Fully data-driven. No human bias. Designed for stability and long-term outperformance.
Traditional research and analysis make it practically impossible to consistently beat the stock market index over time.
A DIFFERENT APPROACH WAS REQUIRED.
AFM is powered by mathematics, not human judgment. By covering the entire S&P 500 - rather than concentrating on just 20-30 popular stocks - it delivers a safer, fully diversified investment approach.
AFM-managed accounts have outperformed the S&P 500 every year since 2019.
| Total Outperformance | |
|---|---|
| 14.7% | |
| Annual Outperformance | |
| 2021 | 0.8% |
| 2022 | 1.8% |
| 2023 | 2.2% |
| 2024 | 2.1% |
| 2025 | 1.2% |
| 2026 | 0.3% |
Note: All AFM-managed accounts have exceeded S&P 500 performance over every one-year period to date.
(Past performance is not indicative of future results.)
(Data updated daily)
AFM replaces fundamental research with a disciplined, fully automated process based on mathematical models.
AFM includes all 500 companies in the S&P 500, providing broad market coverage and reliable long-term growth.
No margin trading, short selling, futures, options, or arbitrage. AFM’s top priority is capital protection.
AFM has outperformed traditional large-cap funds over time by staying systematic and avoiding emotional decision-making.
Unlike traditionally managed funds, AFM spans the entire S&P 500 index and therefore requires sufficient capital to ensure efficient execution and proper diversification.
It is therefore primarily offered to Family Offices and High-Net-Worth Individuals.
AFM is equally well suited to long-term investors seeking to build and preserve wealth across generations — e.g. education funding, property acquisition, and retirement planning — where consistency and capital preservation are paramount.
AFM is a data-driven application that uses mathematics instead of subjective judgment. By removing human bias, it delivers consistent results over time. With a unique service charge and no hidden commissions, it remains a highly cost-effective solution.
LX InfoTech Sàrl acts as your trusted partner, providing personalized account setup and ongoing support. Each portfolio is uniquely tailored to reduce volatility and align perfectly with your specific investment goals.
Contact
If you would like to receive further information or discuss whether this approach is appropriate for you:
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Autonomous Fund Management (AFM) originated from a concept conceived by Peter Seilern, who sought a fundamentally different approach to investing in equity markets.
Early work, including Computer-Assisted Trading (CAT), demonstrated that investment decisions could be improved through data-driven, mathematical processes rather than human judgment.
Practical implementation, however, was not feasible at the time. Critical elements, such as reliable internet connectivity, cloud computing, real-time market data, instant trade execution, and sufficiently low transaction costs, were not yet available.
It was not until the early 2000s that these technological conditions began to emerge and thanks to further development, the concept evolved into a workable framework.
Ten years ago, in collaboration with HES-SO Valais (University of Applied Sciences of Western Switzerland), the system was further refined and adapted for practical application.
This process culminated in the launch of AFM in its current form—a self-sustaining, data-driven investment procedure operating entirely without human intervention.
LX InfoTech Sàrl was subsequently established to support the deployment of AFM, providing dedicated services to investors while ensuring the system’s ongoing advancement.
Today, AFM is further enhanced through the integration of artificial intelligence while remaining firmly anchored to its founding principle: the complete absence of human judgment in investment decisions.
Peter Seilern, now inactive, earned his Master's degree in Physics at the EPUL, the Federal Polytechnic School of Lausanne (EPFL). He gained experience as a research engineer at Litton Industries' Guidance and Control Systems Division in California before spending three years in New York as an associate at Dillon, Read & Co. Inc.
Upon his return to Switzerland, he pioneered the development of Computer-Assisted Trading (CAT), a system that enables investors to trade securities depending on performance metrics and other criteria.
Autonomous Fund Management (AFM), an extension of CAT, was first introduced in 2007 and provides investors with a data-driven approach to managing their assets. In early 2019, he collaborated with HES-SO Valais to launch the current version of AFM.
Leyun Xia was born in Shanghai, where he studied French at university. At the age of 21 he moved to Switzerland to continue his studies and after a language stay allowing him to perfect his French, he joined the HES-SO Valais where he obtained a Bachelor’s Degree in computer science and a Master's in Business Administration.
He then worked for 10 years as a research scientist at the same university participating in projects devoted to the fields of data mining and machine learning.
In 2017 he paired with Peter Seilern as part of a research project at HES, playing a key role in the development and testing of AFM, before successfully deploying the system into a live environment in mid-2019.
Leyun founded LX InfoTech Sàrl to continue developing AFM’s program in a fast-changing financial market. The company also provides exclusive service for AFM account holders, taking responsibility for setting up accounts and their ongoing maintenance.