Value and Relative Strength Chronicles

April 22, 2010

Of all the different investment factors that have been tested and employed over time, value and relative strength have emerged as “best by test.” In other words, when applied consistently over time, these two factors have proven the ability to generate superior performance over buy-and-hold. What is especially great about these two investment factors is that they tend to have a very low correlation to each other. This low correlation allows them to be very good complements.

If all investors cared about was return, then finding uncorrelated strategies wouldn’t be such a big deal. Simply pick value or relative strength and hold on for the long run. However, in the real world, investors have a preference for more stable returns. Value moves in and out of favor, as does relative strength, which presents a dilemma for the investor. Yet, by mixing the two it is possible to reduce the volatility without sacrificing the return too much (and in some cases it can even be augmented.)

Greg Carlson, of Morningstar, recently wrote These Funds Can Ferret Out Value Across Asset Classes in which he screened for some excellent value funds that have the flexibility to change their allocations to equities and fixed income depending on where they find the best value.

Carlson explained his screening criteria:

We used Morningtar’s Premium Fund Screener to sort through the conservative-allocation, moderate-allocation, and world-allocation categories. We set the screener to identify distinct share classes of funds within these categories that are covered by Morningstar’s fund analysts, require no more than $10,000 as an initial investment (we also excluded those that list a minimum initial investment of zero, as these are institutional share classes), and are open to new investors.

We also wanted funds that held up better than the majority of their category peers in 2008 (when the bulk of the market’s decline occurred) and managed to generate at least a 20% gain in 2009. Because last year’s rally was led by speculative, economically sensitive fare, we didn’t want to exclude funds that lagged their category peers in 2009 yet still posted a sizable absolute return. (World-allocation funds gained an average of 25% in 2009, while moderate-allocation funds gained 24% and conservative -allocation funds gained 20%.) Finally, we wanted funds with managers who had been on board for a minimum of five years, beat at least three fourths of their category peers over that span, and had below-average expense ratios.

This screen yielded six funds as of April 19, 2010.

Of the six funds from this screen, I wanted to see how the two biggest funds do when mixed with our Global Macro strategy (available as a separately managed account and as DWTFX.) Our Global Macro strategy is a global tactical asset allocation strategy in which the allocations are driven by a systematic relative strength process.

Efficient frontiers are shown below:

(Click to Enlarge)

(Click to Enlarge)

Given the assets in these two value-based asset allocation funds ($50 Billion in Vanguard Wellington and $12 Billion in Van Kampen Equity & Income), it is no secret that these funds have been successful. However, I suspect that there are many fewer investors who are aware of the potential volatility reduction and increased performance by mixing it with our Global Macro strategy. The correlation of Global Macro and Vanguard Wellington was only 0.34, and only 0.42 for Global Macro and Van Kampen Equity & Income over this time frame.

The potential benefits of mixing value and relative strength are there for the taking.

VWELX and ACEIX returns are taken from Yahoo! Finance. Please note that the Arrow DWA Tactical Fund (DWTFX) was converted to our Global Macro strategy on 8/3/09.

Click here to visit ArrowFunds.com for a prospectus & disclosures. Click here for disclosures from Dorsey Wright Money Management. Past performance is no guarantee of future results.

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Theory versus Practice

April 22, 2010

William Sharpe, a Nobel Prize winner in Economics, wrote a recent paper about how the 4% retirement spending rule is inefficient. MarketWatch had a recent feature discussing his paper–and more than anything about the spending rule itself, the piece made me think about how large the gulf in finance is between theory and reality. As Yogi Berra is reported to have quipped, “In theory, there’s no difference between theory and practice. But in practice, there is.” (There’s a link to Mr. Sharpe’s paper in the MarketWatch article.)

The 4% retirement spending rule is clearly a rule of thumb, and I am sure that most practitioners modify it depending on the client’s circumstances. (We prefer a 3% spending rule, and I’ve seen other rules based on the yields available. For example, one paper I read advocated a spending rule of 125% of the yield on the S&P; 500, arguing that you can spend more when yields are high than when they are low.) Mr. Sharpe says the 4% spending rule is too simplistic. He’s right–rules of thumb are supposed to be simplistic. But no one using it is really going to mistake it for the be-all-and-end-all.

An extraordinarily complex retirement spending rule that takes many complicated factors into account is just as likely–or maybe even more likely–to fail. The real world is a much messier place than an ivory tower. Things that seem like good ideas in theory, even to Nobel Prize winners (I’m thinking Long-Term Capital Management here), often fail miserably in practice.

The reason that complicated things never work in real life is that there are too many unknowns in the equation. In modern portfolio theory, market returns and correlations between assets are not stable, so the whole thing is essentially unworkable. A perfect retirement spending rule could be made for each client if the practitioner only knew exactly what their investments would earn each year and how long the client would live. That’s not going to happen, so we are left with rules of thumb.

The most important thing about any modeling approach is how robust it is. If you jiggle around the inputs, does it fail miserably or does it continue to work? Is it based on historical inputs which are guaranteed to change, or does it just adapt without making assumptions? We have strong feelings about this. The fewer factors a modeling approach uses, the less likely it is to be knocked down by some unanticipated factor interaction. We use a single-factor model and test rigorously for robustness (you can read our white paper on Bringing Real-World Testing to Relative Strength here). Academic finance would be much more useful to real investors if they kept in mind another saying: it is better to be approximately right than precisely wrong.

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Icelandic Volcano Humor

April 22, 2010

On Wall Street, even natural disasters are turned into fodder for jokes. CNBC.com has a cute article on a few of the quips.

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Fund Flows

April 22, 2010

The Investment Company Institute is the national association of U.S. investment companies, including mutual funds, closed-end funds, exchange-traded funds (ETFs), and unit investment trusts (UITs). Members of ICI manage total assets of $11.82 trillion and serve nearly 90 million shareholders. Flow estimates are derived from data collected covering more than 95 percent of industry assets and are adjusted to represent industry totals.

The affinity for taxable bonds continued in the week ending 4/14/10.

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