Data hub: every figure on this site, with its source and date
Every number used anywhere on this site appears below with its value, unit, primary source, document identifier, publication date and freshness status. Nothing is averaged and nothing is estimated. Where two credible sources disagree, both appear as separate rows. Where we looked for a source and could not find one, the row says so. The table is the site's working method made visible: if a claim on any page cannot be traced from here, it should not be on that page.
Published 27 August 2026 · Updated 28 August 2026 · AI Trading Book Editorial
- Current — the latest published version of the source that we could locate.
- Historical — describes a specific past period and will not be superseded.
- Verify before use — changes frequently. Vendor pricing and tier limits in particular.
- Proposal — published but not in force. Consultations and draft rules.
- Data not found — we searched for a primary source and did not locate one.
Regulation
| Fact | Value | Source | Date | Status |
|---|---|---|---|---|
| FCA position on AI-specific rules | No extra AI regulation planned | FCA AI approach page | upd. 13 Feb 2026 | Current |
| UK algorithmic trading regime | MAR 7A + onshored RTS 6 | FCA Handbook | In force | Current |
| RTS 6 conformance testing | Article 6 | Onshored RTS 6 | In force | Current |
| RTS 6 annual self-assessment | Article 9 | Onshored RTS 6 | In force | Current |
| RTS 6 stress testing | Article 10 | Onshored RTS 6 | In force | Current |
| RTS 6 kill functionality | Article 12 | Onshored RTS 6 | In force | Current |
| FCA algorithmic controls review | 10 firms; adequate pre-trade controls, weak understanding of third-party algorithms | FCA multi-firm review | 21 Aug 2025 | Historical |
| UK retail CFD rules | In force | FCA PS19/18; COBS 22.5 | 1 Aug 2019 | Current |
| FCA AI Lab announced | — | FCA | 9 Jun 2025 | Historical |
| FCA AI Lab testing began | — | FCA | Oct 2025 | Historical |
| FCA AI Lab showcase | — | FCA | 28–29 Jan 2026 | Historical |
| FCA AI Lab second cohort | — | FCA | from late Apr 2026 | Current |
| ASIC AI use-case review | 624 use cases / 23 licensees; 61% planning growth; 92% of genAI cases 2022–23 | ASIC REP 798 | 29 Oct 2024 | Historical |
| ASIC algorithmic rules modernisation | Trading Algorithm definition; immediate-suspension controls | ASIC CP 386 | 27 Aug 2025 | Proposal |
| CP 386 submissions lodged | — | Law Council of Australia; AFMA | Oct 2025 | Historical |
| AU product intervention order in effect | — | ASIC 20-254MR | from 29 Mar 2021 | Current |
| AU order extended to | 23 May 2027 | ASIC 22-082MR | 2022 | Current |
| AU leverage cap — major FX | 30:1 | ASIC product intervention order | 29 Mar 2021 | Current |
| AU leverage cap — minor FX, gold, major indices | 20:1 | ASIC product intervention order | 29 Mar 2021 | Current |
| AU leverage cap — other commodities | 10:1 | ASIC product intervention order | 29 Mar 2021 | Current |
| AU leverage cap — crypto CFDs | 2:1 | ASIC product intervention order | 29 Mar 2021 | Current |
| AU margin close-out | 50% of initial margin | ASIC product intervention order | 29 Mar 2021 | Current |
| AU binary options ban | Retail clients | ASIC product intervention order | from 3 May 2021 | Current |
