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Since we're into March, I'll be running numbers tomorrow looking for March buys. You're all invited to join in (it's been quiet here lately, hopefully hoopmd and I didn't scare everyone away).

On that note, I've been thinking about the criticism levied against the techniques some of us have developed for evaluating the stocks returned by MFI. It even inspired me to go back and re-read the book. Today, as well, I'm going to try and take some time to read through Piotroski's paper. My dad's a CPA who's done exceptionally well in the market, and I'm trying to get him to engage on some of these issues (he's pretty swamped with tax season right now). So the criticism hasn't fallen on deaf ears. If there are problems with some of the ideas that have been developed, I want to know what they are.

So far, this is what I think (feel free to shoot holes).

Greenblatt developed a mechanical investing scheme that is demonstrably effective at beating the market, and producing results that are "quite satisfactory." His method identifies value stocks. His book is written to demonstrate that this method can be applied blindly with very good results. However, in his book (e.g., pg. 69) as well as his lectures, he makes it clear that in applying his method you will buy bad companies if you don't go further. I'm willing to do this in order to avoid costly mistakes, and to improve on his returns (as outrageous as that may sound).

The reason MFI works is that some stocks are beaten down because the market is often irrational. For example, nothing happened this week that warrants KG being written down 20% overall. Either it was overpriced before (which is irrational) or it's underpriced now (which is irrational).

However, over the long haul, the market is efficient. Therefore, if we are to buy a stock that is underpriced (in every respect of the word) we can expect that stock to eventually be fairly priced. So we'll make money buying underpriced stock.

The problem is that the efficiency that provides our expectation of eventual fair value also drives the price of some company's stock down before we can know why. A great example of this occurred when the Challenger exploded. Nearly every NASA vendor's stock was immediately hit. However, within a day or two all but two companies had recovered. Well before the post-mortem had uncovered the actual cause of the explosion, Wall Street had identified the two vendors associated with O-Rings and had punished their stock. Creepy, huh? Likewise...some of the companies identified by MFI deserve to be cheap, and will, ipso fatso, continue to be cheap and even *depreciate* after showing up on the screen. Eventually they will disappear from MFI as their reported fundamentals catch up with their declining market value.

Break-break.

Piotroski has taken a different approach. Using the more traditional screen for value, P looks at the 20% of all companies that are cheapest in terms of price to book. So instead of screening on return of capital/earnings to stock price, P looks at stock price to physical value of the company. He then tries to resolve the problem of the market's efficiency--to determine which of these companies are cheap for irrational reasons, or at least reasons not warranted by what we know from their filings. To do so, he looks at a variety of factors designed to determine the financial health of the company.

Greenblatt's approach is simpler than P's, and performs better overall. However, it is reasonble to believe that P is doing a better job than Greenblatt at determining the financial health of the companies he returns. Whereas Greenblatt only looks at return on capital for the most recent reporting period, P is looking at a number of measures, most of which require positive trends. Greenblatt, however, still sees better results. Why?

My thesis is that Greenblatt's initial cut at the market is so much better than P's, that Greenblatt's results are better than P's even though P's overall analysis is more thorough and effective. In other words, Greenblatt is identifying value much (much) more effectively than P. P is using a value analysis which has not, as Greenblatt states in his book, been particularly valid since the period after the depression when the stock market was feared.

Greenblatt and P are doing two very different things (Greenblatt does some of what P does, but very little). Both are doing what they're doing very, very well (critics must realize that P's results are almost as good as Greenblatt's). Since P's weakness is likely due to his inferior determination of value vis-a-vis Greenblatt, it makes sense to use Greenblatt to determine value and then use Piotroski to determine financial health. This is our basic method. We've (I've) added some other steps, but these steps are just designed to reduce MFI results to a more manageable number, to reduce the number of companies I have to crunch numbers on. If there were a really easy way to do the Piotroski analysis on a large number of companies, I might propose using P on all 100 MFI returns. I just don't want to spend that much effort. (So far, the spreadsheets I've found haven't done an adequate job).

In order to whittle down the list, we've talked about two additional things to look at: the MSN stock scouter rating, and a simple analysis of EBITDA and EPS trends. Here's my take on these two...

