Can you beat the market with blended Value Ratios ?

Wednesday, Mar 27 2013 by
11
Can you beat the market with blended Value Ratios

Anyone who has read our book "How to Make Money in Value Stocks" will be well primed in the idea that buying cheap stocks is a strategy that beats the market. This is hardly surprising. If you can buy productive assets on sale you ought to do no worse than even. What is surprising is the extent to which these stocks in general outperform.

Benjamin Graham once said that 'in the short run the market is a voting machine but in the long run it's a weighing machine' snappily illustrating one of the critical ideas for stock market success - that the market over-reacts but eventually corrects itself. But to pick up the extra profit that can be made by exploiting this corrective mechanism, investors have long debated what is meant by 'cheap'.

What is cheap? Different strokes for different folks?

Generalising grossly, most valuation is done by comparing a company's share price against either what it can earn or what it owns. Price/Earnings ratios, Price/Cashflow ratios, Dividend Yield, Earnings Yield, EV/EBITDA ratios etc all aim to judge price against what a company can earn, while Price/Book, Price/Tangible Book, Price/Net current assets, Price/Cash and so on all compare price against what it owns.

Investors are a hugely sectarian bunch and defend their preferred valuation metrics from all comers. But frankly, over the very long term there isn't that much difference in which ratio one prefers to use. The returns to ALL value ratios are highly correlated over the long run and have very similar return profiles.

What one does find though is that during different market cycles, different ratios enjoy their time in the sun. A brief glance at recent history shows that this is so:

  • In the late nineties the Price to Sales ratio was most effective as dotcom companies failed to generate any earnings but flew to the moon.
  • In the recoveries from most bear markets (2002+, 2009+ etc) the biggest bargains judged by asset based measures (P/B, P/C) often massively outperform.
  • Between 2002-2007, EV/EBITDA based metrics were all the rage as the credit bubble grew and private equity sought to buy companies outright.
  • In the current yield deprived times we live in, the dividend yield has been the most successful value metric as investors have thirsted for income.

All this begs the question as to how can one build a perennial strategy based on a single favoured ratio? If…

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Disclaimer:  

As per our Terms of Use, Stockopedia is a financial news & data site, discussion forum and content aggregator. Our site should be used for educational & informational purposes only. We do not provide investment advice, recommendations or views as to whether an investment or strategy is suited to the investment needs of a specific individual. You should make your own decisions and seek independent professional advice before doing so. Remember: Shares can go down as well as up. Past performance is not a guide to future performance & investors may not get back the amount invested.


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14 Comments on this Article show/hide all

marben100 27th Mar '13 1 of 14
2

Whilst I'm not keen on mechanical strategies, I certainly welcome further value metrics that can be used to screen for potentially interesting investments. Adding these sounds like a great idea. I am certainly a fan of quality/value as selection criteria - very much along Buffett lines. Buffett ROIC would be good to see in the "quality" vein.

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Funnymoney 27th Mar '13 2 of 14
1

Ed,

Great article. Re. "keen to build out composite rankings" and with reference to momentum, where is the breakout indicator? All websites have a new highs screen, but nobody has a "New High Since.." screen. This would show the number of days that a stock has been below the previous high when the new high is hit - you can't really follow "How to make Money in Stocks" without it. I have to use a charting package to find the breakouts which really make CANSLIM work. The screen would also have to show the depth of the trough (i.e. if the stock topped at 100 and went to 75 before going back up that would be a 25% drop, which is important because flatter bases are the best.

One thing I noted from a previous edition of WWOWS (which was not in the first edition) is that a lot of the returns for P/S actually came from stocks with a P/S ratio under 0.17, as opposed to the headline figure of 1. Unfortunately he did not show the year by year returns for doing this. It would be interesting to know if the composite indicator ends up giving you, say, P/S of below 0.4.


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dangersimpson 27th Mar '13 3 of 14
1

Hi Ed,

Having a ranking factor for some of the common value, quality & momentum would be a valuable addition imo. You could do it either with a 1-100 rating or a number of standard deviations from the mean of that ratio for all stocks in the market.

In the short term I guess you can use it to implement strategies like the one you describe or the Magic Formula.

It might require a different type of screener interface but the ability to create our own weighted average would be the best because then we can create our own simple models.

So for example if I thought that the Magic Formula worked better with P/FCF rather than EV/EBIT I could create an equal weight model with ROCE & P/FCF and see what it gives.

Thinking out load...you could do it for say the 10-15 most accepted sources of excess return on and have a simple page with these factors and sliders for say simple weightings 1-10 and then the output could be the top and bottom 5% of stocks based on weighted average of the factors.

