0000000001217730

AUTHOR

Nikolaos Kourentzes

showing 2 related works from this author

Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team

2021

Abstract COVID-19 disrupted international tourism worldwide, subsequently presenting forecasters with a challenging conundrum. In this competition, we predict international arrivals for 20 destinations in two phases: (i) Ex post forecasts pre-COVID; (ii) Ex ante forecasts during and after the pandemic up to end 2021. Our results show that univariate combined with cross-sectional hierarchical forecasting techniques (THieF-ETS) outperform multivariate models pre-COVID. Scenarios were developed based on judgemental adjustment of the THieF-ETS baseline forecasts. Analysts provided a regional view on the most likely path to normal, based on country-specific regulations, macroeconomic conditions,…

Multivariate statisticsEx-ante[QFIN]Quantitative Finance [q-fin]Visitor pattern05 social sciencesUnivariateCOVID-19Hierarchical forecastsVisitor arrivalsDevelopmentDestinationsSettore SECS-P/06 - Economia ApplicataCompetition (economics)Settore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Tourism Leisure and Hospitality Management0502 economics and businessEconomicsEconometrics050211 marketingScenario forecastingBaseline (configuration management)050212 sport leisure & tourismTourismComputingMilieux_MISCELLANEOUSForecasting
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Forecasting : theory and practice

2022

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a varie…

FOS: Computer and information sciencesComputer Science - Machine LearningTime seriesEconomicsApplicationOther Engineering and Technologies not elsewhere specifiedEconometrics (econ.EM)HAMethodMachine Learning (stat.ML)ReviewStatistics - ApplicationsMachine Learning (cs.LG)FOS: Economics and businessBusiness and EconomicsStatistics - Machine LearningMethodsPrincipleREVIEWApplications (stat.AP)Övrig annan teknikN100Business and International ManagementNationalekonomiEconomics - EconometricsBusiness AdministrationFöretagsekonomiAPPLICATIONSOther Statistics (stat.OT)Wirtschaftswissenschaftenstat.OTStatistics - Other StatisticsComputer Science - Learning003: SystemePRINCIPLESecon.EMApplicationsMETHODSStatistics - Applications; Statistics - Applications; Computer Science - Learning; econ.EM; Statistics - Machine Learning; stat.OTEncyclopediaPredictionPrinciplesREVIEW ENCYCLOPEDIA METHODS APPLICATIONS PRINCIPLES TIME SERIES PREDICTIONForecasting
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