Quantra – Advanced Algorithmic Trading Strategies

Quantra – Advanced Algorithmic Trading Strategies

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?

  • 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 – Advanced Algorithmic Trading Strategies

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