R2G vs private port

A few questions for MisterChang.

Have you done longitudinal studies of your R2G ports to see if you are getting adequate returns and matching or even besting the reported out-of-sample returns?

Have you done slippage studies to see if you are getting results as good or even better than the current variable-slippage benchmark used by R2G? Have you examined different strategies for improving your slippage? I was able to double the performance of one particular R2G port by answering this question.

Have you looked into developing hedging strategies specific to your R2G ports?

My point is …

…there are ways to potentially enhance the alpha of an already-good R2G port. It will also mean a lot of work. You may want to do this before embarking on private port development, as an exercise answering these questions will help develop your P123 skills and may help you decide if R2G ports by themselves can meet your needs fully, or not.

MisterChang - As I see it, every individual needs to do their own self-assessment before they can answer your question. Here are some questions that will help you answer for yourself:

  • What is it that brings you to Portfolio123? And why have you stayed? (95% register then never come back).
  • Do you have an aptitude for finance, mathematics, statistics, …
  • Do you feel you are a good judge of character (i.e. model developers)?
  • are you confident in trading black box strategies?
  • are you confident in your own abilities for developing and trading models?
  • do you have the time to learn the P123 trading “language” or syntax if you prefer?
  • what level of investment performance would you be happy with?

Marc - Correct me if I’m wrong (I’m no expert) but I believe that factor testing fits into quantitative analysis.

As for the approach of reading Greenblatt or using Piotroski, this approach may not be as straightforward as you claim. There is no doubt in my mind that there are thousands of Piotroski screen followers on AAII and elsewhere. Given that these strategies are used on small companies, where is the advantage when they have so many followers?

The high alpha issue is really a problem with P123, the way R2G is set up. I have seen advertisers that promote investment systems where the top performers achieve 30% return per year. It is P123’s job to manage expectations. By displaying backtests in the way that they do, it can only be that developers MUST over-optimize to the point where in many cases the results are not credible going forward. But since the backtest data is readily available, subscribers demand this backtest performance.

Since I wish to provide models that get subscribers, I must compete with other backtests whether or not I feel it is right. And this does require many, many hours of development. I don’t believe I would have any less work trying to do it your way. It has been my experience that about 99% of the ideas I read about don’t pan out. And if they do, it is a very small advantage over equal weighted index.

I’d like to end with this quote . It is out of context (it has to do with HFT) but there is a point there.

“While companies raise about $250 billion a year in equity financing through IPOs and additional equity offerings, (Jack) Bogle said there’s $33 trillion worth of trading going on, which is basically betting on the psychology of the markets.”

Jack Bogle is of course the founder of Vanguard. He is complaining about HFT but $33 Trillion worth of trading per year really causes a detachment of stock prices from underlying value. In some markets a P/E Ratio of 50:1 is too low and in other market conditions 8:1 is too high. There is no absolute value. If there was then there would be no point to ranking systems.

We are all really doing battle against every other trader, human or computer. And mass psychology is one of the most important elements.

Steve

This is a good idea, something I am already doing with one strategy and now looking at doing with another.

Don

MasterChang,
It no secret you can make more alpha with less liquidity stocks
So for me I main advantages to private portfolio, is the ability to tailor-made the liquidity of the model, to the sum of money I want to invest in it
The second is the ability to run update in different day then Monday
(If for some reason you miss an update)
However I think the average person will consume allot of time if he want to challenge some of the r2go models, and it is not so easy to succeed to make a better alpha, but you should try it if you like the proses

I like to think some of the reedy to go models are also develop with idea and not just test what work
(For example my Sherman’s why to go shield wall where I try to make alpha with low risk)

When you developing a model you need try to understand also why it was working
Is the rule making sense? Or was it just luck or optimized to the past?

Of course if you have knowledge of the markets that is near Greenblatt or Piotroski
It is a very good starting point,
Good luck!

I want to add a little comment to Steve,
It is nice that p123 gives a place for low performance models to compete between themselves, but don’t underestimate the high performance ones
Because for me a model that was design to 100% a year, but made in reality only 50%, is better than a model that design to 30% a year and made 35%
The bar for 30% is also not really separate between over optimize models, because I can easily design a model that when I will launch from 1999 will show less than 30% and if I launch from 2003 will do much more than 30%

P123 is a great tool and it is realistic to aim and to make, more than 30% a year in reality
Amiran

Mister Chang!

