What Kind of a Blend is 130/30?
While reading “Challenges in Quantitative Equity Management” from the Research Foundation of the CFA Institute, I came across this concept, related to 130/30 funds, mentioned several times; in fact, mentioned often enough to get on my nerves:
In theory, these strategies are a long-only fund plus a zero-capital long-short overlay.
Bullshit, bullshit, bullshit.
Did I say “bullshit?” Yes, at least as these funds are commonly implemented.
The common tack is for the fund to use one (1!) factor model to “score” each stock, then use a covariance matrix to weight the holdings. Since only one model is used, the 100% long component and the 30% additional leveraged long component have a very strong correlation to each other. Additionally, the 30% short component has a pretty strong inverse correlation to the long components. In reality, as commonly executed, 130/30 is just one frickin’ leveraged strategy.
OK, I’m overstating the case just a bit, as there is some diversification benefit, but it’s not as much as it could be. That diversification benefit comes pretty much entirely from the short side, because to the extent that they add positions on the long side (and increase diversification there), they also dilute the impact of their factor models (because they’re taking the top-scoring 350 or so stocks, instead of the top-scoring 200 or so stocks), so it comes out in the wash. It may be better to simply leverage the existing 100% long component instead of adding additional stocks for the extra 30% component (something to think about).
Now imagine three different factor models, one that works best on the short side, and two that work best on the long side. Take the best-returning long side model and put it at 100% weight, then put the others at 30% weight apiece. Now one would get a true, large diversification benefit, whereas there’s much less diversification benefit when the same model is used to define all segments.
Of course, if all three models aren’t on the same order of magnitude in terms of returns, then we potentially have another dilution problem … adding a diversifying strategy that compounds at 6% annually to a main strategy that compounds at 20% annually doesn’t necessarily help the situation, as the manager may be better off in the long run being non-diversified and compounding faster.
My second gripe on the above quoted idea is the assertion that the long-short extension is “zero-capital.” No it ain’t. Leverage costs money, and even if the cost is smaller for a fund than for a retail hack like myself, there are other costs to leverage. First, it exacerbates the impact of any heteroscedascity of returns that the manager hasn’t accounted for; second, it leaves the manager at the mercy of the general availability of leverage in the credit marketplace; third, it introduces a credit risk from the specific counterparty providing the leverage. While it may tie up less capital, it increases risk*, and that needs to be accounted for somehow. To their credit, they do mention leverage as a problem:
Theoretically, the advantage of this strategy is obvious: If the long-short strategy is profitable, it is a zero-cost contribution to returns with no capital invested. In practice, however, there might be two problems: (1) The strategy is leveraged, and (2) it is very sensitive to the quality of the forecasts used for shorting.
An additional gripe on the ideas inherent in 1X0/X0 discussions is the assertion that the strategy will have “beta of 1 to the market” - this is “beta bullshit” that I have already addressed in another post. Beta could be high or low, depending on the factor models used.
The point is that, generally speaking, the generally accepted assumptions used in portfolio management by Wall Streeters probably shouldn’t be.
* Don’t for damn second think that “risk” is solely defined by volatility of returns! There are lots of different kinds of “risk” … risk of ruin (often worse in “low-vol” leveraged strategies than in high-vol unleveraged strategies), risk of not achieving a benchmark return, etc.
I’ve written about diversification and strategy blends before.
I’ve written about 130/30 before.
I’ve used a research paper to put together an example long/short trading system.
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September 4th, 2008 at 1:25 pm
Hi Bill,
I like the new look of your site as well as the tabbed menu. However, I want to let you know that I conducted a usability study last year of a website that used two narrow right columns similar to your layout. The far right column was completely ignored. Every user/participant in the study couldn’t accomplish a single task that required noticing information or links in the far right column.
That said, your placement of the 300×250 ad unit and 350?x? callout makes sense.
September 4th, 2008 at 6:26 pm
I guess it’s a good thing the 160×600 ad and the quote machine are in the left column, then.
September 6th, 2008 at 5:38 pm
“Bullshit, bullshit, bullshit.”
