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DSMM'18: Proceedings of the Fourth International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets
ACM2018 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
SIGMOD/PODS '18: International Conference on Management of Data Houston TX USA 15 June 2018
ISBN:
978-1-4503-5883-5
Published:
15 June 2018
Sponsors:
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Abstract

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research-article
Predicting population-level socio-economic characteristics using Call Detail Records (CDRs) in Sri Lanka
Article No.: 1, Pages 1–12https://doi.org/10.1145/3220547.3220549

Prior work has shown that mobile network big data can be used as a high-frequency alternative data source to derive proxy measures that have strong predictive capacity to estimate census and poverty data in developing countries. Given that the ...

research-article
Feature Selection Methods For Understanding Business Competitor Relationships
Article No.: 2, Pages 1–6https://doi.org/10.1145/3220547.3220550

Understanding competition between businesses is essential for assessing the likely success of new ventures or products, for making decisions before investing capital in new businesses, and understanding the impacts of regulatory policy. One important ...

research-article
An Ontology of Ownership and Control Relations for Bank Holding Companies
Article No.: 3, Pages 1–6https://doi.org/10.1145/3220547.3220551

We consider the challenges and benefits of ontologies for information management for regulatory reporting from bank holding companies (BHCs). Many BHCs, especially the largest and most complex firms, have multiple federal supervisors who oversee a ...

extended-abstract
Learning Financial Networks using Quantile Granger Causality
Article No.: 4, Pages 1–2https://doi.org/10.1145/3220547.3220548

In the post-crisis era, financial regulators and policymakers require data-driven tools to quantify systemic risk and to identify systemically important firms. We propose a statistical method that measures connectivity in the financial sector using time ...

short-paper
Community Detection in Financial Entities: An Extended Abstract
Article No.: 5, Pages 1–2https://doi.org/10.1145/3220547.3220554

In this work we explore relationships between financial entities for the purpose of community detection. We use the MFIBlocks algorithm to perform the task via subspace clustering and present some initial results over the FEIII 2018 challenge dataset.

short-paper
Public Access
short-paper
Analysis of year-over-year changes in Risk Factors Disclosure in 10-K filings
Article No.: 8, Pages 1–4https://doi.org/10.1145/3220547.3220555

Risk Factor Disclosures -- Item 1A -- in 10-K forms filed with SEC is one of the important sections since it contains a company's yearly risk updates, and thus helps investors decide whether to invest in a company or not. It is crucial to read this ...

short-paper
Public Access
Financial Entity Identification and Information Integration (FEIII) 2018 Challenge: The Report of the Organizing Committee
Article No.: 9, Pages 1–3https://doi.org/10.1145/3220547.3225218

This report presents the goals and outcomes of the 2018 Financial Entity Identification and Information Integration (FEIII) Challenge. We describe the challenge task and the training dataset. The report summarizes the process, outcomes and plans for the ...

short-paper
Defining and Capturing the Competitor Relationship across Financial Datasets
Article No.: 10, Pages 1–6https://doi.org/10.1145/3220547.3220556

The 2018 FEIII Data Challenge aims to enhance a given knowledge graph by validating and enriching the set of competitor edges in the graph using multiple datasets. Upon an investigation of the data, we find that some of the competitor edges given as ...

short-paper
PREFER: PREdiction Model for Financial Entity Relation
Article No.: 11, Pages 1–2https://doi.org/10.1145/3220547.3220557

The Financial Entity Identification and Information Integration (FEIII) is a competition for the understanding relationships between financial entities. To predict competitor relation between two entities, there are three challenges - 1) relevant ...

short-paper
Predicting competitor links in company networks
Article No.: 12, Pages 1–3https://doi.org/10.1145/3220547.3220558

The scored task at FEIII Challenge 2018 proposed the identification of competitor relationships in a network of companies from the financial and IT sectors. This article describe our BBVA Data & Analytics submission to the challenge and our experiments ...

short-paper
Using supervised learning techniques for entity relationships
Article No.: 13, Pages 1–2https://doi.org/10.1145/3220547.3226044

Given different financial data resources, it is very challenging to relate entities across the various resources since each resource has its own way of describing the entities and relationships. We work on identifying such relationships using context ...

short-paper
Public Access
Hybrid Link Prediction for Competitor Relationships
Article No.: 14, Pages 1–4https://doi.org/10.1145/3220547.3220559
Index terms have been assigned to the content through auto-classification.

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Acceptance Rates

DSMM'18 Paper Acceptance Rate 14 of 17 submissions, 82%;
Overall Acceptance Rate 32 of 64 submissions, 50%
YearSubmittedAcceptedRate
DSMM'1913323%
DSMM'18171482%
DSMM'1617635%
DSMM'1417953%
Overall643250%