Dr Diana Roman
Tower A 028
- Email: email@example.com
- Tel: +44 (0)1895 267502
Dr Diana Roman is a lecturer in the Department of Mathematics. Her research is in the area of decision making under uncertainty and risk, tackled through the paradigm of stochastic optimisation. This means that the parameters involved in optimisation are not known with certainty, but described by statistical distributions and approximated by discrete distributions, given by possible realisations, called “scenarios”. Optimisation and simulation techniques can be applied to a variety of fields. A major application is financial portfolio optimisation. Key research sub-areas are: risk modelling and minimisation, modelling randomness in asset prices, hedging against downside risk and extreme loss, cash flow matching of assev values and liabilities, finding computational solutions for the resulting optimisation models.
Dr Roman is a leader for level two modules and for level one project groups. She is a supervisor for final year projects and also for research students. Dr Roman is part of the Admissions team in the Department of Mathematics.
Newest selected publications
Alwohaibi, M. and Roman, D. (2018) 'ALM models based on second order stochastic dominance'. Computational Management Science. pp. 1 - 25. ISSN: 1619-697X Open Access Link
Roman, D., Arbex Valle, C. and Mitra, G. (Accepted) 'Novel Approaches for Portfolio Construction using Second Order Stochastic Dominance'. Computational Management Science. ISSN: 1619-697X Open Access Link
Maasar, MA., Roman, D. and Date, P. (2016) 'Portfolio optimisation using risky assets with options as derivative insurance'. ISSN: 2190-6807 Open Access Link
Date, P., Ponomareva, K. and Roman, D. (2015) 'An algorithm for moment-matching scenario generation with application to financial portfolio optimization'. European Journal of Operational Research, 240 (3). pp. 678 - 687.Open Access Link
Hussin, SAS., Mitra, G. and Roman, D. (2014) 'An asset and liability management (ALM) model using integrated chance constraints'. ISSN: 0094-243X Open Access Link