- Joined
- 20 November 2005
- Posts
- 787
- Reactions
- 92
HERE is an interesting paper on trend following in stocks. I think this is a simple way to overcome the n-day breakout suggested above.
Interesting that they adjust all their data for dividends too.
Some other things to consider when testing a system and its viability in the real world.
Firstly there is no real point building a simplistic system that, when operational, requires a discretionary over ride to distinguish signals. I have numerous people come to me because they've done certain courses, which all shall remain nameless, that teaches trend following in various formats. The problem is that when they run the system rules they get 10 signals each and every day. From that juncture one must then pick and choose which to take and as we all know, we'll always pick the wrong ones.
The above issue comes from "simplistic" systems. A simplistic system will have several inherent errors when it comes to real world trading. The one I just mentioned above is the most common, especially in this kind of environment. The other is more serious when it comes it comes to the psychology of the system. A simplistic system will tend to generate many false signals during a bearish market phase which in turn will lead to a lot of frustration but also a dwindling account balance. I see this as a real risk for those embarking on this journey in the current environment. Any old simple trend following system will do okay in this environment. I know of a very well known broker touting such a system to the public that uses a 22/35 week crossover method. Yes it will catch killer long term trends but it will get mauled in any longer term bearish environment and will also be prone to false signals in a sideways period. Another simplistic system would be some kind of price breakout, like a channel breakout of a n-day high.
HERE is an interesting paper on trend following in stocks. I think this is a simple way to overcome the n-day breakout suggested above.
Another "common sense" assumption is finding those golden trends, albeit with added volatility and risk. Essentially a business will grow and with it so will the share price. One therefore needs to find the "emerging" businesses, that is those that may end up being the next TOL or CSL. Almost every one of these will be a relatively new listing and therefore be trading below $10.00. I recommend to my subscribers looking to get a bit more "bang for their buck" to only take signals on those stocks trading below $10 without any lower limitations. If you remove the signals above under $10.00 you get a reasonable increase in the risk adjusted return. If however you only take signals below $5 you get a substantial increase in risk adjusted return.
This process will also reduce the universe and, with simplistic systems, reduce the potential trade frequency and therefore the discretionary input levels.
What is an easy way to find these? Focus on stocks that do not pay dividends, which is, funnily enough, another portfolio I run.
The question of survivorship.
One I have pondered for hrs.
I have not culled my data for 4 yrs.
So have atleast all the delists for the last 4 yrs in 7 bourses.
That helps.
I trade the ASX 300 (Well a margin list predominantly made up of),which to some degree minimises the problem.
While always a risk If I'm only trading 10% of my account on anyone trade then There is that minimisation.
Anything I systems trade is pretty heavily tested so I have a good idea of overall expected performance based on 1000s of portfolios.
By this I mean Ill know if one or 2 of these event appear and turn an otherwise profitable method into a loser. From testing on mine--it doesnt.
There is much to developing and designing a system.
When you REALLY REALLY understand these words---and you'll get that from experience rather than comprehension---then you'll have the Ahh of Ahh moments.
The developement and application through developement becomes a breeze.
THEN look beyond that which you have developed to how a system which is average can be made well above average!
T/T returns about 35% compounded annually---so how is it that it has returned 1300% on initial funds in 4.5 yrs?
HERE is an interesting paper on trend following in stocks. I think this is a simple way to overcome the n-day breakout suggested above.
Winning trades are only reduced to alleviate risk concentrations.
Winning trades are only reduced to alleviate risk concentrations.
Does this mean that if a winner is such a champion that it grows to over 20% of the portfolio and your portfolio limit is 20% max per stock, then you reduce the position??
And also the author of the paper details why they did not consider a short system and one of the reasons was due to forced buy-ins (which cannot be backtested).
Is a forced buy-in the short equivalent to a margin call?
Tech what level of drawdown was acceptable (after system testing) to achieve the 22-28% return?
I recall initial drawdown was on the system was about 12%.
What was the maximum MaxDD for techtrader during system trading?
In Peak to valley from memory around 22%
Initial drawdown around 8%
Tech i recall you saying you tested the system between 1993-2001. And you started forward testing the system in realtime in 2002? So in your first year you mustve had quite a shock and sitting on pretty significant drawdowns yeh?
No There was always open equity to ofset the initial and inevitable string of first loses as the portfolio takes shape I can post some curve figure piks if you want.
Just a bit more to add (generally not in response to tech)
Survivorship bias and indices makeup are issues raised in this thread but like i said thats to do with your data provider. They should take care of this.
I think a (more) major problem with systems design and backtesting is curve-fitting. To avoid this we can forward test the system. Ie. Design/Test a system between 1992-1999 and then run it over the years 1999-2006, for example.
Youve not explained curve fitting correctly
I think a (more) major problem with systems design and backtesting is curve-fitting. To avoid this we can forward test the system. Ie. Design/Test a system between 1992-1999 and then run it over the years 1999-2006, for example.
I'm only reciting stuff from a book here...no experience (testing or trading) to draw from...but in the book Way of the Turtle, Curtis Faith was of the opinion that whilst curve-fitting is bad, optimisation was not. From memory he defined curve-fitting (or overfitting) as being lots of indicators and their variables tuned to produce exceptional results in historical testing, usually covering a shorter than adequate period of time.
Optimisation on the other hand he saw as tuning things like MA or breakout lengths. His theory was that by chosing the most optimal value, if/when markets change characteristics in the future, your chances of having settings in your system that are close to the new optimal values are greater than if you'd purposely (or ignorantly) chosen a non-optimal value.
Eg. Historical testing reveals that the optimal breakout length for entries in your market is 100. 20 days either side of that are entries that result in 5% less CAR, 80 and 120. In the future the markets change and the new optimal value is 120. You're CAR is only 5% less than optimal. If you'd chosen 80 on the other hand, for no apparent reason other than it seemed 'robust', you system might earn 10% less. The explanation is oversimplified, but it made sense to me.
Nizar.
Sorry
Just back from Island sitting/exploring.
Nizar,Can you please explain curve-fitting to me?
We use cookies and similar technologies for the following purposes:
Do you accept cookies and these technologies?
We use cookies and similar technologies for the following purposes:
Do you accept cookies and these technologies?