Senior Lecturer in Statistics and Financial Econometrics.
For the academic terms 2012/13, 2013/2014, and 2014/15 I was the module leader of Applied Statisrics for Business and Management (core level 4). I am the module leader of Research Methods (level 5, since 2013/14) which focuses on applications of the Linear Model using R. I am aslo the module leader of Econometrics (level 5, since 2014/2015) which focuses on the analysis of finaicial time series using R. I am also the supervisor of level 6 statistics and econometrics dissertations.
My research interests are:
Bayesian non-parametric methods and related Markov chain Monte Carlo computation, Time Series modelling, Bayesian Regression methods and Bayesian variable selection.
The application areas I am interested in are:
Financial Econometrics, Quantitative Finance, Market Micro Structure and Portfolio Management.
- Institute of Mathematics and Statistics, University of Kent PhD. Statistics Thesis: Bayesian nonparametrics & applications in financial econometrics
- Department of Statistics, University of Michigan M.A. Mathematical Statistics, Magna Cum Laude (GPA 3.95 out of 4)
- Leonard Stern School of Business, New York University M.B.A. Financial Engineering, Summa Cum Laude (GPA 4 out of 4)
- London School of Economics & Political Science BSc (Econ.) Econometrics and Mathematical Economics
- Fulbright Foreign Student Program Fulbright scholarship in pursuit of a master’s degree in the US
- Graduate Research Fellowship, National Science Foundation Scholarship in pursuit of a master’s by research degree in Statistics in the US.
- Engineering and Physical Sciences Research Council Doctoral Student Award
- Higher Education Academy (HEA) Senior Fellow of HEA
- Leadership Foundation Aurora Alumni
- UELT, University of Kent Postgraduate Certificate in Higher Education (PGCHE)
- ICAEW: Institute of Chartered Accountants in England and Wales UK ACA, Chartered Accountant
Research and knowledge exchange
- M. Bedford, S. Coulton, J. Billings, M. Kalli, C. Farmer (2016); Development of risk models for the prediction of new or worsening acute kidney injury on or during hospital admission: a cohort study; Health Services and Delivery Research, Volume 4, Issue 6, ISSN 2050-4349.
- 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.
- M. Kalli, S.G. Walker, P. 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, S.G. Walker (2011); Slice Sampling Mixture Models; Statistics and Computing, Volume 21, Issue 1, 93-105.
National Institute of Health Research (NIHR) Reports
- M.Kalli, M.Bedford, C. Farmer, and S. Coulton (2015), Development of risk models for prediction of worsening acute kidney injury, (2015)
- M.Kalli, Bayesian logistic regression models with variable selection for assessing risk of newborn deaths in East Kent, (2010)
- Bayesian nonparametric vector autoregressive models (with J. Griffin), Journal of Econometrics. (November 2016)
• Principal Investigator - 0.5FTE
- NIHR (grant: 11/2004/28) Development of a risk model for the prediction of new or worsening Acute Kidney Injury (AKI). £240,000 of which £80,000 attributed to CCCU. (20 months, awarded Dec 2012)
- NIHR (grant: 11/2004/33) Bayesian hierarchical models for evaluating the effect of predictive risk models on clinical decision support system. £225,000 of which £75,000 attributed to CCCU. (20 months, awarded November 2015)
- Carl Gower; 01/2017 (Business School, Canterbury Christ Church University).
- Rachel Taylor; Started 01/2017 (COaST centre, Canterbury Christ Church University).
- Michael Bedford; Completed 05/2015 (Canterbury Christ Church University and University of Kent).
Teaching and subject expertise
• University of Kent
– Introduction to Statistics (level 3)
– Introduction to Linear Algebra (level 3)
Medway School of Pharmacy
– Research Methods - Biostatistics (level 6)
– Multivariate Analysis (level 7)
– Advanced Statistics (level 7)
• University of Michigan
Department of Statistics
– Applied Statistics (level 5)
– Introduction to Time Series Analysis (level 5)
Ross School of Business
– Corporate Finance (level 7)
• Stern School of Business, New York University
– Forecasting and Time Series Analysis (level 7)
– Theory of Interest (level 7)
Conferences and Workshops -Invited Speaker
Bayesian nonparametric time varying vector autoregressive models.
• 11th Annual RCEA Bayesian Econometric Workshop Melbourne, July 2017
• 11th Bayesian Nonparametrics Conference Paris, June 2017
• 10th Conference in Computational & Financial Econometrics, Seville, Dec 2016
Bayesian time varying model selection: An application to inflation modelling.
• 9th Conference in Computational & Financial Econometrics, London, Dec 2015
Bayesian nonparametric Vector Autoregressive models.
• Seminar, European Central Bank Frankfurt, November 2015
• NBP Workshop on Forecasting, Narodowy Bank Polski Warsaw, September 2015
• Centre of Operational Research and Econometrics (CORE), Louvain Le Neuve, June 2015
• European Seminar on Bayesian Econometrics, Paris, November 2014
•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, Dec 2013
• Seminar, Vienna University of Economics & Business, Vienna, Dec 2013
Time varying sparsity in dynamic regression models.
•6th Conference in Computational & Financial Econometrics, Oviedo, Dec 2012
Slice Sampling algorithms in Bayesian nonparametrics: theory and properties.
•ISBA World Meeting, Special Topics: Beyond MCMC methods in Bayesian Inference, Kyoto, June 2012
Flexible modelling of dependence in volatility processes.
•4th ERCIM Conference in Computing & Statistics, London, Dec 2011
Stick Breaking Processes and the Slice Sampler
•Functional Simulation Workshop, University of Warwick, June 2008
Modelling the conditional distribution of daily stock returns: an alternative Bayesian semi-parametric model.
•8th Bayesian Non-parametrics Conference, University of Cambridge, Aug 2007
- Associate Member of Peer Review College - EPSRC (02/ 2017 --)
- Statistics Outreach Ambassador - RSS (06/2016 --)
Funding Committee Member:
- NIHR-Research for Patient Benefit-South East Coast. (01/2008-06/2015)
- NIHR-Health Technology Assessment. (06/2012- 06/2016)
- Engineering and Physical Sciences Research Council. (01/2013 --)
- Economics and Social Research Council. (02/ 2012 --)
- Medical Research Council. (02/2014 --)
Journal of Econometrics, Journal of the American Statistical Association, Journal of Business and Economic Statistics, Bayesian Analysis, Statistics and Computing, Journal of Applied Econometrics, Econometric Theory, Journal of the Royal Statistical Society-C, Journal of Financial Econometrics, Quantitative Finance, Review of Financial Studies, Computational Statistics and Data Analysis, Journal of Computational and Graphical Statistics, and Journal of Time Series Analysis.
- International Bayesian Society (ISBA). (01/2008--)
- Royal Statistical Society (RSS). (01/2009 --) ∗ Committee Member of East Kent RSS section. (12/ 2016 --)
Publications and research outputs
Please see the research and knowledge exchange section