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November 2002
Realistic Expectations
"You can't expect to win unless you know why you lose."
-- Benjamin Lipson

 

HE RECENT BEAR MARKET HAS MANY investors questioning not only their investments but their overall philosophy as well. Many had taken on too much risk when stocks only appeared to go up back in the '90s. For those who did, there's been quite a price to pay.

As stocks continue their descent, preservation of capital has taken on new importance. Discouraged investors are pulling money out of equities, now seeking the safety of bonds, CDs, or even their own mattresses. Cash has consistently flowed out of equity mutual funds and into fixed income counterparts.

If managers can't put up positive returns -- or at least protect your investment -- why would you want to use them? Why would you buy a fund or a stock if all it did was decline? Isn't the purpose of investing to make money, not lose it?

A Little Perspective

Obviously no one but a fool would invest in a guaranteed losing prospect. But even over the past two years, stocks weren't guaranteed to decline, they just did. Indeed, when the entire market is falling -- and often precipitously -- can you really blame equity managers for losing money?
Equal Opportunity Bear
Graph--Major Market Indexes, March 2000 - October 2002
In the past thirty months, it didn't matter if you were a large, mid, small cap or even foreign stock investor, if you were long, you probably lost money.

If you own stocks or stock funds, you've got to expect them to fall when almost all stocks are losing ground. Just as you wouldn't expect to catch tuna when fishing in a fresh water pond, you shouldn't expect your stocks or stock funds to post gains when the entire market is in decline. About the only way to avoid this fate is to own something other than stocks.

Indeed, when you see equity funds or managers claiming positive returns over the past two years, you can be reasonably certain they're not just fishing in the stock pond; they're holding pretty good slugs of bonds or cash.

And that's the point: If you want to minimize the risk to your invested capital, diversify your portfolio. If you only own one asset class, your returns will suffer right along with it when it declines. The only way a long portfolio could have avoided losses in the past two years was to own something other than or in addition to stocks.

While you can't reasonably expect your equity portfolio or mutual fund manager to match the performance of cash or bonds Archive Indexwhen stocks are down, you can expect them to match or even outperform their appropriate benchmark. Back in the bubble days, the best managers not only turned in double-digit returns, they bested the benchmarks as well. In the bear market they may still suffer declines, just not as severely as their benchmark.

We've argued before (The Best Asset Allocation) that investors are more loss averse than risk averse. Given this loss aversion, it's not surprising that they would want to measure their portfolios and managers relative to positive returns rather than appropriate benchmarks. It's understandable, just not very valid.

Our Portfolios

What brings this up is some recent correspondence. One reader asked what we're selling. She said she had looked all over the site and still couldn't find the pitch.

Perhaps that's what the Web's come to: Anything free must come at a price. Initially it was designed as a way for academics to exchange ideas and then blossomed into a techie cyberworld. Back then, the idea was that everything should be free in this new unregulated world. As the Web became more commercialized however, pay sites, banner adds, and now even pop-ups became prevalent. Little is free and everything comes at a cost.

But believe it or not, we're still posting actual research for free. As The Quantitative Approach indicates, this site is an effort to interest more investors in the quantitative approach to investing. This page gives you some insight into how models are created and tested out of sample. No pitch, no sale, just research.
Our Quant Portfolios
Portfolio 3
  • Top 30 Stocks Based on Stepwise Regression Across All Stocks of the S&P 500
  • No Attempt is Made to Sector-Weight this Portfolio
  • Rebalanced Every 60 Days
  • Stocks Remain in the Portfolio Until Falling Below the Top 40
  • The Highest Rated Stocks Not Already in the Portfolio are Added When Existing Constituents are Removed

Portfolio 4
  • Top Stocks of Each Sector Based on Stepwise Regression of Each Individual Sector of the S&P 500
  • Number of Stocks Selected in Each Sector Determined by Current Sector-Weightings of the S&P 500
  • Rebalanced Every June
  • Stocks Remain in the Portfolio for 12 Months Unless Deleted for Special Circumstance e.g. Acquisition
  • Stocks Removed for Mergers and Acquisitions are Replaced by the Next Highest Rated Stocks in Their Specific Sector

Portfolio 5
  • Based on 9 different Growth/Value/Blend and Large/Mid/Small Cap styles as defined by Morningstar's "Stylebox"
  • Index SPDRs and I-Shares used to represent each component of the Stylebox
  • Stylebox sectors and weightings optimized using CAPM regression
  • Reallocated mid-first month of each calendar quarter

Which brings us to a second correspondent who wondered why anyone would possibly want to invest in one of our portfolios. In his words, they're "a guaranteed way to lose money."

First of all remember we're not selling anything, not even our models. We're not encouraging anyone to invest in them, we're still developing them. As the page title says, these are works in progress.

No one should put all of his or her funds into only one asset class much less equity model. Our models are 100% stocks and not surprisingly, act like stocks. When the market's up, they're up and when it's down, they're down. No surprises here.

Unlike some mutual fund managers, we don't try to game the system by adding bonds or cash. We aren't trying to time the market or asset allocate. What we are trying to do is build and test quantitative stock models, so it should come as a surprise when they act like stocks.

Yes, they've lost a lot of money over the past two years, but so have 95% of all stocks. No, they wouldn't have been good investments over that period, but then we never claimed they were. At best they can serve as a portion of an asset allocation, representing equities, or even smaller subclasses of available assets. We aren't trying to develop a stand alone single bullet for all markets.

An that's the point: All of our portfolios are being tested for how well they characterize the class or subclass of assets they're designed to represent. To do this, you want to see how they perform in a variety of market conditions, both up and down.

When equities are down, the goal isn't necessarily to produce a positive return (although that would certainly be nice), but rather to beat the appropriate benchmark. In a down market, this may simply mean losing less than the benchmark.

Over time, most series revert back to the mean. Stock investors are learning that now as the seemingly ceaseless bear market brings the excess return of the 90's back in line with the historical averages. Given this, a model can be deemed successful if it on average outperforms its benchmark. Over the past two years that amounts to losing less than the benchmark.

Would you have made money by using even a successful stock model between 2000 and 2002? Probably not. But if you're a long-term investor, one who will maintain positions more than a few days, a week or even a year or two, a sound asset allocation and holdings representing the various investment classes that consistently outperform their benchmarks, will put you ahead of the market.

So no, it's not surprising that our equity models fall right along with the broader stock market. We're not selling them to you or even suggesting you actually invest in them. Instead, we're trying to develop them to be successful over the long-term and along the way we're giving you a glimpse of the underlying quantitative process. Just don't expect us to pull a tuna out of a freshwater pond.


 

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