Momentum, direction, and divergence

Curated by Brian Kim, CPA — every pick gets a plain-English summary and the key takeaways.
Brian Kim, CPA · 2.89M YouTube Subscribers →What this book actually teaches
- 01Double-smoothing price momentum with two sequential EMAs produces oscillators that are both smoother and more responsive than single-smoothed RSI or stochastics.
- 02The True Strength Index (TSI) is Blau's signature indicator and the cleanest expression of the double-smoothing approach.
- 03Divergence between price and a smoothed oscillator is treated as the highest-value signal, though it is prone to hindsight bias in practice.
- 04Lookback parameters should be tested per market, not accepted as defaults — the engine generalizes, the settings do not.
- 05This is a methods monograph, not a trading system; risk management, sizing, and rigorous backtesting are out of scope.
What's in this book
William Blau's argument in Momentum, Direction, and Divergence is that conventional momentum oscillators like the Relative Strength Index and the stochastic give lagging, noisy signals because they use single-period smoothing, and that double-smoothing the underlying price change — applying an exponential moving average to the momentum, then a second EMA to the result — produces indicators that are both smoother and more responsive. The book is a technical-analysis methods text aimed at building a better oscillator toolkit.
The arguments develop a small family of indicators. Blau introduces the True Strength Index (TSI), his best-known contribution, which double-smooths price momentum and its absolute value and divides them to produce a bounded oscillator that swings between meaningful extremes without the choppiness of an unsmoothed RSI. He extends the same double-smoothing logic to build directional indicators and to refine stochastic-style oscillators, arguing that the same engine — two EMAs applied in sequence — generalizes across the oscillator family. He then works through the practical interpretation: zero-line crossings, overbought/oversold thresholds, and especially divergence between price and oscillator, which he treats as the highest-value signal because it identifies waning momentum before the price reverses. The later chapters apply the indicators to futures and stock charts and discuss parameter selection — the lookback periods for the two EMAs — and how to test the indicators on a specific market rather than accepting default settings.
This is aimed at technical analysts, systematic traders, and active investors who already use oscillators and want a more rigorous, less noisy version. It assumes the reader is comfortable with EMAs, lookback periods, and basic chart interpretation.
The weaknesses are real. The book is narrow by design — it is a methods monograph on smoothing, not a complete trading system, so there is no risk management framework, no position sizing, and no edge testing beyond visual chart inspection. Visual chart inspection is itself a weak form of evidence; modern readers would want walk-forward backtests on out-of-sample data, and the book predates that standard. Divergence trading, which Blau elevates, is notoriously prone to hindsight bias — divergences are obvious after the reversal and ambiguous in real time. And the double-smoothing approach, while cleaner, still inherits the fundamental problem of all momentum oscillators: it works in trending and mean-reverting regimes differently, and the book does not give the reader a regime filter.
Worth reading for the technical analyst who specifically wants a better-engineered oscillator and is willing to do the testing work the book does not. Not a starting point for someone new to technical analysis.
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About William Blau
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