Quantitative Trading is an approach that relies on mathematical and statistical data to find trading opportunities.
The term “Quantitative Trading” gets its name from quantitative analysis. In financial markets, the quantitative analysis provides traders with tools to turn complicated patterns into numerical values used to analyze market movements.
Traders who depend on quantitative analysis are known as quant or quant jockeys.
Harry Markowitz was the one that applied mathematical models in financial markets. He mentioned it in his doctoral thesis, which was published in the Journal of Finance.
What is Quantitative Trading?
Price and volume are two common data points for Quantitative Trading. These points help quantitative traders to make trading decisions based on mathematical databases.
The main concept of Quantitative Trading is to create a trading model using mathematical calculations and then develop a computer program to apply the model on historical market data. This model is back-tested, and if it generates favorable outcomes, the tester may want to try and apply it to real market data.
For example, a trader finds out that the price of a particular currency pair moves upward during the New York trading session. He/she will build a program that looks for this scenario on a currency pair’s entire historical data during the New York session. If the program found that a currency pair rose 80% of the time throughout the New York session, then a trader’s model will anticipate there is an 80% probability of currency pair rising during the New York session.
This is just a simple example of how Quantitative Trading works. Typically, quantitative traders choose a group of assets to find complex historical data and apply them in real markets.
Quantitative Trading is sometimes confused with algorithmic trading. Algorithmic trading involves using automated systems to identify trading opportunities and perform trade on the trader’s behalf. Quantitative Trading uses mathematical models to calculate an asset’s historical data. However, it doesn’t execute trading on the trader’s behalf.
Quantitative Trading is often linked with HFT (high-frequency trading). HFT is a trading technique that uses computer programs to perform a large number of trades over a short period.
Originally, Quantitative Trading was done by large financial institutions due to the complexity of statistical data. However, with technological advancement, some individual traders have joined Quantitative Trading.
Quantitative Trading strategy
1. Momentum trading
Momentum trading a.k.a. trend-following is a simple approach that involves riding the trend till it lasts. Traders use quantitative analysis to predict the overall momentum of the market.
Suppose a trader wants to find the market sentiment for GBP/USD and wants to pick winning trades during an uptrend. He/she would build a model that would only focus on the winners during an uptrend. In this way, he/she can try to anticipate the market sentiment.
2. Algorithmic pattern
As mentioned earlier, algorithm trading uses an automated system to find trading opportunities. But, this strategy doesn’t involve the use of an Algo. Instead, it involves building a model to determine when large institutions are going to trade, so, traders can trade against them.
Consider a trader who built a model that predicted that XYZ firm would buy thousands of units of a currency pair. He/she could buy that currency pair before time and later sell it for a higher price if it went up in value.
Nowadays, large firms do trading using different trading brokers and crossing networks to hide their intentions. Using quantitative analysis can be handy in this case.
Quantitative Trading conclusion
Quantitative Trading is all about mathematical and statistical models that try to identify potential trading opportunities. Mastering Quantitative Trading requires exceptional mathematical and coding skills. If a trader has a full grasp of these subjects, then Quantitative Trading can be a very attractive prospect.
It is very important to note that Quantative Trading is often based on historical data and there is absolutely no guarantee on how a trading strategy will perform in the future based on past results.
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