When you want to find your own private models, p123 is like flying a turbo jet instead of walking.
If you want to do it, do it here!

I do not believe it is as hard as it has been described here, if (!!!) you keep your models simple and base them on facts the financial science community
have researched successfully for alpha (Size (Small Caps, Micro Caps), Momentum, Earnings Surprise, Value, combine them and you have a great ranking system!).

I put in 3 years of work, say 10hours a week and I am very happy about it. The models I cannot trade because of time restrictions I published
as r2gs.
Now I do put in 2-3hours of “work” a week. Whenever I like to do more, I do more, but not because I have to.
I do trade a 100 Stock, 3 month model, that could not be published as a r2g because the liquidity would be too low, but the model is a dream (40% ann., very low drawdowns, very less work because It trades only every three months.)
drawdowns, this alone would be an argument to go private!
There is very good free stuff here, start with a ranking of olikea, add market timing (get in cash when the market trades below the 200 ma for example), do not
care about shorting and add 1 Sell rule (Rank based) and 1-3 Buy rules.
Use evenid as a start of robustness tests, test it with 1, 5, 10, 20, 50 and 100 Stocks, and see how it performs and trade only models that
react smooth to variable changes like this. Expect drawdowns of lets say 20-40%, everything else is a fiction. If you do not want to go through them,
forget trading / investing all together! Read (all!) posts of olikea and denny, you will learn more then in all the trading books or blogs combined, and it is for free! Also read the robustness tests of r2gs (they are free) and learn about it.
With p123 this is not a rocket science, if you keep it simple!
Also there are quite well tradable free models (r2g and public ones).
Do not try to design the perfect model, if you find something with 40-60% performance ann. With 20-40% mdd, go for it, step in with 25% of your capital and go up after the first year. In 3 Years you could to 100% and will have more experience than 99.99% of all human beings.
The learning will be phenomenal!
My rec: Go for it, I wish you all the best.

Regards

Andreas

Steve,

Nice post. Your models are starting to vindicate your beliefs. I like your ideas. P/E is not the be all and end all.

Judgetrade/Amirans - you both have very nice, very profitable trading systems. Also some good advice there.

Amiran - You have made a little contradiction:

“I like to think some of the reedy to go models are also develop with idea and not just test what work
(For example my Sherman’s why to go shield wall where I try to make alpha with low risk)”

According to your model comments, you use TLT instead of IEF because “it works better in backtest” :slight_smile:

Mister Chang- When Judgetrade says “it is (not) as hard as it has been described here”…: this is all relative. Three years at 10 hours a week really amounts to about one year of full-time effort. And this comes from an extraordinary individual with a PHD based on trading systems: http://www.uni-kassel.de/upress/online/frei/978-3-89958-188-1.volltext.frei.pdf . I leave you to be the judge of how much work is involved. There is nothing wrong with employing R2G models while you come up to speed on system development as JT suggests.

Steve

Gary - Thx (A couple of models are showing some under performance… has me worried).

I suppose that’s like asking if chewing fits into eating. It’s part of the process, but not the process itself. (If you chew without ever swallowing, you’ll eventually die of starvation.)

It’s a matter of context. As an example, let’s go back to a recent forum discussion on the benefits of earnings acceleration. Denny tested the basic formula for EPS acceleration, stated that “EVERY ranking system I tried to develop using it had higher returns after I removed it from the system or by setting its weight to 0. Just saying, it hasn’t worked for me” and asked “Anyone out there have a system that is improved by adding earnings acceleration?” It took me about ten seconds to find a system where it worked. The “problem” was that I’m not sure it’s possible to get it to work through any sort of factor analysis process.

