Smart Money, Crowd Intelligence, and AI

Using human and artificial intelligence to beat the S&P 500

February 2022. Reading Time: 10 Minutes. Author: Nicolas Rabener.

SUMMARY

  • Smart money, crowd intelligence, and AI ETFs have underperformed the S&P 500 since their inception
  • Somewhat surprisingly, all three have almost the same factor exposures
  • Negative exposure to value, and positive exposure to size and momentum factors

INTRODUCTION

Welcome to the qualifying round of the 2022 US Investment Olympics.

The goal of the games is simple: beat the S&P 500, either by generating higher returns or playing dirty and going for higher risk-adjusted returns.

Let the games begin!

QUALIFICATION

Like the 2022 Winter Olympics in Beijing, the US Investment Olympics are not easy to qualify for. Mutual funds are automatically barred from participation: Their fees are just too high for them to have a realistic shot against the S&P 500. Hedge funds have even higher fees and theoretically should be hedged, so they can’t compete with the stock market either. In fact, the only securities capable of matching the index are exchange-traded funds (ETFs).

So far, there are eight ETF contestants representing three themes:

  • Smart money (GVIP, GURU, GFGF, and ALFA): These ETFs mimic the trades of famous investors and mutual and hedge fund managers. Their pitch is high alpha at low fees.
  • Crowd intelligence (BUZZ & SFYF): Stocks are selected based on the wisdom and sentiment of the crowd.
  • Artificial Intelligence (AIEQ & QFRT): The equities in these ETFs are chosen by AI programs. In the case of AIEQ, IBM’s famous Big Watson makes the picks.

Although less expensive than the average mutual or hedge fund, the ETFs have fees of 64 basis points (bps) and are not cheap compared to low-cost index trackers. But then again, top-notch performance isn’t free (read Replicating Famous Hedge Funds).

Despite their contemporary themes, our ETFs have yet to resonate much with the investment community. Their cumulative assets under management (AUM) are only $700 million, even though some have track records going back to 2012. But then a