NeuroEvolution-BTC-Trader
Unverified ML strategy on Crypto by SC4RECOIN. BotFinder score 18 out of 100.
Building a population of models that trade crypto and mutate iteratively
Source: github
BotFinder analysis pending.
NeuroEvolution-BTC-Trader
NeuroEvolution BTC Trader The goal of this project was to create a model that would trade on technicals through neuroevolution. The initial population is built given a specified network topology and assigned random weights. For each generation, these weights are randomly mutated and each network is assigned a fitness value based on its performance. A pooling algorithm is then used to select models for the next generation and the process is repeated. Models with a higher fitness tend to make it to the next generation where their weights are mutated and ideally create a higher performing generation. See python branch for original implementation
⚠ No verified equity curve — no track-record source connected.
Drawdown profile
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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)