I’m not going to reiterate the whole discussion here, but in sum, you start with an idea: EPS acceleration should work. But that doesn’t mean you can articulate an earnings acceleration factor or formula, rank based on it, and expect good results. If you stay at the idea level and reason why it should work and consider it in the context of how markets in general work, you right away encounter two obstacles: accelerating earnings can be associated with overvaluation and/or we know business can’t accelerate forever so more likely, there’s a mean reversion flavor to this. So the real investing idea is to look for companies with accelerating earnings whose shares are not overvalued and for which there’s reason to believe the trend is sustainable for at least a little while. Now, we’re in places where factor testing alone can’t really go, or at least not without some creativity. It’s not hard to address the value proposition. But mean reversion is a bigger challenge: We know that in general past performance does not assure future outcomes but we need to find particular instances in which that might actually occur. We can’t do it directly so we need indirect tests. A model I discussed came at it indirectly through a pattern above average returns on capital (a set of standbys which, if we fully understand what they tell us, can actually do an incredible amount of heavy lifting). There are countless other ways to do it (sentiment, technical analysis, earnings quality, and so on), pretty much none of which can be encountered if one is guided by more testing rather than the core ideas. In fact, it would almost be wrong to describe such supporting items as being there to control for the conditions surrounding acceleration. Many serve very broad purposes and carry acceleration along for the ride.

Essentially, I find factor testing way too limiting, and that’s so whether one devotes 20 minutes to factor testing, or 2,000 hours. I prefer to think in terms of idea development and model testing. That means individual rank factors combined with some, potentially many, other rank factors and screening rules – something that isn’t important just for the basics (e.g., liquidity filters) but as an inextricably intertwined part of the model, and none of it occurring randomly or through a massive procedural practice but instead through an effort to develop idea and express them in terms computers can understand.

Marc,

I generate ideas and concepts and attempt to build my systems around specific themes. I use all aspects of a trading system - universe, buy/sell rules and ranking and hedge to try to create integrated systems. I’d prefer you don’t tell others how I build systems or classify me having never worked with me.

Not all my systems work over all time frames, but ‘idea and concept’ based approach is the process I follow. A lot of what I call my P123 time is ‘reading time.’

Technical breakouts. Quality-Value. Contrarian. These are all thematic based approaches. I’ve never built a system with you. But, as Quant mentions, I collaborated with Quantonomics on 1 1/2 rankings. We began with research reading and literature review and a very specific focus of what we were trying to do with our system and built the ranking from there.

Having said that, bottom up factor testing is used by quant. departments at JP Morgan, Goldman Sachs and dozens of other firms. These shops often begin with a list of X number (say 100 to 200 or) permutations of ‘common’ factors (like their list of the canned P123 factors). Factors that have some logical basis and have worked well historically. They regularly rerun ‘factor’ reports on their trailing period performance by market cap, sector, liquidity bands, etc. And then send out these 100 plus page reports on trailing period factor results to institutional clients as well as using them to adjust and build systems that try to capture ‘what’s working now.’ This is an integral part of what most quant shops are doing.

Many pension funds are now using ‘factor capture’ portfolio’s in place of higher cost active management. I’ve heard the former head of the Texas pension fund for teachers speak on this. I’ve read the academic materials for b-school classes on this - including books like ‘Simulation and Optimization’ in Finance. Some of them at least. So…it’s a little out-of-bounds to say that factor analysis is not a part of ‘mainstream practice.’

And for the record…The first thing I did on P123 was to attempt to a) clone all the existing AAII screens (I was a member there from 2008 to 2010), b) build ‘basic’ screens around concepts I had read about in books like the ‘Little Book that beats the Market’, ‘The Little Book of Investing’, ‘The Intelligent Investor’, ‘Investments’ by Bode, Kane and Miller, ‘The Pillars of Investing’ by William Bernstein, ‘Global Investing’ by Ibbotson, ‘Unconventional Success’ by David Swenson, ‘Way of the Turtles’ and about a dozen others as well as several hundred or so (mostly) SSRN papers, including a literature review on behavioral finance and papers on best practices in trading system design and all the posts on P123 I could find (including all of your tutorials). I also built out ‘common sense’ systems based on the public ranks and P123 systems and what I’ve seen work in my angel investing and operating a company. Many good ideas failed out of sample (by failed I mean underperformed an equal weighted benchmark in the same cap range).

In fact, the only one of the AII or public systems from 2008 that I’ve tracked that’s continued to work really well for me was Piotroski. My initial P123 versions of Can-Slim, Tiny Titans, basic ‘value mo’ and several others have not faired very well.

