I have a daily time series data spanning over 22 years. I need to compute some meaningful yearly standard deviation statistics / generate probability distribution and estimate tail risk. 22 years obviously is not enough, so was wondering about perhaps generating overlapping 1-year change time series and analyzing the daily change in it - that would give me around 5200 observations. Struggling a bit on how to interpret the distribution that I generated - it appears to be a daily change of the yearly change, so was wondering if it could be used at all or if there is a better way to use overlapping data?
Thanks a lot for the inputs,