People

Professor Spyridon Vrontos

Head of Department - Professor (R)
School of Mathematics, Statistics and Actuarial Science (SMSAS)
Professor Spyridon Vrontos

Profile

Biography

Spyridon is Professor of Actuarial Science and Head of School of Mathematics, Statistics and Actuarial Science, University of Essex. He served for many years as the Lead of the Actuarial Science Research Theme and as Course Director for BSc Actuarial Science and MSc Actuarial Science. Spyridon's expertise is in Actuarial and Financial Data Science. Spyridon was the recipient of the Charles A. Hachemeister Prize of Casualty Actuarial Society. His research portfolio includes projects funded by Casualty Actuarial Society, Society of Actuaries, Academy of Finland, Innovate UK, HEFCE, EIRA Network, University of Essex, Essex Police, Essex County Council, Suffolk County Council, Hellenic Foundation for Research and Innovation, Hellenic Association of Insurance Companies, Hellenic and British insurance companies, pension funds, hospitals, and Lloyd's Brokers and Coverholders. Spyridon's research on Asset Liability Management in a Time Varying Volatility Environment was funded based on the Research Grant Competition from the Society of Actuaries, The Actuarial Foundation and CKER. His principal research is concerned with predictive modelling in actuarial science and finance, actuarial and financial mathematics, design of optimal bonus malus systems, asset - liability management for pension funds, performance measurement for pension funds, hedge funds and mutual funds, predictability of financial time series, risk management and solvency and risk theory. His publications have appeared in internationally recognised and world-leading academic journals such as International Journal of Forecasting, Journal of Banking and Finance, European Journal of Finance, Journal of Financial Data Science, Quantitative Finance, Journal of Empirical Finance, Journal of Forecasting, Journal of Asset Management, Scandinavian Actuarial Journal, ASTIN Bulletin and Applied Stochastic Models in Business and Industry. Spyridon's consulting work include Valuation and Funding of Employee Benefits based on International Accounting Standards, Funds Performance Evaluation and Funds of Funds, Valuation and Funding of Pension Funds, Ratemaking and Bonus Malus Systems, Financial Planning Tools for Pre and Post Retirees, Property Insurance, General Insurance, Actuarial and Financial Data Science. Spyridon received his BSc, MSc and PhD from Athens University of Economics and Business, Greece. He is a member of European Finance Association (EFA) and of Global Association of Risk Professionals (GARP).

Qualifications

  • Ph.D. in Statistics, Athens University of Economics and Business, (2005).

  • M.Sc. in Statistics, Athens University of Economics and Business, (1998).

  • B. Sc. in Statistics, Athens University of Economics and Business, (1996).

Research and professional activities

Research interests

Actuarial Mathematics and Actuarial Modelling

Open to supervise

Design of Optimal Bonus &ndash Malus Systems

Open to supervise

Asset - Liability Management for Pension Funds

Open to supervise

Performance Measurement for Pension Funds, Hedge Funds and Mutual Funds

Open to supervise

Predictability of Financial Time Series

Open to supervise

Risk Management and Solvency

Open to supervise

Risk Theory

Open to supervise

Conferences and presentations

A comprehensive approach to survival analysis of hedge funds

RCEA Conference On Recent Developments In Economics, Econometrics And Finance, Online Conference, 2022

A comprehensive approach to survival analysis of hedge funds

Conference in Macroeconomic Analysis and International Finance, Rethymno, 2022

Forecasting the Equity Premium Using Machine Learning Techniques

18th Conference on Research on Economic Theory and Econometrics, Tinos, 2019

On the Directional Predictability of U.S. Stock Market

17th Conference on Research on Economic Theory and Econometrics, Tinos, 2018

Survival Analysis of Hedge Funds

16th Conference on Research on Economic Theory and Econometrics, Milos, 2017

Out-of-sample equity premium prediction: A complete subset quantile regression approach

15th Conference on Research on Economic Theory and Econometrics, Tinos, 2016

Performance evaluation of funds, 14th Conference on Research on Economic Theory and Econometrics (C.R.E.T.E. 2015), Chania.

Chania, Greece, 2015

Performance evaluation of funds, WBS Pensions Research Network Workshop 2015, London.

London, United Kingdom, 2015

Performance evaluation of funds, Computational and Financial Econometrics Conference 2014, London.

London, United Kingdom, 2014

Out-of-sample equity premium prediction: A complete subset quantile regression approach, 31st French Finance Association Conference, Aix-en-Provence, France, 2014.

Aix-en-Provence, France, 2014

Hedge fund return predictability; To combine forecasts or combine information? 1st Annual Conference of International Association for Applied Econometrics, London, UK, 2014.

London, United Kingdom, 2014

A Quantile Regression Approach to Equity Premium Prediction, 2014 Conference of the Financial Engineering & Banking Society (F.E.B.S), Global Trends in Financial Intermediation, Financial Markets, and Financial Modeling, Surrey, UK, 2014.

Guildford, United Kingdom, 2014

Hedge fund return predictability; To combine forecasts or combine information? 13th Conference on Research on Economic Theory and Econometrics, Milos, Greece, 2014.

