90+ Forex Robot & Expert Advisor Statistics for 2026: Usage, Performance & Scams

Posted by

James Miller

October 10, 2026

On October 1, 2026

Updated October 3, 2026

Forex robots, called Expert Advisors on MetaTrader, sit inside a $9.6 trillion-a-day currency market, yet most retail traders who use leveraged products still lose money. This page collects 90+ statistics on the market, the MetaTrader Expert Advisor marketplace, robot performance, retail outcomes, AI adoption and trading bot scams. Each figure links to the regulator, research paper, platform or dataset that published it, and the MQL5 Market figures come from our own analysis of a public dataset of 2,098 MT4 Expert Advisors.

If you are new to automated trading, start with what an Expert Advisor is, then use the numbers below to set realistic expectations before you test one.

Key takeaways

$9.6 trillion a day was traded in OTC foreign exchange markets in April 2025, up 28% in three years. (BIS Triennial Survey, September 2025)
74-89% of retail CFD accounts typically lose money in EU national regulators’ analyses. (ESMA, March 2018)
90.2% of MT4 Expert Advisors on MQL5 Market had zero buyer reviews in a 2,098-listing snapshot. (MQL5 Market dataset, HiPips analysis, October 2020)
34.2% of MT4 Expert Advisor descriptions in the same snapshot mention martingale. (MQL5 Market dataset, HiPips analysis, October 2020)
R² < 0.025: across 888 trading algorithms, backtest Sharpe ratios explained almost none of the live results. (Wiecki et al., via Quantpedia, May 2016)
$7.9 billion was reported lost to investment scams by US consumers in 2025, with a median loss above $10,000. (FTC, April 2026)
22,364 AI-related crime complaints cost Americans nearly $893 million in 2025, the first year the FBI counted them separately. (FBI IC3, April 2026)

Forex market and algorithmic trading statistics

bar chart comparing algorithmic trading market size estimates from Mordor Intelligence, Straits Research, Market Research Future and Technavio, ranging from 9.58 to 20.23 billion US dollars

FX market size and execution

$9.6 trillion per day was traded in OTC FX markets in April 2025 (net-net basis, all FX instruments). That is the pool every forex robot trades in. (BIS Triennial Survey, September 2025)
28% growth in global FX turnover from $7.5 trillion a day in April 2022. (BIS Triennial Survey, September 2025)
42% higher FX spot turnover in April 2025 than three years earlier. Spot is the segment retail forex robots trade. (BIS Triennial Survey, September 2025)
31% of global FX turnover was spot in April 2025, up from 28% in 2022. (BIS Triennial Survey, September 2025)
89.2% of all FX trades had the US dollar on one side, up from 88.4% in 2022. (BIS Triennial Survey, September 2025)
75% of FX trading went through sales desks in the UK, US, Singapore and Hong Kong SAR. (BIS Triennial Survey, September 2025)
1,100+ banks and dealers in 52 jurisdictions reported data to the 2025 survey. (BIS Quarterly Review, December 2025)
59% of FX turnover was executed electronically in April 2025, a share virtually unchanged since 2022. (BIS Quarterly Review, December 2025)
80%+ of customer trades were matched by dealers inside their own liquidity pools rather than on a public venue. (BIS Quarterly Review, December 2025)

Algorithmic trading market size

$20.23 billion is the 2026 algorithmic trading market size in Mordor Intelligence’s report, projected to reach $29.54 billion by 2031. (Mordor Intelligence, September 2026)
54.47% of 2025 algorithmic trading spending went to cloud deployments, or $11.02 billion. (Mordor Intelligence, September 2026)
$18.9 billion is Straits Research’s 2025 estimate, rising to $37.31 billion by 2034. (Straits Research, 2026)
41.2% of the algorithmic trading market was in North America in 2025. (Straits Research, 2026)
$18.02 billion is the 2024 market value stated on Market Research Future’s report page. (Market Research Future, 2026)
$9.58 billion is a second 2024 value stated on the same Market Research Future page, about half the first one. Treat any single market-size figure with caution. (Market Research Future, 2026)
$23.94 billion of growth is expected from 2025 to 2030 at a 16.7% CAGR. (Technavio, 2026)
$14.27 billion was the 2024 value of the solutions segment alone. (Technavio, 2026)

The four publishers do not measure the same thing: some count software and services, some count the value of trading tools. The spread in the chart above is the useful number: estimates for roughly the same years differ by a factor of two.

