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

Author

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  • 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
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    References listed on IDEAS

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    1. Baillie, Richard T & Bollerslev, Tim, 1989. " Common Stochastic Trends in a System of Exchange Rates," Journal of Finance, American Finance Association, vol. 44(1), pages 167-181, March.
    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.
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    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. 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.
    4. 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).
    5. 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].
    6. 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).

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    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

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