Mining Data for Financial Applications (eBook, PDF)

5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
Redaktion: Bitetta, Valerio; Severini, Lorenzo; Ponti, Giovanni; Gullo, Francesco; Ferretti, Andrea; Bordino, Ilaria

• Format: PDF

Produktbeschreibung

"Information Extraction from the GDELT Database to Analyse EU Sovereign Bond Markets" and "Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 151
• Erscheinungstermin: 14. Januar 2021
• Englisch
• ISBN-13: 9783030669812
• Artikelnr.: 62299247

Inhaltsangabe

Trade Selection with Supervised Learning and Optimal Coordinate Ascent (OCA).- How much does Stock Prediction improve with Sentiment Analysis?.- Applying Machine Learning to Predict Closing Prices in Stock Market: a case study.- Financial Fraud Detection with Improved Neural Arithmetic Logic Units.- Information Extraction from the GDELT Database to Analyse EU Sovereign Bond Markets.- Multi-Objective Particle Swarm Optimization for Feature Selection in Credit Scoring.- A comparative analysis of Temporal Long Text Similarity: Application to Financial Documents.- Ranking Cryptocurrencies by Brand Importance: a Social Media Analysis in ENEAGRID.- Towards the Prediction of Electricity Prices at the Intraday Market Using Shallow and Deep-Learning Methods.- Neither in the Programs Nor in the Data: Mining the Hidden Financial Knowledge with Knowledge Graphs and Reasoning.- Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting.