What Is Quantitative Trading?

Trading techniques based on quantitative analysis, which depend on mathematical computations and number crunching to find trading opportunities, are known as quantitative trading. Price and volume are two of the most popular data inputs used as the major inputs to mathematical models in quantitative analysis.
Because financial institutions and hedge funds commonly employ quantitative trading, the transactions are typically enormous, including the buy and selling of hundreds of thousands of shares and other assets. Individual investors, on the other hand, are increasingly using quantitative trading.
Quantitative trading has the problem of having a restricted application: as other market participants hear about it or when market conditions change, a quantitative trading technique loses its efficacy.

Quantitative trading is an extremely sophisticated area of Quant finance. It can take a significant amount of time to gain the necessary knowledge to pass an interview or construct your own trading strategies. Not only that but it requires extensive programming expertise, at the very least in a language such as MATLAB, R or Python. However as the trading frequency of the strategy increases, the technological aspects become much more relevant. Thus being familiar with C/C++ will be of paramount importance.

A quantitative trading system consists of four major components:

  • Strategy Identification - Finding a strategy, exploiting an edge and deciding on trading frequency

  • Strategy Back testing - Obtaining data, analysing strategy performance and removing biases

  • Execution System - Linking to a brokerage, automating the trading and minimising transaction costs

  • Risk Management - Optimal capital allocation, “bet size”/Kelly criterion and trading psychology