We study the accuracy of a wide variety of estimators of asset price variation constructed from high-frequency data (so-called "realized measures"), and compare them with a simple "realized variance" (RV) estimator.  In total, we consider almost 400 different estimators, applied to 11 years of...

Inflation is a far from homogeneous phenomenon, a fact often neglected in modeling consumer price inflation.  Using a novel methodology grounded in theory, the ten sub-components of the consumer price index (excluding mortgage interest rates), are modeled separately and forecast,...

Inflation targeting central banks will be hampered without good models to assist them to be forward-looking.  Many current inflation models fail to forecast turning points adequately, because they miss key underlying long-run influences.  The world is on the cusp of a dramatic turning point in...

While there has been a great deal of interest in the modelling of non-linearities and regime shifts in economic time series, there is no clear consensus regarding the forecasting abilities of these models. In this paper we develop a general approach to predict multiple time series subject to...

Inflation is a far from homogeneous phenomenon, but this fact is ignored in most work on consumer price inflation. Using a novel methodology grounded in theory, the ten sub-components of the consumer price index (excluding mortgage interest rates, or CPIX) for South Africa are modeled separately...

This paper studies the small sample properties of processes which exhibit both a stochastic and a deterministic trend. Whereas for estimation, inference and forecasting purposes the latter asymptotically dominates the former, it is not so when only a finite number of observations is available...

To forecast at several, say h, periods into the future, a modeller faces two techniques: iterating one-step ahead forecasts (the IMS technique) or directly modeling the relation betwen observations separated by an h-period interval and using it for forecasting (DMS forecasting). It is known that...

The class of Functional Signal plus Noise (FSN) models is introduced that provides a new, general method for modelling and forecasting time series of economic functions.  The underlying, continuous economic function (or 'signal') is a natural cubic spline whose dynamic evolution is driven by a...

We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models.  Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses,...

 We propose a new class of multivariate volatility models utilizing realized measures of asset volatility and covolatility extracted from high-frequency data. Dimension reduction for estimation of large covariance matrices is achieved by imposing a factor structure with time-varying conditional...