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Combo 3 New Courses From AmiBroker of https://crabaca.store/
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Combo 3 New Courses From AmiBroker

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Combo 3 New Courses From AmiBroker

Combo 3 New Courses From AmiBroker

Combo 3 New Courses From AmiBroker

Archive : Combo 3 New Courses From AmiBroker

Rotational System Construction in AmiBroker by Matt Radtke
May 10, 2019 | Matt Radtke

 

This course will examine several AmiBroker rotational system creation techniques. It contains around two hours of online teaching as well as Excel files with AmiBroker test results for the example strategy covered in the course and AFL code templates that you can easily alter for your own purposes.

Prerequisites
Check out the free presentation
Introduction to Rotational Strategies, Scoring, and Ranking
Install a data source and AmiBroker version 6.x (Version 6.2 or later is preferable).
AFL proficiency of intermediate level or above, including the capacity to design and carry out back tests and optimizations using AmiBroker’s default back test engine
basic understanding of how a Custom Backtest functions. The CBT Intensive course comes highly recommended if you have never utilized cognitive behavioral therapy.
Course Description
Introduction to Rotational Strategies, Module 1
Rotational strategies: what are they?
Typical Strategy and Rules
A simple rotational strategy
Module 2: Support for Rotational Strategies in AmiBroker
The Rotational Mode of AmiBroker
Using backtest with the Sample Strategy
rotated state
Results Comparison Benefits and Drawbacks
Module 3: Using a CBT to Recreate Rotational Mode
controlling the process of rotation
From Mid to Low Level Conversion CBT Results Comparison
More CBT functionality in Module 4
Separate Worst Rank is Maintained for Long and Short Comparisons of Results (Rebalancing)
Summary
Unit 5: Business Hours (Q&A)
Session of Business Hours (Course Attendee Q&A)
AmiBroker Matt Radtke Intensive Custom Backtester
For traders who wish to utilize AmiBroker to build complicated back tests and optimizations utilizing the Custom Backtest (CBT) interface, there is the CBT Intensive course.
After completing this 4-plus hour training, you will be able to: – Choose which of the Custom Back Tester’s three levels to utilize when Utilize the – Custom Back Tester to add personalized trading metrics The – Custom Back Tester allows you to add custom portfolio measures. Enter, amend, and exit transactions at will – Complete total control over the processing of entry and exit signals – Carry out auxiliary tasks like hedging
1. AmiBroker Topic Summary for Session 1
2.Architecture
3. User Functions Constructed from Data
4. Second Object Model Session
1. Getting Started with the CBT
2. Advanced CBT
Session 3 of the mid-level CBT.
1. Low-intensity CBT
2. Common Errors
Programming Adaptive Strategies in AmiBroker with Matt Radtke

The emphasis of this course will be on utilizing AmiBroker’s Custom Backtest (CBT) interface to create adaptive trading strategies. CBT was first covered in the CBT Intensive.

When this course is over, you will be able to: Create your own Market Regimes
Think about how a trading regime assigns setup, entrance, and departure.
Rank metrics by regime in summary
Adopt adaptive (regime-specific) parameters in your AFL.
compare the performance of the adaptive approach to a starting point
Prerequisites:

installed AmiBroker 6.0 or a later version. Versions 6.20 and later are advised.
installed and prepared a data source to function with AmiBroker.
possess a fundamental understanding of AFL, including the capacity to design and carry out back tests and optimizations using AmiBroker’s default back test engine.
Recognize the AmiBroker object model and how to create custom metrics, as well as how the CBT operates.

Topic Overview for Session 1

Market Regimes Definition
Market Regime Performance
Metrics for Regime Assignment

2nd session

Excel Updates for Out-of-Sample Testing, In-Sample Optimization, and AFL

3rd session

Optimization for Out-of-Sample (OOS)
Results with Out-of-Sample (OOS) Adaptivity
OOS Adaptive and OOS Static Comparison
OOS Adaptive and OOS Optimization are contrasted.
Dynamic Parameter Refresh

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