bump!
For a start you're running a test using a group of stocks that is different from the group of stocks 14 years ago. For example there might be 50% of the present stocks in the group from the test start 14 years ago which gives you a bias toward stock survivors for that 50%. (E.G. CBA $25 and BHP $9). In reality the Index constituents are changed quarterly.I would like to get some feedback on the portfolio backtest results I am currently getting.
To me, backtests are a rough idea of how a system might work. The proof is in the present market.
Now you go and backtest every stock individually with that system and keep only the good ones for your portfolio. You can easily double your return and reduce drawdown that way. The Sharpe ratio will be impressive.
But is it real or am I fooling myself?
Is it reasonable to expect that most of these stocks will reverse their behaviour from the last 15 years? Winners turn into losers? Some of them can be expected to do so, obviously.
As you said, survivorship is a big factor in testing, a real no-no to use the current index constituents. But what if you used only the top 10? The 4 banks, 2 miners and TLS, WES, WOW, WPL, maybe a few more. They have been in the ASX20 for many years.
Does survivorship bias still apply then?
You would have to consider many periods of testing. One year results differs greatly or not to five year results? Tech/a Monte Carlo test suggestion. Test real time?On that subject, Wysi (and others), assume you have a mildly profitable system, but nothing to write home about, single-digit returns. Hardly worth the effort. That may be on the ASX 200 or whatever stocks.
Now you go and backtest every stock individually with that system and keep only the good ones for your portfolio. You can easily double your return and reduce drawdown that way. The Sharpe ratio will be impressive.
But is it real or am I fooling myself?
You could 'reasonably' expect the top ten to be around for awhile so that universe would give a closer to reality result because your system is not benefiting from these stocks over other stocks that come and go.As you said, survivorship is a big factor in testing, a real no-no to use the current index constituents. But what if you used only the top 10? The 4 banks, 2 miners and TLS, WES, WOW, WPL, maybe a few more. They have been in the ASX20 for many years.
Does survivorship bias still apply then?
You would have to consider many periods of testing. One year results differs greatly or not to five year results? Tech/a Monte Carlo test suggestion. Test real time?
I'm afraid I can't offer much advice because I'm over backtest dreaming. At present simply using what I have learned so far to make decisions on what to buy, when to buy and when to sell.
You could 'reasonably' expect the top ten to be around for awhile so that universe would give a closer to reality result because your system is not benefiting from these stocks over other stocks that come and go.
Really though, to get an accurate backtest of an Index, the constituents would have to be as they were at the start date of the test and changed quarterly from the test start date forward. Otherwise you aren't testing all of the Index back then rather the stocks that have survived and are still in the Index today.
1. Could this be why "they" keep changing the constituents i.e to skew any backtest result
2. Your portfolio of stocks becomes your Index so to speak. What's wrong with that?
1. Uh, no.
2. Your sample is biased. It will consist of those companies that have survived through the period and you could not have known this at the start period. It is amongst the most egregious forms of over-fitting to do this.
On backtests, if you throw enough efforts, even by chance, a stack will look good. All sorts of rules can be invented and backfitted to produce unbelievable outcomes....even on random noise. There is no skill (beyond coding it) to producing an outstanding backtest. It is a large distance between finding one that looked good and it actually being predictive.
Not exactly sure how you would Monte Carlo a set decision rule on a set piece of data. Running 1 million of those yields a million identical outcomes.
Enjoy the journey of discovery that's ahead....
1. No past performance is a guarantee of future performance.
2. It is impossible to know for sure whether any company will survive at any time but surely one could pick some companies that one could reasonably expect to survive in future for as far back as they are being backtested. So maybe its not all about survivor bias (which one cannot argue against) but survivor probability.
Not exactly sure how you would Monte Carlo a set decision rule on a set piece of data. Running 1 million of those yields a million identical outcomes
He used the word Portfolio which implied to me that it was a group of stocks. As such Monte Carlo would be beneficial--as for survivorship---from 100s of tests on various strategies my findings have been that if there is a repeatable and profitable set of rules in one chart if the same setup occurs in another you'll see similar results.
By running 1000s of portfolios you will then be able to determine a set of likely results over those 1000s.
Out of sample test/walk forward test/live test---and provided there isn't a dramatic change in the real-time trading V the tested data set/s you'll get a similar profitable result.
You certainly have more time than me to answer in depth
But then again your probably a touch typist!
Hi, I am newbie here so please dont get worked up if my queries appear to range between absurd and stupid
I would like to get some feedback on the portfolio backtest results I am currently getting.
I am quite concerned with "Max % Trade DD = -38%"!! However, the "Max % System DD = -19%" seems reasonable. Do you think this could be realistic? or do you think there is scope for improvement?
For a start you're running a test using a group of stocks that is different from the group of stocks 14 years ago. For example there might be 50% of the present stocks in the group from the test start 14 years ago which gives you a bias toward stock survivors for that 50%. (E.G. CBA $25 and BHP $9). In reality the Index constituents are changed quarterly.
To me, backtests are a rough idea of how a system might work. The proof is in the present market.
On that subject, Wysi (and others), assume you have a mildly profitable system, but nothing to write home about, single-digit returns. Hardly worth the effort. That may be on the ASX 200 or whatever stocks.
Now you go and backtest every stock individually with that system and keep only the good ones for your portfolio. You can easily double your return and reduce drawdown that way. The Sharpe ratio will be impressive.
But is it real or am I fooling myself?
Is it reasonable to expect that most of these stocks will reverse their behaviour from the last 15 years? Winners turn into losers? Some of them can be expected to do so, obviously.
I don't know the answer but would like to find out without risking my money. Any ideas?
As you said, survivorship is a big factor in testing, a real no-no to use the current index constituents. But what if you used only the top 10? The 4 banks, 2 miners and TLS, WES, WOW, WPL, maybe a few more. They have been in the ASX20 for many years.
Does survivorship bias still apply then?
Building a process to develop a portfolio via algo on a fixed dataset will produce the same outcome no matter how many times you run it.
14 year test is almost certainly a stock portfolio using yahoo data and maybe even a trend trader using tech/a's conditions. You are correct though, it doesn't actually state this. :silly:Well to be fair, it doesn't actually say what group of stocks were used for the backtest. Yes, index constituents are changed quarterly, which is why I wouldn't base a backtest on them. There is no indication in the original post that the backtest used index constituents.
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