| You plot a straight line, taking all price and time points for the past 60 days (trend), fitting the line by minimizing the sum of squares between the actual price and the "trend line" ("least squares" fitting), then you calculate volativity in a standard way again - Average of (price -trend)^2 - (Average of (price -trend))^2 = sigma^2, where sigma is the volativity (again, a standard way to estimate the error if you fit to a line). Then you use a random walk with volativity sigma around the trend to describe it. That's a bit of "rocket science", using the words like "Wiener process", etc. And then again, random walk does not describe these markets, IMHO, but is very close. But the result is simple. Roughly, price deviation from the trend line then is sigma x squareroot(time), there is some coefficient in front of sigma sqrt(t), which gives 95% probability, so you draw the random walk "fan" around the trend line. A bit of "rocket science", but then again, I teach it -g- |
