Understanding Max Iwamoto's "Bollinger Bands" Part 3 [Max Iwamoto]

Max Iwamoto Profile

Keisuke Iwamoto. As the nickname “Technical Analyst with a middle-school diploma,” he is a rare no-education analyst in the industry. Even in these days where educational background still heavily matters, he fights daily against the FX market, which is unrelated to such things. With the feeling of “now that anyone can start FX easily, I want you to acquire skills that can keep you winning steadily,” he serves as a columnist and seminar lecturer.

Meter by squaring the deviation is the key to standard deviation

Last time, we touched on the overview of standard deviation and the shortcomings of mean absolute deviation, which are essential for understanding Bollinger Bands. To briefly recap: mean absolute deviation is one way to measure data dispersion, but when calculating dispersion of different data sets, even if the mean absolute deviation value is the same, the data dispersion is not necessarily equal. Therefore, for more detailed data dispersion, standard deviation is more appropriate. However, since we did not cover the calculation process of standard deviation at all, this time we will explain that point in detail.

Continuing from last time, we will discuss a topic that at first glance has nothing to do with trading, but whether you understand this or not will make a big difference in how you view and utilize Bollinger Bands, so please read to the end.