Quantra – Trading Alphas: Mining, Optimisation and System Design

Why should you choose micro alpha models over other trading strategies such as traditional factor models, risk-parity, or trend following? In short, these models, if built well, can provide better performance, stability, and risk management than other trading systems. In this course, you will learn where micro-alphas reside and how to write the most efficient codes to quickly analyse, backtest, optimise and go live with your trading strategy in the least amount of time possible.

• Backtesting, adding stop-loss and profit-take using vectorised approach
• Mining micro-alphas using trends, mean-reversion, correlation across assets, and cointegration
• Metrics for analysing strategy which include total profit, sharpe ratio, sortino ratio, profit factor, drawdown, and profit per trade
• Parameter optimisation using machine learning techniques such as clustering
• Building a trading system from scratch
• Explain software architecture, logging, storage, hardware, testing and version control
• Brief study on execution models, implement parallel computing and describe different levels of logging

What You’ll Learn In Trading Alphas: Mining, Optimisation and System Design?

• Introduction
• Micro Alphas
• Market Inefficiencies: Trend
• Market Inefficiencies: Mean Reversion
• Trading with Trends and Mean Reversion
• Market Inefficiencies: Chart Patterns
• Market Inefficiencies: Correlation, Fundamental and Alternative
• Market Inefficiencies: Cointegration
• Time Series Alphas
• Live Trading on Blueshift
• Live Trading Template
• Cross-Sectional Alphas
• Timing Alphas
• Combinations of Alpha
• Finding Micro-Alphas
• Assessing Results
• Total Profit
• Sharpe and Sortino Ratios
• Profit Factor and Drawdown
• Profit Per Trade
• CAGR, Alpha, and Beta
• Strategy Execution
• Micro-Alpha Portfolio
• Portfolio Optimisation
• Advanced Alpha Mining
• Machine Learning Alphas
• Basics of Vectorized Backtest
• Adding Vectorized Stop-loss and Profit-takes
• Impact of Profit Take and Stop Loss on Strategy
• Designing a Trading System
• Asynchronous Computing
• Distributed Computing
• Importance of Logging and Storage
• Hardware Elements of a Trading System
• Software Elements of a Trading System
• Testing and Version Control
• Implementation of a Trading System
• Types of Servers
• Trading Logic
• Testing and Operation
• Capstone Project
• Run Codes Locally on Your Machine
• Summary

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Quantra – Trading Alphas: Mining, Optimisation and System Design

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