Swissquote’s Quantitative Asset Management department (QAM) was created in 2008 to explore quantitative research in finance. One of the team’s landmark achievements is the launch of the Robo-Advisor, a sophisticated automated asset manager that uses powerful and fully in-house developed algorithms.
The team
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Bringing together an alchemy of skills, the QAM department is made up of seven physicists and mathematicians. These talented professionals boast a wide range of expertise and experience, and a passion for research and analysis.
Purpose
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QAM’s goal is to provide clients with the latest science in finance, all in a simple and intuitive format, while developing new ideas and opportunities.
Dr SERGE KASSIBRAKIS
Head of Quantitative Asset
Management
FLORENT GALLIEN
Head of Research
TEODOR GODINA
Quantitative Researcher
Dr NATALIYA CAPON
Data Scientist Researcher
BENOÎT PERNOLLET
Researcher Engineer
JESSE IDEMUDIA
Quantitative Researcher
GUILLAUME DARMAN
Quantitative Researcher
QAM has three main activities
Quantitative
finance
This field seeks to optimise investment portfolios, order execution, dynamic management of portfolio limits, and quant strategies. Our Robo-Advisor provides quantitative finance services.
Artificial intelligence
and big data
QAM leverages data and artificial intelligence to serve several Swissquote departments. For example, it helps the Legal department detect insider trading and the Marketing department with the creation of personas.
Quantitative risk
analysis
Quantitative risk analysis is derived from quantitative finance and is particularly important for the Controlling department. Its purpose is to anticipate market risk, especially for options and futures.
Timeline and key achievements
2008
Creation of the QAM department.
2009
Creation of Quant Funds, Long Only Equity Swiss Regulated Funds, in CHF and EUR. 2016 Lipper Fund award winner.
2010
Launch of the first customisable automated asset manager in Europe – ePrivate Banking – now known as the Robo-Advisor.
2017
AI Volatility Surface: first use of artificial intelligence to calculate volatility surface and optimise internal processes (client segmentation and detection of insider trading).
2021
Launch of a new widget – Investment Inspiration – which makes daily equity investment recommendations based on trading activity.
The Swissquote EPFL chair
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The Swissquote Chair in Quantitative Finance promotes research, teaching and the sharing of knowledge in order to improve expertise and understanding of financial engineering among the academic community, the financial industry and policy makers.
Housed at the Swiss Finance Institute @ EPFL, the Swissquote Chair plays an important role in leading research and teaching initiatives in financial engineering at EPFL.
