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Titlebook: Data Science for Economics and Finance; Methodologies and Ap Sergio Consoli,Diego Reforgiato Recupero,Michaela Book‘‘‘‘‘‘‘‘ 2021 The Edito

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楼主: genial
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Andrea Donnellan,Peter Mora,Xiang-chu Yin that a limited number of shareholders control many firms, revealing a significant concentration of power. Finally, we show how these measures computed at different levels of granularity (i.e., sector of activity) can provide useful policy insights.
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series forecasting for applications in economics and financ.This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applicati
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Computational Earthquake Science Part Ietric approaches, the empirical literature has shown evidence of some gain in nowcasting ability. In this chapter, we propose to review recent advances of the literature on the topic, and we put forward innovative alternative indicators to monitor the Chinese and US economies.
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Sentiment Analysis of Financial News: Mechanics and Statistics, are provided on real data. The general goal is to provide guidelines for financial practitioners for the proper construction and interpretation of their own time-dependent numerical information representing public perception toward companies, stocks’ prices, and financial markets in general.
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AMMOS Software: Method and Applicationext, we describe how SL tools can be used to analyze company growth and performance. Finally, we review SL applications to better forecast financial distress and company failure. In the concluding section, we extend the discussion of SL methods in the light of targeted policies, result interpretability, and causality.
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