Hi. Tricky math/data science question for a million dollar, for geniuses with iq 160+
We have 4 series of data - graphs that go somewhat randomly, we know that they are correlated and cointegrated, i.e. in some time frame they move almost the same/very similar - i.e. they go up/down together and move away and get closer to some reasonable distance, that's what we have calculated by the Johansen test, etc. (so it is almost 100% certain that they were and will be co-integrated and correlated) For example, the prices of similar / dependent commodities.01. The question: How do we find out that one of the graphs/price has moved significantly away from the others, but at the same time there is a high probability that the distance will no longer increase significantly and, on the contrary, it is taking the opposite course - that is, it is already starting to approach the other 3 graphs.
02. If we were to use classic percentages, and the distance in percentages, how do we calculate it since all values are dynamic?
constantly with each other are not static numbers. If we also normalize the graphs to the percentage normalized range 0-100, it is always for the selected time period, but by changing the time range-period, the proportions will also change and it will be scattered. At the same time, how do we determine which of the prices / graphs is overpriced and which is underpriced compared to the others?
03. If we enter a trade, how do we know that the deviation is sufficient and will not increase further? of course, we never know exactly, but how do we determine a statistically significant deviation and at the same time a statistically high probability that the deviation will no longer increase, but on the contrary decrease - so we can enter the trade.
well thank you, if needed we can communicate via e-mail, thanks
Martin