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CCC is a small cap (880 mil) with a high RS (96) and has made a high volume breakout to new highs from a 10 week sideways pattern.  My initial stop is at 17.94.

IBD gives this an overall rating of A+, and ranks it 3rd out of 58 in the Computer-Tech Svcs subsector.  It's a big cap, 29,981 mil, with a PSR of 0.99, and an RS of 85. It's currently in a 13 week sideways pattern, with a double top in the 42.00 area. I'll buy this on a high volume breakout above that price. My initial stop will be at 39.09.

ENER, LDK, SOLF, SPWR, just to cite a few examples, all have surged today and in recent days on great volume, some with big gaps, so I've bought calls, in anticipation of a substantial move. So far, I have calls on the Dec ENER 90 and 100 strikes, the Dec LDK 50, and the Dec SOLF 25's.  I'll exit either with my system stops, or on the first sign of a major reversal, or when I can't stand the pressure any longer.

And that's mostly why I bought it. IBD gives it a B+ overall. RS= 85. My initial stop is at 24.94. 

I'm indebted to Covestor member fallond for bringing this to my attention. I couldn'[t resist writing the folks at CXO about their recent report on the use of stops, and to my utter amazement, got a super reply back overnight. Talk about reponsive! Anyway, here's the note I received, and below that, the note that I sent.

Don,

Thanks for your comments.

Please note that the three studies reported in http://www.cxoadvisory.com/blog/external/blog8-11-08/ and http://www.cxoadvisory.com/blog/external/blog8-04-08/ are done by others. Prior to these studies, I had not noticed any formal studies on stop losses for some time. The authors of the studies are generally academics at universities, although I believe Andrew Lo ("When Do Stop-Loss Rules Stop Losses?") is probably well-grounded in real hedge fund activities. I assign highest credibility to the study in which he participated. As noted, this study concludes that “in the presence of momentum and/or regime-switching, stop-loss rules can add value.”

I do not have the resources to test all the permutations you suggest, but I can offer some general observations derived from reviewing hundreds of academic papers and practitioner claims:

 - Academic researchers tend to use somewhat simplified and rigid rules in their studies. These limitations may stem from data availability constraints, programming complexity or lack of theoretical arguments to support refining assumptions (related to a desire to avoid data mining/snooping bias). They sometimes focus on abstract statistical outcomes difficult for practitioners to interpret or implement.

 - Practitioners often rely on small samples and/or poor sampling methods. They tend to be very empirical in approach, incorporating substantial hindsight bias/data mining bias into their analyses (exacerbated by importing data mined rules from others). Many practitioner analyses do a poor job of addressing trading frictions. Some say that what they do is “more art than science.” The “foundational” books by Taleb and Aronson listed in the right margin of CXOadvisory.com are antidotes.

 I’ll take a look at the study you cite. You may be interested in the 30 items on trend following at http://www.cxoadvisory.com/blog/internal/blog-momentum-investing/.

Best regards,

Steve LeCompte

CXO Advisory Group LLC

(And here was my not to CXO)

Dear CXO, Thanks a bunch for your recent research on whether stops work. Although I'm not in a position to challenge the validity of your findings, as presented, I was really surprised at the results. I wonder if I might suggest adding a couple of variables to the mix? I'm a trend follower, with a fully automatic system. It has done fairly well over virtually all test periods, and in actual use (Don't ask about my discipline in sticking to it religiously!:) There are several ingredients that I believe are essential to a good system, and if stops are combined with those, I believe the very same parameters that you tested for would look better if whipsaw trades are filtered out at the onset. For instance: 1. If I only enter a trade on a high volume (say, at least 1 StDev above average) high range (ditto), with my own system, that has made a significant improvement. 2. I got the impression from your article that your stop would be moving up steadily as a move progresses. Does it stall out and go flat during brief consolidations? If not (mine does), I believe some simple rules to enforce that would also greatly improve the score. Years ago, as you probably know, Welles Wilder's Parabolic was all the rage, but a great drawback to it was that it automatically raised the stop into a parabolic curve, without regard to the stock or future's price and volatility. By modifying that, increasing the acceleration factor only if there are new highs (up to the max of .20), and decreasing it for every day that there is not a new high (down to a minimum of 0.00), made a great difference for me and my commodity clients. It greatly improved their score. 3. Throwing in any kind of long term filter also made a great difference. I'd really like to see your test rerun with some of these ideas. Thanks a bunch! PS: have you looked at this super report using a 10 ATR stop?

http://www.blackstarfunds.com/files/Does_trendfollowing_work_on_stocks.pdf

I bought this on a pullback after the recent breakdown in the grains. My initial stop is at 24.43.

