Vol-1774
urn:nbn:de:0074-1774-1

Copyright © 2016 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.

MIDAS 2016
MIning DAta for financial applicationS

Proceedings of the First Workshop on MIning DAta for financial applicationS (MIDAS 2016)
co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2016)

Riva del Garda, Italy, September 19-23, 2016.

Edited by

Ilaria Bordino *
Guido Caldarelli **
Fabio Fumarola *
Francesco Gullo *
Tiziano Squartini **

* UniCredit, R&D Department, Milan, Italy
** IMT Institute for Advanced Studies, Lucca, Italy

Table of Contents

Preface

Clustering underlying stock trends via non-negative matrix factorization 5-16
Andrea Pazienza, Sabrina Francesca Pellegrino, Stefano Ferilli, Floriana Esposito
Clustering of exchange rates and their dynamics under different dependence measures 17-28
Martí Renedo, Argimiro Arratia
A general framework for building machine learning models for pricing american index options with no-arbitrage and its limitation (extended abstract) 29-30
Huisu Jang, Jaewook Lee
Towards a sharp estimation of transfer entropy for identifying causality in financial time series 31-42
Àlex Serès, Alejandra Cabaña, Argimiro Arratia
Brexit or Bremain? Evidence from bubble analysis 43-54
Marco Bianchetti, Davide Emilio Galli, Camilla Ricci, Angelo Salvatori, Marco Scaringi
Good news and bad news: Do online investor sentiments reaction to return news asymmetric? 55-66
Alya Al Nasseri, Faek Menla Ali, Allan Tucker
Sentiment extraction from financial public disclosure documents 67-72
Ali Caner Türkmen
A probabilistic approach for financial IoT data (extended abstract) 73-74
Salvatore Cuomo, Pasquale De Michele, Vittorio Di Somma, Giovanni Ponti

2016-12-28: submitted by Francesco Gullo, metadata incl. bibliographic data published under Creative Commons CC0
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