The Compound and Friends:

  • Hosted by Downtown Josh Brown and Michael Batnick
  • Rotating guests every Friday for expert insight on business and investing

Episode 109 with Rob Arnott at Future Proof:

  • Live audience present during the episode
  • Guest: Rob Arnott, founder and chairman of Research Affiliates
  • Discussion topics: lessons from the tech bubble, smart beta, big tech valuations, Tesla and Nvidia, impact of AI on markets and economy

Rob Arnott Introduction:

  • Native to Orange County
  • Founder and chairman of Research Affiliates
  • Core portfolio manager of PIMCO All Asset, All Authority, and PIMCO RAE funds

Smart Beta Strategies in Tech Bubble:

  • Smart beta strategies attracted significant inflows due to investors' appetite for higher returns
  • Performance chasing led to money pouring into multi-factor strategies without considering valuation
  • Factors trading rich relative to historical norms were warned against in 2016 paper by Rob Arnott
  • By 2020, most factors were extremely cheap relative to history

Cheap Factors vs. Rich Factors:

  • Graph shows majority of factors trading cheap relative to history (80%)
  • Quality factor always trades at a premium but can be small or large depending on valuation
  • Value factor was off the charts cheap during this time period

Catalysts for Value Investing:

  • Higher interest rates could diminish growth advantage of high-priced growth companies
  • Inflation may break current return of growth bubble and favor value stocks

NVIDIA as an Example of Big Market Delusion:

  • NVIDIA is a great company with visionary products but priced beyond perfection (42 times sales)
  • Definition of bubble: implausible growth assumptions needed to justify current price; marginal buyer doesn't care about valuation models
  • Other AI companies also have high multiples but not as extreme as NVIDIA's

Lessons from Past Tech Bubbles:

  • Comparison between top 10 tech names of 1999 and their performance since then
  • Not all companies at the forefront of breakthroughs perform well in the long run

AI's Impact on Markets:

  • AI has potential to revolutionize various industries, including investing
  • Neural networks and algorithms based on AI already used by quant funds and super jumbo hedge funds
  • AI can create market-beating returns if it discovers new forms of fundamental investing

Potential Risks with Tech Stocks:

  • Market cap-weighted indexes have become heavily concentrated in a few big tech stocks
  • Biggest stocks getting bigger as a percentage of overall index weight
  • Hubris is dangerous; enthusiasm, optimism, and lack of fear suggest a good time to rebalance into segments with fear

Role of AI in Investing:

  • AI has the potential to outperform average financial advisors in managing money
  • However, human element and client relationship are crucial aspects that AI may struggle to replicate

Meta (formerly Facebook) and Llama Release:

  • Meta's release of Llama and widespread use of sophisticated AI raises questions about stock performance
  • Companies like Meta could continue to thrive due to their ability to find new opportunities and leverage advanced technology