Of course if this is not possible in the short term then just having the ranking factors available in the screener means we could do it ourselves in excel. Just screen for ranking >0 for the factors we are interested in to get the data for all stocks - export to excel, put in the weighted average calc and sort by the factor.

Cheers,

Danger

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Edward Croft 27th Mar '13 4 of 14
1

In reply to Funnymoney, post #2

Funnymoney - O'Shaughnessy has dramatically changed the content of the book in each edition... it's quite hard to find passages unless you have them all !

Re. Breakouts. It's something I've thought about previously - am just wondering how we could statistically do this. The Turtles just focused on (I think) new 20 day or 55 day highs regardless of context... but certainly O'Neill / CANSLIM looks for those nice flat bases. Hmmm...

So you are thinking...  

  • Day's since last high
  • Percentage below high
  • Depth of low from last high

 

?

 

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Edward Croft 27th Mar '13 5 of 14
1

In reply to dangersimpson, post #3

DS - I do think some of this will be possible in future... but obviously its a question of balancing priorities with demand - there are a lot of potential use cases for creating alternative composite ranks / Magic Formula style rankings (you may have seen the recent Knovy-Marx paper?) ... so we could perhaps put something together in the screener.

Might be some time yet as there are other priorities first - e.g. full historical ratios in the screener ...

Blog: Follow @edcroft on Twitter
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Funnymoney 27th Mar '13 6 of 14

In reply to Edward Croft, post #4

Ed,

Your list is a good one - Day's since last high on the day of the new closing high is the absolute essential. If you think about the price data as if it were in Excel it is quite easy to see that checking for a new high is a very simple formula. You have a second formula in the next column which triggers if a new high is met and gives you the days since the last trigger. I have a formula in Metastock I use which is a bit more complicated and is in Metastock language. O'Neill is about the technical and the fundamental, so 20/55 day highs are not going to replicate his advice. You get huge confidence buying out of a base, but at the moment there is no website which gives you this information. The idea I could get a list of stocks each day which tick all the O'Neill boxes is very exciting - at the moment I have to get the breakouts list and then look each one up to see if it qualifies - sometimes there can be quite a long list.

I would say that if you are going to attack the US market having this facility could bring you a lot of customers.

Could I suggest posting on Elance or similar if your guys are stuck on the coding? Just a thought.

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Aerodynamicist 5th Apr '13 7 of 14

I seem to remember that after the first one or two editions of his book, O;Shaughnessy set up as a fund manager using his own methods and did quite badly. This suggests he is really data mining and saying what would have worked in the past but may not work well in the future. I have not seen his latest edition but if the methods keep changing that is not reassuring..

On Stockopedia screens, if you start at the top with the highest return and work down looking for one you can actually use it is very frustrating. The main faults are 1) Having only one or two stocks qualifying, which is not diversified enough, 2) Selecting tiny stocks with one or two million capitalisation, which have spreads of like 30% and have not been and cannot actually be traded, 3) Not following the guru's recommended screening parameters, like Dreman's four screens where Dreman insists on using medium to large stocks while Stockopedia ignores this and includes many tiny ones, 4) Using distorted figures for value parameters as in the Magic Formula where the returns on investment are so high, nominally, they would have made the fortunes of the owners, if true, but are an accounting error. I had to work right down to O'Higgins' forecast dogs to find one I could believe and was tradeable but that had five insurance companies out of ten stocks and so was also not diversified. The whole system needs a thorough QA and overhaul.

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Mark Carter 5th Apr '13 8 of 14

In reply to Aerodynamicist, post #7

Aero, there's a twist to the tale on O'Shaughnessy that Greenblatt has talked about. It is true that he set up a fund to follow his own method, which subsequently did disastrously. O'Shaughnessy then sold his fund, which ironically turned out to be a turning point, and the fund performed strongly again. Greenblatt used this as a warning that oftentimes mechanical strategies can work badly, and even the inventors themselves can abandon them.

From what I recall, O'Shaughnessy favoured the "Cornerstone Growth" strategy. Although I can't find an index for this specifically, I note on the AAII website that there is a "O'Shaughnessy Small Cap Growth and Value" strategy which has returned a very creditable 18.1% pa, compared with the S&P 500 of 2.6% pa.

It's not all beer and skittles, of course, because if you had chosen "O'Shaughnessy Value", you would have a return of 4.8% pa, which is only a marginal improvement on the indices.

You said: "Magic Formula where the returns on investment are so high, nominally, they would have made the fortunes of the owners, if true, but are an accounting error." I agree completely with that statement. His returns on capital look just too good to be true, and we should probably be skeptical about its validity.