Milos, Greece, 2014

Out-of-sample equity premium prediction: A complete subset quantile regression approach, 7th International Conference on Computational and Financial Econometrics. London, UK, 2013.

London, United Kingdom, 2013

Hedge Fund Predictability, 6th CSDA International Conference on Computational and Financial Econometrics. Oviedo, Spain, 2012.

Oviedo, Spain, 2012

On a renewal risk process with dependence under a Farlie - Gumbel Morgenstern copula, 5th International Conference of Mathematical and Statistical Methods for Actuarial Sciences and Finance, Venice, Italy, 2012.

Venice, Italy, 2012

Performance Evaluation of Pension Funds, 5th CSDA International Conference on Computational and Financial Econometrics, London, UK, 2011.

London, United Kingdom, 2011

Asset-Liability Management for Pension Funds in a Time-Varying Volatility Environment, 28th European Meeting of Statisticians, Piraeus, Greece, 2010.

Piraeus, Greece, 2010

Asset Liability Management Using Derivatives, 6th Conference in Actuarial Science & Finance on Samos, Samos, Greece, 2010.

Samos, Greece, 2010

Asset Allocation Using Derivatives, 11th Insurance: Mathematics and Economics, Piraeus, Greece, 2007.

Piraeus, Greece, 2007

Pension Fund Management: Asset Allocation Under Long Range Dependence, 3rd Ιnternational Conference on Applied Financial Economics, Samos, Greece, 2006.

Samos, Greece, 2006

On the Application of Fractional Brownian Motion in Insurance as a Modelling Tool for Long Range Dependence, 10th International Congress on Insurance: Mathematics and Economics, Leuven, Belgium, 2006.

Leuven, Belgium, 2006

Fractional Brownian Motion and Applications in Insurance and Finance, Second Summer School in Actuarial - Financial Mathematics, Samos, Greece, 2005.

Samos, Greece, 2005

Insurance control for a simple model with liabilities of the fractional Brownian motion type, 3rd Conference in Actuarial Science & Finance in Samos, Samos, Greece, 2004.

Samos, Greece, 2004

Testing for Long - Range Dependence: The case of Athens Stock Exchange, HERCMA 2001, Athens, Greece, 2001.

Athens, Greece, 2001

Design of an Optimal Bonus - Malus System in Automobile Insurance, HERCMA 1998, Athens, Greece, 1998.

Athens, Greece, 1998

Teaching and supervision

Previous supervision

Amy Sut Moy Sing Wong
Amy Sut Moy Sing Wong
Thesis title: Temporal Global Trends of Human Population and Dependency on Coral Reefs
Degree subject: Biological Sciences
Degree type: Doctor of Philosophy
Awarded date: 4/7/2023
Nor Syahilla Binti Abdul Aziz
Nor Syahilla Binti Abdul Aziz
Thesis title: On Modelling Volatility and Mortality for Pension Schemes.
Degree subject: Actuarial Science
Degree type: Doctor of Philosophy
Awarded date: 28/1/2021
Najlaa Tarik Jassim Jassim
Najlaa Tarik Jassim Jassim
Thesis title: Asymmetric Loss Functions and Combination of Forecasts with Applications in Equity Premium Prediction
Degree subject: Statistics
Degree type: Doctor of Philosophy
Awarded date: 6/1/2021
Jonathan Iworiso
Jonathan Iworiso
Thesis title: On the Predictability of U.S. Stock Market Using Machine Learning and Deep Learning Techniques
Degree subject: Statistics
Degree type: Doctor of Philosophy
Awarded date: 22/5/2020

Publications

Publications (1)

Noferini, V., Vrontos, S. and Wood, R., (2024). Efficient computation of \lowercase{$f$}-centralities and nonbacktracking centrality for temporal networks

Journal articles (26)

Vrontos, I., Galakis, J., Panopoulou, E. and Vrontos, S., (2024). Forecasting GDP growth: the economic impact of COVID-19 Pandemic. Journal of Forecasting. 43 (4), 1042-1086

Vrontos, ID., Galakis, J., Panopoulou, E. and Vrontos, SD., (2024). Modeling the Economic Impact of the COVID-19 Pandemic Using Dynamic Panel Models and Seemingly Unrelated Regressions. Econometrics. 12 (2), 17-17

Sing Wong, A., Vrontos, S. and Taylor, M., (2022). An assessment of people living by coral reefs over space and time. Global Change Biology. 28 (23), 7139-7153

Meligkotsidou, L., Panopoulou, E., Vrontos, ID. and Vrontos, SD., (2021). Out-of-sample equity premium prediction: a complete subset quantile regression approach. The European Journal of Finance. 27 (1-2), 110-135

Vrontos, S., Galakis, J. and Vrontos, I., (2021). Modeling and predicting U.S. recessions using machine learning techniques. International Journal of Forecasting. 37 (2), 647-671

Iworiso, J. and Vrontos, S., (2021). On the Predictability of the Equity Premium Using Deep Learning Techniques. Journal of Financial Data Science. 3 (Winter, 2021), 74-92

