AI Signal Execution for Spot Crypto with Stop-Loss and Deduplication
Summary
This document describes a spot trading workflow in which an external AI service gathers data and news, forms a buy, sell, or hold decision, and sends a structured signal to an execution bot. The bot receives signals through a channel, checks required fields and timestamps to avoid duplicate processing, verifies available quote or coin balances, and executes a configured trade size. It also tracks recent trades and displays account equity, signal, and stop-loss information.
Risk controls include a percentage threshold that can sell after a buy when price falls, or buy back after a sell when price rises. These rules, along with the signal-driven nature of the system, are operational design details rather than evidence of trading edge. The document gives no backtest or live performance results, and does not explain how the AI decision is validated or how positions are sized across signals. It advises initial simulation or small-scale use and regular monitoring, while noting that AI decisions should not be relied on alone.
Key ideas
- An external service sends structured buy, sell, or hold signals to a spot execution bot.
- The bot checks signal timestamps to reduce duplicate trades and verifies balances before orders.
- A percentage-based rule can exit after a decline from a buy or buy back after a rise from a sale.
- The system records recent trades and reports equity, current signals, and stop-loss status.
- The document describes implementation and safeguards but provides no evidence of profitability.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.