Tonghuashun Hot Rank

Problem

In A-share short-term research, relying only on “a stock is hot” can be misleading: hot-list names may reflect temporary attention rather than durable sector momentum, the stock may already be locked in limit-up, or it may be a resource oligarch rather than a tech oligarch. ths-hot-rank addresses this by connecting public Tonghuashun hot-rank data with sector strength, limit-up structure, oligarch classification, and technical checks, producing a reviewable research workflow rather than direct trade signals.

How It Works

The skill fetches Tonghuashun A-share top-100 hot-rank data, supporting day and hour lists. The workflow has six steps: pull data via scripts, falling back to the public API when needed; group stocks by concept_tag and score sector strength while identifying limit-up effects; filter for upward trends and mark whether limit-ups are sealed; cross hot-list names with the TechOligarch pool while excluding ResourceOligarch and inaccessible sealed limit-ups; call westock-data for MA, KDJ, and RSI validation; then output a Markdown report covering sector strength, confirmed sector effects, sector details, trend candidates, oligarch intersections, and dual-threshold conclusions.

Boundaries

It is useful for intraday screening, post-close review, sector heat attribution, or intersecting a personal watchlist with the hot rank. It depends on Python 3.x; without westock-data, technical deep-dive is skipped, and without ontology, oligarch intersection is skipped. The output is research reference only and is not investment advice; high attention often comes with high volatility, limit-up reversals, and sector decay.