Practical Approach To Amibroker Backtesting Optimization and Walkforward Testing

DAY 1 – 08.,00 PM – 09.30 PM (1.30 Hours)
    1) Introduction to Amibroker and AFL
    2) Understanding Amibroker Trading System
    3) Introduction to Backtesting in Amibroker
    4) Introduction to Position Sizing in Amibroker
    5) Amibroker Backtesting Settings
    6) How to Backtest for Cash Markets (Investing)
    7) How to Backtest for Futures Markets & Margin Trading
DAY 2 – 08.,00 PM – 09.30 PM (1.30 Hours)
    1) How to Apply Commissions Calculations
    2) Impact of Trade Commissions and Slippages in your Strategy
    3) How to Apply Target and Stoploss in Backtesting
    4) Amibroker Apply Stop Function
    5) Amibroker Backtesting Metrics
    6) Amibroker Custom Backtesting Metrics
    7) Various Amibroker Backtesting Modes
    8) Dynamic Position sizing
DAY 3 – 08.,00 PM – 09.30 PM (1.30 Hours)
    1) Understanding Optimization
    2) How to Peform Smart Optimization
    3) How to Perform Optimization 3D Visualization
    4) How to Avoid Curve Fitting. Practical Guidelines
    5) In Sample and Out of Sample Data
    6) Walk Foward Analysis
    7) Monte Carlo Analysis
    8) Complete Process Involved in Building a Trading System to Execution
About Mentor

Mr.Rajandran is a Full time trader and founder of Marketcalls & Co-Founder of Traderscafe, trades mostly using discretionary Trading Concepts like Market Profile, Trading sentimental analysis, building timing models, algorithmic trading models. Instructs professional traders, full time traders & aspiring full time traders. Rajandran attended college in the Chennai where he earned a BE in Electronics and Communications. Rajandran has a broad understanding of trading softwares 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.

PRICING

ENGLISH

17-June-2020 – 19-June-2020

Rs.10,000

75% OFF

Discounted Price

Rs.2,500

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