88 A-Share Swing Trend Model
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About this skill
Problem
Generic indicators often copy the same template across names and miss market sentiment, trend, and position controls. The 88 swing model turns A-share swing decisions into a repeatable workflow: score market heat, verify the monthly trend, then extract buy and sell rules from no more than 8 recent historical swings of the same instrument.
How It Works
- Sentiment scoring: combines market width, volume trend, 20-day highs/lows, up/down counts, and limit-up/limit-down pressure into a
0-100score with position constraints. - Trend filters: requires an ascending monthly line and prioritizes high-heat sectors before analyzing individual swing signals.
- Swing recognition: uses entry
5%, exit3%, minimum3days, and1day cooldown to generateC1-C5andS1-S5position tiers. - Engine-driven output: sentiment engine, analysis engine, and reporter keep scoring and reporting consistent.
Boundaries
This is best for A-shares or ETFs with complete data and identifiable swings, not a universal template or profit guarantee. The 8% stop-loss and monthly-turn clearing rule are hard constraints; when data is missing, monthly trend falls, or swing count is low, the model should degrade or stay passive.
Use Cases
- An A-share analyst needs to check monthly trend eligibility and output C1-C5 position suggestions.
- A strategy operator screens the top five sectors by 20-day, 60-day, and 5-day momentum.
- A quant engineer calculates market width, volume trend, and up/down counts to derive position limits.
- A research editor renders sentiment tiers, buy/sell axes, and error cards into fixed-layout reports.
Best For
- A-share strategy researchers who want to convert historical swings into auditable trade signals.
- Quant analysts who need stable sentiment scores and position caps without ad-hoc formulas.
- Sector strategy operators who filter the top five trackable sectors from multi-period momentum.
- Research report editors who render trend, sentiment, and axes into fixed-format cards.
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