Stefan Klauser from Aisot Technologies reveals that AI-optimized portfolios can surpass their indexes by 3-4% annually.
Source: Interview Salima Barragan, allnews, published January 30, 2024 - translated from French
Will we see performance gaps between AI adopters and AI skeptics? This is the view of Aisot Technologies (aisot), an ETH Zurich spin-off, which has developed an AI platform capable of detecting market trends based on a massive amount of data. Its system enables the creation of equity or cryptocurrency strategies that outperform their benchmark index. This year, the fintech company plans to extend its platform to multi-asset portfolios. CEO Stefan Klauser answers questions from Allnews.
Salima Barragan, allnews: How does your artificial intelligence-based platform work?
Developed over the past three years, our AI Insights platform offers asset managers and financial advisors the ability to create customized portfolios at scale.
It integrates next-generation machine learning, quantitative finance, and NLP (natural language processing), making the creation and customization of investment strategies highly efficient. Users can simulate multiple scenarios and optimize portfolios according to their preferences and market conditions.
Salima Barragan, allnews: Does AI add extra alpha?
Our AI-optimized portfolios have recorded significant outperformance. In the equity market, our portfolio, which has been selecting and re-weighting a subset of 10 S&P 500 stocks each week since early 2022, regularly outperforms the index by an annual margin of 3 to 4%. In the cryptocurrency market, our strategies not only outperform benchmark indices such as Bitcoin or Ether, but they also offer better risk management and lower volatility.
In addition to outperforming indices, the use of AI also allows for market-like performance under restrictive conditions, for example in portfolios focused on sustainable investment. The extent of outperformance and risk control depends on the design of the AI model, the quality of the data, and market conditions. Our approach integrates AI with conventional investment strategies to optimize performance and manage risks.
Salima Barragan, allnews: What data does the machine use to predict market trends?
Our system conducts an in-depth study of the market by incorporating various sources of alternative, macroeconomic, and market data. By cross-referencing them, our analyses become more accurate and efficient. Market data provides real-time information on price movements and trading activity. Alternative data, such as news, offers unique qualitative insights. Finally, macroeconomic data contributes to a broader understanding of the interconnections and trends in the economic landscape.
Salima Barragan, allnews: Can parameters be filtered for individual securities?
Portfolios can account for elements such as volatility targets, asset weighting, turnover ratios, and environmental, social, and governance (ESG) factors for each security.
Salima Barragan, allnews: Can you also create AI-based products?
A feature called "Product Launch Pad" allows AI-optimized portfolios to be transformed into tradable products. From strategic development to product creation, the user enjoys a seamless experience.
Salima Barragan, allnews: How will AI transform the asset management industry?
Thanks to rapid data analysis, AI is set to revolutionize the asset management industry and is becoming essential to generate performance. With its potential to increase efficiency, reduce costs, improve customer engagement, and develop sophisticated financial instruments, AI is initiating a paradigm shift towards a more dynamic, personalized, and data-driven approach to asset management.
Salima Barragan, allnews: What are your current projects?
A few weeks ago, we launched the latest 'equities' section of the AI Insights platform. Our ambition this year is to extend it to bonds, investment funds, and other asset classes. This approach will give users the tools they need to establish multi-asset strategies.