| AU algorithmic share — listed equities | approximately 85% | ASIC, with CP 386 | 27 Aug 2025 | Current |
| AU algorithmic share — SPI 200 futures | approximately 94% | ASIC, with CP 386 | 27 Aug 2025 | Current |
| AU algorithmic share — 3-year bond futures | approximately 46% | ASIC, with CP 386 | 27 Aug 2025 | Current |
| NZ advice licensing | FAP licence + dispute resolution scheme | FMA licensing pages | upd. 1 Jul 2026 | Current |
| NZ discretionary management | DIMS, licensed separately | Financial Markets Conduct Act 2013 | In force | Current |
| NZ robo-advice exemption | Granted 2018, amended 2020; superseded by FSLAA regime | FMA | 2018 / 2020 | Historical |
| NZX Participant Rules edition | — | NZX | 19 Feb 2026 | Current |
| NZX procedures | — | NZX | 17 Nov 2025 | Current |
| NZ retail leverage cap | — | — | — | Data not found |
| IOSCO report on AI in capital markets | IOSCOPD788 | IOSCO | 12 Mar 2025 | Current |
| IOSCO agentic AI report | IOSCOPD823 (FR/02/2026) | IOSCO | May 2026 | Current |
| EU AI Act | Regulation (EU) 2024/1689 | EUR-Lex | in force 1 Aug 2024 | Current |
Retail losses and consumer harm
| Fact | Value | Source | Date | Status |
|---|---|---|---|---|
| AU retail CFD investors losing money, FY2024 | 68% | ASIC REP 828 | 20 Jan 2026 | Current |
| UK CFD customers losing money | approximately 80% | FCA | — | Current |
| UK loss-making accounts, sampled | 82% | FCA CP16/40 sample | — | Historical |
| IG retail loss disclosure | 70% | IG, under COBS 22.5 | — | Verify before use |
| Interactive Brokers UK loss disclosure | 69% | IBKR UK, under COBS 22.5 | — | Verify before use |
| NZ retail loss rate | — | — | — | Data not found |
| Reduction in aggregate AU retail net loss after intervention | 91% | ASIC REP 724 | — | Historical |
| Reduction in loss-making AU accounts per quarter | 51% | ASIC REP 724 | — | Historical |
| Scam websites removed, 2025 | 11,964 | ASIC 26-063MR | 8 Apr 2026 | Current |
| Scam websites removed, prior 12 months | 6,270 | ASIC 26-063MR | 8 Apr 2026 | Historical |
| Year-on-year increase in takedowns | 90% | ASIC 26-063MR | 8 Apr 2026 | Current |
| Social media scam advertisements removed | more than 1,100 | ASIC 26-063MR | 8 Apr 2026 | Current |
| Scam sites removed since 2023 | more than 25,000 | ASIC 26-063MR | 8 Apr 2026 | Current |
| Fabricated brand advertised returns | 85% and 374% ("Deep Blue") | ASIC 26-063MR | 8 Apr 2026 | Current |
| Fabricated brand named | "Quantum AI" | ASIC 24-180MR | — | Historical |
| Celebrity-impersonation scam losses | AUD 7.4m | ASIC 26-195MR | 17 Aug 2026 | Current |
| Scams removed, celebrity-impersonation action | more than 19,400 | ASIC 26-195MR | 17 Aug 2026 | Current |
| Total AU reported scam losses, 2025 | AUD 2.18bn | National Anti-Scam Centre | 2025 | Current |
| AU investment scam losses, 2025 | AUD 837.7m | National Anti-Scam Centre | 2025 | Current |
| Total AU reported scam losses, 2024 | AUD 2.03bn (−25.9%) | National Anti-Scam Centre | 2024 | Historical |
| AI-branded share of investment scam losses | — | — | — | Data not found |
Performance, accuracy and adoption
| Fact | Value | Source | Date | Status |
|---|---|---|---|---|
| AI hedge fund index annualised return | 9.8% vs 13.7% S&P 500 | Eurekahedge AI Hedge Fund Index | Dec 2009 – Jul 2024 | Historical |
