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Structural change and lead-lag relationship between the Nikkei spot index and futures price: a genetic programming approach

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  • Donald Lien
  • Y. K. Tse
  • Xibin Zhang

Abstract

In this paper we adopt a nonparametric genetic programming (GP) approach to identify the structural changes in the Nikkei spot index and futures price. Due to the dominance of the 'normal' period in sample data, the lead-lag relationship identified in the spot-futures system based on conventional methods such as the test for Granger causality pertains to the normal period and may not be applicable in an 'extreme' period. Using GP we identify the lead-lag relationship based on the chronological ordering of the structural changes in the spot and futures markets. Our results show that in recent periods, major market changes originated from the spot market and spread over to the futures market.

Suggested Citation

  • Donald Lien & Y. K. Tse & Xibin Zhang, 2003. "Structural change and lead-lag relationship between the Nikkei spot index and futures price: a genetic programming approach," Quantitative Finance, Taylor & Francis Journals, vol. 3(2), pages 136-144.
    • Handle: RePEc:taf:quantf:v:3:y:2003:i:2:p:136-144
    DOI: 10.1088/1469-7688/3/2/307
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    1. P. Silvapulle & C. W. J. Granger, 2001. "Large returns, conditional correlation and portfolio diversification: a value-at-risk approach," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 542-551.
    2. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(4), pages 405-426, December.
    3. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2002. "On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 217-239, October.
    4. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    5. M. A. H. dempster & C. M. Jones, 2001. "A real-time adaptive trading system using genetic programming," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 397-413.
    6. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    7. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    8. Jun Wang, 2000. "Trading and hedging in S&P 500 spot and futures markets using genetic programming," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(10), pages 911-942, November.
    9. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2001. "Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 363-393, March.
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    Cited by:

    1. Shao, Ying-Hui & Yang, Yan-Hong & Shao, Hao-Lin & Stanley, H. Eugene, 2019. "Time-varying lead–lag structure between the crude oil spot and futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 723-733.
    2. Lee Chee Tong, 2005. "Does Stock Market Liberalisation Benefit The Economy? Evidence From Industry-Level Data," SCAPE Policy Research Working Paper Series 0516, National University of Singapore, Department of Economics, SCAPE.
    3. Harry J. Turtle & Chengping Zhang, 2015. "Structural breaks and portfolio performance in global equity markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 909-922, June.
    4. Alemany, Nuria & Aragó, Vicent & Salvador, Enrique, 2020. "Lead-lag relationship between spot and futures stock indexes: Intraday data and regime-switching models," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 269-280.
    5. Ma, Chaoqun & Xiao, Ru & Mi, Xianhua, 2022. "Measuring the dynamic lead–lag relationship between the cash market and stock index futures market," Finance Research Letters, Elsevier, vol. 47(PB).
    6. Lee Chee Tong, 2005. "Does Stock Market Liberalisation Benefit The Economy? Evidence From Industry-Level Data," Finance Working Papers 22580, East Asian Bureau of Economic Research.
    7. Aysegul Ates, 2016. "Relation between ISE 30 index and ISE 30 index futures markets: Evidence from recursive and rolling cointegration," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 4(1), pages 35-42, February.
    8. Ren, Fei & Ji, Shen-Dan & Cai, Mei-Ling & Li, Sai-Ping & Jiang, Xiong-Fei, 2019. "Dynamic lead–lag relationship between stock indices and their derivatives: A comparative study between Chinese mainland, Hong Kong and US stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 709-723.
    9. Chueh-Yung Tsao, 2010. "Portfolio selection based on the mean-VaR efficient frontier," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 931-945.
    10. Gong, Chen-Chen & Ji, Shen-Dan & Su, Li-Ling & Li, Sai-Ping & Ren, Fei, 2016. "The lead–lag relationship between stock index and stock index futures: A thermal optimal path method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 63-72.

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