MetaTrader and Expert Advisor marketplace statistics

bar chart of 2,098 MT4 Expert Advisor listings by price band: 11.1% free, 38.9% from 1 to 100 dollars, 27.9% from 101 to 499 dollars, 9.5% from 500 to 999 dollars and 12.5% at 1,000 dollars or more

MetaTrader platform adoption

750+ brokers and banks provide services to millions of traders on MetaTrader 4. (MetaQuotes, 2026)
No new MT4 licences: MetaQuotes states MetaTrader 4 licences are no longer available for purchase and its development focuses on MetaTrader 5. (MetaQuotes, 2026)
June 2021 is when the number of companies using MetaTrader 5 overtook those using MetaTrader 4. (MetaQuotes, June 2021)
7 million lines of code made up MetaTrader 5 at that point, against 2 million for MetaTrader 4. (MetaQuotes, June 2021)
14% growth in the MetaTrader 5 iOS audience over six months, a record after the app returned to the App Store. (MetaQuotes, April 2023)
500,000 registered MQL5.community members were reached in February 2015. (MetaQuotes, February 2015)
$80,000 in prize money a year drew hundreds of developers to MetaQuotes’ Automated Trading Championship. (MetaQuotes, 2026)

Inside the MQL5 Market for MT4 Expert Advisors

The figures below are our analysis of a public snapshot of 2,098 MT4 Expert Advisors listed on MQL5 Market on 9 October 2020. Shares are of all listings in the snapshot.

2,098 MT4 Expert Advisors were listed in the snapshot. (MQL5 Market dataset, HiPips analysis, October 2020)
833 distinct sellers published those listings; the median seller had one. (MQL5 Market dataset, HiPips analysis, October 2020)
16.5% of all listings came from the 10 most prolific sellers. (MQL5 Market dataset, HiPips analysis, October 2020)
$100 was the median price of an MT4 Expert Advisor. (MQL5 Market dataset, HiPips analysis, October 2020)
$1,147.50 was the mean price, more than ten times the median, because a long tail of expensive listings pulls it up. (MQL5 Market dataset, HiPips analysis, October 2020)
$40 to $450 was the price range of the middle half of listings. (MQL5 Market dataset, HiPips analysis, October 2020)
11.1% of MT4 Expert Advisors were free. (MQL5 Market dataset, HiPips analysis, October 2020)
50.0% were priced at $100 or less. (MQL5 Market dataset, HiPips analysis, October 2020)
12.5% were priced at $1,000 or more. (MQL5 Market dataset, HiPips analysis, October 2020)
$30,000 was the highest listed price. (MQL5 Market dataset, HiPips analysis, October 2020)
90.2% of MT4 Expert Advisors had zero buyer reviews. A review count is the first trust signal most buyers see, and nine in ten listings had none. (MQL5 Market dataset, HiPips analysis, October 2020)
2.4% had 10 or more reviews. (MQL5 Market dataset, HiPips analysis, October 2020)
78.5% of all reviews went to the top 1% of listings. Attention in the marketplace is highly concentrated. (MQL5 Market dataset, HiPips analysis, October 2020)
38 was the median number of demo downloads per listing. (MQL5 Market dataset, HiPips analysis, October 2020)
82.7% of listings had fewer than 100 demo downloads. (MQL5 Market dataset, HiPips analysis, October 2020)
42.6% of listings were still on version 1.0, meaning the seller had not published an update. (MQL5 Market dataset, HiPips analysis, October 2020)
99.2% of the listings live in the snapshot were published in 2019 or 2020. Older listings had largely left the market, so most Expert Advisors you can buy are young products. (MQL5 Market dataset, HiPips analysis, October 2020)

