This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...

We calculate impulse response functions from regime-switching models where the driving variable can respond to the shock. Two methods used to estimate the impulse responses in these models are generalized impulse response functions and local projections. Local projections depend on the observed...

We propose a new time series model where the threshold is specified as an empirical quantile of recent observations of a threshold variable. The resulting conditional threshold traces the fluctuation of the threshold variable, which can enhance the fit and interpretation of the model. In the...

Estimating Limited Dependent Variable Time Series models through standard extremum methods can be a daunting computational task because of the need for integration of high order multiple integrals and/or numerical optimization of difficult objective functions. This paper proposes a classical...

We investigate the information theoretic optimality properties of the score function of the predictive likelihood as a device to update parameters in observation driven time-varying parameter models. The results provide a new theoretical justification for the class of generalized autoregressive...

The topic of this chapter is forecasting with nonlinear models. First, a number of well-known nonlinear models are introduced and their properties discussed. These include the smooth transition regression model, the switching regression model whose univariate counterpart is called threshold...

We propose a more flexible range-based volatility model which can capture volatility process better than conventional GARCH approach. Considering the regime switching process is appropriate for dealing the structure change embedded in the time series data. Range-based volatility CARR model with...

We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under...