Market Manipulation. Search

Enforcement data

These 8 charts are computed from this site's own library of 3272 market manipulation enforcement actions, rebuilt on every deployment. Each has a stated methodology, an explicit list of what it does not show, and a downloadable CSV that is free to reuse with attribution.

A standing caveat that applies to every chart here. Enforcement data measures enforcement, not conduct. It records manipulation that was detected, charged and announced — which is a different population from manipulation that occurred, in ways that are unknown and unknowable from this data alone. Nothing on these pages should be read as a measure of how much market manipulation there is.

Enforcement actions per year, by agency

This library holds 3272 manipulation enforcement actions across 7 agencies. 2026 carries 137 actions against 199 in 2025, but the most recent year is always incomplete and year-on-year comparisons are dominated by the timing of large multi-defendant sweeps rather than by any underlying trend.

Market manipulation enforcement actions per year, by agencyA stacked column chart of enforcement actions per year from 2004 to 2026, with each column divided by the agency that brought the action. Agencies are distinguished by ink density rather than by colour, in the order SEC, CFTC, ASIC, AMF-FR, SEBI, FCA. 0 125 250 375 500200420062008201020122014201620182020202220242026Actions filed2004 - SEC: 22004 - AMF-FR: 32005 - SEC: 12005 - AMF-FR: 82006 - AMF-FR: 92007 - SEC: 12007 - AMF-FR: 142008 - AMF-FR: 172009 - SEC: 12009 - AMF-FR: 132010 - AMF-FR: 142011 - SEC: 42011 - AMF-FR: 122012 - SEC: 12012 - AMF-FR: 72013 - SEC: 582013 - CFTC: 292013 - AMF-FR: 102013 - FCA: 52014 - SEC: 912014 - CFTC: 262014 - ASIC: 62014 - AMF-FR: 92014 - FCA: 92015 - SEC: 1692015 - CFTC: 222015 - ASIC: 92015 - AMF-FR: 92015 - FCA: 62016 - SEC: 1602016 - CFTC: 212016 - ASIC: 72016 - AMF-FR: 62016 - FCA: 42017 - SEC: 1772017 - CFTC: 192017 - ASIC: 102017 - AMF-FR: 122017 - FCA: 12018 - SEC: 1702018 - CFTC: 402018 - ASIC: 82018 - AMF-FR: 132018 - FCA: 52019 - SEC: 1452019 - CFTC: 362019 - ASIC: 52019 - AMF-FR: 102019 - FCA: 12020 - SEC: 1342020 - CFTC: 322020 - ASIC: 92020 - AMF-FR: 52020 - FCA: 62021 - SEC: 1102021 - CFTC: 262021 - ASIC: 122021 - AMF-FR: 82021 - FCA: 22022 - SEC: 1362022 - CFTC: 242022 - ASIC: 112022 - AMF-FR: 42022 - SEBI: 3122022 - FCA: 22023 - SEC: 1602023 - CFTC: 242023 - ASIC: 132023 - AMF-FR: 62023 - SEBI: 1532023 - FCA: 12024 - SEC: 1572024 - CFTC: 222024 - ASIC: 92024 - AMF-FR: 92024 - SEBI: 682024 - FCA: 12025 - SEC: 942025 - CFTC: 42025 - ASIC: 102025 - AMF-FR: 102025 - SEBI: 752025 - FCA: 32026 - SEC: 732026 - CFTC: 92026 - ASIC: 42026 - AMF-FR: 12026 - SEBI: 482026 - FCA: 2SECCFTCASICAMF-FRSEBIFCA

Methodology and caveats · CSV

Monetary relief ordered per year

Aggregate relief is dominated by a small number of very large settlements: in most years, the single largest action accounts for a substantial share of the annual total, which is why the median penalty on each technique page is a better guide to a typical outcome than any yearly total.