1. Stock scouter. According to MSN, this number correlates with stock performance over the next 3-6 months, and is updated daily. It takes into account mostly financial factors, but also looks at technical analysis (which I don't like at all--I think tech analysis is counter to this entire approach) (specifically MSN looks at four areas: fundamentals, valuation, ownership and technical considerations). The rating is 1-10, with 8+ being "market outperform." I think it would be fine to buy a company that was simply "market perform," (4-7) but given that we can find companies that are 8+ within the 100 returned by MFI, I wonder why we would not want to simply stick with 8+ companies? So far, 8+ seems to correlate almost perfectly with the best performing MFI returns. However, I'm a little bit torn here. My gut tells me that anything above about a 5 is probably fine, and that 8+ might be eliminating too many gems. At any rate, this is a very quick and easy number to get--you just plug the ticker into the website. I'm definitely uneasy buying a company that is below 5, given that so many are available for purchase that rate well, and given the correlation we've seen on this board between stock value increases and MSN ratings among MFI stocks.

2. EBITDA and diluted EPS from continuing operations. These are two measures that I've been looking at since December. Greenblatt talks about the need to look at data that describes the core business as much as possible, and both of these take out extraneous factors such as one-time charges, accounting write-offs, etc. What I'm looking for here is yearly improvement over five years. For example, consider ANIK (does anyone know how to post a table???):http://moneycentral.msn.com/investor/invsub/results/statemnt.asp?Symbol=anik

2005 2004 2003 2002 2001
EBITDA 7.2 1.6 -2.1 -6.2 0.1
Diluted EPS from Cont. Operations 0.98 0.08 -0.31 -0.68 0.02

So here, if you can actually read the data, we see that 2001 was better than 2002; however, since 2002 both these metrics have steadily improved. I'd rather the company had been profitable this entire time, and that 2002 had been better than 2001; however, this data gives me good reason to believe that ANIK's management is good at growing sales and controlling costs (EBITDA), while managing their overall process efficiently to return a profit without diluting shareholder's equity (dil EPS, cont ops).

This, also, is very easy to check--so far, much easier than calculating the P Score. And given the choice between buying a company that's trading cheap but that has positive momentum in these two areas, and another that is managed erratically, I think I'd prefer to buy the former.

Finally, before buying any company, it is essential to read through recent company news (at least over the past 6 months) and to actually read all recent SEC filings. The verbiage in these is often more telling than anything you'll find in the press, particularly since we're often dealing with microcaps that are largely below the radar. One of the bennies of developing a more rigorous sreening process is that I'm simply incapable of reading every recent SEC filing and news story on 100 stocks.

Conclusion

Of each of these steps, I see MFI and Piotroski being the two most important (followed very closely by a review of the news and filings). To be honest, I don't know if we are enhancing Greenblatt with Piotroski or enhancing Piotroski with Greenblatt--it's probably more accurate to say that we are enhancing Piotroski with Greenblatt. That will sound like sacrilege to many, but I hope you've taken time to follow my argument.

Adding the MSN rating and a cursory look at EBITDA and EPS trends is merely a way to reduce the volume of detailed analysis that must be accomplished. I think these two brief analyses are reasonable to use and have both been demonstrated to be predictive of stock value performance against MFI returns. So why not use them?

So far, I have two nagging concerns. First of all, it has been noted by stock screening gurus that combining screens is not demonstrably superior to merely using a screen. However, are we really combining screens here? Technically, I think not. Piotroski screens on price to book, then he analyzes the financial health of the companies returned by his screen. We're using a different screen--MFI--for Piotroski's price to book screen. Then we're using Piotroski's method of analyzing the financials (note that P is an accounting prof, whereas Greenblatt is a finance/investment prof). Everyone on this board seems to agree that it is better to look at the financials before you buy, this is just a method of analyzing financials that has been proven effective for value stocks. It could be argued, however, that my technique of rejecting companies without growing EBITDA and EPS amounts to the introduction of a screen. But this could also be seen as a purely fundamental analysis. Anyway...

My second nagging concern is that by only buying healthy looking companies we probably won't buy the outrageously huge winners. This process, as outlined, will likely result in us buying relatively boring stocks (that, so far this year, are only returning, say, 25% per quarter or so...ho hum). I don't know how critical it is to have a few meteoric stocks in the MFI portfolio. In other words, if we remove all the outlyers--the really awesome stocks as well as the horrible dogs--what effect would this have on our expectation of 27% or so per year? There's simply no way to tell without just doing it.

