Category: Advanced Indicator Set 1

Input parameters

Calculations

HMax = MaxList(Max(High, Close[1]), Period)

LMax = MinList(Min(Low, Close[1]), Period)

Choppiness = 100.0 * Log(Sum(TrueRange,Period)/(HMax -LMax)) / Log(Period)

where:

Close[1] is Close one bar ago,

Max(a,b) is the largest of a and b,

MaxList(a,N) is the largest a in N bars back,

MinList(a,N) is the smallest a in N bars back,

Sum(a,N) is the sum of a over N bars back,

TrueRange is True Range.

Discussion

Developed by E.W. “Bill” Dreiss (a commodity trader currently living in Australia), the Choppiness Index indicator is deemed to measure something akin to the fractal dimension of the time series during the most recent Period bars. According to fractals theory, the fractal dimension of two-dimensional objects can be anywhere between one (a straight line) and two (a geometric plane). A “random walk”, i.e. a line connecting points with totally random coordinates, has fractal dimension of 1.5.

Dreiss constructed his Choppiness Index so it varies on the 0-100 scale. The basic idea is that when the market was heavily trending during the past Period bars (the time series has the form almost of a straight line), the fractal dimension is close to one and the Choppiness Index is around zero. When the market did not trend (the market is “choppy”), the fractal dimension is close to 1.5 and the Choppiness Index is around 100.

In other words, the Choppiness Indicator can be viewed as an indicator measuring the market‘s trendiness (the output is well below its average on the chart) versus the market’s choppiness (the output is well above its average on the chart). For trendy markets the indicator, however, does not show the direction of the trend.

References

1. Dreiss, Bill, The Fractal Wave Algorithm, Charts And Systems, Commodity Traders Consumer Report, July/August, 1992.