MQL5 Market MT4 snapshot (9 Oct 2020)	Value
Listings / distinct sellers	2,098 / 833
Median price / mean price	$100 / $1,147.50
Free listings	11.1%
Listings with zero reviews	90.2%
Share of all reviews held by the top 1% of listings	78.5%
Median demo downloads	38
Listings still on version 1.0	42.6%

Expert Advisor strategy and performance statistics

bar chart of the share of MT4 Expert Advisor descriptions mentioning stop loss 62.7%, martingale 34.2%, grid 27.6%, scalping 22.3%, hedging 16.5%, no martingale 6.7%, AI or neural network 5.1% and news filter 2.8%

What sellers say their Expert Advisors do

A mention is a keyword match on the seller’s own text, so “no martingale” also counts as a martingale mention; the separate line for explicit “no martingale” claims shows the size of that overlap.

62.7% of MT4 Expert Advisor descriptions mention a stop loss. More than a third do not mention one at all. (MQL5 Market dataset, HiPips analysis, October 2020)
34.2% mention martingale, the recovery method that increases position size after a loss. (MQL5 Market dataset, HiPips analysis, October 2020)
27.6% mention a grid. (MQL5 Market dataset, HiPips analysis, October 2020)
22.3% mention scalping. (MQL5 Market dataset, HiPips analysis, October 2020)
16.5% mention hedging. (MQL5 Market dataset, HiPips analysis, October 2020)
6.7% explicitly state that they use no martingale. (MQL5 Market dataset, HiPips analysis, October 2020)
5.1% mention neural networks, AI or machine learning, well before the current wave of “AI trading bot” marketing. (MQL5 Market dataset, HiPips analysis, October 2020)
2.8% mention a news filter. (MQL5 Market dataset, HiPips analysis, October 2020)

Backtests versus live results

888 trading algorithms with at least six months of out-of-sample results were studied; backtest Sharpe ratios had almost no power to predict live performance (R² < 0.025). (Wiecki et al., via Quantpedia, May 2016)
0.17 was the R² reached when machine learning used many features of backtest behaviour instead of the Sharpe ratio alone, still far from a reliable forecast. (Wiecki et al., via Quantpedia, May 2016)
80%+ of 50-round constant-betting runs ended with a positive return even with a 20% house edge in the authors’ simulations. A high win rate can come from the betting pattern alone, which is why a martingale or grid Expert Advisor can look excellent until it fails. (Dimitrov and Shafer, Judgment and Decision Making, May 2025)

Retail trader outcome statistics

bar chart of the share of retail clients losing money by regulator: ESMA 74 to 89 percent for EU CFDs, FCA about 80 percent for UK CFDs, CFTC about two thirds for US forex and ASIC 85 percent for Australian options CFDs, median 80.8 percent

Europe and the UK

74-89% of retail CFD accounts typically lose money across EU jurisdictions. (ESMA, March 2018)
€1,600 to €29,000 was the range of average losses per retail CFD client. (ESMA, March 2018)
50% of minimum required margin is the level at which EU providers must close out a retail client’s CFD positions. (ESMA, March 2018)
80% of UK customers, approximately, lose money when investing in CFDs. (FCA, December 2022)
£100 million a year of consumer harm was prevented by the FCA’s CFD actions in 2021 alone. (FCA, December 2022)

United States

Two out of three customers at registered US OTC forex dealers lost money over a year; about one-third made a profit. (CFTC, 2026)
2% is the minimum US margin on major currency pairs (5% on others), which caps retail leverage. (CFTC, 2026)
60th percentile: in US retail futures accounts, a trader has to rank above the 60th percentile of the profit-and-loss distribution just to break even. (CFTC Office of the Chief Economist, November 2024)
20% of retail futures traders entered the market only once in the sample period. (CFTC Office of the Chief Economist, November 2024)
95% of retail futures accounts held an average margin below $20,000. (CFTC Office of the Chief Economist, November 2024)

