Tom Madell's  Instablog

Whether you have been a) an active investor, or, b) in buy and hold mode with your investments, or, c) just sitting on the sidelines in cash, your prior actions or inactions represent your decisions about what you felt has been an appropriate course of action. Even if you have been a relatively inactive investor, it makes sense to examine whether the application and timing of your prior buy, sell, or "considering buying an ETF or fund investment but do not" decisions are helping or hurting your bottom line.

Looking back over at least the last several years, we'd all like to hope we made the right decisions when we either bought or sold or held back on making an investment. If it turns out we were right, this means we either made a profit or avoided a loss. But if we were wrong, this means we missed out on a potential gain or actually suffered a loss.

Experience has shown me that many investors, surprisingly, don't really have a clear idea of which of these two basic possibilities it was, or at least, the extent to which they might have benefited, or failed to do so, as a result of their choices. This is especially true in instances when they sell completely out of an ETF or fund or elect to sit on the sidelines; in each of these instances, it is more than likely that they will not track what might have been the result of doing otherwise. Click here to see a little more detailed and visual example of what I mean.

Obviously, one can get a general idea of how a given ETF, stock, or bond fund has performed by checking its reported performance in newspapers or on websites. But, especially with highly volatile investments such as stocks, these sources cannot likely tell you how wise your decision was because they won't show performance from the day you acted (or could have) right up to the present. They only show buy and hold performance over one set period, such as exactly over the last year. Since it is extremely unlikely you would have held your fund only over that same exact period, the return shown will not be valid for any other period of ownership. Or, say your potential decision occurred when the fund was either at what turned out to be a relatively high or low price during that year; your return could then easily vary significantly from that reported in a year-over-year table. Your actual return becomes even more complicated if you made more than one buy or sell decision on different dates during the year.

Even if you are sure that your actions resulted in more gain than loss, you may want to put your belief to an accurate, quantifiable test that either confirms or refutes your belief. After all, we know from research that the majority of investors self-appraise their decisions as being above average, leading to what has been named "the better-than-average effect." Obviously, most investors cannot all be better than average. Human egos dictate that most people tend to be overly positive in the appraisal of their own abilities, whether about investing, driving, or most things actually.

Why do investors really need to know their own "personalized" performance, rather than the general performance found in a fund performance table? Such performance tracking is particularly important, not just to satisfy curiosity, but to help you appraise what your future strategy should be. Should an investor always continue to use what has been their customary decision-making strategy? Probably only if one's prior strategy has been consistently working to help them achieve better returns than they might have received using a different strategy.

If, for instance, they learn that their active decision-making strategy is not performing as well as a low cost index fund, perhaps they would be better off abandoning that strategy in favor of a pure buy and hold or passive strategy that involves hardly any decisions or strategic analysis. In fact, trying to figure out the best time or conditions under which to buy or sell an investment is so difficult that the great majority of investors, and even mutual fund managers themselves and their research/investment teams, more often than not fail to beat comparable indexes.

More on Why to Put Your Investment Strategy to a Test

Let's say you have $10,000 sitting in a money market account or a bank earning very little right now. Suppose you would like to invest that 10K but are unsure where to invest it, and whether you should invest it right now or wait for the "best" opportunity. And, should you invest it all at once or try to "time" your purchases gradually according to either the calendar or your thoughts about the market?

While the buy and hold investor might opt to invest it all at once and merely hope for the best, many investors might wait for a market drop, or attempt to maximize gains by investing only when "signs" pointed to potentially greater gains ahead. In other words, the more active investor might follow some sort of strategy, either complex or straightforward, whereby he invested only when he determined the time was right (or followed an advisor who felt that way).

Obviously, there is no absolute way to know in advance what will turn out have been the "most correct" approach for this particular 10K; such can only be known in hindsight. However, once you have already made some prior investments (or tracked those you didn't), you can tap into your previous experience to help you get a better idea of what might be the most effective strategy for future investments. Of course, if you don't really subject your past investment decisions to a reasonably rigorous test, you likely won't really have enough of a basis to go on to guide you in making your current decision. Instead, you might mainly rely on your above-mentioned subjective ego which could easily give you reason to think that your prior decisions were indeed good, even without solid confirming evidence. It follows that you will be less likely to consider an alternate strategy. At the end of this article, we will spell out in detail an example of perhaps the best way to prove beyond a doubt how effective particular prior decisions were.

You can also put to a meaningful test any prior decision to either partially or fully sell a fund investment (except those made because you needed the money for a non-investment expenditure - this is more of a "forced" decision.) More likely, such decisions are executed because you (or your advisor) have determined that this would be a wise action, with the goal of coming out better than holding on. What would certainly be helpful is accurate data on whether your prior sale(s) wound up helping or hurting your bottom line. Too many "hurting" rather than "helping" decisions might suggest a change of strategy.

As we have said, many people will never closely examine whether their prior decisions indeed later proved to be wise or mistaken. They likely feel some relief at making a decision, but then move on without ever really examining whether there might be a pattern of missed gains or increased losses in their actions.

A way to accurately see whether your decisions are helping or hurting you is readily accessible and should involve only a small effort on your part. Using it just once or twice on a few of your key past investment decisions could help convince you your decision making is either on track, or perhaps needs to be altered. Unfortunately, the method to calculate your actual rate of return in these types of situations has been given the ugly name of Annual Percentage Yield (APY), or also the Internal Rate of Return (I.R.R.). However, all it entails is determining an annualized rate of return that takes into consideration the timing of investment decisions, including purchases and sales, as well as the compounding of the returns over multiple year periods.

Why Less Decision-Making Tends to Do Better

One of the reasons that index funds quite often beat managed funds, and fund returns in performance tables are almost always higher than the long-term "investor returns" the public actually achieves and thus are a relatively inaccurate method of estimating one's own potential returns, is undoubted related to what we have discussed thus far. When investing in an index fund, you are nearly assured that no fund manager will make decisions as to when is the "right" and "wrong" time to buy and sell. You would think that a financially trained, professional fund manager would typically be able to outperform an index such as the S&P 500 by making astute decisions. He/she would focus on the "best" investments at the time, and avoid the "worst." But because, in my opinion, there is such a considerable aspect of investing that is counterintuitive (meaning not discernible through a logical analysis but more successfully attacked by going against what the majority concludes), neither professional managers nor ordinary individual investors will typically be able to "figure out" what the best stocks to own are, nor the best time to buy or sell them. Even when a fund manager does make successful choices, the very presence of a highly paid, skilled manager as well as his associated trading costs, will often pull down his winning advantage so that he is no longer able to beat the index.

The same is likely true of individual investors regarding their ETF or fund investing. Aside from some buy and hold investors who may make no attempt to act on their investments, most fund investors (or their advisors) feel that there should be some advantage in using whatever knowledge they have to formulate good guesses as to when to buy and sell one or more funds. But are they able to buck the difficulties that stymie professional fund managers? Not very often.

By using the technique we are about to give you, you can find out precisely whether your own decision regarding a particular past fund investment has turned out relatively well or not so well, and if the latter, whether you should consider altering your strategy in the future and merely use a more "passive" method, or even perhaps switch to a more counterintuitive/contrarian approach of going against the majority.

You might think "past is past" or "let sleeping dogs lie" - i.e. there is nothing one can/should do about any inopportune decisions one might have made, so just forget it and move on. While this is likely what many investors do indeed do, it might be better to test the facts than to accept simply making assumptions about them which will likely have varying degrees of accuracy. There is something you can do to help stop missing out on lost opportunities but first you must be able to recognize if this is indeed happening and the extent it may be affecting your prior results. Of course, if your decisions turned out to have been profitable, then perhaps nothing new needs to be done. But if you don't know for sure, then any possible future improvements become equally hard to discern.

