PhD dissertation of Giorgio Mirone

BigDataFinance Early stage Researcher Giorgio Mirone defended his PhD dissertation entitled “Measurement, assessment and forecast of integrated variance” on Friday 23 November 2018. Giorgio Mirone has been enrolled in the PhD programme in Economics and Business Economics. Professor Kim Christensen has been his supervisor and Professor Asger Lunde has been his co-supervisor. The dissertation can […]

11.12.2018 Read more

Big Data Finance: PhD Thesis in Three Mi..

BigDataFinance Early Stage Research Vladimir Petrov, based at Universi..

27.11.2018 Read more

Volatility seasonality of Bitcoin prices..

“Learning properties of Bitcoin and other cryptocurrencies and c..

21.06.2018 Read more

big data in finance

BigDataFinance 2015–2019, a H2020 Marie Sklodowska-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.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 675044.



BigDataFinance protagonist at the 6th Lindau Meeting in Economic Sciences

ESR Chiara Perillo from Univer.. ESR Chiara Perillo from University of Zurich shared the stage with Nobel Prize L..

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BigData analysis of financial interconnectedness: the new challenge to prevent contagion

The following blog article is .. The following blog article is based on the opening statements delivered by Chiar..

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Scientific paper receives multiple prizes

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The Order Book: A Challenge For Tomorrow’s Econometrics

The modeling of the order book.. The modeling of the order book is certainly one of the major chal- lenges for th..

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A brief introduction to Big Data and Signal Processing

The chaotic nature of financia.. The chaotic nature of financial big datasets requires in depth analysis of their..

13.11.2017 Read more

BigDataFinance Conference – Presentations Available!

BigDataFinance conference pres.. BigDataFinance conference presentations from Oct 4th and 5th 2017 are now ava..

19.10.2017 Read more


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