|
|
|
|
|
Charalampos M. Liapis and Sotiris Kotsiantis
The use of deep learning in conjunction with models that extract emotion-related information from texts to predict financial time series is based on the assumption that what is said about a stock is correlated with the way that stock fluctuates. Given th...
ver más
|
|
|
|
|
|
|
|
|
|
|
Valerio Marciello, Mario Di Stasio, Manuela Ruocco, Vittorio Trifari, Fabrizio Nicolosi, Markus Meindl, Bruno Lemoine and Priscilla Caliandro
The environmental impact of aviation in terms of noise and pollutant emissions has gained public attention in the last few years. In addition, the foreseen financial benefits of an increased energy efficiency have motivated the transport industry to inve...
ver más
|
|
|
|
|
|
|
|
|
|
|
Stoicea Paula, Tudor Valentina Constan?a, Stoian Elena, Micu Marius Mihai, Soare Elena and Militaru Dan Ciprian
The objective of the analysis is to quantify the impact of subsidies on the activity of two large farms of 600 ha and 3000 ha, respectively. The innovative solution from this analysis is to create a model that can be used at the macroeconomic level, show...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shari De Baets, Dilek Önkal and Wasim Ahmed
Many people do not possess the necessary savings to deal with unexpected financial events. People?s biases play a significant role in their ability to forecast future financial shocks: they are typically overoptimistic, present-oriented, and generally un...
ver más
|
|
|
|
|
|
|
|
|
|
|
Warwick Smith, Anca M. Hanea and Mark A. Burgman
Economic and financial forecasts are important for business planning and government policy but are notoriously challenging. We take advantage of recent advances in individual and group judgement, and a data set of economic and financial forecasts compile...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yi-Chang Chen, Shih-Ming Kuo, Yonglin Liu, Zeqiong Wu and Fang Zhang
Most of the growth forecasts in analysts? evaluation reports rely on human judgment, which leads to the occurrence of bias. A back-propagation neural network (BPNN) is a financial technique that learns a multi-layer feedforward network. This study aims t...
ver más
|
|
|
|
|
|
|
|
|
|
|
A.S. Albychev,A.A. Chervyakov,E.V. Nikulchev
Pág. 116 - 122
The enhancement of Big Data, computer systems for data aggregation, distributed information systems determines the need to create new decision-making systems. Decision support systems at the federal level should not only increase the quantitative charact...
ver más
|
|
|
|
|
|
|
|
|
|
|
Flavius Darie
Pág. 103 - 117
This study investigates whether different specifications of univariate GARCH models can usefully forecast volatility on the foreign exchange market. The study uses only forecasts from an asymmetric GARCH model, namely Exponential GARCH (EGARCH) for CHF/R...
ver más
|
|
|
|
|
|
|
|
|
|
|
Panagiota Keramea, Nikolaos Kokkos, Georgios D. Gikas and Georgios Sylaios
Over the latest decades, oil marine pollution has posed a vital threat for global ocean health, since spillages of any scale are related to environmental, social and financial impacts. The worldwide increase in oil and gas demand, and the parallel rise i...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alan Kanamatovich Karaev, Oksana S. Gorlova, Marina L. Sedova, Vadim V. Ponkratov, Nataliya S. Shmigol and Svetlana E. Demidova
Improving the accuracy of cash flow forecasting in the TSA is the key to fulfilling government payment obligations, minimizing the cost of maintaining the cash reserve, providing the absence of outstanding debt accumulation, and ensuring investment in va...
ver más
|
|
|
|
|
|