Hanken researcher member of global financial research project
The project “Digging into High Frequency Data” Opens in new window aims at improving the security of financial markets, which have been radically altered over the past decade due to vastly improved trading speeds. The team will create a transatlantic securities market database, allowing researchers to better analyse high frequency data generated by automated trading.
- Hanken’s part in the project will focus on machine learning with the aim of learning to provide interpretable models on big financial data by visualizing and conducting exploratory analysis to find structures in this data, says Peter Sarlin, Associate Professor and project leader at Hanken.
The project will make use of machine learning methods for exploratory analysis, including so called visual dynamic clustering, which pertains to reducing complexity of big data, by reducing the volume of data, dimensionality of data and the frequency of data.
The funding of the project is international, in Finland the project is funded by the Academy of Finland.
At Hanken, the project is led by Associate Professor Peter Sarlin. The other principal investigators are: Dr Patrice Fontaine (EUROFIDAI, France); Prof Terrence Hendershott (UC Berkeley, USA), Prof Loriana Pelizzon (Goethe University, Germany); Prof Mila Getmansky Sherman (University of Massachusetts Amherst, USA), Prof Tomaso Aste (University College London, UK) and Prof Jean-Pierre Zigrand (London School of Economics, UK).
Read more about the project:
https://diggingintodata.org/awards/2016/news/winners-round-four-t-ap-digging-data-challenge
More information:
Peter Sarlin
peter.sarlin@hanken.fi
+358 40 572 7670