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How does quantitative trading work?

2024-08-03

Quantitative trading works by using data-based models to determine the probability of a certain outcome happening. Unlike other forms of trading, it relies solely on statistical methods and programming to do this.

You may, for example, spot that volume spikes on Apple stock are quickly followed by significant price moves. So, you build a program that looks for this pattern across Apple’s entire market history.

If it finds that the pattern has resulted in a move upwards 95% of the time in the past, your model will predict a 95% probability that similar patterns will occur in the future.

Quantitative vs algorithmic trading

Algorithmic (algo) traders use automated systems that analyse chart patterns then open and close positions on their behalf. Quant traders use statistical methods to identify, but not necessarily execute, opportunities. While they overlap each other, these are two separate techniques that shouldn’t be confused.

Here are a few important distinctions between the two:

  • Algorithmic systems will always execute on your behalf. Some quant traders use models to identify opportunities, but then open the position manually
  • Quantitative trading uses advanced mathematical methods. Algorithmic tends to rely on more traditional technical analysis
  • Algorithmic trading only uses chart analysis and data from exchanges to find new positions. Quant traders use lots of different datasets

What data might a quant trader look at?

The two most common data points examined by quant traders are price and volume. But any parameter that can be distilled into a numerical value can be incorporated into a strategy. Some traders, for example, might build tools to monitor investor sentiment across social media.

There are lots of publicly available databases that quant traders use to inform and build their statistical models. These alternative datasets are used to identify patterns outside of traditional financial sources, such as fundamentals.