Liquidity analysis and prediction in the processing industry by applying VG process: The case of the Czech Republic

Abstract

This paper is devoted to liquidity analysis and prediction possibilities in the processing industry in the Czech Republic. The objective of this paper is to propose and apply pyramidal decomposition of the current liquidity ratio time series of the processing industry in the Czech Republic. Further, we analysed the primary factors affecting liquidity ratio evolution and predicted a two-year probability distribution of the current liquidity ratio by applying the variance gamma process. In the paper, we identified four main factors, which influence liquidity in the processing industry in Czech Republic. Based on these findings, we modelled probability distribution of the liquidity for the period 2016 and 2017 with respect to the empirical distribution. It was shown that when Gaussian distribution is used, the risk is undervalued especially for heavy tails (extreme values) of the probability distribution.