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This article attempts to present the comments section of my recent article concerning the outperformance of Seeking Alpha recommendations in a more concise, user-friendly manner. Competent small investors using Seeking Alpha can significantly outperform institutions by investing in microcap stocks. A highly diversified portfolio with a 60/40 split between microcaps and cash is likely to outperform a 100% large cap portfolio – and do so with much less risk. When the comments section of my article entitled, “Why Seeking Alpha Recommendations Outperform Mutual Funds And Brokerage Analysts” , started to get repetitive, I thought it useful to summarize the questions that came up, as well as my replies. Q. Assuming it was suitable in terms of an investor’s time horizon, risk tolerance, etc., would the following portfolio make sense? 60% in Vanguard Equity Income Fund – VEIPX (large cap value) 7.5% in Vanguard International Explorer Fund – VINEX (international mid/small cap blend) 7.5% in Vanguard Small Cap Value Funds – VISVX , VSIAX , and VBR (U.S. small cap value) 15% in Vanguard Intermediate Term Bond Index Funds – VBIIX , VBILX , BIV , and VICSX 10% in Vanguard Long Term Bond Index Funds – VBLTX and BLV A. It makes a lot more sense to be in the index funds you suggest, rather than in actively managed mutual funds. But if you have the time, skill, and inclination for an active, “do it yourself” approach, the odds are that you will do significantly better over time than with indexing. Aside from whatever alpha you might generate in your taxable accounts, the ability to control the timing of your trades can help you save big bucks through tax minimization and deferral. For a reasonable management fee (1% annually or less for portfolios of $100,000 or more), you can hire a Registered Investment Advisor (RIA) to do these things. If, however, you choose an RIA with too much money under management, you will lose much of the advantage that could come from self-managing your portfolio, since it is more difficult (if not impossible) for large, actively managed portfolios to effectively participate in microcap investing. In 1999, Warren Buffett said: “If I had $10,000 to invest, I would focus on smaller companies because there would be a greater chance that something was overlooked in that arena. The highest rates of return I’ve ever achieved were in the 1950s. I killed the Dow. You ought to see the numbers. But I was investing peanuts then. It’s a huge structural advantage not to have a lot of money. I think I could make you 50% a year on $1 million. No, I know I could. I guarantee that. But you can’t compound $100 million or $1 billion at anything remotely like that rate.” As far as Vanguard is concerned, their index funds are certainly a superior alternative to actively managed mutual funds and brokers’ picks. Due to the enormous magnitude of their assets under management, though, they are at a huge disadvantage vs. competent individual investors and small Registered Investment Advisors (RIAs) in any attempt they might make to generate alpha – especially in the realm of small caps. Q. What steps do you think I should take in order to implement an investment strategy that takes advantage of Seeking Alpha (SA) recommendations? A. To the extent that you can do so in a tax-efficient way, you should sell off any actively managed mutual funds you might own as fast as you can – with the caveat that if you own funds with contingent deferred sales charges, you should check the anniversaries of your purchases and hold off if you can reduce these charges by 1% or so by waiting for a few months. For the time being, the proceeds should go into a combination of cash and index funds in proportions determined by your time horizon and risk tolerance. Then open a discount brokerage account and SLOWLY move money into the SA situations that make sense to you, based upon your research and interactions with other SA contributors. You might also want to take a look at my book ( Data Driven Investing ), which is available free through Google Books – and can also be bought used in hard copy for well under $10. Basically, it’s an overview of the many ways that stocks (especially small caps) become mispriced and offers ways to exploit these market inefficiencies. Q. How do you track the “sells” in the SA articles (I seldom if ever see one)? A. If you click on NYU and Purdue , this will take you to the studies themselves and you will see what their methodologies were. Good sources of “sells” include Citron and Whitney Tilson – they’re not always right, but their work is extremely thorough and they have pretty good batting averages. Q. Isn’t there a massive survivorship bias due to SA people posting picks and then not following up and/or leaving SA? A. The issue you point out of contributor turnover is NOT a source of survivorship bias in the studies’ results. Whether a contributor stayed active or not had no bearing upon the observed results of their recommendations. Each recommendation’s performance was tracked over well-defined periods of time, and if a recommended position was intended to be closed, the opening and closing would be tracked as two totally separate and independent recommendations – rather than as single recommendation that was opened and subsequently withdrawn. Q. Isn’t there too small a data sample to draw firm conclusions, since some well-regarded investors don’t believe that even 80 years of data is enough? A. When it comes to stocks there is no such thing as a 100% firm conclusion as far as predicting what will outperform or underperform. Reliance on quantitative data alone can lead us to draw conclusions that are very wrong. That is why I felt the need to write about qualitative factors behind the numbers. Q. Small and microcap stocks are far more likely to go bankrupt or be delisted. Did you include those in your numbers? A. The analysis done in Data Driven Investing ( pgs. 70-73 ) indicates that the risk of “nanocap” company failure during the 1970-1997 period was well under 2% per year. The riskiest time to buy and hold a