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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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