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Associate Professor in the Department of Statistics of Athens University of Economics and Business |
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Published Papers 1.
Galakis, J., Vrontos, I.D. and Xidonas, P. (2022). On tree-structured
linear and quantile regression based asset pricing, Review of Accounting and
Finance, 21 (3), 204-245. 2.
Galakis, J., Vrontos, I.D., and Vrontos, S.D. (2021). Style Rotation
Revisited, The Journal of Financial Data Science, 3 (2), 110-133. 3.
Vrontos, S.D., Galakis, J. and Vrontos I.D. (2021). Implied
Volatility Directional Forecasting: A Machine Learning Approach, Quantitative
Finance, 21 (10), 1687-1706. 4.
Vrontos, S.D., Galakis, J. and Vrontos I.D. (2021). Modeling and
Predicting U.S. Recessions using Machine Learning Techniques, International
Journal of Forecasting, 37, 647-671. 5.
Meligkotsidou L., Panopoulou, E., Vrontos I.D. and Vrontos S.D. (2021).
Out-of-sample equity premium prediction: a complete subset quantile
regression approach, European Journal of Finance, 27, 110-135. 6.
Koki, C., Meligkotsidou, L. and Vrontos, I.D. (2020). Forecasting under
model uncertainty:Non-homogeneous hidden Markov models with Polya-Gamma data
augmentation, Journal of Forecasting, 39, 580-598. 7.
Meligkotsidou L., Panopoulou, E., Vrontos I.D. and Vrontos S.D. (2019). Quantile forecast combinations in realised volatility
prediction, Journal of the Operational Research Society, 70, 10, 1720-1733. 8.
Meligkotsidou, L., Tzavalis E. and Vrontos I.D. (2017). On Bayesian
Analysis and Unit Root Testing for Autoregressive Models in the Presence of
Multiple Structural Breaks, Econometrics and Statistics, 4, 70-90. 9.
Andersen, J.V., Vrontos, I.D., Dellaportas, P. and Galam, S. (2014).
Communication impacting financial markets,
Europhysics Letters, 108, 2,
28007-p1-p6. 10. Meligkotsidou L., Panopoulou, E.,
Vrontos I.D. and Vrontos S.D. (2014). A
Quantile Regression Approach to Equity Premium Prediction, Journal of Forecasting, 33, 558-576. 11. Meligkotsidou L. and Vrontos I.D.
(2014). Detecting
Structural Breaks in Multivariate Financial Time Series: Evidence from Hedge
Fund Investments, Journal of Statistical Computation and Simulation, 84, 5, 1115-1135. 12. Meligkotsidou L., Tzavalis E. and
Vrontos I.D. (2014). A Bayesian method of distinguishing unit
root from stationary processes based on panel data models with
cross-sectional dependence, Statistics and Computing, 24, 297-315. 13. Vrontos S.D., Vrontos I.D. and
Meligkotsidou L. (2013). Asset-Liability Management for Pension Funds in a
Time-Varying Volatility Environment, Journal of Asset Management, 14,
306-333. 14. Meligkotsidou L., Tzavalis E. and
Vrontos I.D. (2012). A
Bayesian panel data framework for examining the economic growth convergence
hypothesis: do the G7 countries converge?, Journal of Applied Statistics, 39, 9, 1975-1990. 15. Vrontos I.D. (2012). Evidence for Hedge Fund Predictability from a
Multivariate Student’s t Full Factor GARCH model, Journal of Applied Statistics, 39, 1295-1321. 16. Vrontos I.D., Meligkotsidou L. and
Vrontos S.D. (2011).
Performance Evaluation of Mutual Fund Investments: The impact of
Non-Normality and Time-Varying Volatility, Journal of Asset Management, 12, 292-307. 17. Giannikis, D., and Vrontos I.D. (2011). A Bayesian approach to detecting nonlinear
risk exposures in hedge fund strategies. Journal of Banking and Finance, 35,
1399-1414. 18. Meligkotsidou L., Tzavalis E. and
Vrontos I.D. (2011). A
Bayesian Analysis of Unit Roots and Structural Breaks in the Level, the Trend
and the Error Variance of Autoregressive Models of Economic Series, Econometric Reviews, 30, 2,
208-249. 19. Diamantopoulos K. and Vrontos I.D.
(2010). A
Student-t Full Factor Multivariate GARCH model. Computational Economics, 35, 63-83. 20. Meligkotsidou L., Vrontos I.D. and
Vrontos S.D. (2009). Quantile
Regression Analysis of Hedge Fund Strategies. Journal of Empirical Finance, 16, 264-279. 21. Meligkotsidou L. and Vrontos I.D.