I bought this stock based on its high volume high range breakout from a 7 week sideways pattern to new 52 week highs. Cap = 416. PSR = 1.23; EPS = 93;  RS = 98.  IXYS gets an overall rating of A from IBD, and is ranked #7 out of 133 in the Elec-Semiconductor Mfg subsector. My initial stop is at 10.97.

James O’Shaughnessy has carried out the most complete long-term publicly available study on the most commonly followed criteria used to evaluate stocks (in all, 65 criteria or combinations of these).  He based this on the universe of virtually all publicly traded stocks for the period 1951-2003. (1)

I have not been able to find any research that contradicts his findings.  There is, however, much that supports them (see especially David Dreman, Ibbotson & Associates, and Investor’s Business Daily in Bibliography). Before looking at his research, a caveat of sorts: there are a vast array of criteria used to select stocks–some of them actually rational—far more than can be discussed here.  Used singly, or in combination, over one period of time or another, one set of criteria or another will outperform all the others, even including the ones below. This includes your own personal favorite criteria, even if it means buying on the full moon and selling on the new. And apart from the entire subject of selection criteria, keep in mind that Rule One on limiting losses and letting profits run must at all times take precedence. To the extent that I’ve applied these criteria to my own trades, it has paid off. And for all of those trades that I’ve made in violation of these criteria, I’ve paid for it.        

As you read through these criteria, bear in mind, they are to be understood as principles, not rigid preconditions, and not necessarily sufficient alone to justify putting on a particular trade. And they are also for stocks in the aggregate, over time. Although flipping an evenly balanced coin many times will eventually result in about the same number of heads or tails, in the short run, one can still easily come up heads or tails dozens of times in a row.  These criteria provide a slight edge, so do not lead to an equal number of heads and tails over time.  Short term, they will behave very much like the coin. Long term, however, when applied to a series of trades over time, they become very profitable.

In a nutshell, here’s what O’Shaughnessy found: all else being equal,

1)      Size matters more than any other factor: in eight years out of ten, stocks of the smallest companies perform significantly above average, and it follows that the performance of the largest companies is significantly below average.  If the only change you make in your stock selections from now on is to give priority to smaller companies (say, under $500 million capitalization), you are likely to do much better than the overall market.

2)      Value ratios trounce growth measures in seven years out of ten. But the most popular value ratio, the PE (Price/Earnings), is not as significant or reliable as some others are.  The most significant and consistent is the PSR (Price/Sales). If the only change you make in your stock selections is to limit yourself to stocks with low value ratios, in the long run, you are likely to do much better than the overall market.

3)      “Growth” stocks, those with the highest rate of earnings increases over the last 1 to 5 years, in spite of the limitless hype, and against what may seem as obvious as Received Truth, in six years out of ten, perform way below average. If the only change you make in your stock selections is to avoid stocks with the highest rate of earnings increases, you are likely to do much better than the overall market.

4)      Momentum, as defined by RS (relative strength), is extremely important. Stocks that have gone up the most in the last 12 months are more likely to go up further in the next year than almost any other category of stocks.  Those that have fallen the most in the last 12 months are more likely to drop–and further– than any other category of stocks. If the only change you make in your stock selections is to limit yourself to stocks with high relative strength, and avoid those that have fallen the most, you are likely to do much better than the overall market.

5)      A high RS combined with low Value ratios gives the best absolute returns with risk much lower than that of so-called “Growth” stocks.

Taking these points one at a time: Looking at the entire universe of all stocks, year by year, from 1951-2003, the questions that he asked were:

To what extent does capitalization (total value of a company, based on the price per share times the number of shares in existence) matter?  Answer: a great deal.  The largest companies do far worse, and the smallest companies far better. During O’Shaughnessy’s study, $10,000 put into the average of all stocks would have grown to $2,677,557, but $10,000 put into the large caps would only have grown to $1,590,667. At the other extreme, $10,000 put into stocks under $25 million would have grown to $806 million (300 times more than the average stock).  Because the performance of stocks in the ultra small category dwarfs all others, those under $25 million need to be shown with their own chart: [Note: the following charts are based on O’Shaughnessy’s data from the second edition of his book, which shows year by year results]

As you can see, companies under $25 million did so much better than all other categories, that the performance of the 5 largest categories merges into a line near 0.

