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The interactions between price discovery, liquidity and algorithmic trading for U.S.-Canadian cross-listed shares

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  • Frijns, Bart
  • Indriawan, Ivan
  • Tourani-Rad, Alireza

Abstract

We analyze price discovery dynamics for Canadian companies cross-listed on the NYSE from January 2004 to August 2017. We employ a structural vector autoregression to assess the interactions between price discovery, liquidity and algorithmic trading activity. We observe that over time, the U.S. market is gaining dominance in terms of price discovery. Improvements in liquidity increase a market's contribution to price discovery, and vice versa. We find that algorithmic trading activity is negatively related to price discovery, indicating negative externalities of high-frequency trading. These results are robust to fragmentation in the Canadian financial markets as well as regulatory changes in both the U.S. and Canada.

Suggested Citation

  • Frijns, Bart & Indriawan, Ivan & Tourani-Rad, Alireza, 2018. "The interactions between price discovery, liquidity and algorithmic trading for U.S.-Canadian cross-listed shares," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 136-152.
    • Handle: RePEc:eee:finana:v:56:y:2018:i:c:p:136-152
    DOI: 10.1016/j.irfa.2018.01.005
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    Cited by:

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    8. Lei Wu & Kuan Xu & Qingbin Meng, 2021. "Information flow and price discovery dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 329-367, January.
    9. Xunfa Lu & Zhitao Ye & Kin Keung Lai & Hairong Cui & Xiao Lin, 2022. "Time-Varying Causalities in Prices and Volatilities between the Cross-Listed Stocks in Chinese Mainland and Hong Kong Stock Markets," Mathematics, MDPI, vol. 10(4), pages 1-19, February.
    10. Ben Ammar, Imen & Hellara, Slaheddine, 2021. "Intraday interactions between high-frequency trading and price efficiency," Finance Research Letters, Elsevier, vol. 41(C).
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    12. Cepoi, Cosmin-Octavian & Anghel, Dan-Gabriel & Pop, Ionuţ Daniel, 2021. "Asymmetries and flight-to-safety effects in the price discovery process of cross-listed stocks," Economic Modelling, Elsevier, vol. 98(C), pages 302-318.
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    More about this item

    Keywords

    Market microstructure; Price discovery; Cross-listings;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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