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.

Format:

Book

Contributor:

Bitetta, Valerio, editor.

Bordino, Ilaria, editor.

Ferretti, Andrea, editor.

Gullo, Francesco, editor.

Pascolutti, Stefano, editor.

Ponti, Gio, 1891-1979, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 11985.

Lecture Notes in Artificial Intelligence ; 11985

Language:

English

Subjects (All):

Artificial intelligence.

Optical data processing.

Computer organization.

Computers.

Electronic commerce.

Application software.

Artificial Intelligence.

Image Processing and Computer Vision.

Computer Systems Organization and Communication Networks.

Information Systems and Communication Service.

e-Commerce/e-business.

Computer Appl. in Social and Behavioral Sciences.

Local Subjects:

Artificial Intelligence.

Image Processing and Computer Vision.

Computer Systems Organization and Communication Networks.

Information Systems and Communication Service.

e-Commerce/e-business.

Computer Appl. in Social and Behavioral Sciences.

Physical Description:

1 online resource (IX, 133 pages) : 37 illustrations, 27 illustrations in color.

Edition:

First edition 2020.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-030-37720-5

9783030377205

Access Restriction:

Restricted for use by site license.