  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. We extend this analysis
to incorporate the effects these scaling relations have upon risk. We decompose
the return series within these time windows and carry out a Value-at-Risk
calculation. In doing so, we observe the manifestation of the scaling relations
through the change in the Value-at-Risk level. Moreover, we model the observed
scaling laws by analysing the hierarchy of rare events on higher order moments.
