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Quantitative Investment Strategies: Pros and Cons

In  a comment on last week’s post about the psychological benefits of index funds, Kevin pointed out an article from Motley Fool arguing that the problem with index funds is that they don’t make any attempt to separate good companies from bad companies. And as a result, they end up investing in companies that perform poorly (like the financial sector over the last year).

The author of the article suggests that a strategy could be developed for running stocks in the S&P 500 through a number of mathematical equations to see which ones should be kept in the fund and which ones should be eliminated.

This type of strategy is known as quantitative analysis because it considers only mathematical (i.e., “quantitative”) factors when analyzing a company instead of including subjective criteria such as strength of management, brand name advantage, and so on.

The advantage: Low cost

To me, there’s one big potential advantage for quantitative strategies: Since they’re purely mathematical, they can be (almost) entirely automated. This allows for a fund using a quantitative analysis strategy to have far lower operating costs than a fund that uses teams of researchers to manually research companies before investing in them.

Not as low-cost as index funds

However, there’s no way that any actively managed fund–even one using an automated strategy–can have lower costs than a (Vanguard) index fund. Why? Two reasons.

First, a quantitatively-run fund needs data. Lots of it. Generally, this data comes at a price–whether paid for directly or paid for in terms of labor-hours from researchers.

Second, a quantitatively-run fund is (most likely) going to have higher portfolio turnover than an index fund. And as we’ve discussed before, portfolio turnover leads to significant (albeit unreported) expenses.

It worked once…but will it work again?

My second issue with quantitative strategies is that there’s no way to know for certain if they’ll work in the future. The fact that they worked in the past doesn’t necessarily mean anything.

Given that there’s a functionally infinite number of quantitative strategies an investor could use, there’s also a functionally infinite number of ones that would have outperformed an index over any given historical period. Look long enough and you’ll find one.

Look even longer, and you can find some that have worked historically, but are clearly nonsense. Example: U.S. stock market movements have been shown to have very high correlation to butter production in Bangladesh.

In the Motley Fool article, the author performs a backward-looking test to see how his strategy would have performed. And…surprise surprise! It beat an S&P 500 index fund.

My question: Was this the first quantitative strategy the author tried? Or did he also run the numbers for a handful of others which ended up underperforming the index?

As they say, we don’t call the man who won the jackpot at a slot machine an expert on probabilities. Similarly, the success of any given strategy over a particular historical period could have been purely luck. A strategy has to outperform the index for an extended period of time (think: multiple decades) before we can attribute it’s success to anything meaningful.

And even if it wasn’t luck…

…it’s entirely possible that some fundamental shift could occur that causes the strategy not to work as well in the future.

In summary

If you want to try to beat the market, a quantitative analysis fund could very well be your best bet. Personally, however, I’m going to be sticking with a strategy based on simple arithmetic–arithmetic that will apply over every extended period: Lower costs means greater returns.

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  1. Quantitative investing is just another flavor of active investing. It’s historically been lower fee than the traditionally run active funds only because those silly quants started out charging less.

    Other than the fees, quant funds are just like any active fund from the investor’s point of view, and everything you say about them applies to active funds in general: higher cost, no guarantee that past performance will continue, etc.

  2. Yeah, the only reason I was picking on quantitative funds in particular is that I was asked specifically what I thought of that one article.

    As you know, I’m fairly skeptical about the value provided by any active fund.

  3. Thanks, Mike, for the response.

    I think your point about a quantitative system being just a slightly more sophisticated version of an active fund rings very true.

    I guess I found the other beginning of the Fool article an interesting thing to bring up – that investors should still understand how an index fund actually divides your investment before you run off and make assumptions about its diversification.

  4. Hi Kevin.

    As much as I argued with it, thank you for bringing up that article. I found it pretty interesting indeed.

    And I couldn’t agree more with your statement that investors should know exactly what they’re investing in–whether it’s an index fund, active fund, or otherwise.

  5. Overall, quant strategies are just as impossible as most any other strategy of trying to consistently beat the market over a significant period of time. While markets aren’t entirely random, they’re nearly close enough to make prediction intractable. A great book is Mandelbrot’s “Misbehavior of Markets.”

  6. Hi rm. Thanks for the book suggestion. I just added it to my swaptree list. 🙂

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