A systematic approach to investing in the US market.

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.

Autonomous Fund Management (AFM) is driven by mathematics, not human judgment. 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
17.5%
Annual Outperformance
2021	0.8%
2022	1.8%
2023	2.2%
2024	2.1%
2025	1.2%
2026	1.1%

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)

View Live Intraday (during market hours)

Historical Performance (across multiple timeframes)

Why Choose AFM?

Data-Driven

A procedure, not a portfolio manager.

AFM replaces forecasting, opinions and discretionary reactions with a disciplined autonomous process based on data, mathematics and systematic execution.

Broader Diversification

AFM includes all 500 companies in the S&P 500, providing broad market coverage and reliable long-term growth.

Safety First

What AFM deliberately avoids:

No human intervention in investment decisions
No market timing based on news or sentiment
No margin trading
No short selling
No derivatives, futures or options

Consistent Growth

AFM has outperformed traditional large-cap funds over time by staying systematic and avoiding emotional decision-making.

Who is it for? AFM spans the entire index. It is primarily intended for High-Net-Worth Individuals and Family Offices, where sufficient capital allows broad S&P 500 coverage and efficient execution.

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.

Why?

How It Works

Concept

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.

Setup & Configuration

LX InfoTech Sàrl acts as your partner, providing personalized account setup and ongoing support. Each portfolio is uniquely tailored to reduce volatility and align perfectly with your specific investment goals.

Get Started

Full ownership: Assets stay safely in your own account.
Trading access: LX InfoTech receives trading rights only.
Automated: The system operates directly in your account.
Flexible: Complete freedom to pause or exit at any time.

If you would like to receive further information or discuss whether this approach is appropriate for you:

Arrange a Consultation

All enquiries are treated with strict confidentiality.

Your assets remain in your brokerage account, in your name. AFM has trading authority only and cannot withdraw cash, transfer securities or access your master account. A master/sub-account structure is recommended for additional protection.

AFM connects to your existing brokerage account and applies a systematic investment process. Investment decisions are generated by the AFM procedure without discretionary intervention by a human portfolio manager.

Yes. Since your assets remain in your own account, AFM can be discontinued at any time with a single click through the AFM Client Portal or by contacting the service provider.

AFM charges an annual service fee of 0.75% of assets under management. There are no performance fees or additional commissions charged by AFM. Larger portfolios may qualify for institutional pricing.

No. AFM follows a long-only investment strategy.

AFM originated as a scientific research project supervised by the University of Applied Sciences of Western Switzerland (HES-SO). It was conceived by Peter Seilern and developed with Leyun Xia. LX InfoTech Sàrl provides portfolio configuration and technical support.

Over the period analysed, AFM generated an average daily outperformance of 0.01%, with a standard deviation of 0.07%, indicating low variability in its daily excess returns.

A minimum investment of US$1 million is required to implement the strategy efficiently across the S&P 500 universe. Below this amount, transaction costs may have a disproportionate impact on performance.

AFM is a combination of curiosity and common sense. There is no catch.

Origins of AFM

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

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

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 an exclusive service for AFM account holders, taking responsibility for setting up accounts and their ongoing maintenance.

Most investment managers use research and personal judgment to guide their decisions. AFM replaces this with a disciplined, fully automated process based on mathematical models.

That means no bias, no guesswork, and no panic-driven reactions — just an approach designed for steady long-term growth.

Fund managers tend to concentrate their research on the largest companies in the S&P 500.
But here’s the catch:

The top 15 companies account for only 41% of total S&P500 market capitalisation.
The remaining 485 companies represent 59%, yet receive practically no analytical attention.

AFM takes a different approach:
Rather than focusing on a narrow group of dominant companies, AFM systematically analyses and captures opportunities across the entire index - resulting in greater stability and lower volatility.

Interesting sideline: The largest company in the S&P 500 is roughly 1,000 times the size of the smallest!


Traditional management tends to focus on large cap stocks (ex. largest 15).	AFM covers the entire S&P range.

AFM’s first priority is the safety and preservation of investor capital. Outperformance is a natural result of its disciplined, data-driven process — not the product of speculation or concentration risk.

AFM represents a new generation of investment management: transparent, mathematical, and inherently safer than the traditional human-driven approach.

AFM is designed to deliver performance that is more consistent and stable over time, in contrast to the greater concentration risk often associated with traditional large-cap strategies.

Relative performance of similar funds and AFM to the S&P 500

J	F	M	A	M	J	J	A	S	O	N	D
2021
	-0.1%	0.4%	0.2%	0.2%	0.1%	-0.2%	0%	0.2%	-0.4%	0%	0.2%
2022
0%	0.2%	0.1%	0.1%	0.3%	0.2%	0.2%	0.2%	0.2%	0.3%	0.5%	0.2%
2023
-0.1%	0.3%	0%	0.2%	0.2%	0.3%	0.2%	0.1%	0.1%	0.2%	0.1%	0.1%
2024
0.2%	0.1%	0%	-0.1%	0%	0.2%	0.2%	0.2%	0.5%	0.1%	0%	0.4%
2025
0.3%	-0.2%	0.4%	0%	-0.1%	0.1%	-0.2%	0.3%	-0.2%	0.2%	0.1%	0.3%
2026
0.1%	0.2%	0.2%	-0.3%	-0.1%	0%	0.9%	0%

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A systematic approach to investing in the US market.

Investment management without human emotion.