Just wanted to briefly drop by to gently announce (I think the kids call it a "humblebrag") the success of the Double-Slit Indicator over the past year. As some of you know, there's been a lot of trial/error seeking ways to exploit the uncertainty principle in ways that could be implemented on time series.

Well, the DSI continues to accurately predict the 1- or 2-bar price direction without any errors. The one hiccup, close to being solved, is whether the output is for either 1 or 2 bars out -- the direction is always correct, but there is 50% accurancy so far on the n+ bars target. I've been testing whether taking the 2-bar position works, except it doesn't when DSI meant 1. I'm close.

This is as close to a Grail as there is, IMHO and all that. Anyway, probably oversharing, but hey, yolo, like also the kids say.

Yes, understood. The solution works for what I need. Thank you.

Our posts crossed each other. I think the solution is what I need. Thanks so much, Bruce. Hope all's well.

To clarify, I use the formula above typically on Daily timeframes. However, I would like to calcuate in minutes (or some shorter timeframe) the bars elapsed since the signal. Thank you.

Hello.

How can I output a bars-ago count in minutes for this red-to-green indicator:
 

Thanks, Bruce. I understand and I know the idea was not feasible. Thanks for taking a look. I really appreciate it.

It's the "turned green" component of the DSS. Your "turned red" version is exactly correct -- I just tested. Many thanks, Bruce. I needed this for an alert.

Hello. 
I use the following for a red-to-green indicator:

XAVG((XAVG(STOC10, 5) - MIN(XAVG(STOC10, 5), 10)) / (MAX(XAVG(STOC10, 5), 10) - MIN(XAVG(STOC10, 5), 10)), 5) > XAVG((XAVG(STOC10.1.1, 5) - MIN(XAVG(STOC10.1.1, 5), 10)) / (MAX(XAVG(STOC10.1.1, 5), 10) - MIN(XAVG(STOC10.1.1, 5), 10)), 5) AND XAVG((XAVG(STOC10.1.1, 5) - MIN(XAVG(STOC10.1.1, 5), 10)) / (MAX(XAVG(STOC10.1.1, 5), 10) - MIN(XAVG(STOC10.1.1, 5), 10)), 5) <= XAVG((XAVG(STOC10.1.2, 5) - MIN(XAVG(STOC10.1.2, 5), 10)) / (MAX(XAVG(STOC10.1.2, 5), 10) - MIN(XAVG(STOC10.1.2, 5), 10)), 5)

What is the green-to-red version, please? 

Thank you.

Thanks, Bruce. I am familiar with how stock data in particular is typically both nonormal as a characteristic and also the normality assumption / sample size relationsip. I&#39;m also generally aware of how often Gaussian models are described as inadequate for describing significance in market returns. I think lognormal would work too, but I am not after that yet.

I&#39;m trying something atypical by seeking a way to measure normality, even in non-lognormal ways. I think possibly some tickers actually might have Gaussian distributions even when the general returns for the universe typically are not. I don&#39;t know what the reason for this is, but I have some thoughts, and I do think that reason is causal. Volatility as a factor is more normally distributed than return prices.

My hope in forcing an normal-distribution evaluation on all tickers is that it would make those with that hidden characteristic filter to the top where I could do some additional testing on them. 

Before trying anything, a question: is it possible to use whatever normality test for evaluating volatility itself and not returns?