A05 · TOPIC · market-data-qualityGRA dossier · service level R0
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Topic dossier · Capital Markets Nexus

Market data quality

Markets run on data: prices, trade reports, reference data, identifiers and issuer disclosures. When data are late, inconsistent or wrong, prices mislead, supervisors miss build-ups of risk and investors cannot compare issuers. This page sets out how data quality problems arise and travel through reporting chains, how integrity is measured, which standards make records comparable, and who decides on data rules and their enforcement.

01In brief

The short answer.

Market data quality is the accuracy, timeliness and consistency of the prices, trade reports, reference data, identifiers and issuer disclosures markets run on. When data are late, inconsistent or wrong, prices mislead, supervisors miss build-ups of risk and investors cannot compare issuers.

02Geography

Connected activity in East Asia.

For market data quality, in GRA's spatial-finance reading, the map opens on night lights and population density with night lights tonight from NASA GIBS, framed on East Asia; every other NASA layer, live feed and forecast waits in the layer list.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 2

Connected activity, for this page

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

For market data quality, in GRA's spatial-finance reading, the map opens on night lights and population density with night lights tonight from NASA GIBS, framed on East Asia; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA/NOAA VIIRS · CIESIN/Columbia, NASA SEDAC HBASE · GDACSSources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). CC BY 4.0
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Observed (EO): NASA/NOAA VIIRS (Suomi NPP). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • Context: CIESIN/Columbia, NASA SEDAC HBASE. Center for International Earth Science Information Network (CIESIN), Columbia University, and NASA Socioeconomic Data and Applications Center (SEDAC): Global Human Built-up And Settlement Extent (HBASE) 2010; Seto, Guneralp and Hutyra 2012, Global Grid of Probabilities of Urban Expansion to 2030; Global Urban Heat Island (UHI) Data Set, 2013.
  • Live: GDACS (EC JRC / UN OCHA) Events are indicative, not official warnings.
  • Optional layers (35 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
03The question

Market data quality: how the risk develops.

Integrity, disclosures and sources. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Errors propagate downstream

A wrong identifier, a misclassified instrument or a mistimed trade report travels into indices, risk models, regulatory aggregates and research. Each downstream user inherits the error and may compound it with its own transformations.

Mechanism

Fragmentation hides the whole

Trading spread across exchanges, alternative venues and bilateral markets means no single feed shows the full market. Without a consolidated tape or harmonised trade repository data, aggregate exposures and liquidity must be reconstructed from partial views.

Mechanism

Identifiers make records joinable

Legal entity identifiers, ISINs, CFI codes and unique transaction and product identifiers let records from different firms and jurisdictions be matched. Lapsed, missing or inconsistent identifiers break the joins supervisors rely on.

Mechanism

Disclosure quality shapes pricing

Issuers disclose financial and sustainability information under different standards and levels of assurance. Inconsistent, late or unassured disclosure widens information gaps between investors and can raise the cost of capital for the issuers concerned.

04Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

Term Definition
Legal entity identifier A twenty-character code identifying a legal entity in financial transactions, under the GLEIF system.
Consolidated tape A single feed of prices and volumes from all trading venues for an asset class.
Trade repository An entity that collects and keeps records of derivatives transactions for supervisors.
05Indicators

What is measured, and how well.

Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.

Indicator Unit Cadence Source type Label
Legal entity identifiers with lapsed registration status share of issued identifiers monthly GLEIF Global LEI Index OFFICIAL
Trade repository report rejection rate share of submitted reports quarterly Regulator data quality reports OFFICIAL
Derivatives trade pairing and reconciliation rate share of reportable trades quarterly Regulator data quality reports OFFICIAL
Reference data completeness for traded instruments share of instruments with complete mandatory fields monthly Instrument reference data registers ESTIMATED
Late or missing periodic issuer filings count per period quarterly Regulatory filing systems OFFICIAL
Financial statement restatements count per period annual Issuer filings REPORTED
Listed issuers with assured sustainability disclosure share of listed issuers annual Issuer reports and assurance statements REPORTED
06Canvas

From sources to decisions.

The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.

Pipeline canvas · Market data quality as a run graphDesign, not a record
Market data quality: food security early warning to early action Market prices, crop conditions and rainfall feed a seasonal outlook and a food security analysis by area; projected phases are tested against pre-agreed triggers, and early actions are released before the lean season. Design of the process, not a record of a run.

Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.

07Sources

Where the evidence comes from.

Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.

