Generate trading signals using Smart Money Concepts, a framework for interpreting institutional trading behavior. Analyze trend continuation, reversals, price gaps, and order concentration zones, then combine structural signals and gaps to determine a trading direction.
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Smart Money Concepts (ICT) signal engine. Uses the smartmoneyconcepts library to implement institutional-trading-school analysis of BOS, ChoCH, FVG, and order blocks (OB).
安装前可以查看交给 AI 代理的指令内容。
The modern institutional trading school (ICT / Inner Circle Trader), built around the core idea of tracking the behavior of "smart money" (institutional capital):
| Concept | English | Meaning |
|---|---|---|
| Break of structure | BOS (Break of Structure) | Trend continuation signal |
| Change of character | ChoCH (Change of Character) | Trend reversal signal |
| Fair value gap | FVG (Fair Value Gap) | Price refill target |
| Order blocks | Order Blocks | Institutional order concentration zones |
| Liquidity | Liquidity | Stop-hunt target zones |
Direction from ChoCH + confirmation from BOS + filtering by FVG:
pip install "vibe-trading-ai[smc]"
| Parameter | Default | Description |
|---|---|---|
| swing_length | 10 | Window for swing high/low detection |
| close_break | True | Whether BOS/ChoCH requires a closing-price break |
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Compare a Chinese company's US depositary receipts, Hong Kong shares, and mainland shares after adjusting for exchange rates and share ratios. Analyze pricing gaps, valuation differences, and delisting risks to support research into its different listings.
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Retrieve stock prices, futures quotes, exchange rates, and economic indicators with the free Python library AKShare. The skill explains market-specific functions, symbol formats, and data preparation for analysis and testing strategies against historical data.
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Explore bundled libraries of investment factors, signals used to compare securities, and inspect individual formulas and metadata. Evaluate a factor or an entire library across a chosen universe and period, producing aggregate performance statistics and an HTML report.
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Assess whether a Chinese A-share company may receive ST or *ST risk warnings next financial year. Review financial forecasts, dividends, audit opinions, and regulatory penalties, then report risk severity separately from confidence in the prediction.
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Plan portfolio allocations across assets using risk, correlations, return forecasts, and trading costs. Compare five optimization methods, produce settings for config.json, and define rebalancing rules that adjust holdings back toward their target weights.
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Diagnose failed or abnormal backtests, which test trading strategies on historical data. Inspect result files, strategy code, and configuration to identify bugs, make targeted repairs, rerun tests, and verify the updated metrics.
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