(2008). Detecting
Structural Breaks and Identifying Risk factors in Hedge Fund returns: A
Bayesian approach. Journal of
Banking and Finance, 32, 2471-2481. 22. Giannikis D., Vrontos I.D. and
Dellaportas P. (2008). Modelling
nonlinearities and heavy tails via threshold Normal mixture GARCH models, Computational Statistics and Data Analysis,
52, 1549-1571. 23. Vrontos S.D., Vrontos I.D. and
Giamouridis D. (2008). Hedge
fund pricing and model uncertainty, Journal
of Banking and Finance, 32, 741-753. 24. Dellaportas P. and Vrontos I.D. (2007). Modelling Volatility Asymmetries: A Bayesian analysis of a
class of tree structured multivariate GARCH models, Econometrics Journal, 10, 503-520. 25. Giamouridis D., and Vrontos I.D.
(2007). Hedge
fund portfolio construction: A comparison of static and dynamic approaches, Journal of Banking and Finance, 31,
199-217. 26. Vrontos I.D, Dellaportas P. and
Politis D.N. (2003). A
full-factor multivariate GARCH model. Econometrics
Journal, 6, 312-334. 27. Vrontos I.D, Dellaportas P. and
Politis D.N. (2003). Inference
for some multivariate ARCH and GARCH models. Journal of Forecasting, 22, 427-446. 28. Vrontos I.D., Giakoumatos S.G.,
Dellaportas P. and Politis D.N. (2001).
An application of three bivariate time-varying volatility models. Applied Stochastic Models in Business and
Industry, 17, 121-133. 29. Vrontos I.D., Dellaportas P. and
Politis D.N. (2000). Full
Bayesian inference for GARCH and EGARCH models. Journal of Business and Economics Statistics, 18,
187-198. 30. Giakoumatos S.G., Vrontos I.D.,
Dellaportas P. and Politis D.N. (1999).
An MCMC Convergence Diagnostic using Subsampling. Journal of Computational and Graphical Statistics, 8,
431-451. Conference Proceedings 1.
Vrontos I.D., Dellaportas P. and Politis D.N. (1999). Bayesian analysis of bivariate ARCH and GARCH models. Hercma '98: 4th Hellenic European
Conference on Computer Mathematics and its applications, E.A.
Lipitakis (Ed), pp. 459-466. Fellowships and
Awards ·
1993-1994 ·
1997-2001 ·
2017-2018 ·
2018-2019 ·
2020-2021 Funded Research Projects 1.
Modelling the Economic and Financial Impact of COVID-19 (Hellenic
Foundation for Research and Innovation, ELIDEK, 2022-2023). 2.
A Bayesian Tree structured quantile regression approach to financial
series predictability (ELKE OPA-funded research project, 2018-2019). 3.
Bayesian Threshold Regression Models with Application to Economic and
Financial Data (ELKE OPA-funded research project, 2017-2018). 4.
Quantile Autoregressions in Realised Volatility Prediction (ELKE
OPA-funded research project, 2015-2017). 5.
Large Shocks, Structural Breaks and Macroeconomic Relationships
(ARISTEIA II), Supported by the General Secretariat for Research and
Technology (Primary and Scientific Coordinator: Elias Tzavalis, Athens
University of Economics and Business), Member of the Research Group,
2014-2016. 6.
Systemic Risk Tomography (SYRTO) Project, Funded by the European Union
under the 7th framework programme (FP7-SSH/2007-2013) Grant Agreement no
320270 (Primary and Scientific Coordinator: Roberto Savona, University of
Brescia, Leader of the AUEB research group: Petros Dellaportas), Member of
the AUEB Research Group, 2013-2016. 7.
The Dark Side of The Accretion History of the Universe, Thales Program,
Supported by the European Commission and Greek National Resources (Project
Coordinator: Antonios Georgakakis, National Observatory of Athens, Leader of
the Statistics Research Group: Loukia Meligkotsidou), Member of the
Statistics Research Group, 2012-2015. 8.
Analysis of Financial time series using Bayesian non-parametric methods
(ELKE OPA-funded research project, 2009-2010). 9.
Asset-Liability Management for Pension Funds in a Time-Varying
Volatility Environment (CKER SOA US - funded research project, joint with S.
Vrontos and L. Meligkotsidou, 2008-2009) 10.
Hedge funds return predictability in the presence of model uncertainty
and implications for wealth allocation (INQUIRE UK - funded research project,
joint with D. Giamouridis, 2006) Unpublished Papers 1.
Vrontos I.D. and Giamouridis D. (2008).
Hedge fund return predictability in the presence of model uncertainty and
implications for wealth allocation.
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