I hope to hit a significant milestone in my portfolio one of these days, hopefully sooner than later, at which I think I could actually afford to simply buy equal amounts of 100 MFI stocks once a year. That way, I think I'd be able to afford to ignore the dogs. Until then, I think I'll continue looking for an efficient way to identify bad companies and eliminate them from the screen results.

TDT
Standing by for flaming arrows...
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Hello TDT,

I believe you have a very valid concern here:

Greenblatt specifically allow you to tweak his formula as long as you start with the top 50-100 MF picks (see page 106). Piotroski's analysis seems like a logical way to further whittle down the list and use MSN StockScouter as one more safety measure.

The concern is that you might (or might not) loose the huge winners that still don't show any good P-fundamentals or some other compelling story and are thus shunned by the market.

I also see P as not quite a screen but a quick fundamentals check that you can use to rank the list MF returns - albeit a check that will give you a rank that everyone is aware of and thus is probably already priced for.

ZiggyD


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I also see P as not quite a screen but a quick fundamentals check that you can use to rank the list MF returns - albeit a check that will give you a rank that everyone is aware of and thus is probably already priced for.

Interesting--I hadn't thought of it that way. Then why does Piotroski's method work at all?
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Hi TDT, I think everything makes sense here... except the msn screener.

I ran it through my portfolio and it knocks stocks I own for all kinds of dumb reasons like it isn't being accumulated lately by wall st and negative earnings disappointments (that could be do to depreciation etc.) and I just find it too finicky to trust for anything. It's interesting to see what it says but I would never have it play any significant part in deciding what stocks I buy.

Maybe it helps on the lower end to make sure the stock isn't a total bomb, but I don't trust it for finding the difference between a 5 and a 10 stock.

Jeremy
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Piotroski works (as I presume you are well aware) because it's more likely that well managed companies with good numbers will do better than poorly managed companies with bad numbers.

Presumably, those "good" companies in the first category are already priced accordingly and that is why I wrote: probably already priced for. The MF is looking for those companies that are out of the probability and are selling for less than their intrinsic market value. Therefore, I see Piotroski as a way of refining the MF and not the other way around as you suggested.
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TDT:
Did you consider using a diferent and/or bigger data base than S&P compustat?.I believe Portfolio 123 use Reuters . The SiPro universe seems big as well.

Also I think the magic formula has no reason to not work in international markets,like Europa.Now,with the much anticipated dollar weakness makes sense.

The main problem I see will all of this is when the whole MFI concept will underperform the market and specially when you will have months of negative returns.It would be awesome to have 25% a quarter,8% a months and 2% a week.But we all know that this is not going to happen in real world.

So when the tought times arrives ,then, it would be dificult to sticks to a strategy that it is not fully backtested and that was cooking and evolving all the time.

I think ,IMHO,that MFI works 90% of it´s potential with the simple parameters shown in the book. It´s also shocking to see the (Dorfman) Robot portfolio
http://www.bloomberg.com/apps/news?pid=10000039&sid=aDfZA.kxtYKk&refer=columnist_dorfman


The Robot has deliver 727% return in 7 years(the S&P has return 13 % in that period) with only a few basic parameters:Market cap bigger than 500,only profitable companies,and equity bigger than debt.Then you take the 10 lowest P/E ratios (or the high earning yields).

Simple.Nice?
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By the way ,that dumb Robot is doing it again.Since the begining of the year(not exactly 1st January) the 10 stocks portfolio are returning 6.7% (2.1% for the S&P) without dividends.Today is up 1.5% (0.5% the S&P).

But is so boring and catatonic........you just buy 10 stocks every 1st January and see them going up and up ..........even you can´t think about (is not good for your bottom line).

Just go fishing,golfing,having, laugh.

The only job (that I know)you get paid to do nothing ,just nothing(not even think).
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This is all good, engaging stuff. I can't say that I really disagree with anyone at this point in time (what a cop out, huh?). I am wondering about the MSN rating at this point too. But am planning to stick with our game plan for now. I'm a bit OCD so I am planning on recalculating my TYD returns and breaking it down by P score like I did about 10 days ago. I hope to do this over the weekend some time. Hope everyone has a good weekend. Brad.
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To post in tabular format, use < PRE > and < / PRE > , but without any spaces between the brackets and slash

2005 2004 2003 2002 2001
EBITDA 7.2 1.6 -2.1 -6.2 0.1

Hope this works!!

