University of Bath School of Management University of Bath School of Management

Dr Jooyoung Jeon

Dr Jooyoung Jeon
Contact

telephone +44 (0) 1225 386742
email Dr Jooyoung Jeon

Publications

Leading Refereed Journal Papers

DPhil degree in Management Studies

Job Title:

Lecturer

Division:

Information, Decision and Operations

Key Research Interests:

Renewable Energy Analytics, big data, decision making under uncertainties, financial risk management, social media analytics

Research Interests

Dr Jooyoung Jeon’s research focuses on business analytics. He is particularly interested in estimating forecast uncertainty in the following areas: renewable energy analytics (generation and demand), financial risk analysis and social media analytics. His research has been supported by the Peer to Peer Energy Trading and Sharing project funded by the UK EPSRC (EP/N03466X/1), the Safe Wind project under the 7th EU Framework Program (Theme 2007-2.3.2: Energy Grant Agreement N° 213740) and Her Majesty’s Government.

Jooyoung have a BSc in computer science from the Seoul National University, a MSc in Finance from the London Business School and a DPhil degree in Management Studies from the Saïd Business School, University of Oxford. The previous appointments include Lecturer in Management Science at Strathclyde Business School and Junior Research Fellow at the University of Oxford. He has also worked for the IBM and co-founded an IT company.

He has held the visiting Associate Professorship in the Graduate School of Engineering Practice, Seoul National University since 2016.

PhD Supervision

I welcome enquiries from potential PhD students in my research interest areas.

Publications

Leading Refereed Journal Papers

Jeon, J. & Taylor, J. W. 2016. . Short-term Density Forecasting of Wave Energy Using ARMA-GARCH models and Kernel Density Estimation. International Journal of Forecasting, 32: 991-1004, DOI:10.1016/j.ijforecast.2015.11.003

Taylor, J. W. & Jeon, J. 2015. . Forecasting wind power quantiles using conditional kernel estimation.. Renewable Energy, 80: 370-379, DOI:10.1016/j.renene.2015.02.022

Jeon, J. & Taylor, J. W. 2013. Using CAViaR models with implied volatility for value-at-risk estimation. Journal of Forecasting, 32(1): 62-74, DOI: 10.1002/for.1251.

Jeon, J. & Taylor, J. W. 2012. Using conditional kernel density estimation for wind power density forecasting. Journal of the American Statistical Association, 107: 66-79, DOI: 10.1080/01621459.2011.643745.