And Joseph Piotroski didn’t walk in off the street and come up with his model after 5 or 10 hours of work. First, he earned an undergrad degree in accounting, then an MBA and a PhD and, along the way, he had to read and master all of the academic literature in his field and write countless papers, leading up to a thesis. That’s the academic process that led to him coming up with that ‘one simple idea.’ A decade of learning or so it seems to me. How many ideas did he backtest and discard to get to it? Good ideas take time regardless of process.

As far as this quote from you:
“That sort-of reminds me of the story about proposals in the early 1800s to save money by shutting down the U.S. Patent Office because all the good ideas had already been discovered. It was a bad idea back then (and one that was thankfully never followed.) It’s a bad idea now. And an analogous idea for p123 (don’t bother trying to develop your own ideas; all the ideas you need are already here) doesn’t seem any better.”

Does that really relate to what I said? It’s a silly analogy. I believe medicines will continue to be invented, but I go to a Doctor…I don’t try and learn medicine. If I loved medicine, maybe I would. I believe cars will keep getting better and so will airplane navigation systems…but I buy my cars and plane tickets…I don’t try to build them from scratch or go out and get my pilot’s license. Etc.

We live in a ‘trade based’ economy…where the most limited asset is, frequently, time and focused attention. Is it really wise to think that below average effort will yield above average results in a highly competitive field.

I don’t always put in 20 hours a week. But, I put in 20-40 hours from 2008 to end of 2009. Then 5 to 10 or so hours a week for 3 or so years. Then 30-40 hours a week the second half of last year. And I’m at least of average intelligence and discipline. And had an undergrad business degree with a focus in finance. And had been a COO for 3-4 years.

If MisterChang loves the process and wants to learn this stuff, great. I wish him well and look forward to having him in the community. But, there is a steep learning curve…and he will likely need to invest some significant time to get up to the level of many R2G’s. Whether or not he can beat the top quartile R2G’s over time is very much unknown. The amount and size by which he can beat them is also uncertain.

Best,
Tom

Thanks guys for the very good input. I often wonder about how much I want to be a “manager” who basically outsources the analysis, vs an analyst who goes deep and knows detailed knowledge.

I was trading 3 R2G’s but recently dropped down to 2. I’m getting a feel of what is reliable and what is not. Also getting a feel of how much volatilaty I can stomach in real time. The old posts by P123 veterans are very very helpful. Also I prefer R2G’s that have been around for longer, as well as R2G designers who have been here a long time, especially those who post insightful ideas.

Rallan, I haven’t looked into what kind of slippage I was getting. It’s a good idea. I’ve only looked at my account size as a whole vs what R2G says it should be.

The learning curve is great, if you do not try to design the perfect model (e.g. I lean to the idea and concept
based on ideas (size, value, momentum etc.) that have been proven to be robust by the scientific community.).

A good enough model can make you rich and you know what you are trading, which is
very important to get through real time drawdowns.

You could start here and you got everything you need to come up with a decent model:

https://www.portfolio123.com/port_summary.jsp?portid=1118154

“It is nice that p123 gives a place for low performance models to compete between themselves”

Amirans - I found this card with my Monopoly game. Any ideas what it means?
Steve


GetOutOfJailCard.gif

I use R2Gs primarily because they seem to give better results for the higher liquidity stocks that I am primarily interested in. I have spent a couple of years and many, many hours trying to best the higher liquidity R2G’s performance and have failed (so far). I recognize that there are some people out there who are just better at this than I am. I am glad they exist! I’ll probably continue using R2Gs for the SP500-like Universe stocks into the future. Having said that, it is easier to come up with your own sims having higher returns using lower liquidity/mktcap universes. One real benefit of doing your own port is you can create your own universe and possibly stay away from exactly the same low liquidity stocks that everyone else is piling into on Monday (potentially affecting the price). Second, there is managing doubt. When you put a $100k bet on a port of 10 stocks, you want to feel pretty good that it will give the results you expect from the sim. A rational developer will always doubt their own work and be at least a little nervous with the ports use with your own real money. Humility is good with ones own work. That is compared to the doubt one has about a black box R2G. When you are getting great results from an R2G, your doubt disappears. But when you get poor results (as all ports do sooner or later over time, R2G and personal ones) then that doubt will come storming back. The doubt/uncertainty of your own port versus the R2G black box will always be in play. Looking at the R2G developer’s ‘resume’ is important. One thing I have noticed with many of the R2G developers who have active ports is that they give virtually no information about their background and experience. I would feel very nervous about using real money with someone who is just a userid. If they are secretive about themselves, then maybe they have a reason to be.