Bill
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I see I left a line out:

2005 2004 2003 2002 2001

EBITDA 7.2 1.6 -2.1 -6.2 0.1

Diluted EPS from Cont/ops 0.98 0.08 -0.31 -0.68 0.02

Bill

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Hi TDT -- you make some really good points in your post, particularly:

My second nagging concern is that by only buying healthy looking companies we probably won't buy the outrageously huge winners.

Yes! You are right! I have been working hard myself (on a different type of screen) at manually doing the final sifting, and overall my success rate has been poor with one exception: when the only thing I do is eliminate the real, blatant, obvious, total losers. And I really mean, total complete utter disaster losers. Not a company where debt is pretty high, or margins are lower than you'd like, or inventories are ballooning... but real bad cases like:

1) They are being investigated by the SEC on numerous fronts
2) They have just lost their only customer
3) Their recent healthy-looking financial results were due to an obvious one-time event only (like, they just sold off ALL their useful assets)
4) Numerous recent headlines about the company likely filing Chapter 11
5) The company is actually "winding down" their business and the last year's results were due to selling off their assets

I have watched in despair as one company that I immediately wrote off because its debt was high and book value was negative then proceeded to triple in three weeks; upon (much) closer inspection the assets contributing to book value were carried at much lower than their current value (GAAP rules), and the company was actually pretty healthy.

To juice MFI returns, I think you really only need to avoid the total losers, most of the time.

How to find them?

1) Read the headlines for the last few months for any shocking info (Yahoo's site is good for that, others are too)

2) Pull up the latest 10-K or 10-Q SEC filing (don't be intimidated) and read just the business description. It will say, for example, that the company is winding down its operations.

3) Read the company's press release for its latest earnings announcement and look for things like "revenues have decreased by 80% due mainly to the loss of our most significant customer".

These are pretty simple steps to take. I wouldn't try to run lots of numbers, or even the Piotroski test, etc. I would look just for things in plain sight.

-Mike
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Did you consider using a diferent and/or bigger data base than S&P compustat?.I believe Portfolio 123 use Reuters . The SiPro universe seems big as well.

FYI, I have used SI Pro and am now using S&P Compustat (actually their Research Insight product based on the same database). S&P is way better than SI Pro for quality of data -- no competition. Problem: it costs A LOT, far more than SI Pro. Reuters supplies data for SI Pro but Reuters may have more and better data than it provides to SI Pro. I have not used Reuters data directly so don't know anything about it.

-Mike
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...the only thing I do is eliminate the real, blatant, obvious, total losers.

I think I might know the company you're talking about that tripled in three weeks. I don't know that we can conclude much from that, however, as the MFI doesn't pretend to uncover stocks that are poised for meteoric incrases. In the super-stratospheric sense.

I think you're idea of eliminating the absolute obvious dogs is a reasonable step that anyone should do if at all possible (however, even this is not necessary in order to reap "quite satisfactory" gains). But, unless you're buying (let's say) 42 out of 50 companies returned (assuming you were to find 8 absolute obvious dogs), you're still left with a decision. Which of the remaining non-absolute obvious dogs are you going to buy?

If, at this point, we were to see our list of 42 non-dogs ranked on Piotroski scores I'm very inclined to think we should buy the top x stocks on this list. All I'm left with from your post is to infer that you would rather throw a dart--although I seriously doubt that's what you (or anyone else on this board) would actually do in practice. I suspect that everyone ends up making conscious decisions. Perhaps we would seek an even mix of company sizes, or perhaps spread our portfolio out among different sectors (someone recently mentioned a reluctance to load heavily on tech stocks). Maybe we'll buy stocks from companies we know something about--I regrettably bought Valassis on this basis.

So my point is that I don't really believe that many people are going to randomly pick from the screen after they've taken the time to research all the companies for really scary stuff. As you go through this process, you're bound to end up with some favorites.

My thinking on all this is that I'd rather have an objective way of determining which stocks from the MFI screen I'm going to buy.

