IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v3y2003i2p136-144.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1088/1469-7688/3/2/307
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1088/1469-7688/3/2/307?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    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. 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.

    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. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    2. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    3. Shernaz Bodhanwala & Harsh Purohit & Nidhi Choudhary, 2020. "The Causal Dynamics in Indian Agriculture Commodity Prices and Macro-Economic Variables in the Presence of a Structural Break," Global Business Review, International Management Institute, vol. 21(1), pages 241-261, February.
    4. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    5. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    6. Yeh, Chia-Hsuan & Yang, Chun-Yi, 2010. "Examining the effectiveness of price limits in an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 2089-2108, October.
    7. Mittnik, Stefan, 2014. "VaR-implied tail-correlation matrices," Economics Letters, Elsevier, vol. 122(1), pages 69-73.
    8. Lei Jiang & Esfandiar Maasoumi & Jiening Pan & Ke Wu, 2018. "A test of general asymmetric dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1026-1043, November.
    9. Jeng-Bau Lin & Chin-Chia Liang & Wei Tsai, 2019. "Nonlinear Relationships between Oil Prices and Implied Volatilities: Providing More Valuable Information," Sustainability, MDPI, vol. 11(14), pages 1-15, July.
    10. Ioana-Andreea Boboc & Mihai-Cristian Dinică, 2013. "An Algorithm for Testing the Efficient Market Hypothesis," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-11, October.
    11. Lijun Wang & Haizhong An & Xiaohua Xia & Xiaojia Liu & Xiaoqi Sun & Xuan Huang, 2014. "Generating Moving Average Trading Rules on the Oil Futures Market with Genetic Algorithms," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, May.
    12. Nusair, Salah A. & Olson, Dennis, 2019. "The effects of oil price shocks on Asian exchange rates: Evidence from quantile regression analysis," Energy Economics, Elsevier, vol. 78(C), pages 44-63.
    13. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng, 2016. "A nonparametric approach to test for predictability," Economics Letters, Elsevier, vol. 148(C), pages 10-16.
    14. Jiangze Du & Xizhuo Chen & Jincheng Gong & Xiao Lin & Kin Keung Lai, 2023. "Analysis of stock markets risk spillover with copula models under the background of Chinese financial opening," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3997-4019, October.
    15. Guoxiang Xu & Wangfeng Gao, 2019. "Financial Risk Contagion in Stock Markets: Causality and Measurement Aspects," Sustainability, MDPI, vol. 11(5), pages 1-20, March.
    16. Lee, Chia-Hao & Chou, Pei-I, 2020. "Structural breaks in the correlations between Asian and US stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    17. Kanjilal, Kakali & Ghosh, Sajal, 2017. "Dynamics of crude oil and gold price post 2008 global financial crisis – New evidence from threshold vector error-correction model," Resources Policy, Elsevier, vol. 52(C), pages 358-365.
    18. Jinghua Wang & Geoffrey Ngene, 2018. "Symmetric and asymmetric nonlinear causalities between oil prices and the U.S. economic sectors," Review of Quantitative Finance and Accounting, Springer, vol. 51(1), pages 199-218, July.
    19. Michel Beine & Gunther Capelle-Blancard & Helene Raymond, 2008. "International nonlinear causality between stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 663-686.
    20. Zhang, Lingxiang & Zhang, Xiaotong, 2011. "Spurious Granger causality between a broken-trend stationary process and a stochastic trend process," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(8), pages 1673-1681.

    More about this item

    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:taf:quantf:v:3:y:2003:i:2:p:136-144. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    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.