Terry Tian: Hi. My name is Terry Tian. I'm an alternative investment analyst with Morningstar. Today, we have Vikas Kapoor, portfolio manager of Ramius Dynamic Replication.
Vikas, thank you very much for joining me today.
Vikas Kapoor: Thank you, for having me Terry.
Tian: We have seen a number of hedge fund replication mutual funds launched in recent years, including your fund which was launched in 2010.
Tian: Could you just explain a little bit about the idea of hedge fund replication?
Kapoor: Sure. The core idea behind hedge fund replication is that in a diversified portfolio of hedge funds, the majority of risk and return is driven by the set of systemic long and short betas, let's call them alternate betas. And a lot less of the return is driven by idiosyncratic security selection called alpha.
The idea is very similar to what has happened in the long-only world, where you own IBM shares and you [look at how] replicable IBM is with the S&P 500. And they are very different. However, you can create a portfolio of 40 to 50 U.S. large-cap stocks, and so long as you can measure the beta of that portfolio to S&P 500 that explains a lot of the risk and return. It's the same logic, the same theory [with hedge fund replication].
The difference is that the alternate betas are different because hedge funds are different. They go long and short, and they try to capture a different set of risk and return. What has happened in the last few years is that a lot more of those instruments are available in a liquid tradable way, and, hence, you see a lot of explanation of a portfolio of hedge funds coming from liquid factors because people can measure them and trade them. That's really the core principle in that if you can own in a liquid way the majority of the risk and return of a diversified portfolio, you don't have to pay 2 and 20 or take the illiquidity risk and the nontransparency risk of actually investing in hedge funds.
Tian: But there are several limitations of the strategy. For example, with the selection bias, a replicator can only be as good as the underlying pool of hedge funds he tries to replicate.
Tian: How does your fund deal with this issue?
Kapoor: Terry, you're touching on I think the core principle of what we will call as version 1 of the advancements in replication that have come around. If you look at the original set of products and original set of research, that was much more driven by looking at indexes like HFRI, which is one typical example that gets thrown around, and then using some long-only tools like backward-looking regressions to try to capture some of the factor risk.
To your point about selection bias, HFRI indexes and hedge fund indexes in general have a number of biases. But beyond that, if you believe hedge fund indexes are good to replicate, you have to believe that all hedge funds have equal skill. We don't believe it, and we believe there is a very small subset of hedge funds that actually possess skill in really deciding the set of good and smart long and short betas to deliver.
So rather than replicating the nonefficient hedge funds, one example that you and I have talked about before is if HFRI has 2,000 hedge funds and you believe 50% of them are good and 50% of them are bad, why do you want to replicate the 1,000 bad ones? What we do is try to focus on the good ones that have gone through our very detailed due diligence and research process, but then also impose our top-down asset-allocation thinking and try to construct an efficient portfolio because replication is only a means to the end.
What you are replicating should be worth replicating and then you can gain access to it in a liquid way given all the liquid tradable instruments that are out there.