Search results for "Forecasting"

Economic policy uncertainty effects for forecasting future real economic activity

2018

Recently introduced measures for Economic Policy Uncertainty (EPU) included in the data from 1997 - 2016 have a role in forecasting out-of-sample values for the future real economic activity for both the euro area and the UK economies. The inclusion of EPU measures, either for the US, the UK or for overall European economies, improves the forecasting ability of models based on standard financial market information, especially for the period before the 2008 global crisis. However, during and after the crisis period, the slope of the yield curve and excess stock market returns improves the out-of-sample forecast performance the most compared to an AR-benchmark model. Hence, the EPU informatio…

Comment améliorer la prévision des ventes pour le marketing ? Les apports de la théorie du chaos

2013

La littérature en marketing constate un décalage entre les avancées réalisées par les chercheurs qui développent de nouvelles méthodes de prévision des ventes, et l'usage massif de méthodes traditionnelles reposant sur l'hypothèse de linéarité des processus analysés. Cette recherche expose la contribution potentielle de la théorie du chaos à l'amélioration de la prévision des ventes. Une illustration de ces apports est proposée avec une application à la prévision des ventes de consoles de jeux vidéo au Japon. Les résultats mettent en évidence la capacité de la méthode proposée à détecter la présence de chaos dans la série et montrent la possibilité de préciser l'horizon de prévisibilité des…

How many longitudinal covariate measurements are needed for risk prediction?

2014

Abstract Objective In epidemiologic follow-up studies, many key covariates, such as smoking, use of medication, blood pressure, and cholesterol, are time varying. Because of practical and financial limitations, time-varying covariates cannot be measured continuously, but only at certain prespecified time points. We study how the number of these longitudinal measurements can be chosen cost-efficiently by evaluating the usefulness of the measurements for risk prediction. Study Design and Setting The usefulness is addressed by measuring the improvement in model discrimination between models using different amounts of longitudinal information. We use simulated follow-up data and the data from t…

20 years of health promotion research in the Nordic countries : Health, wellbeing and physical activity

2018

Qualitative analysis of housing demand using Google trends data

2019

Big data analytics often refer to the breakdown of huge amounts of data into a more readable and useful format. This study utilises Google Trends big data as a proxy for an analysis of housing demand. We employ a qualitative method (fuzzy set/Qualitative Comparative Analysis, fsQCA), instead of a quantitative method, for our estimate and forecast. The empirical results show that fsQCA successfully forecasts seasonal time series, even though the dataset is small in size. Our findings fill the gap in the qualitative and time series forecasting literature, and the forecasting procedure herein also offers a good standard for industry.

Application of artificial neural network and genetic algorithm to forecasting of wind power output

2007

Nonlinear black-box models for short-term forecasting of air temperature in the town of Palermo

2011

Weather data are crucial to correctly design buildings and their heating and cooling systems and to assess their energy performances. In the intensely urbanized towns the effect of climatic parameters is further emphasized by the Urban Heat Island (UHI) phenomenon, known as the increase in the air temperature of urban areas, compared to the one measured in the extra-urban areas. The analysis of the heat island needs detailed local climate data which can be collected only by a dedicated weather monitoring system. The Department of Energy and Environmental Researches of the University of Palermo (Italy) has built up a weather monitoring system that works 24 hours per day and makes data availa…

Lagrangian matches between observations from aircraft, lidar and radar in a warm conveyor belt crossing orography

2021

Warm conveyor belts (WCBs) are important airstreams in extratropical cyclones, often leading to the formation of intense precipitation and the amplification of upper-level ridges. This study presents a case study that involves aircraft, lidar and radar observations in a WCB ascending from western Europe towards the Baltic Sea during the Hydrological Cycle in the Mediterranean Experiment (HyMeX) and T-NAWDEX-Falcon in October 2012, a preparatory campaign for the THORPEX North Atlantic Waveguide and Downstream Impact Experiment (TNAWDEX). Trajectories were used to link different observations along the WCB, that is, to establish so-called Lagrangian matches between observations. To this aim, a…

Faktoru modeļu priekšrocības ekonomiskās aktivitātes īstermiņa prognozēšanā

2014

Promocijas darba anotācija Pēdējā desmitgadē Latvijas tautsaimniecības attīstība bijusi īpaši svārstīga, kas sarežģīja ekonomiskās politikas lēmumu pieņemšanu ekonomiskās situācijas stabilizēšanai. Lai atvieglotu lēmumu pieņemšanu, ekonomisko aktivitāti īstermiņā var prognozēt ar ekonometriskiem modeļiem. Promocijas darba mērķis ir novērtēt faktoru modeļu priekšrocības ekonomiskās aktivitātes prognozēšanas kontekstā un noteikt Latvijas gadījumā nepieciešamo instrumentu un metožu klāstu īstermiņa prognozēšanai. Promocijas darbā tiek sniegtas atbildes uz faktoru modeļu lietošanas problēmjautājumiem īstermiņa prognozēšanā, kā arī novērtēti daži faktoru modeļu lietošanas aspekti. Faktoru modeļu…