Generate trading signals using Ichimoku Kinko Hyo, a five-line chart framework. Combine conversion-line and base-line crossovers with price position and cloud direction to classify conditions as long, short, or stand aside using pandas.
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Ichimoku Kinko Hyo five-line system signal engine. A standalone Japanese technical-analysis school that generates trading signals from Tenkan/Kijun crossovers, cloud position, and Chikou confirmation. Pure pandas implementation.
安装前可以查看交给 AI 代理的指令内容。
A standalone Japanese technical analysis framework that uses a five-line system and the cloud to provide a complete trend-evaluation structure:
| Line | Japanese | Calculation | Meaning |
|---|---|---|---|
| Conversion line | Tenkan-sen | (9H+9L)/2 | Short-term trend |
| Base line | Kijun-sen | (26H+26L)/2 | Medium-term trend |
| Leading Span A | Senkou Span A | (Tenkan+Kijun)/2 shifted forward by 26 | Upper cloud boundary |
| Leading Span B | Senkou Span B | (52H+52L)/2 shifted forward by 26 | Lower cloud boundary |
| Lagging Span | Chikou Span | Closing price shifted backward by 26 | Trend confirmation |
Signals are triggered only on TK crossover events, with three filters:
Warm-up requires 78 candles (52+26).
| Parameter | Default | Description |
|---|---|---|
| tenkan_period | 9 | Tenkan-sen period |
| kijun_period | 26 | Kijun-sen period |
| senkou_b_period | 52 | Senkou Span B period |
| displacement | 26 | Forward/backward shift period |
pip install pandas numpy requests
1 = long, -1 = short, 0 = stand aside还没有评价。欢迎分享你的使用感受。
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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.
中文简介正在准备中。当前显示英语简介。