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The Little Book that Still Beats the Market

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Hi all,

Not sure if anyone has read this book but I thought I'd give a rundown and a few comments anyway to see if I can't rouse a bit of constructive brainstorming.

Basic theory:

Basically, Joel GreenBlatt's strategy runs as follows. You sort two list of the entire market. One by P/E and the other by ROC. You filter them by market cap. This should be big enough so the stocks are sufficiently liquid. He recommends anything over about $50m market cap. You then add the rankings of the two lists and sort by the smallest list. The idea being that you get those business that are the best of both worlds. ie, are quality businesses (high ROC) at reasonable prices (low p/e). As far as portfolio management, you simply buy 2-4 stocks every month until you've done so for a year. If then every month after that you re-balance those stocks that you bought 12months ago (doing some tax tweaking in the process) so you conducting rolling purchases.

In principle I love the theory. I've done a fair amount of reading about simple statistical models outperforming more complex expert driven models. (read some of the blogs on greenbackd.com like this and this).

The idea behind this strategy is that it still works even though everyone already knows about it because people in the market have far too short an investment horizon. Which given the current proliferation of "Wiped of the market"-itis I can certainly identify with.

Secondly, most naysayers will argue that the model is far too simple to be useful. The theory rebuts that because you own between 30-50 quality stocks, the diversification mitigates the outliers and that "on average" you'll be buying quality stocks at low prices.

For example, the ROC could be temporary. ROC is a sign that either competition will compete it away or that there are high barriers to entry protecting it. The strategy contends that on average you'll be ahead.

My questions:

I wonder why for a long term strategy they chose a 1 year holding period. Is this to say that on average, stocks will only take a year to correct their misspricing? Furthermore, is this to say that stocks that turn out to be losses are outliers or are they just perpetually undervalued due to market bias?

Secondly, if a stock is still in your top list after 12 months should you stick it out another 12 months and save some brokerage or cut your losses / take profits there and then?

My backtest:

I decided to see how the strategy went since 1989. I (stupidly) didn't include a dividend adjusted return figure but the results were impressive just the same.

Geometric returns (before dividends) of 18.19% p.a is pretty impressive in my books. I'll get back with the revised returns later on.

The strategy under-performed the market in 7 of those 22 years with only 2 instances of 2year consecutive losses (important because you would have to sit through 2 years of losses and stick with it).

It only physically lost money in 5 of the 22 years with one period of consecutive losses over 2 years.

Again, all this may change once I account for dividends. So I'd disregard most of until its updated.
 
Re: The Little Book that Still Beats the Market.

Thanks for posting opulence. I'm very interested in the back test results.
 
Re: The Little Book that Still Beats the Market.

Hi all,

Not sure if anyone has read this book but I thought I'd give a rundown and a few comments anyway to see if I can't rouse a bit of constructive brainstorming.

Basic theory:

Basically, Joel GreenBlatt's strategy runs as follows. You sort two list of the entire market. One by P/E and the other by ROC. You filter them by market cap. This should be big enough so the stocks are sufficiently liquid. He recommends anything over about $50m market cap. You then add the rankings of the two lists and sort by the smallest list. The idea being that you get those business that are the best of both worlds. ie, are quality businesses (high ROC) at reasonable prices (low p/e). As far as portfolio management, you simply buy 2-4 stocks every month until you've done so for a year. If then every month after that you re-balance those stocks that you bought 12months ago (doing some tax tweaking in the process) so you conducting rolling purchases.

In principle I love the theory. I've done a fair amount of reading about simple statistical models outperforming more complex expert driven models. (read some of the blogs on greenbackd.com like this and this).

The idea behind this strategy is that it still works even though everyone already knows about it because people in the market have far too short an investment horizon. Which given the current proliferation of "Wiped of the market"-itis I can certainly identify with.

Secondly, most naysayers will argue that the model is far too simple to be useful. The theory rebuts that because you own between 30-50 quality stocks, the diversification mitigates the outliers and that "on average" you'll be buying quality stocks at low prices.

For example, the ROC could be temporary. ROC is a sign that either competition will compete it away or that there are high barriers to entry protecting it. The strategy contends that on average you'll be ahead.

My questions:

I wonder why for a long term strategy they chose a 1 year holding period. Is this to say that on average, stocks will only take a year to correct their misspricing? Furthermore, is this to say that stocks that turn out to be losses are outliers or are they just perpetually undervalued due to market bias?

Secondly, if a stock is still in your top list after 12 months should you stick it out another 12 months and save some brokerage or cut your losses / take profits there and then?

