Math Is Hard. Let's Go Shopping!

I've always been fascinated by the idea of a computer-managed investment portfolio. If we could just come up with some rules and investment principles that beat the averages more often than not, we could eliminate human errors and the guesswork element by having an automated algorithm manage our money.

Or so I'd like to think. If it were that simple, everyone would be doing it, right?

Certainly lots of people have tried, with mixed levels of success. Many funds use "quant" -- short for quantitative -- strategies to help them pick stocks. Some of these are little more than stock screeners, set to search for a (human) manager's preferred combination of attributes. Others use super-sophisticated market models and automate all of the investment decisions, with a human "portfolio manager" to fine-tune the model and keep an eye on things.

What most of these strategies have in common is that they apply rules that work most of the time. As you probably noticed, whatever last year was, it wasn't normal. Some quant strategies got clobbered, and those funds now look pretty lousy at first glance.

But even though the market continues to be volatile, things have settled down from last fall's craziness. What are these funds, and are they worth your money?

What quant strategies really are
Quant funds come in lots of different flavors, but for many, the quantitative analysis boils down to two elements: investment selection and portfolio optimization.

The investment selection part is straightforward in concept, though the details of a particular strategy can be complicated. Joel Greenblatt's "Magic Formula" system of value stock selection, as outlined in his (excellent) The Little Book That Beats the Market, is a good example of a simple quant strategy that screens for promising value stocks and trades them in a fixed, disciplined way.

The next step, portfolio optimization, addresses how you mix and match the stocks you like. In a nutshell, if you were to quantify the risk and return of every possible combination of assets and plot them on a graph, you would find an "efficient frontier" of portfolios that maximize return for every level of risk. Optimization fine-tunes the portfolio to put it on that frontier.

So does it work in real life? The short answer is yes, for many funds it works pretty well. But how much of a difference does it really make?

How different is it really?
Let's take a look at a couple of quant funds. Schwab Core Equity (SWANX) is a large-cap "blend" fund that stayed ahead of the S&P 500 in 2008, but has lagged so far this year. Quant Long/Short Fund (USBOX), another large-cap blend fund (but one that can sell stocks short in addition to taking long positions), did well in 2005 and 2006, but has lagged somewhat since. (Blend funds combine value and growth stocks.)

So where are they these days, and how do they compare to a normal actively managed large-cap blend fund? Take a look:

Fund

Top Holdings Include ...

2008 Return

YTD Return

Schwab Core Equity

Wal-Mart (NYSE: WMT  ) , Hewlett-Packard (NYSE: HPQ  ) , ExxonMobil (NYSE: XOM  )

(33.2%)

(2.7%)

Quant Long/Short

ExxonMobil, Texas Instruments (NYSE: TXN  ) , Intel (Nasdaq: INTC  )

(41.5%)

0.9%

Fidelity Fund (FFIDX)

ExxonMobil, Wal-Mart, Apple (Nasdaq: AAPL  ) , Cisco Systems (Nasdaq: CSCO  )

(40.3%)

2.7%

Sources: Morningstar, individual fund company websites. YTD = year to date.

Two things are worth noting: First, quant funds often end up focusing on the same sectors -- and even picking the same stocks -- as more traditional managers. Second, there are good and not-so-good quant funds, and they go through good and bad periods, just like regular actively managed funds.

Long story short
Quantitative strategies aren't a magic bullet. It's just another way to manage a fund. Because the models are created and fine-tuned by humans over time, manager tenure counts, just as with any other fund. Expenses are an important consideration, as is the performance of the manager's strategy in the past.

In other words, we can evaluate quant funds in the same ways we'd evaluate any other funds. That said, Amanda Kish -- the Fool's fund guru and lead advisor of the Champion Funds newsletter -- notes that because quant funds sometimes come at the stock-picking process from a different angle, adding a quant fund to a portfolio of active equity funds can make your overall portfolio less volatile -- and improve your performance -- over time.

And as we've seen, that diversification doesn't have to cost you in long-term performance -- as long as you pick the right funds. In the new issue of Champion Funds, available at 4 p.m. EST today, Amanda takes a look at three quant funds, longtime Foolish favorites, that appear poised for a good run in coming months. If you're looking to smooth out your ride through the next stage of market turbulence, you could do a lot worse than to take a look at these three Champs.

Not a Champion Funds member? No worries -- help yourself to a free trial for 30 days of complete access.

Fool contributor John Rosevear owns shares of Apple, which is a Motley Fool Stock Advisor selection. Intel and Wal-Mart are Motley Fool Inside Value picks. Try any of our Foolish newsletters free for 30 days. The Motley Fool has a disclosure policy.


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