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Dependence structure of the commodity and stock markets, and relevant multi-spread strategy

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  • Kim, Min Jae
  • Kim, Sehyun
  • Jo, Yong Hwan
  • Kim, Soo Yong
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    Abstract

    Understanding the dependence structure between the commodity and stock markets is a crucial issue in constructing a portfolio. It can also help us to discover new opportunities to implement spread trading using multiple assets classified in the two different markets. This study analyzed the dependence structure of the commodity and stock markets using the random matrix theory technique and network analysis. Our results show that the stock and commodity markets must be handled as completely separated asset classes except for the oil and gold markets, so the performance enhancement of the mean-variance portfolio is significant as expected. In light of the fact that WTI 1 month futures and four oil-related stocks are strongly correlated, they were selected as basic ingredients to complement the multi-spread convergence trading strategy using a machine learning technique called the AdaBoost algorithm. The performance of this strategy for non-myopic investors, who can endure short-term loss, can be enhanced significantly on a risk measurement basis.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0378437111004845
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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 390 (2011)
    Issue (Month): 21 ()
    Pages: 3842-3854

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    Handle: RePEc:eee:phsmap:v:390:y:2011:i:21:p:3842-3854

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Commodity; Random matrix theory; Network analysis; Multi-spread trading; AdaBoost algorithm;

    References

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    1. Cars H. Hommes, 2001. "Financial Markets as Nonlinear Adaptive Evolutionary Systems," Tinbergen Institute Discussion Papers 01-014/1, Tinbergen Institute.
    2. Evan Gatev & William N. Goetzmann & K. Geert Rouwenhorst, 2006. "Pairs Trading: Performance of a Relative-Value Arbitrage Rule," Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 797-827.
    3. Matteo Barigozzi & Giorgio Fagiolo & Diego Garlaschelli, 2009. "Multinetwork of international trade: A commodity-specific analysis," Papers 0908.1879, arXiv.org, revised Jun 2010.
    4. G. Bonanno & F. Lillo & R. N. Mantegna, 2001. "High-frequency cross-correlation in a set of stocks," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 96-104.
    5. Pawe{\l} Sieczka & Janusz A. Ho{\l}yst, 2008. "Correlations in commodity markets," Papers 0803.3884, arXiv.org, revised Jan 2009.
    6. Valeriy V. Gavrishchaka, 2006. "Boosting-Based Framework For Portfolio Strategy Discovery And Optimization," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 315-330.
    7. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
    8. Jaume Masoliver & Josep Perello, 2008. "The escape problem under stochastic volatility: the Heston model," Papers 0807.1014, arXiv.org.
    9. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    10. Siqueira, Erinaldo Leite & Stošić, Tatijana & Bejan, Lucian & Stošić, Borko, 2010. "Correlations and cross-correlations in the Brazilian agrarian commodities and stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2739-2743.
    11. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 11(1), pages 193-197, September.
    12. Kim, Min Jae & Kwak, Young Bin & Kim, Soo Yong, 2011. "Dependence structure of the Korean stock market in high frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 891-901.
    13. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciché & N. Vandewalle & R. Mantegna, 2004. "Networks of equities in financial markets," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 38(2), pages 363-371, 03.
    14. Jaume Masoliver & Josep Perello, 2009. "First-passage and risk evaluation under stochastic volatility," Papers 0902.2735, arXiv.org.
    15. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, 03.
    16. Sieczka, Paweł & Hołyst, Janusz A., 2009. "Correlations in commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1621-1630.
    17. Robert Elliott & John Van Der Hoek & William Malcolm, 2005. "Pairs trading," Quantitative Finance, Taylor & Francis Journals, vol. 5(3), pages 271-276.
    18. Bertram, William K., 2009. "Optimal trading strategies for Itô diffusion processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2865-2873.
    19. B. Podobnik & I. Grosse & D. Horvatić & S. Ilic & P. Ch. Ivanov & H. E. Stanley, 2009. "Quantifying cross-correlations using local and global detrending approaches," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 71(2), pages 243-250, September.
    20. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    21. Dong-Hee Kim & Hawoong Jeong, 2005. "Systematic analysis of group identification in stock markets," Papers physics/0503076, arXiv.org, revised Oct 2005.
    22. Brennan, Michael J & Schwartz, Eduardo S, 1990. "Arbitrage in Stock Index Futures," The Journal of Business, University of Chicago Press, vol. 63(1), pages S7-31, January.
    23. Lee, Sangwook & Kim, Min Jae & Kim, Soo Yong, 2011. "Interest rates factor model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(13), pages 2531-2548.
    24. L. Kullmann & J. Kertesz & K. Kaski, 2002. "Time dependent cross correlations between different stock returns: A directed network of influence," Papers cond-mat/0203256, arXiv.org, revised May 2002.
    25. Gilles Zumbach, 2009. "Time reversal invariance in finance," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 505-515.
    26. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
    27. repec:dgr:uvatin:2001014 is not listed on IDEAS
    28. Bertram, William K., 2010. "Analytic solutions for optimal statistical arbitrage trading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(11), pages 2234-2243.
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    Cited by:
    1. Ladislav Kristoufek & Miloslav Vosvrda, 2013. "Commodity futures and market efficiency," Papers 1309.1492, arXiv.org.
    2. Lim, Kyuseong & Kim, Min Jae & Kim, Sehyun & Kim, Soo Yong, 2014. "Statistical properties of the stock and credit market: RMT and network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 66-75.

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