Chaotic Behaviour in Iran Foreign Exchange Rate Market

Chaotic theory suggests a new method for studying trends in markets and reveals the hidden pattern behind the data that common models can not define them. The usual tests for chaos are calculation of the largest Lyapunov exponent (Le) and strange attractors. A positive largest Lyapunov exponent indicates chaos. Positive amount of "Le" shows chaoticness of process and difficulty of predictability and when it is negative, it shows that process in the long run is non chaotic and predicable. If "Le" moves towards positive quantity near zero, chaotic system is weak and middle term predictability is possible. In this article, with regard to test of strange attractor and biggest Lyapunov exponent probability of chaos on several foreign exchange rates vs. IRR (Iranian Rial) from 1992/3/25 to 2007/5/23 and two artificial models with regard to the Takens embedding theorem have been investigated. Results show that data in this market have complex chaotic behavior with big degree of freedom, in addition; trend in Iran Exchange Market is not linear and we can not forecast it with common linear methods.