Today, David Varadi of CSS Analytics presented another interesting new indicator: the MAC-Z score.

See his original post:

The Relationship Between the MACD and Z-Score: Creating the MAC-Z score

QUOTE:
Effectively the Z-score is the difference between the current price and a moving average divided by the standard deviation of price over the same time period. (...)

MAC-Z= (Z-score, 25)*A+ (MACD,25)/(Stdeva,25)*B

where A and B are constants that can range between 2 and -2 in .2 increments to reduce computational time.

Here we go (demo requires Community.Indicators):

MAC-Z pullback system

Just a comment. Combining a moving average regressive term, z-score, and price velocity, MACD, both normalized to a measure of volatility makes sense. One can experiment with the weights, but I have intuitive trouble arguing for anything but equal weight.

What really causes me difficulty is the recommended argument of negative weight for the regression term and a positive weight for the trend term.

The only way the indicator makes sense for me when correlated against price moves and on an intuitive level, is the positive and equal weight scenario.

The magnitude of the weights is only a matter of scale, the ratio is what matters in practice.

It is also useful to note that there is fundamentally no difference between the two terms. Both are regressive, it's just that one has a long period and one a short. The A term, z-score, is the short period regression, the difference between high frequency price and a moving average. The B term is the long period regression, the difference between a fast MA and a slow MA, same thing, just different period view.

I will also note that I find it to be a very useful complement to other indicators.

If anyone has some intuitive insight into positive and negative weight combination, please respond.