Thanks for the reply, Boggo.
...Been around too long to have any sensitivity about that. But I do think your amended comment reads better. I don't like when opinion or experience is stated as fact for everyone.
...Mate, firstly - that's just an assumption, is it not?
My friendly challenge to you is to answer what a failed company / companies has to do with a thread about the systematic use of fundamental data?
...I recently selected DSH for a portfolio in a thread that craft started. That portfolio, like the magic formula portfolio posted in this thread is also performing just as terribly.
...I recently posted in a thread, in answer to a query on fundamental clues to bankruptcy risk, that a very poor price performance (relative to market) is one of the potential signs.
Losing three months gains in a week? Wouldn't be unheard of at all for me. I was looking like being up around 10% for the past 3 months since mid-May in my 'real-life' portfolio. I'm suddenly back down to just under 3%. Nothing unusual.
Another example: there was a poster in the thread I mention (that craft started) who was incredulous and worried that I'd actually bought DSH. It's a 25 stock portfolio! Sorry, but I don't consider a 4% portfolio drop a disaster at all! I don't need a company to go bust for that to happen, anyway!
Comment: I've mentioned in (yet another) thread (I don't normally enter the F/A or T/A 'debate')....that I don't see stock analysis as being under a "F/A" or "T/A" analysis umbrella. It's either a qualitative assessment or a quantitative assessment, in my book. The data inputs can be price, volume, financial data, media data or whatever. I agree - there's a whole slew of opinion formed on stocks based on subjective analysis of financial data. Some good and some bad. Same thing for "T/A." There's good and there's bad subjective analysis of stocks based on stock price or price/volume charts.
Anyone who reads my posts would be in no doubt that I have no time for either, in my own investing.
Most liked posts in thread: Magic Formula on the ASX
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Second year update.
This time we did an 'All Stocks' and also an ASX200 version (the 'All Stocks' would relate closest to the previous year).
In the All Stock portfolio: 7 out of 10 trades were profitable. The average gain of the winners was 29.5% (there were no runaways, max was JIN at 77.5%). The 3 losers lost 9,12 and 20%
The overall price return was 16.6%
Dividend payments (interestingly, 9 out of the 10 stocks paid a div, with 8 of those 9 at 100% franking) resulted in an additional 4.77%
Total return for the 12 months:
In the ASX200 portfolio: 1 stock (SAI) was bought out half-way through the year (was not replaced). 7 out of the 10 trades were profitable. The average gain of the winners was 26.8% (again no runaways, max was MND at 65.5%). The 3 losers lost 4.3% (which was lost in the last week - wasn't sold the week prior with the other losers as it was sitting on a win) along with 8 and 26.2%
The overall price return was 14.9%
Dividend payments (paid by all 10 companies with 9 out of 10 being fully franked - not as surprising, as this is the ASX200) resulted in an additional 4.43%
Total return for the 12 months:
The 'market' (this time I'll just use ASX300 / ASX300 accumulation) did around 2.5% and 7%
Comments for fun:
- I was surprised / amused that the 2 portfolios (All Stocks and ASX200) produced virtually identical results.
- The previous year had 2 takeovers, this year had 1 (only in the ASX200)
- FLT (Flight Centre) was common to both All Stocks and ASX200 portfolio and gained 33%
- PRT and MND were on the first year's list...both had lost about 17%. PRT remained in the All Stock portfolio and gained 30% this year; MND was in the ASX200 portfolio and gained 65% this year.
- Dividends are important; this year accounting for almost a quarter of the return, same as last year
Not sure if @Alan5056 is still about. After 2 years of posting between mid-2015 and mid-2017 (with a total return CAGR of 20.5% - beating the market and no doubt most traders and fund managers), I didn't bother posting selections for 2017/18 as I didn't feel there was any interest or demand - which was no problem, as I don't follow this system in my own plan. It was just for interest.
Anyway - for whatever reason I came up with the selections (as I see them) for 2018/19. Possibly due to the somewhat revived interest in individual stocks and the others running excellent trading threads etc.
This time no split between ASX200 and all cap ranges etc. Just the top 30 like Greenblatt mentioned in his book.
Will follow the Top 10 (to keep in line with previous 2 years) as well the as 30 as a group (31 actually - yes, I realised that!)
I might have to bother doing the selections for 12 months ago now, hmmm...not sure. Anyway, here's the current lot.
Last edited: Jul 15, 2018
Thereis an excellent bunch of writing about the Magic Formula in "Quantitative Value", I recommend reading it, if you are relying on the Magic Formula!
The main issue with this methodology is that it ranks value and quality equally, which generally results in portfolios that overpay for quality.
A better solution (and that adopted by the authors of Quantitative Value) is to split the universe into deciles based on EBIT/TEV, select the value decile and then split your selection into high quality and low quality halves.