Source What it gives Licence class
GLEIF Global LEI Index Legal entity identifiers with reference data and parent relationships CC0, open data
ESMA Financial Instruments Reference Data System Reference data for instruments admitted to trading on EU venues Free, reuse with attribution under the ESMA legal notice
ANNA Derivatives Service Bureau ISINs, CFI codes and unique product identifiers for OTC derivatives Free access with registration, DSB terms
SEC EDGAR and XBRL financial statement data Issuer filings and structured financial statement data Public domain, US government records
ESMA and national authority reports on reporting data quality Findings on completeness, accuracy and timeliness of EMIR, SFTR and MiFIR reporting Free, reuse with attribution under the ESMA legal notice
Swap data repository public dissemination under CFTC rules Real-time public reports of swap transactions Public access, terms per swap data repository
08Decisions

Who decides, and what the evidence serves.

Capital Markets Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decides The question Evidence this page serves
Securities regulators and ESMA Which reporting fields, validation rules and data quality thresholds to require Published rejection, pairing and completeness measures
The ISSB and jurisdictions adopting its standards Which disclosure requirements to adopt and on what assurance timetable Comparability and assurance evidence across issuers' reports
Issuers' boards and audit committees Whether internal controls over financial and sustainability reporting are adequate Restatement and late filing patterns described as context
GLEIF and the LEI Regulatory Oversight Committee How to improve renewal and coverage of legal entity identifiers Lapse rates and coverage by jurisdiction

Outputs this topic produces

  • Data lineage descriptions for the market data each indicator relies on
  • Guides to identifiers and classifications under ISO 17442, ISO 6166 and ISO 10962
  • Checklists for comparing disclosures prepared under different standards
  • Summaries of reporting data quality findings published by authorities
09Core questions

What data specialists ask.

  • How reliable are the prices, benchmarks and reference data that markets use?
  • How consistent and comparable are issuer disclosures across markets?
  • How concentrated is the supply of market data, indices and analytics?
  • How are errors detected, corrected and communicated?
10Mechanisms

How information fails.

Benchmarks based on submissions rather than transactions proved vulnerable to manipulation, which led to reforms towards transaction-based reference rates. Prices for thinly traded assets may be estimated rather than observed, so valuations can lag reality. Reference data errors, such as wrong identifiers, can propagate through automated systems.

Disclosures vary in scope, timing and definitions across jurisdictions, making comparison hard. A small number of providers supply much of the industry's indices, prices and analytics, so an error or outage at one can affect many users at once.

11Methods and data

Assessing data quality.

  1. 01

    Data lineage

    Tracing where a data point comes from and how it was transformed. Lineage is often undocumented.

  2. 02

    Cross-source comparison

    Comparing prices or reference data across providers to detect anomalies, using econometrics.

  3. 03

    Disclosure comparability review

    Assessing consistency of definitions and scope across issuers and jurisdictions.

  4. 04

    Concentration analysis

    Mapping dependence on key data providers, with network science and contagion.

12Methods

How it is studied, and what the methods cannot say.

  1. EconometricsVolatility and regime models · Event studies · Liquidity measurementApplied here
  2. Payment and financial market technologySettlement cycle analysis · Liquidity simulation for infrastructuresApplied here
  3. Distributed ledgers and digital assetsTokenised settlement design review · Stablecoin reserve and redemption analysisApplied here
  4. Financial economics and macro-financeYield curve and spread decomposition · Leverage and fire-sale channelsApplied here
13Questions

Questions and answers.

What is a legal entity identifier?
A twenty-character code under ISO 17442 that identifies a legal entity in financial transactions. It links to reference data such as legal name, address and, where reported, parent entities, and must be renewed to stay current.
Why does a consolidated tape matter?
It brings trade and quote data from all venues into one feed. Without it, investors and supervisors see the market through partial views, and best execution and liquidity are harder to assess.
Are sustainability disclosures comparable across issuers?
Increasingly, where jurisdictions adopt IFRS S1 and S2 or equivalent standards. Differences in scope, transition reliefs and assurance remain, and the page keeps them visible.
Does this page certify data or disclosures?
No. Auditors, assurance providers and regulators hold those roles. The page describes standards, measures and published findings.
What happened to interbank offered rates?
After manipulation cases, many jurisdictions moved from submission-based rates to reference rates based on actual transactions.
Why does concentration of data providers matter?
Because many firms rely on the same few sources, a single error or outage can spread widely and simultaneously.
Does the platform validate data products?
No. It studies data quality as a sector issue and does not assess or endorse any provider.
How should data errors be corrected?
Promptly, transparently and with a record, so users know what changed and why. The platform applies the same rule to its own outputs.
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