Treshold models for financial time series

In modeling of financial time series is widely accepted ARCH model with conditional heteroscedasticity, but this model is not able to operate with other non-linearities such as leverage or asymmetry (the volume of revenue is different when the yield is positive or negative). Therefore, we work in this thesis with threshold models TAR, TARCH and DTARCH. These models have piecewise linear conditional mean and DTARCH model even piecewise linear conditional variance. The main utility of threshold models is further specified test of threshold nonlinearity, which is the base for comprehensively defined procedure of determining the type of model, including an estimate of all its parameters. At the end, the procedures introduced in this text are demonstrated using simulated and real data. Powered by TCPDF (www.tcpdf.org