Showing papers in "International Journal of Forecasting in 1987"

TL;DR: In this article, the authors present the results of a survey designed to discover how business firms prepare sales forecasts, what methods they prefer, and the accuracy of their predictions and find that subjective, extrapolation and naive techniques are widely used by American business firms in various forecasting situations.

TL;DR: This paper found that the fundamental variables are integrated of different orders and there is a lack of cointegration between the exchange rate variables in the monetary model and relative prices, which indicated that it is not worthwhile to forecast from the pure monetary model.

TL;DR: In this article, the authors describe methods for choosing and assessing volatility forecasts using open, high, low and close prices and show that high and low prices are valuable when seeking accurate volatility forecasts.

TL;DR: This paper tested the martingale hypothesis for daily and weekly rates of change of futures prices for five currencies and found some evidence against the null hypothesis for each currency with daily data, but only for one currency.

TL;DR: In this article, the authors empirically evaluate the uncertainty of forecasts using the 1001 series of the M-Competition and provide tables to help users to construct more realistic confidence intervals for their forecasts.

TL;DR: In this article, the sensitivity of forecasts from a VAR model using different lag structures is examined, using simple ad hoc rules as well as statistical criteria, such as mean square error and Bayesian rules, and the results indicate that the accuracy of VAR forecasts varies dramatically across alternative lag structures.

TL;DR: The authors reviewed the empirical research on forecasting in marketing and provided a framework for discussing forecasts in the area of marketing, and then reviewed the literature in light of that framework, with particular emphasis on a pragmatic interpretation of the literature and findings.

TL;DR: This paper analyzed mean probability distributions reported by ASA-NBER forecasters on two macroeconomic variables, GNP and the GNP implicit price deflator, and showed that a non-central scaled t-distribution fit the empirical distributions remarkably well.

TL;DR: In this paper, the authors compare the performance of time-series and static and dynamic models to construct forecasts for the Canadian dollar/U.S. dollar exchange rates over the period 1976 :12-1984: 9.

TL;DR: In this article, the performance of various structural exchange rate models based on the methodology developed by Meese and Rogoff (1983 a,b, 1985) means of improving forecast performance is compared.

TL;DR: This paper found that persons who were more deeply involved in a planning exercise were more optimistic about the outcome of the plan than those who were less involved, and that one reason for the optimism bias is that during the planning process the illusion of control over the environment leads the planner to change assumptions about uncontrollable events which are likely to affect the outcome.

TL;DR: This article examined the predictive performance of econometric market share models and used data for fifteen brands from three markets to examine the predictive ability of the models in more detail, and concluded that market shares did not usually capture enough of the important features of the market to be used by themselves as stand alone forecasting instruments.

TL;DR: In this article, the authors investigated the efficacy of combining forecasting models in order to improve earnings per share forecasts in the utility industry by comparing three types of forecasting models which use historical data are compared to the forecasts of the Value Line Investment Survey.

TL;DR: In this paper, the authors apply a time series approach, intervention analysis, to several marketing policy applications illustrating the flexibility and value of the method for testing hypotheses and providing forecasts, and empirical evidence is presented for two different marketing situations, one that involves a change in advertising and another that involves offering price specials.

TL;DR: No support was found for the contention that scenarios improved upon ‘eyeball’ extrapolation or made judgmental sales forecasts more accurate than quantitative extrapolations, and scenarios were found to be tainted by many of the same biases previously identified by cognitive psychologists.

TL;DR: In this article, the authors attributed these movements to the two important changes in monetary policy that occurred during these years, such as the breakdown of the Bretton Woods and the introduction of the gold standard, and they continued more or less unabated until early 1985.

TL;DR: In this article, the authors present several methods for obtaining earlier estimates, including (a) simple univariate models, (b) an OLS model that employs data on electric power input, corrected for the effects of temperature and (indirectly) of the manufacturing output mix, and (c) a transfer-function model based on business surveys.

TL;DR: A new method based on recent results of the General Theory of Optimal Algorithm and a nonlinear modelling technique based on Group Method of Data Handling are considered to derive forecasts and show that the Optimal Error and GMDH predictors provide accurate one step ahead forecasts with respect to those obtained by some linear and nonlinear statistical models.

TL;DR: An automated forecasting system that encompasses an objective ARIMA method with the Holt-Winters procedure in a weighted averaging scheme is presented and reveals that especially for one-step ahead forecasting, the automated system competes favorably with both automated methods and the individualized Box-Jenkins analysis.

TL;DR: In general, the proper loss function for the forecasting problem will be asymmetric as discussed by the authors and the proper statistical criteria for making and evaluating these exchange rate forecasts are implied by the underlying decision problem.

TL;DR: The results obtained by Brodie and de Kluyver are likely to be specific to aggregate bimonthly data as mentioned in this paper, which causes researchers to specify models with unrealistic constraints.

TL;DR: In this article, the authors presented the results of a post-sample simulation of a speculative strategy using a portfolio of foreign currency forward contracts, which was still profitable over a three year period and it was possible to reject the hypothesis that the sum of profits was zero.

TL;DR: In this article, prior information of historical linkages is utilized in the form of restricted least squares and applied to the Louisville metropolitan area to improve the efficiency of forecasts by incorporating interindustry linkages in wage and employment determination into an econometric model.

TL;DR: This article conducted an empirical analysis of the approaches to obtaining linear combinations of forecasts and found that the most accurate forecasts were obtained by adding a constant term and not constraining the weights to add up to one.

TL;DR: In this paper, five alternative techniques have been applied to measure the degree of uncertainty associated with the forecasts produced by a macro-model of the French economy, the Mini-DMS developed at INSEE.

TL;DR: The relatively high predictive power of a naive market share model is due to its similarity to the reduced form representation of the underlying model and the comparison with forecasts generated from structural models that are likely to be misspecified.

TL;DR: The authors provided an explanation of why econometric market share models with explanatory variables do not always dominate naïve models that simply predict that future share will equal current share, while long-term forecasts of market share are biased.

TL;DR: In this paper, it is suggested that the predictability criterion, if interpreted in terms of conventional forecasting methods, would enable us to provide more conclusive results and assume added importance as the recent vintage of econometric modelling techniques heavily rely on these causality tests.

TL;DR: In this article, Brodie and de Kluyver have reported empirical results in which simple naive models have produced forecasts as accurate as those derived from econometric models and applied some recent theoretical results to show that these findings are plausible.

TL;DR: In this article, the authors argue that time series models can provide more accurate predictions than econometric models, but they do so by introducing bias and lack of bias is more important than accuracy.