Our genesis

Alfred Escher founded one of Switzerland’s largest banks, Credit Suisse...

...and three of its largest insurance companies to finance and insure the Gotthard railway line and tunnel. Since there were not enough engineers available for this massive undertaking, he also co-founded the ETH Zurich (Swiss Federal Institute of Technology). In his spirit and in the best Swiss tradition, we embrace entrepreneurship and long term thinking in our organisation.

ETH Zurich is a leading science, technology, engineering and mathematics university in Zurich, Switzerland...

...It was founded in 1854 with a stated mission to educate engineers and scientists, serve as a national center of excellence in science and technology and provide a hub for interaction between the scientific community and industry. 21 Nobel Prizes have been awarded to students or professors of the Institute in the past, the most famous of whom was Albert Einstein. Today, ETH Zurich is one of the world's top six universities.

Credit Suisse Asset Management is the asset management arm of a truly global financial powerhouse...

...of a truly global financial powerhouse, with a footprint in 50 countries, and 47,000 employees from over 150 different nations. The business offers investment solutions and services globally to various types of clients, including pension funds, governments, foundations and endowments, corporations and individuals, along with its private banking businesses. The asset management capabilities span a diverse range of asset classes, with a focus on traditional and alternative strategies.

Company timeline


Prof. Didier Sornette wins a contract with AEROSPATIALE / EADS  (now Airbus Industries) to develop a prediction system for the rupture of pressure tanks embarked in the European Ariane rocket based on the analysis of acoustic emissions. This “rocket science” is the first step in the invention and development of LPPLS (Log Periodic Power Law Singularity) techniques for the prediction of complex systems.


While working as a professor at UCLA (University of California, Los Angeles), Prof. Didier Sornette introduced LPPLS for earthquake precursory analysis and forecasts.


Prof. Didier Sornette joins ETH Zurich and launches a dynamical group to study the predictability and control of crises and extreme events in complex systems. The study is applied to financial bubbles and crashes, earthquake physics and geophysics, the dynamics of success on social networks and the complex system approach to medicine (immune system, epilepsy, etc.) toward the diagnostic of systemic instabilities.


 In reaction to the financial crisis, Prof. Didier Sornette creates the Financial Crisis Observatory to demonstrate the feasibility of advance warnings on financial instabilities.

Under the supervision of Prof. Didier Sornette, Qunzhi worked on his Master and PhD project using ML/NLP tools to extract sentiment from massive news articles and  predict stock returns with news sentiment.


Prof. Didier Sornette and Qunzhi Zhang, PhD incorporate Sentiment Studies GmbH as an ETH Zurich spinoff to develop and deliver innovative applied science in the new field of behavioral financial indicators.

Qunzhi Zhang and Prof. Didier Sornette apply available ML tools and develop new tools to generate trading rules with behavioural financial indicators.


David Solo joins the ETH Zurich spinoff team to help develop a unique set of LPPLS-based investment portfolio strategies.

In parallel Qunzhi Zhang is developing ML-based investment portfolio strategies, by incorporating both the LPPLS indicators and the more general indicators and automating the trading rules.


Experienced portfolio managers from Credit Suisse join forces with ETH Zurich spinoff team to finalize and operationalize the LPPLS-based investment portfolio strategies.
Sentiment Studies GmbH is transformed into Systematic Investment Management AG (SIMAG), an independent joint venture between Credit Suisse Asset Management and the ETH Zurich spin-off.

The ML-based investment portfolio strategies are getting sophisticated with proprietary ML methods designed specially for the noisy financial data. In parallel Qunzhi Zhang and the SIMAG team is developing deep learning-based methods to extract new indicators from raw data automatically.


Certification as Investment Manager of Collective Investment Schemes; Launch of SIMAG Investment Funds.

Developing new AI tools to automatically collect structured/unstructured data and analyse them to generate more indicators and enhance the SIMAG score.

More about us


Interdisciplinary team of experienced professionals dedicated to your performance

The Board

Strong governance and guidance from industry leaders in finance and academia