V.10:10 (416-419): Phase Transitions by Christopher K. Smith

Phase Transitions by Christopher K. Smith

Here's a concept to visually compare an indicator's historical profitability over a range of parameters simultaneously with the indicator's current standing, allowing the trader to identify those trading signals that have been historically profitable.

Market technicians use technical indicators to help clarify some aspect of market behavior. For example, the price moving average helps clarify the longer-term trend of the market while eliminating shorter-term noise. One problem that arises in using indicators, however, is that it is often difficult to separate the signal being given by the indicator from the noise. Traditionally, traders have sought to eliminate noise from indicator signals through manipulation of the indicator's parameter values . For example, if the moving average is producing whipsaw signals, the parameter length is increased. Conversely, if the indicator's signals are lagging the market, the parameter length is decreased. The problem with this approach is that it is often difficult to determine which parameter values are best for trading a given market. This can be solved by searching for key indicator changes called phase transitions.

Phase is calculated as the distance of an indicator above or below a median point (often a zero point). Phase transitions occur when an indicator moves through the center of their value ranges. Understanding phase transitions begins with an understanding the phase of an indicator. For the simple moving average, phase may be defined as the distance of the closing price above or below a given moving average. Thus, the phase is positive when price is above the moving average and the phase is negative when price is below the moving average. Phase may be calculated for nearly any indicator. (See sidebar "Indicator phase" for a discussion of potential methods to calculate phase for a variety of indicators.) Searching for significant phase transitions in the market helps extract important signals from an indicator while ignoring the noise. Searching for phase transitions also helps clarify the overall state of the market by examining indicator action over a variety of time frames.