IDEAS home Printed from https://ideas.repec.org/p/rdg/icmadp/icma-dp2002-08.html
   My bibliography  Save this paper

The Cointegration Alpha: Enchanced Index Tracking and Long-Short Equity Market Neutral Stragies

Author

Listed:
  • Carol Alexandra

    (ICMA Centre, University of Reading)

  • Anca Dimitriu

    (ICMA Centre, University of Reading)

Abstract

This paper presents two applications of cointegration based trading strategies: a classic index tracking strategy and a long-short equity market neutral strategy. As opposed to other traditional index tracking or long-short equity strategies, the portfolio optimisation is based on cointegration rather than correlation. The first strategy aims to replicate a benchmark accurately in terms of returns and volatility, while the other seeks to minimise volatility and generate steady returns under all market circumstances. Additionally, several combinations of these two strategies are explored. To validate the applicability of the cointegration technique to asset allocation, pioneered by Lucas (1997) and Alexander (1999), and explain how and why it works, we have employed a panel data on DJIA and its constituent stocks. When applied to constructing trading strategies in the DJIA, the cointegration technique produces encouraging results. For example, between January 1995 and December 2001 the most successful self-financing statistical arbitrage strategies returned (net of transaction and repo costs) approximately 10% with roughly 2% annual volatility and negligible correlation with the market. The comprehensive set of back-test results reported is meant to offer a detailed picture of the cointegration mechanism, and to emphasise its practical implementation issues. Its key characteristics, i.e. mean reverting tracking error, enhanced weights stability and better use of the information contained in stock prices, allow a flexible design of various funded and self-financing trading strategies, from index and enhanced index tracking, to long-short market neutral and alpha transfer techniques. Further enhancement of the strategy should target first, the identification of successful stock selection rules to supplement the simple cointegration results and second, the investigation of the potential benefits of applying optimal rebalancing rules.

Suggested Citation

  • Carol Alexandra & Anca Dimitriu, 2002. "The Cointegration Alpha: Enchanced Index Tracking and Long-Short Equity Market Neutral Stragies," ICMA Centre Discussion Papers in Finance icma-dp2002-08, Henley Business School, University of Reading.
    • Handle: RePEc:rdg:icmadp:icma-dp2002-08
    as

    Download full text from publisher

    File URL: http://www.icmacentre.ac.uk/pdf/discussion/DP2002-08.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:bla:jfinan:v:44:y:1989:i:1:p:167-81 is not listed on IDEAS
    2. Baillie, Richard T & Bollerslev, Tim, 1994. "Cointegration, Fractional Cointegration, and Exchange Rate Dynamics," Journal of Finance, American Finance Association, vol. 49(2), pages 737-745, June.
    3. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    4. Diebold, Francis X & Gardeazabal, Javier & Yilmaz, Kamil, 1994. "On Cointegration and Exchange Rate Dynamics," Journal of Finance, American Finance Association, vol. 49(2), pages 727-735, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hain, Martin & Hess, Julian & Uhrig-Homburg, Marliese, 2018. "Relative value arbitrage in European commodity markets," Energy Economics, Elsevier, vol. 69(C), pages 140-154.
    2. Chen, Qi-an & Hu, Qingyu & Yang, Hu & Qi, Kai, 2022. "A kind of new time-weighted nonnegative lasso index-tracking model and its application," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    3. Sánchez-Granero, M.A. & Balladares, K.A. & Ramos-Requena, J.P. & Trinidad-Segovia, J.E., 2020. "Testing the efficient market hypothesis in Latin American stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    4. Wen, Danyan & Ma, Chaoqun & Wang, Gang-Jin & Wang, Senzhang, 2018. "Investigating the features of pairs trading strategy: A network perspective on the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 903-918.
    5. Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    6. Bruno Breyer Caldas & João Frois Caldeira & Guilherme Vale Moura, 2016. "Is Pairs Trading Performance Sensitive To The Methodologies?: A Comparison," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 130, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

