Implementing the Moving Mini-Max Indicator for Turning Points and Trends

Summary

The article explains a Moving Mini-Max indicator inspired by a simplified analogy to quantum tunneling. It transforms a price window into normalized values using transition probabilities across nearby prices. One version emphasizes local minima and another local maxima; the smoothing-window parameter controls how broadly neighboring observations contribute. The author implements the calculations in MQL5, plots both series, and describes using their crossings with moving averages to mark possible support and resistance, as well as their relative extremes to signal short-term trend changes.

The indicator needs extra historical bars for its window and is shifted to account for lag. The author reports that it can identify local highs and lows within a selected window, while also acknowledging false signals in the support and resistance application. The article offers implementation details and chart-based observations, not a controlled test, quantified accuracy, or evidence of profitability. Its claims should therefore be treated as hypotheses for further testing, and the window-dependent turning points may change as new bars arrive.

Key ideas

• Moving Mini-Max transforms a price window into normalized values using recursively calculated transition probabilities.
• Separate formulations emphasize local maxima and local minima in the price series.
• The smoothing window affects how readily nearby price barriers influence the calculation, and introduces lag.
• The author proposes using crossings and relative indicator extremes to identify support, resistance, and short-term trend changes.
• The article reports false signals and does not provide a controlled performance evaluation.

Tags

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