The returns on High Quality Value are better than Low Quality Value, Value and Magic Formula.
Here are all the analysis on Magic Formula done by the QVAL guys: http://blog.alphaarchitect.com/tag/magic-formula/
The book also has some really interesting observations (not necessarily negative) about this methodology and the general issue of mistaking the ceiling of a methodology for its floor.
Thanks sinner, I'm familiar with that work, and prior to the QV book coming out had concluded that you are better off with value first, then quality, as opposed to an equal split (you could see that from looking at Novy-Marx' data, which one of the co-authors of QV mentioned at the time as well). That's if you're using quality at all. I've previously mentioned that I'm quietly cautious on quality for several reasons - one of the co-authors of the QV book doesn't like to use it at all.
I was crook as a dog the other day and grabbed "The Little Book that Beats the Market" off the shelf for a quick read in bed with a cuppa (Greenblatt has a very entertaining writing style)...and that's what reminded me of this approach.
They (NCAV, MF, QV etc) are not my investment plan, as it were - I just find looking at stuff to be fun.
In my view, at the end of the day they are slightly different approaches that will produce slightly different numbers. Most of these things are variations on a theme, to various degrees. Any quality measure combined with any value measure (equal weighted) gives you an MF type of approach (e.g. Price to Book with Gross Profits to Assets). Or, for example, the Piotroski approach written about 13 years ago (quintile on P/B first, then a top F Score) is the exact same theme going on with QV. And, in fact, compares quite favourably with the more complex QV.
I've had different views (as we all do, as we keep thinking about these things). It all depends on what the investor is trying to achieve. For example: some investors might like to start with 'quality' (however they define it). They might find a quantitative sort on quality measures to be an initial, very useful cull of the market...to then go on and do their own intrinsic value calcs on. Certainly not my approach - but entirely valid. Greenblatt talks about this in relation to the Magic Formula (and apparently it's what he actually did / does in his funds). It depends what the investor is trying to achieve (which of course, is not always the highest CAGR, as much as we'd like it).
Anyway, it's all food for thought and I really appreciate the input. I also completely agree with you that QV is a wonderful summary of - just that: a quantitative approach to value, and I regard the work extremely highly, as you obviously do. As a matter of fact, I started putting it together on the ASX a couple years back and then abandoned it. Might have to look at it again sometime.
Awesome post, systematic, it's obvious my cautionary note was not required for you!
I also noticed how well the Piotroski/FS_SCORE + P/B value decile performed (I posted this link in another thread recently but it's even more relevant here) http://blog.alphaarchitect.com/2015...ple-methods-to-improve-the-piotroski-f-score/ with CAGR and maxDD approaching that of QV for a lot less effort.
Thanks for reminding me about this as I had some research to do on P/B based on this regression model which works off P/B and RoE, which for me was a completely different way of looking at the same data http://epchan.blogspot.com.au/2014/02/fundamental-factors-revisited-with.html .
I had also considered setting up QVAL portfolio for the ASX, same as you, but in the end I didn't mostly because there is something about the logits used in the book which rubs me the wrong way (same reason I don't like Altman z score). So in the end I adopted a much simpler model (read, robust) influenced by the work of Eric Falkensteins DefProb (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1103404) to replace the logits and use that as part of my ASX portfolio selection.
Nice to see some people with similar thoughts!
Most of my research has shown that roe outperforms roic (roce also beats roic for that matter). I think quality tends to mean revert so filtering according to value is more important. Instead of ranking on quality using a straight roe > 0 filter will work just as well if not better. However this can be problematic on the asx since we are not very well diversified.
I am currently holding 3 of your stocks from your list - but I tend to focus on small caps on the asx (less efficiently priced and room to grow). I think there are several stocks that would rank higher than those listed so im curious about where you are getting your data from?
What I have been thinking about recently is front running these quantitative investing funds. Most of their strategies are fairly simple and if they were to ever get a decent amount of assets under management you would only need to figure out the holding period to pick them off.
I'm an investor because it's the optimal method for me, all the turnover is handled inside the funds! But if anything, I wish they had a longer holding period, more like allocate 20% of capital each to 5 portfolios (generating a new one and dropping the oldest each year) with 5 year holding period.
Given mention of Novy-Marx, various profitability measures, Piotrosky and interaction with value....
Might be worth reviewing this:
Of note, these guys reckon there is no premium to quality in a univariate sense. Further, the quality measures which are presently popular are likely data snooped. However, they seem to think that conditioning value by quality produces good stuff. ... Which suggests there is mispricing of value stocks that can be picked up via quality metrics.
Asness finds that Quality Minus Junk does produce a premium.
