Political risk modelling and measurement from stochastic volatility models

Abstract

The past decades have seen an unprecedented global rise in unforeseen political events, which have led to social unrest, economic declines and a renewed interest in political risk modelling. Whilst continuous time financial models have been developed for a range of risk factors, there is currently no method for political risk modelling. In this paper we propose a new model for political risk modelling; to the best of our knowledge this is the first model for continuous time stochastic volatility models. We derive a method for obtaining political risk states from a continuous time stochastic volatility model, and our model enables us to derive the evolution of political risk states over time. We derive two important properties of our political risk model: we find a solution for the characteristic function and prove weak convergence. Next, we derive a method for calculating standard risk measures for our political risk, namely Value at Risk, variance, moments, as well as upside and downside risk measurement. We also provide numerical experiments to illustrate our results.