High-Frequency Trading: Benefits vs Disadvantages

Third, the technologies that are in use in China’s futures markets are still below the technology required by most HFT traders, who usually have high requirements for streaming data on equities and derivatives prices, and demand millisecond updates. We focus on the attention constraints of financial market participants as a possible channel because extant research shows that limited attention affects how financial information is reflected in stock prices following earnings announcements. DellaVigna and Pollet (2009) document inefficient price responses to earnings surprises on Fridays, when investors are distracted by the upcoming weekend. The common motivation for the limited attention literature is that human decision-makers’ attention is a limited resource. But with the ascendancy of algorithmic trading, the direct participation of human decision-makers in trading has been diminishing. Order submissions and executions now https://www.xcritical.com/ occur in sub-second increments as ultra-fast computers operate in time scales that humans cannot even register, let alone react to.

Market efficiency in real time: evidence from low latency activity around earnings announcements

Market makers provide liquidity and tighten spreads, especially in thinly traded securities. For active stocks, competition is fierce, and ultra-low latency is critical. HFT market-making focuses on the most liquid securities like large-cap stocks and ETFs. Algorithms input countless data points to forecast expected trading activity and optimize quoting strategies. Historical trade data trains the models to adapt quoting to changing conditions. Colocation, purpose of high frequency trading microwave networks, and specialized hardware like GPUs reduce latency.

purpose of high frequency trading

HFT software development stages

purpose of high frequency trading

Internationally, regulators have taken diverse approaches to regulating HFT. In the United States, the Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC) first focused on equity market microstructure issues like colocation and order types. Relatedly, the market impact from high HFT volumes exacerbates volatility spikes. Since HFT systems react similarly to price movements, their collective reaction reinforces the original move even further. This self-perpetuating feedback loop leads to outsized swings as machines rapidly amplify each other’s behaviors.

The Role of High-Frequency and Algorithmic Trading

In this paper, we explore how the market-making role of HFT has changed over time and the role of regulation in shaping them. There can be a significant overlap between a “market maker” and “HFT firm”. HFT firms characterize their business as “Market making” – a set of high-frequency trading strategies that involve placing a limit order to sell (or offer) or a buy limit order (or bid) in order to earn the bid-ask spread. By doing so, market makers provide a counterpart to incoming market orders.

purpose of high frequency trading

High-Frequency Trading (HFT): Definition, Origin, Strategies, Return, Regulations

At the same time, HFT helps to keep markets in line by exploiting small price differences and bringing disconnected assets back into equilibrium. High-frequency trading is highly debated and charges have been levelled against many HFT firms for illegal activities. The argument for HFT is that, in most cases, it provides substantial trading volume and liquidity to the market. This means that retail traders are more likely to have someone to buy from or sell to when needed. HFT strategies require complex statistical algorithms coded by top programmers. Recruiting and retaining quantitative experts and developers drives up compensation costs.

What are some controversies about HFT?

  • Well known names in the HFT space would include Getco, Infinium and Optiver.
  • While executing trades at high speeds and frequencies, they help reveal important information about market conditions and price movements.
  • It must be designed to be intuitive and user-friendly, allowing traders to quickly access key information such as real-time market data, order status, and trading history.
  • The time has come to re-think and examine the impact of HFT from a broader perspective.
  • Following this regulation, even though HFTs participated in a larger proportion of trades, their role was primarily that of liquidity takers rather than market makers.

The fastest connections using microwave/laser technology between key hubs like Mumbai and Delhi reportedly cost over Rs 140 crore per link. Low latency trading aims to exploit short-term pricing inefficiencies and arbitrage opportunities by executing at the fastest possible speeds. Even small improvements in system speeds allow HFT firms to act before competitors in a market where milliseconds matter. Strategies take advantage of brief pricing discrepancies between assets and exchanges by trading large volumes to maximize cumulative profits.

Speed of Market Access and Market Quality: Evidence from the SEC Naked Access Ban

Firms made massive investments in technology like co-located servers and fiber optic networks to shave milliseconds off latency. The earliest high-frequency trading firms included Getco LLC, founded in 1999, and Tradebot Systems, founded in 1999. These firms used strategies like market making and arbitrage to profit off tiny price discrepancies in stocks. Early HFT focused heavily on the NASDAQ stock exchange, which was one of the first exchanges to go fully electronic in 1983. This allowed algorithmic trading firms to send orders directly to the exchange via computer systems and receive confirmations of trades executed in milliseconds. HFT has become very prevalent in the stock market over the last couple of decades.

purpose of high frequency trading

Get the best trading software development services

Moreover, in some cases, certain phrases end up being used interchangeably and adding to the disorientation. To help you better understand this area of finance, we’re going to discuss each trading method in more detail. Algorithmic, high-frequency, algo-, or automated trading are terms that often show up in trading-related articles. This happens because both — the technological and financial landscapes have many nuances, and slight differences in operations create new terms.

