Scoring Trend Entries with Confluence Ranks and Risk-Based Sizing
Summary
This trend-following method assigns separate long and short scores using five components: trend direction, RSI momentum, directional efficiency, the ATR volatility regime, and volume participation. Each contributes up to 20 points. Trades open only when a directional score clears a threshold, while the score also scales risk per trade between a threshold-level amount and a higher amount for a perfect score. Quantity is calculated from risk and stop distance, with notional capped by a leverage limit.
The description gives implementation settings and says its defaults were selected through a parameter search on BTCUSDT hourly data, considering earlier and later history segments. It does not report performance metrics, so the search process is not evidence of profitability. The score is a weighted checklist, not a probability estimate. The author also cautions that choppy conditions can produce repeated small losses, volume feeds vary by venue, and fills, funding, gaps, and parameter overfitting limit how closely backtests may match live trading.
Key ideas
- Five directional and market-condition components contribute equally to long and short scores.
- Entries require a score threshold, and stronger scores increase the risk allocation.
- Position quantity depends on risk and stop distance, subject to a leverage-based notional cap.
- The BTCUSDT hourly defaults were selected through a historical parameter search and may not transfer to other markets.
- Choppy markets, variable volume data, and simplified fill assumptions are important limitations.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.