Outperformance and cost efficiency with AI

| News

Payoff online information platform on SIMAGs active management approach as alternative to passive ETF investments at comparable costs


Many investors value ETFs because of their lower costs compared to actively managed funds. In exchange, they are prepared to forego additional performance potential (Alpha). Using artificial intelligence in the investment process allows investors to take advantage of both approaches.

The scientific developments of recent years in the field of artificial intelligence bring considerable advantages for the investment industry: together with the enormously increased performance of modern computers and the volume of financial data available for evaluation (‘big data’), it has become ever more possible to investigate and optimise the robustness of investment strategies under various market conditions. Artificial intelligence will help to construct winning portfolios, which promise the greatest chance of success in various market conditions. And this all happens without human intervention, using objective - ie data-based rules - in much the same way as a passive ETF is constructed.

Added value with customisation

To generate Alpha, the artificial intelligence follows similar logical if-then decision rules to those used by successful active portfolio managers to derive decision rules. Artificial intelligence is, however, much faster in the evaluation and interpretation of successful rules. What a successful active manager has learned over the course of his or her career, artificial intelligence can achieve in a fraction of the time.

However, artificial intelligence does also have its limits: predicting the future remains an impossible task despite supercomputers and big data. But that should not be the aim. Even though we cannot know what the future will look like, we can still estimate quite well today which stock combinations promise the greatest success in which market environment. At Simag, we have both the necessary know-how in the field of artificial intelligence and the computer technology to examine thousands of equities worldwide every day for their attractiveness potential in different stock market regimes. Using a continuously customised selection of the most promising stocks, a broadly diversified portfolio is constructed. If market conditions change, the portfolio is adjusted to the new market conditions on the basis of the successful rules acquired.

We believe that this type of portfolio offers an optimal combination of the advantages of passive investment cost-effectiveness with the outperformance potential of active approaches. The outperformance target of Simag funds is around 2% compared to the benchmark, with a moderate tracking error. Simag currently offers two regulated funds: a United States fund using the MSCI USA ESG Leaders Index as a benchmark, and a global fund with the MSCI World ESG Leaders as benchmark. The launch of an emerging market fund with MSCI Emerging Markets ESG Leaders as benchmark is planned for the second half of the year. The funds are suitable both for professional private investors and for institutional investors who expect added value for their core equity investments as part of their strategic asset allocation.


Article on payoff information platform