Bulle ou rotation ? Ce que les marchés nous préparent vraiment - Anne-Laure Frischlander-Jacobson

The discussion revolves around the current state of the financial markets, particularly the perceived bubble in Artificial Intelligence (AI) and its broader implications for investment strategies. Anlor Frischlander Jacobson, a financial advisor and founder of Evvest, shares her insights. She notes that while markets are at all-time highs, they are also highly concentrated, with a few large tech companies driving much of the growth. She expresses concern about the current valuation levels, drawing parallels to the dot-com bubble of 2000. She highlights the cyclically adjusted price-to-earnings ratio (CAPE or Shiller P/E), which stands at around 44 for the US market, a level not seen since the peak before the 2000 crash. This indicates that it would take 44 years for a company to earn back its investment based on its current earnings. Frischlander emphasizes that the market's rise is largely attributed to the AI revolution, but she questions who is truly benefiting and who might be caught in a speculative bubble. She believes that while AI as a technology will persist, there's a risk of a bubble forming around companies that are artificially inflating their valuations by associating themselves with AI, even if their underlying technologies might become obsolete. She recalls the dot-com era where the justification for high valuations was often a vague notion of a "revolution" and a "new model," a sentiment she now hears regarding AI. She draws an analogy to the California Gold Rush, where the miners (the direct participants in the gold rush) didn't all get rich. Instead, companies that supplied the miners, like Levi's (selling jeans) and Huntington (building railroads to transport them), thrived by providing essential services around the revolution. This suggests that in the current AI revolution, the true winners might be those who provide infrastructure and essential services rather than those directly developing the core AI technology, especially if their business models are not fundamentally sound. Frischlander points out that unlike in 2000, many of the current high-flying tech companies are profitable. However, she cautions that the concentration in a few "magnificent seven" tech stocks (like Nvidia, Amazon, Tesla) makes the S&P 500 vulnerable. If these few stocks falter, the entire index could be significantly impacted. She also notes that the European market, for instance, is not as overvalued as the US market. A significant concern raised is the "SaaS Apocalypse," referring to the potential disruption of Software as a Service (SaaS) companies by AI. Many SaaS companies have built their valuations on subscription models for services that could be replicated or offered for free by major AI providers like OpenAI or cloud platforms. For example, a company offering legal document generation services might be disrupted if OpenAI integrates a similar, free service. Similarly, AI could generate personalized training programs, impacting existing coaching platforms. The discussion also touches upon private debt and private equity. Frischlander observes a significant increase in default rates in private debt, rising from 5% to 15% in two years. This suggests that the high yields offered by private debt (8-12%) reflected underlying risks that are now materializing. She likens the current situation to the 2007 subprime crisis, where complex financial products and perceived low volatility masked significant underlying risks. In private equity, she notes that some funds might hold onto underperforming assets ("zombie companies") to avoid marking down valuations, potentially creating a false sense of stability. The conversation shifts to identifying resilient sectors and investment strategies. Frischlander favors companies that are indispensable and have strong pricing power, those that will not be replaced by AI and will enable its functioning. Examples include luxury goods (like Hermès's Kelly bag, which AI cannot replicate) and established brands like McDonald's. She also highlights sectors that will benefit from AI infrastructure and development, such as pharmaceuticals (where AI can accelerate drug discovery), renewable energy (due to AI's high energy consumption), and heavy industries and infrastructure providers. She expresses a preference for established, "sleepy" companies with solid fundamentals and dividend-paying stocks. However, she cautions against chasing excessively high dividend yields, as this can sometimes signal underlying business issues. She recommends investing in diversified funds and ETFs rather than concentrating on individual stocks, especially for those who are not professional stock pickers. She mentions specific fund managers and ETFs that focus on quality growth, defensive strategies, and value investing. The conversation also touches on the role of central banks and the potential for a shift back to fundamentals. With central banks having reached the end of their interest rate-cutting cycles, markets may need to rely more on intrinsic value. She also discusses the potential for a return of small-cap stocks, which are currently undervalued due to their exclusion from major ETFs, but warns of their sensitivity to economic downturns. Emerging markets are presented as an interesting investment area, particularly those that benefit from a weaker dollar and are exporters of commodities like oil, such as Latin America. The role of bonds is also discussed, with a warning that they are not risk-free and can be volatile when interest rates rise. Finally, Frischlander advises investors to remain diversified, maintain a long-term perspective, and have some cash on hand to capitalize on opportunities that arise during market downturns. She emphasizes the importance of diligence, especially in understanding what one is investing in, and avoiding overly complex financial instruments. She offers 20 minutes of free investment advice to listeners who mention "La Martingale."