Raymond Micaletti

Raymond Micaletti studied engineering at Notre Dame and Princeton, where his focus on probabilistic engineering mechanics turned out to be a straight line into finance. The math used to analyze buildings in earthquakes and airplanes in turbulence is the same math used to price options. He spent the early part of his career in systematic long-short equity and global macro before pivoting to tactical asset allocation around 2014. That pivot led him to develop the relative sentiment indicator that powers MOOD, his ETF built on how institutions position themselves relative to retail traders.

On this episode of Behind the Ticker, Ray sits down with Brad to walk through the origin story of relative sentiment, how the MOOD ETF actually makes allocation decisions week to week, and why a former engineer from Princeton ended up breeding longhorns in Puerto Rico while running a one-of-a-kind tactical fund.

Discovering Relative Sentiment

The core idea behind MOOD came from a Lehman Brothers quant equity pamphlet that had been sitting on Micaletti's desk for a decade. The pamphlet contained an indicator tracking how institutions were positioned relative to retail traders. He implemented it, tested it, and found it was okay but not great. He didn't let it go. He added new information, smoothed out the signal, and something clicked.

The real proof came in two market selloffs. In August 2015, the market dropped and every indicator in Micaletti's suite went bearish except relative sentiment. The market then rallied 10% in a straight line. Six months later, same pattern: 10% selloff, everything bearish except relative sentiment, and the market took off and didn't look back. He discovered that whenever momentum was negative but institutions were buying the dip, the market tended to produce its best annual returns.

He wrote a paper on the findings and sent it to Wes Gray at Alpha Architect, a PhD from Chicago who studied under a Nobel Prize winner. Gray challenged him to control for additional variables. The results held up. Gray's assessment: "This is interesting. It's not momentum, it's not trend, it's not value. It's its own thing. You should launch it as an ETF."

How MOOD Actually Works

MOOD runs five distinct models, each capturing a different dimension of relative sentiment across different asset classes. Micaletti runs these models once a week on Wednesdays. Three models use weekly data, one uses monthly data, and the fifth uses daily data that he smooths by taking a multi-day average.

The models produce a target equity allocation. If that target is within 10 percentage points of the current allocation, he doesn't trade. So if the fund is 50% equities and the target comes in at 56%, it stays at 50%. If it moves to 65%, outside the band, the portfolio adjusts. This keeps turnover in check and avoids trading on noise that won't meaningfully move the needle over short time horizons.

The equity side of the portfolio is purely rules-based. The non-equity side involves some art alongside the science. For non-equity positions, Micaletti looks at three things: whether the signal is bullish (rules-based gate), the expected duration of the signal, and the historical performance metrics like Sharpe ratio and max drawdown. He's working on formalizing this into a full optimization, but for now there's a qualitative overlay on the non-equity sleeve.

Building the Business Without Being a Salesman

Micaletti is refreshingly honest about his temperament. "My hobby is to decipher the market," he told Brad. "I'm one of those plant guys that just wants to be kind of left alone. I'm not a sales guy." When he asked Wes Gray how to pitch the fund, Gray told him he wouldn't be able to sell it for the first three years. Micaletti's response: "That's fine by me."

The fund's performance did the talking. People found MOOD on their own and reached out. He now works with a media company that has a network of tactically-oriented RIAs and gets warm introductions. His comfort zone is one-on-one conversations, not pitching to large groups. And he's deliberately not looking for a step function in AUM. "If you go through a period of mediocre performance and you have all these disappointed people," he said, the steady, organic growth he's seeing is ideal.

Key Takeaways

• MOOD is built on a relative sentiment indicator that tracks institutional positioning versus retail traders. When institutions buy the dip while momentum is negative, markets have historically produced their best forward returns.
• The fund runs five models weekly, with a 10-percentage-point dead band around the target equity allocation to control turnover.
• Wes Gray at Alpha Architect vetted the research, challenged the controls, and ultimately said the signal was distinct from known factors like momentum, trend, and value.
• The equity sleeve is fully rules-based; the non-equity sleeve incorporates signal strength, duration, and historical performance with a qualitative overlay.
• Micaletti moved to Puerto Rico, breeds longhorns, and freely admits he's not a natural salesman. The fund grew organically through performance and word of mouth for its first three years.

Listen to the full conversation on Spotify, Apple Podcasts, or YouTube.