The only weaknesses I can come up with for using Piotroski to facilitate this is that he's only good up to about $700m cap, and that he's not backtested using MFI returns. But he is backtested using a very similar basket of stocks, and it's entirely reasonable to expect that P would work for this basket of stocks. It certainly appears that there is a real correlation between P score and appreciation among the MFI stocks.

For the larger stocks, I think we should probably look at whether a company's debt exceeds its equity--if it does, we should eliminate it. Then, we should buy on P/E (assuming we've identified the obvious dogs).

TDT
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All I'm left with from your post is to infer that you would rather throw a dart--although I seriously doubt that's what you (or anyone else on this board) would actually do in practice.

Yes, that is what I'd recommend, unless the investor is a really serious cut above most of us and really understands how to analyze the businesses. Anything else and you are introducing a bias that is untested. If we could figure out how Greenblatt did his back testing, and have all his data available to reproduce it, then we could make some progress on that, but that is going to be pretty close to impossible. (Particularly since the S&P "Point in Time" database, which is really important to have, is likely very expensive.)

The point I'm trying to make in a number of posts here is that fine-tuning or modifying the straight MFI strategy is introducing biases that may sound good theoretically, but run a high risk of being counterproductive. For an example, let me comment on one other point:

For the larger stocks, I think we should probably look at whether a company's debt exceeds its equity--if it does, we should eliminate it.

That is an example that I'd say falls under what I'm trying to say. GAAP equity may be greatly understated (or overstated, if it includes goodwill or intangibles). Real estate purchased decades ago is carried on the books at original purchase price. Remember Eddie Lampert and K-Mart? He saw K-Mart more as a real estate holding company than a retailer and pounced. The books looked just awful and he made an enormous return while K-Mart was obviously one of the companies that would have failed any kind of filter like Piotroski or debt/equity, etc. There are many other such examples.

Here's the problem: if you're looking for a nice clean set of books, indicating very little business risk and little cause for rejection by typical herd-mentality analysts, then it is likely that the price is already where it should be. The highest profits are likely to come from companies that look pretty ugly at first glance. Most of us will not be able to get much deeper than that first glance, and so we will dismiss them. Plus, MFI already takes into account high debt levels in its ROI calculation.

Now, all the above applies to most of us who are typical weekend investors who haven't spent years learning how to value companies and look deeply into their businesses, nor have the time or interest to devote themselves to this. Buffett, Greenblatt, Weitz, Bill Miller, even Tom Gardner and Bill Mann will be able to do a whole lot more analysis and cherry-pick the MFI companies, no doubt at all.

I think I might know the company you're talking about that tripled in three weeks.

Maybe so -- Morgan's Foods, MRFD.OB. Owned 99 KFC and Taco Bell restaurants, most of which were bought about 10 years ago, and carried on the books at original cost. You could have bought the company for a net $50k per restaurant back when I first found them -- what a deal. It didn't last long and I missed the boat by thinking I "knew better" than to invest in a company with negative book value.

-Mike
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TDT,

Forget the nay-sayers! If they want to throw darts then let them throw darts. Let's just do our thing, bro.

Hoop
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Here's the problem: if you're looking for a nice clean set of books, indicating very little business risk and little cause for rejection by typical herd-mentality analysts, then it is likely that the price is already where it should be. The highest profits are likely to come from companies that look pretty ugly at first glance.

That's a perfectly reasonable and generally accepted view. However, it goes against the basic premise of Greenblatt's book (that the market is not efficient vis-a-vis all stocks at all times), and also directly contradicts Piotroski's documented research (when applied to small companies, which are the only companies we propose conducting Piotroski's analysis against).

1. Greenblatt goes to great lengths to demonstrate that his process specifically takes advantage of the inefficiencies of the market (the "herd mentality analysts". Ironically, it then relies on the efficiencies of the market to make money. In fact, and you can correct me if I'm wrong, the ineffiency of the market is the only causal factor mentioned in the book as to why the MFI works.

