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BigDataFinance SIGNED

Training for Big Data in Financial Research and Risk Management

Total Cost €


EC-Contrib. €






Project "BigDataFinance" data sheet

The following table provides information about the project.


There are not information about this coordinator. Please contact Fabio for more information, thanks.

 Coordinator Country Finland [FI]
 Project website
 Total cost 3˙463˙286 €
 EC max contribution 3˙463˙286 € (100%)
 Programme 1. H2020-EU.1.3.1. (Fostering new skills by means of excellent initial training of researchers)
 Code Call H2020-MSCA-ITN-2015
 Funding Scheme MSCA-ITN-ETN
 Starting year 2015
 Duration (year-month-day) from 2015-10-01   to  2019-09-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
2    TTY-SAATIO FI (TAMPERE) coordinator 0.00
3    AARHUS UNIVERSITET DK (AARHUS C) participant 580˙163.00
5    UNIVERSITAT ZURICH CH (ZURICH) participant 530˙453.00
6    INSTITUT JOZEF STEFAN SI (LJUBLJANA) participant 469˙995.00
7    ALLIANCEBERNSTEIN LIMITED UK (LONDON) participant 273˙287.00
8    ING GROEP NV NL (AMSTERDAM) participant 255˙374.00
12    OLSEN LTD AG CH (ZURICH) partner 0.00
13    Techila Technologies FI (TAMPERE) partner 0.00


 Project objective

BigDataFinance, a Marie SkÅ‚odowska-Curie Innovative Training Network “Training for Big Data in Financial Research and Risk Management”, provides doctoral training in sophisticated data-driven risk management and research at the crossroads of Finance and Big Data for 13 researchers. The main objectives are i) to meet an increasing commercial demand for well-trained researchers experienced in both Big Data techniques and Finance and ii) to develop and implement new quantitative and econometric methods for empirical finance and risk management with large and complex datasets. To achieve the objectives, the emphasis is put on exploiting big data techniques to manage and use datasets that are too large and complex to process with conventional methods.

Banks and other financial institutions must be able to manage, process, and use massive heterogeneous data sets in a fast and robust manner for successful risk management; nonetheless, financial research and training has been slow to address the data revolution. Compared to the USA, Europe is still at an early stage of adopting Big Data technologies and services. Immediate action is required to seize opportunities to exploit the huge potential of Big Data within the European financial world.

This world-class network consists of eight academic participants and six companies, representing banks, asset management companies, and data and solution providers. The proposed research is relevant both academically and practically, because the program is built around real challenges faced both by the academic and private sector partners. To bridge research and practice, all researchers contribute to the private sector via secondments.

BigDataFinance provides the European financial community with specialists with state-of-the-art skills in finance and data-analysis to facilitate the adoption of reliable and realistic methods in the industry. This increases the financial strength of banks and other financial institutions in Europe.


List of deliverables.
A report on a new model with statistical analysis of the relation between order book dynamics and news arrivals Documents, reports 2020-03-11 10:41:34
A report on an extended approach to characterise financial markets from an event-driven perspective Documents, reports 2020-03-11 10:38:00
A report on a new model augmented with news data sources Documents, reports 2020-03-11 10:38:00
A report on the analysis of the structure and dynamics of volatility in financial markets with news arrivals Documents, reports 2020-03-11 10:38:01
A report on an analysis of the behavioural differences between institutional and individual investors and ownership diversity during the recent financial crisis Documents, reports 2020-03-09 16:07:47
A report on a tested and validated risk management tool based on scaling laws for FX markets Documents, reports 2020-03-09 16:07:33
Compilation of training material Other 2020-03-09 16:07:33
Final conference Other 2020-03-09 16:07:54
Report on dissemination activities Documents, reports 2020-03-09 16:07:43
A report on back-tested, validated risk management and portfolio construction tools to monitor risks in smart beta investing Documents, reports 2020-03-09 16:07:28
A report and software on data sampling techniques Documents, reports 2020-03-09 16:07:44
A report on a tested and assessed prototype for a real-time financial market mood and confidence index Documents, reports 2020-03-09 16:07:35
A report and software on a verified and validated knowledge extraction prototype with different data sources Documents, reports 2020-03-09 16:07:49
A report on a model to define and measure systemic risk in financial networks and its empirical analysis Documents, reports 2020-03-09 16:07:41
A report on a tested and validated system for risk management with real data and simulated stressed scenarios Documents, reports 2020-03-09 16:07:43
A report and software on a real-time learning method to update decentralised models and address financial market velocity Documents, reports 2020-03-09 16:07:44
Summer School: Introduction to econometrics and empirical modelling of financial markets Other 2019-09-06 08:54:20
Dissemination plan Documents, reports 2019-09-06 08:54:20
Website published Other 2019-09-06 08:54:20
Kick-off meeting: Data Science in Finance Other 2019-09-06 08:54:20
Conference: Big Data in Finance Other 2019-09-06 08:54:20
Winter School and Workshop: Complex networks in finance Other 2019-09-06 08:54:20
Training Event: Textual data in finance Other 2019-09-06 08:54:20

Take a look to the deliverables list in detail:  detailed list of BigDataFinance deliverables.