| Cumulative return comparison | 115% vs 210% S&P and 133% MSCI World | Eurekahedge | Jan 2011 – Jan 2020 | Historical |
| Worst month since 2010 launch | −3.38% vs −1.11% | Eurekahedge | Jan 2022 | Historical |
| Review of ML equity experiments | 27 experiments; no conclusive evidence of returns at scale | Buczynski, Cuzzolin & Sahakian, Int. J. Data Science & Analytics 11(3) | Apr 2021 | Current |
| Recommended t-statistic threshold | above 3.0 | Harvey, Liu & Zhu, Review of Financial Studies 29(1) | Jan 2016 | Current |
| Deflated Sharpe Ratio | Adjusts for trials, track length, non-normality | Bailey & López de Prado | 2014 | Current |
| Probability of Backtest Overfitting | Method | Bailey & López de Prado | — | Current |
| Assessment of published backtests | A large proportion may be misleading | Bailey, Borwein, López de Prado & Zhu, Notices of the AMS | 2014 | Current |
| Directional accuracy anchor | 58.07% | Yu & Yan | — | Historical |
| Directional accuracy anchor | 64.21% | Ding et al. | — | Historical |
| Transformer directional accuracy | approximately 69.1% | ScienceDirect study | 2025 | Historical |
| Deep learning vs linear, high-frequency | 65–75% vs 57–67%, 500 NASDAQ stocks | Sirignano & Cont, Quantitative Finance | 2019 | Historical |
| Source of 80–90%+ accuracy claims | Look-ahead bias from shuffled splits | arXiv 2407.09831 (preprint) | — | Current |
| UK firms using AI | 75% of 118 surveyed | Bank of England & FCA | 21 Nov 2024 | Current |
| Planning adoption within 3 years | 10% | Bank of England & FCA | 21 Nov 2024 | Current |
| Use cases with automated decisioning | 55% | Bank of England & FCA | 21 Nov 2024 | Current |
| Use cases fully autonomous | 2% | Bank of England & FCA | 21 Nov 2024 | Current |
| Use cases implemented by third parties | 33% | Bank of England & FCA | 21 Nov 2024 | Current |
| Firms using foundation models | 17% | Bank of England & FCA | 21 Nov 2024 | Current |
| Firms with an accountable person for AI | 84% | Bank of England & FCA | 21 Nov 2024 | Current |
| Complete / partial understanding of AI used | 34% / 46% | Bank of England & FCA | 21 Nov 2024 | Current |
| Leading use cases | Process 41%, cyber 37%, fraud 33% | Bank of England & FCA | 21 Nov 2024 | Current |
| Use-case materiality | 62% low / 22% medium / 16% high | Bank of England & FCA | 21 Nov 2024 | Current |
| Provider concentration, top three | Cloud 73%, model 44%, data 33% | Bank of England & FCA | 21 Nov 2024 | Current |
| Systemic risk observation | Correlated positions amplify shocks | Bank of England, Financial Stability in Focus | 9 Apr 2025 | Current |
| IOSCO use-case survey | Client communications 66.7%, algorithmic trading 63.3%, robo-advising 60%, surveillance 53.3%, productivity 50% | IOSCO | 2024 | Historical |
| Algorithmic share, developed equity markets | 60–75%; plateau 70–80% | Select USA | — | Current |
| US algorithmic share, historical | ~15% (2003) → over 70% (2010) | Select USA | — | Historical |
| FX orders algorithmic | ~25% (2006) → ~80% (2016) | — | — | Historical |
| HFT share of US equity | 50–55% | SEC | 2023 | Historical |
| Regulator assessment of AI tool profitability | — | — | — | Data not found |
Market size estimates
Eight estimates spanning roughly 22 times. Published in full because the spread is definitional rather than statistical — the reasoning is on the market size page.