My backtest:

I decided to see how the strategy went since 1989. I (stupidly) didn't include a dividend adjusted return figure but the results were impressive just the same.

Geometric returns (before dividends) of 18.19% p.a is pretty impressive in my books. I'll get back with the revised returns later on.

The strategy under-performed the market in 7 of those 22 years with only 2 instances of 2year consecutive losses (important because you would have to sit through 2 years of losses and stick with it).

It only physically lost money in 5 of the 22 years with one period of consecutive losses over 2 years.

Again, all this may change once I account for dividends. So I'd disregard most of until its updated.

I read the first book. The one that didn’t have “still’ in the title. Is Greenblatt sense of humour still on display in the update?

From memory GreenBlatt defines return on capital (ROC)as EBIT/(Net Working Capital + Net Fixed assets)

And earnings yields (inverse of P/E) is defined as EBIT/EV

The ranking and selecting companies with the lowest combined score and the holding periods are as I remember it. I think there was further research around holding period and basically the holding period is there because things change and a time frame is the systems control for monitoring that change.

I also remember him saying that he personally uses discretion within in the lowest ranked companies – but he didn't emphasise that, instead he emphasised for those that don’t have the judgment to make discretionary decisions that diversifying across 30-50 or so was adequate to mitigate the inevitable bombs.

There is some sound logic for Greenblatt’s formula when you are using the criteria he defines because

By using EBIT to define profit you are negating financial structure implications.

By using (Net Working Capital + Net Fixed assets) to define capital you are identifying only tangible capital employed in generating the profit.

EBIT/(Net Working Capital + Net Fixed assets) is a measure of economic return and superior to ROE etc…

Because you are using EBIT (pre financial structure) you need to use EV to define the market value.

Ranking by (Net Working Capital + Net Fixed assets) allows you to sort in order of economic return. Ranking by EBIT/EV allows you to sort order of cost – The logic is to buy the best combination of highest economic return for lowest cost – the essence of value investing.

Good foundation for initial scans and I use similar scans all the time. Not sure that I would want to use the results of the scans as my exclusive investment strategy (but I’m a focused rather than diversifying type of investor) but a great way to identify potential prospects for more research.
 
I forgot to mention – that I consider the biggest problem with scans and the main reason I would not invest based solely on the results is the problem of abnormal years.

With a scan for Greenblatt formula using either EBIT or NPAT (as part of ROC and P/E) earnings in a year that are not representative of ‘normal’ earnings will skew the results. Results will be full of companies that have had an abnormally good reported earnings and companies that may be having a temporary off year will appear as expensive. Perhaps within the Greenblatt system the designated holding period is inter-related to earnings volatility whereby the short term earnings momentums(or perception of) may typically persist for another 12 months after the most extreme valuations?

Has anybody ever seen a scanner that is capable of scanning on the average earnings of the past (X) years?
 
I forgot to mention – that I consider the biggest problem with scans and the main reason I would not invest based solely on the results is the problem of abnormal years.

With a scan for Greenblatt formula using either EBIT or NPAT (as part of ROC and P/E) earnings in a year that are not representative of ‘normal’ earnings will skew the results. Results will be full of companies that have had an abnormally good reported earnings and companies that may be having a temporary off year will appear as expensive. Perhaps within the Greenblatt system the designated holding period is inter-related to earnings volatility whereby the short term earnings momentums(or perception of) may typically persist for another 12 months after the most extreme valuations?

Has anybody ever seen a scanner that is capable of scanning on the average earnings of the past (X) years?

That's exactly (although more eloquently put than my post) what my initial reaction was.

I think that both your theories play a roll. The 12month earnings momentum I feel plays a part and also makes sense. It would take time for competitors to realise / implement a new strategy.

But their argument in the book is there is an effective averaging system because you're purchasing 20 or more stocks. So sure, some of those might be just having a good year, but by the same token, some of them may be so cheap that they are on the list despite only mediocre to good returns and then have a blinder the next year instead. They argue that on average you will be fine.

I'm planning on learning some VBA this summer because the last time I backtested is was an extremely long and laborious task in excel and so inflexible that to add features like a yearly average returns will take me a fair bit of time.

The trouble is, (and dare I say it, some technical analyst will come across this too) is how do you pick the parameters for the averaging? whats to say that a 3 year average isn't just fitting our backtest to the results?
 
The trouble is, (and dare I say it, some technical analyst will come across this too) is how do you pick the parameters for the averaging? whats to say that a 3 year average isn't just fitting our backtest to the results?