What are the Benefits and Limitations of High-Frequency Trading?

Certain estimates say HFT accounts for over half of all trades in US equity markets. However, critics say it gives firms with the fastest systems an unfair advantage and increases volatility. Regulators continue to debate if additional oversight or regulations are needed.

Cvitanic and Kirilenko (2010) demonstrate that HFTs provide less liquidity during a crisis. A growing literature finds that HFTs as endogenous liquidity providers withdraw liquidity from the market at the time of crisis (Raman et al., 2014, Cespa and Vives, 2013, Korajczyk and Murphy, 2019). To avoid being picked off by more informed investors, HFTs issue competitive prices for a limited time. Frequent order cancellations by HFTs also raise concerns regarding the nature of liquidity that HFTs provide, with researchers claiming the liquidity as ‘ghost’ (Virgilio, 2019) or ‘phantom’ in nature. In this study in mid-2015, we did not find sufficient evidence to suggest that HFT practices have created dramatic new and strong forces to transform the regional markets of the Asia Pacific region. In fact, we found that there has been a mixed response to the implementation of HFT among financial markets here.

More fully automated markets such as NASDAQ, Direct Edge, and BATS, in the US, gained market share from less automated markets such as the NYSE. Economies of scale in electronic trading contributed to lowering commissions and trade processing fees, and contributed to international mergers and consolidation of financial exchanges. Company news in electronic text format is available from many sources including commercial providers like Bloomberg, public news websites, and Twitter feeds.

Since they trade so frequently, all traders have likely transacted with a HFT firm at some point. Costs also accrue from running complex HFT infrastructure virtually non-stop. Keeping data centers staffed and maintained around the clock, servers powered on perpetually, and connectivity robust enough to avoid any downtime or latency costs millions. Though often criticized for an unfair advantage, profitable HFT firms do pay significant taxes that fund government services. Estimates suggest nearly ₹7,000 crore in annual state and local tax revenues from HFT in India. To mitigate losses during unpredictable swings, HFT systems incorporate tight risk controls.

Thus, making algorithmic trading widely applicable to trading with high market volumes such as mutual funds, investment banks, hedge funds, etc. Opinions vary about whether high-frequency trading benefits or harms market performance. Either way, wise traders don’t try to time market trends; for the typical investor, a long-term buy-and-hold strategy will invariably outperform technology built for the short term. High-frequency trading (HFT) takes advantage of proprietary computer algorithms and super-fast (and often proprietary) connections to analyze securities, identify opportunities, and execute trades for extremely short-term gains. High-frequency trading (HFT) uses algorithms and extremely fast connections to make rapid trades, often in fractions of a second. It frequently involves the use of proprietary tools and computer programs that analyze markets, identify trends, and execute trades for very short-term gains.

As soon as an asset meets a pre-determined price set by the algorithm, the trade occurs, satisfying both buyer and seller. So while there is always room improvement, let’s not fail to appreciate – like the mother in Churchill’s story – why our equity markets are the envy of the world by focusing on the equivalent of the boy’s cap. Specifically, keeping the price of IBM artificially low to facilitate the large buy order would, by definition, disadvantage every seller of IBM at that time. Those disadvantaged sellers could include an institution (trading for individuals) or individual investors directly. In essence, some market participants that enter large orders want other market participants to subsidize their trading.

They are slightly different terms but have similarities and tend to go together. The investment of time and money in development and supporting the direct market access (DMA) APIs is significant. One famous incident often linked to HFT is the May 6, 2010, “Flash Crash” in the U.S. stock market. During this event, the Dow Jones Industrial Average plunged about 1000 points (around 9%) and recovered those losses within minutes.

Subsequently, this piece has been shown to hold material flaws and holds little credibility today. Some papers were commissioned by exchanges who gain commercially from HFT business (e.g. Gomber/Deutsche Boerse). Not only was credibility compromised, but more importantly, in many cases, so was the methodology. As time progressed more universities and researchers, un-conflicted by association, were able to conduct research into the area and the position began to shift. One issue is whether a two tiered market exists between firms with higher and lower technological resources. There are also questions about whether market manipulation and market abuse have occurred.

An EA is a program in the platform that executes coded strategies for algorithmic trading. Traders write code in the MetaQuotes language, known as MQL4, which is then executed on the MT4 platform. One major controversy is around the fairness of HFT and whether it gives high-frequency traders an unfair advantage over other market participants. The speed advantage enables HFT firms to detect trading patterns and place orders microseconds before others.