GptBasedStrategyBTCTabased is a production algorithmic trading strategy paper-traded live from a $10,000 seed. Live paper-trading performance: -28.90% annualised return (-16.49% total), Sharpe -0.90 over 126 days.

TL;DR

• Strategy family: AI / LLM-driven — LLM-in-the-loop strategies: GPT, DeepSeek, and multi-agent hedge-fund setups.
• Live track record: -28.90% annualised return (CAGR), Sharpe -0.90, max drawdown -18.86% over 126 trading days.
• Code: open-source on python_tradingbot_framework — tradingbot/gptbasedstrategytabased.py.

Live performance snapshot

• Annualised return (CAGR): -28.90%
• Current paper-portfolio worth: $8350.67 (seeded at $10,000)
• Total return since seed: -16.49%
• Sharpe: -0.90
• Max drawdown: -18.86%
• Days live: 126

See the full chart, current holdings, and historical backtest on the strategy’s live page →.

How GptBasedStrategyBTCTabased works

A full technical writeup for GptBasedStrategyBTCTabased is in progress. In the meantime:

• Source code: tradingbot/gptbasedstrategytabased.py.
• Open-source framework: python_tradingbot_framework.

Run it yourself

GptBasedStrategyBTCTabased is part of the open-source python_tradingbot_framework — fork the repo, run the code locally, or deploy your own variant. The source lives at tradingbot/gptbasedstrategytabased.py. The live page shows today’s portfolio state alongside the full historical backtest.

Related AI / LLM-driven strategies

• DeepSeekToolBot — also in the AI / LLM-driven family. See live performance →
• AIHedgeFundBot — also in the AI / LLM-driven family. See live performance →

FAQ

Is GptBasedStrategyBTCTabased profitable live?

Since deployment, GptBasedStrategyBTCTabased has produced an annualised return (CAGR) of -28.90% on a $10,000 paper seed (-16.49% cumulative), with a Sharpe ratio of -0.90 and a max drawdown of -18.86% over 126 trading days. Numbers refresh daily on the live page.

Can I run GptBasedStrategyBTCTabased myself?

Yes. GptBasedStrategyBTCTabased is part of the open-source python_tradingbot_framework — you can fork the repo, inspect the strategy, and run the code locally or on your own Kubernetes cluster. The exact source file is here.

How does GptBasedStrategyBTCTabased compare to other quantitative strategies?

GptBasedStrategyBTCTabased belongs to the AI / LLM-driven family. LLM-in-the-loop strategies: GPT, DeepSeek, and multi-agent hedge-fund setups. Browse the full leaderboard to compare it against strategies from other families.

Compare every strategy

Browse the full live leaderboard to see how GptBasedStrategyBTCTabased ranks against 23 other paper-traded strategies, all seeded with the same $10,000.