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RE: [amibroker] Re: Analyzing a system



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<SPAN 
class=558521215-18022003>OK....... but how does that negate the value of data 
prior to 4/10/01? True the moves may be finer on a tick by tick basis but many 
other things also affect the market I.E. internet trading, an increase in Retail 
trade versus institutional. Increases in liquidity and volume etc. Perhaps I 
miss your point
 Jayson 
<FONT face=Tahoma 
size=2>-----Original Message-----From: nickhere 
<nickhere@xxxxxxxxx> [mailto:nickhere@xxxxxxxxx]Sent: Tuesday, 
February 18, 2003 8:57 AMTo: 
amibroker@xxxxxxxxxxxxxxxSubject: [amibroker] Re: Analyzing a 
systemBut movement up to that time was in fraction. 
now we move in decimnal .01--- In amibroker@xxxxxxxxxxxxxxx, 
"Jayson" <jcasavant@xxxx> wrote:> Nick,> Your data base is 
converted to decimal as well is is not? Pull up a chart> and look at 
1/3/2000 you will see decimals not fractions...> > Jayson> 
-----Original Message-----> From: nickhere <nickhere@xxxx> 
[mailto:nickhere@xxxx]> Sent: Monday, February 17, 2003 9:29 PM> 
To: amibroker@xxxxxxxxxxxxxxx> Subject: [amibroker] Re: Analyaing a 
system> > > When testing a system shouldnt all data before 
4/10/2001 be ignore.> on 4/10/2001 was the date all exchanges converted 
to decimal.> > nick> > --- In 
amibroker@xxxxxxxxxxxxxxx, "tchan95014 <tchan95014@xxxx>"> 
<tchan95014@xxxx> wrote:> > Hello,> >> 
>> >> >> > Here is an example on how I select a 
ticker to be included in a> system> > portfolio (a sure form of 
curve fitting, but...) I also touch upon> how> > I analyze the 
system base on one selected ticker trying to fine> tune> > this 
system. I hope to invite some discussions and debates, critics> > 
and comments.> >> >> >> >> > 
1) trade range: 1/1/99 - today> >> >> 
>    The range is selected to cover the big runup and big 
crash,> hoping> > to detect the system as well as target's 
response to the big swings.> >> >> > 2) A 
short term EOD system is used.> >> >> > 3) After 
optimize the system to death (another curve fitting), I> > selected 
some parameters that look stable. (Thanks to Herman's> > 3DCharts, I 
used it every time I do the optimization)> >> >> > 
4) I started to run the system on a bunch of tickers, say N100.> 
>> >> > 5) I then select only those with, say > 20% 
RAR over the test> period,> >> >> > (I 
would like to use MAR, but so far it is very difficult so I> 
choose> > RAR) I put those selected into a watchlist.> 
>> >> > 6) I then run tests on the watchlist.> 
>> >> >    a) I move the test range from 
1999 - 2003 --> 2000 -> 2003,> again I> > chop off those 
not meeting a certain RAR, then 2001 -> 2003, then> 2002> > 
-> 2003. I only want those that are profitable on every test and> 
they> > have to show to generate a certain RAR.> >> 
>> >    b) There will be only less than a handful 
candidates now.> >> >> > 7) I will then start to 
run the optimization again on the selected> > candidates, just want to 
make sure the original optimized> parameters> > are still a 
good choice. If yes, good, a new portfolio is created,> if> > 
NOT, well, all bets are off, I might start again on the newly found> 
> optimized parameters on the whole N100 again and start the whole> 
> process to see if the new parameters are stable on SOME other> 
tickers.> >> >> > 8) You might want to start 
testing the watchlist on any UN-tested> data> > range now. I 
did not.> >> >> > 8) It is a tedious process but 
interesting journey.> >> >> >> >> 
> OK, let us say I have the portfolio selected and system chosen. I> 
will> > go into each ticker selected to do some more analysis.> 
>> >> > As an example, I offer one below.> 
>> >> >> >> > Again, it is a short 
term EOD system, as you can see below.> >> >> 
>> >> >       a) There are 
240 trades from 1/1/1999 - 2/14/2003> >> >> 
>             - a 
RAR% > 260% system> >> >> 
>             - a 
MaxDD% > -86% system when position sizing = 100%> >> 
>> 
>             - I 
am eagerly waiting for the portfolio level position> >> 
>> 
>               
sizing feature to arrive.> >> >> 
>       b) When the profit% per trade was 
analyzed> >> >> 
>             - 
max. loss = -20.1%> >> >> 
>             - 
max. gain = +84%> >> >> 
>             - 
average = 3.14% (all entries in the profit% per> trade> 
>> >> 
>               
column are averaged)> >> >> 
>             - 
standard deviation (SIGMA) = 14.76%> >> >> 
>             - 
average - 2 * sigma = -26.37%> >> >> 
>                   
- this is larger than the max. loss, a good> sign.> >> 
>> 
>             - 
average + 2 * sigma = +32.66%> >> >> 
>                   
- max. gain is much larger than this, also a> good sign> 
>> >> 
>                   
- FAT tail effect> >> >> 
>             - 
It was found that if I align trades from max. loss> to max> > 
gain sequentially it takes the first 223 entries to get the gains> 
to> > offset the losses, it pretty much leaves only 18 profit trades 
to> make> > the extra profits taken home> >> 
>> 
>             - 
18 / 240 < 8% of the trades makes the day.> >> >> 
>             - 
It also hints loudly that I have to take every> trade,> > 
because it is extremely difficult to be selective in choosing> 
trades> > and hit on those 8% big winning trades, they are so few and 
far in> > between that I can not afford to miss any.> 
>> >> 
>             - 
The FAT tail is very important, it means the losses> have> > 
been kept in check and profits have been left to run.> >> 
>> >       d) Further analysis on the 
biggest losses> >> >> 
>             - 
most of the biggest losses are the results of the> GAPs, I do> 
> not see any way to prevent these trades, I guess I have to live> 
with> > them.> >> >> 
>             - 
Further check might be focused on the MAE (Maximum> Adverse> > 
excursion) on profit trades to see if there is any chance to use> 
the> > collected statistic to create a hard stop to further minimize 
the> > losses.> >> >> >> 
>> > NOTE: this system has a very low profit factor of 1.34, but 
thanks> to> > Fred, it has also the following statistics on the 
last day of range> >> >> >    
CAGR%  = 267.13> >> >> >    
MDD%   = -68.89> >> >> 
>    MAR    = 3.88> >> 
>> >    UPI    = 56.35> 
>> >> >    KRatio = 3.30> 
>> >> >    MFlat  = 267> 
>> >> >> >> > Some more statistics on 
the analysis of profit % per trade:> >> >> 
>                     
average  sigma    avg - 2 sigma    avg + 2 
sigma> >> >> >    For ALL 
trades:  3.14%    14.76    
-26.73           
+32.66> >> >> >    Losing 
trades    6.14%    4.31     
-14.77           +2.49> 
>> >> >    only> >> 
>> >    Winning trades   
14.06%   15.33    
-16.60           
+44.73> >> >> >    only> 
>> >> >> >> > I can not offer any 
useful analysis on these statistics but I do> hope> >> 
>> > TJ can offer All trades, losing trades, winning trades 
report.> >> >> >> >> > As you 
can see it is a very difficult system to trade. It is only> an> 
> example to illustrate the process.> >> >> 
>> >> > Hope you find these info interesting and tickle 
you brain.> >> >> >> >> 
>> >> > Thomas> > 
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