The emergence of the internet gave rise to electronic trading. With the advancement in supercomputers and electronic communication, high-frequency trading has become commonplace in today’s financial markets. But what exactly is a high-frequency trading strategy?
The high-frequency trading strategy is a method of trading that uses powerful computer programs to conduct a large number of trades in fractions of a second. It is a type of algorithmic trading strategy that uses high speeds, high turnover rates, and high order-to-trade ratios to take advantage of small, short-lived profitable opportunities in the markets.
In this post, we take a look at high-frequency trading strategy and explain what it is. We end the article by discussing high-frequency backtesting and if retail traders actually can be successful at HFT trading.
What is a high-frequency trading strategy?
High-frequency trading (HFT) is a method of trading that uses powerful computer programs to conduct a large number of trades in fractions of a second. That is, supercomputers are programmed to use complex algorithms to analyze multiple markets, identify profitable opportunities, and execute trades in fractions of a second.
HFT, therefore, can be considered a type of algorithmic trading strategy characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools.
It uses sophisticated technological tools and computer algorithms to rapidly trade securities. In fact, there is no single definition of HFT; however, its key attributes include highly sophisticated algorithms, the closeness of the server to the exchange’s server (colocation), and very short-term trading durations.
The strategy is mostly employed by institutional traders who have the necessary resources to use high-powered computers to analyze the markets and identify trends in a fraction of a second. The super-fast computers can analyze the markets and spot minute and short-lived profitable opportunities before they become clear to other traders watching the markets.
Is high-frequency trading profitable?
Yes, high-frequency trading is very profitable for the few trading firms with the right equipment. The trading opportunities that HFT strategies target are often short-lived, so speed is of utmost importance. Typically, the traders with the fastest execution speeds are more profitable than traders with slower execution speeds.
Apart from speed, HFT is also characterized by high turnover rates and order-to-trade ratios. Since the profits per trade are usually very small — pennies per share per trade — they magnify their profits by trading huge volumes at a time and making multiple trades (thousands of trades) in a day.
In fact, HFT strategies are structured to make a profit off the smallest changes in prices. By making such trades over and over, which is why they are called “high-frequency trading” anyway, they theoretically generate huge profits, but a fraction of a cent at a time.
High-frequency trading software
High-frequency trading requires complex electronic trading systems and computer algorithms. There are different software available for HFT, but what HFT traders consider is the features of the software. One key feature is the latency time — the time that elapses from the moment a signal is sent to its receipt — which determines the speed of order execution. High-frequency traders go for software with the lowest latency so as to gain a competitive edge in trading.
Other features high-frequency traders look for in HFT software include:
- Ability to trade multiple markets: Access to global equity markets, futures, options, and FX.
- Risk control: Risk assessment of every order request and ensures compliance with pre-configured risk management parameters.
- Brokerage access: Ability to the multiple brokers, exchanges, and electronic communication networks (ECNs).
- Centralized monitoring and control: It should have servers that can be distributed across various geographical locations of the exchange servers, but all strategy performance monitoring and control functions can be performed from a centralized remote location.
- Execution speed: Ability to execute, at least, tens of thousands of orders per second per single FIX connection.
- Low latency: Sub-millisecond for a roundtrip.
- Distributed and scalable: The ability to scale and increase efficiency by having different strategies run concurrently. Can have multiple components deployed across multiple servers at various execution venues.
High-frequency trading strategy example
There are different strategies and methods high-frequency traders employ in their trading, but whatever strategy is programmed into the HFT software. So, let’s say an HFT system that monitors the market for index arbitrage opportunities identifies one that could make a profit of one penny per share and the order flow can take up to a million shares. It quickly makes the trades within a split of a second.
With the 1 million shares making a penny per share, the trade would have made $10,000 in profit. However, the trading fees have not been included.
Types of high-frequency trading strategies
High-frequency traders use different strategy models. Some of their strategies include:
- Market making: This involves placing buy and sell limit orders to earn the bid-ask spread. By setting their sell prices a little above the current marketplace and their buy prices a little below the market price, they can pocket the difference between the prices. Market makers act as counterparties for incoming market orders, providing liquidity to the market. For doing that (providing liquidity), they also get paid a fraction of a cent for every trade by the exchanges. These fractions of a cent can add up to a huge amount of money when you consider that the volume is in millions.
- Event arbitrage: Some economic, political, or natural events generate predictable short-term responses in certain securities, creating arbitrage opportunities that high-frequency traders take advantage of.
- Index arbitrage: This is an opportunity that arises from the fact that index tracker funds have to buy and sell large volumes of securities to rebalance their portfolio weights. HFT firms that are able to access and process such information can take advantage of it by front-running the index tracker funds.
