We will briefly introduce to the theory of time series. We will take into account the USD/TRY currency taked from Borsa Istanbul. Our aim is to determine whether there is a difference on the interval which is before crisis and after crisis. To do this, we will divide all dataset into three part, then consider each part on itself. We suggest to use the log return anlaysis for further the statistical tests and calculations. We build a new dataset which consist of weekly log return data. After we use the decompose function in R programming to split trend, seasonal and resudial component for the new dataset, we introduce to ARIMA model for the residual dataset. Then we again build a new data set which is consist of monthly variance,called risk for our problem, from weekly log return dataset. In order to decide if there is a statistically significance difference between the difference time interval, we regard the Kolmogorov's Smirnov test and Mann-Whitney test. We will use the R programming language for all application progresses.
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