High-Frequency Trading Behaviour and Its Impact on Market Quality: Evidence from the UK Equity Market

Benos, Evangelos; Sagade, Satchit

doi:10.2139/ssrn.2184302

Cited by 33 publications

(43 citation statements)

References 10 publications

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“…This relatively benign view of HFT is shared by regulators in other markets, for example, the Bank of England. Researchers from the Bank of England recently concluded that (Benos and Sagade, 2012):…”

Section: Resultsmentioning

confidence: 99%

High-Frequency Trading and Its Regulation in the Australian Equity Markets

Ali¹

2015

The Handbook of High Frequency Trading

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Section: Resultsmentioning

confidence: 99%

High-Frequency Trading and Its Regulation in the Australian Equity Markets

Ali¹

2015

The Handbook of High Frequency Trading

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“…Additionally, we include a set of controls as we expect that MP disp is also influenced by other factors, in particular we include hourly and daily dummies as market activity varies over time (Chan et al, 1996;Jain, 1988;McInish and Wood, 1992). We expect that volatility influences the MP disp as it influences activity of market participants, which has been in particular shown for HFTs by Benos and Sagade (2012). The volatility is calculated as mean standard deviation of the price volatility between both markets.…”

Section: Operationalization Of Key Variablesmentioning

confidence: 99%

High-Frequency Trading and its Role in Fragmented Markets

Haferkorn

2017

Journal of Information Technology

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The financial services industry is among the leading industries in IT-spending. Still, little research exists which investigates how IT influences the financial services sector. Against this background, we study how a technology which emerged within the last years affects securities trading: High-Frequency Trading (HFT). Hereby, we focus on HFT and its impact on market efficiency. On the basis of a long-term analysis, we find that HFT decreases price dispersion among two distant markets. Analyzing the introduction of the German HFT Act, we further observe that the price dispersion between two leading trading venues for German blue chip securities increased. We conclude that HFT increases market efficiency in the European market landscape by transmitting information between distant markets.

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“…Indeed, in an admittedly simplified framework, and in a special case, Cvitanić and Kirilenko [11] have shown that "the faster humans submit and vary their orders, the more profits the machine makes." 3 A second high frequency trading strategy that "front runs" orders is contained in a recent paper by McInish and Upson [27]. As explained therein, HFTs can exploit the quote exception rule to take advantage of "stale" orders.…”

Section: The "Front Running" Profits Of Hftsmentioning

confidence: 99%

Liquidity Suppliers and High Frequency Trading

Jarrow

Protter

2015

SIAM J. Finan. Math.

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This paper provides a mathematical analysis of how high frequency traders profit from their speed with respect to the limit order book. We show that their profits can be decomposed into two components. The first is due to their ability to execute market orders at limit order prices and without incurring any liquidity costs themselves. The second is by "front running" market orders with limit prices. These trading profits are shown to be at the expense of ordinary traders who submit market orders and sophisticated traders who submit limit orders or who use algorithmic trading to split up and execute large trades. We do not consider the welfare implications of our insights for the efficient functioning of financial markets. Introduction.One might (roughly) classify traders in financial markets into three rubrics: ordinary traders (OTs), sophisticated traders (STs), and high frequency traders (HFTs). The OTs, often individuals, generate small trades typically involving only a few hundred shares either using an electronic platform or a financial advisor. In contrast to OTs, we have STs, such as mutual funds, insurance companies, pension funds, etc., who typically make larger trades. To avoid large liquidity costs concomitant with such large trades, STs may farm out their trades to financial institutions (including hedge funds) who employ algorithmic strategies to break the large order into small pieces with rapid trading. These two groups, the OTs and the STs, hold securities for their investment value over relatively long time horizons. They trade based on information events or for portfolio rebalancing considerations. The third type of trader, the HFTs, are fundamentally different. They trade and hold securities only over extremely short time intervals. They trade seeking to earn profits, typically at the expense of the OTs, and especially at the expense of the STs, in spite of their use of algorithmic trading strategies to minimize liquidity costs.The speed advantage of the HFTs in their access to financial data and execution translates into three sources for their economic profits:1. Market power: The ability to trade strategically given a nontransitory quantity impact on prices. 2. Informed trading: The first to access market moving information.

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High-Frequency Trading Behaviour and Its Impact on Market Quality: Evidence from the UK Equity Market

Cited by 33 publications

References 10 publications

High-Frequency Trading and Its Regulation in the Australian Equity Markets

High-Frequency Trading and Its Regulation in the Australian Equity Markets

High-Frequency Trading and its Role in Fragmented Markets

Liquidity Suppliers and High Frequency Trading

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