Impact Of High-frequency Trading Research Articles

The Flash Crash: The Impact of High-Frequency Trading on the Stability of Financial Market

The growing prevalence of High-Frequency Trading (HFT) in financial markets has sparked intense debate over its impact on market stability. This paper aims to research the adverse effects that come along with HFT's enhancement of liquidity and price discovery efficiency. It contrasts the hardware infrastructure and execution speeds of high-frequency automated trading against manual trading and analyzes how the liquidity bubbles provided by HFT contribute to market volatility. This paper then concludes with three main points. First, HFT can pose a threat to market stability. Second, specific HFT strategies may mislead other market participants and lead to price distortions. Lastly, HFT may exacerbate market participation inequality, posing a market fairness challenge. Based on these findings, this paper recommends that regulatory authorities and policymakers pay closer attention to the potential risks of HFT and implement measures to maintain market stability and fairness.

Impact of High-Frequency Trading with an Order Book Imbalance Strategy on Agent-Based Stock Markets

It is known that there is a positive correlation between order book imbalance and future returns. Although some previous studies using actual trading data have suggested that high-frequency trading (HFT) may take this characteristic into account, HFT firms have not disclosed their specific strategies. Furthermore, there has been a long-standing debate in the empirical research field as to whether HFT is the cause of flash crashes, but no final conclusion has been reached. In the present study, we analysed the impacts of HFT taking into account the correlation between order book imbalance and future returns on a stable market and on a market with a flash crash, using agent-based simulations, which are said to be capable of analysing events in their essence. We also analysed how HFT investment performance differs between those two market conditions. The results showed that HFT has the effect of further stabilizing the market when the market is stable but does not take place during flash crashes and so is unable to affect the market either for the good or the bad. The results also suggest that the proposed HFT’s performance is more sensitive to market price fluctuations than conventional HFT (i.e., HFT following a position market-making strategy) and tends to have high risk and high returns.

The Joint Impact of High Frequency Trading and Market Fragmentation on Liquidity

The Joint Impact of High Frequency Trading and Market Fragmentation on Liquidity

The Impact of High-Frequency Trading in Experimental Markets

The impact of high-frequency trading (HFT) strategies on market quality has been debated in both public forums and academic studies for years. Although some consider HFT to be inherently bad, others view it as providing important liquidity to markets. Thus, the question regarding HFT’s impact on market quality remains open. To address this, we conducted two sets of controlled laboratory experiments, one with and one without an HFT robot trader. We focus on two aspects of HFT trading strategies that have the potential to affect market quality negatively: arbitrage and directional trading. Indeed we designed the HFT robot to have a perfect view of the market before executing a trade to provide it the best chance to influence the market. The introduction of this HFT robot had a significant positive impact on trading volume and bid depth, but it had a negligible impact on other market quality indicators such as efficiency, price volatility, bid-ask spread, and book depth. Thus, we find that in this polar case, HFT is neither a drain on nor a boost to market quality, suggesting that HFT trading, in its worst case, has a benign effect on the market. TOPICS:Futures and forward contracts, derivatives Key Findings • We seek to examine the effect of high-frequency trading on market quality using controlled laboratory experiments. • We find no statistically significant effects for most measures of market quality when we introduce high-frequency trading. The only measures that are affected by high-frequency trading are trading volume and bid depth. • High-frequency traders are effective middlemen and invoke a response from traders in terms of bidding behavior.

The Impact of High-Frequency Trading on Australian Futures Market Liquidity and Efficiency

This article examines the co-location of high-frequency trading (HFT) facilities and capacity of the Australian futures market to absorb information following major scheduled macroeconomic announcements. The findings show that the co-location of HFT facilities has increased trading activities and liquidity across the four futures contracts investigated. The four futures contracts also demonstrate a market capacity to absorb information from major announcements efficiently. For instance, the majority of price adjustments are impounded within 30 seconds following major announcements. The authors conclude that abnormal trading profits are unlikely to be generated by HFT in the Australian futures market. TOPICS:Futures and forward contracts, derivatives Key Findings • The co-location of HFT facilities has increased trading activities and liquidity across the four futures contracts investigated in the Australian futures market. • These futures contracts also demonstrate a market capacity to absorb information from major announcements efficiently. • Abnormal trading profits are unlikely to be generated by HFT in the Australian futures market.

Impact of High Frequency Trading on Equity Market with Reference to NSE India

Impact of High Frequency Trading on Equity Market with Reference to NSE India

J-REIT Market Quality: Impact of High Frequency Trading and the Financial Crisis

Using the introduction of Arrowhead low latency trading platform by Tokyo Stock Exchange as a natural experiment, I analyze the impact of high frequency trading on market quality of J-REITs, in terms of liquidity, volatility, and systemic risks. I also analyze the impact of the 2008 financial crisis. The results document that while the crisis has significantly deteriorated the market quality, the J-REIT markets were resilient. Further, the introduction of Arrowhead improved the J-REIT market quality but has also increased the probability of flash crashes. Finally, using difference-in-differences regression model, I show that since REITs have a higher transparency and better price discovery, they were much less affected by the financial crisis and Arrowhead as compared to non-REIT common stocks.

