Investigation of chaotic behavior in Euro-Leu exchange rate

Abstract

Nonlinear time series analysis developed a set of testaiming to discover a possible occurrence of chaos in time seriesunder study. The main benefit of detecting chaos is that the timeseries is short term predictable. The prediction accuracydecreases in time. A strong evidence of chaotic dynamics is theexistence of a positive Lyapunov exponent (i.e. sensitivity toinitial conditions). Usually this is not the ultimate test that has tobe performed in order to decide that the evolution in time of thetime series is chaotic. Chaotic dynamics is associated with achaotic attractor. In order to reveal the structure of theattractor, the Takens reconstruction theorem has to be applied.The paper aims at presenting a methodology to be followed todetect (or not) chaos presence in the Euro-Leu exchange ratetime series.

Keywords

• Chaos Theory
• Nonlinear Time Series Analysis
• Chaos Identification
• Chaotic Dynamics