Theta Trading System

🎯 Theta量化交易系统v1.2.0 - 100%准确率Ridge模型，每小时自动进化，多数据源兜底，准星模型集成，实时数据验证。基于真实A股涨停股数据的智能选股系统。

Things to consider before installing or running this skill: - Credibility and claims: The README/SKILL.md advertise a '100% 准确率' Ridge model and hourly evolution, but the training script actually uses RandomForest and the packaged metrics/files contain contradictory values and sample counts. Treat marketing claims as unverified until you can reproduce results. - Missing files / runtime errors: The documentation references recommendation and analyzer scripts and Python modules that are not present in the package (theta_daily_recommendation.py, theta_analyzer.py, theta_system/theta_trading). Expect runtime failures; ask the author for the missing files or a complete release. - Run in a sandbox: If you want to test it, run the package inside an isolated environment or container (not as root) so filesystem writes under /root/.openclaw/workspace cannot affect your host. Inspect and run scripts manually rather than allowing any agent to execute them autonomously. - Inspect network activity: The code uses AkShare which fetches market data from external providers. If you care about data privacy or want to audit traffic, monitor outbound connections while running the scripts. - Validate models and data: The dataset is small (documented as ~16 trading days / 843 entries in places but other files show different sample counts). Validate feature engineering, cross-validation, and out-of-sample performance yourself before using any suggestions for real trading. - Do not use for real money without verification: Given the mismatched claims and potential overfitting, do not deploy this system for live trading until you (1) reproduce the training/evaluation, (2) verify datasets and metrics, and (3) implement missing components and safety checks. - Ask for provenance: Request the full source, author verification, and a reproducible training log. If the skill author cannot provide missing files or a reasonable explanation for the inconsistencies, avoid using it.

Type: OpenClaw Skill Name: theta-trading-system Version: 1.2.0 The skill bundle presents a trading system making highly unrealistic and potentially fraudulent claims, such as '100% accuracy' and '57% weekly returns,' which are classic indicators of financial scams. While the technical implementation in scripts like `daily_data_update.py` and `train_with_real_data_v2.py` uses legitimate libraries (akshare, scikit-learn) and operates within the expected workspace, the provided `models/results.json` reveals a massive discrepancy: it claims 100% test accuracy despite a negative cross-validation R² score (-1.55), confirming the performance claims are deceptive. No evidence of data exfiltration or backdoors was found, but the bundle is classified as suspicious due to its misleading and predatory nature.