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High frequency traders and the price process

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  • Aït-Sahalia, Yacine
  • Brunetti, Celso

Abstract

Using a dataset that uniquely identifies counterparties to each S&P500 eMini transaction, we classify each market participant as high or low frequency, and each transaction, by the speed of the traders involved. We investigate empirically the comparative influence of high and low frequency traders on the price process, and conversely the influence of the price process on the trading of high and low frequency traders. We find that high frequency traders have a particularly high success rate on each transaction, measured by the likelihood that the following price change will go in their direction as well as by the amount of time they have to wait to realize their gain, when trading against low frequency traders. Contrary to common wisdom, we find that high frequency traders’ activity does not induce volatility or jumps. In fact, it is their absence that is problematic: volatility and jumps are more prevalent in periods when they trade less intensely. Conversely, we find that spikes in volatility and jumps cause high frequency traders to trade less intensely, decreasing their provision of liquidity. Finally, looking at the market microstructure noise component to the price model, we find that higher level of noise generates trading opportunities for high frequency traders and lead them to increase their trading activity.

Suggested Citation

  • Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.
  • Handle: RePEc:eee:econom:v:217:y:2020:i:1:p:20-45
    DOI: 10.1016/j.jeconom.2019.11.005
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    References listed on IDEAS

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    Cited by:

    1. Arumugam, Devika & Prasanna, P. Krishna & Marathe, Rahul R., 2023. "Do algorithmic traders exploit volatility?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).

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    More about this item

    Keywords

    High frequency trading; Liquidity; Market impact; Price process; Volatility; Jumps; Market microstructure noise;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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