High-frequency Trading Activity Research Articles

Algorithmic Trading and Challenges on Retail Investors in Emerging Markets

Mixed views on automated trading in the extant literature lead to ongoing debates on algorithmic trading (AT) and high-frequency trading (HFT). This study elaborates on the rising ethical issues and regulatory challenges of algorithmic trading and high-frequency trading in emerging markets. While developed capital markets are dominated by institutional investors, emerging markets consist of a large proportion of retail investors who may suffer from aggravated liquidity asymmetry and stock price turbulence due to HFT and AT. Furthermore, we review current regulations of HFT in the U.S. and European markets and provide a framework of regulatory enforcements on AT and HFT for investor protection in emerging markets. This study cautions policymakers in emerging markets that legal and regulatory monitoring of AT and HFT activities is especially necessary.

High-Frequency Trading (HFT) and Market Quality Research: An Evaluation of the Alternative HFT Proxies

We examine the soundness of high-frequency trading (HFT) proxies that are widely defined on the limit order book (LOB) information. We use a unique TRTH (Thomson Reuters Tick History) millisecond time-stamped intraday trades and quotes dataset enriched with 10 levels of LOB depth messages for 149 highly fragmented LSE listed stocks for the period 2005 to 2016. We explore a sharp uptrend in HFT activities and accompanying improvement in market liquidity in the European market. We show that alternative HFT proxies built on LOB are not equally powerful. The HFT proxy defined on the five best LOB prices (the mid point of a typical limit order book) provides a better HFT identification than the one popularly defined on the first best prices (BBO). We suggest that picking the LOB information beyond a certain level (e.g., the best five prices) of market depth in developing HFT proxy is counterintuitive. Evidence indicates that high-frequency traders (HFTs) participate in both competitive (narrow) and passive (wider) quoting as a market making strategy; however, they do not participate in passive quoting excessively.

High-frequency trading and market quality: The case of a “slightly exposed” market

Impacts of high-frequency trading (HFT) on market quality and various actors have been broadly studied. However, what happens when HFT is not a prominent figure in a market remains relatively unexplored. The paper seeks to answer this question focusing on 30 blue chip stocks in an emerging market, Borsa Istanbul, through Dec 2015 to Mar 2017. Despite a low share in the overall activity, HFT has observable effects, i.e. liquidity provision by non-HFT traders significantly reduces with HFT. Moreover, HFT generates profits on both positive and negative return days. Yet, HFT activity does not have an impact on volatility. These findings raise concerns regarding HFT and show potential externalities are not specific to the markets with HFT dominance.

The adaptive market hypothesis and high frequency trading

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.

International Review of Equity Market Structure Regulation: Phase III

International Review of Equity Market Structure Regulation: Phase III

Optimal market-Making strategies under synchronised order arrivals with deep neural networks

This study investigates the optimal execution strategy of market-making for market and limit order arrival dynamics under a novel framework that includes a synchronised factor between buy and sell order arrivals. Using statistical tests, we empirically confirm that a synchrony propensity appears in the market, where a buy order arrival tends to follow the sell order’s long-term mean level and vice versa. This is presumably closely related to the drastic increase in the influence of high-frequency trading activities in markets. To solve the high-dimensional Hamilton–Jacobi–Bellman equation, we propose a deep neural network approximation and theoretically verify the existence of a network structure that guarantees a sufficiently small loss function. Finally, we implement the terminal profit and loss profile of market-making using the estimated optimal strategy and compare its performance distribution with that of other feasible strategies. We find that our estimation of the optimal market-making placement allows significantly stable and steady profit accumulation over time through the implementation of strict inventory management.

High-Frequency Trading and Market Quality: The Case of 'Slightly Exposed' Market

Impacts of high-frequency trading (HFT) on market quality and various actors have been broadly studied. However, what happens when HFT is not a prominent figure in a market remains relatively unexplored. The paper seeks to answer this question focusing on 30 blue chip stocks in an emerging market, Borsa Istanbul, through Dec 2015 to Mar 2017. Despite a low share in the overall activity, HFT has observable effects: liquidity provision by non-HFT traders significantly reduces with HFT; HFT activity on the sell side induces higher volatility; and HFT generates profits on both positive and negative return days. These findings raise concerns regarding HFT and show potential externalities are not specific to the markets with HFT dominance.