Good question and one I have never found a generalised answer for. Even more misleading is when you are applying any sort of average when an extrapolation of a statistical valid trend is more appropriate. (ie 5,10,15,20,25 gives an average of 15 but it would be fair to extrapolate 30 as the next in the sequence)

I actually just looked up the links you listed - nice site (to me anyway) Thanks. Have you read James Montier's Value Investing? I suspect you have but if you haven’t- I reckon there's a fair chance it would be right up your alley.


Cheers
 
Has anybody ever seen a scanner that is capable of scanning on the average earnings of the past (X) years?

I haven't seen one, which is why I generally think of scanners as being of limited use (the other reason being that a lot of the data is often wrong). I'm sure a lot of instos are using Capital IQ data and building their own prop scanners that would use long run averages.

Does anyone know if FinAnalysis on Morningstar would have the functionality for to take 10 years worth of NPAT for the entire market? The data is definately there, it's just accessible with any of the scanners I have seen.
 
I haven't seen one, which is why I generally think of scanners as being of limited use (the other reason being that a lot of the data is often wrong). I'm sure a lot of instos are using Capital IQ data and building their own prop scanners that would use long run averages.

Does anyone know if FinAnalysis on Morningstar would have the functionality for to take 10 years worth of NPAT for the entire market? The data is definately there, it's just accessible with any of the scanners I have seen.

If you mean for every company that makes up the market (as opposed to a market average) Yes FinAnalysis can and in some case more than 10 years is available. That is what I do currently, download on mass and then manipulate in Excel to perform my own scans.

McLovin do you know how comprehensive the Capital IQ (Compustat) data for Australia Is? or how widely used it is for Aus companies?
 
If you mean for every company that makes up the market (as opposed to a market average) Yes FinAnalysis can and in some case more than 10 years is available. That is what I do currently, download on mass and then manipulate in Excel to perform my own scans.

Thanks for that, do you have any idea on cost?

McLovin do you know how comprehensive is the Capital Q data for Australia? or how widely used it is?

I know it's generally considered the best data available, including for Australia, but I have only used it a few times myself. I can't help you with how widespread it is in Australia, but if it's used as much here as it is overseas then it would be almost universal. I believe that RM's new service uses C IQ data.
 
Thanks for that, do you have any idea on cost?
A Bucket load - Its marketed as an institutional product.



I know it's generally considered the best data available, including for Australia, but I have only used it a few times myself. I can't help you with how widespread it is in Australia, but if it's used as much here as it is overseas then it would be almost universal. I believe that RM's new service uses C IQ data.
I thought the Morningstar (Finanlysis) database was the most comprehensive for Australia. I'm going to have to research this a bit more - seems Capital IQ only have an institutional offering as well, The interface looks better - the decider for me though will be who has the most comprehensive (breadth and history) data.
 
A Bucket load - Its marketed as an institutional product.

So similar to Capital IQ ($30k+)?

I thought the Morningstar (Finanlysis) database was the most comprehensive for Australia.

I thought the Finanalysis service was just a slightly beef upped version of the Aspect Huntley data which isn't as reliable as the C IQ stuff (although as I alluded to, the few times I've used C IQ has been when I worked overseas so I have limited knowledge of its Australia reliability). I didn't realise it was a full on insto product.
 
I am using FinAnalysis provided through my uni. From that I too made my own scanners. It's a bit crap though because from what I understand CIQ has a point in time feature where as the FinAnalysis I use only has interim and anual figures. When I was running the backtest I did, I had to delete a few companies from each year due to incomplete data. For me it went back to 1989.

I think you're about right on the cost, most of those big data providers look to be somewhere between the 20-30k a year price. I've often wondered if there was scope to start an "internet cafe" style place where people could come and use it but you'd have to control the data pretty strictly or they'd crack the sh**s at you. There is a bloomberg terminal at uni but you can't export to excel only look at the colourful charts and DOS like interface.

I haven't read anything by James Montier but I'm Amazoning it as we speak. I've read both The Intelligent Investor and Security Analysis which is where I got the foundation of my value investing knowledge along with a great book that collated all of Buffet's letters together. His "Superinvestors of Graham and Doddsville" is excellent.


Oh and about the (5,10,15,20,25) bit, therein lies probably the essence of all confusion in the markets. Will it continue or will it mean revert? Is it cyclical or is it structural. I'm sure I'd be a lot richer if I knew the answer to that but safe to say that value investing relies heavily on mean reversion.
 
A Bucket load - Its marketed as an institutional product.



I thought the Morningstar (Finanlysis) database was the most comprehensive for Australia. I'm going to have to research this a bit more - seems Capital IQ only have an institutional offering as well, The interface looks better - the decider for me though will be who has the most comprehensive (breadth and history) data.
How do you get access to Finanalysis for your own personal use if it's a institutional product?
 
