导师简介
Mihai Cucuringu is an Associate Professor in the Department of Statistics, and an Affiliate Faculty in the Mathematical Institute at University of Oxford. He is also a Stipendiary Lecturer in Statistics at Merton College, University of Oxford, and a Turing Fellow at The Alan Turing Institute in London.
Website:
http://www.stats.ox.ac.uk/~cucuring/
招生信息
The Oxford Man Institute has implemented a visitors programme, to facilitate visits to Oxford from strong PhD students (and postdocs) from worldwide universities, for a duration typically in the range 3-6 months (potentially with an extension of up to a total of 12 months, if the project requires it), to work on a quantitative finance research topic.
The project would be supervised by Prof. Mihai Cucuringu, ideally on topics broadly situated at the intersection of machine leaning and statistics for finance:
news sentiment propagation in financial networks (US Equity)
a deep learning framework for asset pricing with heterogeneous data sources (news and technical factors) (Chinese Equity)
lead-lag detection and network clustering for nonlinear multivariate time series (US equity)
cross-asset models (CAM) for learning stock interactions; high-dimensional setting (Chinese Equity)
times series price and limit order book simulation with GANs (US/EU Equity)
factor models for limit order flow, conditional order flow imbalance, cross-impact, nowcasting and forecasting (US Equity)
analysis of option volume for predicting spot market returns (US Options/Equity)
analysis and modelling of client order flow in limit order markets
network effects in high-frequency order flows (US Equity)
graph-based asset pricing; fundaments and trade flow data (US Equity)
microstructure and network effects in cryptocurrency markets (top 14 most liquid crypto exchanges)
clustering and change-point detection in time series and correlation networks
dimensionality reduction and cross-impact for fundamentals data for short/medium term forecasts
determinants of cancellation behaviour in limit order books
modelling of non-bank financial institutions
commonality in volatility
申请方式
Note that the institute is not able to handle any visa-related issues. Please contact Chao Zhang (chao.zhang@stats.ox.ac.uk) for further inquiries, along with a CV.
