We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to...

The volatility of growth in U.S. real GDP declined dramatically in the mid-1980s. Viewed through the lens of linear autoregressive models, this phenomenon appears to be the result of a structural break in the innovation process that drives GDP fluctuations. We present an alternative model that...

Using Gretl, I apply ARMA, Vector ARMA, VAR, state-space model with a Kalman filter, transfer-function and intervention models, unit root tests, cointegration test, volatility models (ARCH, GARCH, ARCH-M, GARCH-M, Taylor-Schwert GARCH, GJR, TARCH, NARCH, APARCH, EGARCH) to analyze quarterly time...

In this paper I explore the informational content in cross-currency flow maintained by large custodian banks with an objective to design a statistical arbitrage trading system that could exploit such information. After an initial simple test involving one-step ahead forecasts for JPYUSD FX pair...

We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to...

Koop, Pesaran and Smith (2011) suggest a simple diagnostic indicator for the Bayesian estimation of the parameters of a DSGE model. They show that, if a parameter is well identified, the precision of the posterior should improve as the (artificial) data size T increases, and the indicator checks...

This paper conducts an empirical analysis of the heterogeneity of recessions in monthly U.S. coincident and leading indicator variables. Univariate Markovswitching models indicate that it is appropriate to allow for two distinct recession regimes, corresponding with 'mild' and 'severe'...