How Does the Volatility of the Markets Change Through Time?
Using Autocorrelation Functions to Describe Non-Stationarity in Volatility with Self-Similarity
In my previous article I exhibited how, year-by-year, the variance of market returns doesn’t seem to take on constant values. I showed that the observed sequences of variance ratios for the returns of the S&P 500 Index are incompatible with the idea that they represent sequential, but noisy and therefore different, measurements of the same quantity! That article is linked to below.
It’s true that the tests presented, which examine how one year’s estimates compare to the next one from 1928 to date, are somewhat arbitrary. Why one year, not two, or four, or six months? Why start on the 2nd. of January and end on the 31st. of December, perhaps some other choice of groupings would deliver a different result.
These are valid criticisms but, I don’t think, undermine the key result. If the variance were stationary it would not fail any of these tests, no matter how the time…
