ARTEMIS is an autonomous trading infrastructure that learns from every market signal — including the ones it doesn't trade. Plug into your Binance Futures account. Let the system adapt.
ARTEMIS is not a signal service or a copy-trading platform. It is infrastructure — designed for people who want to understand what their system is doing and why.
Every filter threshold, prior strength, and starvation trigger is exposed as an environment variable. Modify, fork, extend — the architecture is yours to inspect via the published paper.
Connect via Binance Futures API keys. Non-custodial — ARTEMIS never holds or withdraws funds. Your capital stays in your account at all times. You keep full control.
The full system is documented in a Zenodo preprint with Bayesian optimization details, FDR correction, and out-of-sample validation. Citable. Reproducible. Transparent.
Experiments on 301 live trades over 60 days show that ARTEMIS consistently outperforms static and random baselines through continuous Bayesian optimization. Win rate improvement of +10.1pp is statistically significant at p < 0.01 (Wilcoxon signed-rank test).
| Methodology | Trades | Win Rate | Status |
|---|---|---|---|
| Fixed (Static Baseline) | 87 | 31.2% | Underperforming |
| Random Updates | 142 | 28.7% | Non-viable |
| Shadow-Only Learning | 294 | 35.1% | Neutral |
| ARTEMIS (Full System) | 301 | 41.3% | Active Alpha |
Most systems discard signals that don't pass their filters. ARTEMIS simulates them — and learns from the outcome without risking a single dollar.
When filters become too restrictive, most systems simply stop trading — and stop learning. ARTEMIS detects this automatically and heals itself through a two-tier protection architecture.
Author: David López Oñate · Researcher - Kinqo AI.
Published on Zenodo (v1.1 · 2026-03-02 · CC BY 4.0).
Peer-reviewable methodology with full Bayesian optimization details, FDR correction, and out-of-sample validation across three market regimes.
@article{onate2026artemis,
title = {ARTEMIS: Adaptive Multi-Agent
Trading System with Risk-Free
Exploration via Shadow Mode},
author = {L{\'o}pez O{\~n}ate, David},
year = {2026},
note = {Zenodo Preprint v1.1},
doi = {10.5281/zenodo.18841943}
}
The current system operates on cryptocurrency futures. Our 2026–2027 roadmap expands ARTEMIS into multi-asset portfolio optimization and universal regime detection.
Correlation matrices and Kelly criterion position sizing across concurrent trades.
Expansion to Forex and equities via meta-learning adaptation across markets.
Pre-trained transformer for universal market regime detection across asset classes.
ARTEMIS connects via read/write Binance API keys — non-custodial, no withdrawal permissions ever. One integration. Continuous adaptation.
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