I will try to tweak this over the coming months and see if it has any value, but if anyone else better at working this out wants to try - and can factor in more sophisticated statistical analysis (standard deviation etc.) that would be good..
I think calculating the correlation coefficient will give you what you want. Expect it will be quite high.
I think a vague positive correlation might be present - but it has to be useful enough to be able to forward map reasonably well. it may involve 'bending time' by having an overlap that differs - making one XX month period longer or shorter against the other, fading sharper moves by averaging to a line of travel if a given % of change is over a certain ratio, or factoring in when certain MAs cross as start and end points for a range (when the halving comes etc.)
Basically any mathematically sound and constant fix that looks a better fit by playing with it over a decent long term period of the two comparable cycles that have - ostensibly - some key things in common because of Bitcoin's unique cyclical nature.
The drop from top to bottom seemingly correlates in percentage terms, for a start - so it's not a total wild goose chase.
It's not really my field, but I'll try and wrap my head around ways to work on it - then test (and back test) to see how I can get anything close enough. So far it 'looks' like we aren't moving as fast away from the bottom as in 2015 - because it was a sharper 'snap' down-and-up in '15 than from the last bottom. I need to look at correlations with opening price, closing price, high and low (or maybe weighted average) to see which (if any) are better fits as time goes on. Then see if I can work on and refine any promising factor so it gives me a better prediction. Daily may not be as close as three day candles etc.
So far I can only get data easily for daily historical data in CSV easily, so I shall hunt down other sources (I can get per minute historical data, too - but I am not sure it will help) I only want to see repeating patterns that occasionally will give a prediction with a
better than even chance correctly guessing likely direction and a rough price range within a range of + or - XX% in say XX days time +/- X days ?
If I can find anything close enough to be useful - or find no real correlation at all, it will be worth knowing. I hope I can learn something - even if it is just my own limits
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