Optimizing Returns for Venture Investors

On the heels of the most recent posts from John Sharp, one of my partners at Hatcher, I got to thinking it is high time I wrote my first post. Now to put everyone at ease, I have no aspirations to mimic the frequency of posts from Brad Feld or Fred Wilson (both of which I am a huge fan of), just getting my feet wet. That being said, there are a few things I have been thinking about that I will try to share over the coming couple of months, for anyone who is interested in reading! And after that, who knows, maybe there is a blogger in me that is trying to break free. Now on with the show…

This first post draws directly from our work at Hatcher over the past year, where we looked at our own track record, and asked ourselves “can we do Venture better?”. Yes, this is a plug on what we are doing at Hatcher but also quite a loaded question. 

What does better mean? Since the investment world is dominated by the risk vs. return paradigm, could we provide better returns? Could we mitigate risk better? I found reframing here helps a little: since risk implies uncertainty, and uncertainty is essentially unpredictability, can we have better predictability of our returns? Or come up with a way to combine both? What could we do differently that wouldn’t just add to the endless hyperbole today around the VC space, dancing unicorns and unicorpses, and would actually create value? 

Of course, the concept of balancing risk vs. returns is well known in all facets of investing. It guides our expectations when studying opportunities in everything from Public Equity, Real Estate, the corner Ice Cream store, Derivatives and of course Venture Capital. Over time and specifically in public markets, this balancing act has generated benchmarks for expectations of both risk and return. In fact, public securities of all types now have myriad models to help investors analyze the predictability of their returns. These include Black Scholes, CAPM, and regularly published data such as global market risk premiums, betas, VaRs (and the list goes on and on). 

So if you are an investor in Public securities, you can, using data, predict with a certain probability, your expected returns.

Straightforward. Risk vs. Return 101.

But where are those models for Venture Investing? Can we look at a fund today and say with certainty, we believe this fund can generate an 20% IRR with 50% probability? Not that I have seen. Yet.

There are, of course, some firms that disclose return data, publications such as Cambridge and Associates which give overall returns data, and folks like CB Insights who are now starting to collect and disseminate individual firm data. However, the information is disjointed and predominantly covers only the most successful players in the space (who would want to share that their funds are performing poorly?). In addition, the historical data is usually limited to overall returns and does not provide any additional tools to allow investors to predict with a specific probability their expected returns in a specific fund at inception. 

That means the selection process of Limited Partners is still predominantly based on qualitative criteria, and is rooted in whether the LP believes the General Partner can replicate their performance from previous experience by picking the winners. Granted, thorough DD is performed on the GP, process, history etc, which are all important, but since the 80/20 rule covered here by John holds true for individual funds as we have found in our research, GPs are still looking for that needle in the haystack to generate returns. Some GPs will find those needles. And their LPs will make money. 

Unfortunately, most will not achieve the high returns LPs require, and likely not go on to raise another fund. And their LPs will lose money.

So as any other entrepreneurs that see a problem worth fixing, we asked ourselves is there a way to systematically bring predictability to expected Venture performance, and to do so while generating attractive returns for our investors? As John mentions, we looked at tons of information, over a very long period of time* (details to come in future posts). And the results were clear: by using a data-driven approach to define our Optimal Investment Model we are confident that we can, through a combination of our Hatcher platform, global partnerships and structured portfolios deliver superior, more predictable venture returns. 

*Consulting firm Redseer was commissioned by Hatcher to conduct the study required to support its investment thesis.

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Wissam Otaky

Prior to joining Hatcher, Wissam served as the CFO of MarkaVIP, at the time the Middle East’s top fashion & lifestyle ecommerce business. Wissam previously spent 5 years with Dubai Contracting Company in multiple roles, including working as the company’s Business Development Manager and Group Financial Advisor, handling multiple acquisitions and greenfield projects, and leading the company’s efforts in Jordan and KSA. He co-founded 2 startups early on in his career in Montreal, Canada and is now an active angel investor and advisor to startups. Wissam holds a Bachelor of Commerce degree from McGill University with a double major in Finance and Economics and a minor in Statistics, which he earned with first class honors in 2002, and has been a chartered financial analyst since 2006.

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