R_selflearning
Unverified ML strategy on Forex by vzhomeexperiments. BotFinder score 18 out of 100.
Developing self learning robot
Source: github
BotFinder analysis pending.
R_selflearning
Rselflearning Repository for the Udemy course. Please support this project by joining this on-line course: https://www.udemy.com/course/self-learning-trading-robot/?referralCode=B95FC127BA32DA5298F4 Note: this course is the part of the series of step-by-step tutorials allowing to build more comprehensive Automated Trading System based on Decision Support System approach. Check out other courses of the series. Synchronize or Deploy Setup Environmental Variables Add these User Environmental Variables: PATHT2 - path to Development Terminal MT4, folder \MQL4\Files PATHT1, PATHT3, etc - paths to the Terminals where all other terminals are located PATHDSSRepo - path to the folder where this repository is stored on the local computer Goal Create model-based self-testing artificially intelligent trading system. Motivation There are probably just 3 possible types of mechanical trading systems: Human Idea[captured from the screen pattern] -> Indicator[parameters] + fix trading rules + Fresh Data = trading decision Past Data + Algorithm[based on some idea] -> Model[hyperparameters] + Fresh Data
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Drawdown profile
Data unavailable — contact the owner.
Verification ledger
How the score has moved
Recalculated at each data collection. Transparency means showing the bad weeks too.
No score history is stored yet — only the current score is shown.
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Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)