Enterprise Applications, Markets and Services in the Finance Industry: 10th International Workshop, FinanceCom 2020 Helsinki, Finland, August 18, 2020, Revised Selected Papers

Preface
Organization
Contents
Machine Learning Applications in Trading and Financial Markets
State-of-the-Art in Applying Machine Learning to Electronic Trading
	1 Introduction
	2 Background
		2.1 Components of an Electronic Trading System
		2.2 Upstream Decision Making
		2.3 Analysing Information Sources
		2.4 Trading Decision Making and Order Execution Management
		2.5 Pre-trade and Post-trade Analytics
	3 Survey Methodology
	4 Results Per Categories
		4.1 Analysing Data Patterns
		4.2 Information Processing and Analysis
		4.3 Trading Decision Making and Order Execution Management
	5 Summary, Conclusions and Further Work
	References
Using Machine Learning to Predict Short-Term Movements of the Bitcoin Market
	1 Introduction
	2 Related Work
		2.1 Market Efficiency and Financial Market Prediction
		2.2 Bitcoin Market Prediction via Machine Learning
	3 Methodology
		3.1 Data
		3.2 Generation of Training, Validation and Test Sets
		3.3 Features
		3.4 Targets
		3.5 Prediction Models
		3.6 Evaluation
	4 Results
	5 Discussion
	6 Conclusion
		A Supplemental Tables
		B Supplemental Graphical Material
	References
Fraud Detection and Information Generation in Finance
Scalable and Imbalance-Resistant Machine Learning Models for Anti-money Laundering: A Two-Layered Approach
	1 Introduction
	2 Related Work
	3 Data
	4 Methodology
		4.1 Two-Layered Model Concept
		4.2 Framework
		4.3 Feature Extraction
		4.4 Tackling Class Imbalance
	5 Experimental Setup
	6 Results
		6.1 First Layer Results
		6.2 Second Layer Results
		6.3 Overall Results
	7 Conclusions and Future Work
	A Appendix
	References
Leveraging Textual Analyst Sentiment for Investment
	1 Introduction
	2 Data
	3 Methodology
		3.1 Trading Signals
		3.2 Portfolio Construction
		3.3 Impact of Forecast Error
		3.4 Performance Evaluation
	4 Results
	5 Discussion and Conclusion
	Appendix
	References
Alternative Trading and Investment Offerings by FinTechs
Portfolio Rankings on Social Trading Platforms in Uncertain Times
	1 Introduction
	2 Theoretical Foundations
		2.1 Social Trading
		2.2 Rankings on Online Platforms
		2.3 Rankings in the Context of Social Trading Platforms
	3 Dataset and Descriptive Statistics
	4 Analysis
	5 Discussion
	6 Conclusion
	References
What Do Robo-Advisors Recommend? - An Analysis of Portfolio Structure, Performance and Risk
	1 Introduction
	2 Foundations and Related Research on Robo-Advisors
		2.1 Robo-Advisor Definition and Process
		2.2 Research on Robo-Advisor Portfolio Structures
	3 Methodology
		3.1 Analysis Approach
		3.2 Analysis Measures and Statistical Test Procedures
	4 Findings
		4.1 Portfolio Products and Allocation
		4.2 Portfolio Performance and Risk
	5 Discussion
		5.1 Implications
		5.2 Limitations and Future Research
	6 Conclusion
	Appendix
	References
Invited Talk
The Financial Viability of eHealth and mHealth
	1 Introduction
	2 eHealth/mHealth Costs
	3 Occupation Therapy Case Study
		3.1 Actual OT Paper-Based Assessment Process
		3.2 Proposed mHealth-Based OT Assessment Process
		3.3 Tentative Direct Cost Analysis Model
	4 Conclusions
	Reference
Author Index