This paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to fit them using a BEKK-type parameterization of the...

This paper introduces a new class of multivariate volatility models that utilizes high-frequency data.  We discuss the models' dynamics and highlight their differences from multivariate GARCH models.  We also discuss their covariance targeting specification and provide closed-form formulas...

There is widespread disagreement about the role of housing wealth in explaining consumption.  This paper exploits liquid and illiquid wealth time series from household balance sheet data for South Africa, previously constructed by the authors, to explain fluctuations in the ratios of...

Even in scientific disciplines, forecast failures occur.  Four possible states of nature (a model is good or bad, and it forecasts well or badly) are examined using a forecast-error taxonomy, which traces the many possible sources of forecast errors.  This analysis shows that a valid model can...

A new test for non-linearity in the conditional mean is proposed using functions of the principal components of regressors.  The test extends the non-linearity tests based on Kolmogorov-Gavor polynomials (Thursby and Schmidt, 1977, Tsay, 1986, and Terasvirta, Lin and Granger, 1993), but...

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...

A new test for non-linearity is developed using weighted combinations of regressor powers based on the eigenvectors of the variance-covariance matrix. The test extends the ingenious test for heteroskedasticity proposed by White (1980), but both circumvents problems of high dimensionality and...

We investigate the properties of the composite likelihood (CL) method for (T x NT) GARCH panels.  The defining feature of a GARCH panel with time series length T is that, while nuisance parameters are allowed to vary across NT series, other parameters of interest are assumed to be common.  CL...

A key ingredient of many particle filters is the use of the sampling importance resampling algorithm (SIR), which transforms a sample of weighted draws from a prior distribution into equally weighted draws from a posterior distribution.  We give a novel analysis of the SIR algorithm and analyse...

Motivated by features of low latency data in finance we study in detail discrete-valued Levy processes as the basis of price processes for high frequency econometrics.  An important case of this is a Skellam process, which is the difference of two independent Poisson processes.  We propose a...