🎯
Focusing
Building RLXBT — reproducible backtesting and research infrastructure. Publishing failures, benchmarks, and fixes.
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VBRL space
- Switzerland
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23:17
(UTC +02:00) - https://rlxbt.com/
- @SOvsiienko
Pinned Loading
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ml-quant-trading
ml-quant-trading PublicForked from initial-d/ml-quant-trading
PyTorch research stack for ML multi-factor trading: 213 factors, bias correction, portfolio optimization, and vectorized backtesting.
Python
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quant-research-log
quant-research-log PublicReproducible quant research: failed strategies, backtesting probes, execution-cost studies, and engine defects found with RLXBT.
Python
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rlxbt
rlxbt PublicEvidence-first infrastructure for quant research, event-driven backtesting, robustness analysis, and trading RL.
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