There are N data sets in periods occurring weekly/monthly, across a 10-year historical timeline.
In each period, five dates are observed (labelled a to e), where a denotes the day the period starts/an event occurs (T=0), while b to e denotes subsequent days following the event (T = 2 to 4).
An illustration is created to better understand how the components are structured and fed into the formulae for statistical inference.
Question: Is there a method to elicit principal components from the N data sets, and also find correlation?
P.S. This model intends to observe events/numbers (e.g. in the economic calendar) occurring weekly and monthly that affects changes in market prices.