A perfect bundle of courses for traders who want to improve their trading outcomes by using statistical analysis. Learn new strategies such as momentum, mean-reversion, sentiment trading, index arbitrage, long-short, and triplets trading strategies. Learn to generate time series, cross-sectional alphas, as well as how to combine and optimise alphas. Learn the ins and outs of medium-frequency trading(MFT) and order flow analysis. Get hands-on training in Python and live trading deployable models.
- Learn about mean reversion trading strategies taught by Dr Ernest Chan, who employed these techniques in his own hedge fund.
- Create and backtest the time series and cross-sectional momentum strategies on stocks, stock indices, fixed income, commodities, and futures markets.
- Learn the ins and outs of medium-frequency trading(MFT), order flow analysis, different types of orders taught by Dr Ernest Chan.
- Find micro-alphas, optimise the parameters without overfitting and combine the alphas taught by seasoned Quant Dr Thomas Starke.
- Backtest, add stop-loss and profit-take by using a vectorized approach.
- Devise new trading strategies based on Twitter and news sentiment data, and predict market trends by quantifying market sentiments.
- One-click integration of quantitative models into a live trading platform to analyse strategies in a live trading environment.
What You’ll Learn In Advanced Algorithmic Trading Strategies?
- 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
More courses from the same author: Quantra
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Quantra – Advanced Algorithmic Trading Strategies
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