High frequency traders in a simulated market

Purpose An agent-based market simulation is utilized to examine the impact of high frequency trading (HFT) on various aspects of the stock market. This study aims to provide a baseline understanding of the effect of HFT on markets by using a paradigm of zero-intelligence traders and examining the resulting structural changes. Design/methodology/approach A continuous double auction setting with zero-intelligence traders is used by adapting the model of Gode and Sunder (1993) to include algorithmic high frequency (HF) traders who retrade by marking up their shares by a fixed percentage. The simulation examines the effects of two independent factors, the number of HF traders and their markup percentage, on several dependent variables, principally volume, market efficiency, trader surplus and volatility. Results of the simulations are tested with two-way ANOVA and Tukey’s post hoc tests. Findings In the simulation results, trading volume, efficiency and total surplus vary directly with the number of traders employing HFT. Results also reveal that market volatility increased with the number of HF traders. Research limitations/implications Increases in volume, efficiency and total surplus represent market improvements due to the trading activities of HF traders. However, the increase in volatility is worrisome, and some of the surplus increase appears to come at the expense of long-term-oriented investors. However, the relatively recent development of HFT and dearth of appropriate data make direct calibration of any model difficult. Originality/value The simulation study focuses on the structural impact of HF traders on several aspects of the simulated market, with the effects isolated from other noise and problems with empirical data. A baseline for comparison and suggestions for future research are established.

The Impact of High-Frequency Trading on Volatility. Evidence from the Italian Market

The huge increase of HFT activity in recent years has posed the crucial question of whether it is beneficial for financial markets to both researchers and regulators. Recent academic research has studied the impact of HFT on different measures of market quality, such as liquidity, transaction costs, market integrity and efficiency, though the results are sometimes non conclusive. This study focuses on the impact of HFT on stock price volatility over the period 2011-2013 for a sample of 35 blue chips traded on Borsa Italiana. High frequency traders (HFTrs) are identified according to two methods. The first one, based on public information on the trading strategies of market participants, led us to identify 14 traders (so called ‘pure’ HFT firms). The second one includes the main investment banks active in the European markets, since they carry out some proprietary trading which could take the form of HFT (as stemming from the evidence reported in ESMA, 2014). These approaches allow the identification of a lower and upper bound for the actual share of HFT on total trading volume. Potential endogeneity of HFT is controlled through an instrumental variable approach, using as an instrument the introduction of a new trading platform that eased the HFT activity by decreasing the latency. Results show that an exogenous increase of HFT activity causes a statistically and economically significant increase in volatility. In details, an increase by one standard deviation of HFT activity carried out by ‘pure’ HFT firms raises volatility by an amount between 0.5 and 0.8 standard deviations. This means that, if HFT activity increases by 10 percentage points the annualized intraday volatility increases by an amount between 4 and 6 percentage points depending on the specification used. If we also take into account the activity carried out by investment banks the impact of an increase by 10 percentage points of HFT activity leads to an increase of annualized volatility by an amount between 3 and 5 percentage points. This paper adds to the existing literature by providing new empirical evidence from the Italian market. Furthermore, it contributes to the policy debate, which had recently led the European regulators to introduce new rules aimed at mitigating possible negative effects of HFT.

Asymmetric effect of market liquidity demand shocks on price shocks

Purpose – With the launch of CSI 300 Index Futures trading on April 16, 2010, China's stock market presents a more diversified trend, such as arbitrage, trends strategy entering the market rapidly. Therefore, the liquidity demand also presents a higher frequency, and the change is more complex than the original situation. In recent years, many literatures are engaged in high-frequency trading (HFT) related research, and an important concern is the impact of HFT on market volatility and liquidity. Is it playing the role of stabilizing the market, or bringing more noise and turmoil? Based on this, the purpose of this study is trying to study what kind of impact the HFT have on market liquidity before and after the launch of the CSI 300 Index Futures. Design/methodology/approach – The paper uses the simultaneous equations model of price and net order flow proposed by Deuskar and Johnson and for the first time introduces an asymmetric identification through heteroskedasticity (ITH) method. The paper applies the method to the high-frequency data of CSI 300 Index and the Futures and classifies the buying and selling orders through volume clock. The price risks are decomposed into a component driven by the impact of liquidity demand shocks (flow-driven risks (FDRs)) and a component driven by external information (information-driven risks (IDRs)). Findings – The empirical results show that the flow-driven risk of CSI 300 Index Futures is about 20 percent. In addition, before the introduction of the Index Futures, there is no asymmetric effect between liquidity demand shocks and price shocks existing in either CSI 300 Index or CSI 300 Index Futures. While after the introduction of stock Index Futures, the asymmetric effect in the both two markets emerges. The impact of the buying net order flows on the price is less than the impact of the selling net order flows on CSI 300 Index, whereas the impact of the buying net order flows on the price is larger than the impact of the selling net order flows on CSI 300 Index Futures. The paper further analyzes the relationship between liquidity and FDR and gets the conclusion that the reasons for the deterioration of the liquidity level are caused by the impact of the external information shocks, rather than the liquidity demand shocks. And entries of HFTs like arbitrage traders and hedge traders play a positive role in improving the liquidity level in the market. Originality/value – The paper introduces an asymmetric ITH method for the first time and finds asymmetric effect of the net order flow on the return in both CSI 300 Index market and the corresponding Index Futures market.