Vrontos, S., Galakis, J. and Vrontos, I., (2021). Implied Volatility Directional Forecasting: A Machine Learning Approach. Quantitative Finance. 2021 (10), 1687-1706

Galakis, J., Vrontos, I. and Vrontos, S., (2021). Style Rotation Revisited. Journal of Financial Data Science. Spring 2021 (2), 110-133

Iworiso, J. and Vrontos, S., (2020). On the Directional Predictability of Equity Premium Using Machine Learning Techniques. Journal of Forecasting. 39 (3), 449-469

Abdul Aziz, NS., Vrontos, S. and Hasim, HM., (2019). Evaluation of Multivariate GARCH Models in an Optimal Asset Allocation Framework. The North American Journal of Economics and Finance. 47, 568-596

Meligkotsidou, L., Panopoulou, E., Vrontos, I. and Vrontos, SD., (2019). Quantile Forecast Combinations in Realised Volatility Prediction. Journal of the Operational Research Society. 70 (10), 1720-1733

Tzougas, G., Vrontos, S. and Frangos, N., (2018). Bonus-Malus Systems with Two Component Mixture Models Arising from Different Parametric Families. North American Actuarial Journal. 22 (1), 55-91

Vrontos, S., (2016). Hedge Funds Managerial Skill Revisited: A Quantile Regression Approach. Bankers, Markets & Investors. 140

Panopoulou, E. and Vrontos, S., (2015). Hedge fund return predictability; To combine forecasts or combine information?. Journal of Banking & Finance. 56, 103-122

Tzougas, G., Vrontos, S. and Frangos, N., (2015). Risk Classification for Claim Counts and Losses Using Regression Models for Location, Scale and Shape. Variance. 9 (1), 140-157

Meligkotsidou, L., Panopoulou, E., Vrontos, ID. and Vrontos, SD., (2014). A Quantile Regression Approach to Equity Premium Prediction. Journal of Forecasting. 33 (7), 558-576

Tzougas, G., Vrontos, S. and Frangos, N., (2014). OPTIMAL BONUS-MALUS SYSTEMS USING FINITE MIXTURE MODELS. ASTIN Bulletin. 44 (2), 417-444

Chadjiconstantinidis, S. and Vrontos, S., (2014). On a renewal risk process with dependence under a Farlie–Gumbel–Morgenstern copula. Scandinavian Actuarial Journal. 2014 (2), 125-158

Tzougas, G., Vrontos, S. and Frangos, N., (2014). Optimal bonus-malus systems using finite mixture models. ASTIN Bulletin. 44 (02), 417-444

Vrontos, SD., Vrontos, ID. and Meligkotsidou, L., (2013). Asset-liability management for pension funds in a time-varying volatility environment. Journal of Asset Management. 14 (5), 306-333

Vrontos, ID., Meligkotsidou, L. and Vrontos, SD., (2011). Performance evaluation of mutual fund investments: The impact of non-normality and time-varying volatility. Journal of Asset Management. 12 (4), 292-307

Meligkotsidou, L., Vrontos, ID. and Vrontos, SD., (2009). Quantile regression analysis of hedge fund strategies. Journal of Empirical Finance. 16 (2), 264-279

Vrontos, SD., Vrontos, ID. and Giamouridis, D., (2008). Hedge fund pricing and model uncertainty. Journal of Banking & Finance. 32 (5), 741-753

Frangos, NE., Vrontos, SD. and Yannacopoulos, AN., (2007). Reinsurance control in a model with liabilities of the fractional Brownian motion type. Applied Stochastic Models in Business and Industry. 23 (5), 403-428

Frangos *, NE., Vrontos, SD. and Yannacopoulos, AN., (2005). Ruin probability at a given time for a model with liabilities of the fractional Brownian motion type: A partial differential equation approach. Scandinavian Actuarial Journal. 2005 (4), 285-308

Frangos, NE. and Vrontos, SD., (2001). Design of Optimal Bonus-Malus Systems With a Frequency and a Severity Component On an Individual Basis in Automobile Insurance. ASTIN Bulletin. 31 (1), 1-22

Conferences (1)

Frangos, N., Vrontos, S. and Yannacopoulos, A., (2006). On the application of fractional Brownian motion in insurance as a modelling tool for long range dependence.

Grants and funding

2024

An exploratory consultancy project with Pacific re Life Ltd

Pacific Life Re Limited

2022

Evaluation of Essex Police's Knife Crime intervention pilot

Essex Police

Analyse tradesman insurance data to determine risk and premium

Polaris

Evaluation of Essex Police's Knife Crime intervention pilot

Essex Police

2021

Analyse question set used by property insurers to determine risk

Polaris

Advent Insurance Management Limited KTP Application

Innovate UK (formerly Technology Strategy Board)

Shepherd Compello KTP

Innovate UK (formerly Technology Strategy Board)

2020

Planning tools for pre and post retirees

Maji Financial Wellbeing Ltd

2017

To develop a predictive, self-learning model for automotive warranty expenditure with reference to a broad range of drivers ranging from product quality to dealer and customer behaviour.

MSX International

Contact

svrontos@essex.ac.uk
+44 (0) 1206 874717

Location:

STEM 5.5, Colchester Campus