 

It's also disconcerting to hear that O'Shaughnessy tweaks the formulas in his books. This indicates to me that there's a fair chunk of data-mining going on here. A good way of assessing the validity of a mechanical strategy is to perform an "out-of-sample" analysis. In other words, if O'Shaughnessy published his work in 2000, then how those strategies performed subsequently is very illuminating. If they continued to succeed, then there is some reason to have confidence in the strategy. The fact that the strategies were tweaked seems to suggest that luck may have played a significant role.

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Edward Croft 5th Apr '13 9 of 14

In reply to Mark Carter, post #8

I've been looking at the OSAM performance history over the last decade and it's not that bad actually - http://www.osam.com/   Remember - OSAM are running very plain vanilla growth and value strategies.  I think its admirable that they are generally outperforming the market.    It's no  surprise to me either that his value strategies are beating his growth strategies - the market does tend to overpay for growth as we all ought to know.

Personally I think there are many better ways to improve on these mechanical returns - but fascinating nonetheless.

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RobertB73 5th Jul '13 10 of 14
1

I've put together my own composite rankings in the past, weighting each factor differently to get a final score which is then percentile ranked. In addition, I use a Piotroski-like scoring system to rank stocks based on how many of the attributes they score above a certain amount on, e.g score 1 if factor is in top two quartiles of peer group.

Using the two together is interesting as not only do you find stocks with a high composite score, but also ones which meet as many criteria as possible but not in a rigid way like a screen (much like Stockopedia's own splendid checklists!).

It would be brilliant if you could do this via Stockopedia, as exporting data into excel is a pain, especially dealing with blank cells etc.

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Edward Croft 5th Jul '13 11 of 14
1

In reply to RobertB73, post #10

Hi Robert.

There are several approaches. The way we are creating our own Composite Rank / Value Rank / Quality Rank etc is outlined in this help article http://help.stockopedia.co.uk/knowledgebase/articles/184381

What you are talking about is the Piotroski approach of scoring +1 for each metric that passes. We score quite a lot of indicators in this way including the Montier C-Score so we do have to deal with this in computation.

We are thinking about ways that we could open this up to subscribers. Clearly it would require some additional computation which couldn't just be done on the fly. I anticipate that we might some day let subscribers define their own custom rankings which we could backtest and compute daily. It's likely though to be at least a year off.

Trust me though - we do share your ambitions !

Hope that helps,

Ed

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gpmorgan 9th Feb '15 12 of 14

What about listing the  out-performance of each of the major screening items...ie. F-Score, Z-Score, M-Score, C-Score, Gross Profits to Assets, Magic Formula and include your Momentum (broken down to the Earning vs. Price Momentum pieces), Value and Quality scores based on your own back-testing.  Then blend them to create differing characteristic's depending on return expectations, max draw downs, and semi-standard deviations scores so one could fashion a portfolio congruent with their own objectives.

Your site so far exceeds that of any other site I have seen and I am a Financial Professional with over 30+ years of experience.  You have provided more information and background than any other site I have visited and more tools to take advantage of the most recent research.  My hat is off to you and your team.  Keep up the exceptional work.

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Edward Croft 9th Feb '15 13 of 14

In reply to gpmorgan, post #12

Hi gpmorgan, we are working on it ! It is taking time and a lot of dedication to build the backtesting capabilities into the site - especially at a price that is affordable to private investors. Factset et al can do all of the above - but they charge £20k annually plus... so doing it for £200 per year is a challenge :-) All in good time.

Thanks for the very kind words - really appreciated !

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gpmorgan 9th Feb '15 14 of 14

Edward,

Thanks for the quick response. I wasn't so much concerned with the end user (me) being able to do the backtestings, simply you guys doing it in whatever manner you are now and sharing the results with us about how the various factors create different outcomes in term of portfolio characteristic's, based on different combinations...thoughts?

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About Edward Croft

Edward Croft

CEO at Stockopedia where I weave code, prose and investing strategies to help investors beat the stock markets. I've a background in the City and asset management but now am more interested in building great stock selection tools for the use of investors online.   Traditionally investors online have had very poor access to the best statistics, analytics and strategies for the stock market and our aim is to set that straight.  High Quality fundamental information has been prohibitively expensive in the past and often annoyingly dull. People these days don't just want to know the PE Ratio and look at a balance sheet. They expect a layer of interpretation over data, signal from noise and the ability to know at a glance whether a stock is worth investigating or not. All this is possible using great design and the insights gleaned from quantitative research.  Stockopedia is where we try to make it happen ! more »

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