you are right. It is weird. When I try, it actually happens for ALL
zip-Files listed there!!!

On 11 Dez., 17:25, Astor <[email protected]> wrote:
> Yes. It does display the JBookTrader-my.zip, but once clicked, it display the
> message that the page does not exist. I'll look for patch.txt
>
> ________________________________
> From: Klaus <[email protected]>
> To: JBookTrader <[email protected]>
> Sent: Sat, December 11, 2010 7:37:29 AM
> Subject: [JBookTrader] Re: Dynamic Parameter Optimization
>
> Hi,
>
> I just checked, it is there:
> go to files; sort them by date of upload and you find: JBookTrader-
> my.zip
> close to the top.
> This is the recent one.
>
> alternatively you can find patch.txt
> this is an older version.
>
> Klaus
>
> PS alternatively you can sort by name of uploader and then you see it
> if you look for Klaus
>
> On 11 Dez., 03:21, Alexana <[email protected]> wrote:
>
>
>
>
>
>
>
> > Klaus, I tried to look at the file you had posted, but seems the page
> > is not there. Can you repost?
>
> > On Dec 10, 9:22 am, Klaus <[email protected]> wrote:
>
> > > it is online in the group file repository.
>
> > > Klaus
>
> > > On 10 Dez., 14:37, Astor <[email protected]> wrote:> Thanks Klaus! I 
> > > look
> >forward to seeing it.
>
> > > > ________________________________
> > > > From: Klaus <[email protected]>
> > > > To: JBookTrader <[email protected]>
> > > > Sent: Fri, December 10, 2010 3:55:37 AM
> > > > Subject: [JBookTrader] Re: Dynamic Parameter Optimization
>
> > > > Dear Astor,
>
> > > > I posted it earlier for a previous JBT version.
> > > > I will upload a version for the current JBT in a few moments, This is
> > > > an excerpt of my production code, but note that I modified it somewhat
> > > > to
> > > > ignore certain error conditions (missing volume values and wrongly
> > > > ordered dates).
>
> > > > Cheers
> > > >   Klaus
>
> > > > On 8 Dez., 21:53, Astor <[email protected]> wrote:
>
> > > > > Thanks Klaus. Exellent description. Can you post your JBT extension 
> > > > > for
> > > > > backtests? I would love to incorporate that into my program.
>
> > > > > ________________________________
> > > > > From: Klaus <[email protected]>
> > > > > To: JBookTrader <[email protected]>
> > > > > Sent: Wed, December 8, 2010 2:48:13 PM
> > > > > Subject: [JBookTrader] Re: Dynamic Parameter Optimization
>
> > > > > use of-out-of sample data is a must in all machine learning approaches
> > > > > (and this is actually what we do here).
> > > > > (So, yes i also take the approach, this is actually the reason why I
> > > > > built JBT extension for batches of backtests.)
>
> > > > > Perhaps it can be better understood if looks at the danger of
> > > > > presenting all the data.
> > > > > What can happen is that the strategy (and actually JBT does not
> > > > > support learning of parameters, but only of parameter settings)
> > > > > that is generated is sort of memorizing the presented data.. and then
> > > > > provides good results there, but not beyond.
> > > > > The result does not generalize to further data.
>
> > > > > It is like with people, if you really want someone to understand
> > > > > something, you will teach him (presenting examples
> > > > > is one approach for teaching). But at the end you want to know whether
> > > > > he really understood (i.e., got the principles
> > > > > and is able to use them to solve knew problems) or whether he just
> > > > > memorized. The only way to find this out is to show him s.th. he has
> > > > > not seen before...
> > > > > That is what use of out-of-sample means. Simulated forward-Trading is
> > > > > another way to achieve the same result, but then you are doing it in
> > > > > real time (i.e., need weeks), but if you have more data, you can do
> > > > > this simply in minutes with testing..
>
> > > > > On 8 Dez., 15:15, Astor <[email protected]> wrote:
>
> > > > > >  >people do a lot of silly things.  A lot of them agree on these 
> > > > > > silly
> > > > things
> > > > > >  
> > > > > > True enough. This thing, though, has been the subject of so much
> >academic
> > > > > > research that it is probably not one of them. Of course, just like
> > > > > > you, everybody wants to use as much data as possible for model
> >optimization,
> > > > > so
> > > > > > a technique called "bootstrapping" is used, which is similar to
> >walk-forward
> > > > > > optimization that I was proposing.
>
> > > > > > ________________________________
> > > > > > From: ShaggsTheStud <[email protected]>
> > > > > > To: [email protected]
> > > > > > Sent: Tue, December 7, 2010 11:13:26 PM
> > > > > > Subject: Re: [JBookTrader] Re: Dynamic Parameter Optimization
>
> > > > > > I dunno, people do a lot of silly things.  A lot of them agree on
> these
> > > > silly
> > > > > > things.
>
> > > > > > If you had extra data, why would you not use it to see the 
> > > > > > sensitivity
> >of
> > > > >your
> > > > > > parameters?
>
> > > > > > On Tue, Dec 7, 2010 at 8:34 PM, Astor <[email protected]> wrote:
>
> > > > > > Shaggs, I wish I could claim credit for this approach but it is not 
> > > > > > my
> > > > > >approach.
> > > > > > It is a standard statistical methodology used by every professional
> >Quant
> > > > > shop,
> > > > > > without exceptions. In institutional settings, you could never get 
> > > > > > any
> > > > > strategy
> > > > > > past the Investment Committee without presenting strong 
> > > > > > out-of-sample
> > > > >results.