I thought the Morningstar (Finanlysis) database was the most comprehensive for Australia. I'm going to have to research this a bit more - seems Capital IQ only have an institutional offering as well, The interface looks better - the decider for me though will be who has the most comprehensive (breadth and history) data.

I'd be interested in hearing which you go with (either here or by PM). I'm going to go with one or the other shortly and I had been leaning toward IQ only because I have some knowledge of it.
 
I am using FinAnalysis provided through my uni. From that I too made my own scanners. It's a bit crap though because from what I understand CIQ has a point in time feature where as the FinAnalysis I use only has interim and anual figures. When I was running the backtest I did, I had to delete a few companies from each year due to incomplete data. For me it went back to 1989.

I think you're about right on the cost, most of those big data providers look to be somewhere between the 20-30k a year price. I've often wondered if there was scope to start an "internet cafe" style place where people could come and use it but you'd have to control the data pretty strictly or they'd crack the sh**s at you. There is a bloomberg terminal at uni but you can't export to excel only look at the colourful charts and DOS like interface.

I haven't read anything by James Montier but I'm Amazoning it as we speak. I've read both The Intelligent Investor and Security Analysis which is where I got the foundation of my value investing knowledge along with a great book that collated all of Buffet's letters together. His "Superinvestors of Graham and Doddsville" is excellent.


Oh and about the (5,10,15,20,25) bit, therein lies probably the essence of all confusion in the markets. Will it continue or will it mean revert? Is it cyclical or is it structural. I'm sure I'd be a lot richer if I knew the answer to that but safe to say that value investing relies heavily on mean reversion.

Opulence,

I thought I might draw your attention to websites below about backtests on the Benjamin Graham criteria. If you have access to the data and the appropriate skills to perform the backtests on the ASX i would be fascinated in the results.

http://www.oldschoolvalue.com/blog/investing-strategy/graham-stock-checklist-screen/

http://www.oldschoolvalue.com/blog/investing-strategy/graham-guru-stock-value-screen/

It is particularly interesting to see how he reduces the criteria to produce the best results. Keep it simple:-

1. An earnings-to-price yield at least twice the AAA bond rate

2. P/E ratio less than 40% of the highest P/E ratio the stock had over the past 5 years

6. Total debt less than book value

7. Current ratio great than 2

The website also some stock screeners with the backtest results.

http://www.oldschoolvalue.com/stock-screener.php

Check out the returns from the turnaround CROIC screener results. :)

My personal view is an investor can make reasonable returns by keeping the strategy as simple as possible. Stick to a simple selection criteria and have at least a dozen holdings. I am interested in finding the most profitable criteria for the ASX.

Cheers

Oddson.
 
It is particularly interesting to see how he reduces the criteria to produce the best results.
Oddson.
My personal view is an investor can make reasonable returns by keeping the strategy as simple as possible. Stick to a simple selection criteria and have at least a dozen holdings. I am interested in finding the most profitable criteria for the ASX.

Cheers

Oddson.

I think you'd definetly like the Greenbakd blog I linked in the original post. Yeah, extra factors are not always going to make your model more profitable. At the risk of getting into econometrics, every time you add a variable your R2 will increase but also widen your standard errors. So you can explain more of what you're looking at but be less sure about your explanation!

Im so keen to learn VBA to drastically speed up my backtesting skills!
 
I think you'd definetly like the Greenbakd blog I linked in the original post. Yeah, extra factors are not always going to make your model more profitable. At the risk of getting into econometrics, every time you add a variable your R2 will increase but also widen your standard errors. So you can explain more of what you're looking at but be less sure about your explanation!

Im so keen to learn VBA to drastically speed up my backtesting skills!

I had a read of the blog in the original post - very interesting reading. Unfortunately i do not have the spare time, money or skill to do the backtesting required to create a profitable investment strategy for the ASX. I do however think about it alot!

I believe that the disciplined application of a simple investment strategy on the ASX can provide the private investor returns per annum around 12 - 20%. As the blog points out, discipline is required over the long term.

My investment strategy idea at the moment:-

1. Earnings yield greater than double the AAA bond yield
2. Debt less than equity
3. Return on capital greater than 12%
4. 5 year revenue growth greater than 10% per year
5. Large management shareholding.

The stock must meet the 5 criteria and you must have a minimum of 12 holdings. I have yet to come up with the when to sell criteria but i suspect it should either be once you made 100% return or 3 years.

Thoughts?

Cheers

Oddson
 
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