Research

Journal Articles:

1. Forecasting Value-at-Risk using deep neural network quantile regression, with with A. Raftapostolos and G. Kapetanios (Accepted, Journal of Financial Econometrics) Formely circulated as Deep Quantile Regression.

2. Choosing between persistent and stationary volatility, with L. Giraitis and G. Kapetanios, Annals of Statistics, 2022, Vol. 50, pp. 3466-3483

3. Kernel-Based Volatility Generalised Least Squares, with G. Kapetanios and K. Petrova, Econometrics and Statistics, 2021, Vol. 20, pp. 2-11

Working Papers:

1. High-dimensional generalised penalised least squares, with K. Chrysikou and G. Kapetanios (submitted)

2. Deep Neural Network Estimation in Panel Data Models, with K. Chrysikou, G. Kapetanios, J. Mitchell and A. Raftapostolos (submitted)

3. Sieve-type GLS inference for panel data models, with G. Kapetanios 

4. A generalised Lp-norm filter for time-varying coefficient models, with G. Kapetanios and K. Petrova 

5. Non-linear nuclear norm penalised inference, with G. Kapetanios and A. Raftapostolos

Work in Progress:

1. Time-varying estimation in panel data models

2. Choosing between persistent and stationary large dimensional volatility, with Y. Dendramis and G. Kapetanios

3. A two-step semi-parametric volatility estimator for conditional volatility of asset returns, with L. Giraitis and G. Kapetanios

4. Regularisation of large covariances by nearest-neighbour thresholding, with D. Georgiadis and G. Kapetanios

Other:

1. On statistical time series methods for forecasting the 2020 CoViD pandemic, with K. Chrysikou, G. Kapetanios, A. Raftapostolos and M. Weale