Two-Regime Threshold Autoregressive Model Simulation

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This Demonstration allows you to study realizations from a two-regime threshold autoregressive (TAR) process of the first order by changing its parameters. The two-regime TAR(1) model is represented by:
Parameters are initially set to
,
, and
to obtain the following two-regime TAR(1) process:
Note that the process is stationary and geometrically ergodic despite the coefficient -1.5 in the first regime. The series contains large upward jumps when it becomes negative (due to the -1.5 coefficient) and there are more positive than negative jumps. The model also contains no constant term, but
is not zero.
Contributed by: Jozef Barunik (March 2011)
Open content licensed under CC BY-NC-SA
Snapshots
Details
The TAR model is motivated by empirically observed nonlinear characteristics such as asymmetry in declining and rising patterns of a process. It is used for financial time series modeling. The model uses a simple threshold to improve linear approximation.
More information about TAR processes can by found at:
R. S. Tsay, Analysis of Financial Time Series, New York: Wiley, 2001.
Permanent Citation
"Two-Regime Threshold Autoregressive Model Simulation"
http://demonstrations.wolfram.com/TwoRegimeThresholdAutoregressiveModelSimulation/
Wolfram Demonstrations Project
Published: March 7 2011