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Table of Contents
This page collects credible, sourced statistics on automated and algorithmic trading, the retail investing boom, and the tools behind them. Every figure links to its original source. If you are a writer, journalist, or researcher, you are welcome to cite any of these statistics, and a link back to this page is always appreciated. Figures from market-research vendors are labeled as estimates, and older peak-era figures are dated so you can use them accurately.
Last updated: September 2026.
Key Algorithmic Trading Statistics for 2026
Here are the numbers I keep coming back to, grouped by theme and updated as new data lands. Every figure links to its original source so you can verify it and cite it directly.
The Rise of Algorithmic Trading
Rules-based, automated strategies now dominate the market that discretionary human stock-pickers once ruled. One widely cited analysis estimated that fundamental discretionary traders account for only about 10% of U.S. stock trading volume, while passive and quantitative (rules-based) investing makes up roughly 60%, more than double its share a decade earlier. Source: JPMorgan, via CNBC (2017).
You will often see the claim that “70 to 80% of trading is algorithmic.” Treat that number with care: it is hard to tie to a single primary study and varies by market and by how “algorithmic” is defined. The honest version is that credible estimates put automated activity at a majority of U.S. equity volume, with well-attributed figures ranging from around 60% up.
How Big the Algorithmic Trading Market Is
The global algorithmic trading market was valued at roughly USD 20.2 billion in 2026 and is projected to reach about USD 29.5 billion by 2031, a compound annual growth rate near 7.9%. Source: Mordor Intelligence (market-research estimate, 2026).
A separate vendor estimate put the market at USD 11.1 billion in 2019 growing to an estimated USD 18.8 billion in 2024, an 11.1% CAGR. Source: MarketsandMarkets. Market-sizing vendors differ substantially, so these are best read as directional estimates that agree on one thing: the market is large and growing.
High-Frequency Trading
At its peak, a tiny number of ultra-fast firms drove the majority of U.S. share volume. By 2009, high-frequency trading firms, about 2% of trading firms, accounted for roughly 73% of all U.S. equity order volume. Source: industry figures summarized on Wikipedia (HFT), referring to 2009.
The TABB Group estimated HFT made up about 56% of U.S. equity trades by value in 2010. Source: TABB Group, via Wikipedia. These are peak-era figures; more recent estimates commonly place HFT nearer 50% of U.S. equity volume, though current figures are largely proprietary.
The Retail Trading Boom
Everyday investors have become a structural force in the market, not just a headline. 62% of U.S. adults reported owning stock in 2025, up slightly from recent years. Source: Gallup (2025).
Retail investors accounted for more than 20% of U.S. equity trading volume in 2025, and an even higher share of activity in lower-priced stocks. Source: Jefferies, via Sherwood News (December 2025).
The trend is dramatic over time. Retail trading roughly doubled from about 10 to 15% of U.S. equity volume before the pandemic to a peak near 22 to 25% during the 2021 meme-stock surge. Source: Bloomberg Intelligence and academic research, as aggregated by DayTrading.com (2021).
Commission-Free Brokerages by the Numbers
The app-based, commission-free broker is the front door for this new generation of traders. Robinhood ended 2024 with 25.2 million funded customers, up 8% year over year, and USD 193 billion in assets under custody, up 88%. Source: Robinhood Markets official results (2024).
Robinhood took in USD 50.5 billion in net deposits and USD 2.95 billion in total net revenue, up 58%, in 2024. Source: Robinhood Markets.
The growth traces back to the pandemic boom. Robinhood reported 18 million net cumulative funded accounts as of March 31, 2021, up 151% year over year. Source: Robinhood S-1 filing, via PYMNTS (2021).
Python: The Language of Automated Trading
Nearly every retail trading bot, backtest, and quant library runs on Python, and its dominance shows up in the broader data. Python was the number one language in the TIOBE Index and named its Programming Language of the Year for 2024. Source: TIOBE Index (2024).
About 51% of all developers use Python, making it one of the most-used programming languages in the world. Source: Stack Overflow Developer Survey (2024). Python is the default language of data science and quantitative finance, which is exactly why it is the natural choice for building a trading bot.
Crypto and 24/7 Markets
Crypto is where retail automation runs hardest, in part because the market never closes. The total crypto market capitalization ended 2024 at about USD 3.4 trillion, up 97.7% on the year, peaking near USD 3.91 trillion in December. Source: CoinGecko 2024 Annual Report.
The top 10 centralized crypto exchanges handled about USD 17.4 trillion in spot trading volume in 2024, up from USD 7.2 trillion in 2023. Source: CoinGecko.
More than 560 million people worldwide owned cryptocurrency in 2024, roughly 6.8% of the global population. Source: Triple-A (2024).
Crypto trades 24 hours a day, 7 days a week, versus about 6.5 hours a day for U.S. stocks. That structural difference is a big reason automated bots suit crypto so well: the opportunities never stop, but a human has to sleep. U.S. market hours source: NYSE.
The Broader Trading Boom
The appetite for active, tech-enabled trading shows up beyond stocks. The Options Clearing Corporation cleared a record 12.28 billion options and futures contracts in 2024, up 10.6% from 11.1 billion in 2023. Source: OCC.
Automation Adoption Among Retail Traders
Hard data on how many retail traders actually use bots is still thin, and the figures that exist are self-reported surveys rather than measured market activity, so treat them as directional. In one such survey, about 37% of crypto traders said they use AI or automated tools in their trading. Source: Finance Magnates survey, via TradingView News (2025). Read it as a self-reported snapshot, not a market truth.
How to Cite This Page
You are welcome to use any statistic on this page in your own work. When a figure comes from a primary source such as a company filing, an exchange, or a survey, please cite that original source, which I have linked next to every number. When you are citing the collection itself, use one of the ready-made formats below. A link back to this page is always appreciated, and it helps other people find the data too.
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