Quantitative Asset Management
Meet the team
Innovation at all levels
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.
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.
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.
QAM has three main activities
This field seeks to optimise investment portfolios, order execution, dynamic management of portfolio limits, and quant strategies. Our Robo-Advisor provides quantitative finance services.
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 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
Creation of the QAM department.
Creation of Quant Funds, Long Only Equity Swiss Regulated Funds, in CHF and EUR. 2016 Lipper Fund award winner.
Launch of the first customisable automated asset manager in Europe – ePrivate Banking – now known as the Robo-Advisor.
AI Volatility Surface: first use of artificial intelligence to calculate volatility surface and optimise internal processes (client segmentation and detection of insider trading).
Launch of a new widget – Investment Inspiration – which makes daily equity investment recommendations based on trading activity.
The Swissquote EPFL chair
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.
Statistically validated leadlag networks and inventory prediction in the foreign exchange market
Efficient Reduction of the Sample Covariance Matrix of Returns with Application to Portfolio Allocation
Traders’ collective portfolio optimization with transaction costs : towards microscopic validation of agent-based models
In the press
High-quality and visionary work never goes unnoticed. Our Robo-Advisor has received significant press coverage.
L’irrésitible essor des robo-advisors
Swissquote: Robo-Advisor s’étend aux cryptodevises
Les robo-advisors ont le blues
Avec le robo-advisor, le client y gagne plus que la banque
Quand les robo-advisors seront nos amis financiers?
Les Robots conseillers qui se disputent le marché suisse
Les robo-advisors s’étendent à l’assurance et à l’achat de voitures
A Genève, quand la gestion de fortune taille dans ses frais
Interviews and videos
Robots-conseillers: l’âge de raison
L’alliance entre la gestion de fortune traditionnelle et le trading direct
Robo-Advisor, le sur-mesure de l’investissement
En Suisse, l'intelligence artificielle est devenue omniprésente
Robo-Berater: das Zeitalter der Vernunft
Swissquote Trading Day Genève – Robo-Advisor et marches des devises
Robo-Advisor : Le juge final reste le client
Interview Robo-Advisory: Currency Hedging I Swissquote
Interview Robo-Advisory: Granular Universe I Swissquote
Interview Robo-Advisory: Multi-asset class I Swissquote
Contact the QAM
Need information or clarifications?
Feel free to write to the QAM team at email@example.com