The standard Bolling Bands assumes a normal distribution. However, a normal distribution is an incorrect model for stock prices. This is because stock prices cannot fall below zero. If we assume that the percentage return follows a normal distribution, then a lognormal distribution is a more accurate model.
This is why I've transformed the standard deviation using the log function. It's much more useful for stock prices that have a low value and high volatility.
This is why I've transformed the standard deviation using the log function. It's much more useful for stock prices that have a low value and high volatility.
Notes de version:
The standard Bolling Bands assumes a normal distribution. However, a normal distribution is an incorrect model for stock prices. This is because stock prices cannot fall below zero. If we assume that the percentage return follows a normal distribution, then a lognormal distribution is a more accurate model.
This is why I've transformed the standard deviation using the log function. It's much more useful for stock prices that have a low value and high volatility .
This is why I've transformed the standard deviation using the log function. It's much more useful for stock prices that have a low value and high volatility .