Detect Elliott Wave impulse and ABC completions to output buy and sell signals.
npx skills add https://github.com/wudye/traderAssistHK --skill elliott-wave-wudye
Please help me install this Agent Skill. Skill: elliott-wave Source: https://github.com/wudye/traderAssistHK/tree/main/backend/src/skills/elliott-wave Command: npx skills add https://github.com/wudye/traderAssistHK --skill elliott-wave-wudye
This Skill solves the problem of translating Elliott Wave theory into actionable buy/sell timing signals by identifying swing-point structures and validating impulse (5-wave) and corrective (ABC) patterns automatically.
Provide a map of symbols to OHLCV DataFrames (with high/low columns indexed by datetime) and ask the engine to generate the corresponding signal series.
High-intent search queries and answers about installing and using this skill.
Elliott Wave theory translates into actionable buy and sell timing signals by detecting swing-point structures and validating impulse (5-wave) and corrective (ABC) patterns automatically. It uses Zigzag swing points and Fibonacci ratio tolerances for structured validation.
Zigzag swing detection validates impulse patterns by enforcing the three classic impulse rules alongside Fibonacci ratio constraints on the detected 5-wave advance. This structured validation ensures only theoretically compliant wave completions are recognized.
Yes, you can use this numpy and pandas implementation to detect ABC correction completions by analyzing high and low price series indexed by datetime. It identifies Fibonacci-aligned relationships within the pullback to mark correction-finished reversal opportunities.
The signal output convention for impulse and corrective pattern detection uses integers: 1 for buy, -1 for sell, and 0 to stand aside. These event-like signals are emitted at detected pattern completion points for trend-top and correction-complete decision support.
Elliott Wave pattern matching works for multiple instruments simultaneously by accepting a map of symbols to OHLCV DataFrames. The engine processes each instrument's high and low prices to generate corresponding integer signal series independently.
A limitation of using Fibonacci validation for wave detection is that it relies on strict Fibonacci ratio tolerances and rolling Zigzag swing points. If the OHLCV data lacks clear swing structures, the engine may output zero signals, indicating you should stand aside.
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