To see these other categories more clearly, here’s the chart of their performance, without the smallest group:

Overall, those over $500 million did somewhat worse than average, and those defined as “large” performed significantly (41%) worse than average. Definitions of capitalization categories vary considerably.  In his study, “large” was defined as the largest 1/6 of all stocks; currently this is greater than $1.145 billion.  Industry practice, however, is to define large as greater than $5 billion. These include most of the big corporations that you’re familiar with, your “blue chips,” the household names, the GE’s, Exxon’s, GM’s, IBM’s, and more recently, the Intel’s, Nike’s, and Microsoft’s.  However the line is drawn, the stocks (remember, the stock is not the company) of larger companies have far less profit potential. During his 45 year study, the smallest stocks out-performed large stocks in 32 years significantly (by an annual average of 36.3%), and under-performed large caps in the periods from 1969-1973, and 1984-1990 modestly (by an average of 10.7%). So, although it’s true that large caps occasionally modestly outperform small caps, in most years, and long-term, small caps significantly outperform.

Various authors, including O’Shaughnessy and David Dreman, while pointing out the vastly superior record of small caps, nevertheless warn against trading in them because of their illiquidity. This is actually a complete non-issue, since one can easily limit oneself to those that are highly liquid (with hundreds of thousands of shares traded daily). This applies to the smallest of the small, including so-called “penny” stocks, which are those trading under $5, or more generally under $1, depending on who’s defining them.  Penny stocks are widely reputed to be strictly for losers.  This is primarily because many of them have no sales and rarely even trade.  But if you reject all of the ultra small stocks with no liquidity or sales (these are the ones that understandably give penny stocks a bad name), and limit yourself to those traded on the major exchanges, you’re left with a few percent  (still, hundreds) that are highly tradable.  Historically, based on size alone, these have been far more profitable than average, so I don’t hesitate to trade these ultra small stocks, provided that they meet all of my other stringent criteria. The recent move to decimalization of stock prices has narrowed the bid/ask spread substantially, so that the difference between the buy and sell price is commonly about 1% even for the smallest of liquid stocks.   I have found that diversifying can reduce the somewhat greater volatility of small caps to well below that of the NASDAQ, without reducing the benefits that small caps offer.  If you ignore ultra small stocks because “they’re riskier,” you’re acting on a false premise, and throwing out the baby with the bath water.  But if you’re determined to limit yourself to larger and higher priced stocks, and select stocks based on the rest of these criteria, you will still be ahead of the game.

What about Value Ratios?  A value ratio is an objective attempt to assess the value of a stock, by comparing certain numbers on the company’s financial statements with the price of the company’s stock.  The traditional key measures are based on Earnings, Sales, Cash Flow, and Book Value.  More recently, the q ratio has come into use, as the most reliable of these.  Unfortunately, it’s not widely available, except for the market as a whole. There are many others, but these are the key measures–key, because they’ve been found over time to matter the most.  Each ratio is arrived at by dividing the current price of the stock by the annual earnings, sales, cash flow (= income plus depreciation and amortization), or book value (= assets less liabilities) per share. This gives you, respectively, the PE (Price/Earnings) ratio, the PSR (Price/Sales) ratio, the PCF (Price/Cash Flow) ratio, and the PB (Price/Book Value) ratio.  The q ratio is arrived at by dividing the Price by the replacement cost of the entire company and everything in it, in today’s dollars.  It was found by Nobel prize winner James Tobin to be significantly more accurate than the far more popular PE ratio in determining whether the market or a given stock is over or under valued.  When value ratios are low, this is an objective way of saying that, with regards to the earnings, sales, cash flow, etc., the stock is cheap.

1.      To what extent do low value ratios matter? (Traditionally, “low” means Price/Earnings, PE < 20; Price/Book, PB < 1.0; Price/Cash Flow, PCF < 1.0; Price/Sales Ratio, PSR < 1.0)  Answer: Overall, especially in conjunction with high Relative Strength, a great deal. Individually, however, they vary.  Although the PE ratio is the most popular of these, it is not actually the most significant.  Historically, a PE over 20 has been considered high. Under 10 is low.  The long-term average of the market is 13. Although it has topped out a bit over 20 at previous bull market highs, in the final stages of the 90’s bull market, the biggest winners had an average PE of 45 before their last big advance.  They reached an average of around 85 at the top.  On the other hand, they also fell the hardest when it was over. The NASDAQ, which is home to the majority of high tech stocks, dropped over 75% from its March 2000 high to its recent low.  The Dow, which is comprised of blue chips, has fallen 30%. Small caps with low value ratios have dropped minimally or even risen during this period.  A low PB (price/book) or PCF (price/cash flow), is even more important; a low PSR (price/sales/ratio) is extremely important; but the much touted high ROE ratio (return on equity) was found by O’Shaughnessy to have little or no value.  A stock (or mutual fund) with low value ratios may properly be thought of as cheap, all else being equal.  Cheapness is not a measure of price level, but of low value ratios. A $50 stock with low value ratios is “cheaper” than a penny stock with high ratios.  But don’t jump into a stock or mutual fund just because it’s cheap; stocks can be cheap for years, are often cheap for good reasons, and may well be on their way to getting much cheaper.