An Example

Suppose you had $10,000 at hand in cash back in early 2009. You correctly sized up that the US economy was in one of the worst morasses in generations so that made you extremely apprehensive about investing that money anywhere near the stock market. So far, so good - you likely avoided some significant losses in stocks.

But what about further into 2009? Stocks came roaring back with a vengeance beginning that March. Was the turnaround to be trusted? Obviously, like always, everyone had their own opinion; some investors decided it was still too risky while others started buying.

If you were in the latter group, perhaps influenced by my Newsletter at funds-newsletter.com which for the first time put out an overall Buy alert for all 9 US "Morningstar grid" categories plus diversified international stock funds on Nov. 12, 2009, you might have put that 10K to work in one or more stock funds on that very day and continued to hold. If so, let's "test" how you would have done compared to not acting right up to the present time (Jan. 30). (Note: My Newsletter has not issued a "Sell signal" for any of these categories during the elapsed period, and instead, has advocated continuing to hold.) Let's also assume that the fund you chose to buy was my most highly recommended fund in terms of percent allocation as of that time, the Vanguard Growth Index (VIGRX) (given my "overall" Buy signal, it could have been any fund in these 10 categories). In fact, I was so positive on the Large Growth category that I had even earlier, on Oct. 8, 2009, issued a "Buy signal" for this category on my website.

How well you would have done reflects the price on the Nov. 12, 2009 purchase date as compared to the NAV now, taking into account distributions, and annualizing the result over the period of nearly 27 mos. Unless you have your own software to compute how well you would have done, I recommend using this online tool that will easily perform the calculation for you; all you need to do is plug in, in addition to the starting date: a) the amount of the investment; assume that you invested the entire 10K on the above date; the tool also allows you to enter any additional investments ("payments") as well as any sales ("withdrawals"); b) the ending date; and c) the current value of the account which, as an investor in the fund, you can get either from your fund's website, or by taking the number of shares you currently own and multiplying by the current NAV; this amount is referred to as the "future value." (Do not add as additional investments the shares credited to your account from distributions; these amounts are not payments that you make and are "included" automatically when you get the future value.) That's all there is to it!

If you never "pulled the trigger" and made that investment, you can still compute what return you would have made if you had. However, since you won't have a ready amount for the future value, you will need to find out what the distributions would have been on the number of shares you would have purchased with $10,000 at the NAV on 11/12/2009. This information may be available on the fund company's web site, or you can contact them for that information.

In the above example, our tool shows the Internal Rate of Return is 13.0%. This annualized rate of return can then be compared to what you would have gotten by staying in cash - probably just a fraction of a percent - or perhaps going into a bond fund.

We computed the IRR for the PIMCO Total Return Fund Instit (PTTRX), our most highly recommended bond fund as of 11/12/2009, and found that it was 6.9%. As you can see then, in this example, you would have been considerably better off by investing in the above stock fund than in PTTRX; but either choice would have been immensely better than staying in cash over the entire period.

Aside from the above mentioned Buy signals, we made several others beginning first in early 2009 up to the most recent ones this past summer, as can be seen by reviewing our Newsletters. In fact, had one acted on our Buy signal for the Small Cap Growth category and invested in the fund we regularly recommended to our readers, the Vanguard Small Cap Growth Index (VISGX), the IRR from the Jan. 31, 2009 date of our signal through this Jan. 30 computes to an annualized 28.1! or over 110% cumulative; a $10,000 investment would have grown to over $21,000 over the nearly 3 year period!

For those who are interested, all of our current signals for the above 10 categories, while not Buys, are Holds which means we still expect investors to show a moderately good outcome when our recommendations are held over the next several years.

Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

Summary: While many investors prefer to invest in specific stock funds (and fund categories) that have previously topped the performance charts, there is now considerable evidence that selecting funds from among categories that show sustained relatively poor performance is a sounder strategy. Unlike Morningstar's "star ratings" which primarily measure degree of high past performance and have been found to be flawed predictors of future performance, using Morningstar's "Buy the Unloved" strategy is a better way to add (or eliminate) funds from a portfolio. But even this approach has its pitfalls. Even better perhaps, is to pick out-of favor categories based on long-term underperformance while avoiding categories that have been in long-term cycles of excessively high performance. Investors should heed the fact that no fund category underperforms or outperforms indefinitely. A good guideline for when reversals of fortune can be expected to occur is after 5 years; by 10 years, a reversal would become quite a high probability event.

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For over 25 years now, I have been analyzing how different categories of funds, including various stock, bond, foreign, and specialized sectors, perform. My goal has been to see if there might be a way to do a little better than the average investor over the longer term.

Early on, I tended to think that spotting and then avoiding downward trends in an investment category was the best way to manage one's investments with a particular emphasis on loss avoidance. In that regard, I suspect I was on a similar wavelength as the majority of fund investors.

Later, however, I repeatedly began to observe that performance of investment categories tended to run in multi-year cycles. Thus, while avoiding downtrends might be good strategy if implemented relatively early on, longer-term downtrends (in the range of a full 5 years or even more) for the various categories of stock funds usually turned out to be the precursors of decent and even considerably above average returns ahead.

Predictions Everywhere But Are They Trustworthy?

But such observations, representing essentially "educated guesses" about the future, no matter how honed by many years of observing the markets, can rightfully only be greeted by a healthy degree of skepticism.

To truly elicit confidence in the face of a world already far too filled with investment predictions, investors might want to consider going beyond most "ordinary" predictions, which are essentially just judgments stemming from past observation. Rather, to prove their worth, predictions might be expected to address two elements:

• First, are they empirically grounded, meaning based on sufficiently numerous prior observations which suggest a subsequent associated outcome? That is, specific past events should be carefully analyzed to determine if there is, in fact, some basis of a consistent relationship between them and future happenings. What boils down to mere guesswork, or speculatively interesting, but as yet statistically unconfirmed hunches should be minimized.
• The above well-grounded, but not yet conclusive, findings should then be subject to further "validity testing" to see how well they can actually predict yet to happen (future) events.

These two elements are indeed the very foundation for a predictive science's most established conclusions and therefore should likewise be part of the methodology for any work that claims to make investment predictions that are most worthy of one's attention. And, that is why I have adopted such a two-pronged approach to arrive at my site's stock fund Model Portfolios which represent an encapsulation of my research-based predictions.

Should You Trust Morningstar "Star Ratings?"

While many investors who come across my website may be unfamiliar with it, the great majority undoubtedly have at least some knowledge of the most widely known fund investor site, morningstar.com. Morningstar is perhaps best of all to millions (even those who have never visited its highly recommended site) for its "star ratings" of funds, which show up on numerous other websites (and in fund marketing promotions) as well. In fact, it has been shown that investors do place a great degree of confidence in putting money into funds that receive either a 5 or 4 star rating from Morningstar, the highest of their ratings, while avoiding the lowest 1 or 2 star funds.

This is in spite of Morningstar's own frank acknowledgement that "the star rating is a grade on past performance. ...We never claim that they predict the future." Since good fund past performance is widely recognized as a relatively poor predictor of good future performance, one must wonder why so many investors seem to gravitate toward the 4 and 5 star funds. (To learn more about the pluses and minuses of Morningstar star rankings, you may want to read this article.)

Morningstar is also the originator of the so-called "Style Box," basically a 3 by 3 grid showing a summary of the category of investments a stock fund emphasizes, taking into account the "growth" vs. "value" orientation as well as a "large-cap" vs. "small-cap" focus.

According to its site, "Morningstar is one of the most recognized and trusted names in the investment industry and serves more than 7.4 million individual investors, 245,000 financial advisors, and 4,200 institutional clients around the world."

