Replication strategy as it pertains to investing is a growing phenomenon.
When it comes to hedge fund replication, Maz Jadallah, CEO of AlphaClone, is something of a pioneer.
Jadallah was "first to market" with a hedge fund replication ETF, AlphaClone Alternative Alpha ETF (ETF Series Solutions ALFA).
Jadallah spoke with Benzinga about AlphaClone and how it enables everyday investors to mimic the tactics of successful hedge fund billionaires.
Benzinga: What is AlphaClone and what does it do?
Maz Jadallah: At its core, AlphaClone builds what we call self-driving equity strategies. They're self-driving because they automatically select the investments they make and stocks they invest in based on a particular approach we take.
They're also self-driving because they adjust their market exposure as well. It's a 100 percent rules-based strategy.
What we're trying to do is leverage public information put out by institutional investors in order to build self-adjusting, self-driving strategies for investors.
BZ: So, is this active or passive investing?
MJ: Actually, we combine the best of both active and passive investing.
On the active side, it's about accessing managers that have demonstrated true stock picking skill. It's about aggregating their best ideas and their highest-conviction ideas into one portfolio. It's about varying the market exposure that you have based on rules.
On the passive side, we offer our strategies in ETFs. They are transparent and relatively liquid. We call it "smart passive," and that's essentially what we try to offer investors.
BZ: Who is AlphaClone for?
MJ: The strategy fits different kinds of advisers, whether retail-oriented or institutional.
These are buy and hold strategies so we're looking essentially to solve many of the pain points around investing.
BZ: What sorts of pain points?
MJ: With manager selection, it's one of downside risk, drawdowns.
It's one of behavioral risks, buying at the wrong time, selling at the wrong time.
There are also risks that we try to account for when we're constructing our portfolios and the rules that we use to do that.
So, our strategies are core allocations inside a retail investor’s portfolio.
BZ: Could you talk a little bit about the internal process in terms of selection?
MJ: We call it Clone Scoring. Really, our score is our attempt at discerning, identifying and measuring true stock selection skill on the part of the manager.
The process is really tied to whether the manager has demonstrated selection scale over a long period.
A manager's returns can stem from multiple sources. They can stem from the fact that the manager has selection skills. They can stem from the fact that the manager's using leverage. They can stem from the fact that the manager has timed the market correctly. They can stem from the manager's trading skill.
There are many sources of performance. It's difficult to know what you're getting, what you're paying for, when all you are doing is evaluating the manager's actual performance number.
BZ: How does AlphaClone sort all of this out?
MJ: The data set we use to score of managers allows us to strip away all of the sources of potential returns, and evaluate them on one thing and one thing only - what position were they in at the end of every quarter?
We can use that insight to develop a method to identify managers who have demonstrated stock selections over a long period. That's what we do. That's what Clone Scoring is.
BZ: Is the process repeated, and if so, how often?
MJ: We score them (managers) every six months.
One of the things that trips up investors is that they fall in love with their managers. Our computers don't fall in love. They evaluate everyone every six months and pick managers with a high score.
We also don't over concentrate on a particular manager. There are always at least 20 managers in our strategies. The reason for that is that we want to mitigate as much manager-specific risk as possible.
BZ: So, AlphaClone literally “clones” the positions of the top managers?
MJ: Maybe the word clone is a little bit misleading. We don't invest in all of their positions. We like to take their high-conviction ideas, the ideas that are going to drive true performance in their portfolios, as opposed to their entire portfolio.
We aggregate those over multiple managers. We developed a rules-based downside hedge mechanism based on the 200-day moving average for the S&P 500.
BZ: How does that work?
MJ: If the index— because it's below its average, then we move from long only to market neutral. Then we wait until the end of the following month to evaluate the trigger again.
It's binary, right? It's either long only or market-neutral.
The reason we do it that way is that we want to have a high degree probability that we're long only when the market is running over multiple months. We also want a high degree of probability that we're well hedged when the market is selling off over multiple months.
So, it’s 100 percent rules-based. It doesn't matter how Maz feels waking up in the morning.
That's our philosophy. Google is building self-driving cars. We're building self-driving ETFs.
At the time of this writing, Jim Probasco had no position in any mentioned securities.
Image Credit: Public Domain© 2024 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.
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