P-Signal Multi-Timeframe Bitcoin Trading Strategy

Summary

This document describes a Bitcoin strategy that calculates a P-Signal from a smoothed ratio of price changes to their standard deviation, then maps the result through an approximation of the Gaussian error function. It tracks the indicator on daily, weekly, and monthly timeframes. Entries occur when the signal is below zero and rising; exits occur when it is above zero and falling. Separate entry valves limit repeated entries for each timeframe.

The text argues that shorter and longer timeframes may complement one another by responding to daily moves while using weekly and monthly signals to filter noise. It provides indicator formulas, parameter defaults, and a published Binance futures backtest period, but reports no performance results. It also flags uncertain market fit, lagging crossovers, and difficulty in sharp moves. The stated improvements—testing parameter choices, stops, auxiliary indicators, and position sizing—are suggestions rather than validated findings; broad backtesting is needed before live use.

Key ideas

• The P-Signal applies a Gaussian error function to a moving-average and standard-deviation ratio of price changes.
• The strategy monitors Bitcoin on daily, weekly, and monthly timeframes.
• It enters when a below-zero signal rises and exits when an above-zero signal falls.
• Separate entry valves restrict repeat entries on each timeframe.
• The document gives no backtest performance figures and notes potential lag, market-fit uncertainty, and parameter risk.

Tags

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