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Apichat Chaweewanchon and Rujira Chaysiri
With the advances in time-series prediction, several recent developments in machine learning have shown that integrating prediction methods into portfolio selection is a great opportunity. In this paper, we propose a novel approach to portfolio formation...
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Thabang Mathonsi and Terence L. van Zyl
Hybrid methods have been shown to outperform pure statistical and pure deep learning methods at forecasting tasks and quantifying the associated uncertainty with those forecasts (prediction intervals). One example is Exponential Smoothing Recurrent Neura...
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Olajide Olubayo Thomas,Olajide Idowu Okunbanjo
Pág. 41 - 49
In today?s Nigeria, employment in organizations has turned upside down due to poor economic situations which do not allow many companies to pay their employees well. There is a need for individuals to look for ways to increase their incomes for meeting f...
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Emanuele Ogliari, Alfredo Nespoli, Marco Mussetta, Silvia Pretto, Andrea Zimbardo, Nicholas Bonfanti and Manuele Aufiero
The increasing penetration of non-programmable renewable energy sources (RES) is enforcing the need for accurate power production forecasts. In the category of hydroelectric plants, Run of the River (RoR) plants belong to the class of non-programmable RE...
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Fabian Pape
Pág. Finance an - 75
This forum contribution critically rethinks the macro-financial approach to liquidity by focusing more explicitly on its public-private hybrid dimension. To do so, it introduces the notion of a ?liquidity regime?: a heuristic device aimed at tracking the...
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