Learn the important components for building an algorithmic trading system from scratch. This course has been built for newbies using the easiest programming language called AFL – Amibroker Formula Language.
What will you learn?
This course will give you an overview of the critical components needed for your own algo trading system. This will give a thought to pieces that will make you successful as an indie automated trader to control your own destiny.
Goals: Who would benefit from this course?
Professionals – To understand the mechanics of standard implementations of the single asset and portfolio based trading strategies. Recognize pros and cons of various approaches to designing strategies and the common pitfalls encountered by algorithmic traders.
Algorithmic Traders – To recognize what works and what doesn’t in Rule-Based Trading. Understand the statistical properties of strategies and Robust strategy validation procedures. Acquire hands-on experience in Algo trading API’s, Algo Trading Workflow and improve methods to prevent overfitting.
Academics/Students – To gain familiarity with the broad area of algorithmic trading strategies. Master the underlying theory and mechanics behind the most common strategies. Acquire the understanding of principals and context necessary for new academic research into a large number of open questions in the area.
1) Introduction to Algorithmic Trading Pros and Cons in Algorithmic Trading.
2) Setting up your Algorithmic Trading Desk and Test Environment.
3) Understanding Trading Components.(Amibroker, Datafeed, Trading Bridge/API’s)
4) Algorithm Selection Process.(Trend Following, Mean Reversion, Seasonal, Pattern Based Trading)
5) Intraday Trading Systems Vs Positional Trading Systems.
6) Automating your Investment Strategies.
7) Introduction to Orderbook Dynamics and Type of Orders.
8) Backtesting and Optimizing your trading systems.
9) Understanding the Risk Metrics (Risk-Adjusted Returns, Sharpe Ratio, Max Drawdown, Expectancy, K- Ratio, Skewness… Etc.)
10) Out of Sample and Monte Carlo Validation procedures to check the robustness of trading systems.
11) Filters and Timing.
12) Integrating Trading API’s with Decision support tool (Amibroker)
13) Realistic modeling of Transaction cost (Trading Commissions, Slippages, Taxes… Etc.)
14) Ways to control slippages while execution.
15) Understanding VAR and CVAR concepts.
16) Dynamic Position Sizing, Importance of Portfolio Protection Strategies and Automated Hedging.
17) Evaluating Implementation of Trailing Stops, Profit Booking and Partial Profit/Loss in your trading system.
18) Trading the Equity curve feedback.
19) Holding Period Analysis, Multi Time-frame Strategies
20) A Ranking, Position Score and automating stock selection process.
21) Rotational Trading System Models and Non-Linear Trading Models.
22) Avoiding Survivorship Bias, Data Snooping, Curve Fitting.
23) Trading System Health and Detecting System Breakdown.
24) Common errors encountered in Algorithmic Trading
25) Automating Effective Money Management Rules.
26) Building an End to End Fully Automated Trading System with minimal Supervision.
Mentor: Mr. Rajandran from MarketCalls
About the Mentor
Rajandran is a Full-time trader and founder of Marketcalls, hugely interested in building timing models, algos, discretionary trading concepts and Trading Sentimental analysis. He now instructs users all over the world, from experienced traders, professional traders to individual traders. Rajandran attended college in the Chennai where he earned a BE in Electronics and Communications. Rajandran has a broad understanding of trading software like Amibroker, Ninjatrader, Esignal, Metastock, Motivewave, Market Analyst(Optuma), Metatrader, Tradingivew, Python and understands individual needs of traders and investors utilizing a wide range of methodologies.
Knowledge about Futures and Options Trading Concepts, Basics of Technical Analysis. Basic knowledge about Amibroker (Technical analysis tool). Deeply passionate to learn Automated trading.
Frequently Asked Questions
Should I attend this programme?
The course is a practitioner-orientated professional course that will enhance the short-term and long-term career prospects of anyone working in (or looking to enter) Algorithmic Trading Strategies.
When will the Algorithmic Trading Strategies Workshop commence?
The course starts on Saturday 07th April 2018 and ends on 08th April 2018.
How long is the course?
The course has a total of 14 hours of live lectures and 24+ hours of recorded webinars on How to Design your own trading strategies using Amibroker.
How do I contact the Instructor post the course?
1 Year of Slack Access will be provided to our private trading community where we will be discussing algo trading, trading strategies, trading API and best practices.