| Firm | Base | Forecast | CAGR | Status |
|---|---|---|---|---|
| Fortune Business Insights | USD 2.53bn (2025) | USD 4.33bn (2034) | 6.0% | Verify before use |
| Coherent Market Insights | USD 3.59bn (2026) | USD 6.68bn (2033) | 9.3% | Verify before use |
| Dataintelo | USD 4.2bn | USD 9.8bn | 9.8% | Verify before use |
| IMARC Group | USD 18.8bn | USD 43.2bn | 9.39% | Verify before use |
| ReAnIn | USD 20.58bn | USD 43.27bn (2032) | 11.2% | Verify before use |
| Grand View Research | USD 21.06bn (2024) | USD 42.99bn (2030) | 12.9% | Verify before use |
| Straits Research | USD 57.65bn | USD 150.36bn (2033) | 12.73% | Verify before use |
| Technavio | — | Growth of USD 23.94bn (2025–30) | 16.7% | Verify before use |
| Official statistical series | — | — | — | Data not found |
Platform pricing
All captured from vendor pages in August 2026. Every row is verify before use — tariffs, tier limits and promotional pricing change often, and a stale price is worse than no price.
| Platform | Pricing (USD) | Notable limits | Status |
|---|---|---|---|
| TradingView | 0 / 12.95 / 29.95 / 59.95 / 199.95 per month, annual billing | Charts per tab 2/4/8/16; indicators 5/10/25/50; alerts 20/100/400/1000 | Verify before use |
| TrendSpider | 14-day trial 19–49; then 52.38 / 56.42 / 73.20 / 128.40 promotional | Workspaces 5/10/15/20; bots 5/10/50/100; add-ons for futures data and backtest depth | Verify before use |
| Trade Ideas | Basic 89/mo or 1,068/yr; Premium 178/mo or 2,136/yr | Charts 10/20 | Verify before use |
| Cryptohopper | 0 / 29 / 69 / 129 | Positions 80/80/200/500; coins 15/15/50/75; page changed 26 Jun 2026 | Verify before use |
| 3Commas | Page shows 15/20, 38/50, 105/140 without a stated billing period | DCA·signal·grid bots 5·2·2 / 20·20·10 / 1000·1000·1000 | Verify before use |
| Pionex | No subscription; spot maker/taker 0.050%/0.050% | Withdrawal tiers by KYC: 0 / 20,000 / 1,000,000 USDT | Verify before use |
| QuantConnect | Free research tier; live from approximately 60/mo; datasets 5–350+/mo | LEAN open source; Python 3.11 / C#; 20+ brokers | Verify before use |
| Interactive Brokers API | — | Web / FIX / TWS; 170 markets in 40 countries (vendor statement) | Verify before use |
| Capitalise.ai | Free for eligible IBKR clients | — | Verify before use |
| Alpaca | Commission-free US equities and options | FINRA broker-dealer since 2018; 30+ countries | Verify before use |
| Composer | — | SEC-registered; pricing not captured | Data not found |
Documented incidents
| Incident | Detail | Date | Status |
|---|---|---|---|
| Knight Capital | approximately USD 440m lost in about 45 minutes; 4,026,087 executions across 154 securities; approximately 397m shares; shares −75% in two days; SEC penalty USD 12m under the Market Access Rule | 1 Aug 2012 | Historical |
| Flash Crash | Joint CFTC/SEC report | event 6 May 2010; report 30 Sep 2010 | Historical |
| 3Commas — first unauthorised trades | FTX accounts, DMG pairs; escalated 21 Oct | 20 Oct 2022 | Historical |
| 3Commas — platform update | Keys assessed as not taken from its database; many affected keys never connected | Dec 2022 | Historical |
| 3Commas — mass revocation | Circulated key dataset confirmed genuine; exchanges asked to revoke | 28 Dec 2022 | Historical |
| 3Commas — verified total loss | — | — | Data not found |
| OKX spot-grid behaviour | Below the lower bound the bot stops buying while the asset continues falling | — | Current |
Where the data does not exist
Twelve gaps recur across the site. Each was searched for and each is published as a gap rather than filled.
