What is Systematic Trading?
Investors investing in a hedge fund seek to achieve absolute positive returns in all market conditions, i.e. they aim to be hedged from turbulent market volatility to reduce risk in their portfolio as compared to investments in other instruments.
Hedge fund managers follow a plethora of techniques to safeguard their investors from losing money. One such technique is systematic trading, which employs quantitative data and utilizes a mathematical, computer oriented approach to trade the markets, thereby eliminating the emotional interference of manual trading.
In this article, we walk you through the basics of systematic trading.
Definition of systematic trading
Systematic trading is a technique employed by some hedge funds to ensure a risk-disciplined and unbiased approach to trade the markets. In systematic trading, traders use a quantitative algorithm to trade in any asset class, such as forex, commodity, indices and others. They utilize market signals, such as price volatility and changes in trade volume, to detect market trends early and profit from them.
Despite its name, systematic trading is not necessarily entirely automated. Some use partial automation and utilize the services of the machine to tap trends early, and curate strategies that can reap the most out of such price movement.
Variations of systematic trading
Depending on the type the fund manager prefers, systematic trading can be completely automated or partially manual. Here are two flavors that you may come across.
Also referred to as algo trading, automated trading, or black-box trading, algorithmic trading refers to a computerised trade process. In this process, the user feeds specific instructions into the software (pertaining to time, price, quantity, or any other programmable attribute) and allows it to perform transactions on its own.
The transactions depend on the software speed, i.e. the machine is capable of performing vast volumes of rapid transactions as well as vast amounts of calculations to determine optimal take profit and stop loss positions, thereby generating profits from such an exercise.
Here, trades are placed automatically at the best prices, and the software is capable of following the schedule fixed by the hedge fund manager.
For systematic traders, it allows them more flexibility by feeding in the requisite rules and letting the program run its course. One use case for algorithmic trading for example, is for enhancing trading conditions; when fund managers want to buy a large amount of shares discreetly without affecting the price.
Manual overriding (partial or complete)
Several hedge fund managers believe that automation, in conjunction with their trading experience, can provide optimal results for investors. Instead of full automation, they prefer having some control over trade decisions, such as avoiding entering trades during illiquid market conditions due to major events that may be hard, if not impossible, to model into the algorithm.
If executed well, this method can help the fund generate higher quality risk-adjusted returns and minimize market risk. However, with manual intervention, there is always the risk of fund managers making an error in judgement.
Types of systematic trading strategies
Here are some of the common ideas that systematic hedge managers follow:
Cash futures arbitrage
Futures pricing refers to the current anticipated price of an asset in the future. More often than not, it is different from the spot price. It allows the trader to gain an arbitrage opportunity. If the futures is at a premium, he can short the futures and go long for the same number of stocks. In a general day-to-day scenario, the difference is negligible for a manual user to benefit from it. But with machines employed, a hedge manager can often make sizable profits from the automated process.
Pair trading, also known as statistical arbitrage trading, involves a parallel long and short position in two highly correlated items. The emphasis is on high correlation, and the fund manager tries to benefit from the arbitrage in them.
In case of an underperforming asset, it is expected that the price will adhere to the correlation and hence, converge soon. Systematic trading assists in screening all the correlated instruments and allows the trader to know which instruments are likely to regain its actual value and executes the requisite trade to benefit from the movement.
Sentiment Analysis trading
Every time a piece of news surrounding a company surfaces, it inadvertently leads to a movement in the stock price of the company. In Sentiment Analysis trading, the software analyses the underlying sentiment, or emotion, attached to news and anticipates if the trajectory would be upward or downward, and makes the requisite moves.
As the name suggests, momentum trading relies on trading the momentum of the underlying asset. Here, the systematic trader goes long when the price movement is on an uptrend, and vice versa enters a short position when it is on a downtrend.
The algorithm will then exit once it detects that the trend is ending with the momentum fading, or bows out once it hits the targeted take profit or stop loss levels. In this strategy, the trader curates algorithms that decide the appropriate time to enter the market.
It also contains indicators to exit the market, along with the holding period that the fund manager finds apt. It eradicates the risk of getting in or out too early, or missing the trend movements altogether.
Benefits of systematic trading
Here’s why systematic trading has been increasing in popularity in recent years.
Disciplined, logical trading
Manual trading is prone to emotion-based decisions which may lead to a trader incurring huge losses. With the help of systematic trading strategies, fund managers adopt a highly logical approach to trading, eradicating any human emotions that will affect trade execution and cloud judgement. This enforces discipline in trading and ensures that every trade is executed in strict accordance to a trading strategy.
Ability to backtest your strategies
Systematic trading strategies follow a sequential rule system allowing fund managers to back-test its effectiveness. Backtesting refers to the ability to test strategies based on historical data. It informs the fund manager about the results had it been executed in the past.
While backtesting is not a foolproof idea as actual trading conditions tend to vary wildly from ideal execution conditions, it gives the manager an idea of how the strategy may fare in a given scenario. The speed in which backtesting can be done can allow for quick iteration of trial strategies, allowing rapid improvements to the original strategy and elimination of those which don’t seem feasible.
Using automation to benefit from profitable situations
Human beings react slower than machines when it comes to trend identification and trade execution, hence this leads to manual traders losing out on short interval movements. With systematic trading, the machine is allowed to make automated trades enabling it to execute buy-and-sell orders on its own, thereby allowing more trading opportunities.
Issues involved in systematic trading
Changing market conditions
Markets change all the time. A trading system that might have been profitable in the past may not always remain so. This decay in trading systems means that there is a need for algorithm traders to constantly monitor and maintain the systems, either by adjusting the parameters or displacing existing trading systems that are better suited for the new market environment.
High costs involved
For hedge funds employing systematic trading in their strategies, it is essential to ensure optimal trading execution conditions to generate quality alpha. Besides the cost of acquiring the right talent to come up with new strategies and maintain them, there are high costs incurred in ensuring the underlying infrastructure of the algorithm strategies are hosted close to the trading counterparties to ensure minimal slippages.
It is mostly applicable in cases where a trader manually overrides the system. While there may be situations where this is necessary to avoid risks from major events, the override may also happen when a trader’s emotions result in an erroneous decision that goes against the trading strategy of the system, resulting in losses.
Systematic trading is more than just finding an algorithm that works. There is a constant need for monitoring of both the markets as well as the trading systems, and requires a thorough understanding of the infrastructure, and also good relationships with the trading counterparties to ensure scalability and optimal results.
Salzworth Global Currency Fund utilized algorithms to trade price action opportunities in the forex spot market systematically and profitably. Irrespective of the prevailing market conditions, it aims to provide an absolute return to its investors every year.
It follows an in-house algorithm to eradicate human vulnerabilities, ensures discipline in its risk management methodology, and follows a systematic approach to achieve the desired outcome.
Salzworth Global Currency Fund
Raphael leads the expansion of Salzworth’s corporate and institutional partnerships. Prior to joining Salzworth, he was leading the partnership efforts for a FX prop desk and FX brokerage. Raphael started his career at Credit Suisse, before moving to StashAway, a robo-advisor wealth platform, building up a diverse range of skill-sets from managing infrastructure systems to auditing investment algorithms. Armed with a Master of Computing, Raphael seeks to present a robust set of algorithm trading offerings for Salzworth Global Currency Fund and relevant connections to benefit clients and partners of Salzworth.