VIDYA Trend Signals from Price and Dual-Average Crossovers

Summary

This beginner guide explains the Variable Index Dynamic Average (VIDYA), a lagging trend indicator that adjusts its smoothing using the absolute value of the Chande Momentum Oscillator. It describes the calculation in terms of an EMA smoothing factor and CMO, and identifies the CMO period, EMA period, and applied price as key settings. The article then presents three simple signal approaches: classify trend or generate buy and sell signals from the close’s position relative to VIDYA, and compare a faster VIDYA setting with a slower one for crossover signals.

The guide outlines how to display indicator values and signals in an MQL5 chart comment, but its strategies are basic rules rather than a tested trading system. It provides no quantified backtest results, transaction-cost analysis, or risk controls, and recommends testing and adapting the rules before live use. The text also describes comparing current values; a practical implementation would need precise crossover and bar-timing rules to avoid ambiguous or unstable signals.

Key ideas

• VIDYA adjusts EMA-style smoothing according to the absolute value of the CMO.
• A close above or below VIDYA is used to label trend direction and produce simple directional signals.
• Comparing fast and slow VIDYA values provides a second crossover-based signal method.
• The guide focuses on indicator use and MQL5 implementation rather than measured trading performance.
• The rules need testing and clearly defined signal timing before practical deployment.

Tags

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