Modern calculation of textual sentiment involves a myriad of choices for 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 weighting of...

We provide a hands-on introduction to optimized textual sentiment indexation using the R package sentometrics. Textual sentiment analysis is increasingly used to unlock the potential information value of textual data. The sentometrics package implements an intuitive framework to efficiently...

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...

The subject of unobservable variables encompasses this thesis. These latent (i.e., unobservable) variables must be inferred using statistical models or observable proxies. The objectives of my doctoral thesis are to develop and test new statistical models to infer these variables and link them...

Heuristic optimization methods and their application to finance are discussed. Two illustrations of these methods are presented: the selection of assets in a portfolio and the estimation of a complicated econometric model