Digging into High Frequency Financial Data: present and future risks and opportunities (ATLANTIS)

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During the past decade, global equity markets have been fundamentally altered due to the vast improvements in the speed of trading and the consequent fragmentation (with multiple trading venues) of market activity. The increase in trading speed allows markets to operate far beyond human capabilities. Among other changes, traditional market makers have been replaced by high-frequency traders (HFTs) in most markets. This replacement has had a dramatic impact on the functioning and the stability of the financial markets. The resulting changes have led to intense debate and scrutiny from investors, market makers, exchanges, and regulators.To properly investigate from different perspectives the impact of HFTs on financial markets and the extent by which the resulting market efficiency, stability and ability to serve the real economy and society are affected, it is crucial to have the appropriate data and the capacity to manage these data in the first place.The first objective of this project is to structure, verify and homogenize multiple datasets already available to the researchers of the project and to create a transatlantic securities markets database (for common stocks but also for other securities such as bonds, options and futures) that can be easily used for research in Europe and the US. The primary goal is to set up the basic infrastructure to clean up and link the US and European datasets and to make this data accessible and exploitable for the research team and to provide knowledge on how to merge these data to other researchers and regulators. Such data in its raw form is unsuitable for analysis and the limit-order books need to be recreated in the first place, taking into consideration the peculiarities of each exchange and alternative trading venue. At present, no such database exists.The second objective is to analyze, compute and build models based on high frequency data to improve our understanding how electronic markets work. As demonstrated by successive financial crises in the last twenty years, the lack of empirical financial data in research and regulation is a hindrance to the wider understanding of these events. It is important to have a holistic data in order to understand causes, financial contagion, and consequences of financial turbulence. This project will help with interpreting the data, understanding global interconnectedness between securities and financial stakeholders, and providing new insights for understanding financial crises and constructing effective financial regulations.A subsequent third goal is to create a network of European and US researchers in finance and computational science who collaborate to generate and use very advanced computational tools to analyze and interpret this data for research and policy purposes. To go further, as part of this transatlantic initiative, the team plans to collaborate with other research centers in finance, applied mathematics, in physics and in computer science.The partners and principal investigators in this research team are:- PELIZZON Loriana, Research Center SAFE, Goethe University Frankfurt, Germany - "SAFE"- HENDERSHOTT Terrence John, Haas School of Business, University of California Berkeley, USA - "HAAS BS"- ZIGRAND Jean-Pierre, London School of Economics, United Kingdom - "LSE"- FONTAINE Patrice, Centre National de la Recherche Scientifique, Laboratory EUROFIDAI, Grenoble, France - "EUROFIDAI"- GETMANSKY SHERMAN Mila, Isenberg School of Management, UMass Amherst, USA - "UMASS"- SARLIN Peter, Hanken School of Economics, Helsinki, Finland - "HANKEN"