Systematic trading is an automated trading system normally used by Hedge funds.  It includes the use of technical analysis to identify market trends such as price and volume data. This kind of trading is used to define trade goals, achieve risk control measures as well as data cleaning, minimizing human error.

One of the main benefits of systematic trading is that it excludes human emotions in the decision-making process, minimizing risk. As well as operating at a faster speed spotting more profitable opportunities including those occurring in short time intervals.

The automated system allows faster execution on trading orders.

Additionally, the opposite of systematic trading is called discretionary trading, and here the trader can make decisions based on current market conditions but in systematic trading, it's rule-based trading, where trades are identified regardless of market conditions.

The difference is, discretionary trading is more suitable for traders who prefer to be in control of every trading decision. While systematic trading is more compatible for traders who want speed and accuracy in execution.

Below are some common types of trading strategies implemented by systematic trading;

Pair trading

Pairs trading is based on a correlation of two or more stocks or other financial instruments typically by matching a long position with a short position of two stocks with a high historical correlation. In other words, Pairs trading seeks 2 securities with similar characteristics and that have a price relationship visible in their historical trading range.

Pair traders use statistics, technical and fundamental analysis to measure the direction of the 2 underlying securities that allow a successful execution.

A pairs trade must have a positive correlation in order to be a profitable strategy. Pair traders usually take long positions in an underperforming security and sell short in an outperforming security. Nevertheless, it remains difficult to identify a positive correlation of 0.80.

Momentum trading

Momentum trading is when traders use price trends to buy or sell an asset. They sell when the security loses momentum and buy-in short-term uptrends.

Momentum traders use the strength of price movement to open a position thinking that the underlying security will continue to move in that specific direction because there’s enough force behind it. They would then close their position once the underlying security’s price starts to edge lower.

Looking at the volume, volatility, and timeframe, a trader can identify the ideal entry for taking this kind of position.

Cash futures Arbitrage

Cash futures arbitrage strategy is taking advantage between the spot price and the future price of a stock. This means traders can combine the purchase of a long position in an asset and the sale of a short position in a futures contract on the same underlying asset. In short it is benefiting from selling futures at a premium price while buying an equivalent quantity of the same asset at a lesser price.

News-based automated trading

This kind of trading involves assessing the market sentiment through the news, to estimate stock price movements, usually, news reports can spur strong short-term moves in the market, so traders can take this as an opportunity.

There are different kinds of news that can be market movers, Periodic news, that’s often recurring such as central bank announcements or monetary changes. Periodic news also includes economic data such as job reports or earnings, these indicators can cause volatility in the markets making them an important key factor in trading.  There’s also an unexpected kind of news such as political turmoil or abrupt market conditions that can cause surprising volatility in the markets.

News based traders can take advantage of price actions by keeping track of news releases. News traders can identify a relationship between certain news announcements and their price action through looking at historical data or price trends.

Hidden Markov model

The Markov model is used to forecast the value of a variable not through its historical performance but through its current position. Automated trading can simplify the predictability of a stock to create more market opportunities.

It is mostly used as a statistical signal to predict stock prices.