Professor Baibing Li BSc (Yunnan), MSc (Vrije Brussel), PhD (Shanghai Jiao Tong)
Professor of Business Statistics and Management Science
Bayesian statistical modelling; data mining; statistical modelling for financial markets; transportation and traffic studies
Baibing is Professor of Business Statistics and Management Science at the School of Business and Economics. Prior to his current appointment, he was a Lecturer in Statistics in the School of Mathematics and Statistics at Newcastle University. In 2004, he moved to Loughborough University, as a Lecturer in the School of Business and Economics, where he was subsequently appointed as Reader in 2007, and then Professor in 2011. He is programme director of Management Sciences and programme director of Management.
Baibing’s research focuses on statistical machine learning and data mining, covering a wide range of topics such as predictive modelling, dimension reduction, and forecasting, as well as applications to various business and management problems in transport studies and financial markets.
Baibing’s research focuses on statistical machine learning and data mining, covering a wide range of topics such as predictive modelling, dimension reduction, and forecasting.
In his recent theoretical research on state space models and Markov switching processes, Baibing develops new algorithms to deal with state estimation/forecasting problems for stochastic nonlinear dynamic systems when new data is collected in real time. His research interests also cover predictive modelling, dimension reduction methods, kernel methods, and mixture models.
In the recent years much of his work has involved applications to transport studies and financial markets. The former includes transportation demand analysis, travel behaviour modelling, and intelligent transportation systems. The latter involves statistical modelling for financial markets, hedge fund performances, etc.
Baibing enjoys supervising his PhD students, whose research topics span a wide range of business and management problems such as, for example, stochastic frontier analysis for economic growth, traffic flow modelling and analysis with high-frequency data, liquidity timing analysis of hedge funds, asset portfolio allocation, and financial market modelling and forecasting via Markov switching approach, mispricing chasing and hedge funds performances. Baibing welcomes applications for PhD research in various areas of business analytics, such as financial market modelling and forecasting, data mining and applications in marketing.
Baibing is a Chartered Statistician (CStat) of Royal Statistical Society and Senior Member of IEEE. In the recent years, Baibing served as external examiner at Manchester Business School (2011-2014) and UCD College of Business, University College Dublin (2015-2018). He is a reviewer for a number of journals including Journal of the Royal Statistical Society: Series A, Series B, and Series C; Transportation Research: Part B and Part C; IEEE Transactions on Automatic Control; Journal of the Operational Research Society; European Journal of Operational Research, etc.
Baibing has published research articles in a wide range of outlets. His recent representative publications include:
Li, C, Li, B, Tee, K-H (2020) Measuring liquidity commonality in financial markets, Quantitative Finance, 20(9), pp.1553-1566.
Li, B (2019) Measuring travel time reliability and risk: A nonparametric approach, Transportation Research Part B: Methodological, 130, pp.152-171.
Li, C, Li, B, Tee, K-H (2019) Are hedge funds active market liquidity timers?, International Review of Financial Analysis, 67, 101415.
Li, B, Liu, C, Chen, W-H (2017) An Auxiliary Particle Filtering Algorithm with Inequality Constraints, IEEE Transactions on Automatic Control, 62(9), pp.4639-4646.
Li, B and Hensher, D (2017) Risky Weighting in Discrete Choice, Transportation Research Part B: Methodological, 102, pp.1-21.