Episode summary
Where LPs Should Look for Venture Alpha
How I Invest With David Weisburd
· · Hosts: David Weisburd · Guests: Abe Othman
Summary
Abe Othman argues that venture capital cannot be analyzed as one market: seed, Series A, and Series B-plus behave like different asset classes because their return distributions have different power-law shapes. Using AngelList data on tens of thousands of early-stage financings, he says the biggest error in seed analysis is relying on external datasets that miss failed companies and on spreadsheet assumptions about dilution that distort returns.
His core claim is that seed investing is so dominated by extreme outcomes that expected value is the wrong framework. Because many credible seed deals are priced in at roughly 80% to 90%, the advantage from picking the “best” company is often much smaller than it looks. Abe says this makes broad exposure to credible deals more rational than concentrated conviction, while Series A remains harder because investors must both select well and work more actively.
He also argues that adverse selection is central: the fact that a deal is available to you can itself be a negative signal, especially outside your domain. That logic leads him away from startup-picking quant models and toward picking venture funds instead, where pricing is more uniform and data-driven signals can still help identify above-average managers without paying a higher price for the insight.
Key takeaways
- Abe Othman says seed, Series A, and later-stage venture behave like separate asset classes because their power-law return profiles differ.
- He argues that in seed, the correct framework is broad exposure to credible deals, not concentrated bets on a few “best” startups.
- Abe says expected value breaks down in seed because the distribution is so extreme that outcomes can escape far beyond the threshold you observe.
- He finds that small checks outperform big checks, which he attributes largely to adverse selection and crowding into hotter rounds.
- He says fund selection is a better place for data-driven alpha because venture funds generally charge similar fees while startup prices already reflect most visible signals.
Notable quotes
“venture capital is not an asset class. It is actually three different asset classes”
“the optimal strategy if you don't crystal ball about which investment is going to be the next tuber is to invest in everything”
“you can't even refer to the concept of expected value. It literally doesn't exist”
“the cheapest and most effective way to diligence a preede investment is to write a check”
“the individual idiosyncratic signal is worth almost nothing and the common signal is worth everything”
How the episode opens
Abe, before today's podcast, I looked up when our first podcast was. It was actually episode four. It was the fourth episode. Now, this is going to be roughly 250. So, it's it's good to have you back on. — Unbelievable. Congratulations on the success. Like, that's that's absolutely amazing. I think since the last time we talked, I've also had two kids since the last time we chatted. So, it's only been two years. lot of lot of stuff has been uh has been going on since uh since the last time we we spoke. So congratulations I guess to all of us for for yeah accomplishments.
It's amazing seeing the uh the amount of like traction you've gotten like um yeah super cool and it's it's such a privilege to be invited back. Um yeah that's that's really neat. — You've been at Angelist for six and a half years. You started out as head of data science. Today you're a consulting researcher. You've had access to some of the most interesting data in I think in the entire venture capital ecosystem. What's one thing that you've changed your thinking on in the last year?
A big perspective that I had and I think this is pretty common for people who get into the venture capital ecosystem from starting a startup. A sense, you know, you start a company, you go out to raise money, you're introduced to a bunch of VCs, and it kind of hits you. They're like, "What is this?
Like, "Who are these people? What are their jobs? Why do they behave the way that they behave?
Why do they never say no? Why do they constantly talk about circling back? You know, cultural awakening.
And I think one of the reasons that I was so keen to join Angel, why I had the opportunity was, you know, given the size of the data that I'm able to work with was a sense of look, can I try to rationalize the behavior of venture capitalists?
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- venture alpha
- angelist data
- power-law returns
- adverse selection
- seed investing strategy
Companies and tickers mentioned
- AngelList
- Strawberry Tree Management Company
- AngelList Asset Management LLC
Watch the episode
Watch “Where LPs Should Look for Venture Alpha” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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How I Invest With David Weisburd, this episode and its artwork belong to David Weisburd. Octagon is not affiliated with the show; this page is an independent summary.
