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

In 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.     

Liquidity commonality and high frequency trading: Evidence from the French stock market

High frequency trading (HFT) depends on sophisticated algorithms to closely monitor price changes across securities. Theory predicts this technological advantage should translate into market-wide liquidity co-variation, by transmitting information-based liquidity shocks. Using a dataset of orders and trades from the French stock market, we investigate whether HFT algorithms constitute a source of systematic liquidity risk. We demonstrate that, across securities, the liquidity offered by high frequency traders is significantly less diverse than that of traditional traders; this finding is in line with the cross-asset learning hypothesis. The excessive co-movement in liquidity is also partly explained by common market making rules. In periods of increased market stress, we find HFT, designated market making, and order size to be important sources of liquidity commonality. Our results have policy implications for market regulators in Paris, suggesting the inclusion of maximum spread-limit rules in market making contracts will reduce the possibility of liquidity drying up when markets are in turmoil.     

Does high-frequency trading actually improve market liquidity? A comparative study for selected models and measures

The increasing volume of messages sent to the exchange by algorithmic traders stimulates a fierce debate among academics and practitioners on the impacts of high-frequency trading (HFT) on capital markets. By comparing a variety of regression models that associate various measures of market liquidity with measures of high-frequency activity on the same dataset, we find that for some models the increase in high-frequency activity improves market liquidity, but for others, we get the opposite effect. We indicate that this ambiguity does not depend only on the stock market or the data period, but also on the used HFT measure: the increase of high-frequency orders leads to lower market liquidity whereas the increase in high-frequency trades improves liquidity. We hypothesize that the observed decrease in market liquidity associated with an increasing level of high-frequency orders is caused by a rise in quote volatility.     

High-frequency trading and stock liquidity: An intraday analysis

This paper studies the impact of high-frequency trading (HFT) on intraday liquidity of CAC40 stocks listed on Euronext. Spreads display an intraday L-shaped pattern, while quoted depth follows an inverse pattern: low at the open and increasing towards the end of the trading day. When liquidity demand is particularly high, there is a high rate of order cancellations attributable to high-frequency traders who use frequent order cancellations to strategically manage their limit orders and close positions near the market close. Using the generalized method of moments estimator, we generate strong evidence that greater intensity of HFT is associated with lower spreads and higher depth. The positive effect of HFT on liquidity is due mainly to decreased adverse selection costs arising from asymmetric information among market participants.     

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.     

国外高频交易的发展现状及启示

证券市场上的高频交易模式大体上分为四类:订单拆分策略、做市交易策略、定量化交易策略和其他策略。研究发现:(1)高频交易降低了买卖价差,提高了市场流动性,而并没有增加市场波动率,甚至反而可能降低了市场波动率;(2)没有发现高频交易者存在系统性抢单行为(并不排除有特定高频交易者存在此类行为);(3)学术研究认为高频交易有导致市场风险的可能性,但是事件调查大多认为高频交易不是引发市场风险的罪魁祸首。本文认为,对高频交易的监管应该注重抓住重点区别对待,以维护公平、透明、高效的市场秩序。     

Very fast money: High-frequency trading on the NASDAQ

This paper provides evidence regarding high-frequency trader (HFT) trading performance, trading costs, and effects on market efficiency using a sample of NASDAQ trades and quotes that directly identifies HFT participation. I find that HFTs engage in successful intra-day market timing, spreads are wider when HFTs provide liquidity and tighter when HFTs take liquidity, and prices incorporate information from order flow and market-wide returns more efficiently on days when HFT participation is high.     

Pick Your Poison—Fragmentation or Market Power? An Analysis of RegNMS,High Frequency Trading,and Securities Market Structure

The publication of Michael Lewis's has intensified an already contentious debate over high frequency trading (HFT). But the causes that have given rise to HFT are more complicated—and the general economic consequences far more positive—than at least the popular accounts (including Lewis's own) of the book would suggest. While directing much of its attention to the powerful computers and “predatory” potential of HFT, the “media” version of Lewis's book has all but ignored the fundamental driver of such activity: the implementation in 2007 of SEC Regulation NMS, which required all exchanges to direct their orders to the exchanges with the best prices. Before RegNMS, U.S. equity trading was largely dominated by NYSE and Nasdaq. The major exchanges' effective “ownership” of their order flow gave exchange specialists significant edges in trading. RegNMS has resulted in the proliferation of competing stock exchanges, which in turn has dramatically reduced both trading costs and the economic franchise value enjoyed by institutional traders associated with the previously dominant exchanges. The balance of evidence strongly indicates that the cost of trading has declined for retail traders and investors. The big losers have been the previously advantaged wholesale traders. HFT is simply one of the outcomes of the new, more competitive trading environment created by Regulation NMS.     

