Recent studies on affective forecasting clarify that the emotional reactions people anticipate often differ markedly from those they actually experience in response to affective stimuli and events. However, core personality differences in affective forecasting have received limited attention, despite their potential relevance to choice behavior. In the present study, 226 college undergraduates ...

When forecasting aggregated time series, several options are available. For example, the multivariate series or the individual time series might be predicted and then aggregated, or one may choose to forecast the aggregated series directly. While in theory an optimal disaggregated forecast will generally be superior (or at least not inferior) to forecasts based on aggregated information, this i...

By analysis of historical data of the ionosphere, it is suggested to apply grey theory to ionospheric short-term forecasting, grey range information entropy is defined to determine the optimum grey length of the sample sequence, the prediction model based on residual error is constructed, and the observation data of multiple ionospheric observation stations in China are adopted for test. The pr...

A double forecasting model based on conditional expectation is proposed through probability distribution of port cargo throughput. A compound variable, being composed of the number of cargo ships arriving at the port and the operating efficiency of handling equipment, is constructed. The port cargo throughput is the sum of all compound variables which indicated the cargo throughput each time wh...

This paper presents a hybrid wavelet support vector machines (WSVM) model that combines both wavelet technique and the SVM model for crude oil price forecasting. Based on the purpose, the main time series was decomposed to some multi-frequently time series by wavelet theory and these time series were imposed as input data to the SVM for forecasting of crude oil price series. To assess the effec...

This expository article reviews the game-theoretic framework for probability and the method of defensive forecasting that derives from it. The game-theoretic framework, introduced by Vladimir Vovk and myself in Probability and Finance: It’s Only a Game! (Wiley 2001 [51]), can replace measure theory as a mathematical framework for classical probability theory, discrete and continuous. Classical ...

This paper examines a new time series method for very short-term wind speed forecasting. The time series forecasting model is based on Bayesian theory and structural break modeling, which could incorporate domain knowledge about wind speed as a prior. Besides this Bayesian structural break model predicts wind speed as a set of possible values, which is different from classical time series model...

This paper presents a novel approach to financial time series analysis and prediction. It is mainly devoted to the problem of forecasting university facility and administrative cost recovery. However, it can also be used in other areas of a similar nature. The methodology incorporates a two-stage hybrid mechanism for selection of prediction-relevant features and for forecasting based on this se...

Do professional forecasters distort their reported forecasts in a way that compromises accuracy? New research in the theory of forecasting suggests such a possibility. In a recent paper, Owen Lamont finds that forecasters in the Business Week survey make more radical forecasts as they gain experience. In this paper, I use forecasts from the Federal Reserve Bank of Philadelphia’s Survey of Profe...

Collopy, Adya and Armstrong (1994) (CAA) advocate the use of atheoretical "black box" extrapolation techniques to forecast information sys tems spending. In this paper, we contrast this approach with the positive modeling approach of Gurbaxani and Mendelson (1990), where the primary focus is on explanation based on economics and innovation diffusion theory. We argue that the objectives and prem...