Title Mining data for financial applications : 4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised selected papers / Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Stefano Pascolutti, Giovanni Ponti (eds.)

Published Cham : Springer, 2020

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Description 1 online resource (ix, 133 pages) : illustrations (some color) Series Lecture notes in artificial intelligence Lecture notes in computer science ; 11985 LNCS sublibrary. SL 7, Artificial intelligence Lecture notes in computer science. Lecture notes in artificial intelligence. Lecture notes in computer science ; 11985. LNCS sublibrary. SL 7, Artificial intelligence. Contents Intro -- Preface -- MIDAS 2019: The 4th Workshop on MIning DAta for financial applicationS -- Workshop Description -- Organization -- Contents -- MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning -- 1 Introduction -- 2 Background -- 3 Algorithm -- 4 Experiments -- 5 Related Work -- 6 Conclusion -- References -- Curriculum Learning in Deep Neural Networks for Financial Forecasting -- 1 Introduction -- 2 Related Work -- 3 Data -- 3.1 Data Structure -- 3.2 Microsoft Baseline -- 4 Methods -- 4.1 RNN Model: Encoder-Decoder LSTM -- 4.2 CNN Model: Dilated CNN 4.3 Evaluation -- 5 Results -- 5.1 World-Wide Error Rates -- 5.2 Segment-Level MAPEs -- 6 Discussion -- References -- Representation Learning in Graphs for Credit Card Fraud Detection -- 1 Introduction -- 2 Related Work -- 3 Inductive Representation Learning-Based Fraud Detection -- 3.1 Graph Structure -- 3.2 Traditional Network Featurization -- 3.3 Transductive Representation Learning -- 3.4 From Transductive Towards Inductive Representation Learning -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Tools -- 4.3 Experimental Design -- 4.4 Evaluation Metrics -- 5 Results -- 6 Conclusion -- References Firms Default Prediction with Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Firm-Default-Prediction Problem -- 3.1 Definition of Adjusted Default Status -- 4 Data and Methods -- 4.1 Dataset Description -- 4.2 Machine-Learning Approaches -- 5 Experimental Results -- 5.1 Evaluation Measures -- 5.2 Datasets -- 5.3 Balanced Versus Imbalanced Classes -- 5.4 Baselines -- 5.5 Prediction of Adjusted Default -- 5.6 A Practical Application: Probability of Default for Loan Subgroups -- 6 Conclusion -- References Convolutional Neural Networks, Image Recognition and Financial Time Series Forecasting -- 1 Introduction -- 2 Methods and Data -- 2.1 Recurrence Plots -- 2.2 CNN Model -- 2.3 Datasets -- 3 Experiments and Results -- 3.1 CNN Specifications -- 3.2 Experiment 1: Predicting Direction of SP500 -- 3.3 Experiment 2: Bankruptcy Detection -- 4 Conclusions -- References -- Mining Business Relationships from Stocks and News -- 1 Introduction -- 2 Related Work -- 3 Relationships from News -- 4 Relationships from Stocks -- 5 Comparing Relationship Graphs from Stocks and News -- 6 Conclusions -- References Mining Financial Risk Events from News and Assessing their Impact on Stocks -- 1 Introduction -- 2 Related Work -- 3 Risk Event Extraction -- 3.1 Risk Sentence Classification with Word Localization -- 3.2 Entity Recognition and Disambiguation -- 3.3 Target Entity Identification -- 4 Assessing Impact of Risk Events -- 5 Stock Movement Prediction -- 6 Experiments and Evaluations -- 6.1 Data Description -- 6.2 Results -- 7 Conclusion and Future Work -- References -- Monitoring the Business Cycle with Fine-Grained, Aspect-Based Sentiment Extraction from News -- 1 Introduction -- 2 Literature Review 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. -- Provided by publisher Notes Includes author index Online resource; title from PDF title page (SpringerLink, viewed January 21, 2020) Subject Data mining -- Congresses Finance -- Data processing -- Congresses Data protection -- Congresses Big data -- Security measures -- Congresses Data mining Data protection Finance -- Data processing Genre/Form proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès. Form Electronic book Author Bitetta, Valerio, editor Bordino, Ilaria, editor Ferretti, Andrea, editor Gullo, Francesco, editor Pascolutti, Stefano, editor Ponti, Giovanni, editor ECML PKDD (Conference) (2019 : Würzburg, Germany) ISBN 9783030377205 3030377202

Other Titles MIDAS 2019

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