> Source: https://ashareapi.com/en/docs/guides/market-breadth/ · Markdown version for LLMs / AI agents Guide # Read market temperature from advance/decline Market breadth (advancing vs declining) is the most direct way to tell whether "today was a broad rally or a split" — it reflects the true sentiment of the whole market better than a single index. This guide uses a free endpoint, covering how to read temperature, track several days, and spot a turning point. ## 1. Why look at advance/decline (30 seconds) An index (e.g. Shanghai Composite) can be dragged by a few heavyweights; **advance/decline** reflects the whole market: - **Broad rally**: far more advancers than decliners → warm sentiment (good money-making effect) - **Broad selloff**: far more decliners → cold (loss-making effect) - **Split**: roughly even → structural market (picking the right sector matters more than the index) - **Limit-ups**: extreme sentiment — many limit-ups = active themes / euphoric money ## 2. Fetch the data (free endpoint) `/v1/changedist` is a **free endpoint (no Key)**. Returns **two parts**: breadth overview + percentage-change buckets, with `structured` for programmatic use. Python: breadth (structured) ``` import requests r = requests.get("https://api.ashareapi.com/v1/changedist", timeout=30) j = r.json() s = j.get("structured") # for code print(s) # [{"上涨": "3006", "上涨占比": "53%", "下跌": "2303", ...}] # data is Markdown (for humans); structured is a 2D array (for code) tables = j.get("tables") # [overview row, bucket rows...] for t in tables: print(t) ``` - **Free endpoint**: no Key needed - **`structured` is a conditional field** — only attached when data is Markdown (changedist qualifies) - **Use `structured` / `tables` for programmatic work**, do not parse Markdown ## 3. Reading the fields | | | Field | Meaning | Use | | advance/decline | Up/down counts | Quick breadth read | | advance ratio | advance / total | > 60% warm / | | limit-up/down | Extreme sentiment | many limit-ups = active themes (watch for overheating) | | suspended/flat | Non move | small, ignore | | two-market turnover | Liquidity activity | rising on volume = healthy / falling on low volume = weak advance/decline Up/down counts Quick breadth read advance ratio advance / total > 60% warm / limit-up/down Extreme sentiment many limit-ups = active themes (watch for overheating) suspended/flat Non move small, ignore two-market turnover Liquidity activity rising on volume = healthy / falling on low volume = weak **The buckets** (>7% / 7-5% / 5-2% / 2-0% etc.) reveal **strength** — "3000 up" with lots of >5% gains is very different from "3000 up but mostly +1%". ## 4. How to read "market temperature" - **Never judge off one day** — sentiment has inertia; **track several days** to find the turning point - **Overheat**: high ratio + many limit-ups + rising turnover → possible sentiment top (pullback risk next day) - **Freezing**: very low ratio + many limit-downs → often a **sentiment bottom** (bounce probability rises, but combine with other) | | | Advance ratio | Limit-ups | Read | | > 60% | many (≥40) | Warm / euphoric (watch for overheating) | | 50-60% | moderate | Neutral-warm | | 40-50% | few | Neutral-cold | | | very few | Cold / weak | | | near 0 | Freezing (extreme, cautious) > 60% many (≥40) Warm / euphoric (watch for overheating) 50-60% moderate Neutral-warm 40-50% few Neutral-cold < 40% very few Cold / weak < 30% near 0 Freezing (extreme, cautious) ## 5. Live data (2026-09-29) | | | Metric | Value | Read | | Advance / decline | 3006 / 2303 | Broad rally (clear more advancers) | | Advance ratio | 53% | Neutral-warm | | Limit-up / down | 42 / 9 | 40+ limit-ups, some theme activity | | Two-market turnover | ~618bn CNY | (sample; check the day) Advance / decline 3006 / 2303 Broad rally (clear more advancers) Advance ratio 53% Neutral-warm Limit-up / down 42 / 9 40+ limit-ups, some theme activity Two-market turnover ~618bn CNY (sample; check the day) **Read**: 53% ratio + 42 limit-ups = "neutral-warm, some theme heat" — not freezing, not overheated. This **lukewarm** state especially needs the multi-day trend (next section). ## 6. Track several days and spot the turning point Python: log a few days, find the sentiment turn ``` import requests, time def breadth(): j = requests.get("https://api.ashareapi.com/v1/changedist", timeout=30).json() s = j["structured"][0] return int(s.get("上涨", 0)), int(s.get("下跌", 0)), int(s.get("涨停", 0)) # simulate logging (in practice store daily) history = [] for day in range(5): up, down, zt = breadth() history.append((up, down, zt)) time.sleep(1) for i, (up, down, zt) in enumerate(history): ratio = up / (up + down) if (up + down) else 0 print("day%d ratio %.0f%% limit-up %d" % (i + 1, ratio * 100, zt)) ``` - **Trend**: ratio **climbing** → warming; **falling** → cooling - **Spike**: jumps to >70% (with many limit-ups) → watch overheat; drops to - **Discipline**: breadth is a **thermometer** (describes state), not a **predictor** (does not guarantee reversal/continuation). Use it for environment, then set strategy preference (not a direct buy/sell) ## 7. Common misreads (important) - **① Data basis**: `/v1/changedist` is the **current period**. For a historical day use another means (this guide focuses on "today") - **② Index vs breadth**: the index may look fine due to heavyweights while the market is **really split** — breadth exposes that illusion - **③ Many limit-ups ≠ necessarily euphoric**: check **persistence** and **theme concentration** (scattered vs one sector clustering differ) ## FAQ Is this paid? No. changedist is one of the 5 free endpoints (quote / kline / hot / market-overview / changedist), no Key. How do I use structured? structured is conditional — only attached when data is Markdown. changedist qualifies, so use j.get("structured") for the array, or j.get("tables") for all tables (overview + buckets); do not parse Markdown. Can I get a historical day breadth? Currently changedist returns the current period. Historical breadth needs other means; this guide focuses on reading today. What ratio is "overheated"? No absolute threshold. Generally >70% with many limit-ups and rising turnover is euphoric (higher pullback risk next day); Last updated: 2026-09-29 Data from live ashareapi /v1/changedist responses (measured 2026-09-29: advance 3006 / decline 2303 / limit-up 42 / limit-down 9 / advance ratio 53%); fields and structured/tables structure measured live. Related - [Endpoint reference (changedist)](/en/docs/endpoints/changedist) - [Technical indicators from K-line](/en/docs/guides/kline-technical-indicators) - [Factor screening basics (incl. health check)](/en/docs/guides/factor-screening) - [Error codes & rate limits](/en/docs/errors) [← All tutorials](/en/docs/guides)