| What is missing | Where it would appear |
|---|---|
| NZ retail loss rate | NZ regulation; CFD statistics |
| NZ retail leverage cap | NZ regulation |
| NZ algorithmic share of turnover | NZ regulation; market size |
| NZ regulator study of AI adoption | NZ regulation |
| Any FMA publication on algorithmic or AI trading conduct | NZ regulation |
| Count of UK firms authorised for algorithmic trading | UK regulation |
| UK-specific algorithmic share of turnover | UK regulation; market size |
| Any regulator assessment of AI trading tool profitability | UK, AU and NZ regulation; evidence |
| Loss statistics split by trading method | CFD statistics |
| Multi-year cohort study of retail traders | CFD statistics |
| Official AI trading market statistic | Market size |
| Audited live accuracy for any retail AI product | Prediction accuracy |
How this table is maintained
A figure enters only with a named source, a retrievable identifier where the source type has one, and a date. Where two credible sources disagree, both get rows — retail loss rates and market-size estimates are the two places this happens most. Nothing is averaged, harmonised or rounded to a convenient value.
Rows marked verify before use are re-checked before being cited anywhere new; vendor pricing is the main category. Rows marked historical describe a fixed past period and will not change. When a source publishes a new version, the row updates and the change is logged on the corrections page rather than applied silently. The full standard is set out in the editorial policy.
If you find an error, or a primary source for one of the twelve gaps, the corrections page is the route. A document number or URL is more useful than a description.
Frequently asked questions
What is the data hub?
A single table containing every figure used anywhere on this site, with its value, unit, primary source, document identifier where one exists, publication date and a freshness status. It exists so that any claim on any page can be checked in one place.
What does the freshness status mean?
Current means the source is the latest published version we could locate. Historical means the figure describes a specific past period and will not be updated. Verify before use means the value changes frequently — vendor pricing in particular — and should be re-checked at the source before being relied on.
How are figures selected for inclusion?
A figure appears only if it has a named source, a retrievable identifier such as a report or media release number, and a date. Where two credible sources disagree, both are listed with their own rows rather than averaged or reconciled.
Why are some cells marked data not found?
Because we looked for a primary source and could not locate one. It means the figure could not be verified, not that it does not exist. Publishing the gap is more useful than filling it with an estimate borrowed from a neighbouring jurisdiction.
Can I reuse these figures?
Yes, and preferably by citing the original source listed in the row rather than this page. Each entry names the regulator publication, paper or vendor page it came from precisely so that it can be traced past us.
Which figures conflict with each other?
Retail loss rates range from 68% to 82% across different measures, and market-size estimates span roughly 22 times. In both cases the conflict is definitional — different populations, periods and boundaries — so both are published in full rather than resolved.
How current is the platform pricing?
Captured from vendor pages in August 2026 and marked verify before use. Platform tariffs, tier limits and promotional pricing change frequently, so any pricing figure should be re-checked at the vendor's own page before it is relied on.
How often is this page updated?
When a source publishes a new version, when a figure we marked verify before use is re-checked, or when a correction is made. Changes are logged on the corrections page rather than applied silently.
What is the largest gap in this data?
New Zealand. Of fourteen comparable regulatory data points tracked across three markets, we located New Zealand primary sources for three, against thirteen for the United Kingdom and twelve for Australia.
Do any of these figures measure whether AI trading is profitable?
Only indirectly. The Eurekahedge AI Hedge Fund Index comparison and the peer-reviewed review of 27 machine-learning experiments are the closest available evidence. No regulator publishes an assessment of AI trading tool performance.
How do I report an error?
Through the corrections page, ideally with the document number or URL of the source that contradicts what is published here. Corrections are logged with the date and what changed, rather than edited in silently.
Compiled by AI Trading Book Editorial from the primary sources named in each row. Figures are reproduced as published, without averaging or harmonisation. Conflicting values appear as separate rows with their own sources. The composition count in the chart is our own tally of the tables on this page. Published 27 August 2026. Changes are logged on the corrections page.
Informational research only. Nothing on this page is personal financial, legal, tax or investment advice. Regulatory positions, vendor pricing and published statistics change; verify at the named source before relying on any figure.