If the intensity parameter in a jump diffusion model is identically zero, then parameters characterizing the jump size density cannot be identified. In general, this lack of identification precludes consistent estimation of identified parameters. Hence, it should be standard practice to...

In this paper, we provide new evidence on the empirical usefulness of various simple seasonal models, and underscore the importance of carefully designing criteria by which one judges alternative models. In particular, we underscore the importance of both choice of forecast or simulation horizon...

This paper introduces a conditional Kolmogorov test, in the spirit of Andrews (1997), that allows for comparison of multiple misspecifed conditional distribution models, for the case of dependent observations. A conditional confidence interval version of the test is also discussed. Model...

We employ parametric and non-parametric cointegration to investigate the extent of integration between African stock markets and the rest of the world. Long-run correlation estimates imply very low association between the two. The two distinct cointegration approaches confirm the latter through...

This paper examines the forecasting properties of a Markov regime-switching model applied to Swedish interest rate volatility. A Monte Carlo testing procedure is used to arrive at a three state specification that is able to capture the high degree of leptokurtosis in the data without additional...

In this paper, we analyse the heavy-tailed behaviour in the dynamics of housing-price returns in the United States. We investigate the sources of heavy tails by estimating autoregressive models in which innovations can be subject to GARCH effects and/or non-Gaussianity. Using monthly data...

We use a novel data set covering all domestic debit card transactions in physical terminals by Norwegian households, to nowcast quarterly Norwegian household consumption. These card payments data are free of sampling errors and are available weekly without delays, providing a valuable early...

This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models such as Generalized Autoregressive Conditional...

When alternatives are compared using an estimated criterion function, this may introduce a discrepancy between the true and the estimated criterion. In this paper, we consider a situation where a preordering (ranking) of stochastic sequences is defined from expected loss/gain, using a parametric...

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...