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How to paper trade a strategy on daily bars with Vibe Trading

Save a paper account and step it forward against completed daily bars without ever reaching a broker.

Short answer: Install or upgrade with pip install -U vibe-trading-ai; then create and manage saved paper accounts with vibe-trading paper, or from the REST API or Web page; let the agent match orders or a strategy against completed daily bars with the paper_trade_step tool. All steps.

  • Money
  • Intermediate
  • 30 minutes
  • From the README
  • Any agent

Who it is forA learner who backtested a strategy and wants to see how it behaves going forward before any real money.

The problemBacktests look good in hindsight; you need a forward test that cannot peek at the future.

The outcomeA saved paper account that moves forward one completed day at a time and never touches a broker.

What you need first

  • Python 3.11 or later for a local install, or Docker
  • An LLM API key from a supported provider, or Ollama locally
  • Market data works without keys for many markets through free fallbacks

Steps

  1. Install or upgrade with pip install -U vibe-trading-ai
  2. Create and manage saved paper accounts with vibe-trading paper, or from the REST API or Web page
  3. Let the agent match orders or a strategy against completed daily bars with the paper_trade_step tool
  4. Check the account each day; saved accounts only move forward

Prompt for your agent

Using HKUDS/Vibe-Trading, create a saved paper account and paper trade <strategy> on <symbols> against completed daily bars. Each day report positions, cash and PnL, and confirm no broker connector is enabled.

Caveat. Paper fills on completed daily bars ignore real slippage and liquidity, and live broker trading is marked experimental. Not financial advice: paper trade first, and remember you can lose money.

Use this in your AI agent

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Using the Deduped MCP, get the setup steps for HKUDS/Vibe-Trading and "Paper trade a strategy on daily bars"

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claude mcp add --transport http deduped https://dedupedai.com/mcp

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