portfolio consisting of the 100 smallest cap stocks (minimum $10 million market cap in 2002 dollars) was 1996, as 16 of those companies were no longer around 5 years later – a disappearance rate of 3.2% annually. I no longer have the data at my fingertips, but I’d imagine many of these failures were dotcom bubble-related. Note also that these disappearances would have included any liquidations that were not 100% losses for shareholders. Given that our book was already well over 500 pages long, we didn’t calculate corresponding figures for larger cap companies. Our point, however, was that nanocaps had performance advantage to burn, even after deducting their worst case failure rate. Q. Where is the volatility data on the return-by-market-cap indices you list in your article? A. You can see the annual returns for various market caps by clicking here . Q. Is the tradeoff between risk and return in going 100% microcap what your CFA courses would suggest as optimal? A. So long as it is appropriately diversified in other respects, there’s no good reason why small investors shouldn’t have 100% of their stock exposure in nanocaps and microcaps. A portfolio that is 60% nanocaps and 40% cash is likely to outperform one that is 100% large caps – with far less risk. Robert Haugen’s books used to be (maybe still are) a part of the CFA curriculum. You’ll find that our views are very much the same as far as optimal portfolio construction. His institutional portfolios can not be 100% nanocap, of course, but the application of the alpha-generating factors he cites to a universe including nanocaps would result in very few large cap companies being owned. Q. You have no data on how SA contributors who are laypeople vs. those who are CFA analysts perform. Isn’t this a problem with your thesis? A. I started with the belief that the NYU and Purdue studies were accurate and objective. From there, I looked at the qualitative reasons for the phenomena they found. According to the “wisdom of crowds” theory, the recommendations of uninformed contributors (i.e. random picks) should have an alpha of 0 – because their losing picks’ results should cancel out their winners. What’s left, then, are the picks of informed investors. If one is able to identify and ignore uninformed recommendations, it is logical to believe that significantly greater alpha is attainable (via Seeking Alpha) than what the academics at NYU and Purdue observed. In other words, if 80% of the contributors are uninformed, the split between positive and negative alpha picks might be 60/40 (1/2 of 80% plus 20% = 60% correct, if we assume that informed means correct) – whereas if half the uninformed recommendations are weeded out, the resulting split would be closer to 80/20 (1/2 of 40% plus 60% = 80% correct). The show “Who Wants To Be A Millionaire” provides solid evidence that the “wisdom of crowds” phenomenon can be exploited in a real life situation. When contestants have asked the audience for answers, the audience has been correct 91% of the time (whereas calling a smart friend had only a 65% success rate). See here . Q. Aren’t microcaps and nanocaps too risky due to their illiquidity? A. Lack of liquidity is only a problem if your time horizon is too short or you are inadequately diversified. Q. Here’s what the “NYU study” submitted in a Masters’ program found. What in the world does it say about real world investing? “The study finds that securities in the Micro Capitalization category achieved an average absolute return of +1.75% between the opening price and closing price on the recommendation day for Long recommendations and -3.05% for Short recommendations. Both numbers were significant at the 1% level. During an earlier time period, professional analysts covering U.S. stocks achieved abnormal returns of 1.76% for upgrades and -3.19% for downgrades (Jegadeesh). The study conducts analysis of how securities traded during a six-day window beginning one day before and continuing for five days after recommendation. This study additionally tracks the performance of each security through the 30th, 60th, and 90th trading day.” A. All this says is that stocks tend to go up on the day of buy recommendations and down on the day sell recommendations are made. Its purpose for being mentioned in the study is to allow calculation of what happens during the days that follow. Again, the passage you cite re: +1.75% for SA buys vs. +1.76% for analyst upgrades, along with comparison of short/downgrade performance only considers Day 0 returns. In the real world of investing nobody (other than those seeking to capture the bid/asked spread) buys at the open on Day 0 and sells at the close. Aside from that, one would actually have to buy at the close on Day -1 to realize the entire Day 0 return. In the real world of investing, one would expect that mutual funds would reap whatever benefits might be had from alpha generated by sell-side analysts – either by buying at the open on Day 0 or through interpretation of analyst “body language” prior to the recommendation. Since mutual funds are presumably run by investment professionals who are among the first to learn of sell-side recommendations AND THEY ARE UNABLE TO GENERATE ALPHA, prospects are indeed bleak for average retail investors seeking value added from their brokers’ picks. I make no claim that every SA recommendation is appropriate for everyone in every situation. As the NYU study points out, some subsets of these recommendations have achieved much better performance than others. Rather than rehashing the NYU findings at length, let’s just consider the performance of SA recommendations that combine the first two of the four SA advantages pointed out in my article (i.e. sell-side neglect of microcap stocks and sell-side reluctance to issue sell recommendations). Per the NYU study: “Aggregate results showed Micro Cap [short] recommendations provided impressive and statistically significant returns on the first trading day (-3.92%), between t open and t+4 close (-4.91%), at t+30 (-12.28%), at t+60 (-16.57%), and at t+90 (-17.53%).” According to Table 4, the significance of these