Grant, you've got several questions bound up in those two paragraphs. i'm going to try to tease them apart.
First, I want to again say that I don't think that it's productive to think of the hedge fund as a high-yield bank CD. I've tried to point out before that the expected returns of those two instruments are different by an order of magnitude. I'll expound on that: No one would ever borrow money to put it into a high-yield CD. The structure of the market is that the borrow rate is higher than the CD rate; it's a losing proposition. But if we're building the hedge fund right, then it does make sense to borrow money, in the form of leverage, and invest in the hedge fund. We expect to have institutions that, for instance, put $100M in capital to work with our hedge fund, and choose to use 3X leverage so that the fund is actually managing $300M in investments for them. I don't see that happening with ETFs.
The next question is whether, at limit, will the strategies all be highly correlated. I suppose, ad extremum, we could be confronted with a host of algorithms that each go up exactly .05% per day. If that happened we'd have to develop other tools to figure out the degree of correlation. In practice, though, the world is a lot messier. Algos go up a a few points one day, down the next, and up again. An algorithm can be quite predictable over a long period, but that doesn't mean it's going up every day, exactly like every other desireable algo. The fact that they go up differently means we can evaluate their correlation.
Next I want to tackle is crowdsourcing. Your first sentence characterizes the choice as one of "institutional grade algos versus an innovative fund." I think that's a false choice. We're actually doing both. We are building a quant hedge fund from crowd-sourced algorithms. That is innovative, despite my lack of modesty in saying it so baldly.
I agree, it would be both neat and awesome if we could get 10,000 of our community members allocations from the hedge fund. Unfortunately, we don't have that many members writing high-quality algorithms that we can invest in (yet). You can download the contest CSV and look at the entries. There aren't 1000 good algos, let alone 10,000. If we get there, we'll fund them, and that will be the thrill of a lifetime for us all.
You don't quite say it explicitly, but I think you're saying that it doesn't count as crowd-sourcing if we use algorithms from a few dozen people rather than a few thousand. Does Kaggle count as a crowd-sourcing solution? I think that's a semantic argument, and probably not a very interesting one.
We have not signed any institutional investors. (Also, to be clear, we are not soliciting nor advertising for them either.) We've had informal talks with a number of people in the industry, and the response has been very positive. When you get down to it, a lot of these deals boil down to "what's the price?" We're doing a lot of work to lay the foundation for the fund so that when it comes to sign the deal, we get a price for the money that we like. That day isn't here yet.
I think there are a lot of parallels between the institutional money and VC money. Any of the questions you ask apply to VC and institutional investors alike. Why aren't they members of the community? I can't speak for them, but my guess is that because it's not their community. We're a community of quants, not institutional investors. How can you (or I, for that matter) know that we're building a product they will invest in? That's not something that is provable beforehand. We are, I assert, building something that has never been built before. You can never be sure it will work until it already has worked. What you can count on, though, is that our interests are aligned. We only make money if the community makes money, and vice versa. Are there investors out there who are looking for something like us, but not exactly us? There certainly are. However, we can't be everything. One of the best ways to make a startup fail is to lose focus and to try to do too much. We've talked to a lot of smart people, collected a lot of advice and experience, and we've made a choice. The response we've gotten supports that choice. If the data starts running the other way, we'll evaluate it when we get there.
Finally, your question about the black-box algos. It hasn't been an issue with investors yet. It's weird, but they are used to investing in black boxes. I'm not too worried about it, either way. As we negotiate contracts with algorithm authors, I see granting the right for someone to review the algorithm code as one of the potential terms of the contract. We will see how that one shakes out.