Civil penalties and disgorgement ordered per yearA stacked column chart of monetary relief per year, separating civil penalties from disgorgement. Penalties are punitive; disgorgement returns gains. They are shown separately because adding them together and calling the result a fine double-counts the harm. $0 $1.9bn $3.8bn $5.6bn $7.5bn200420062008201020122014201620182020202220242026USD ordered2004 - Disgorgement: $17k2005 - Civil penalty: $110k2005 - Disgorgement: $318k2009 - Disgorgement: $2m2011 - Disgorgement: $259k2013 - Civil penalty: $1.1bn2013 - Disgorgement: $47m2014 - Civil penalty: $1.7bn2014 - Disgorgement: $35m2015 - Civil penalty: $1.7bn2015 - Disgorgement: $1bn2016 - Civil penalty: $680m2016 - Disgorgement: $367m2017 - Civil penalty: $422m2017 - Disgorgement: $289m2018 - Civil penalty: $978m2018 - Disgorgement: $257m2019 - Civil penalty: $990m2019 - Disgorgement: $294m2020 - Civil penalty: $912m2020 - Disgorgement: $839m2021 - Civil penalty: $304m2021 - Disgorgement: $223m2022 - Civil penalty: $1bn2022 - Disgorgement: $741m2023 - Civil penalty: $419m2023 - Disgorgement: $405m2024 - Civil penalty: $442m2024 - Disgorgement: $450m2025 - Civil penalty: $6bn2025 - Disgorgement: $189m2026 - Civil penalty: $45m2026 - Disgorgement: $30mCivil penaltyDisgorgement

Methodology and caveats · CSV

Penalty distribution by technique

Penalty distributions within every technique are heavily right-skewed: the median is far below the mean, and outliers extend well beyond the upper whisker. Any single "typical penalty" figure for a technique is misleading, which is why this site reports medians alongside the spread.

Distribution of civil penalties by manipulation techniqueA horizontal box plot for 11 techniques on a logarithmic scale, because penalties span six orders of magnitude. Each row shows the interquartile range as a box, the median as a vertical line, whiskers to the furthest values within 1.5 times the interquartile range, and individual outliers as points. Sample size is printed beneath each label.Civil penalty (USD), logarithmic scale $1k $10k $100k $1m $10m $100m $1bn $10bnLogarithmic scale: each gridline is ten times the previous one.Price manipulation n=56 Price manipulation median: $12m$325m$400m$436m$475m$475m$800m$866m$1.5bnPonzi schemes n=165 Ponzi schemes median: $1m$12m$12m$13m$15m$16m$18m$19m$19m$23m$25m$27m$32m$40m$76m$81m$100m$111m$429m$5.9bnWash trading n=32 Wash trading median: $735k$35m$325mSpoofing n=71 Spoofing median: $700k$7m$12m$15m$23m$24m$25m$25m$26m$26m$30m$45m$109m$436mBoiler rooms n=25 Boiler rooms median: $700k$11m$26m$26m$28mPump and dump n=49 Pump and dump median: $307k$2m$3m$3m$5m$23m$26mMatched orders n=23 Matched orders median: $250k$3mUnregistered distributions n=91 Unregistered distributions median: $173k$2m$2m$5m$7m$8m$10m$19m$23m$24m$37mUndisclosed control blocks n=41 Undisclosed control blocks median: $150k$1m$2m$3m$8m$23mRule 105 offering shorts n=79 Rule 105 offering shorts median: $107k$680k$707k$805k$810k$812k$905k$1m$3m$4mInsider trading n=345 Insider trading median: $89k$776k$812k$834k$834k$893k$910k$924k$925k$936k$1m$1m$1m$1m$1m$1m$1m$1m$1m$1m$2m$2m$2m$2m$2m$2m$2m$2m$2m$2m$2m$3m$3m$3m$3m$4m$5m$5m$5m$5m$5m

Methodology and caveats · CSV

Criminal parallel share by technique

The likelihood that a manipulation action runs alongside a criminal prosecution varies sharply by technique. Schemes with identifiable individual victims and clear documentary evidence attract criminal attention far more often than order-book conduct, where intent must be inferred from data.

