Multi-Timeframe Linear Regression Candles for Trend Signals

Summary

This strategy smooths open, high, low, and close prices with linear regression, then applies a simple moving average to the transformed values. It uses candle direction on the active chart and on a 15-minute linear regression series as a confirmation rule: matching bullish colors trigger a long entry, while matching bearish colors trigger a short entry. The code also plots exponential moving averages and marks signals near the smoothed candle highs or lows, although the described entry conditions do not use those averages as filters.

The document provides implementation parameters and backtest settings for ETH/USDT futures over a stated date range, but gives no reported performance results. It identifies lag from smoothing, false signals in ranging markets, sensitivity to parameter choices, and the lack of an explicit stop-loss in the code. It also describes multi-timeframe confirmation as improving reliability, but supplies no evidence establishing that claim. The document is best read as a rule-based trend signal example that needs testing and risk controls before use.

Key ideas

• Linear regression followed by SMA smoothing is used to create less noisy candle values.
• Entries depend on matching candle directions on the chart timeframe and a 15-minute series.
• The code displays EMA lines, but the stated entry logic does not depend on them.
• Smoothing can delay signals, and ranging markets may create false entries.
• The supplied ETH/USDT futures backtest settings are not accompanied by performance results.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.