year authors and title journal last update
List of publications.
2019 Anastassia Fedyk, James Hodson
Trading on Talent: Human Capital and Firm Performance
published pages: , ISSN: 1556-5068, DOI: 10.2139/ssrn.3017559
SSRN Electronic Journal 2019-12-16
2019 Vladimir Petrov, Anton Golub, Richard B. Olsen
Intrinsic Time Directional-Change Methodology in Higher Dimensions
published pages: , ISSN: , DOI:
2019 Anastassia Fedyk, James Hodson
Aggregation Effect in Stale News
published pages: , ISSN: 1556-5068, DOI: 10.2139/ssrn.2433234
SSRN Electronic Journal 2019-12-16
2019 Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis, Adamantios Ntakaris, Juho Kanniainen, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis
Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data
published pages: 64722-64736, ISSN: 2169-3536, DOI: 10.1109/access.2019.2916793
IEEE Access 7 2019-12-16
2018 Ntakaris, Adamantios; Kanniainen, Juho; Gabbouj, Moncef; Iosifidis, Alexandros
Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators
published pages: , ISSN: , DOI:
5 2019-12-16
2018 Baltakiene, M.; Baltakys, K.; Cardamone, D.; Parisi, F.; Radicioni, T.; Torricelli, M.; de Jeude, J. A. van Lidth; Saracco, F.
Maximum entropy approach to link prediction in bipartite networks
published pages: , ISSN: , DOI:
11 2019-12-16
2019 Sergio Garcia-Vega, Xiao-Jun Zeng, John Keane
Stock Price Prediction Using Kernel Adaptive Filtering Within a Stock Market Interdependence Approach
published pages: , ISSN: , DOI:
2019 Margarita Baltakienė, Kęstutis Baltakys, Juho Kanniainen, Dino Pedreschi, Fabrizio Lillo
Clusters of investors around initial public offering
published pages: , ISSN: 2055-1045, DOI: 10.1057/s41599-019-0342-6
Palgrave Communications 5/1 2019-12-16
2018 Vladimir Petrov, Anton Golub, Richard B. Olsen
Agent-Based Model in Directional-Change Intrinsic Time
published pages: , ISSN: 1556-5068, DOI: 10.2139/ssrn.3240456
SSRN Electronic Journal 2019-09-09
2018 Milla Siikanen, Kęstutis Baltakys, Juho Kanniainen, Ravi Vatrapu, Raghava Mukkamala, Abid Hussain
Facebook drives behavior of passive households in stock markets
published pages: 208-213, ISSN: 1544-6123, DOI: 10.1016/
Finance Research Letters 27 2019-09-09
2019 Ioannis Anagnostou, Drona Kandhai
Risk Factor Evolution for Counterparty Credit Risk under a Hidden Markov Model
published pages: 66, ISSN: 2227-9091, DOI: 10.3390/risks7020066
Risks 7/2 2019-09-09
2019 Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
Feature Engineering for Mid-Price Prediction With Deep Learning
published pages: 82390-82412, ISSN: 2169-3536, DOI: 10.1109/access.2019.2924353
IEEE Access 7 2019-09-09
2019 Ioannis Anagnostou, Javier Sanchez Rivero, Sumit Sourabh, Drona Kandhai
Contagious defaults in a credit portfolio: a Bayesian network approach
published pages: , ISSN: 1755-9723, DOI:
Journal of Credit Risk 2019-09-09
2018 Kęstutis Baltakys, Juho Kanniainen, Frank Emmert-Streib
Multilayer Aggregation with Statistical Validation: Application to Investor Networks
published pages: , ISSN: 2045-2322, DOI: 10.1038/s41598-018-26575-2
Scientific Reports 8/1 2019-09-09
2019 Vladimir Petrov, Anton Golub, Richard Olsen
Instantaneous Volatility Seasonality of High-Frequency Markets in Directional-Change Intrinsic Time
published pages: 54, ISSN: 1911-8074, DOI: 10.3390/jrfm12020054
Journal of Risk and Financial Management 12/2 2019-09-09
2018 Chiara Perillo, Stefano Battiston
A multiplex financial network approach to policy evaluation: the case of euro area Quantitative Easing
published pages: 49, ISSN: 2364-8228, DOI: 10.1007/s41109-018-0098-8
Applied Network Science 3/1 2019-09-09
2019 Sergio Garcia-Vega, Xiao-Jun Zeng, John Keane
Learning from data streams using kernel least-mean-square with multiple kernel-sizes and adaptive step-size
published pages: 105-115, ISSN: 0925-2312, DOI: 10.1016/j.neucom.2019.01.055
Neurocomputing 339 2019-09-09
2018 Milla Siikanen, Kestutis Baltakys, Hannu KKrkkkinen, Jari Jussila, Ravi Vatrapu, Raghava Mukkamala, Abid Hussain, Juho Kanniainen
How Facebook Drives Investor Behavior
published pages: , ISSN: 1556-5068, DOI: 10.2139/ssrn.3040621
SSRN Electronic Journal 2019-09-09
2018 Frank Emmert-Streib, Aliyu Musa, Kestutis Baltakys, Juho Kanniainen, Shailesh Tripathi, Olli Yli-Harja, Herbert Jodlbauer, Matthias Dehmer
Computational analysis of structural properties of economic and financial networks
published pages: 1-32, ISSN: 2055-7795, DOI: 10.21314/jntf.2018.043
The Journal of Network Theory in Finance VOLUME 4, NUMBER 3 (SEPTEMBER 2 2019-09-09
2018 Kȩstutis Baltakys, Margarita Baltakienė, Hannu Kärkkäinen, Juho Kanniainen
Neighbors matter: Geographical distance and trade timing in the stock market
published pages: , ISSN: 1544-6123, DOI: 10.1016/
Finance Research Letters 2019-09-09
2018 Giorgio Mirone
Cross-sectional noise reduction and more efficient estimation of Integrated Variance
published pages: 40, ISSN: , DOI:
CREATES Research Papers 2019-09-06

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