Daxiapi A-Share Market Temperature Analysis
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About this skill
Problem
When A-share moves are noisy, a single index level or valuation percentile can easily mistake short-term sentiment for a long-term trend. This skill frames the question as market heat, sentiment extremes, and trend consistency, placing valuation, fear-greed, trend, and momentum in one structured report so strategic and tactical signals are not mixed.
How It Works
It uses data from daxiapi.com and analyzes commands such as market compass, market temp, market style, and market value. The framework separates:
- Long-term valuation: uses valuation temperature for monthly-to-quarterly strategic positioning.
- Short-term sentiment: combines fear-greed, trend temperature, and momentum temperature for weekly tactical timing.
- Cross-checking: trend and momentum signals are stronger when they move in the same direction.
The output typically includes a core conclusion, valuation positioning, sentiment indicators, large/small-cap style, scenario judgment, risk notes, and disclaimers. A value of 0 is treated as possibly stale rather than extreme fear.
Boundaries
It is intended for broad A-share market heat, valuation percentile, sentiment inflection, and medium-to-short-term trend strength. It is not for individual stock entry/exit, earnings interpretation, sector analysis, real-time intraday signals, or automated trading. Users should consider data refresh timing, non-trading-day delays, indicator lag, and API errors such as 401 or 429; treat outputs as scenario-based references, not definitive predictions.
Use Cases
- Produce a weekly A-share market note covering valuation, fear-greed, trend, and momentum.
- Check tactical position at month-end by seeing whether fear-greed is oversold or extreme.
- Compare large-cap versus small-cap style and key index valuations using market compass data.
- Cross-check trend and momentum indicators to validate a short-term trading signal.
Best For
- Quant researcher writing A-share strategy notes and consolidating market temperature signals.
- Portfolio manager checking valuation extremes before monthly rebalancing.
- Finance editor drafting market briefs with citable valuation and fear-greed data.
- Agent engineer integrating CLI market data and generating standardized reports.
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