Evaluation of derivatives impact to early systemic risk of Euro area

Abstract

The country’s systemic risk has become a fairly widely discussed topic since the global financial crisis of 2008. There is a growing interest among researchers in the development of an Early warning system that helps to assess the relationship between an independent variable for the current period and a dependent variable for a future period. Such models can be used to as early warning of the level of the country's systemic risk, and may help to take early actions to prevent or decrease the impact of systemic crisis. Evaluation of systemic risk is very complicated, as it is difficult to accurately predict the extent of the links between various institutions, and the possible spread and scale of the country's systemic risk. In addition, the country's systemic crisis is affected by many factors, many elements of the financial system. Financial derivatives are one of many elements of financial system, and the market of financial derivatives is huge compared to other financial instruments. The impact of financial derivatives to economies of various countries has been widely studied, however, the research on their impact to countries‘ early systemic risk remains under-researched. For this reason, assessment of the impact of derivative financial instruments on the early systemic risk is very relevant. Aim and tasks. The purpose of the article is to assess the impact of financial derivatives on the country's early systemic risk in the Euro area region. Results. It is shown that correlation fluctuates between weak-strong level, when analyzing relationship between various factors of financial derivatives and early systemic risk in the Euro area. Results of linear regression analysis prove that the group of financial derivatives independent variables (interconnection, size, liquidity, complexity, stability, leverage) can be used to reliably estimate the dependent variable (early systemic risk). Logistic regression analysis also provides similar results to the linear regression analysis. Additionally, it is shown, that logistic regression is more suitable to analyze impact on early systemic risk. Analysis of impact of individual financial derivatives factors to early systemic risk demonstrate, that three financial derivatives factors – size, complexity, and leverage – may be the best predictors of an impending systemic crisis. Among these factors, the size factor has the largest impact on early systemic risk of the Euro area, and complexity factor shows improved statistical parameters, which indicates, that this parameter is more suitable to be used in early warning system models.