IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v26y2021i1p898-913.html
   My bibliography  Save this article

Intertemporal price discovery between stock index futures and spot markets: New evidence from high‐frequency data

Author

Listed:
  • Imtiaz Mohammad Sifat
  • Azhar Mohamad
  • Kevin Reinaldo Amin

Abstract

This article utilizes high‐frequency 15‐s intraday data from September 2017 through to August 2018 to investigate price leadership dynamics between Kuala Lumpur index futures (FKLI) and its underlying spot market: FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBM KLCI) in Bursa Malaysia. Harnessing the explanatory powers of Wavelet analysis, we employ Maximal Overlap Discrete Wavelet Transform to evaluate interdependence between contemporaneous futures and spot returns. We observe that price discovery between futures and spot markets at granular level is a scale‐dependent phenomenon. Moreover, we record a counter‐intuitive but not unprecedented evidence of futures market lagging the spot market in price formation. This discrepancy approaches convergence in 1–8 min. Our findings constitute evidence against the efficient market hypothesis and hint at opportunities for statistical arbitrage by high‐frequency trading. The results from time‐frequency domain receive strong support from vector error correction robustness checks, though corroboration is less conclusive from DCC‐GARCH and Baba, Engle, Kraft, and Kroner‐GARCH results.

Suggested Citation

  • Imtiaz Mohammad Sifat & Azhar Mohamad & Kevin Reinaldo Amin, 2021. "Intertemporal price discovery between stock index futures and spot markets: New evidence from high‐frequency data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 898-913, January.
  • Handle: RePEc:wly:ijfiec:v:26:y:2021:i:1:p:898-913
    DOI: 10.1002/ijfe.1827
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.1827
    Download Restriction: no

    File URL: https://libkey.io/10.1002/ijfe.1827?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
    ---><---

    References listed on IDEAS

    as
    1. Luís Aguiar-Conraria & Maria Soares, 2011. "Oil and the macroeconomy: using wavelets to analyze old issues," Empirical Economics, Springer, vol. 40(3), pages 645-655, May.
    2. Vacha, Lukas & Barunik, Jozef, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Energy Economics, Elsevier, vol. 34(1), pages 241-247.
    3. Jusoh, Hashim & Bacha, Obiyathulla & Masih, Abul Mansur M., 2014. "Multi-scale Lead-Lag Relationship between the Stock and Futures Markets: Malaysia as a Case Study," MPRA Paper 56954, University Library of Munich, Germany.
    4. Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
    5. Tse, Y. K., 2000. "A test for constant correlations in a multivariate GARCH model," Journal of Econometrics, Elsevier, vol. 98(1), pages 107-127, September.
    6. Chan, Howard Wei-Hong & Pinder, Sean M., 2000. "The value of liquidity: Evidence from the derivatives market," Pacific-Basin Finance Journal, Elsevier, vol. 8(3-4), pages 483-503, July.
    7. Paramita Mukherjee & Suchismita Bose, 2008. "Does the Stock Market in India Move with Asia?: A Multivariate Cointegration-Vector Autoregression Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 44(5), pages 5-22, September.
    8. Martin T. Bohl & Christian A. Salm & Bernd Wilfling, 2011. "Do individual index futures investors destabilize the underlying spot market?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(1), pages 81-101, January.
    9. Lin, Chu-Bin & Chou, Robin K. & Wang, George H.K., 2018. "Investor sentiment and price discovery: Evidence from the pricing dynamics between the futures and spot markets," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 17-31.
    10. Alzahrani, Mohammed & Masih, Mansur & Al-Titi, Omar, 2014. "Linear and non-linear Granger causality between oil spot and futures prices: A wavelet based test," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 175-201.
    11. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
    12. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    13. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, vol. 30(5), pages 2673-2685, September.
    14. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2013. "Intraday volatility spillovers between spot and futures indices: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1795-1802.
    15. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    16. A. Can Inci & H. Nejat Seyhun, 2018. "Degree of Integration Between Brent Oil Spot and Futures Markets: Intraday Evidence," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(8), pages 1808-1826, June.
    17. Kofman, Paul & Koedijk, Kees & Campbell, Rachel, 2002. "Increased Correlation in Bear markets: A Downside Risk Perspective," CEPR Discussion Papers 3172, C.E.P.R. Discussion Papers.
    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. Liwei Jin & Xianghui Yuan & Li Peiran & Hailun Xu & Feng Lian, 2023. "Option features and price discovery in convertible bonds," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(3), pages 384-403, March.

