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OptAMA
Optimal Trader Adaptive Moving Average

Optimal Trader is using an in-house developed adaptive moving average filter for most indicators. OptAMA, Optimal Trader Adaptive Mean Average filter, reacts fast on major price changes and smoothes noise efficiently in stock data. The results are clearer signals in many models and fewer erroneous signals when the trend is uncertain. Trading signals are raised consistently earlier which is important in sudden upward or downward movements, since the largest price differences often take place early in these phases.

 

Introduction

In the field of Technical Analysis there is 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.

The use of moving averages eliminates some of the noise, but it does so on the cost of a time delay (lag). The more the stock signal is smoothed, the larger the time delay becomes. For example, a 10 day's moving average has a lag of about 5 days. This has a major impact on your trading decisions because they will always lag 5 days.

As the chart above shows another drawback is that it takes time for the moving average to converge back to normal levels when sudden major price changes have occured. Indicators using moving averages are not reliable while the mean average lags behind.

 

Historical Development

Using exponential moving averages results in slightly less amounts of lag because newer stock prices are valued more than older stock prices. Thus a change of trend is noticed slightly earlier by an exponential moving average than by an ordinary mean average.

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. The first and most famous adaptive moving average filter in the field of signal processing is the Kalman filter (Rudolf Kalman, 1960) and in technical analysis Kaufmanns Adaptive Moving Average (Perry Kaufmann, 1995) has served as guidance.

 

A Comparison between Different Moving Averages

The chart above highlights several undesirable properties of moving average filters. 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.

Wrapping it all up there are four conflicting demands on an ideal moving average:

• Minimum lag, otherwise trading signals are raised late.
• Maximum smoothness, except at price gaps, otherwise erroneous trading signals will be triggered.
• Minimum undershoot at price gaps, otherwise it will take unnecessary time to converge to the new price level.
• No overshoot, distortion of the signal produces false price levels resulting in false trading signals

 

OptAMA - Optimal Traders Adaptive Moving Average filter

OptAMA, Optimal Traders Adaptive Moving Average, is trying to fulfill the above 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. Compare the smoothing of OptAMA of the price movement below to an exponential moving average with the same smoothing strength.

Another unique feature of OptAMAs implementation in Optimal Trader is that it is separately fine-tuned for every model. The consequence is that OptAMAs characteristics differ a little between the models in Optimal Trader.

Because of the unique features of OptAMA we can't reveal the technology behind OptAMA. If you are interested in using OptAMA as a seperate function outside of Optimal Trader, i.e in Excel, please for a price.