Mining Data for Financial Applications : 4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers / edited by Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Stefano Pascolutti, Giovanni Ponti.

1st ed. 2020.
Cham : Springer International Publishing : Imprint: Springer, 2020.
Computer Science (Springer-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence 11985
Lecture Notes in Artificial Intelligence ; 11985
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This book constitutes revised selected papers from the 4th Workshop on Mining Data for Financial Applications, MIDAS 2019, held in conjunction with ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain.
MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning
Curriculum Learning in Deep Neural Networks for Financial Forecasting
Representation Learning in Graphs for Credit Card Fraud Detection
Firms Default Prediction with Machine Learning
Convolutional Neural Networks, Image Recognition and Financial Time Series Forecasting
Mining Business Relationships from Stocks and News
Mining Financial Risk Events from News and Assessing their impact on Stocks
Monitoring the Business Cycle with Fine-grained, Aspect-based Sentiment Extraction from News
Multi-step Prediction of Financial Asset Return Volatility Using Parsimonious Autoregressive Sequential Model
Big Data Financial Sentiment Analysis in the European Bond Markets
A Brand Scoring System for Cryptocurrencies Based on Social Media Data.
Bitetta, Valerio, editor., Editor,
Bordino, Ilaria. editor., Editor,
Ferretti, Andrea. editor., Editor,
Gullo, Francesco. editor., Editor,
Pascolutti, Stefano. editor., Editor,
Ponti, Giovanni. editor., Editor,
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