2. Piotroski's score only correlates with increased returns at a significant level for those companies with little or no analyst coverage, and for which there is low trading volume (you should read the paper if you're going to continue shooting down its application). Piotroski specifically states, and his analysis clearly supports, that "the benefits to financial statement analysis are concentrated in small and medium sized firms, companies with low share turnover and firms with no analyst following." His approach, moreover, is not so much a way of picking stellar winners; but rather, "it convincingly demonstrates that investors can use past historical information to eliminate firms with poor future prospects from a generic high [value] portfolio." Interestingly, he showed that portfolios with high scores had about 2% of their stocks delist for performance-related reasons (e.g., bankruptcy, liquidation) whereas low scores had five times as many. Perhaps what is most groundbreaking about Piotroski's research, and which contradicts what seems to be your underlying premise, is that actual stock performance among value stocks is contrary to common notions of risk/reward. In fact, the evidence presented in the paper shows that, contrary to the street's gut, "the healthiest firms yield both higher returns and stronger subsequent financial performance than the most financially distressed firms." Although there are certainly diamonds in the rough, their collective value does not balance that of their sick cohorts.

I think it's worth eliminating low scoring stocks in order to cut the chances of buying a stock that will delist by 80%.

You seem to be supporting your random-choice view on two points: that you can't trust the books, and that you can't eliminate financially at-risk companies for fear of missing a MRFD.OB.

First, if we can't trust the books then we can't trust MFI.

Secondly, any strategy in existence, other than a completely nondiscriminating indexing strategy, is going to eliminate some stellar companies.

TDT
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You seem to be supporting your random-choice view on two points: that you can't trust the books, and that you can't eliminate financially at-risk companies for fear of missing a MRFD.OB.

Hi TDT -- apologies if this is how my post came out, but that's not at all what I was suggesting.

The great majority of investors, who are likely to suffer from the usual psychological failures of investors, are best off doing a random choice, because it keeps them within the parameters Greenblatt has already tested for. That's point number one.

Number two: I would not support choosing "financially at-risk companies." Nowhere did I say that. I did say "look pretty ugly at first glance." That's entirely different, the difference being seeing the obvious stuff on the surface (what most of us see, including most analysts), and seeing more deeply that there is a solid company underneath. The Piotroski test, to me, looks a little too hard at surface metrics. Even MFI's ROI is, in my opinion, a lot better of an indicator than any of the Piotroski tests.

Number three: I do trust the books! For goodness sakes I don't know where you found anything I said otherwise. However, GAAP reported numbers don't tell the whole story, as in the example of MRFD.OB I gave, as well as K-Mart and others.

Finally, the Piotroski tests are, nothwithstanding any critical comments here, really quite good overall. I have implemented and back tested (using SI Pro historical databases) a Piotroski type test as described in Mauldin's Bull's Eye Investing and overall the results are reasonably good. A score threshold of, for example, 8, finds a good selection of strong gainers but a fairly large number of stocks resulting in major losses as well. It is not infallible by any means.

I have worked on screens for a couple of years in quite some detail (for an example of one that is very successful so far, see http://invest.kleinnet.com/hg ). One thing that I have learned over and over is that any one given screen needs to be built from ground up to look for a specific type of company undergoing some specific dynamic. That can be a turnaround, a profitable growth company, a steady dividend payer, etc., but the bottom line that I have found is that the screen needs to look for only one type of company. Greenblatt has chosen high ROI as his measure of quality. Mixing or combining screens frequently results in companies that pass both screens frequently being oddities, passing both screens by fluke. For example, high ROI may make a company pass MFI, but Piotroski looks for increasing ROA over the prior year (among other tests of course). Increasing ROA is a very different test from a high ROI and not, to my thinking, consistent with the MFI approach. It is a major change in the selection of MFI candidates that is nowhere remotely tested with real data or experience, whereas random selection among the MFI candidates is. That is my warning here.

We can continue this but I am not sure either of us is going to budge much... because we have our own experiences which we probably favor. I hope that I have contributed a little something from my own experience that might be helpful overall.

-Mike
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Hi Mike, FWIW I read your posts with great interest, and although I may not agree with everything you've said I do appreciate you bringing another approach and viewpoint to the converstation here, and hope you will continue to post.

Jeremy
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Forget the nay-sayers! If they want to throw darts then let them throw darts. Let's just do our thing, bro.

Hoop

That's the nice thing about these boards. We can try different methods to hopefully improve the results of the screen. I'll be interested to see the different results.

