Stocks & Commodities V. 32:4 (28-30): Expansions & Contractions, Part 2 by Dirk Vandycke
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Expansions & Contractions, Part 2 by Dirk Vandycke
Divergence Of The Fittest
In the first part of this three-part article series, we found out how to measure intrinsic divergences. In this second part, we will identify divergences that take place when price may appear to be strong but has a tendency to close near the lows.
The concept of divergence is nothing new. When one indicator behaves differently than another, it sometimes suggests that a change in trend is about to take place. Technical analysis is all about measuring probabilities rather than forecasting. Because of this, it is difficult to quantify concepts such as divergence. Most attempts get stuck in an algorithmic approach that tries to capture specific graphical setups. This ends up giving you mediocre results. In this article, I will provide a statistical framework that results in an indicator you can use to measure divergences.
WHAT IS DIVERGENCE?
In part 1, I talked about measuring intrinsic divergence, which measures divergence within one time series as opposed to the more popularly used divergence between different time series. On a normal price chart you won’t see intrinsic divergence, but the divergence between different time series — which I refer to as extrinsic divergence — is something you can see on a chart. It may, however, lag, and it’s difficult to detect algorithmically.
Divergence Of The Fittest
In the first part of this three-part article series, we found out how to measure intrinsic divergences. In this second part, we will identify divergences that take place when price may appear to be strong but has a tendency to close near the lows.
The concept of divergence is nothing new. When one indicator behaves differently than another, it sometimes suggests that a change in trend is about to take place. Technical analysis is all about measuring probabilities rather than forecasting. Because of this, it is difficult to quantify concepts such as divergence. Most attempts get stuck in an algorithmic approach that tries to capture specific graphical setups. This ends up giving you mediocre results. In this article, I will provide a statistical framework that results in an indicator you can use to measure divergences.
WHAT IS DIVERGENCE?
In part 1, I talked about measuring intrinsic divergence, which measures divergence within one time series as opposed to the more popularly used divergence between different time series. On a normal price chart you won’t see intrinsic divergence, but the divergence between different time series — which I refer to as extrinsic divergence — is something you can see on a chart. It may, however, lag, and it’s difficult to detect algorithmically.
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