Morningstar's "Buy the Unloved" Strategy

Given the proven lack of success in validating its star ratings to foresee future outperformance, it is therefore worth noting that Morningstar has postulated and subsequently attempted to verify the effectiveness of what they hope will be a more predictive strategy called "Buy the Unloved." This strategy has certain underpinnings that appear to add force to my own observation and findings that poorly performing investment categories can wind up being better places to put your money than the best performing ones. (It should be noted that my Model Portfolio was developed totally independently of the Morningstar approach and uses an entirely different methodology.)

Briefly, Morningstar's "Buy the Unloved" entails the following, according to Russel Kinnel, Morningstar's director of mutual fund research:

"Invest in mutual funds from the three equity categories that received the greatest redemptions in the prior year. (Bond funds and asset-allocation funds are excluded.) Then do the same thing the next year and the next year. After three years (or four or five--those time periods work just as well), you start rolling over that original group of funds in the next group of unloved."

In addition, the strategy suggests avoiding those categories that are receiving the greatest inflows from investors. (And for those investors so inclined, one might even "short", i.e. make bets against, such categories using Exchange Traded Funds (ETFs). Note, however, "shorting" should be viewed as a technique only for very aggressive investors. I have never recommended this technique on my site. In fact, currently, there appears to be insufficient evidence available to justify Morningstar's shorting strategy.)

Of course, to follow the "unloved" approach you must have access to data on "flows" in and out of fund categories. Such data, however, is hard for even the most web-savvy of investors to come by.

Given the high regard accorded to Morningstar's research, we find it highly encouraging that they can now report successful forecasting results using their Buy the Unloved method. By using their definition of "unloved" stock fund categories to buy, and then holding 3-5 yrs, their research shows you will outperform the averages. More specifically, examining 17 full years of results, Morningstar's Kinnel reports:

"From the beginning of 1994 to the end of 2010, the unloved earned 308% cumulatively or 9% annualized. That's far better than the loved, which earned 157% cumulatively or 6.1% annualized. The MSCI World Index returned 4.6% annualized, and the S&P 500 returned 8% annualized."

One fascinating aspect of these results is that they are quite comparable to the research reported on my site which also shows that selecting stock fund categories based on those that are "out-of-favor" is an outperforming strategy. However, my results, compiled between 2000 and 2010, while also showing about a 3% outperformance, achieve that outperformance in comparison to the S&P 500 itself, not just between the most favored vs unfavored categories; the comparable S&P 500 comparison for Morningstar data is a mere 1%.

The latter Morningstar article also confirms something we recently pointed out to our readers: The method doesn't work as well when category returns are all bunched together, such as in the last year or two. Thus, there are periods especially during bear markets, when nearly all stock fund categories show poor performance. The practical effect is that no matter which category you previously invested in an attempt to get the best returns, there is little outperformance possible. (See our Oct 2010 Newsletter and below for more on this topic.)

I believe that one conceptual problem with the Morningstar strategy could be that its "unloved" categories are selected based on only one year's data. But fund investors often likely continue to sell funds for far longer than merely a year. If so, this would result in a continued drag on the category's subsequent performance considerably beyond a single year.

Even More "Unloved"

We favor a method that identifies long-term underperformance as a measure of how out-of-favor a category has become, not merely a category that is relatively disliked by investors for just a single year. To the contrary, an out-of-favor category, and therefore in our view, a particularly desirable new investment to make, has performed quite poorly over the last 5 to 10 yrs. Additionally, we usually recommend that it has shown signs of a sustained comeback over the last year. (Note: Our precise method of predicting which investment categories have the best forward-looking potential is proprietary; we report the categories our selection methods identify on our site but do not intend to publish the exact selection rules.)