Ten years from now, if you're independently wealthy and I'm dead, I'll definitely admit your way is superior...chris(still live and kickin'}
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YES! Your praise is exactly what I am looking for.

Maybe, I'll admit your way is better now. Maybe you know something that we do not (hopefully, something other then just words: evidence, data, etc.) That would be a bit more productive here.



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Hi Mike, FWIW I read your posts with great interest, and although I may not agree with everything you've said I do appreciate you bringing another approach and viewpoint to the converstation here, and hope you will continue to post.


Thanks, Jeremy -- I do hope to balance the discussion somewhat, as I believe Greenblatt is pretty clear about using a random selection method unless you have special analysis capabilities. My own experience (with a lot of data and careful back testing) bears that out.

I would read pages 104-107 of the book again. In summary:

99% of all readers should simply stick with the magic formula and pick 20 to 30 stocks at random (he mentions "birth sign" as one way). I think that includes all of us. But... if you think you're in the 1%, then he makes it really clear that you have to be good at analyzing and valuing businesses by estimating normal earnings several years into the future and placing values on businesses (p. 105). He is saying that you should do your own Magic Formula implementation (p. 106) by calculating your own future estimates of ROC and earnings yield, starting with the top 50 or 100 companies from magicformulainvesting.com . If you have a high confidence in your ability to understand the businesses, you can own fewer companies (use less diversification).

See how he structures the instructions on these pages. Number one, pretty much everybody should just do the Magic Formula, picking at random. Number two, if you modify that strategy by applying your own analysis, you should still use the Magic Formula but based on your own projected future estimates of ROC and earnings yield.

This is a very important point that I have tried to describe multiple ways now. Even when Greenblatt says you can mix approaches, he is not saying to use the Magic Formula screen and then another, unrelated, screen. He is saying use the Magic Formula plus a super-Magic Formula, both of which test the same business metrics. That's the key point I am trying to make.

Of course everyone is free to implement this any way they like. However, in a discussion board dedicated to the Magic Formula, it should be made clear that Greenblatt describes a few strategies he thinks will work well, and specifically says (although I haven't found the page in the book at the moment) that anything else moves away from what he has tested, and so basically, you're on your own. It might work, and it might not, and you have no historical basis or data to tell.

-Mike
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Excellent argument. Your post above provides better insight into what you are saying. I don't disagree with what you have said above. You can certainly do well by following the book. We will, in the meantime, continue to look into a few things - prospectively. Brad.
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Your post above provides better insight into what you are saying.

Thanks Brad, sorry it took about 3 tries to get there :-).

-Mike
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He, he. To quote the late, great Jimmy V: "Don't ever give up... don't ever give up."
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Here's my screen beyond Magic Formula lists:
MSN Wizzard: better than industry's % rev. growth, sales growth, net profit margin, D/E. MSN STock Rating 6 or greater, with B for Value and no less than C for ownership.
Yahoo Finance: No higher than 2.5 rating, more cash than debt. From Cash
Flow Statement, increasing Operating Cash during last 2 quarters.
From Schwab Quotes and Research, C or better rating.
From IBD, C or better overall rating and avoid entry point if recent high
volume selling (but do go in on 3 to 4 day reversal of trend if above
signs are positive). Except in rare exceptions, avoid overbought
stocks (grossly, within 1 or 2% of year's high).
From Market Edge, "Good entry points" or Buys and Strong Buys. (Great if
you could learn how they arrive these recommendations.) I do not follow
Market Edge strictly but it helps me decide on a particular stock when
there are conflictive ratings. Market Edge also provides a better
understanding of the entire market which is of help in not so magic
investment. I will know in 3 years if by doing all this I am
improving my odds.



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I questioned you guys a week or so ago, but I've got to say, I've come around a bit. I'm still skeptical, but I'm impressed with a) the amount of research and work you guys have done on this topic and b) the short-term results of adding another filter to MFI stocks. Of course, the real test is whether these results live up to the test of time. If they do, you guys deserve some credit. Hell, if they don't, you guys deserve some credit for the amount of grinding away you've done on this stuff.

I simply let my humility follow Greenblatt to the letter of his book, and fortunately, I'm up 8.5% on my MFI stocks over the past 10 weeks. But if that can be improved with adding the P score to the MFI screen - that's great.

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