1. For whom is the algo trading course useful?
It is useful for anyone who wants to start a career/business in algo trading.
- The algo trading course suits students from non-programming background because it uses AFL as the tool for education.
- At the same time, the course also suits students with strong programming skills in R/C++/Python/Java/Matlab. For students with programming background, professional trading concepts are introduced in AFL, which can be replicated in technology of their choice. For example, real-time handling of trade triggers and API integration is similar in most technologies
2. What are the pre-requisites for taking algo trading course?
Students should be familiar with Amibroker & Programming basics.
3. What if I miss one or two classes?
Recording for all sessions will be provided. Further, you will have access to a professional forum for discussion with other students/practitioners.
4. Will I learn AFL coding completely after taking Algo Trading Course
To learn anything completely, any course cannot be sufficient. Our commitment is, to provide you a strong foundation in AFL coding, as well as overall algo trading
5. How do you plan to deliver so much in just 14 hours?
First, the course is not for 14 hours- it includes two month of support. We could have completed the sessions in 2 days. But we spread it over 3-months so that students get ample time to practice. 14-hours of live training is supported with lots of code samples, assignments and forum interaction.
Anything basic about Amibroker/Technical Analysis/Algo Trading will be supported through forum by a designated Trading Councillor.
6. Do I get a good afl strategy? Tell me about AFL strategies you provide
Yes, you will be given good AFL strategies… but please read this to know what we mean by a “good strategy” : https://algoji.com/best-amibroker-afl/
7. What do you cover for Quantiative Analysis/Python?
We will show you how to integrate Python with Amibroker, perform ADF tests for pair trading, regression analysis and time series detrending.
8. Would we be covering Kalman filters? ARCH/GARCH Models?
We have included how to integrate Amibroker with Python COM Server. Price data will be passed from Amibroker to Python. In Python, you can use statistical libraries like numpy/pandas for ADF and Kalman filter. Then pass calculations back to Amibroker for including these parameters in overall trading strategy. So basically you will be able to harness full power of python.
9. Will you teach me Python/R? Please provide resources for learning Python/R
In this course, we focus on strategy discovery, design and deployment using Amibroker. Given time constraints, we will not discuss Python per se; but rather its practical use by integration with Amibroker.
Detailed Content & Youtube videos
Session-1 AFL Structure and Coding Resources
- AFL Coding Tutorial- indicator, buy/sell, exploration, backtesting, optimization, live trading
- AFL Resources
Session-1 Video Replay: https://www.youtube.com/watch?v=kdeS-890COo
Session 2: Coding Trading Rules- exrem, flags, looping, flags
- Uses of Exrem and limitations
- Where looping is necessary?
- Difference between if and iif
- Controlling SL, TSL through looping
Session 3: Debugging Practices (Title, Trace)
- Title for debugging AFL variables
- Common Coding Mistakes
- Trace for debugging RT functions
Session-3 Video Replay: https://www.youtube.com/watch?v=bCRSB7aG4VQ
Session 4: Selecting Indicators, Timeframes, Costs
1. Measuring Volatility
2. Patterns vs Indicators
3. Indicators for Price Trends
4. Momentum and Oscillators
5. Scalping systems
6. Pair Trading and Mean Reversion
7. Multiple Time frames
Session-4 Video Replay: https://www.youtube.com/watch?v=dTdVS6C0eQ0
Session 5: Strategy Design Process
- Trading Premise
- Design Guidelines
- Robustness of Strategy
Session-5 Video Replay: https://www.youtube.com/watch?v=qpZXEY0Oy7A
Session 6: Backtesting & Optimization Practices
- All backtesting settings
- Visual backtesting, verifying data and trades
- In-sample and out-sample tests
- Testing parameters for robustness
- 3D Optimization Graph
- Using Optimization Engine
- Smart Optimization and avoiding curve fitting
Session-6 Video Replay: https://www.youtube.com/watch?v=72EqM5urCCk
Session-7 Paper Trading and Execution Strategies
- Simulated Trading vs Actual Trading
- Using Paper Trading AFL- amibroker settings
- Using Paper Trading AFL- Verifying repainting signals, verifying future looking signals
- Using Paper Trading AFL- Verifying backtests
- Using Paper Trading AFL- improving execution at hi/lo, candle open/close without coding
- Using Paper Trading AFL- improving execution by using bid/ask prices
Session-7 Video Replay: https://www.youtube.com/watch?v=vDTo-Eg9seo
Session-8 The Bigger Picture- Portfolio Modeling
- Understanding Probabilities
- Setting up Profit Targets
- Portfolio Modeling
- Raising CAR/MDD upto 5x and beyond
Session-8 Video Replay: https://www.youtube.com/watch?v=aCBeuaSran8
Session 9: Position Sizing Strategies
- Exit partial quantity at exit and partial quantity at TSL
- Enter partial quantity on momentum and partial quantity on trend
- Grid trading with both scale-in and scale-out
Session 10: Doubts & Queries
Session 11: Quantiative Analysis
- Integrating AFL with VB Script, Java Script
- Integrating AFL with COM objects
- Integrating AFL with Python
- ADF Tests for pair trading
- Backtesting years of Options Data
Session-11 Video Replay: https://www.youtube.com/watch?v=se1UQsnKD1A&t=68s
Session 12: Multi-leg Strategies
- Automatically hedging a position in futures with options
- Straddles and strangles
- Pair Trading revisited
Session 13: API Integration
- Presto API Functions
- Managing limit orders
- IB API Integration
Session 13 Video Replay: https://www.youtube.com/watch?v=DHLcZVep6fI
Session 14: Live Trading Practices
- Focus on skill building
- Process Oriented
- Trading Psychology blah blah
- Keeping commonsense intact
- Trade journals
- Colleagues and Peers