In today's era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent...

Die Preise für Immobilien sind in vielen Ländern in den vergangenen Jahren deutlich gestiegen und es wächst die Sorge, dass sich erneut spekulative Preisblasen bilden. Für politische Entscheidungsträger kann es dabei schwer sein, den richtigen Zeitpunkt für regulierende Eingriffe in den...

Low-visibility conditions at airports can lead to capacity reductions and therefore to delays or cancelations of arriving and departing flights. Accurate visibility forecasts are required to keep the airport capacity as high as possible. We generate probabilistic nowcasts of low-visibility...

Seit dem Berichtsjahr 2008 enthalten die Datenlieferungen zur deutschen amtlichen Wanderungsstatistik Angaben zum Geburtsstaat von zu-, fort- und umziehenden Personen. Wegen unzureichender Qualität wurden diese Daten bislang nur für Schätzungen nach Geburtsstaatengruppen im Rahmen...

Ensuring energy security is a major concern of policymakers and economic planners. This objective could be achieved by managing the energy supply and its demand. The latter has received less attention, especially in developing countries. Neglect of energy consumption and its accurate forecasting...

XGBoost is recognized as an algorithm with exceptional predictive capacity. Models for a binary response indicating the existence of accident claims versus no claims can be used to identify the determinants of traffic accidents. This study compared the relative performances of logistic...

The use of advanced predictive techniques and reasoning models has greatly assisted clinicians in improving the diagnosis, prognosis, and treatment of diabetes. Although numerous studies have focused on the relationship between abnormal blood glucose levels and diabetes, few have focused on the...

Childhood circumstances may impact senior health, prompting this study to introduce novel machine learning methods to assess their individual and collective contributions to health inequality in old age. Using the US Health and Retirement Study (HRS) and the China Health and Retirement...

This paper develops a large-scale application to improve the labour market matching process with model- and algorithm-based statistical methods. We use comprehensive administrative data on employment biographies covering individual and job-related information of workers in Germany. We estimate...

This paper follows the recent literature on real estate price prediction and proposes to take advantage of machine learning techniques to better explain which variables are more important in describing the real estate market evolution. We apply the random forest algorithm on London real estate...