How does HFT activity impact market volatility and the bid-ask spread after an exogenous shock? An empirical analysis on S&amp;P 500 ETF

Bazzana, Flavio; Collini, Andrea

doi:10.1016/j.najef.2020.101240

Cited by 12 publications

(5 citation statements)

References 15 publications

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“…One should treat this possibility with caution and keep in mind that the price formation, and systemic instabilities for that matter, occur as a result of the interaction of all market participants. HFT share in the electronic message and order traffic as well as in trade numbers and turnover is substantially high especially in developed markets (Brogaard, 2010;Boehmer et al, 2018;Bazzana and Collini, 2020). Besides, few traders with large activity constitute the aforementioned HFT share.…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, HFT's participation in the trading of Swedish large stocks in a 2011-2012 sample is between 25% and 50% (Hagströmer and Norden, 2013). HFT share in U.S. equities markets in 2016 is approximately 60% (see for example Bazzana and Collini, 2020). Besides equity markets, futures markets are also concentrated with HFT activity; shares in total trading volume of U.S. foreign exchange futures, interest rates futures, and Treasury 10-year futures being around 80%, 66%, and also 66%, respectively (Miller and Shorter, 2016).…”

Section: Introductionmentioning

confidence: 99%

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High-Frequency Trading and its Impact on Market Liquidity: A Review of Literature

Ersan

Dalgic

Ekinci

et al. 2021

Alanya Akademik Bakış

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High-frequency trading (HFT) has been dominating the activity in developed financial markets in the last two decades. Despite its recent formation, the literature on the impacts of HFT on financial markets and participants is broad. However, there are ongoing debates and unanswered questions within many subtopics. We survey through the research towards HFT effects on liquidity in an attempt to explain the coexistence of evidence regarding both the positive and the negative impacts of HFT. We name two main factors leading to mixed results. Former concerns the negative market conditions such as intraday shocks, through which HFT trading patterns may sharply change. Latter regards the certain characteristics of HFT liquidity provision with the potential to present externalities for the market.2 BYX exchange utilized by CBOE reduced order processing times by around sevenfold from 445 microseconds in 2009 to 64 microseconds in 2018 (Baldauf and Mollner, 2020). HFT firms are in an arms race that leads them to send data from exchanges to electronic traders in latencies as small as 4 nanoseconds (Sprothen, 2016). 3 Throughout the text, we use 'high-frequency trading (trader)' and 'low-latency trading (trader)' interchangeably. We use 'HFT' as the acronym for high-frequency trading; 'HFTs' as the acronym for high-frequency traders; and non-HFTs as the acronym for low-frequency traders (traders other than high-frequency traders).

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High-Frequency Trading and its Impact on Market Liquidity: A Review of Literature

Ersan

Dalgic

Ekinci

et al. 2021

Alanya Akademik Bakış

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“…Jarrow and Protter (2012) argued that high-frequency traders make gains by drifting stock prices away from intrinsic value, resulting in greater volatility, which is detrimental to other market players. In their empirical study, Bazzana and Collini (2020) segregated HFT into active and passive categories and found only active HFT increased volatility and bid-ask spreads for S&P ETF.…”

Section: Key Factors Influencing Stock Market Volatilitymentioning

confidence: 99%

Stock market volatility: a systematic review

Dhingra,

Batra,

Aggarwal

et al. 2023

JM2

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Purpose The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility. Design/methodology/approach This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area. Findings The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area. Originality/value This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

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“…Today, HFT dominates trading volume, accounting for roughly 70% of activity [ 36 – 38 ]. A growing body of research investigates the impact of HFT on liquidity, bid-ask spreads, volatility, and efficiency [ 39 – 42 ]. They basically find that HFT activity is associated with narrower spreads, lower volatility, and greater liquidity.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

The adaptive market hypothesis and high frequency trading

2021

PLoS ONE

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This paper uses NASDAQ order book data for the S&P 500 exchange traded fund (SPY) to examine the relationship between one-minute, informational market efficiency and high frequency trading (HFT). We find that the level of efficiency varies widely over time and appears to cluster. Periods of high efficiency are followed by periods of low efficiency and vice versa. Further, we find that HFT activity is higher during periods of low efficiency. This supports the argument that HFTs seek profits and risk reduction by actively processing information, through limit order additions and cancellations, during periods of lower efficiency and revert to more passive market-making and rebate-generation during periods of higher efficiency. These findings support the argument that the adaptive market hypothesis (AMH) is an appropriate description of how prices evolve to incorporate information.

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How does HFT activity impact market volatility and the bid-ask spread after an exogenous shock? An empirical analysis on S&P 500 ETF

Cited by 12 publications

References 15 publications

High-Frequency Trading and its Impact on Market Liquidity: A Review of Literature

High-Frequency Trading and its Impact on Market Liquidity: A Review of Literature

Stock market volatility: a systematic review

The adaptive market hypothesis and high frequency trading

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