معرفی
Alexis Marchal is an Assistant Professor in the Department of Finance at the École Polytechnique Fédérale de Lausanne (EPFL), specifically affiliated with the School of Management (HEC Lausanne). Based at Odyssea 1.04, Station 5 in Lausanne, Switzerland, Marchal maintains an active research profile in quantitative finance and machine learning applications to financial markets.
Marchal's research interests focus on the intersection of finance and artificial intelligence, with particular emphasis on deep learning applications for financial modeling. Their work spans volatility modeling, asset bubble detection, and innovative applications of computer vision to financial data analysis. The research demonstrates a strong methodological approach combining traditional financial economics with cutting-edge machine learning techniques.
Analysis of Marchal's publications reveals a consistent focus on applying advanced computational methods to solve complex problems in asset pricing and financial market analysis. The research outputs show increasing sophistication in methodology, moving from traditional statistical approaches to more complex deep learning architectures, particularly Long Short-Term Memory (LSTM) networks. This trajectory indicates a researcher at the forefront of computational finance.
- Nonstandard Errors (2024) - Published in the Journal of Finance
- Deep Learning, Jumps, and Volatility Bursts (2020)
- Deep Learning for Asset Bubbles Detection (2020)
- Risk & Returns around Fomc Press Conferences (2021)
While specific grant information isn't detailed in the available materials, Marchal's affiliation with the Swiss Finance Institute suggests participation in collaborative research initiatives. The work on the multi-author 'Nonstandard Errors' paper indicates engagement with broad research communities in finance methodology. Marchal's research has gained significant attention, with the 'Nonstandard Errors' paper accumulating over 17,000 downloads.
