Data collection:
Collecting historical and real-time data, including prices, trading volumes, financial reports, news, etc., which form the basis of quantitative models.
Model development:
Developing models to forecast market trends using statistical methods, machine learning, etc. This may involve predicting stock price trends, identifying market timing for buying and selling, etc.
Strategy backtesting:
Testing the performance of trading strategies using historical data to evaluate their performance and risks under different market conditions.
Executing strategies:
Using algorithms to execute trades, which can be completed within milliseconds, greatly enhancing the speed and efficiency of trading.
Risk management:
Monitoring the performance of the market and strategies in real-time, adjusting strategies to control risks.