As China’ largest oilfield, Daqing is of great importance to China, this paper analyzes the status of the Daqing oilfield and forecasts its ultimate recoverable reserves by use of the URR model. The forecast results are presented for three scenarios which show that the ultimate recoverable...

Over the last four decades, bankruptcy prediction has given rise to an extensive body of literature, the aim of which was to assess the conditions under which forecasting models perform effectively. Of all the parameters that may influence model accuracy, one has rarely been discussed: the...

Of the methods used to build bankruptcy prediction models in the last twenty years, neural networks are among the most challenging. Despite the characteristics of neural networks, most of the research done until now has not taken them into consideration for building financial failure models, nor...

Purpose The aim of this paper is to suggest a new approach to the problem of sales forecasting for improving forecast accuracy. The proposed method is capable of combining, by means of appropriate weights, both the responses supplied by the best-performing conventional algorithms, which base...

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

A two-regime self-exciting threshold autoregressive process is estimated for quarterly aggregate GDP of the fifteen countries that compose the European Union, and the forecasts from this nonlinear model are compared, by means of a Monte Carlo simulation, with those from a simple autoregressive...

Tests for relative predictive accuracy have become a widespread addendum to forecast comparisons. Many empirical research reports conclude that the difference between the entertained forecasting models is 'insignificant'. This paper collects arguments that cast doubt on the usefulness of...

This paper examines the corporation tax forecasting techniques used by the Institute for Fiscal Studies. For current year forecasts a judgemental forecast is found to have performed better than relying solely on a simple model or information on the receipts available so far in the current...

We analyze the performance of Bayesian model averaged exchange rate forecasts for euro/US dollar, euro/Japanese yen, euro/Swiss franc and euro/British pound rates using weights based on the out-of-sample predictive likelihood. The paper also presents a simple stratified sampling procedure in the...

We propose a new time series model aimed at forecasting crude oil prices. The proposed specification is an unobserved components model with an asymmetric cyclical component. The asymmetric cycle is defined as a sine-cosine wave where the frequency of the cycle depends on past oil price...