Seeking Postdocs for Data Science in Finance

Would you like to get desired and prestigious EU funding for your Post-Doc? We are seeking talented  researchers in quantitative finance / financial data science for hosting and coaching them for EU-funding. The idea is to make a joint EU application for  2 year postdoc position at research group on Financial Computing and Data Analytics, […]

21.04.2023 Read more

The ups and downs of a PhD project: Big ..

Read here the success story of ESR5 Chiara Perillo and ESR12 Vladimir ..

02.01.2020 Read more

Listening to the financial heartbeat wit..

Time, as they say, is of essence in the financial world. Every second ..

29.08.2019 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.



Portfolio credit risk: standard models won’t hit the mark in capturing default dependence

Portfolio credit risk models a.. Portfolio credit risk models are concerned with potential losses due to defaults..

20.08.2019 Read more

Using news for finding firm relations and implications on financial markets

Finding correlations between p.. Finding correlations between publicly traded companies is a topic of interest fo..

14.08.2019 Read more

An introduction to sentiment analyses

The general idea behind sentim.. The general idea behind sentiment analyses in finance is the existence of releva..

12.08.2019 Read more

Financial Data Analysis: Machine Learning and Interconnections Between Stock Markets

Financial markets are complex,.. Financial markets are complex, interconnected and deterministically chaotic syst..

07.08.2019 Read more

Smart beta investing – How can big data help?

Smart beta is a relatively new.. Smart beta is a relatively new term that has became ubiquitous in finance in the..

31.05.2019 Read more

Call for Papers

Please visit https://bigdatafi.. Please visit

06.05.2019 Read more


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