2021/03/24 by Luke De Clerk, De Clerk, Luke, Sergey Savel’ev +1
Decision Sciences · Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #Econometrics (econ.EM) #FOS: Economics and business #Financial Risk and Volatility Modeling #Market Dynamics and Volatility #Stock Market Forecasting Methods
paper · pdf · doi:10.48550/arxiv.2103.13199
openalex publication_date 2021/03/24 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Here, we analyse the behaviour of the higher order standardised moments of\nfinancial time series when we truncate a large data set into smaller and\nsmaller subsets, referred to below as time windows. We look at the effect of\nthe economic environment on the behaviour of higher order moments in these time\nwindows. We observe two different scaling relations of higher order moments\nwhen the data sub sets' length decreases; one for longer time windows and\nanother for the shorter time windows. These scaling relations drastically\nchange when the time window encompasses a financial crisis. We also observe a\nqualitative change of higher order standardised moments compared to the\ngaussian values in response to a shrinking time window. We extend this analysis\nto incorporate the effects these scaling relations have upon risk. We decompose\nthe return series within these time windows and carry out a Value-at-Risk\ncalculation. In doing so, we observe the manifestation of the scaling relations\nthrough the change in the Value-at-Risk level. Moreover, we model the observed\nscaling laws by analysing the hierarchy of rare events on higher order moments.\n