Australia

133,674 Australian retail clients lost money trading CFDs in FY 2023-24, with net losses above A$458 million including A$73 million in fees. (ASIC Report 828, January 2026)
85% of retail clients made a net loss trading options CFDs in FY 2023-24. (ASIC Report 828, January 2026)
72% of retail clients lost money at one CFD issuer ASIC reviewed. (ASIC Report 828, January 2026)
A$39 million+ was returned to retail clients through ASIC action over 12 months. (ASIC Report 828, January 2026)

Median retail loss rate across four regulators

Regulator	Market and product	Period	Share losing money
ESMA	EU retail CFD accounts	2018 analysis	74-89% (midpoint 81.5%)
FCA	UK retail CFD customers	2022 statement	about 80%
CFTC	US retail OTC forex accounts	Q2 2021 to Q1 2022 disclosures	about 67%
ASIC	Australian retail options CFD clients	FY 2023-24	85%
Median			80.75%

How it was calculated: the median of each regulator’s published figure, using the midpoint where a range is given. Products, periods and definitions differ, so the median is an indicator, not a pooled loss rate. An Expert Advisor does not change these odds by itself; it executes a strategy faster and without emotion, including a losing one.

Cite this table: <a href="https://hipips.com/blog/forex-robot-statistics/">Retail loss rates by regulator (HiPips, 2026)</a>

AI and automated trading adoption statistics

bar chart from an Investing.com survey of 938 US investors: 24% use AI tools regularly, 27% occasionally, 11% have experimented, 21% are considering it and 17% have no plans

30% of 1,000 surveyed US retail investors use AI tools to pick or alter investments, up 75% in one year. (eToro Retail Investor Beat, October 2025)
28% say they are open to letting AI pick investments, down from 33% a year earlier. (eToro Retail Investor Beat, October 2025)
48% of investors open to AI picks say the main reason is saving research time. (eToro Retail Investor Beat, October 2025)
62% of 938 surveyed US investors have used AI tools to assist investment decisions. (Investing.com survey, Traders Magazine, April 2026)
24% use AI tools regularly, 27% occasionally and 11% have experimented with them. (Investing.com survey, Traders Magazine, April 2026)
34% use AI to generate investment or trading ideas. (Investing.com survey, Traders Magazine, April 2026)
54% trust AI-generated analysis only somewhat and check it elsewhere; 23% trust it mostly or completely. (Investing.com survey, Traders Magazine, April 2026)
17% do not plan to use AI tools for investing at all. (Investing.com survey, Traders Magazine, April 2026)

Forex robot and AI trading scam statistics

bar chart of reported 2025 US losses: investment scams 7.9 billion dollars, people over 60 7.7 billion, crypto investment fraud 7.2 billion, social media investment scams 1.1 billion and AI-related complaints 0.89 billion

Scale of investment fraud

1,008,597 internet crime complaints reached the FBI’s IC3 in 2025, up from 859,532 in 2024. (FBI IC3, April 2026)
$17.7 billion+ in losses came from about 453,000 cyber-enabled fraud complaints. (FBI IC3, April 2026)
49%, nearly half, of all scam-related losses came from investment fraud. (FBI IC3, April 2026)
$7.2 billion was lost to cryptocurrency investment fraud, the largest loss category in 2025. (FBI IC3 2025 Internet Crime Report, April 2026)
181,565 complaints involving cryptocurrency reported losses of more than $11 billion. (FBI IC3, April 2026)
$7.7 billion was lost by Americans over 60, up 37% from 2024. (FBI IC3, April 2026)
$1.1 billion was lost to investment scams that started on social media, more than half of all social media scam losses. (FTC Data Spotlight, April 2026)