2.      To what extent does accelerating earnings growth, the key component in “growth” stocks, matter? Answer: Contrary to what would seem obvious, stocks that have had the greatest acceleration in earnings growth in the preceding 1-5 years have been unprofitable in almost all subsequent years, and an investment in these would have grown only from one fifth to one half as much as throwing darts.  It may defy all reason, but the truth is that prices of such stocks, at any given point in time, have already been bid up far beyond any price that their super earnings can justify.  In one long-term study, covering the period 1951 to 1997, it was found that 96.4% of growth companies were unable to sustain earnings growth past five years (2). In a related study, it has been calculated that “a strategy based on buying the 20% of companies with the highest actual or expected growth rates, while selling short those with the lowest, consistently would have underperformed the broad market by five percentage points a year since 1980.” (3) In spite of IBD’s claim that earnings are the best predictor of stocks prices, “there is no substantial …long-term historical relationship between corporate profits and stock prices.”(4)

3.      To what extent do momentum ratios matter? (momentum refers to how fast a stock is moving) Answer: more than almost any other ratio! It is well known that stocks spend most of the time (75-90%) fluctuating in what is essentially a sideways direction.  If there was only some way to know when a trend is beginning, or is underway.  There is (apart from charting concepts)!  Relative Strength (RS) measures the degree to which a stock has outperformed all other stocks in the last 12 months; a 99 is the highest score possible, and means that a stock has risen more (or fallen less) than 99% of all other stocks. A special note on cheapness: stocks that have fallen the most in the last 12 months, relative to all other stocks, therefore have the lowest RS ratios (lowest is a 1).  These are the least likely to go up in the following 12 months. In 45 years, $10,000 put into the lowest RS stocks each year would have grown to $43,040, vs. $2,677,557 throwing darts.  Over 1500 of the most widely hyped stocks of the 90’s dropped over 90%.  The majority of such stocks never fully recover.  It’s undoubtedly comforting to believe that they will recover, because they’re “good” companies, but remember, almost all of the companies that have ever existed, at some point in time have ceased to exist.  As IBD often points out, the opportunity has always been with new companies whose stocks are hitting new highs for the first time ever, not with fallen giants. The well publicized upward march of the major stock indexes over the decades, which is a key selling tool of brokers, is a major and unconscionable misrepresentation. This is true for a couple of reasons.  First, the indexes are shown in nominal terms (their gains are shown in points or dollars), rather than real ones (adjusted for inflation). It’s easier, and strongly works to the advantage of the brokerage industry to keep it that way.  Nevertheless, if you do not factor in the actual purchasing power of those gains, you unfortunately fail to see their real value after inflation. For example, the consumer price index has risen 6 fold since 1960, and 17 times since 1913.  Divide the current market by 6 or 17, respectively, to see how much it has really gained in terms of what you can buy with those gains (5). Second, putting the indexes in nominal terms masks the real loss that occurs during the prolonged down markets, and creates the impression of steady decent gains—the fabled 10% or so that is so often mentioned, as if it’s virtually a birth right (6). Gains of 10% are anything but assured, and are far from steady.  Furthermore, the indexes are composed of constantly changing stocks, the newest and the strongest. Those that have gone under are continuously deleted from the indexes. You are only seeing the survivors and the newcomers.  The  Dow itself only has one of its original stocks (GE).  The NASD, which is home to about 4000 stocks, delisted (mostly for financial reasons) 200 companies in 1996; 250 in 1997; 596 in 1998, 440 in 1999, and 630 more in the next two years.  From 1996-2001, NASD delisted 2116 stocks. During the great bull market of the 90’s, every year over half of all stocks went down.  In the last up year of the 90’s bull market (1999), 90% of all stocks went down.  That was before the top.  The real story of stocks is that new stocks often go up for a while, many disappear off the face of the earth, and all surviving stocks eventually go down.

4.      Combining low value ratios with high momentum (a high RS) gives the best increase with below average risk.  The reasoning behind this is: a) a low value ratio means that the stock is cheap, as determined by the relationship between its price and its sales, earnings, book value, or cash flow (for instance, sales are high, but the price doesn’t yet reflect this), and b) a high RS (in the 90’s), especially with a stock making a 52-week high on a great increase in volume (at least 100%; better yet, a few hundred percent), means that large traders anticipate that this stock will significantly outperform other stocks, and are placing real money on it.  (This is when you buy a “cheap” stock!)