Highly "Loved" Funds, and Those That Are Slipping

In our methodology, a "loved" category can simply be viewed as one that has a high annualized return over the last 5 or 10 years. (Strong past long-term returns are almost always a sure ticket to category popularity and would suggest the category has likely become overvalued as well.) An in-favor category, just as with an out-of-favor category, often remains so far beyond a single year. If so, when would we finally deem it as an undesirable investment? We consider not only high absolute returns, but also weigh a considerably substantial tapering off in performance as a sign that the category appears to have lost its edge.

All told, I would suggest that my method of identifying popularly favored vs out of favor categories appears to be better matched to the longer-term nature of how categories remain in and out-of favor. Additionally, the act of selecting underperformers is easier for the average investor to implement than delving into fund flows.

The Recent Dry Spell

While my method has proven to have had considerable success since its inception at the start of 2000, a perusal of our 11 year track record will reveal that index-beating Model Portfolio results have not been without some "dry spells." As noted above, outperformance is highly dependent on the availability of outperforming categories. Thus, beginning in the 4th quarter of 2007, the majority of all major categories of stock funds began doing as poorly or worse than the S&P 500 as the market as a whole tanked big time. That being the case, it became extremely unlikely for even previously underperforming categories, or any for that matter, to outperform the Index.

Until early 2009, investors have generally chosen to minimize their risks by investing in the "safest" of stock investments. They also turned to bond funds. As a result of the latter fact, investors who did not put all their "eggs" into just a stock basket were able to make up for a considerable amount of the underperformance that was seen in stocks. Bond funds, while "loved" by investors recently are likely to wind up disappointing investors over the next five years as the 2000-2010 decade's favorable cycle is gradually reversed by expectations of higher interest rates and more inflation.

We anticipate that underperforming stock fund categories, once they escape the influence of the prior decade's period of highly depressed overall stock prices, will once again show the market-beating outperformances seen in the above-referenced table for most of the past 11 years.

Similar Current Recommendations from Both funds-newsletter and Morningstar

Given that both our and Morningstar's recommendations are based on the similar premise that investors should pick fund categories that tend to be trailing the pack rather than leading it, one might expect a fair degree of agreement as to investment recommendations looking forward. And this is indeed the case for recommendations issued this January.

Specifically, both our and the Morningstar method seem to agree that Large Growth is the best category now (see my Jan. Newsletter), and that Large Caps are a better place to be than smaller stocks or emerging markets. The latter category, counter to current public opinion, seems to be the one with the poorest potential for outperformance over the next 3-5 yrs. My site's recently recommended Large Cap funds are Vanguard Growth Index (VIGRX), T. Rowe Price Equity Income (PRFDX),
and Vanguard Large Cap Index (VLACX), and Vanguard Financials ETF (VFH).
The latter fund is within the most underperforming of fund categories by far over
the last 5 years, the Financials. But the Financials have now clearly reversed the
negative 5 year results and have been doing well over the last year.

It should be noted that both Morningstar's 2011 predictions and my model portfolios are designed for investing from a moderately longer-term perspective. Importantly also, neither method implies that stock results will be good/great; it just suggests that relative to the indices, the named categories will do somewhat better. It should be remembered too that the majority of investors do worse than the S&P 500, so just nearly equaling it, or even better, beating it by a small amount is a big accomplishment.

Unfortunately, it appears that most investors think mainly in terms of where the overall market might be headed based on shorter-term considerations when deciding when and where to invest. In simple terms, we are all "wired" to want to avoid losing money. Therefore, when making our decisions, we tend to primarily weigh what we see happening right now and what we fear may happen over perhaps the next 6 months or year. We think this hard-to-break-away-from human tendency is what makes it difficult to follow what this very counterintuitive research suggests.

Additional disclosure: I do have long-term positions in the VIGRX and PRFDX mutual funds mentioned in the article.

Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

1. a previously successful manager being unable to repeat his former success, and/or leaving the fund,
2. investment "style" changes (e.g. no longer focusing on the categories of investments you expected when you purchased it), or
3. even entirely being phased out of existence, or merged with another fund.

Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

Additional disclosure: I have a long-term position in all funds mentioned.