Share of actions with a parallel criminal proceeding, by techniqueA horizontal bar chart showing, for each manipulation technique, the percentage of enforcement actions in this library whose release references a parallel criminal matter. Sample size is given in each label.Share of actions referencing a criminal parallel (%)Ponzi schemes (n=474) Ponzi schemes (n=474): 49% 49%Boiler rooms (n=68) Boiler rooms (n=68): 46% 46%Pump and dump (n=139) Pump and dump (n=139): 42% 42%Insider trading (n=851) Insider trading (n=851): 29% 29%Undisclosed control blocks (n=93) Undisclosed control blocks (n=93): 23% 23%Price manipulation (n=311) Price manipulation (n=311): 19% 19%Spoofing (n=108) Spoofing (n=108): 19% 19%Unregistered distributions (n=157) Unregistered distributions (n=157): 18% 18%Paid stock promotion (n=68) Paid stock promotion (n=68): 18% 18%Matched orders (n=165) Matched orders (n=165): 11% 11%Wash trading (n=106) Wash trading (n=106): 9% 9%Front running (n=61) Front running (n=61): 3% 3%Misleading issuer disclosure (n=214) Misleading issuer disclosure (n=214): 1% 1%Rule 105 offering shorts (n=85) Rule 105 offering shorts (n=85): 0% 0%

Methodology and caveats · CSV

Asset-class mix over time

Equities remain the largest single category in every year of this data, but the share of actions touching digital assets has grown from negligible to a substantial minority, and a growing number of actions are tagged with more than one asset class.

Enforcement actions by asset class, per yearA line chart with one line per asset class, showing the number of enforcement actions per year touching each. Lines are distinguished by ink density rather than colour. Actions touching several asset classes are counted in each. 0 100 200 300 400200420062008201020122014201620182020202220242026Actions2004 - equities: 52005 - equities: 92006 - equities: 92007 - equities: 142008 - equities: 172009 - equities: 142010 - equities: 142011 - equities: 132012 - equities: 82013 - equities: 642014 - equities: 872015 - equities: 972016 - equities: 1042017 - equities: 1202018 - equities: 1062019 - equities: 772020 - equities: 652021 - equities: 552022 - equities: 3572023 - equities: 2132024 - equities: 1432025 - equities: 1192026 - equities: 692004 - futures: 02005 - futures: 02006 - futures: 02007 - futures: 02008 - futures: 02009 - futures: 02010 - futures: 02011 - futures: 02012 - futures: 02013 - futures: 142014 - futures: 112015 - futures: 122016 - futures: 162017 - futures: 142018 - futures: 282019 - futures: 192020 - futures: 222021 - futures: 92022 - futures: 112023 - futures: 142024 - futures: 112025 - futures: 32026 - futures: 22004 - crypto: 02005 - crypto: 02006 - crypto: 02007 - crypto: 02008 - crypto: 02009 - crypto: 02010 - crypto: 02011 - crypto: 02012 - crypto: 02013 - crypto: 02014 - crypto: 12015 - crypto: 22016 - crypto: 02017 - crypto: 32018 - crypto: 122019 - crypto: 72020 - crypto: 112021 - crypto: 142022 - crypto: 172023 - crypto: 262024 - crypto: 122025 - crypto: 62026 - crypto: 22004 - fx: 02005 - fx: 02006 - fx: 02007 - fx: 02008 - fx: 02009 - fx: 02010 - fx: 02011 - fx: 02012 - fx: 02013 - fx: 32014 - fx: 82015 - fx: 62016 - fx: 32017 - fx: 52018 - fx: 02019 - fx: 72020 - fx: 42021 - fx: 22022 - fx: 52023 - fx: 42024 - fx: 52025 - fx: 12026 - fx: 02004 - commodities: 02005 - commodities: 02006 - commodities: 02007 - commodities: 02008 - commodities: 02009 - commodities: 12010 - commodities: 02011 - commodities: 02012 - commodities: 02013 - commodities: 62014 - commodities: 62015 - commodities: 92016 - commodities: 32017 - commodities: 62018 - commodities: 152019 - commodities: 182020 - commodities: 142021 - commodities: 72022 - commodities: 42023 - commodities: 72024 - commodities: 52025 - commodities: 22026 - commodities: 1equitiesfuturescryptofxcommodities

Methodology and caveats · CSV

Months from filing to recorded resolution

Most actions in this library are recorded as resolved on the same date they are announced, because regulators frequently publish settled matters as a single release rather than filing and settling separately. The distribution therefore describes announcement practice as much as litigation duration.

