According to the description of Fractal Dimension Index:
Mandelbrot describes the Fractal Dimension Index (FDI) as a way to measure “how convoluted and irregular” something is. The FDI can be used as a stock market indicator.
We can look at prices in a market as “trending” or “ranging”. During a strong rally, prices trend sharply, sometimes approaching a one-dimensional straight line. And if we believe that prices should move in a more jagged fractal pattern, we would assume that the almost-straight movement will end at a point which we might be able to predict with a degree of accuracy sufficient to make a good trade.
After trending, prices often trade in a range for a while before embarking upon the next trend. Imagine prices trading in a rectangular pattern, zigzagging back-and-forth over the same points in a two-dimensional planar pattern. A plane isn’t a fractal any more than is a straight line, so we might expect prices to break out of the range and get back to acting like a fractal.
And so, the FDI is a method which assigns a number to the line on your chart. The number will be between 1.0 and 2.0. The closer prices move in a one-dimensional straight line, the closer the FDI moves to 1.0. The more closely prices resemble a two-dimensional plane, the closer the FDI moves to 2.0.
This version is made exactly as described by the original inventor of FDI (Carlos Sevcik) with one correction: the formula that Sevcik published is inverted. The error was corrected by Alex Matulich and this version is using the correct calculation.