High-Frequency Trading (HFT)
A new-age trading method that uses advanced algorithms to automatically analyze multiple markets and execute orders based on market conditions.
High-frequency trading is a new-age trading method thatto automatically analyze multiple markets and execute orders based on market conditions.
Speed of order execution is critical in high-frequency trading. Large investment banks and hedge funds employ this trading method.
The speed at which either buy or sell orders are executed in high-frequency trading is difficult to comprehend. High-frequency traders can conduct trades in approximately one 62 millionths of a second.
This high speed is achieved by transmitting data over fiber optic cable, microwave frequency broadcast, or via co-location at exchange server sites.
Distance or the length of the physical lines (usually fiber-optic) transport data are the most significant determinants of latency.
Financial institutions have invested billions of dollars in building infrastructure to reduce latency in the data feed.
The turnover ratio measures how frequently an asset or other portfolio's holdings are replaced in a given period. Turnover ratios can differ based on the type of fund, its investment objective, and the's investing style.
Funds often pay spreads and commissions with high turnover, which increases their costs when buying and selling stocks; high margins from successful high-frequency trades can easily cover these increased costs.
Funds managed by high-frequency traders have high turnover ratios. For example, a fund managed by these firms has stock or assets changed in a matter of seconds.
High order-to-trade ratios
Order-to-trade ratios (OTRs) describe the relationship between orders/quotes entered into, modified, and deleted and transactions executed. High-order trade ratios are an essential feature of this type of trading.
High-frequency and large-volume securities trading enable traders to profit from even little price swings. In addition, it allows institutions to profit handsomely from bid-ask spreads.
Trading algorithms can analyze markets and exchanges. It allows traders to uncover new trading opportunities, such as arbitraging minor price variations between the sale of the same asset.
Many enthusiasts of high-frequency trading believe that it improves. Because deals are done faster and the amount of trades increases, this new-age trading certainly promotes market competition.
the need for paid human traders, lowering the cost of trading. In addition, because it is based on many orders, it aids in price discovery and formation.
High-frequency traders rarely retain their portfolios overnight, only invest a small amount of money, and only hold their positions for a short period before liquidating them.
As a result, theratio, or risk-reward ratio, is relatively high. The ratio is significantly higher than that of a traditional long-term investor.
A high-frequency trader may only make a fraction of a penny profit, which is all they need to make gains throughout the day but also increases the risk of a considerable loss.
One of the most common criticisms of high-frequency trading is that it just creates "ghost liquidity" in the market.
Jobs at High-Frequency Trading Firms
The high-frequency trader life is exciting and rewarding. These firms attract talent from all fields, including quantitative analysts (quants) in developed countries.and engineering. A Ph.D. in computer science or math is a requirement for
For developing economies, a CS, math, or engineering degree or anfrom a college of repute will suffice to be a quant.
Roles in the HFT industry
Quant Analyst / Model Developer - A strong programming knowledge is a must. One must familiarize oneself with quant tools such as R, Matlab, and Python with an edge in probability and statistics.
You would be expected to code or modify existing strategies as a Strategy Developer. It will be your responsibility to code the strategy into the execution platform with the help of a quant.
Traders must be quick problem solvers and good at handling problems. High-frequency traders should be familiar withreading. As an HF trader, your job is very competitive in that you must constantly improve your method. Even when it's lucrative, it can also be disheartening.
Networks/System Administrators are required to maintain the system that receives terabytes of data in a fraction of a second. A network administrator is required to deal with latency systems with extreme precision.
Furthermore, high-frequency tradersto trade many times daily, earning small amounts for each trade. They make an average of $4.11 on each contract they trade. This equates to $66,039 per day on average in the July 2020 E-mini S&P 500 contract alone.
Due to the meritocratic approach of HFT firms, projects are often given a significant amount of autonomy.
Quant roles often involve extended hours, such as 80-90 hours per week. However, for HF traders, the fast-paced growth, intellectual stimulation, and compensation outweigh the negative effects of the workload.
High-frequency trading strategies
index arbitrage, volatility arbitrage, statistical arbitrage, and . In addition to long/short equity, passive market making is frequently used.
The index arbitrage strategy exploits price differences between two or more market indices to generate profits. There are many ways to do this depending on where the discrepancy arises.
Arbitrage may involve the same index traded on two different exchanges, or it may include indexes whose typical relative values temporarily diverge from their standard.
Index arbitrage is the basis of program trading, where computers monitor millisecond changes between various stocks and execute buy or sell orders automatically to exploit discrepancies that shouldn't exist. Because the chances are often brief and razor-thin, large financial institutions prefer to adopt a high-speed,procedure.
The difference between the predicted future price volatility of an asset, such as a stock, and the implied volatility of options based on that asset is what volatility arbitrage is all about.
Consider a trader who believes abecause the implied volatility is too low. In that situation, they could profit from the prognosis by buying a and in the underlying stock. The option price will rise if the stock price does not move and the trader is correct about implied volatility growing.
is an investment bank strategy that includes buying and selling the stock of two merging companies simultaneously at the same time to generate "riskless" gains. Because the deal's completion is unclear, the target company's shares often sell for a discounted cost than the acquisition price.
Merger arbitrageurs are concerned with the likelihood of the deal being authorized and the length of time it will take to complete. Merger arbitrage entails considerable risk because there's a chance the trade won't be authorized.