High Frequency Trading in the Korean Index Futures Market

AbstractWe investigate the trading behavior of high frequency trading (HFT), the impact of HFT on market quality, its role in the price discovery process, and its profitability, using a very detailed data set of the KOSPI 200 index futures market. We find that high frequency traders (HFTs) do not provide liquidity in the futures market, nor does HFT have any role in enhancing market quality. Indeed, HFT is detrimental to the price discovery process. This finding is contrary to those in the existing literature on HFT in equity markets. We also find that profitable opportunities for HFTs are rare after transaction costs are considered, with the notable exception that foreign HFTs can earn a profit in the index futures market. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 35:31–51, 2015

The Impact of High-Frequency Trading on Stock Market Liquidity Measures

For the highly traded S&P 500 exchange traded fund SPY, we find that, over time, transaction size has been decreasing while the number of consecutive buy or sell transactions has been increasing due to the increased prevalence of high frequency trading and order splitting. Collapsing sequences of buy or sell transactions into single transactions produces a time series that has a time-stationary distribution and is more tractable for empirical market microstructure models. If sequences are not collapsed, measures of illiquidity are underestimated, implying that increased high-frequency trading may not necessarily be associated with improved liquidity.

A Blessing or a Curse? The Impact of High Frequency Trading on Institutional Investors

The rapid growth of high frequency trading (HFT) has aroused considerable public attention and policy interests in its impact on institutional investors. Previous studies show that HFT decreases the average bid-ask spread. However, the major component of institutional trading costs is the price impact, as measured by the execution shortfall. Combining data on institutional trades and HFT trades, I find that HFT increases traditional institutional investors' trading costs. Specifically, one standard deviation increase in the intensity of HFT activities increases institutional execution shortfall costs by a third. I also perform various tests to rule out an alternative explanation that high frequency traders are attracted to stocks that have high trading costs. Further analysis suggests that HFT represents a short-lived and expensive source of liquidity provision when demand and supply among institutional investors are imbalanced, and that the impact on institutional trading costs is most pronounced when high frequency traders engage in directional strategies. Additionally, I find that institutional trading skills can alleviate the adverse impact of HFT.

The Flash Crash: The Impact of High Frequency Trading on an Electronic Market

We study intraday market intermediation in an electronic market before and during a period of large and temporary selling pressure. On May 6, 2010, U.S. financial markets experienced a systemic intraday event, known as the Flash Crash, when a large automated sell program was rapidly executed in the E-mini S&P 500 stock index futures market. Using audit trail transaction-level data for the E-mini on May 6 and the previous three days, we find that the trading pattern of the most active non-designated intraday intermediaries (classified as High Frequency Traders) did not change when prices fell during the Flash Crash.

New Era in Canadian Trading

Over the past year, there has been a great focus on the impact of high frequency trading (HFT) strategies. Numerous papers discussing the merits of HFT have been published, and many opinions have been expressed as to whether HFT is beneficial or harmful. Proponents and opponents of HFT are often equally ardent in supporting completely opposite positions regarding market stability, price improvement, and volatility. This has led to confusion and uncertainty as to what the current situation actually is. This article represents an attempt to present an unbiased view of the current Canadian equity landscape and HFT’s role in it. <b>TOPICS:</b>VAR and use of alternative risk measures of trading risk, volatility measures

The Impact of High-Frequency Trading on Markets

Before rushing to judge high-frequency trading, investors need to understand the empirical evidence.

Where is the Value in High Frequency Trading?

We analyze the impact of high frequency trading in financial markets based on a model with three types of traders: liquidity traders, market makers, and high frequency traders. Our four main findings are: i) The price impact of the liquidity trades is higher in the presence of the high frequency trader and is increasing with the size of the trade. In particular, we show that the high frequency trader reduces (increases) the prices that liquidity traders receive when selling (buying) their equity holdings. ii) Although market makers also lose revenue to the high frequency trader in every trade, they are compensated for these losses by a higher liquidity discount. iii) High frequency trading increases the volatility of prices. iv) The volume of trades doubles as the high frequency trader intermediates all trades between the liquidity traders and market makers. This additional volume is a consequence of trades which are carefully tailored for surplus extraction and are neither driven by fundamentals nor is it noise trading. In equilibrium, high frequency trading and traditional market making coexist as competition drives down the profits for new high frequency traders while the presence of high frequency traders does not drive out traditional market makers.