This paper gives an unbiased estimator of the variance of overlapping returns. The estimator improves upon that proposed in Lo and MacKinlay (1988) [LM] (which is widely used in practice), as the LM estimator is consistent but not unbiased in small samples. The relevance of unbiasedness for...

This article seeks to find an answer to the question: 'How many stamps are still around, given that we know their prices at issue, the current price and the amount then issued?' For this purpose, I develop a simple statistical model, the parameters of which are estimated for over 1000 postwar...

This paper discusses the properties of the univariate Dickey-Fuller test and the Johansen test for the cointegrating rank when there exist additive outlying observations in the time series. The authors provide analytical as well as numerical evidence that additive outliners may produce spurious...

Regime-switching models, like the smooth transition autoregressive (STAR) model, are typically applied to time series of moderate length. Hence, the nonlinear features that these models intend to describe may be reflected in only a few observations. Conversely, neglected outliers in a linear...

Periodic autoregressions are characterised by autoregressive structures that vary with the season. If a time series is periodically integrated, one needs a seasonally varying differencing filter to remove the stochastic trend. When the periodic regression model contains constants and trends with...

In this paper we introduce a sequential seasonal unit root testing approach which explicitly addresses its application to high frequency data. The main idea is to see which unit roots at higher frequency data can also be found in temporally aggregated data. We illustrate our procedure to the...

It is argued that for specific forecast settings there must exist an optimally-sized model with forecasts that only need occasional adjustments by experts. The argument is built on recent evidence on the interaction between models and experts. A consequence of this is that the future research...