    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. Josué M. Polanco-Martínez & Luis M. Abadie, 2016. "Analyzing Crude Oil Spot Price Dynamics versus Long Term Future Prices: A Wavelet Analysis Approach," Energies, MDPI, vol. 9(12), pages 1-19, December.
    2. Charlot, Philippe & Darné, Olivier & Moussa, Zakaria, 2016. "Commodity returns co-movements: Fundamentals or “style” effect?," Journal of International Money and Finance, Elsevier, vol. 68(C), pages 130-160.
    3. Bhuiyan, Rubaiyat Ahsan & Husain, Afzol & Zhang, Changyong, 2021. "A wavelet approach for causal relationship between bitcoin and conventional asset classes," Resources Policy, Elsevier, vol. 71(C).
    4. Aloui, Chaker & Jammazi, Rania, 2015. "Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 62-86.
    5. Annastiina Silvennoinen & Timo Ter�svirta, 2015. "Modeling Conditional Correlations of Asset Returns: A Smooth Transition Approach," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 174-197, February.
    6. Charlot, Philippe & Marimoutou, Vêlayoudom, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Energy Economics, Elsevier, vol. 44(C), pages 456-467.
    7. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    8. Kaijian He & Kin Keung Lai & Guocheng Xiang, 2012. "Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach," Energies, MDPI, vol. 5(4), pages 1-26, April.
    9. Małgorzata Just & Aleksandra Łuczak, 2020. "Assessment of Conditional Dependence Structures in Commodity Futures Markets Using Copula-GARCH Models and Fuzzy Clustering Methods," Sustainability, MDPI, vol. 12(6), pages 1-22, March.
    10. Martín-Barragán, Belén & Ramos, Sofia B. & Veiga, Helena, 2015. "Correlations between oil and stock markets: A wavelet-based approach," Economic Modelling, Elsevier, vol. 50(C), pages 212-227.
    11. Annastiina Silvennoinen & Timo Teräsvirta, 2005. "Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations," Research Paper Series 168, Quantitative Finance Research Centre, University of Technology, Sydney.
    12. Bensafta, Kamel Malik & Semedo, Gervasio, 2009. "De la transmission de la volatilité à la contagion entre marchés boursiers : l’éclairage d’un modèle VAR non linéaire avec bris structurels en variance," L'Actualité Economique, Société Canadienne de Science Economique, vol. 85(1), pages 13-76, mars.
    13. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    14. 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.
    15. Milan Bašta & Peter Molnár, 2019. "Long‐term dynamics of the VIX index and its tradable counterpart VXX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(3), pages 322-341, March.
    16. Xiaojie Xu, 2018. "Causal structure among US corn futures and regional cash prices in the time and frequency domain," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(13), pages 2455-2480, October.
    17. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    18. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    19. Colavecchio, Roberta & Funke, Michael, 2008. "Volatility transmissions between renminbi and Asia-Pacific on-shore and off-shore U.S. dollar futures," China Economic Review, Elsevier, vol. 19(4), pages 635-648, December.
    20. Storhas, Dominik P. & De Mello, Lurion & Singh, Abhay Kumar, 2020. "Multiscale lead-lag relationships in oil and refined product return dynamics: A symbolic wavelet transfer entropy approach," Energy Economics, Elsevier, vol. 92(C).

    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:wly:ijfiec:v:26:y:2021:i:1:p:898-913. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.