Got enough time to throw this together. I don’t know how it’ll turn out but I think this is the best I can do for now. There’s the semi-martingale strategy that could be added to this which will require a different dimension (also huge potential) but I want to look at the base first to see what the numbers look like.
I’m not very good with coming up with creative names so I’ll just be calling this MTF recurrence.
1. Find every transient price for h>1 [then max(left h, right h)]
2. For all such prices, find min h value to meet “Fx-Jay” recurrency.
3. Freq Dist. all these values to find min h value to achieve min h value.
4. Complete the above 3 steps for TFs 15m, 30m, 1hr, 2hr, 3hr, 4hr, 6hr, 8hr, 12hr, D1, W1.
5. Create wave sequences for all frames. Leave out the issue of double tops/bottoms for now.
6. Create statistics for 3 wave and 5 wave direction probabilities.
7. Create dashboard to monitor direction bias across time frames.
I’ve completed all these steps before over the past few months, but only for 1 time frame. My biggest fear atm is that the results won’t give a good skewed distribution of wave probabilities. The ones that I came up with for H1(shown in earlier posts) were quite good. I ran a quick test for a lower time frame and they converged a bit more towards 50%. If I’m lucky it will be that way because the h value used was incorrect. In other words, there is a very realistic possibility that the correct h value to achieve 97% recurrency and the correct h value to create maximum skew in wave probabilities are two different values. Luckily for me, I already have 1 basis point of wave probabilities so if it’s twin is way off, then I will know I’m wrong. The problem then will be on how to go about fixing it. (note: big problem)