Median months from recorded filing to recorded resolution, by yearA line chart of the median number of months between the filing date and the resolution date recorded for actions in each year. Values near zero indicate that the action was announced already settled. 0 0.25 0.5 0.75 1200420062008201020122014201620182020202220242026Months2004 - Median months: 02005 - Median months: 02006 - Median months: 02007 - Median months: 02008 - Median months: 02009 - Median months: 02010 - Median months: 02011 - Median months: 02012 - Median months: 02013 - Median months: 02014 - Median months: 02015 - Median months: 02016 - Median months: 02017 - Median months: 02018 - Median months: 02019 - Median months: 02020 - Median months: 02021 - Median months: 02022 - Median months: 02023 - Median months: 02024 - Median months: 02025 - Median months: 02026 - Median months: 0

Methodology and caveats · CSV

SEC trading suspensions per month

Trading suspensions arrive in clusters rather than at a steady rate, because the Commission frequently suspends a batch of related issuers at once. A suspension is a protective measure and alleges no wrongdoing by anyone.

SEC trading suspensions per monthA column chart of the number of Exchange Act section 12(k) trading suspensions ordered in each of the last 48 months for which we hold data. Suspensions are frequently issued in batches, producing an uneven distribution. 0 10 20 30 402018-112019-032019-062019-092020-012020-042020-072020-102021-012021-042021-072021-112023-052024-092025-102026-01Suspensions ordered2018-11 - Suspensions: 12018-12 - Suspensions: 22019-02 - Suspensions: 12019-03 - Suspensions: 12019-04 - Suspensions: 12019-05 - Suspensions: 22019-06 - Suspensions: 82019-07 - Suspensions: 172019-08 - Suspensions: 202019-09 - Suspensions: 272019-10 - Suspensions: 22019-11 - Suspensions: 22020-01 - Suspensions: 132020-02 - Suspensions: 32020-03 - Suspensions: 62020-04 - Suspensions: 232020-05 - Suspensions: 82020-06 - Suspensions: 52020-07 - Suspensions: 132020-08 - Suspensions: 132020-09 - Suspensions: 262020-10 - Suspensions: 12020-11 - Suspensions: 12020-12 - Suspensions: 12021-01 - Suspensions: 12021-02 - Suspensions: 112021-03 - Suspensions: 62021-04 - Suspensions: 32021-05 - Suspensions: 352021-06 - Suspensions: 12021-07 - Suspensions: 32021-08 - Suspensions: 172021-09 - Suspensions: 242021-11 - Suspensions: 12022-06 - Suspensions: 12022-07 - Suspensions: 12023-05 - Suspensions: 12023-09 - Suspensions: 12023-11 - Suspensions: 22024-09 - Suspensions: 12024-10 - Suspensions: 12025-09 - Suspensions: 22025-10 - Suspensions: 72025-11 - Suspensions: 22025-12 - Suspensions: 12026-01 - Suspensions: 12026-02 - Suspensions: 12026-06 - Suspensions: 1

Methodology and caveats · CSV

Venues named most often in manipulation actions

Venue counts measure where enforcement activity is concentrated and where regulators have surveillance reach, not which venues have the most manipulation. A venue that runs good surveillance and refers cases will appear more often, not less.

Trading venues named most often in manipulation enforcement actionsA horizontal bar chart of the trading venues mentioned most frequently across the enforcement actions in this library, ranked by the number of actions naming each.Actions naming this venueBSE BSE: 468 468NSE NSE: 296 296Nasdaq Nasdaq: 145 145Euronext Paris Euronext Paris: 129 129OTC OTC: 109 109NYSE NYSE: 105 105CME CME: 89 89CBOT CBOT: 27 27NYMEX NYMEX: 22 22COMEX COMEX: 20 20ICE ICE: 17 17BSE SME BSE SME: 12 12

Methodology and caveats · CSV

The underlying data

Every chart above is derived from the same source: 3,272 structured enforcement records, each linked to the regulator's own release. The whole library is downloadable as a single JSON file, and the methodology behind its compilation is described on the sources page.