Updated daily · as of Oct 28, 2026 · every number sourced

AI trading bot statistics (2026)

Every statistic we can back up about AI trading bots and agents: how many make money, whether they beat Bitcoin, how AI models do with real money, what users pay, and how often advertised returns hold up. Each links to its source and the date it was measured.

Most numbers are computed by us from public chain and venue data; the rest say where they come from. For the full rankings see the verified leaderboard.

+9.1%trading ROI of 321 AI agents on prediction markets (90 days)
31 of 38Alpha Arena model accounts lost money
6 of 8AI apps on Hyperliquid whose users lost money (30 days)
17 of 18advertised returns nobody else can check

Performance: do AI trading bots make money?

Computed by us from public chain and venue data (grade A). These are the only bots whose results anyone can check.

AI models trading and forecasting

Large language models given real money or real forecasting questions, scored on outcomes nobody could know in advance.

Advertised results: can you trust them?

What AI trading products say about their own returns, against what anyone can check.

Usage: how much people use trading bots

Fees and volume measure demand. Most bots publish no trading record, so this is the most we can say about them.

Security: what could go wrong

Results don't show what a bot can do with your money. These do.

How these numbers are made

Evidence grades

A, verified: computed by us from public chain or venue data. The only grade we rank. B, venue-reported: a platform's own numbers on real accounts. C, claimed: a company's statement with no public record. D, backtest: a simulation.

How we verify results · How we score risk

What these numbers don't say

Past results don't predict future ones, and short windows can flatter luck. A bot that made money for others can still lose yours, and usage or GitHub stars measure attention, not skill or safety. Not financial advice.

Cite these statistics

Free to use under CC BY 4.0. Please credit and link: TradingAgentStack, "AI trading bot statistics (2026)", https://tradingagentstack.com/ai-trading-bot-statistics/, accessed Oct 28, 2026.

Raw data: AI agents (JSON) · AI vaults (JSON) · AI apps (JSON) · Alpha Arena (JSON) · bot usage (JSON) · repo health (JSON). Agents can query everything through our MCP server. Run an AI trading agent with a public account? Get it verified.

FAQ

What percentage of AI trading bots make money?

There's no overall number anyone can verify, because most bots publish no trading record. Where we can check: 90% of active AI agents on prediction markets with enough activity made money over 90 days (141 of 157), but users of 6 of 8 AI trading apps on Hyperliquid lost money over 30 days, and 31 of 38 Alpha Arena model accounts lost money.

Do AI trading bots beat Bitcoin?

Rarely, in the data we can check: 2 of 6 Hyperliquid vaults whose leaders say they're AI-run beat BTC over the same dates. Beating BTC matters because holding it costs nothing and needs no bot.

Which AI model is best at trading?

In Alpha Arena, the only public real-money contest between models, Qwen3 Max led Season 1 (+20.3%) and Grok 4.20 (Mystery Model) led Season 1.5 (+13.0%). Seasons lasted two to three weeks, too short to separate skill from luck, and the same model can finish first in one season and near the bottom in the next.

Are AI trading bot win rates real?

Most can't be checked: 17 of the 18 advertised AI trading returns we checked have no public record or come from backtests. A win rate also says nothing without the size of the losses: a bot can win 90% of trades and still lose money.

How much do people spend on Telegram trading bots?

Users paid 16 Telegram trading bots $6.4M in fees over the last 30 days, according to DeFiLlama. Most charge about 1% per trade, so fees track trading volume.

How often are these statistics updated?

Performance, usage and repo health are recomputed every day from public data. Claims and MQL5 signals are checked by hand each week. Every statistic shows its source and date.

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