Experience

 
 
 
 
 
January 2020 – June 2021
Ghent, Belgium

Post-Doctoral Researcher

Ghent University & HEC Montreal

SNSF PostDoctoral Researcher
 
 
 
 
 
January 2016 – December 2019
Neuchâtel, Switzerland

Teaching Assistant

University of Neuchâtel

Support students and professor for the Fixed Income, Derivatives, and Portoflio Management Course. Assist in supervising master student level thesis.
 
 
 
 
 
August 2015 – December 2015
Québec, Canada

Quantitative Analyst

Lakeroad asset management

Developed and maintained quantitative financial models using Excel, VBA, R, and Matlab. Analyzed and developed various portfolio strategies.

Selected Publications

The advent of massive amounts of textual, audio, and visual data has spurred the development of econometric methodology to transform qualitative sentiment data into quantitative sentiment variables, and to use those variables in an econometric analysis of the relationships between sentiment and other variables. We survey this emerging research field and refer to it as sentometrics , which is a portmanteau of sentiment and econometrics. We provide a synthesis of the relevant methodological approaches, illustrate with empirical results, and discuss useful software.
Forthcoming in Journal of Economic Surveys, 2020

The modern calculation of textual sentiment involves a myriad of choices as to the actual calibration. We introduce a general sentiment engineering framework that optimizes the design for forecasting purposes. It includes the use of the elastic net for sparse data-driven selection and the weighting of thousands of sentiment values. These values are obtained by pooling the textual sentiment values across publication venues, article topics, sentiment construction methods, and time. We apply the framework to the investigation of the value added by textual analysis-based sentiment indices for forecasting economic growth in the US. We find that the additional use of optimized news-based sentiment values yields significant accuracy gains for forecasting the nine-month and annual growth rates of the US industrial production, compared to the use of high-dimensional forecasting techniques based on only economic and financial indicators.
International Journal of Forecasting 35 (4), 1370-1386, 2019

Recent Publications

The advent of massive amounts of textual, audio, and visual data has spurred the development of econometric methodology to transform …

The modern calculation of textual sentiment involves a myriad of choices as to the actual calibration. We introduce a general sentiment …

We test the presence of regime changes in the GARCH volatility dynamics of Bitcoin log-returns using Markov-switching GARCH (MSGARCH) …

We perform a large-scale empirical study to compare the forecasting performance of single-regime and Markov-switching GARCH (MSGARCH) …

Numerical standard error (NSE) is an estimate of the standard deviation of a simulation result if the simulation experiment were to be …

We propose a tone-based event study to reveal the aggregate abnormal tone dynamics in media articles around earnings announcements. We …

We describe the package MSGARCH, which implements Markov-switching GARCH models in R with efficient C object-oriented programming. …

We provide a hands-on introduction to optimized textual sentiment indexation using the R package sentometrics. Textual sentiment …

NSE is an R package for computing the numerical standard error (NSE), an estimate of the standard deviation of a simulation result if …

We propose a simple methodology to simulate scenarios from a parametric risk model while accounting for stress-test views via fully …

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