Forecasting share price movements using news sentiment analysis in a multinational environment

Using a common definition we can define news analysis as the measurement of the various qualitative and quantitative elements of textual news stories. These elements include sentiment, relevance and novelty. By quantifying news stories we can gain a useful way to manipulate and use everyday information in a mathematically concise manner. In this article a framework for news analytics techniques used in finance is provided. Various news analytic methods and software are discussed, and a set of metrics is given that may be applied to assess the performance of analytics. Various directions for this field are discussed. The proposed methods can help the valuation and trading of securities, facilitate investment decision making, meet regulatory requirements, or manage risk

4-metil-fenantrolin és oxon reakciójának kinetikai vizsgálata

Szakdolgozatomban a 4-metil-1,10-fenantrolin és a peroxomonoszulfát-ion közötti reakciót tanulmányoztam. A reakció savas közegben lassú, egylépéses míg semleges közegben gyors, többlépéses. Savas közegben két mono-N-oxid izomer keletkezik, semleges közegben di-N-oxid a termék. Az alapvegyülettel (phen) összehasonlítva a 4-phen oxidációját megállapítható, hogy a két rendszer nagyon hasonlóan viselkedik.BSc/BAvegyészmérnök bscg

Az alfa-részecske mag optikai potenciál meghatározása rugalmas alfa-részecskeszórás kísérletekben

Alfa-részecske és Neodímium atommag által alkotott rendszer paramétereinek meghatározása részecske szórási kisérletekkel.BSc/BAFizika Bscg

Actual Evapotranspiration Estimation Using Sentinel-1 SAR and Sentinel-3 SLSTR Data Combined with a Gradient Boosting Machine Model in Busia County, Western Kenya

Kenya is dominated by a rainfed agricultural economy. Recurrent droughts influence food security. Remotely sensed data can provide high-resolution results when coupled with a suitable machine learning algorithm. Sentinel-1 SAR and Sentinel-3 SLSTR sensors can provide the fundamental characteristics for actual evapotranspiration (AET) estimation. This study aimed to estimate the actual monthly evapotranspiration in Busia County in Western Kenya using Sentinel-1 SAR and Sentinel-3 SLSTR data with the application of the gradient boosting machine (GBM) model. The descriptive analysis provided by the model showed that the estimated mean, minimum, and maximum AET values were 116, 70, and 151 mm/month, respectively. The model performance was assessed using the correlation coefficient (r) and root mean square error (RMSE). The results revealed a correlation coefficient of 0.81 and an RMSE of 10.7 mm for the training dataset (80%), and a correlation coefficient of 0.47 and an RMSE of 14.1 mm for the testing data (20%). The results are of great importance scientifically, as they are a conduit for exploring alternative methodologies in areas with scarce meteorological data. The study proves the efficiency of high-resolution data retrieved from Sentinel sensors coupled with machine learning algorithms, focusing on GBM as an alternative to accurately estimate AET. However, the optimal solution would be to obtain direct evapotranspiration measurements