Umeå University, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raattamaa, Tomas, 2016. "Essays on Delegated Search and Temporary Work Agencies," Umeå Economic Studies 935, Umeå University, Department of Economics.
    2. Sahlén, Linda, 2009. "Essays on Environmental and Development Economics - Public Policy, Resource Prices and Global Warming," Umeå Economic Studies 762, Umeå University, Department of Economics.
    3. Ludwig Chincarini, 2014. "The Impact of Quantitative Methods on Hedge Fund Performance," European Financial Management, European Financial Management Association, vol. 20(5), pages 857-890, November.
    4. Asif, Raheel & Frömmel, Michael & Mende, Alexander, 2022. "The crisis alpha of managed futures: Myth or reality?," International Review of Financial Analysis, Elsevier, vol. 80(C).
    5. Luo, Ji & Tee, Kai-Hong & Li, Baibing, 2017. "Timing liquidity in the foreign exchange market: Did hedge funds do it?," Journal of Multinational Financial Management, Elsevier, vol. 40(C), pages 47-62.
    6. Gert Elaut & Michael Frömmel & Alexander Mende, 2017. "Duration Dependence, Behavioral Restrictions, and the Market Timing Ability of Commodity Trading Advisors," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 427-450, September.
    7. Damir Tokic, 2012. "The passive investor puzzle," Journal of Asset Management, Palgrave Macmillan, vol. 13(2), pages 141-154, April.
    8. Andrew W. Lo & Mila Getmansky & Peter A. Lee, 2015. "Hedge Funds: A Dynamic Industry in Transition," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 483-577, December.
    9. Viet Do & Robert Faff & Paul Lajbcygier & Madhu Veeraraghavan & Mikhail Tupitsyn, 2016. "Factors affecting the birth and fund flows of CTAs," Australian Journal of Management, Australian School of Business, vol. 41(2), pages 324-352, May.
    10. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    11. Christian Lorenz, 2012. "Triangulating health expenditure estimates from different data sources in developing countries," Applied Health Economics and Health Policy, Springer, vol. 10(1), pages 1-13, January.
    12. Carol Alexander & Anca Dimitriu, 2003. "Equity Indexing: Conitegration and Stock Price Dispersion: A Regime Switiching Approach to market Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2003-02, Henley Business School, University of Reading.
    13. James F. Burgess & Matthew L. Maciejewski & Chris L. Bryson & Michael Chapko & John C. Fortney & Mark Perkins & Nancy D. Sharp & Chuan‐Fen Liu, 2011. "Importance of health system context for evaluating utilization patterns across systems," Health Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 239-251, February.
    14. Jung‐Soon Shin & Minki Kim & Dongjun Oh & Tong Suk Kim, 2019. "Do hedge funds time market tail risk? Evidence from option‐implied tail risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(2), pages 205-237, February.
    15. Adrian, Tobias, 2009. "Inference, arbitrage, and asset price volatility," Journal of Financial Intermediation, Elsevier, vol. 18(1), pages 49-64, January.
    16. McDonald, Rebecca & Powdthavee, Nattavudh, 2018. "The Shadow Prices of Voluntary Caregiving: Using Panel Data of Well-Being to Estimate the Cost of Informal Care," IZA Discussion Papers 11545, Institute of Labor Economics (IZA).
    17. Verónica Amarante & Marco Manacorda & Edward Miguel & Andrea Vigorito, 2016. "Do Cash Transfers Improve Birth Outcomes? Evidence from Matched Vital Statistics, Program, and Social Security Data," American Economic Journal: Economic Policy, American Economic Association, vol. 8(2), pages 1-43, May.
    18. Hope Corman & Dhaval Dave & Nancy E. Reichman, 2018. "Evolution of the Infant Health Production Function," Southern Economic Journal, John Wiley & Sons, vol. 85(1), pages 6-47, July.
    19. Agarwal, Vikas & Fung, William H. & Loon, Yee Cheng & Naik, Narayan Y., 2004. "Risk and return in convertible arbitrage: Evidence from the convertible bond market," CFR Working Papers 04-03, University of Cologne, Centre for Financial Research (CFR).
    20. Trottmann, Maria & Zweifel, Peter & Beck, Konstantin, 2012. "Supply-side and demand-side cost sharing in deregulated social health insurance: Which is more effective?," Journal of Health Economics, Elsevier, vol. 31(1), pages 231-242.

    More about this item

    Keywords

    Bootstrap; Commodity Trading Advisor funds; Contraction-Expansion principle; Crude oil futures; Futures trading; Opening Range Breakout strategies; S&P 500 futures; Technical analysis; Time series momentum; Time-varying market inefficiency;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • 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; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:umnees:0948. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: David Skog (email available below). General contact details of provider: https://edirc.repec.org/data/inumuse.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.