Contact

Oxford-Man Institute

Content from the Oxford-Man Institute, our unique collaboration with the University of Oxford, which conducts pioneering research into quantitative finance, with a focus on cutting-edge machine learning techniques and data analytics.

Oxford-Man Institute

Our unique collaboration with the University of Oxford, which conducts pioneering research into quantitative finance.

Featured

Oxford-Man Institute: Fin-GAN - Forecasting via Generative Adversarial Networks

Academic Research read & watch 4 min
July 2023

Oxford-Man Institute: Fin-GAN - Forecasting via Generative Adversarial Networks

Can Generative Adversarial Networks (GANs) forecast financial time-series data? Milena Vuletić Postgraduate Student at the Oxford-Man Institute of Quantitative Finance shares her research findings.

Oxford-Man Institute: Mind Your Language! Market Reactions to Central Bank Speeches

Academic Research read & watch 3 min
June 2023

Oxford-Man Institute: Mind Your Language! Market Reactions to Central Bank Speeches

Can machine learning give investors a better insight into monetary policymaker speeches? Maximilian Ahrens, Postdoctoral Research Fellow in NLP at the Oxford-Man Institute of Quantitative Finance shares his research findings.

The Oxford-Man Institute ('OMI') is Man Group’s unique collaboration with the University of Oxford. Over the last decade, the OMI, part of the university’s Department of Engineering Science, has been conducting pioneering research into quantitative finance, and now focuses primarily on machine learning techniques and data analytics.

Located in the same building as Man AHL’s Oxford Research Lab, the OMI provides us with a direct connection to cutting-edge machine learning research and allows for the fruitful cross-pollination of ideas between the investment and academic communities. Work done at the OMI, including in areas seemingly unrelated to investment – such as galaxy classification and measurement of the height of tides – has directly contributed to our investment methodologies.

 

Go to Oxford-Man Institute

Archive

User Country: Hong Kong SAR (100)
User Language: en-hk
User Role: Public (Guest) (1)
User Access Groups:
Node Access Groups: 1