ENTROPY INDICATORS FOR AN ESTIMATION OF CURRENCY RISKS

Abstract

As the world’s largest by-turnover financial market, foreign exchange market is undoubtedly an open, dynamic system. A wide range of variables influence it, i.e., political and economic factors, global shocks. Simultaneously, currency distress also affects the countries’ financial and real sectors. It determines the crucial importance of maintaining a stable, predictable exchange rate and, in the opposite case, effective currency risk management, requiring proper measurement. Since statistical methods of currency risk assessment do not always guarantee a reliable reflection of potential threats due to the noise in financial time series or irrational agents’ behaviour, it is necessary to search for alternative risk measurement methods. One way is by using tools of the theory of dynamic nonlinear systems, namely entropy indicators, such as Shannon and Renyi. Because of the high economic, or rather trade, openness, besides the hryvnia itself, we investigated currency fluctuations of the leading imported markets for domestic products. The reason is the potential transmission of shocks from these countries to Ukraine via various mechanisms. Counter-intuitively, a high entropy, implying more significant uncertainty, complexity, and unpredictability, simultaneously indicates more mature, efficient, self-organized systems. In contrast, lower entropy values would indicate inefficient markets exposed to shocks and even bifurcations, particularly crises. Moreover, we propose considering entropy as a reliable indicator of risks based on the statistical and economic significance of correlation coefficients with other qualitative characteristics of distributions of exchange rate returns - skewness and kurtosis. The results may help investors and portfolio managers better understand exchange rate dynamics, make effective managerial decisions, and minimize losses from unfavourable volatility.