本課程培養同學運用AI機器學習在金融量化交易中的應用可以提高交易策略的準確性和適應能力。
課程中運用資料科學的方法讓同學們體驗以及實作量化交易利用演算法和統計模型來進行投資和交易的評估。
課程內容：
1. 熟悉金融市場:了解金融市場的基本概念和交易策略，這有助於你建立量化交易策略和模型。
2. 數據收集:獲取金融市場的歷史和實時數據，使用yfinance雅虎財金等來獲取金融數據。
3. 開發交易策略:使用資料科學AI模組來開發你的量化交易策略。學習技術指標的計算、趨勢分析、機器學習等方法。
4. 回測和優化:使用歷史數據來回測你的交易策略，評估其效果。根據回測的結果，優化和調整你的交易策略。
5. 整合量化交易策略:將訓練好的機器學習模型整合到你的量化交易策略中。這可能涉及到生成交易信號、風險管理等方面的應用實務。
最佳實踐：分享並討論同學的專案成果，並進行最佳實踐的探討。。

This course trains students to use AI machine learning in financial quantitative trading to improve the accuracy and adaptability of trading strategies.
The course uses data science methods to allow students to experience and implement quantitative trading, using algorithms and statistical models to evaluate investments and transactions.
Course content:
1. Familiar with financial markets: Understand the basic concepts and trading strategies of financial markets, which will help you establish quantitative trading strategies and models.
2. Data collection: Obtain historical and real-time data of the financial market, use yfinance, Yahoo Finance, etc. to obtain financial data.
3. Develop trading strategies: Use data science AI modules to develop your quantitative trading strategies. Learn the calculation of technical indicators, trend analysis, machine learning and other methods.
4. Backtesting and optimization: Use historical data to backtest your trading strategy and evaluate its effectiveness. Optimize and adjust your trading strategy based on the results of backtesting.
5. Integrate quantitative trading strategies: Integrate the trained machine learning model into your quantitative trading strategies. This may involve application practices in generating trading signals, risk management, etc.
Best Practices: Share and discuss the project results of classmates, and discuss best practices. .

講義

Handouts