The ERC-funded ‘Global Correspondent Banking 1870–2000’ (GloCoBank) project at the University of Oxford will host a workshop for early-career researchers to explore novel approaches to data creation and data analytics in economic, financial and business history.
The workshop aims to explore the crossroads between data scientists, economic historians and geographers, and business researchers in the fields of international economic, business, and financial relations. The workshop is also open to multi-disciplinary applications of large-scale data analytics.
Recent advances in data analytics open up new opportunities for business and economic research. Archival sources can now be digitalised at a larger scale and over longer time spans, for both structured and unstructured data. New analytical techniques can unlock comparative analysis of cross-border financial flows at multiple levels and reconstruct strategic behaviour of actors within complex financial networks.
This workshop will connect early-career researchers endeavouring to advance the frontiers of future research within their core disciplines and set a new vision for data analytics in historical research. We look forward to building a research community to inspire collaboration between disciplines.
Session 2: Text-mining and machine learning for economic and banking time-series
14:00 – 15:30
Jules H. van Binsbergen (Wharton and NBER), Svetlana Bryzgalova (London Business School and CEPR), Mayukh Mukhopadhyay (London Business School), and Varun Sharma (Nanyang Business School)