Steve,

I can’t help much with your monopoly game card
Because I stop to play monopoly when I was 6 years old

I am sorry if you got hurt from my comment,

I wish you a good luck with your new microcap model that is in the trader category.

Just try to remember that investing, in the traders category is not a children’s game.
Some of us take it very seriously

Amiran

Amerans - good answer but is sidestepping the issue of bogus foreign companies. As you are aware, when they cease to trade they are given the last price, which in many cases is extremely generous for the trading system. I believe you have already experienced this with at least one model. You also don’t know how many times this has happened in backtest so the backtest performance is likely much higher than it warrants. I suspect the average subscriber doesn’t realize that there is a difference between trading all stocks versus S&P listed stocks, or at least Country(USA) & Universe(NOOTC). So yes I take this seriously and I go to great pains to eliminate the junk stocks. And in so doing I take a huge hit in performance. So, depending on your perspective, you could either say I am competing in a lower performance category or you could say I am competing in a higher quality category.

Steve

Steve
I love p123,I think it is the best tool I ever used
P123 is also far from perfect
You also made a good point
I already address this point 2 times before,
(For example here: https://www.portfolio123.com/mvnforum/viewthread_thread,6960_offset,10)
I think when a stock stop to trade it should be show as zero in the rebalance
And at the simulation!
Only then, you will really know, statistically, if you take a hit or lose performance by eliminating those companies

When you have an idea, for example using bonds ETF as hedge, you can choose TLT ETF or IEF ETF,
If they will give a similar performance, I will choose what will work better in the simulation
Because I believe in numbers more than in feeling,
That why accurate simulation is very important to me.

Other Issues for improvement are for example
Limiting a category for ready to go with a 30% performance limit.
I can understand liquidity categories, but performance categories??
Do I need to lower the performance of my sp500 model to be in some category?
Is that making sense?

Rebalance for ready to go with ( avr hi lo +2*close) /4….??? (I never understand that logic at all)
And it something we can’t test in simulations!

Differed rebalance systems[/b] to privet portfolios ready to go portfolios and books

Short term “Annualized launch” performance makes models look very different just because the time they have launched (we should to compare last 1.3.6 months, because then we comparing same dates)

It seems most of my comment regard the representation, and I hope some of these issues will be fix in the future

Because as I say P123 is excellent tool

Amiran

The Ranking of this model was not public, now it is. Thank you!
http://www.portfolio123.com/port_summary.jsp?portid=1118154

Amirans - I agree with your comments. I was only pointing out that not is all what it seems with the very high performance models. We all design models with certain objectives in mind. The foundation category provides the opportunity to see a better variety of models other than the “throw caution to the wind” type, which is not for everybody.

“I like to think some of the reedy to go models are also develop with idea and not just test what work (For example my Sherman’s why to go shield wall where I try to make alpha with low risk)”

MMy point is that you chose what worked best in the past (TLT). This may not say anything for the future.

Steve

+1. I share this concern but I would never in a milion year exclude Chinese companies.
I look at it this way: many companies rely on cheap and motivated labor to sustain their business models. People who are ready to put out and be paid very modestly to do so. Can we find such workers in Asia ? oh yeah, so many people are dirt poor and with absolutely no one giving a damn about it, they’re just happy to have paid work. But in the West ? We’re too rich. Even the poor are rich by Asian standards (esp in my country). How do you explain to someone who is paid €4/hour to do nothing that he should work like an animal to be paid €7/hour ?
So where exactly is the growth in the West ? High tech, ok but what else ?

Dealing with bogus companies is a risk management issue. Diversification is a good start. Staying out of China altogether is an overkill and has a HUGE opportunity cost.

Aurelaurel - the problem is that the risks are not truly reflected in the backtests or out of sample stats for that matter. It isn’t just Chinese companies but also other foreign companies, OTCs, and any value company on its deathbed. Choosing these types of stocks will give the greatest performance (on paper) because the penalty for being wrong isn’t what it should be.

Steve