A novel method to probe sparsely sampled random surfaces. Application to implied volatility modelling and prediction.
I held the ceremonial public defence of my thesis on March 5th, 2021, and officially received the title Docteur ès Sciences (PhD).
I gave an invited talk at the Computational and Methodological Statistics conference (CMStatistics 2020) that took place in December 2020. In my talk entitled I spoke primarily about my second paper as well as my case study of US Treasury yield curve and its interaction with the US macroeconomy indicators.
I defended my PhD thesis on September 17, 2020, at Swiss Federal Institute of Technology in Lausanne (EPFL). The president of my jury, Sofia Olhede, and the examiners Łukasz Kidziński, Shahin Tavakoli, and Stephan Morgenthaler as well as my thesis advisor, Victor Panaretos, gave me constructive feedback and I thank them for the overall pleasant experience.
A semester project I supervised at EPFL comparing various econometric forecasting methods for yield curves in MINT (Mexico, Indonesia, Nigeria, Turkey) economies.
A novel simulation method allowing for generating a wide range of simulated data, accompanied by an R package ‘specsimfts’.
Yield curve and macroeconomy interaction: evidence from the non-parametric functional lagged regression approach
In my first single-author publication I applied the tools I developed in my core PhD research to yield curve modelling.
The core paper of my PhD research. Published in Electronic Journal of Statistics (2020)
The paper extending results from my core paper on sparsely observed functional time series. To appear in Journal of Time Series Analysis
In July 2019 I had the opportunity to travel to Palermo, Italy, to give a talk at the European Meeting of Statisticians, the largest statistics conference in Europe. In my talk entitled “Sparsely observed functional time series: estimation and prediction” I spoke about my first paper carrying the same name.