Intraday interactions between high-frequency trading and price efficiency

We examine intraday interactions between high-frequency trading (HFT) and the informational quality of prices to provide evidence on the role of HFT in the price discovery process. HFT and price efficiency display reverse L-shaped patterns with low levels at the open and strong improvement across the trading day. Using the panel vector auto-regression model, we find bi-directional causality between HFT and price efficiency: High-frequency traders react actively to movements in price efficiency, while greater intensity of HFT is associated with more efficient prices. Overall, HFT activities can be considered as efficient ways to incorporate information quickly and accurately into prices.

The impact of the change in USDA announcement release procedures on agricultural commodity futures

In August 2018, the US Department of Agriculture (USDA) ceased its practice of early media access during lockup, in which the news media have access to crop and livestock reports ahead of scheduled announcements. News media no longer have a 90-min window to digest and write custom reports and are now subject to the same information distribution rules as the public. We examine the impact of this regulatory change on the trading of agricultural commodity futures. We assess changes in market quality (e.g., liquidity, volatility, information asymmetry, and high-frequency trading activity) around news announcements before and after the regulatory change. Although the majority of our market quality proxies react to USDA news releases, they are not statistically different before and after the regulatory change. The overall results show that ending the practice of early media access lockup does not have a significant economic impact on agricultural futures trading around USDA news releases.

High-Frequency Trading Activities and Brokerage Firms Effect : Empirical Evidence From the Indonesia Stock Exchange

This research studies the trading activity of type of traders through their brokers. Order imbalance is believed to be a better proxy for explaining trading activity. This paper presents some empirical test that on brokerage level analysis exhibit information paradigm in Indonesia which market makers and specialist are not available. We divide imbalances into groups of samples (all stocks and most liquid stocks), trader type (foreign or domestic) and size of brokerage firm (small to big). Our results show that order imbalances generally have a positive serial correlation for all the traders and brokers analyzed. However, we find that the determinant of order imbalances is a particular phenomenon at the brokerage level, whose results differ from our market-wide analysis. We do not find that previous order imbalances can predict market returns across trader type and brokerage class. In contrast, for the inventory paradigm, the evidence from the brokerage level analysis indicates that information dissemination is induced order imbalance by brokerage house.

A state-space modeling of the information content of trading volume

We propose a state-space modeling approach for decomposing trading volume into its liquidity-driven and information-driven components. Using a set of high-frequency S&P 500 stock data, we show that informed trading is linked with a reduction in volatility, illiquidity, and toxicity/adverse selection. We observe that our estimated informed trading component of volume is a statistically significant predictor of one-second stock returns; however, it is not a significant predictor of one-minute stock returns. This disparity is explained by high-frequency trading activity, which eliminates pricing inefficiencies at low latencies.

Does high-frequency trading reduce market underreaction to earnings news?

This paper examines the impact of high-frequency trading (HFT) on market underreaction to earnings news as measured by the magnitude of post-earnings announcement drift (PEAD). Using a dataset provided by NASDAQ, we are able to better identify HFT activities and reduce measurement errors. We find that the magnitude of PEAD decreases with the increase of HFT. More importantly, we show that this effect is due to HFT's liquidity supplying role (i.e., passive HFT fulfilling market orders), not liquidity demanding role (i.e., HFT initiating market orders). The results also reveal that the effect is more pronounced when earnings surprises are extreme and large. Taken together, HFT seems to help mitigate market inefficiency by providing liquidity.

High-frequency Trading around RBA Announcement

We study high-frequency trading (HFT) activities and their consequent price impacts on the ASX around RBA announcement. RBA announcement provides an ideal setting for studying the speed advantage of high-frequency traders (HFTs), as the announcement has significant impact on stock prices and there is highly limited information leakage prior to announcement. We observe a sharp increase in the number of HFT activities in the first ten seconds after announcement. HFTs’ trades generate significantly higher price impacts, which suggests that the speed advantage enables HFTs to “pick off” slow traders and avoid being “picked off” by other fast traders, imposing adverse selection costs on slow traders.

Is There a Magnet Effect of Rule-Based Circuit Breakers in Times of High-Frequency Trading?

