Jonathan Lellouche
About Jonathan Lellouche
Jonathan Lellouche serves as a Senior Quant at Murex Analytics Team (MACS) in Paris, France, where he has worked since 2005. He specializes in high-performance computing applications, Monte-Carlo simulations, and financial modeling.
Work at Murex
Jonathan Lellouche has been a Senior Quant at Murex Analytics Team (MACS) since 2005, contributing to the company for 19 years. He operates from the Paris Area, France, where he applies his expertise in quantitative analysis and financial modeling. His role involves leveraging advanced programming languages and technologies to enhance the performance of financial applications.
Education and Expertise
Jonathan studied at Lycée Louis-le-Grand and later attended Grenoble INP - Ensimag from 2002 to 2005, where he earned a degree in Computer Science, Mathematics, and Finance. His educational background provides a strong foundation for his work in quantitative finance. He is proficient in programming languages such as C/C++, Python, OpenCL, and CUDA, which he uses for high-performance computing applications.
Technical Skills and Specializations
Jonathan specializes in implementing Monte-Carlo simulations on both CPU and GPU architectures, achieving significant performance improvements. He utilizes a BGM cross currency multifactor model with quadratic local volatility to effectively capture the smile of swaptions. Additionally, he has expertise in developing analytical proxies for PFE/CVA Monte-Carlo simulations across various financial instruments, including commodities, FX, and rates.
Methodologies and Practices
In his work, Jonathan applies Agile and SAFE methodologies in software development processes. He is experienced in calibrating rate models on several tenor swaptions and CMS spread options, which enhances the accuracy and reliability of financial models.
Cloud Computing Knowledge
Jonathan possesses a deep understanding of AWS architecture for cloud-based solutions. This knowledge allows him to effectively integrate cloud technologies into quantitative finance applications, improving scalability and performance.