Bitetta / Bordino / Ferretti Mining Data for Financial Applications

4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers
Erscheinungsjahr 2020
ISBN: 978-3-030-37720-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 11985, 133 Seiten, eBook

Reihe: Lecture Notes in Computer Science

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.

Zielgruppe

Research

Autoren/Hrsg.

Bitetta, Valerio

Bordino, Ilaria

Ferretti, Andrea

Gullo, Francesco

Pascolutti, Stefano

Ponti, Giovanni

Inhaltsverzeichnis

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.