Amibroker For Professional Strategy Design and Algo Trading (APSAT) - AlgoJi

Amibroker For Professional Strategy Design and Algo Trading (APSAT)


Curriculum Revised!

  • Program, backtest, and deploy advanced multi-leg strategies on hedging, option chains, pairs etc.
  • Program, backtest, and deploy advanced scale-in, scale-out and grid trading strategies
  • Seamlessly integrate Amibroker and Python for exhaustive machine learning
  • Build custom execution strategies by programming order management rules
  • Combine different premise like trend, momentum, mean-reversion into a single powerful strategy
  • Combine uncorrelated strategies into a robust portfolio
Trainer Profile: Mr. Saurabh Lohiya
  • 10 years of systematic trading experience, CMT charter holder since 2010
  • Vast experience in Global Markets- Forex, Equities and Commodities; worked at proprietary trading firms
  • Expertise in Trading Strategy Automation and Algorithmic Trading; worked at a large brokerage house
  • Deployed diverse types of trading algorithms- from HFT to MFT to LFT
  • First-hand experience with latest trading technology in Indian and Global Markets

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  1. Free Paper Trading Setup (with limit orders, market orders and execution strategies)
  2. 14 live interactive sessions
  3.  AFL assignments covering trend following, mean reversion, pair trading, options trading, scalping, support-resistance etc.
  4. 18+ recorded sessions
  5. Three-month query resolution support; Intensive group based learning
  6. Life-time access to professional forum of algo traders
  7. Pre-requisites: Participants should have working knowledge of Amibroker and Programming (in any language)
  • Timing for International Participants: Mondays and Fridays, CST 8:30AM-9:30AM
  • Timing for Indian Participants: Mondays and Fridays, IST 8:00PM-9:00PM


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” :

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

  1. AFL Coding Tutorial- indicator, buy/sell, exploration, backtesting, optimization, live trading
  2. AFL Resources

Session-1 Video Replay:

Session 2: Coding Trading Rules- exrem, flags, looping, flags

  1. Uses of Exrem and limitations
  2. Where looping is necessary?
  3. Difference between if and iif
  4. Controlling SL, TSL through looping

Session 3: Debugging Practices (Title, Trace)

  1. Title for debugging AFL variables
  2. Common Coding Mistakes
  3. Trace for debugging RT functions

Session-3 Video Replay:

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
8. Costs

Session-4 Video Replay:

Session 5: Strategy Design Process

  1. Trading Premise
  2. Design Guidelines
  3. Robustness of Strategy

Session-5 Video Replay:

Session 6: Backtesting & Optimization Practices

  1. All backtesting settings
  2. Visual backtesting, verifying data and trades
  3. In-sample and out-sample tests
  4. Walk-forwards
  5. Monte-Carlo
  6. Testing parameters for robustness
  7. 3D Optimization Graph
  8. Using Optimization Engine
  9. Smart Optimization and avoiding curve fitting

Session-6 Video Replay:

Session-7 Paper Trading and Execution Strategies

  1. Simulated Trading vs Actual Trading
  2. Using Paper Trading AFL- amibroker settings
  3. Using Paper Trading AFL- Verifying repainting signals, verifying future looking signals
  4. Using Paper Trading AFL- Verifying backtests
  5. Using Paper Trading AFL- improving execution at hi/lo, candle open/close without coding
  6. Using Paper Trading AFL- improving execution by using bid/ask prices 

Session-7 Video Replay:

Session-8 The Bigger Picture- Portfolio Modeling

  1. Understanding Probabilities
  2. Setting up Profit Targets
  3. Portfolio Modeling
  4. Raising CAR/MDD upto 5x and beyond

Session-8 Video Replay:

Session 9: Position Sizing Strategies

  1. Exit partial quantity at exit and partial quantity at TSL
  2. Enter partial quantity on momentum and partial quantity on trend
  3. Grid trading with both scale-in and scale-out

Session 10: Doubts & Queries

Session 11: Quantiative Analysis

  1. Integrating AFL with VB Script, Java Script
  2. Integrating AFL with COM objects
  3. Integrating AFL with Python
  4. ADF Tests for pair trading
  5. Backtesting years of Options Data

Session-11 Video Replay:

Session 12: Multi-leg Strategies

  1. Automatically hedging a position in futures with options
  2. Straddles and strangles
  3. Pair Trading revisited

Session 13: API Integration

  1. Presto API Functions
  2. Managing limit orders
  3. IB API Integration

Session 13 Video Replay:

Session 14: Live Trading Practices

  1. Focus on skill building
  2. Process Oriented
  3. Trading Psychology blah blah
  4. Keeping commonsense intact
  5. Trade journals
  6. Colleagues and Peers

Contact Trainer

Contact Trainer for APSAT

Other Details

APSAT Course Objective
  1. Explain in-depth professional concepts with foundational content; but at the same time easy to grasp; covering AFL Coding+Technical Analysis+Quantitative  Analysis+Portfolio Modeling
  2. Build strong foundation to start a career/business in algo trading
  3. Algo Trading Course suites audience from all programming backgrounds
  4. It is a short-term duration course(does not require commitment in time)
  5. Affordable (does not require financial commitment)
Why Chose Amibroker for Algo Trading?
  1. It has world’s fastest portfolio backtesting and optimization engine.
  2. AFL, the scripting language of Amibroker, is an Array Based Language. This makes AFL concise and very efficient.
  3. You can get a large number of AFLs and excellent learning resources free over internet.
  4. It has inbuilt batch processor. You can schedule Amibroker to start automatically, do the analysis, and send email alerts while you are at work.
  5. It has an open ecosystem for developers. Amibroker is easy to integrate with Broker APIs and build Data Plugins.
  6. It is really inexpensive. The free trial of Amibroker is sufficient to learn everything in this course.