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Time-varying price discovery in fragmented markets

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  • Nicholas Taylor

Abstract

This article examines temporal aspects of the price discover process in the (fragmented) Standard & Poor's (S&P) 500 market. This is achieved by augmenting the coefficients in the model upon which the price discovery measures are based, by a set of time-varying (theoretically-implied) scaling factors. The factors considered can be characterized as those that measure market liquidity and those that measure the degree of information asymmetry that exists at a particular time. Regarding the latter measures, this feature of financial markets is assessed by considering, inter alia, price discovery around the release of key macroeconomic information. Using high-frequency data from five constituent S&P 500 index markets, the results provide two main insights into price discovery in this fragmented market. First, the majority of price discovery appears to occur in the market for the individual stocks making up the index and in the (electronically traded) E-mini futures market. And second, the E-mini futures market becomes the dominant price discovery market only during periods of extreme information asymmetry and when this market is liquid - a finding that supports theoretical arguments proposed in the related literature.

Suggested Citation

  • Nicholas Taylor, 2011. "Time-varying price discovery in fragmented markets," Applied Financial Economics, Taylor & Francis Journals, vol. 21(10), pages 717-734.
    • Handle: RePEc:taf:apfiec:v:21:y:2011:i:10:p:717-734
    DOI: 10.1080/09603107.2010.535784
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    2. Yang Hu & Yang (Greg) Hou & Les Oxley, 2019. "Spot and Futures Prices of Bitcoin: Causality, Cointegration and Price Discovery from a Time-Varying Perspective," Working Papers in Economics 19/13, University of Waikato.
    3. Ibikunle, Gbenga, 2018. "Trading places: Price leadership and the competition for order flow," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 178-200.
    4. Hou, Yang & Nartea, Gilbert, 2017. "Price Discovery in the Stock Index Futures Market: Evidence from the Chinese stock market crash," MPRA Paper 81995, University Library of Munich, Germany.
    5. Yang Hou & Steven Li & Fenghua Wen, 2021. "Time-varying information share and autoregressive loading factors: evidence from S&P 500 cash and E-mini futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 57(1), pages 91-110, July.
    6. de Jong, F.C.J.M. & Schotman, P.C., 2010. "Price discovery in fragmented markets," Other publications TiSEM 4650a9e7-c4cf-41cf-a771-e, Tilburg University, School of Economics and Management.
    7. Frijns, Bart & Indriawan, Ivan & Tourani-Rad, Alireza, 2015. "Macroeconomic news announcements and price discovery: Evidence from Canadian–U.S. cross-listed firms," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 35-48.
    8. Hu, Yang & Hou, Yang Greg & Oxley, Les, 2020. "What role do futures markets play in Bitcoin pricing? Causality, cointegration and price discovery from a time-varying perspective?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    9. Frijns, Bart & Zwinkels, Remco C.J., 2018. "Time-varying arbitrage and dynamic price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 485-502.
    10. Hou, Yang & Li, Steven, 2017. "Time-Varying Price Discovery and Autoregressive Loading Factors: Evidence from S&P 500 Cash and E-Mini Futures Markets," MPRA Paper 81999, University Library of Munich, Germany.

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