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Gelly Mitrodima's research interests are centered around financial modeling and forecasting, utilizing a Bayesian nonparametric and semiparametric framework. Her methodology includes techniques such as Markov chain Monte Carlo and the development of quantile time series models, specifically designed for financial data analysis. After joining the Department of Statistics at the London School of Economics (LSE), she spent four years at the University of Kent, where she completed her PhD in Actuarial Science from the School of Mathematics, Statistics, and Actuarial Science. Her doctoral thesis focused on using quantile methods to estimate and forecast time-varying conditional asset returns. Gelly has contributed to various publications, including articles and conference papers, and has significant expertise in econometrics, risk management, and statistics.
Department of Economics