Building a Social Media Signal Trading System for Equity Perpetuals
Summary
The document describes a pipeline that turns a financial influencer’s posts into trading signals for Binance stock perpetual contracts. It proposes collecting posts through an RSS feed, asking an LLM to identify explicitly named tickers, direction, confidence, and rationale, then matching valid signals to available contracts. The author emphasizes that the model must account for the influencer’s rhetorical habits, such as teaser questions that should be treated as neutral rather than bullish. Contract discovery is refreshed dynamically as listings change.
Risk controls include small fixed position sizing, a cap on concurrent holdings, no leverage, a hard loss limit, and a trailing giveback exit. The system starts in notification-only mode so signal interpretations can be reviewed before live trading. The document gives no independent performance test of the automated strategy; claims about the source’s record are reported from social media and a tracker. It also notes that stock perpetuals differ from share ownership, including funding costs and lack of dividends, and that results depend heavily on the signal source and LLM interpretation.
Key ideas
- Social posts can be structured into ticker, direction, confidence, and rationale fields before they reach an execution layer.
- An LLM prompt should distinguish explicit recommendations from teaser questions and broad thematic commentary.
- A dynamically refreshed contract map helps match detected stock tickers to currently listed perpetual contracts.
- The proposed controls include capped position sizes, limited simultaneous holdings, a hard stop, and a trailing profit giveback exit.
- Notification-only operation allows human review of signal quality before enabling automated orders.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.