To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...

There is empirical evidence for a time-varying relationship between exchange rates and fundamentals. Such a relationship with time-varying coefficients can be estimated by a Kalman filter model. A Kalman filter estimates the coefficients recursively depending on the prediction error of the...

An accurate forecast of intraday volume is a key aspect of algorithmic trading. This manuscript proposes a state-space model to forecast intraday trading volume via the Kalman filter and derives closed-form expectation-maximization (EM) solutions for model calibration. The model is extended to...

Structural time series models are formulated in terms of components, such as trends, seasonals and cycles, that have a direct interpretation. As well as providing a framework for time series decomposition by signal extraction, they can be used for forecasting and for ‘nowcasting’. The...

Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...

In this paper we develop a general framework to analyze state space models with time-varying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...

In this paper we develop a general framework to analyze state space models with timevarying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...

The neutral band is the interval where deviations from Covered Interest Parity (CIP) are not considered meaningful arbitrage opportunities. The band is determined by transaction costs and risk associated to arbitrage. Seemingly large deviations from CIP in the foreign exchange markets for the US...

A modification of the self-perturbed Kalman filter of Park and Jun (1992) is proposed for the on-line estimation of models subject to parameter in stability. The perturbation term in the updating equation of the state covariance matrix is weighted by the measurement error variance, thus avoiding...

The increasing availability of intraday financial data has led to improvements in daily volatility forecasting through long-memory models of realized volatility. This paper demonstrates the merit of the non-parametric Nearest Neighbor (NN) approach for S&P 100 realized variance forecasting. A...