EDGE: Some of the great traders interviewed by Jack Schwager speak of the necessity of having an “edge.”  The Roulette wheel has a small but persistent edge.  Slot machines steadily take about 2% of every dollar.  Value ratios accomplish the same thing in a slow but steady manner.  All of the studies done on them show that long term, stocks with low value ratios or high RS (relative strength) do a few percent better per year than average. This may not sound like much of an edge, but over time, it becomes immense.

$10,000 put into stocks with the lowest PE’s (Price/Earnings ratios) would have grown to $5,159,955, which is about double the All Stocks average. High PE’s are far worse: $10,000 put into stocks with the highest PE’s would have grown to $1,087,361, about 60% less than would have been possible by throwing darts.  So: if you were to use PE alone, lower is better than higher, but PE is not the best measure by itself, because it’s so easy for accountants to rig the earnings portion of this ratio. [But note further below the value of combining a low PE with a high RS].  Just to keep things in perspective, the low PE category had average annual returns of 17.33%, vs. 14.97% for the average of all stocks.  Although this is only a difference of 2.36% annually, long term the bottom line is approximately double that of throwing darts.

$10,000 put into stocks with the lowest PCF’s (Price/Cash Flow ratios) would have grown to $7,142,991, which is 2.67 times the All Stocks average.  Stocks with the lowest PCF had average annual returns of 18.08%, vs. 14.97% for the average stock, an edge of 3.11% annually. 

$10,000 put into stocks with the lowest PB’s (Price/Book ratios) would have grown to $8,670,540, which is more than triple the All Stocks average. Stocks with the lowest PB’s had average annual returns of 18.86%, vs. 14.97% for the average stock, an edge of 3.89% annually. 

$10,000 put into stocks with the lowest PSR’s (Price/Sales ratios) would have grown to $14,910,164, which is over 5 times the All Stocks average. Stocks with the lowest PSR’s had average annual returns of 19.85%, vs. 14.97% for the average stock, an edge of 4.88% annually. 

In case it’s of interest, here’s the breakdown of PSR’s, by deciles, for the 8210 stocks searchable through my broker’s website, as of 8/11/08:

10% of all stocks have a PSR under      0.29

20% have a PSR under                         0.60

30% have a PSR under                         0.94

40% have a PSR under                         1.42

50% have a PSR under                         2.25

60% have a PSR under                         4.15

70% have a PSR under                       74.00

71.6  % have a PSR under            15782.40

28.4 % have no PSR. Whatever the reason, I treat those as if they are the highest.        

Since the PSR is far and away the single most important value ratio, it might be interesting to see just how much difference it makes long term: Here are the details from O’Shaughnessy:

Decile (1 = lowest PSR = best) During his 45 year study:

1                      $10,000  grew to $14,910,164

2                      $10,000  grew to $  9,737,147

3                      $10,000  grew to $  9,646,689

4                      $10,000  grew to $  6,924,259

5                      $10,000  grew to $  3,505,492

6                      $10,000  grew to $  2,629,117

7                      $10,000  grew to $  1,406,604

8                      $10,000  grew to $     709,086

9                      $10,000  grew to $     291,074

10                  $10,000  grew to $       94,437

High PSR’s are toxic.  Low PSR’s are less risky and have infinitely more upside potential. Fortunately, there are thousands of stocks with low PSR’s, high tech included, so there’s no need to sacrifice standards to have a shot at stocks with what might sound like ultra high potential.  On any given day, there are some 3000 stocks in the lowest 3 deciles above.  Over the 45-year study, $10,000 in these would have increased some 1000 times in value.

(Special note for short sellers: A high PSR is one of the most profitable of all ratios; stocks with the highest PSR’s are likely to drop further than almost any other category of stocks. Therefore, if you’re shorting the market, a high PSR is an essential ingredient.) 

I'm in the middle of updating my notes for my next chapter, on the key research on stock selection criteria, and although I've found a great deal of research on Capitalization, PE, PB, PCF, PSR, RS, and earnings gains, I'm coming up short on any long term (decades as a minimum) research specifically on the validity of the EPS or PEG ratios.  It's practically impossible to read any analysis of a stock, without seeing these trotted out, as if they're received truth. IBD, for instance, places EPS right up there with the RS in terms of its importance.  But since their claims for its importance are essentially only anecdotal, citing their claims in support of the EPS would fall into the Appeal to Authority fallacy.

Does anyone know of any long term studies on the validity of these particular pieces?  Thanks! Don

I reentered this today based on my system's buy signal. My initial stop is at 67.57.