High Frequency Traders: Angels or Devils?

MacIntosh, Jeffrey G.

doi:10.2139/ssrn.2340673

Cited by 4 publications

(1 citation statement)

References 37 publications

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“…But trading activity has profoundly changed from the old phone conversation or click and trade on a screen to software programming. Market statistics confirm that automated algorithms carry out a significant fraction of the trading activity on US and Europe electronic exchanges [2,3]. As algos feed on financial and news data, the speed of information processing has dramatically increased and potentially allows large price movements to propagate very rapidly through different assets and exchanges [4].…”

Section: Introductionmentioning

confidence: 94%

Collective synchronization and high frequency systemic instabilities in financial markets

Calcagnile¹,

Bormetti

Treccani³

et al. 2017

Quantitative Finance

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Recent years have seen an unprecedented rise of the role that technology plays in all aspects of human activities. Unavoidably, technology has heavily entered the Capital Markets trading space, to the extent that all major exchanges are now trading exclusively using electronic platforms. The ultra fast speed of information processing, order placement, and cancelling generates new dynamics which is still not completely deciphered.Analyzing a large dataset of stocks traded on the US markets, our study evidences that since 2001 the level of synchronization of large price movements across assets has significantly increased. Even though the total number of over-threshold events has diminished 1 www.quantlab.it 1 arXiv:1505.00704v1 [q-fin.ST] 4 May 2015 in recent years, when an event occurs, the average number of assets swinging together has increased. Quite unexpectedly, only a minor fraction of these events -regularly less than 40% along all years -can be connected with the release of pre-announced macroeconomic news. We also document that the larger is the level of sistemicity of an event, the larger is the probability -and degree of sistemicity -that a new event will occur in the near future. This opens the way to the intriguing idea that systemic events emerge as an effect of a purely endogenous mechanism. Consistently, we present a high-dimensional, yet parsimonious, model based on a class of self-and cross-exciting processes, termed Hawkes processes, which reconciles the modeling effort with the empirical evidence.

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Section: Introductionmentioning

confidence: 94%

Collective synchronization and high frequency systemic instabilities in financial markets

Calcagnile¹,

Bormetti

Treccani³

et al. 2017

Quantitative Finance

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Rock around the clock: An agent-based model of low- and high-frequency trading

et al. 2015

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Abstract. We build an agent-based model to study how the interplay between low-and highfrequency trading affects asset price dynamics. Our main goal is to investigate whether highfrequency trading exacerbates market volatility and generates flash crashes. In the model, lowfrequency agents adopt trading rules based on chronological time and can switch between fundamentalist and chartist strategies. On the contrary, high-frequency traders activation is event-driven and depends on price fluctuations. High-frequency traders use directional strategies to exploit market information produced by low-frequency traders. Monte-Carlo simulations reveal that the model replicates the main stylized facts of financial markets. Furthermore, we find that the presence of high-frequency trading increases market volatility and plays a fundamental role in the generation of flash crashes. The emergence of flash crashes is explained by two salient characteristics of highfrequency traders, i.e., their ability to i) generate high bid-ask spreads and ii) synchronize on the sell side of the limit order book. Finally, we find that higher rates of order cancellation by high-frequency traders increase the incidence of flash crashes but reduce their duration.

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