- Statistical arbitrage: This arises from temporary price discrepancies between different exchanges or asset classes. HFT systems can spot them and profit from them.
- Latency arbitrage: This is the idea of reducing the latency in any transaction. With a high-speed HFT system, it is possible to take advantage of millisecond price discrepancies. Many HFT firms are switching from fiber optic to microwave technology for long-distance networking to gain latency.
High-frequency trading firms
There are different kinds of HFT firms, ranging from small firms to big trading firms. These are some of the common names:
- Tradebot Systems Inc.
- Jump Trading
- Five Rings Capital LLC
- Jane Street
- Allston Trading LLC
- Geneva Trading
- Chopper Trading
- DRW Holdings LLC
- Susquehanna International Group LLP (SIG)
- Virtu Financial
- Hudson River Trading (HRT)
Is high-frequency trading for small and retail traders?
Not really, high-frequency trading is capital-intensive and requires some technical skills, both of which a small retail trader may not have.
To employ HFT strategies, one needs huge capital and the right software. Even after getting the software, one needs VPS services that can host the system right next to the exchange’s servers to reduce latency and increase the chances of success.
High-Frequency Trading Strategy backtest – does it work?
From our point of view, we believe retail traders stand no chance of making any money by employing high-frequency trading strategies. It requires resources, knowledge, and capital that are best left to institutional investors and traders. HFT requires perfection in everything you do – from backtesting, quotes, and systems. And if you are not the best, you’ll lose out to better players. Thus, this is not worth your time and effort.
Backtesting high-frequency strategies with strict trading rules and settings is difficult. Not only is it difficult to backtest, but you would also be less likely to replicate the results in live trading. Thus, we soo no point in spending a lot of time on such a backtest.
Let’s look at some of the issues with backtesting HFT:
- Latency: retail traders are far from any exchange and you can be sure better-equipped players will front-run you.
- Slippage: The more trades you make, the more you’ll pay for the bid and ask prices. This is much more of an issue compared to swing trading (for example). What is slippage in live trading?
- Disconnection: If you are a swing trader that trades at the open and close (like we mostly do), then disconnection is hardly a problem. But if you are doing HFT it might be an issue. Mind you, this is more of an issue than most people believe. When we were day trading and trading hundreds of trades daily, we often experienced problems with our broker. Some days we were trading blind – and this is rarely a method you make money on.
- Quotes: you need excellent quotes to backtest HFT. Furthermore, you most likely need bid and ask prices to measure slippage.
Please also remember that short-term trading is a zero-sum game.
Is scalping the same as high frequency trading?
No, it’s not the same but both trading techniques are equally difficult. The short time horizon makes most traders chasing ghosts and thus they eventually fail.
This is what we wrote earlier in an article about scalping trading:
We don’t recommend scalping when trading. Scalping is hard and almost all scalpers end up losing. Scalping is a waste of time because it involves competing with better-equipped traders and institutions and you need to deal with lots of randomness and noise in the market. Most likely you end up losing money – scalping strategies are rarely profitable. There are better opportunities in longer time frames. Additionally, backtesting is more difficult the shorter the time frame. Scalping is difficult!
List of trading strategies
We have written over 800 articles on this blog since we started in 2012. Many articles contain specific trading rules that can be backtested for profitability and performance metrics.
The trading rules are compiled into a package where you can purchase all of them (recommended) or just a few of your choice. We have hundreds of trading ideas in the compilation.
The strategies also come with logic in plain English (plain English is for Python traders).
For a list of the strategies we have made please click on the green banner:
These strategies must not be misunderstood for the premium strategies that we charge a fee for:
High-Frequency Trading Strategy (Backtest) – conclusion
A lot of retail traders are attracted to high-frequency trading strategies. We suspect it’s the fast action that is the main driver. Unfortunately, you are almost guaranteed to lose money if you try a high-frequency trading strategy. To succeed you need to be the best because the few winners take home most of the gains. So, save yourself a lot of hassle and money and forget about HFT trading.
How does high-frequency trading work?
High-frequency trading involves supercomputers programmed with sophisticated algorithms to analyze multiple markets, identify profitable opportunities, and execute trades within milliseconds. It leverages high-frequency financial data and electronic trading tools for rapid and high-frequency trading.
Is high-frequency trading profitable?
Yes, high-frequency trading can be highly profitable for trading firms with the right equipment. Traders with the fastest execution speeds are more likely to be profitable, as they capitalize on short-lived opportunities, making small profits per trade but executing a large volume of trades.
What types of strategies do high-frequency traders use?
High-frequency traders employ various strategies, including market making, event arbitrage, index arbitrage, statistical arbitrage, and latency arbitrage. These strategies involve exploiting short-term price discrepancies, market inefficiencies, and arbitrage opportunities.