The impact of mandatory IFRS reporting on institutional trading costs: Evidence from Australia

This study examines the impact of mandatory International Financial Reporting Standards (IFRS) on the market quality of the Australian Securities Exchange (ASX) 200 constituent stocks. Using traditional metrics that are consistent with prior literature (i.e., bid‐ask spreads), the first stage analysis confirms that stock liquidity has improved. However, when the analysis is extended to consider the trading costs incurred by market participants (i.e., execution shortfall), results suggest liquidity has not changed significantly. The paper utilizes rich unique datasets that contain detailed trade information, and findings are robust after controlling for trade difficulty and market conditions. In the era of High Frequency Trading (HFT) and occurrences of ‘fleeting’ liquidity, this paper provides some evidence that while IFRS may have enhanced ‘visible’ bid‐ask spreads, tangible liquidity for market participants, particularly global institutional investors, has not improved significantly.     

The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity

We propose a model for determining the optimal bid-ask spread strategy by a high-frequency trader (HFT) who has an informational advantage and receives information about the true value of a security. We employ an information cost function that includes volatility and the volume of the asset. Subsequently, we characterize the optimal bid-ask price strategies and obtain a stable bid-ask spread. We assume that orders submitted by low-frequency traders (LFTs) and news events arrive at the market with Poisson processes. Additionally, our model supports the trading of the two-sided quote in one period. We find that more LFTs and a higher exchange latency both hurt market liquidity. The HFT prefers to choose a two-sided quote to gain more profits while cautiously chooses a one-sided quote during times of high volatility. The model generates some testable implications with supporting empirical evidence from the NASDAQ-OMX Nordic Market.     

Information‐Hedging Disclosures and Insider Trading

I model the effect of disclosure on the tradeoff between information risk, liquidity risk, and price risk for a well‐informed, risk‐averse insider. Revealing some information before trading decreases the variability of the insider's information advantage and thus reduces his information risk. Disclosure also lowers adverse selection costs for market makers, which reduces the insider's liquidity risk by increasing his trading flexibility. However, disclosure increases price risk for the insider because the price fully reflects the revealed information. The reduction in information and liquidity risks outweigh the rise in price risk when the insider is less risk averse because a less risk‐averse insider's information‐based motive for trading is stronger than his hedging motive. The opposite relation holds when the insider is more risk averse. Therefore, a less (more) risk‐averse insider experiences an increase (decrease) in welfare when he discloses some information before trading. Cost of capital and policy implications are identified.     

Does high frequency algorithmic trading matter for non-AT investors?

The extant literature has typically measured the impact of high frequency algorithmic trading (HFT) on short term outcomes, in seconds or minutes. We focus on outcomes of concern for longer term non-algorithm investors. We find in some cases HFT increases volatility arising from news relating to fundamentals. Furthermore HFT is associated with the transmission of that volatility across industries, and that transmission is based on short term correlations. Finally, we find that the period since the introduction of algorithmic trading (AT) has seen increases in both the variances and covariances of return volatility in most industries. However increases in the variances has not been uniform in that it has fallen sharply in a few industries. The magnitudes are such that, overall, AT has coincided with reduced return volatility variance.     

Security Choice, Information Effects and Firm Characteristics: A Factor Analytic Approach

Abstract:   We examine the marginal choice between debt and equity securities using a factor analytic approach. This data reduction property eliminates the need to select the one best variable to proxy for a particular theoretical construct. Our results reinforce numerous existing findings using traditional methods and suggest both static tradeoff and asymmetric information based considerations are relevant in determining security choice. Two new results are presented related to the accounting liquidity of the firm. First, the preference for equity is increasing with liquidity as suggested by the window of opportunity hypothesis. Secondly, the market response to equity issuance announcements is inversely related to the liquidity of the firm. Profitability and growth measures support Jensen's (1986) agency cost of free cash flow as a potential explanation for the second finding.     

The Elastic Provision of Liquidity by Private Agents

I study a model of investment by financially constrained firms that are heterogeneous with respect to their exposure to an aggregate liquidity shock. A firm that is susceptible to the shock will mitigate its exposure by purchasing claims issued by a firm that is not. Liabilities of an unaffected firm may earn a liquidity premium due to their fungibility, and because they are backed by productive investment, their supply is elastic to the demand. This segmentation implies that an aggregate liquidity shock has different consequences across sectors of the economy.     

Liquidity and Return Relationships in an Emerging Market

In this paper, we investigate the relationship between liquidity and stock returns in the Vietnam stock market during the global financial crisis. Vietnam is one of a new group of frontier emerging markets referred to as CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa). We use a rich and detailed data set of firm characteristics to identify a positive relationship between liquidity and stock returns. This contradicts the negative correlation typically found in stock returns in developed markets. Our results support the proposition that when a market is not fully integrated with the global economy, a lack of liquidity will be a less important risk factor. Our findings contribute to those studies that highlight the diversification benefits from including frontier markets, which have a lower degree of integration with the global economy, in international portfolios.     

