Spy Tomorrow July 2022 Update

This update has been a month in the making. Some of you have noticed the adjustments throughout June. We’ve made a lot of progress with the addition of new panels which help us with our spy/market predictions. We are SPY tomorrow, however, QQQ and IWM also play a prominent role.

July 2022 panel set.

A new video will be out July 1, updating the explanation of the panels, plus, I’ll have a cheat sheet listed below the example. The core numbers I use for predictions are Purple (s) alone; Purple, Orange, Blue (L) row best 2 of 3; Spy, IWM, QQQ (L) row best 2 of 3. I’ve moved a few panels around, most of the panels are the same.

You will also notice that on the member’s pressure reading prediction page I only show the panels. The data has been moved to its own results data page, which will most likely expand over time. This move will keep the prediction panel page cleaner. All the data will not be archived, however, the panel used for prediction will continue to be placed in the insider archive.

New Gauges

I’m adding new ways to view and use the data. Gauges are a new option. There are two gauge pages. The most important one is the one below. It’s the core set of Gauges for a quick view of how the prediction is being made.

The top left is the confidence level of the prediction. 3 or higher seems to offer the best track record. Then you have the Solo Purple (s), and next to it is the market Switch which the underlying market pressure mood.

The second row is the POB best 2 of 3 and the third row is SIQ best 2 out of 3. There is also an all gauges page with includes most of the panels.

I hope to keep this approach and panels steady for a while. There is not much more I can do to improve the way the machine works. However, I can still replace modules to help improve accuracy behind the scenes. I’ll announce it if that is the case. Currently, the three modules (Purple, Orange, Blue) still hold out as the strongest in the latest round of testing (April – June).

The next biggest step is to develop this data for real-time presentation. I sometimes use the data during the day and it’s very helpful. However, this will be an expensive process and will take time and money.