>
> > > > > > >This is not to say that sensitivity to parameter changes, 
> > > > > > >robustness
> > > > checks,
> > > > > > >etc need not be done. They still need to be done on in-sample 
> > > > > > >data.  
>
> > > > > > ________________________________
> > > > > > From: ShaggsTheStud <[email protected]>
>
> > > > > > >To: [email protected]
> > > > > > >Sent: Tue, December 7, 2010 8:53:49 PM
>
> > > > > > >Subject: Re: [JBookTrader] Re: Dynamic Parameter Optimization
>
> > > > > > >So the difference between our approaches is that in your approach 
> > > > > > >you
> >look
> > > > >at
> > > > > > >the 1 "optimal" case, and then you try it on some other set of data
> to
> > > > >verify
> > > > > > >it.  Ok, that is interesting.
>
> > > > > > >I much prefer to have one set of data, and look at the optimization
> >map,
> > > > and
> > > > > > >view the sensitivities to changes in the parameters.  A robust
> >strategy
> > > > will
> > > > > >not
> > > > > > >be a picking out small "local minimums", it will have a wide 
> > > > > > >plateau
> >of
> > > > > > >profitibility, and have good distribution on the trades graph where
> >there
> > > > >are
> > > > > > >not large periods of drawdown.
>
> > > > > > >I think my method is more robust, and would yield better real world
> > > > > >performance
> > > > > > >than your method, but I can't prove it.
>
> > > > > > >On Tue, Dec 7, 2010 at 5:52 PM, Astor <[email protected]> wrote:
>
> > > > > > >>No, you do not do the same thing on both sets. You optimize 
> > > > > > >>and test
> > > > > >different
> > > > > > >>models on in-sample set only. You can do it as much as is 
> > > > > > >>necessary
> >to get
> > > > > >good
> > > > > > >>results. You test only the final model on your out-of-sample and 
> > > > > > >>you
> >can
> > > > >not
> > > > > > >>change the model or re-optimize parameters and re-test on
> > > > > > >>out-of-sample. Out-of-sample is like virginity, - once used it is
> >gone. 
>
> > > > > > >>Results from out-of-sample is what you expect to get in real
> trading.
>
> > > > > > ________________________________
> > > > > > From: ShaggsTheStud <[email protected]>
>
> > > > > > >>To: [email protected]
> > > > > > >>Sent: Tue, December 7, 2010 7:01:03 PM
>
> > > > > > >>Subject: Re: [JBookTrader] Re: Dynamic Parameter Optimization
>
> > > > > > >>Doing the same thing on two different sets of data seems identical
> to
> > > > doing
> > > > > >it
> > > > > > >>on one combined set of data.  How is it different?
>
> > > > > > >>On Tue, Dec 7, 2010 at 4:14 AM, Astor <[email protected]> 
> > > > > > >>wrote:
>
> > > > > > >>The "in-sample" set is where you develop your model and optimize
> your
> > > > > > >>parameters. Because optimization searches through a very large 
> > > > > > >>number
> >of
> > > > > > >>possible parameter values, it finds those values which best fit 
> > > > > > >>the
> >datain
> > > > > >this
> > > > > > >>set. In a different data set, such as the one that may occur in 
> > > > > > >>real
> > > > > trading,
> > > > > > >>these parameters may prove perfectly useless. In Quant research,
> such
> > > > > >situation
> > > > > > >>is (derogatively) referred to as "datamining" or overfitting. With
> >enough
> > > > > >model
> > > > > > >>parameters and extensive optimization, I can get perfect accuracy
> > > > > > >>predicting "in-sample" lottery winners. Of course that model will 
> > > > > > >>not
> >work
> > > > > to
> > > > > > >>predict next, "out-of-sample", lottery winner.  
>
> > > > > > >>>The "out-of-sample" set is a way to verify that the found model 
> > > > > > >>>and
> >its
> > > > > > >>>parameters are general instead of unique to the "in-sample"
> >development
> > > > > set.
> > > > > > >>>Combining the two sets into a single set defeats that purpose.
>
> > > > > > ________________________________
> > > > > > From: ShaggsTheStud <[email protected]>
>
> > > > > > >>>To: [email protected]
> > > > > > >>>Sent: Mon, December 6, 2010 10:21:59 PM
> > > > > > >>>Subject: Re: [JBookTrader] Re: Dynamic Parameter Optimization
>
> > > > > > >>>That whole "in sample" and "out of sample" data thing strikes me
> >very as
> > > > > >very
> > > > > > >>>odd. If it works on the in-sample and not the out-sample, its 
> > > > > > >>>going
> >to
> > > > >have
> > > > > >a
> > > > > > >>>bad distribution as a single set, so why not just combine it?
>
> > > > > > >>>On Sun, Dec 5, 2010 at 5:56 AM, Astor <[email protected]> 
> > > > > > >>>wrote:
>
> > > > > > >>>> we would
> > > > > > >>>>>be required to significantly shorten our optimization periods,
> >thus
> > > > > > >>>>>incurring a penalty of standard error in our confidence bands.
>
> > > > > > >>>>I understand your concern Eugene. However, it is important to
> >recognize
> > > > > >that
> > > > > > >>>>in strategy development and validation there are two sets of 
> > > > > > >>>>data
> >and
> > > > two
> > > > > >sets
> > > > > > >>>>of confidence bands.  First set is used for strategy development
> >and
> > > > > >parameter
> > > > > > >>>>optimization and is often called "in-sample". The second set is
> >used
> > > > only
> > > > > >to
> > > > > > >>>>validate the strategy
>
> ...
>
> Erfahren Sie mehr »

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