🎙️ Hindsight Bias

Wall Street's bears have been eating dust as the S&P 500 has charged ahead. Since this bull market kicked off in October 2022, the benchmark has surged 48% in 19 months.

🐂 This ‘raging bull’ isn't an anomaly. Per Truist's Keith Lerner, nine of the last 10 bull markets have outpaced the current one, with an average run lasting five years.

That’s one reason many Wall Street strategists are revising their S&P targets, calling for more gains ahead.

— Matthew & Shawn

Here’s today’s rundown:

Today, we'll discuss the biggest stories in markets:

• When past performance doesn’t even predict past performance

• Is the AI revolution already losing steam?

This, and more, in just 5 minutes to read.

Chart(s) of the Day

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In The News

🤔 When Past Performance Doesn’t Even Predict Past Performance

Happy Birthday, Dow Jones. This week marked the 128th anniversary of the Dow Jones Industrial Average. 

But it’s not all fun and games. The Wall Street Journal recently used the milestone to expose Wall Street's deceptive marketing practice of "backtesting" to make investment strategies appear more successful than they are.

• As WSJ explains, backtesting is applying hindsight to past data and pretending that a hypothetical portfolio had been run that way all along.
  

• The crux of the issue lies in how the Dow is constructed versus the S&P 500. As previously highlighted, the Dow is price-weighted, meaning higher-priced stocks like Boeing carry more influence despite having a smaller market cap than tech giants like Apple.
  

• The S&P 500 is weighted by market cap, giving appropriate emphasis to the true market leaders.

Supersize me: To illustrate backtesting, WSJ created a hypothetical "Supersized Dow" consisting of the 30 highest-priced stocks over the last decade. The fantasy portfolio would have crushed the real Dow and S&P 500, averaging 30.2% annual returns and turning $10,000 into nearly $140,000.

Hindsight is 20/20: This outperformance relies entirely on hindsight bias. The Supersized Dow bought the highest-priced stocks at the end of the period, not the beginning, when no one could predict which stocks those would be. In reality, buying the highest-priced stocks 10 years ago and rebalancing annually would have underperformed the S&P 500.

• This highlights how backtesting uses past data, pretending a hypothetical strategy was implemented all along, making outperformance look easy. WSJ cites other examples like target-date funds advertising returns based partly on simulated or non-existent historical data. 

Why it matters:

Protecting yourself: To avoid being misled, it’s important to ask tough questions like why the managers weren't using this "great" strategy from the start, how long it was implemented, whether trading costs are included, and what other backtest strategies were abandoned. If the answers don't make sense, it’s generally wise to steer clear.

• As Warren Buffett and Charlie Munger have long warned, investors must be careful about the dangers of Wall Street — where professional salespeople are “like a denizen of thieves, and they'll sell you what they can sell you.”

Bottom line: Backtesting is a statistical trick that allows Wall Street to market hypothetical past performance that can’t be realistically replicated. It’s another reminder that investors must look beyond alluring backtest numbers and demand transparency into a strategy's real-world implementation.

Read more

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📉 Is the AI Revolution Already Losing Steam?

AI this, AI that. Nvidia is crushing it, Elon Musk says human-level AI is coming fast, and virtually every executive is dropping “AI” on their earnings calls. Hey, even the visual above is made by AI itself. 

But is the whole deal a bit too over-hyped right now? It’s possible.

The AI industry is enjoying enormous investment and hype. But there are growing signs that the AI boom may be outpacing reality and could turn into an unsustainable bubble, at least in the near term. 

Consider:

• The rate of improvement in AI capabilities is slowing down as models have already ingested most of the available data on the internet. Synthetic data generated by AIs has not proven effective for further training. The performance gaps between top AI models are narrowing as they converge.
  

• AI, once a promising frontier, could become a commodity technology where no single company has a clear performance edge. The commoditization, combined with the lack of major breakthroughs, makes the long-term viability of AI startups questionable as big tech's resources may outmatch them. Some AI startups are already facing turmoil and out of cash.

Running large AI models is extremely expensive. In 2023, the industry spent about $50 billion on training but only generated $3 billion in revenue. The ongoing costs of operating AI services could eat into profit margins for companies like Google that rely on ad revenue.

Why it matters:

Notably, the adoption of AI for actual productive business use remains limited. 

There’s a big gap between workers experimenting with AI and companies actually investing in and relying on the technology, a disparity suggesting that AI has not yet proven to be the massive productivity booster some had hoped.

• The hype and investment in AI are based on assumptions that the technology will rapidly transform everything. But evidence suggests a slower, more gradual adoption curve as AI runs into cost, performance plateau, and human behavior change barriers. 

Zoom out: That would mirror past technology bubbles like the dot-com era, where inflated expectations led to a crash after reality set in. While AI will likely have a major long-term impact, the current hype and investment frenzy may only be sustainable if AI's development and adoption meet lofty projections. 

Maybe it’s wise to stay optimistic about AI’s potential but temper expectations.

Read more

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Quick Poll

On Friday, we asked: How do you feel about the current financial system in the United States?

— Answers were split. One reader said, “I beleive in capitalism, but it seems greed often takes over and unfettered capitalism can run amuck hurting people down the line more than the greedy people with access realize.” Another said our financial system “permits great wealth appreciation but has scary fault lines like questionable regulation of opaque derivatives, sketchy companies, laughably-terrible auditing of financial firms, etc.”

— Some readers addressed how a few entities and individuals hold more and more power. Others pointed to the government, writing: “The growing national debt ($35+T), combined with the interest on the debt is not sustainable. Either we address this ASAP or we will face drastic times ahead!!!!”

See you next time!

That's it for today on We Study Markets!

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