Trading bot and auto-trading fraud

$1.7 billion in bitcoin was taken from at least 23,000 people by Mirror Trading International, which sold access to a forex “bot trading program”. (CFTC, January 2024)
10% a month, more than 200% a year, was the return that program guaranteed, for as little as $100. A guaranteed monthly return is a red flag on its own. (CFTC, January 2024)
100% “win” rates and returns of tens of thousands of percent are typical claims in AI trading bot scams. (CFTC, January 2024)
$1.7 million was solicited from a single individual by Financial Robotics, Inc. for leveraged off-exchange forex trading. (CFTC, October 2014)
10%+ consistent monthly returns are a common promise of unregistered auto-trading services, which often also claim to carry no risk or to be AI-driven. (FINRA, July 2025)
$15 million+ was taken in investment confidence schemes that lured retail investors through WhatsApp and similar platforms. (SEC, September 2026)
$12.5 million and $2.8 million were allegedly misappropriated by two of those operations while they posed as SEC-compliant. (SEC, September 2026)
$14 million+ was taken from retail investors by fake trading platforms and “AI” investment clubs recruited through social media ads. (SEC, December 2025)

Prop firm and Expert Advisor statistics

bar chart of FTMO limits as a share of initial capital: 1-Step profit target 10% and maximum daily loss 3%, 2-Step phase 1 profit target 10%, Verification target 5% and maximum daily loss 5%

37 forex prop firms on Prop Firm Match’s list allow Expert Advisors in their challenge or funded-account rules. (Prop Firm Match, October 2026)
10% is FTMO’s profit target in the 1-Step Challenge and in phase 1 of the 2-Step Challenge; the 2-Step Verification needs 5%. (FTMO, 2026)
3% of initial capital is FTMO’s maximum daily loss on the 1-Step program. (FTMO, 2026)
5% of initial capital is FTMO’s maximum daily loss on the 2-Step program. (FTMO, 2026)

An Expert Advisor that risks 2% per trade can breach a 3% daily limit with two losing trades. Our prop firm Expert Advisor risk rules checklist shows how to size an Expert Advisor for these limits.

What these forex robot statistics mean in practice

The numbers point the same way. Most retail traders who use leveraged products lose money, and a robot automates whatever strategy it runs, good or bad. A robot that wins often is not the same as a robot that makes money: the martingale index results show a high win rate can come from position sizing alone, and the 888-algorithm study shows a strong backtest says little about live results.

The marketplace makes this harder to judge. In the MQL5 Market snapshot, nine in ten MT4 Expert Advisors had no reviews, over a third described martingale and more than a third did not mention a stop loss. Price was no guide either: the mean was more than ten times the median.

Three practical rules follow from the data:

Treat a guaranteed monthly return, a perfect win rate or an “AI” label as a reason to stop, not to buy. Regulators list all three as fraud signals.
Judge an Expert Advisor on a verified live record and your own backtest, not the seller’s equity curve. The two guides below show how.
Size it for the worst run of losses, not the average trade. Our Expert Advisor risk settings guide covers lot size, drawdown and daily limits.

If you are choosing a platform first, see MT4 vs MT5 for Expert Advisors.

Methodology

We logged 101 candidate figures from 34 sources and checked each one against the page or file that published it. A script fetched every source page, saved its text and confirmed that the number appears there; figures that could not be found on a live page were dropped. Sources we could not open or read (two market research reports, an SEC staff report, a Cambridge journal article, a CFTC advisory page, a ResearchGate preprint, an SSRN abstract and broker risk warnings rendered by scripts) are not used. Six logged figures were left out as duplicates or of marginal relevance, leaving 95 statistics on this page.

Inclusion rules: primary sources only (regulators, central banks, peer-reviewed or working papers, platform operators, survey publishers); every figure keeps its own scope (country, product, period, sample); unlike samples are never averaged into one number. Vendor marketing claims about robot performance are excluded.

Derived figures: the MQL5 Market statistics are our analysis of the public Kaggle dataset “MetaTrader 4 Expert Advisors’ Market” (2,098 listings scraped on 9 October 2020). We publish only aggregates. Strategy shares are keyword matches on seller descriptions in English and Russian. The regulator median is the median of four published figures, using range midpoints. Charts are generated directly from the verified figures.

Refresh schedule: links and figures are rechecked every quarter; the page is fully updated each year when the BIS, FBI IC3, FTC and regulators publish new data. The URL stays the same.