Arnott (of RAFI: Research Affiliates Fundamental Index per above) and Asness used to be good buddies, but not any more.
This thread is fantastic. It is a treat to find highly data rational people coalescing.
Question: Do you think that Quant managers and those with the simple resources to replicate these measures in a day or two, who read this research and more, will not be front running you as you try to front run them? I express some skepticism when there is an argument based on non-linear interaction and mispricing is asserted.
b) The MF uses an earnings yield, not an equity yield just out of interest. But to your point re: a company's past performance...what else is there? No one has a company's future performance, so the only other alternative would be to be, "forward looking" (as you put it) with the company's performance. Well that's just another topic altogether, and a dangerous road to travel, in my opinion. That domain is for super investors, not people like me. Of course, some pull it off (Buffett, ASF's own, craft). I can't punt on myself being that good.
I agree, there's so much data snooping going on with the latest and greatest factors. My take on quality thus far has been to ignore it (due to similar sentiment as above). The only use for quality that I see is in picking up genuine bargains, or mispricings, as you mention (value first, then quality). It just makes sense, there's data to show it, and I'm all for reducing volatility a little. So, I've been looking at it a bit...but even then I still remain cautious - as I lean a little more toward the school of thought that says: any factor you decide to include in your model, should be a stand-alone factor. Actually, Novy-Marx just recently had a paper on exactly that. I'm still definitely undecided at the moment whether to include it, so it sits on the sidelines for now - although I look at it a lot.
I agree about the quality issues you mentioned re snooping and lack of premium. My main concern is the introduction of a variable highly influenced by cyclical factors. If you read the QV book they have a decent (although IMHO not perfect) method to address this, they take the 8 year geometric average of ROA (example). The geometric average and 8 year both underweight the cyclical portion.
Re lack of premium, I think it is important to recognise (a realisation I am only just coming to), for example RoE based portfolio formation might not produce a portfolio of outperforming stocks but those stocks are actually less likely to experience significant drawdown relative to the benchmark (i.e. high correlation with low beta)! Also interesting to note, if you look at the epchan link I posted, that there is starting to find evidence that while "quality" doesn't necessarily influence returns systematically across a universe of stocks, it does influence the future returns of single names along with value metrics. My guess is basically this is capturing the business/profit cycle in a way that value measures never can.
I'm a FA investor and weighted towards income (dividend) with the aim of holding long term, and I don't use a precise model, which is what you are looking for, but, I do look at a couple of things:
- EPS growth. Have earnings over the past few half yearly reports been growing (backward looking but trend seeking)?
- Forecast EPS growth. For what they are worth, consensus targets as provided by Thompson Reuters or Morningstar. Is the positive EPS trend forecast to continue? Where there are less than five analysts making up the consensus forecast, the fewer the number of analysts in the forecast the less weight you give to the forecast.
Personally, if i was using the magic formula model (and I had never hear of it until this thread), I would consider running the results of the earnings yield filter through something that filters for earnings growth trend at least. But I am not a t/a investor, and I don't even know how to back test or run monte carlo simulations, etc.
That's all cool, tinhat. Differences are what make the market!
My only thought to add is that everything I've read has put me off looking at growth - particular longer term growth. A little bit of recent growth is okay.
Re: using forecasts for trend (as opposed to accurate forecasts) - I think that's fair enough. Even David Dreman thought that was okay. I just don't think it's necessary to use. One example summarised from the studies I've read: which performs better, a P/E using trailing earnings or a P/E using forecast earnings (or even a 50/50 blend?). The trailing earnings win. Forecasting earnings trends and looking for past growth trends misses out on mean reversion of earnings. That's just my take, anyway. I like that we all come at this differently!
IDOG for example has 1 bill aum and purchases 50 stock according to yield annually. This leads to 20 mill buying pressure within a short period of time. Might not seem like much for big caps but there are less liquid stocks where this figure is very close to the daily average trading volume.
"The Fund may sell securities that are represented in the
Underlying Index or purchase securities that are not yet
represented in the Underlying Index in anticipation of their
removal from or addition to the Underlying Index."
They will game the gamers. Also, this is an SP500 universe, so none of them is anything other than a liquid monster, even heading into Christmas period when the index is reconstituted.
It is a good thought though. The more obvious the rule, the easier it is to simply replicate, the more that trading it will impact prices....the more counter-measures will be in place. The juice lies with front running the not so obvious quant strategies....
Vanguard has over USD 1bn tracking the Russell 2000 index. Add BlackRock, State Street... and you have some real money.
I have a very dear and very senior (in age) mentor (an incredibly patient and forgiving friend). My conversations with him are like being interrogated by Philip Fisher. He asks me about the management of any firm I invest in as if he might know the CEO's grandfather.
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