Forecasting, Volume 3, Issue 4

Despite the large efforts made by the ocean modeling community, such as the GODAE (Global Ocean Data Assimilation Experiment), which started in 1997 and was renamed as OceanPredict in 2019, the prediction of ocean currents has remained a challenge un...

Forecasting volatility from econometric datasets is a crucial task in finance. To acquire meaningful volatility predictions, various methods were built upon GARCH-type models, but these classical techniques suffer from instability of short and volati...

The present study employs daily data made available by the STR SHARE Center covering the period from 1 January 2010 to 31 January 2020 for six Viennese hotel classes and their total. The forecast variable of interest is hotel room demand. As forecast...

COVID-19 has significantly influenced tourism, including tourists’ and residents’ attitudes toward tourism. At the same time, attitudes and consumer confidence are important for economic recovery in the tourism sector. This study explores the effects...

The decision-maker is increasingly utilising machine learning (ML) techniques to find patterns in huge quantities of real-time data [...]

High-dimensional, non-stationary vector time-series data are often seen in ground motion monitoring of geo-hazard events, e.g., landslides. For timely and reliable forecasts from such data, we developed a new statistical approach based on two advance...

Exponential smoothing methods are one of the classical time series forecasting methods. It is well known that exponential smoothing methods are powerful forecasting methods. In these methods, exponential smoothing parameters are fixed on time, and th...

With an uninterrupted power supply to the consumer, it is obligatory to balance the electricity generated by the electricity load. The effective planning of economic dispatch, reserve requirements, and quality power provision for accurate consumer in...

This paper examines the suitability of Google Trends data for the modeling and forecasting of interregional migration in Russia. Monthly migration data, search volume data, and macro variables are used with a set of univariate and multivariate models...

The verification of probabilistic forecasts in hydro-climatology is integral to their development, use, and adoption. We propose here a means of utilizing goodness of fit measures for verifying the reliability of probabilistic forecasts. The difficul...