You are currently requesting access to the institutional-grade blueprint for Learning Track: Automated Trading using Python and Interactive Brokers – QuantInsti. This is a highly classified quantitative trading asset. Instant digital deployment and lifetime encrypted access are guaranteed immediately upon transaction clearance.
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A complete end-to-end learning programme that starts by teaching basics in Python and ends in implementation of new algorithmic trading techniques in live markets. Highly recommended if you wish to multiply your portfolio and include historical data back-testing & discipline in your trades.
SKILLS COVERED
COURSE FEATURES
- Lifetime Access to the course
- Community support
- Downloadable codes
- Hands-on guided learning
- Get Certified
LEARNING TRACK
Automated Trading using Python & Interactive Brokers
Mini Learning Track
These courses are often bought together for better understanding of connected concepts.
Specialization Bundle
This set of courses have shown to be most effective in learning and implementation of techniques in trading.
PREREQUISITES
It is expected that you have some trading experience and understand basic financial markets terminology like sell, buy, margin, entry, exit positions. You can complete the learning track without any Python knowledge and replicate the models in spreadsheets or any other trading software language you are comfortable with.
AFTER THIS COURSE YOU’LL BE ABLE TO
Automate your trading. Backtest your trading strategies ideas on historical data. Connect with broker by understanding the API structure. Learn to manage your portfolio and place orders.
Multiply your portfolio. Master different quantitative techniques used across different asset classes and options: Statistical Arbitrage, Options Pricing models, Time Series Modelling. Work with actual markets data to create prediction models using machine learning algorithms. Create 20+ new trading strategies.
Start your algorithmic trading desk/business. In a short time of around 40 hours, gain hands-on experience in using technology and mathematics in trading. Get trained by Quants, HFT traders and market practitioners and learn from their experience.
SYLLABUS
Course 1: Getting Started with Algorithmic Trading!
- Introduction
- Why Algorithmic Trading?
- Available Platforms & Languages
- Strategy Paradigms
- Algorithmic Trading Platform
- Regulations & Compliance (Optional Section)
- Downloadable Resources
Course 2: Python For Trading!
- Introduction to Python!
- Python Data Structures
- Data Analysis & Trading
- Dealing with Financial Data
- Backtesting
- Performance Metrics
- Python Installation and Automated Execution
Course 3: Trading using Options Sentiment Indicators
- Introduction to Sentiment Trading
- Breadth Measures
- Option Trading Measures
- Volatility Measures
- Risks in Trading
- Python Installation and Automated Execution
- Conclusion and Downloadable Resources
Course 4: Quantitative Trading Strategies and Models
- Quantitative Trading: An Introduction
- Technical Trading Strategies
- Econometric Models
- Quantitative Trading Strategies for Options
- Python Installation and Automated Execution
- Summary
Course 5: Trading with Machine Learning: Classification and SVM
- Introduction
- Binary Classification
- Multiclass Classification
- Support Vector Machine
- Prediction and Strategy
- Python Installation and Automated Execution
- Downloadable Code
Course 6: Automated Trading with IBridgePy using Interactive Brokers Platform
- Introduction
- Installation Steps
- Know the basic Code Structure
- Learn how to Fetch Data
- Orders Management
- Portfolio Management
- Trading Strategy Implementation
- Downloadable Resources
Course 7: Mean Reversion Strategies In Python
- Stationarity of Time Series
- Cointegration
- Triplets
- Half Life
- Risk Management
- Best Markets to Pair Trade
- Index Arbitrage
- Long Short Portfolio
- Python Installation and Automated Execution
- Summary
INSTITUTIONAL RISK DISCLOSURE: Trading foreign exchange, cryptocurrencies, and algorithmic assets on margin carries a high level of risk and may not be suitable for all investors. Past performance of any trading system or quantitative blueprint does not guarantee future results.
