Bootstrap solutinons for time series

Bootstrap methods are popular computer-intensive data resampling methods which are not only generally in use for statistical analysis but also are applied for economic and econometric analysis. Although they were originally developed for independent and identically distributed data, in recent years several bootstrap methods have been adapted to time series. In this study gives a framework of up-to-date coverage for different kinds of bootstrap methods and bootstrap methods developed for autoregresive (AR) models for time series analysis. The offered procedure and the main line bootstrap methods are describe in second chapter. In third chapter, offered data X* and usual X data are compared with data derived from bootstrap, an application is given about stock prices.