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 estimate a general microstructure model of the transitory and permanent impact of order flow on stock prices. Jumps are detected in both the transaction price (observation equation) and fundamental value (state equation). The model's parameters and variances are updated in real time. Prices...

Markov models introduce persistence in the mixture distribution. In time series analysis, the mixture components relate to different persistent states characterizing the state-specific time series process. Model specification is discussed in a general form. Emphasis is put on the functional form...

Using a Markov switching unobserved component model we decompose the term premium of the North American CDX investment grade index (CDX-IG) into a permanent and a stationary component. We explain the evolution of the two components in relating them to monetary policy and stock market variables....

Using a Markov switching unobserved component model we decompose the term premium of the North American CDX investment grade index (CDX-IG) into a permanent and a stationary component. We explain the evolution of the two components in relating them to monetary policy and stock market variables....

Using a Markov switching unobserved component model we decompose the term premium of the North American CDX investment grade index (CDX-IG) into a permanent and a stationary component. We explain the evolution of the two components in relating them to monetary policy and stock market variables....

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...