We evaluate the contribution of analysts' earnings forecasts to investors' decisions by comparing the association between annual excess returns and a broad set of information items derived from financial statements with the association between excess returns and that information set plus the...

This paper proposes a new approach to modeling volatility changes and clustering, we use a parsimonious high-order markov chain which allows for duration dependence.

A predictor is asked to rank eventualities according to their plausibility, based on past cases. We assume that she can form a ranking given any memory that consists of repetitions of past cases.

Recent work by Clements and Hendry have shown why forecasting systems that are in terms of differences, dVARs, can be more accurate than econometric models that include levels variables, ECMs. For example, dVAR forecasts are insulated from parameter non-constancies in the long run mean of the...

The predictive accuracy of various econometrics models, including random walks, vector autoregressive and vector error-correction models, are investigated using daily futures prices of 4 commodities (the S&P500 index, treasury bonds, gold and crude oil).

Using density forecasts, we compare the predictive performance of dur ation models that have been developed fo modelling intra-day data on stock markets. Our model portfolio encompasses the auto regressive conditional duration (ACD) model, its logarithmic version (Log-ACD), the threshold...

This paper analyzes the rationality of Japanese macroeconomic forecasters. It finds that Japanese individual forecasters are pessimistic in boom and optimistic in recession, and that they over-react to new information. Across forecasters, the magnitude of average forecast revisions is not...

In this paper we argue that even if a dynamic relationship can be well described by a deterministic system, retrieving this relationship from an empirical time series has to take into account some, although possiblu very small measurement error in the observations. Therefore, measuring the...

This paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We show how one should account for unit roots and deterministic terms when generating out-of-sample forecasts. We illustrate the models for various quarterly UK consumption series.

This paper argues that the Commission forecasts dispose of a resaonable track record. Most of the traditional test for examining the quality of predictions are passed in a satisfactory way. The comparisons with forecasts made by the IMF, OECD and national forecast institutes are not unfavourable...