23 citations · 24 across the 7 of their papers we have counts for
7 papers
Clustering doc2vec output for topic-dimensionality reduction: A MITRE ATT&CK calibration
Nathan Monnet, Loïc Maréchal, Julian Jang-Jaccard +1
We introduce a novel approach to text classification by combining doc2vec embeddings with advanced clustering techniques to improve the analysis of specialized, high-dimensional te…
Disentangling the sources of cyber risk premia
Loïc Maréchal, Nathan Monnet
We use a methodology based on a machine learning algorithm to quantify firms' cyber risks based on their disclosures and a dedicated cyber corpus. The model can identify paragraphs…
Cyber risk and the cross-section of stock returns
Daniel Celeny, Loïc Maréchal
We extract firms' cyber risk with a machine learning algorithm measuring the proximity between their disclosures and a dedicated cyber corpus. Our approach outperforms dictionary m…
Measuring the performance of investments in information security startups: An empirical analysis by cybersecurity sectors using Crunchbase data
Loïc Maréchal, Alain Mermoud, Dimitri Percia David +1
Early-stage firms play a significant role in driving innovation and creating new products and services, especially for cybersecurity. Therefore, evaluating their performance is cru…
Prioritizing Investments in Cybersecurity: Empirical Evidence from an Event Study on the Determinants of Cyberattack Costs
Daniel Celeny, Loïc Maréchal, Evgueni Rousselot +2
Along with the increasing frequency and severity of cyber incidents, understanding their economic implications is paramount. In this context, listed firms' reactions to cyber incid…
Fundamentals of Generative Large Language Models and Perspectives in Cyber-Defense
Andrei Kucharavy, Zachary Schillaci, Loïc Maréchal +6
Generative Language Models gained significant attention in late 2022 / early 2023, notably with the introduction of models refined to act consistently with users' expectations of i…
TechRank
Anita Mezzetti, Loïc Maréchal, Dimitri Percia David +5
We introduce TechRank, a recursive algorithm based on a bi-partite graph with weighted nodes. We develop TechRank to link companies and technologies based on the method of reflecti…