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Attempted 3x Leveraged Short with Beta Zero-Targeting Algorithm

I utilized Blue Seahawks's Beta Zero-Targeting code at https://www.quantopian.com/posts/beta-zero-targeting-automatic-never-worry-about-beta-again and an optimized short on two 3x leveraged equities to attempt to produce a stable, beta neutral algorithm; a sort of middle ground.

3 responses

Beta could be reduced further at the cost of reducing returns

I ran a tearsheet on your result. Let's take a look at it.

First off, it still has pretty high beta. If you look at the rolling beta plot, it regularly goes well over .5. I suspect this is because you're not managing your beta so much as you are reacting to it.

Second is the position management. The "top 10 long positions" shows that it goes as much as 60-63% into SPY and TLT. That's a big exposure to a single name.

The third is probably the most important. When you look at the exposure chart you can see your algo is basically a long algo - it's always long the market as a whole, and is not well hedged. Of course, that's even more true given the underlying ETFs you've chosen!

You've got an interesting study. There are a lot of things you can learn from it. I recommend that one of the things you learn is to look at a bigger picture of how you can find a successful strategy, to take a step back from it and think about what your overall strategy is. Taking a mostly-long strategy and tuning it with some low-beta shorts isn't going to get you to a successful place on Quantopian. In the current set of contest rules it might (might!) get you a prize, but it won't get you an allocation. When we update our contest rules later this year, this won't be viable at all, even in the contest.


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Thanks Dan. I barely utilize the research environment so I really should start learning how to use it. Your comments give me something to look at it so thank you for your input.