For UK alone, I have looked at 8 different financial statistics series, covering allshare equities, long conventional gilts and long indexlinked gilts. Each had a return over 1 year and a yield, making 6 so far. There are also 2 inflation series, over 1 year and over 15 years, making 8 in all. As RPI has a longer true data series than for CPI or CPIH, I have stuck with RPI.
The financials have been modelled annually from end1953 until end2018 and end2019 (“2014” was used for my original 2017 DWP submission). For end2019, I have then split the data between end1953 until end1984 (“early”) and end1985 until end2019 (“later”), taking account of when indexlinked gilts became a more mature market. The base data used are summarised for means and standard deviations. The generated random numbers are explained here.
Because there were no data for the earlier period, the long indexlinked gilts have only been modelled for the later period. Any comparisons involving indexlinked gilts are really meaningful for 19852019 alone.
We have 4 experiences, namely “2018a” (19532018), “2019a” (19532019), “early” (19531984) and “later” (19852019). For each period, the random values have been adjusted to have the same mean and standard deviation as the base data.
A simplified “twin regime” approach was then used to build two further experiences, taking the “early” values 25% of the time and the “later” values 75% of the time. This is NOT the same thing as just weighting the values 25:75. So “2019b” takes those values and adjusts the mean and standard deviation to the base data for 1953 through 2019, while “2019c” omits that adjustment exercise. Using different names, they are mapped as follows:
19531984 Early_2019 19852019 Later_2019 19532018_a Whole_2018 19532019_a Whole_2019 19532019_b Twin_2019_Whole 19532019_c Twin_2019_Indiv
