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Quantitative trading is an extremely sophisticated area of quant finance. It encompasses trading strategies based on quantitative analysis which rely on mathematical computations and number crunching to identify trading opportunities. Price and volume are two of the more common data inputs used in quantitative analysis as the main inputs to mathematical models.

The transactions are usually large in size and may involve the purchase and sale of hundreds of thousands of shares and other securities, since quantitative trading is generally used by financial institutions and hedge funds.

At the same time, quantitative trading is also commonly used by individual investors.

A quantitative trading system consists of four major components:

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

Its techniques include high-frequency trading, algorithmic trading and statistical arbitrage. They are believed to contribute to increased market volatility because of the rapid-fire nature of their trading and extremely short investment horizon. Many individual investors are more familiar with quantitative tools such as moving averages and oscillators.