An investigation of higher order moments of empirical financial data and their implications to risk.

ABSTRACT: Here, we analyse the behaviour of the higher order standardised moments of financial time series when we truncate a large data set into smaller and smaller subsets, referred to below as time windows. We look at the effect of the economic environment on the behaviour of higher order moments in these time windows. We observe two different scaling relations of higher order moments when the data sub sets' length decreases; one for longer time windows and another for the shorter time windows. These scaling relations drastically change when the time window encompasses a financial crisis. We also observe a qualitative change of higher order standardised moments compared to the gaussian values in response to a shrinking time window. Moreover, we model the observed scaling laws by analysing the hie

SUBMITTER: De Clerk L 

PROVIDER: S-EPMC8841368 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature