My current post at the Busines School is Senior Lecturer in Finance. I am the module leader of Applied Statistics for Business and Management and Research Methods.
My research interests are:
Bayesian non-parametric models and related Monte Carlo Markov Chain methods, Stochastic Processes, Time Series, Bayesian Regression methods and Bayesian variable selection.
The application areas I am interested in are :
Financial Econometrics, Quantitative Finance, Market Micro Structure and Medical Statistics.
My academic qualifications are:
Bsc in Econometrics and Mathematical Economics, MA in Mathematical Statistics, MBA in Financial Engineering, PhD in Statistics, and PGCHE.
Previous Academic Experience:
Lecturer in Statistics, Center of Health Services Studies, University of Kent.
Teaching Fellow, Stern School of Business, New York University.
Graduate student Instructor, Department of Statistics, University of Michigan
Professional Work Experience:
Senior Quantitative Analyst - Ministry of Finance, Cyprus
Associate, Equity Devision, Goldman Sachs International - New York
Research and knowledge exchange
Co-Investigator - 0.5FTE
NIHR-Health Services Research (grant no: 11/2004/28), Development of a risk model for the prediction of new or worsening Acute Kidney Injury (AKI). Total grant amount £300,000 (Awarded, Dec 2012)
MRC-Methodology: Bayesian predictive modelling for chronic kidney disease. Total grand amount £300,000 (Invited resubmission, Oct 2013)
NIHR-Health Services Research. Evaluating risk models for prediction of new or worsening Acute Kidney Injury (AKI) in secondary care. Total grant amount £275,000 (Awarded, April 2014)
Consultant-Investigator: East Kent Hospital University Trust
Investigation of the rise in re-admission rates in Kent. Total consultancy amount £9,000 (Awarded, January 2010)
Investigation of maternity services in East and Coastal Kent: a statistical perspective. Total consultancy amount £ 6,000 (Awarded, March 2011)
Dr Michael Bedford, renal registar, East Kent Hospital University Trust. ''A Bayesian hierarchical risk model for predicting AKI''. Started July 2011.
Teaching and subject expertise
Applied Statistics for Business and Management, Research Methods (Advanced Applied Statistics), Biostatistics, Hierarchical Linear Models, Corporate Finance and Introduction to probability.
Multivariate methods, Cluster Analysis, and Forecasting and Time Series Analysis.
International Bayesian Society (ISBA). (Jan 2008-present)
- Bayesian non-parametric section. (Jan 2010-present)
- Bayesian Computation section (Jan 2013 – present)
- Economics, Finance and Business section. (Jan 2012-present)
Chartered Institute of Securities and Investments. (June 2012-present)
Funding Committee Member:
National Institute for Health Research-Research for Patient Benefit-South East Coast. (Jan 2008-present)
National Institute for Health Research-Health Technology Assessment. (June 2012-present)
Statistics editor for Manual Therapy Journal. (Jan 2011-present)
Journal of Econometrics,
Statistics and Computing,
Journal of Applied Econometrics,
Journal of the Royal Statistical Society-B,
Computational Statistics and Data Analysis.
The Rimini Conference in Economics and Finance, RCEF-2014, Rimini, June 2014
Bayesian Semi-parametric vector autoregressive models and related impulse response functions with applications to macroeconomics.
7th Conference in Computational & Financial Econometrics, London, December 2013
Bayesian Semi-parametric vector autoregressive models and the estimation of correlation and cross correlation matrices.
Department of Finance, Accounting, and Statistics, Vienna University of Economics and Business, Vienna, Dec 2013
Bayesian Semi-parametric vector autoregressive models.
6th Conference in Computational & Financial Econometrics, Oviedo, Dec 2012
Time varying sparsity in dynamic regression models.
ISBA World Meeting, Japan, June 2012
Special Topics : Beyond MCMC methods in Bayesian Inference, Slice Sampling algorithms in Bayesian nonparametrics: theory and properties.
4th ERCIM Conference in Computing & Statistics, London, Dec 2011
Flexible modelling of dependence in volatility processes.
4th Conference in Computational & Financial Econometrics, London, Dec 2010
Modelling the conditional distribution of daily stock index returns: an alternative Bayesian semi-parametric model.
Functional Simulation Workshop, University of Warwick, June 2009
Stick Breaking Processes and the Slice Sampler
8th Bayesian nonparametrics conference, University of Cambridge, August 2008
A Bayesian semi-parametric GARCH model, and related MCMC algorithms.
Publications and research outputs
M. Kalli, J.E. Griffin, S.G.Walker (2011); Slice Sampling Mixture Models; Statistics and Computing, Volume 21, Issue 1, 93-105.
M.Kalli, S.G. Walker, Paul Damien (2014); Modelling the conditional distribution of daily stock index returns: an alternative Bayesian semi-parametric model; Journal of Business and Economic Statistics , Volume 31, Issue 4, 371-383.
M.Kalli, J.E. Griffin (2014); Time varying sparsity in dynamic regression models; Journal of Econometrics, Volume 178, Issue 2, 779-793.
M.Kalli, J.E Griffin (2015); Flexible modelling of dependence in volatility processes; Journal of Business and Economic Statistics, Volume 33, Issue 1, 101--113.