Get the ChemPriceHub app — track prices on the go. Membership syncs across app & web. View plans

Welcome to ChemPriceHub

 
Home > About 

Why

How we collect price data, calculate average prices, and where the numbers come from.

IMPORTANT - All prices are assessments, not transaction records. Public-channel data is filtered and normalized by our analysts, then aggregated into a daily average. Real transaction prices may vary by region, specification, volume and counterparty. Use our numbers as a general market guideline, not as a guarantee of any specific deal.

How it works

ChemPriceHub builds its China chemical price database in three steps, refreshed on a regular cycle. No private bilateral deal data is used - everything comes from public channels.

  • Step 01 Collect Gather verified quotes from public channels
  • Step 02 Normalize Unify currency, unit and specification
  • Step 03 Average Compute the daily assessed market price

Data sources

Price information is gathered from multiple public channels only. We do not rely on private deal data, and no source can pay to be included or excluded. Each source is curated and cross-checked manually:

  • Public exchange & tender platforms Open chemical exchanges, e-tender portals and auction announcements that publish transacted or listed prices.
  • Industry media & reports Public news outlets, trade press and weekly market round-ups covering China chemical trading activity.
  • Listed company disclosures Public filings, investor bulletins and exchange disclosures from listed producers and distributors.
  • Open government data Customs statistics, price indices and macro trade datasets published by public agencies.

Each incoming quote is tagged with product, specification, vendor, currency, unit and date, then sent through verification before entering the database.

Average price calculation

For each product on each day, we take all verified quotes that match the canonical specification, normalize them onto a common currency and unit, remove outliers, and compute the arithmetic mean. This becomes the daily assessed price shown on the chart.

Average Price AvgPrice = mean( normalize(p) for p in quotes if p.spec == base_spec and p.date == day ) Filtered arithmetic mean of normalized quotes matching the canonical spec on a given day.

Normalization

Every quote is converted to a single comparable form before averaging:

Per-quote normalization normalizedPrice = quote.price × fxRate(currency, USD) × unitFactor(unit, MT) Currency converted to USD, unit converted to MT - all quotes on the same scale.

Outlier removal

Quotes more than 3 standard deviations from the daily mean are dropped, so a single mis-typed or off-market print cannot skew the average:

Outlier filter pool = { p quotes : |p mean| 3 × std } 3-sigma band around the daily mean; extreme prints excluded.

Daily change

The day's change shown beside the price is simply the difference against the previous assessment day:

Day's change change = AvgPrice(today) AvgPrice(prevTradingDay)  ·  changePct = change ÷ AvgPrice(prevTradingDay) × 100

Why a simple mean, not weighted

Public-channel quotes rarely carry a reliable transaction volume, so volume-weighting would inject false precision. A filtered arithmetic mean is the most transparent baseline. Our analysts review the output daily and override only when a clear market event (force majeure, plant outage, policy shift) makes the raw average misleading.

Team

ChemPriceHub is built by a small, focused team of chemical industry professionals. Most of us have spent over a decade working directly inside China's chemical sector - from trading floors and procurement to supply chain analytics.

We are not a large organization; we are a group that knows the Chinese chemical market from the ground up, combining real-world trading experience with disciplined data methods. We stay close to the market, so the numbers you see reflect real trading activity, not third-hand estimates.

ChemPriceHub - Deep China chemical expertise. Public data, transparent methodology.