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 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. Searching for significant phase transitions in the market helps extract important signals from an indicator while ignoring the noise.