Jim O’Shaugnessy on The Great Arbitrage: Human Nature

Is betting on cyclical human nature the smartest way to drive returns? The AI-driven reshuffle will create trillions in alpha— Jim O’Shaughnessy weighs in.

Jim O’Shaugnessy on The Great Arbitrage: Human NatureJim O’Shaugnessy on The Great Arbitrage: Human Nature

How does an “Anti-VC VC” pick his winners?

That’s a question for Jim O’Shaughnessy, Founder and CEO of O'Shaughnessy Ventures, who describes himself as such.

Thinking like a quant is invaluable, Jim insists. Fund managers, or really anyone managing capital needs to rule out emotional highs and lows to rationally dictate how to buy & sell.

Previously, Jim founded and chaired OSAM, a lead quantitative asset management firm with $6.5B in AUM that was acquired by Franklin Templeton in 2022. He served as Director of Systematic Equity at Bear Stearns Asset Management and also happens to be the Father of Patrick O’Shaugnessy from Positive Sum and Invest with the Best.

Insights from our conversation on Change Order have stayed with me even weeks later.

Our deep dive navigated across:

  • why incumbents will struggle against new tech,
  • avoiding biases as an investor,
  • arbitraging cyclical human nature,
  • having no LPs at O'Shaughnessy Ventures, and
  • how generative AI is leading the “great reshuffle”

With generative AI shaking up industries, what opportunities does it create?

It’s interesting to think about the “great reshuffle” happening right now. Traditional playbooks that used to work are collapsing because the rules have changed. People who were successful for decades are now losing their minds trying to adapt to new tech.

It’s a classic reaction: new technology comes in, people panic, and then those who adapt make a big impact. Just like when we had only a few TV networks and major newspapers, those days are long gone.

Back then, everyone had their local newspapers, and they were incredibly partisan. We’re now seeing a similar shift with AI.

The beauty of generative AI is that it lowers the cost of creating and distributing content. We’re talking about setting up a business today with tools that were unheard of before.

For instance, imagine a publishing model where AI helps authors by managing their marketing, tracking sales, and even going on podcasts.

So, while the old ways of media might seem like they’re crumbling, AI is opening up incredible new opportunities. It’s like we’re on the brink of a new era in media — there are so many unexplored use cases.

How did O'Shaughnessy Capital Management come into being?

The idea for O'Shaughnessy Capital Management actually came from a conversation I had with a fellow board member at the St. Paul Chamber Orchestra. This person, who was the general counsel for Control Data, had several money managers but was unsure if they were really doing what they said they’d do or if they were actually adding any value.

It was a classic case of whether you can trust the manager or if you need to verify their claims.

Given my background in crunching numbers in quantitative market research, I saw a perfect opportunity to apply my skills in a new way. I had spent years focusing on metrics like PE ratios, price-to-book ratios, EBITDA.

I knew how to understand what really makes a stock tick, beyond just the CEO or the company’s name.

When faced with the challenge of assessing money managers, I thought, why not use the same rigorous, data-driven approach?

So, I came up with the idea of creating what I called a “normal portfolio.” I took the stocks from each money manager’s portfolio and ran a factor analysis on them.

The goal was to build a digital twin of each manager’s strategy. By isolating the most significant deviations from the average stock—essentially identifying the traits of each manager’s investments—we could create a model that mirrored their decisions.

The real breakthrough was developing a quantitative model to replicate these managers' portfolios. This model was beyond just theoretical; it was designed to check if these managers were truly adding value or if their strategies were just market noise. The results were eye-opening.

Our analysis showed that very few managers actually added value beyond what our models could achieve.

This experience changed my perspective. It became clear that while some talent existed in money management, its true value was better measured through objective methods.

After realizing this, Control Data brought me on board to dig deeper into these insights. I started off providing consultancy services, using my models to analyze and evaluate investment strategies.

This work set the stage for what would become O'Shaughnessy Capital Management.

So, O'Shaughnessy Capital Management was born out of a need to validate and quantify investment strategies in a way traditional methods couldn’t.

The shift from consultancy to a full-fledged investment firm was a natural progression, driven by a more scientific approach to investing.

How do you make your decisions as part of your investment processes?

In venture investing, it's vital to approach it more as a psychologist rather than a physicist.

This means understanding and anticipating human behavior. Emotions like fear, greed, and hope can drive poor decision-making and have historically led to disastrous outcomes.

I like to think of myself as the Anti-VC VC because I have no limited partners (LPs), which gives me a unique freedom in my investment approach.

Traditional VCs, even mega funds, face the agent-principal problem where they must justify their decisions to LPs, potentially leading to more conservative or compromised choices.

My incentive structure is vastly different because it's all in-house capital. This also aligns my interests better. I don't need a perfect elevator pitch or to conform to conventional VC norms. Instead, I want to deep dive into the gap, the go-to market strategy, the founder’s grit, and bet on the bold.

When you think about your time in the business now, how do you try to think like a quant and avoid the biases?

Fear, greed, and hope have driven more bad decisions in investing than almost anything else.

Fear can lead to panic selling during market downturns, causing investors to lock in losses rather than wait for the market to recover.

Greed often results in chasing high returns without fully understanding the risks involved, leading to poor investment choices and substantial losses.

Hope can cause investors to hold onto failing investments, believing they will rebound against all evidence to the contrary.

Ignorance, the only non-emotional horseman, amplifies the effects of fear, greed, and hope.

Without a solid understanding of market dynamics and investment principles, you’re more likely to fall prey to these emotional biases.

Take Isaac Newton, for example.

Despite his brilliance, he succumbed to the South Sea Bubble because he let his emotions override his rational judgment.

Anyone managing money or allocating capital needs to create a master list of qualities for evaluating founders, product categories, industries, and go-to-market strategies.

Don’t fixate on the journey of say, Google; instead, find your own way to the mountaintop.

Ultimately, arbitraging human nature—recognizing that while markets change rapidly, human behavior remains constant—provides a sustainable edge in investing.

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Watch the full conversation featuring Jason Shuman and Jim O’Shaughnessy on YouTube.

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