    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. Nielsen, Morten Orregaard & Shimotsu, Katsumi, 2007. "Determining the cointegrating rank in nonstationary fractional systems by the exact local Whittle approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 574-596, December.
    2. Hassler, U. & Marmol, F. & Velasco, C., 2006. "Residual log-periodogram inference for long-run relationships," Journal of Econometrics, Elsevier, vol. 130(1), pages 165-207, January.
    3. Bang Nam Jeon & Euiseong Lee, 2002. "Foreign exchange market efficiency, cointegration, and policy coordination," Applied Economics Letters, Taylor & Francis Journals, vol. 9(1), pages 61-68.
    4. Kühl, Michael, 2007. "Cointegration in the foreign exchange market and market efficiency since the introduction of the Euro: Evidence based on bivariate cointegration analyses," University of Göttingen Working Papers in Economics 68, University of Goettingen, Department of Economics.
    5. Jose A. Lopez, 1996. "Exchange rate cointegration across central bank regime shifts," Research Paper 9602, Federal Reserve Bank of New York.
    6. Ghosh, Asim, 1996. "Cross-Hedging Foreign Currency Risk: Empirical Evidence from an Error Correction Model," Review of Quantitative Finance and Accounting, Springer, vol. 6(3), pages 223-231, May.
    7. Aggarwal, Raj & Mougoue, Mbodja, 1996. "Cointegration among Asian currencies: Evidence of the increasing influence of the Japanese yen," Japan and the World Economy, Elsevier, vol. 8(3), pages 291-308, September.
    8. Madura, J. & Wiley, M. K. & Zarruk, E. R., 1998. "Cointegration of term structure premiums across countries," Journal of Multinational Financial Management, Elsevier, vol. 8(4), pages 393-412, November.
    9. Barkoulas, John T. & Barilla, Anthony G. & Wells, William, 2016. "Long-memory exchange rate dynamics in the euro era," Chaos, Solitons & Fractals, Elsevier, vol. 86(C), pages 92-100.
    10. Shi-Miin Liu & Chih-Hsien Chou, 2003. "Parities and Spread Trading in Gold and Silver Markets: A Fractional Cointegration Analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 13(12), pages 899-911.
    11. Abul Masih & Rumi Masih, 1998. "A fractional cointegration analysis of the long-run relationship between black and official foreign exchange rates: the case of the Brazilian cruzeiro," Applied Economics, Taylor & Francis Journals, vol. 30(7), pages 853-861.
    12. Nielsen M.O., 2004. "Optimal Residual-Based Tests for Fractional Cointegration and Exchange Rate Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 331-345, July.
    13. Kühl, Michael, 2010. "Bivariate cointegration of major exchange rates, cross-market efficiency and the introduction of the Euro," Journal of Economics and Business, Elsevier, vol. 62(1), pages 1-19, January.
    14. McCrae, Michael, et al, 2002. "Can Cointegration-Based Forecasting Outperform Univariate Models? An Application to Asian Exchange Rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(5), pages 355-380, August.
    15. A. Yuce & C. Simga-Mugan, 1996. "An investigation of the short- and long-term relationships between Turkish financial markets," The European Journal of Finance, Taylor & Francis Journals, vol. 2(4), pages 305-317.
    16. John Barkoulas & Christopher F. Baum, 1996. "A Re-examination of the Fragility of Evidence from Cointegration- Based Tests of Foreign Exchange Market Efficiency," Boston College Working Papers in Economics 311., Boston College Department of Economics.
    17. David McMillan, 2005. "Cointegrating behaviour between spot and forward exchange rates," Applied Financial Economics, Taylor & Francis Journals, vol. 15(16), pages 1135-1144.
    18. Aggarwal, Raj & Mougoue, Mbodja, 1998. "Common Stochastic Trends among Asian Currencies: Evidence for Japan, ASEANs, and the Asian Tigers," Review of Quantitative Finance and Accounting, Springer, vol. 10(2), pages 193-206, March.
    19. P. S. Sephton, 2002. "Fractional cointegration: Monte Carlo estimates of critical values, with an application," Applied Financial Economics, Taylor & Francis Journals, vol. 12(5), pages 331-335.
    20. Aaron D. Smallwood & Stefan C. Norrbin, 2006. "Generalized long memory processes, failure of cointegration tests and exchange rate dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 409-417, May.

    More about this item

    Keywords

    cointegration; enchanced index tracking; long-short equity; market neutral; hedge fund; alpha strategy;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

    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:rdg:icmadp:icma-dp2002-08. 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: Marie Pearson (email available below). General contact details of provider: https://edirc.repec.org/data/bsrdguk.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.