In this paper we argue that measured (RPI) inflation is conceptually mismatched with core inflation: the difference is more than just "measurement error". We propose a technique for measuring core inflation, based on an explicit long-run economic hypothesis. Core inflation is defined as that...

This paper proposes a general Bayesian framework for distinguishing between trend- and difference-stationarity. Usually, in model selection, we assume that all of the data were generated by one of the models under consideration. In studying time series, however, we may be concerned that the...

We present a general class of nonlinear time series Markov regime-switching models for seasonal data which may exhibit periodic features in the hidden Markov process as well as in the laws of motion in each of the regimes. This class of models allows for nontrivial dependencies between seasonal,...

Financial transaction costs are time varying. This paper proposes a model that relates transaction cost to characteristics of order flow. We obtain qualitatively consistent model results for different stocks and across different time periods. We find that an unusual excess of buyers (sellers)...

Correlations between asset returns are important in many financial applications. In recent years, multivariate volatility models have been used to describe the time-varying feature of the correlations. However, the curse of dimensionality quickly becomes an issue as the number of correlations is...

We extend Ohlson's (1995) model and examine the relationship between returns and residual income that incorporate analysts' earnings forecasts and other non-earnings information variables in the balance sheet, namely default probability and agency cost of a debt covenant contract. We further...

Transfer function or distributed lag models are commonly used in forecasting. The stability of a constant-coefficient transfer function model, however, may become an issue for many economic variables due in part to the recent advance in technology and improvement in efficiency in data collection...

Most asset return series, especially those in high frequency, show high excess kurtosis and persistence in volatility that cannot be adequately described by the generalized conditional heteroscedastic (GARCH) model, even with heavy-tailed innovations. Many researchers have argued that these...