If you’ll excuse the quant-speak (yes, your readers may find it more offensive than barnyard talk), EVERY portfolio should have a position such that an increase would raise risk faster than it raises average alpha.
Many investors (managers) find that they have insights about stocks that will under-perform sharply, but no effective way to act on those insights (expected returns). By shorting, they indeed raise the risk from a higher net weight on their favored factor(s), but it is incontrovertible that they are able to reduce their risks associated with the random, stock-specific effects for a given level of total risk.
I won’t –couldn’t, actually — say that this is the common practice for building 1X0/X0 portfolios. Lots of what I see in print is miserably stupid — dumbed down, perhaps, by the PMs who, 50 years after Markowitz and 35 years after Rosenberg, don’t understand elementary financial mathematics. But in most of the shops offering these things, some Junior Financial Engineer actually could implement a portfolio with a better risk-reward ratio.
After all, “every option has a value.” Why not look at the lifting of the short constraint that way?
September 6th, 2008 at 5:42 pm
Oh, and the other side of the coin: reducing any position in a risk/reward optimal portfolio should reduce expected return faster than it reduces risk. That’s the trouble with long-only strategies: you may have beliefs about FNMA going to zero, but can’t capitalize on them. Your zero weight on the stock implies a positive return that is not so. The implied alphas are often much higher than your actual beliefs.
Yes, this all requires that your alpha forecast / strategy is favorable. But I presume that because otherwise you’d just be indexing anyway, no?
September 6th, 2008 at 6:13 pm
Hi Walt, thanks for the comments!
“a position such that an increase would raise risk faster than it raises average alpha”
Attempts at maximizing such a fine edge often run right over a cliff; think Kelly optimization. Especially given that the margin for error in any such calculation is probably larger than the modeler thinks it is. Better to find where you think the edge of the cliff might be, and position oneself 20 paces away. Unless it’s the investor’s money!
I don’t like that you use the word “risk” instead of the more proper “volatility.” I know it’s hard to be consistent with that, but I’m trying.
“Your zero weight on the stock implies a positive return that is not so.”
No. A zero weight could also imply no opinion on the return, or a positive opinion that was not strong enough to outweigh transaction costs.
The “information theory” about beliefs on stocks going down, and the ability to capitalize on it, is theoretical window-dressing at best. Should managers have a short option available? That’s a fund-marketing question for each fund. In T-H-E-O-R-Y, a manager that can go short should have an advantage. That’s in theory.
But at the end of the day, a 1X0/X0 is just a blend of strategies with leverage added. Whether it can outperform, in PRACTICE, a blend of strategies that are all long-only, or a single long-only strategy leveraged to 160%, depends on the strategies. In order to meaningfully benefit from a blended strategy, the strategies must have similar long-term compounding rates as well as (over the longer term) low de-trended correlation. If the compounding rates are dissimilar, than added the less profitable strategy to the blend reduces returns more quickly than it reduces volatility.
It’s a NICE theory, it makes sense, it gives me the warm and cozies when I think about it at bedtime, but it falls flat because of the predominant long-term upward trend in equities, which makes the best short strategies less profitable than the second- or third-best long strategies.
So stop caring if the strategies are long or short, and look for the strategies with the best returns. In my timeframe and my testing, they’re all long. The short side just isn’t as profitable over the long-term as many other, different long strategies, and adding a short component has, in my testing, just degraded the returns. As a result, I spend most of my time looking at long strategies, but I still look for short ones now and then.
Take a look back at Lo’s 130/30 index paper, and imagine that, instead of building an index with all of Credit Suisse’s Alpha Factors in the model, he instead built multiple different models using different sets of factors, structuring long and short strategies. I would betcha that the best 60%-leveraged 3-strategy blend coming out of that experiment would be LONG-ONLY.
September 7th, 2008 at 8:33 pm
Funny, I’ve been talking about minding the gap between theory and reality for years, not only at work but also here on this blog. Then tonight I’m doing some light reading and come across this interview where William Shadwick, developer of the Omega Function, says pretty much the same thing.