Results 121 to 130 of about 5,037 (306)

Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch   +3 more
wiley   +1 more source

Forecasting House Prices: The Role of Market Interconnectedness

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT While the existing research uncovers interconnections between various housing markets, it largely ignores the question of whether such linkages can improve house price predictions. To address this issue, we proceed in two steps. First, we forecast disaggregated house price growth rates from Australia and China to determine whether ...
Zac Chen   +3 more
wiley   +1 more source

Regime‐Dependent Nowcasting of the Austrian Economy

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We nowcast and forecast economic activity in Austria, namely, real gross domestic product (GDP), consumption, and investment, which are available at a quarterly frequency, using a preselected number of monthly indicators based on a combination of statistical procedures.
Jaroslava Hlouskova, Ines Fortin
wiley   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das   +2 more
wiley   +1 more source

Intraday Functional PCA Forecasting of Cryptocurrency Returns

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley   +1 more source

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