Technical analysis is a field in which there is always an ambition to smooth signals for instance stock price data to reduce their noise. This smoothing is performed with a moving average. A simple 10-day moving average of closing prices is the mean of the previous 10 days closing prices. Without smoothing indicators raise more erroneous signals because of noise in the stock signal. Moving averages are not only used on price movements in the models, but also on other internal signals.
Even better results are obtained if the smoothing is adapted to the behaviour of stock prices. If the price suddenly is moving determined in a certain direction, the smoothing can temporary be decreased to shorten lag and lessen undershoot. This is the principle of adaptive moving averaging.
A Comparison between different moving averages :
The exponential moving average is sometimes too slow, which produces unwanted lag, and sometimes too fast, moving too much when there is no noise. The Kalman filter performs better most of the time, but produces erroneous peaks which may result in erroneous signals by the indicator using the filter.
OptAMA, Optimal Traders Adaptive Moving Average, is trying to fulfill the demands in the best possible way. It reacts fast to price gaps, does not lag and smoothes noise efficiently. In every aspect OptAMA is better than other moving averages.
