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When spread bites fast – Volatility and wide bid-ask spread in a mixed high-frequency and low-frequency environment

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  • Virgilio, Gianluca Piero Maria

Abstract

This research focuses on the impact High-Frequency Trading has on price volatility when bid-ask spread is wide. The theoretical part introduces a set of equations and presents an Agent Based Model implemented via a computer-based simulation. The wide spread leads to the appearance of unusual phenomena caused by the relative speed difference between the fast and slow traders. The latter agents tend to quote limit orders that look irrational, as they are distant more than one tick from the top-of-book. The same relative speed difference causes slow traders to post market orders that execute at price worse than originally intended. Both these abnormal orders tend to increase local volatility. Other results found by the simulation are an increase in global volatility (computed both as the difference of maximum less minimum price and as standard deviation of price distribution) and in volatility at sub-second timescales. These occurrences penalise slower traders and affect market stability. All the results are consistent both under quiet and stressed market conditions. The results found are then compared with audit trail data to verify the soundness of theory against practice.

Suggested Citation

  • Virgilio, Gianluca Piero Maria, 2020. "When spread bites fast – Volatility and wide bid-ask spread in a mixed high-frequency and low-frequency environment," Research in International Business and Finance, Elsevier, vol. 51(C).
  • Handle: RePEc:eee:riibaf:v:51:y:2020:i:c:s0275531919302636
    DOI: 10.1016/j.ribaf.2019.101066
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    References listed on IDEAS

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    More about this item

    Keywords

    High-frequency trading; Volatility; Naïve orders; Bad deals; Market stability;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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