Week1: Quantitative Trading History and Frontier
Week2: Market microstructure and transaction data
Week3: Trading interface
3.1, CTP market and trading interface
3.2. Collect data through the market interface
3.3 Classification
Week4: Forecast
4.1, subjective trading to technical indicators
4.2, systematic forecasting
Week5: Backtest 1-Test your trading strategy
5.1, back-testing system
Project: A Preliminary Study of CTA Trading Strategy
…
Week6: Linear model
Week7: Portfolio
7.1. Risks and benefits
7.2. Asset portfolio
7.3. Capital asset pricing model
week8: Stock multi-factor framework 1
8.1. Data processing and factor screening
8.2. Revenue forecast
week9: Stock multi-factor framework 2
9.1. Risk prediction
9.2. Combination optimization
Project: Research on stock multi-factor strategy
Week10: Backtest 2-Establish a backtest framework based on the strategy type
Week11: Feature Engineering of Quantitative Trading
Week12: From backtesting to trading
12.1 Trading interface
12.2 Transaction operation and maintenance
12.3. Backtesting system for optimization of trading results
Week13: Option pricing model
13.1 European options and American options
13.2 BSM model
13.3, Binary Tree
Week14: Option Volatility Trading
Week15: Frontier of Quantitative Trading
15.1 Alternative data and natural language processing
15.2 High-frequency trading
Week16: Fundamental Quantification
16.1 Quantification of the fundamentals of stocks and commodities
16.2 Macro trading
Get resources +VX:daydayit (remarks start the class, AI quantitative investment)