This is a story you might not know. It offers a view into why we believe what we believe at BIP Ventures and how we build extraordinary "right tail" outcomes.
When I came out of grad school, I went to work as an options trader at a hedge fund on the West Coast. After a few years of learning (on somebody else's dime), I launched my own market-making firm. Although I had studied financial science and economic theory in depth in grad school, my real education in risk management and investing started when I launched my fund.
Nothing teaches a person how to manage risk like floor trading, market making, and the drive to create an investing edge. Imagine split-second decisions where millions of dollars are on the line. And the only way to win that game was better theory, trading models, and technology.
Our strategy was mathematically sophisticated but practically simple: we focused on buying options – especially out-of-the-money options (mostly puts but some calls) – that we believed were mispriced, thereby offering the opportunity for massive profits.
When we were right, the payoff was exponential. When we were wrong, the losses amounted to "death by a thousand cuts." We essentially watched for months on end as the value of our accounts slowly declined. This is what options traders call "decay." And it felt like a slow, excruciating demise when we experienced long periods of low volatility. The 'trick' with this strategy was patience.
Our patience was rooted in a reliance on statistical observations. In the late 1990s and early part of the millennium, only a handful of people were talking about "fat tails" – a distribution of stock prices with a higher-than-normal probability of extreme events.
Most modern financial science was and is based on an elegant premise – that securities prices fit neatly into normal distributions. Nobel Prizes for Economics and massive pillars of Economics and Finance rely on normally distributed securities prices as their underpinnings. If stock prices were normally distributed, it meant that extreme movements (more than three standard deviations) would only happen every 70-80 years or so. But actual observations of stock price movements revealed something far different – that extreme stock movements occur far more often than they should (like once every seven years) if stock price movements were normally distributed.
So, our fund bet on the promise of extreme events, usually negative ones.
I spent my days buying options that appeared to be undervalued. We paid a small price (usually for a 'put option') that gave us the right to sell the assets at a certain strike price by a certain expiration date. For example, if we paid $.15 to buy a put option that gave us the right to sell a given stock at $100 with an expiration date six months from that time, and the underlying stock price dropped from $130 per share to $10, then we could turn that $0.15 investment into a profit of $89.85 ($100 - $10 - $.15).
Think about it like this. If I was trading when automobiles (powered by combustion engines) were just coming to market, I might have logically concluded that the advent of the automobile would drive down the value of horses and buggies. If I could buy a 'put' on the price of horses and buggies, I would stand to make a fortune when people rapidly converted from riding in horse-drawn carriages to automobiles. In short, there would be less demand for horses and buggies.
I learned that if investors are patient and thoughtful about buying misplaced tail risk, they could make a fortune. I usually did that by betting on the things that could go wrong. After all, the world is a messy place. Business models fail, competition erodes business advantages, pricing power and accounting scandals happen, and corporations make fraudulent claims about the efficacy of their products. And more recently, cancel culture proved that it is possible to erode revenue and brand equity rapidly (just ask Bud Light).
Here was the problem. I was putting all my effort into identifying scenarios that were likely to go wrong. I was focused on "left side" tails.
At some point, I noticed all the incredible innovation building up around me. I was lucky to be in San Francisco during the rise of the Technological Revolution. I saw Google and thousands of other startups creating entirely new markets. I saw people innovating and solving problems at levels I had never imagined. I saw great strategy and the potential for nearly unlimited equity value creation. I saw outsized positive investment returns.
Not because of failures. Because of startups that were solving problems at speed in a dynamic economy.
It was then that I shifted my focus and tried to identify "right side" fat tails – extreme positive events. I believed, and have come to know, that things go right far more often than they go wrong (despite what the news media tells us), especially in the Innovation Economy. Over the past two decades, that theory has proven itself time and again. The tail is fatter on the right side. The probability of great, outsized returns is bigger, and the upside is not capped. BIP Ventures is an almost two-decade testament to that theory.
By focusing on a fat right tail, we buy into great opportunities with massive upside potential. Focusing on the right fat tail (vs. the left fat tail) has another advantage…we can actually influence and increase the likelihood of extreme positive events. At BIP Ventures, we do that with robust post-capital investment and hands-on efforts like Performance Engineering. In other words, I reversed Nasim Talib's theory and added additional advantages to tilt the odds of fat right tails even further in our favor.
It's why I went into this career. It's why I'm here. It's what has driven our track record since 2007. And it's why our track record has consistently produced at such a high level. Pursuing the fat right tail (the positive side of human endeavor) is why we're here. It's what drives our belief in the possibilities of Venture Capital and the enduring creativity of innovators. And it's how we deliver on our mission to serve everyone in the Innovation Economy.
For those of you who are more statistically inclined, I am happy to share more data and charts on this subject. Here are some related materials to provide a foundational perspective:
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