figures, in every case, exceeded the 99% level. Q. If you wanted to short a microcap stock, you would have to do it in a taxable account. Therefore, your gains on the trade would be taxed as ordinary income. After paying taxes and commissions, would this still be worthwhile? A. Not that either I or any other SA contributor would recommend it – but what if an investor had followed a strategy of shorting microcaps (as recommended by SA contributors) at t and beginning to cover at t+60? Let’s say you short $1,000 worth of stock at the end of the day the short is recommended (t close). If you cover after 60 trading days (t+60), your pre-tax, pre-commission profit (assuming the average result in the NYU study) would be 16.57% – 3.92% = 12.65% = $126.50. If you pay $10 in round trip commissions and $58.25 in taxes (assuming a 50% rate), you’re left with an after-tax gain of $58.25. If you do this trade four times a year, you’ll make $233.00 after tax – even if you don’t reinvest your profits. So you make 23.3% after tax (46.6% pretax). Not bad. In some ways, this was an overly conservative projection. You could possibly improve on these results by: weeding out recommendations that appear uninformed, and shorting more than $1,000 worth of stock at a time – since doubling the transaction size would halve the drag on returns arising from commissions. We get out of our research and investing (or trading) what we put into it. As I demonstrated with my own personal portfolio in Data Driven Investing (with Fidelity statements provided to satisfy doubters – see here ), it is possible to actively trade microcaps and still have plenty of profits left after commissions and taxes. (I do emphasize, though, that past performance is no guarantee of future results.) Q. I’m retired. I don’t have any business investing in microcaps and nanocaps, do I? A. In my opinion, no stock should be considered unsuitable for retirees purely on the basis of having a small market cap. As I observed previously, a highly diversified portfolio that is 60% nanocaps and 40% cash is likely to outperform one that is 100% large caps – and with far less risk. One may further reduce the risk of owning companies with very small market caps by focusing on those with small (or even negative) enterprise values in proportion to their market caps. (Enterprise Value = Market Cap – Cash & Cash Equivalents + Debt (at market value and including unfunded pension liabilities) + Minority Interest at market value + Preferred Equity at market value.) An example of such a company, which I own personally, is AG&E Holdings (NYSE: WGA ), which was written about by an SA contributor at Seeking Alpha . Not that I would bet the ranch on it, mind you. There are no certainties in the market, but I do believe that a company like WGA has its place in a diversified portfolio – even that of a retiree. Q. Isn’t it possible that the data used in the two studies was unique to the periods observed and, therefore, not predictive of future results? A. We live in an uncertain world, and there’s rarely enough data, time, etc., to eliminate every iota of doubt regarding how the future will unfold. Even when no single sampling gets us to a 99% confidence level – or even 90% – I believe that multiple independent samplings and methodologies supporting the same thesis can have great predictive value. Especially when there are strong qualitative reasons to support that thesis. That is why I thought it would be useful to write an article considering what these factors might be. It seems to me that if you consider a large sample of recommendations en masse, track their performance for one or more well-defined periods, and find that these recommendations outperform, that is pretty compelling evidence that the recommendations, on average, were adding value. If there are strong qualitative reasons why this outperformance should be happening (as there is in the case of Seeking Alpha recommendations), there’s good reason to believe that the value added will persist. Q. Can’t these studies be characterized as sentiment indicators and, based on the history of such indicators, be unlikely to have much predictive value? A. I don’t think it’s appropriate to tar all sentiment indicators with the same brush. I can point to a substantial 51 year body of data supporting the validity of relative strength as a sentiment indicator with valuable predictive power. This subject was covered in Data Driven Investing . Between 1952 and 2002, the 100 stocks in our universe (i.e. stocks with market caps > $10 million in 2002 dollars) with the best prior calendar year performance had a compounded annual return of 13.84%, while the 100 with the worst prior calendar year performance returned only 2.70% compounded. See here . Q. How is it possible to track a portfolio based on SA recommendations if some articles say to buy XYZ and others say to sell it? A. The way academics track a portfolio based on SA recommendations is to consider a large sample of recommendations en masse, then track their performance for one or more well-defined periods. If one contributor says “buy” and another says “sell,” you track them both, even if they cancel each other out. Q. Are you trying to position SA articles as “investment advice”? A. I certainly wouldn’t want to position SA as a source of “investment advice.” True investment advice is given with due consideration to the specific risk tolerance, time horizon, tax situation, etc., of the person to whom it is given. Think of SA, actively managed mutual funds, and brokerage recommendations as being three ponds. The quality of the individual fish in each of these ponds varies greatly. Excellent fish, average fish, and fish that will make you sick reside in each of these ponds to varying degrees. Whereas the SA pond apparently has better fish in it, on average, than the other ponds, it is still helpful to use your judgment before consuming what you catch in it. Editor’s Note: This article covers one or more stocks trading at less than $1 per share and/or with less than a $100 million market cap. Please be aware of the risks associated with these stocks.