Long-short equity is anto establish businesses while selling short shares .
Hedge funds frequently deploy long-short equity with a prolonged bias-for example, a 100/20 strategy, with prolonged exposure accounting for 100% ofand short exposure accounting for 20%.
The "pair trade," which involves balancing acompany with a short position on another stock in a similar sector, is a common variation of the long-short concept.
Black box trading system
The components of the black box trading system can help lead you to targeted profits. Even while you are not using the platform, such a system works autonomously throughout the trading day and can smoothly execute your many trades.
The system will recognize new trades and open and close positions after it has been programmed. On the other hand, some methods can connect traders to the brokerage platform without interfering with your day-to-.
What is the most beneficial aspect of employing a black box trading system? First, you do not necessarily need to understand the technical aspects of trading.
Traders and investors can create automated trading using AI systems that allow computers to execute and monitor deals based on exact entry, exit, and money management rules.
One of the most appealing aspects of strategy automation is that it can remove some of the emotion from trading by automatically placing transactions when certain conditions are satisfied.
Advantages of AI trading
1. Reduce emotions during trading.
Emotional considerations such as the fear of losing money or the desire to squeeze a little more profit out of a deal cause discipline to be lost. Because the trading plan will be followed precisely, automated trading helps retain discipline.
2. Backtesting is possible.
Backtesting is a way of determining how well a strategy or model would have performed in the past. It acts as a method of assessing the viability of a trading strategy by examining how it would perform in the real world using existing data.
3. Multiple accounts are easy to manage.
Multi-account management is tedious and may result in missed opportunities. With the use of artificial intelligence, this can be avoided. If programmed effectively, AI can make the proper trades without human intervention.
Popular High-Frequency Trading firms
The forerunners were founded in the 1990s. 16 of the 22 early high-frequency trading firms are still active.
Knight Capital was one of the early HF firms that went bust, notably losing $460 million due to a faulty trading algorithm. This highlights the risks involved in this kind of trading.
Start-ups in this sector had a tough time in the next decade. Among the 21 start-ups founded between 2000 and 2010, only 13 remain today.
All of the firms that followed after veterans were founded in 2010. They are all still operating because of the experiences their founders gained from their former companies during the growth and lean years.
The algorithmic trading business has benefited immensely from the surge in volatility and volumes in 2020. Firms have reported record quarters across the board, and the industry has generally avoided scandals and public attention.
Chopper Trading - is a private trading enterprise focused on technology. Chopper Trading was founded in 2002 by Raj Fernando as a tiny fixed-income trading firm with no clients or shareholders; they trade the firm's capital for the firm's gain.
Virtu - FinancialVirtu, founded in 2008 by Vincent Viola and Doug Cifu, is one of the world's largest high-frequency market makers, with a strong focus on US markets. Virtu has acquired several high-profile reputable trading firms and service providers, including KCG Holdings and ITG.
These are a few of the most famous high-frequency trading firms.
Ethical dilemma and scrutiny
HFT is like any other technological advancement; there are two sides to the coin. These traders ostensibly do not intend to deceive. Instead, this advanced trading aims to provide a competitive edge to its users.
These methods may impact small investors, large trading firms, brokers, and other market participants. Is this trading beneficial to the majority? Well, that depends on the perspective. We will examine a few adverse effects of algorithmic trading on the market.
If traders participate in market manipulation, algorithmic trading can give them an unfair edge. In addition, trading orders can manipulate the market to a trader's benefit. Trillium Capital is a notorious firm engaged in market manipulations.
Trillium Capital is a New York-based firm that specializes in high-frequency trading. Trillium entered several deals ultimately deemed malicious because the company had no intention of carrying out the orders.
The orders were placed so the market would believe there was a lot of movement in specific securities.
Small Investors are being victimized.
Another criticism is that it is unjust to small investors. Because they lack the resources to do so, small investors do not compete on an equal footing.
One could argue that lacking resources such as high-capacity computers and informational imbalances produce unfairness.
The Cascading Effect
The best example of the cascading impact occurred on May 6, 2010, with the "flash crash." In this case, a succession of worldwide events caused investors to be concerned about equities markets. This uneasiness played a role in the steep drop that day.
The Greek fiscal issue initially caused a market drop early in the afternoon. By executing short trades, other traders' bets on the market caused it to continue to fall.
AI traders that can track this type of activity were activated by the wave of movement, resulting in a subsequent sell-off. The enormous amount of orders overburdened the exchange systems.
The difficulty authorities have in identifying the line between lawful and illegal conduct in these ultra-speed trades was demonstrated by a 2014 Securities and Exchange Commission (SEC) settlement against Athena Capital Research.
According to the's ruling, Athena's algorithmic techniques grew more predatory, making sure the company traded attractive stock imbalances after the conclusion of each trading day.
Athena agreed to pay the $1 million fine and refrain from committing or causing further violations of the securities laws without admitting or disputing the findings.
In recent years, high-frequency trading has come under fire for increasing market susceptibility to illegal activity. The United States Court of Appeals for the Seventh Circuit upheld the ruling in 2017 against high-frequency traders for spoofing.
Academics and legislators disagree on whether it should be regulated more stringently than other types of trading and, if so, what those restrictions should be. Still, criminal law has rarely been used to restrict high-frequency trading.