Getting the Right Mix of Capital and Cash Requirements in Prudential Bank Regulation*

Cash reserve requirements are useful as a broadly conceived prudential tool, not just as a narrowly focused means of limiting the risks associated with illiquidity. Indeed, illiquidity risk is neither a necessary nor a sufficient condition for establishing bank liquidity requirements. The primary means of mitigating the systemic costs of bank illiquidity risk is the creation of an effective lender of last resort (LOLR). But instead of focusing narrowly on bank funding risks when designing liquidity requirements, regulators should consider tradeoffs among capital requirements, liquidity requirements, and LOLR policies for achieving the broader prudential goal of limiting bank default risk. When considering the optimal tradeoff between capital ratios and cash ratios as prudential requirements, five “frictions” are identified that favor the use of one or the other: (1) the adverse‐selection costs of raising equity (which favors the use of cash); (2) the opportunity cost of forgone abnormal profits (or “quasi rents”) from lending (which favors the use of capital); (3) the limited verifiability of loan outcomes (which favors the use of cash); (4) the moral hazard that results from costly or postponed loss recognition, given the incentive for risk shifting in bad states (which favors the use of cash); and (5) the prospect of changes in the risk environment (which favors cash since it creates greater option value for maintaining targeted default risk with lower adjustment costs in the face of changing loan risk or illiquidity risk). When viewed from the perspective of achieving the main prudential goal of controlling default risk at a minimum social cost, capital requirements have some limitations that favor liquidity requirements, and vice versa. And thus the optimal regulatory policy will combine liquidity and capital requirements.     

Strategic trading and learning about liquidity

Many practitioners point out that the speculative profits of institutional traders are eroded by the difficulty in gauging the price impact of their trades. In this paper, we develop a model of strategic trading where speculators face such a dilemma because of incomplete information about time-varying market liquidity. Unlike the competitive market makers that they trade against, informed traders do not know the distribution of liquidity (“noise”) trades. Instead, they have to learn about liquidity from past prices and trading volume. This learning implies that strategic trades and market statistics such as informational efficiency are path-dependent on past market outcomes. Our paper also has normative implications for practitioners.     

The external effects of bank executive pay: Liquidity creation and systemic risk

We develop a conceptual framework that links the compensation incentives of bank executives to the risk and return externalities generated by banks but borne by society. Using 1994 to 2016 data from large U.S. commercial banks, we find that CEO pay-performance incentives reduce both negative systemic risk externalities and positive liquidity creation externalities, while pay-risk incentives increase both externalities. Our findings offer support for Federal Reserve guidelines that encourage greater reliance on long-term equity-based compensation, and they infer a regulatory tradeoff: Bank executive pay rules aimed at reducing systemic risk will result in reduced system-wide liquidity creation as well.     

Clearing and Collateral Mandates: A New Liquidity Trap?

All too often, legislative solutions to some financial crisis have serious consequences that are both unwanted and unintended. The author of this article foresees several possible negative consequences arising from Title VII of the Dodd‐Frank Act, which mandates that eligible derivatives be cleared through central counterparties (CCPs) that require initial and variation margin. The new legislation also requires that the remaining non‐cleared derivatives that are traded by some market participants be more heavily collateralized. The Act's authors have argued that derivatives pose uniquely dangerous systemic risks because of the leverage and counterparty risk associated with them. Increased collateralization, their thinking goes, would reduce derivatives‐related leverage and the systemic risk to the financial system associated with such leverage. The author argues that these hopes are unduly optimistic because they fail to recognize how market participants can substitute other forms of leverage, such as bank lines of credit or collateral transformation trades, for the leverage derivatives provided previously. The author also believes that the larger collateral mandates and frequent marking‐to‐market will make the financial system more vulnerable since margin requirements tend to be “pro‐cyclical.” And more rigid collateralization mechanisms can restrict the supply of funding liquidity, and lead to spikes in funding liquidity demand that can reduce the liquidity of traded instruments and generate destabilizing feedback loops. The fragmentation of CCPs across jurisdictions and products will lead to greater demand for CCP‐eligible collateral to maintain the same level of hedging transactions. This demand will likely be met by using riskier assets as collateral and encourage the shadow banking system to create new assets that can be posted as collateral (for example, via collateral transformation services). In sum, although the Dodd‐Frank rules are intended to reduce systemic risk, their expected impact on liquidity makes it a very open question as to whether they will achieve this goal. Although they may reduce some risks, they will simply shift others while possibly creating new ones.     

The fall of high-frequency trading: A survey of competition and profits

We investigate high-frequency trading (HFT) strategies, inventorying the strategies already studied in the literature and introducing innovative strategies detected by private institutional research. To this end, we expand the existing classification, and we offer names for new categories. In a complementary but original manner, we introduce counter reactions from professional traders in response to HFT predatory strategies. These human answers reverse the usual framework of competition between high-frequency traders (HFTs) and low frequency traders (LFTs) and also widen this cadre to HFTs algos (predators) versus execution algos.This survey notes that a continuous increase in competition, between high-speed trading algorithms themselves through predatory strategies and from professional human traders adapting and building adequate responses has made the business more difficult and has led to shrinking profits for HFT. In the end, we believe that excessive competition and a change in the current regulation (favorable to HFT) could kill the goose that laid the golden egg.