William Blau’s EMA-Smoothing Framework for Momentum Indicators
Summary
The document introduces William Blau’s approach to building technical indicators from price data. It describes a four-stage process: calculate an initial indicator, smooth it with successive exponential moving averages (EMAs), normalize the smoothed series to frame overbought and oversold conditions, then smooth again to form an oscillator with a signal line and threshold levels. The article surveys indicator families based on momentum, stochastic measures, mean deviation, MACD, candlestick momentum, and composite high-low momentum. It gives particular attention to the True Strength Index and the interpretation of momentum as price change over a period.
The article explains that smoothing can reveal broader price movement and turning points while reducing noise, but repeated smoothing adds lag. It also outlines an EMA implementation detail: the accompanying code changes the usual period check so that a period of one can represent no smoothing. The discussion is conceptual and implementation-focused; the available excerpt provides no systematic performance tests or evidence that the indicators produce profitable trades. Results may depend on the chosen price input, periods, instrument, and timeframe.
Key ideas
- Blau’s framework builds indicators through calculation, repeated EMA smoothing, normalization, and oscillator construction.
- Momentum is treated as price change over a chosen period and is used to examine the speed and direction of movement.
- Repeated smoothing can suppress price noise, though it also introduces some lag.
- The article covers indicator families based on momentum, stochastic measures, mean deviation, MACD, candlestick momentum, and high-low momentum.
- A modified EMA routine allows a period of one to represent the absence of smoothing.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.