This paper studies whether rule-based circuit breakers in the form of short-lived volatility interruptions exhibit a magnet effect in times of high-frequency trading. Based on a sample of 3,271 volatility interruptions on two major European venues, we analyze whether trading aggressiveness, trading activity, and volatility accelerate close to volatility interruptions indicating a magnet effect. Although the duration of the interruptions is meaningful given today's high-frequent securities markets, we do not find any evidence for a magnet effect. Rather, our results show that trading aggressiveness, trading activity, and volatility gradually slow down towards the triggering threshold and that price changes even revert in case of downward-triggered interruptions. These findings hold both for different levels of high-frequency trading activity and for disclosed and undisclosed price limits triggering the circuit breaker.

The Information Content of High Frequency Trading Volume

We propose a state-space modeling approach for decomposing trading volume into its liquidity-driven and information-driven components. Using a set of high-frequency SP however, it is not a significant predictor of one-minute stock returns. This disparity is explained by high-frequency trading activity, which eliminates pricing inefficiencies at low latencies.

The Competitive Landscape of High-Frequency Trading Firms

This paper studies correlations between the strategies of high-frequency trading (HFT) firms, which is a manifestation of the extent of competition in which these firms engage when pursuing similar strategies. We use a principal component analysis to show that there are several underlying common strategies and that the competing HFT firms pursuing these strategies generate most HFT activity. We investigate whether competition between HFT firms creates a systematic return factor, but find no supporting evidence for such an influence. However, the short-interval return volatility of most stocks loads negatively on a market-wide measure of correlated HFT strategies. The mitigating impact of HFT competition on stock volatility appears to be driven at least in part by a market-making strategy. We further document a negative relationship between two forms of competition—that between HFT firms and that between trading venues. We investigate a potential driver behind this negative relationship, and show that greater HFT competition within a trading venue helps smaller trading venues become more competitive or viable in terms of posting better prices and narrower spreads.

Interactions among High-Frequency Traders

Using unique transactions data for individual high-frequency trading (HFT) firms in the U.K. equity market, we examine the extent to which the trading activity of individual HFT firms is correlated with each other and the impact on price efficiency. We find that HFT order flow, net positions, and total volume exhibit significantly higher commonality than those of a comparison group of investment banks. However, intraday HFT order flow commonality is associated with a permanent price impact, suggesting that commonality in HFT activity is information based and so does not generally contribute to undue price pressure and price dislocations.

Multimarket High-Frequency Trading and Commonality in Liquidity

This paper examines the effects of multimarket high-frequency trading (HFT) activity on liquidity co-movements across different markets. Multimarket trading by HFTs connects individual markets in a single network, which should induce stronger network-wide liquidity co-movements. We use the staggered introduction of an alternative trading platform, Chi-X, in European equity markets as our instrument for an exogenous increase in multimarket HFT activity. Consistent with our predictions, we find that liquidity co-movements within the aggregate network of European markets significantly increase after the introduction of Chi-X and even exceed liquidity co-movements within the home market. They are especially strong in down markets and for stocks with a higher intensity of HFT trading in the post-Chi-X period.

Time to Slow Down for High‐Frequency Trading? Lessons from Artificial Markets

SummaryIn this paper, we focus on the French cancel order tax implemented on 1 August 2012. We question the effectiveness of the modified tax with no exemptions and we analyze its impact on market quality, measured by liquidity, volatility and efficiency. Additionally, this paper raises the question whether this tax leads to a reduction of high‐frequency trading (HFT) activities and a decline in trading volume. Based on our findings we report that introduction of cancel order tax only slightly reduces HFT activities, but it significantly affects market liquidity, increases market volatility and leads to deteriorating market efficiency. We conclude that it is difficult to dissuade investors from entering into unproductive trades and eliminate negative outputs of HFT (such as price manipulations) through tax, without altering the benefits of HFT like liquidity provision and efficient price discovery.

One size fits all? High frequency trading, tick size changes and the implications for exchanges: market quality and market structure considerations

This paper offers a systematic review of the empirical literature on the implications of tick size changes for exchanges. Our focus is twofold: first, we are concerned with the market quality implications of a change in the minimum tick size. Second, we are interested in the implications of changes in the minimum tick size on market structure. We show that there is a large body of empirical literature that documents a decrease in transaction costs following a decrease in the minimum tick size. However, even though market liquidity increases, the incentive to provide market making activities decreases. We document a strong link between the minimum tick size regulations and the recent increase in high frequency trading activity. A smaller tick enhances the price discovery process. However, the question of how multiple tick size regimes affect market liquidity in a fragmented market remains to be answered. Finally, we identify topics for future research; we discuss the empirical literature on the minimum trade unit and the recent calls for a minimum resting time for quotes.