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Data Science for Economics and Finance · Study

BookData Science for Economics and Finance

Sergio Consoli2021

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Bookhybrid2021

Data Science for Economics and Finance

Sergio Consoli · Diego Reforgiato Recupero · Michaela Saisana

42 citations·0/0 files stored·Springer eBooks

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Stock Market Forecasting Methods Statistical Methods and Applications Computational and Text Analysis Methods

Abstract

This open access book covers the use of data science technologies (like machine learning, NLP, or Time Series Analysis) in economics and finance.

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References

1979Distribution of the Estimators for Autoregressive Time Series with a Unit Root 1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 2016Measuring Economic Policy Uncertainty*1997Legal Determinants of External Finance 1979Distribution of the Estimators for Autoregressive Time Series With a Unit Root 2009Power-Law Distributions in Empirical Data 2001Bad is Stronger than Good

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2022On logit and artificial neural networks in corporate distress modelling for Zimbabwe listed corporates 2022EXPERIENCE IN USING BIG DATA TECHNOLOGY FOR DIGITALIZATION OF INFORMATION

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Details

Year2021

Typebook

Published2021-01-01

VenueSpringer eBooks

Languageen

Citations42

Files0 public / 0

ShelfStock Market Forecasting Methods

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doi10.1007/978-3-030-66891-4

openalex_workW3176368795

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