blave-agent
Unverified ML strategy on Crypto by Blave-TW. BotFinder score 18 out of 100.
Quant infrastructure for AI agents — a free, open-source macOS workspace where your Claude Code or Codex turns a trading idea into a backtested strategy and runs it live.
Source: github
BotFinder analysis pending.
blave-agent
Blave Agent Agentic Quant Workspace Turn Your Agent into a Quant Free and open source. Connect your Claude Code or Codex. You describe the idea; it writes the strategy, runs the backtest, and trades it live. English | 繁體中文 | 简体中文 | 日本語 | Español | Português | Tiếng Việt https://github.com/user-attachments/assets/7b33edb7-9c65-4e19-854a-40295c6e8b74 Download for macOS · Download for Windows · Quick start (from source) · Run it with your computer off Star the repo if this is useful — and Watch › Releases to get notified of new versions. What Makes It Different Backtests That Check Whether It Was Luck - Every Type A backtest runs a Monte Carlo permutation test by default (MCPT, lib/validation.py) and records a p-value: could shuffled data have done as well? - A parameter scan (lib/paramscan.py) looks for a plateau of parameters that all work, not the single best cell. - Rolling walk-forward (lib/walkforward.py) measures out-of-sample performance. - The fee has to match the real market. A fee of 0 is flagged by lib/qualitycheck.py and treated as a bug. - One idea gets one backtest by def
⚠ No verified equity curve — no track-record source connected.
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.
Reviews & comments
No reviews collected from the source yet.
⚠ No live verification account connected — ask for proof before buying.
Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)