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Looking at the table of contents for the original (as found on
Amazon), the subject matter looks to be nearly identical between the
two publications. That being the case, the newer publication would
probably be the better bet.
Mike
--- In amibroker@xxxxxxxxxxxxxxx, "Mike" <sfclimbers@xxx> wrote:
>
> Ton,
>
> I was referring to the newer version published earlier this
year "The
> Evaluation and Optimization of Trading Strategies".
>
> I have not read the first publication. However, it is my
> understanding that the newer one includes the primary ideas
> originally published in the older one.
>
> Mike
>
> --- In amibroker@xxxxxxxxxxxxxxx, "Ton Sieverding"
> <ton.sieverding@> wrote:
> >
> > Hi Mike,
> >
> > About which book of Pardo are you talking. The first one from
1992
> or the newest version from the beginning of this year ? I have
found
> two books. Any suggestion ? I am looking for a little bit more
> general background music concerning the Optimization topic and
> therefore have the feeling that his first book called 'Design,
> Testing, And Optimization Of Trading Systems' could bring me some
> extra light in the tunnel ...
> >
> > Regards, Ton.
> >
> >
> > ----- Original Message -----
> > From: Mike
> > To: amibroker@xxxxxxxxxxxxxxx
> > Sent: Tuesday, April 22, 2008 8:50 PM
> > Subject: [amibroker] Re: Difference betwee OOS and IS
> >
> >
> > Louis,
> >
> > Pardo's book is dedicated to the process of designing a
strategy
> that
> > can then be validated using walk forward analysis.
> >
> > The sole purpose of the book is teach about the use, and
> importance,
> > of walk forward. If you are having trouble understanding the
> > concepts, this book may help to clarify things for you.
> >
> > Pardo's book has very little code at all, and none of it is
> > AmiBroker. It is strictly a book on the concept, not an
> > implementation. The book tells you what to expect, and how to
> > interpret the results.
> >
> > If you are having trouble separating the concepts from the
> mechanics
> > as presented in Howard's book, or just need more detail about
> what
> > the process is used for, then Pardo's book may help to answer
> your
> > questions. You will then better understand the mechanics that
> Howard
> > presents, and appreciate that AmiBroker now automates the
entire
> > process.
> >
> > Mike
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, "Louis Préfontaine"
> > <rockprog80@> wrote:
> > >
> > > Hi Howard,
> > >
> > > Thanks for the code and the information. What exactly is
doing
> the
> > CMO
> > > Oscillator? I tried to look for information on the web but
did
> not
> > find
> > > anything convincing. It sure looks interesting and I will try
> to
> > find more
> > > about it, but right now this look like mystery to me.
> > >
> > > Something I wasn't sure in your book, is what you mean by
> objective
> > > function. Do you mean choosing between RAR, or CAR, or K-
Ratio,
> > etc.? I
> > > know this sound like a stupid question after I've read 75% of
> the
> > book,
> > > but... well... I wasn't sure.
> > >
> > > I will try to follow the steps as you write them below.
> However, I
> > am still
> > > worried about MCS; I mean, in the steps you don't use any
random
> > > optimization and you said not to worry about them. I say that
> > because it
> > > seems to me that in the walk-forward it can be easy to get
> lucky
> > with some
> > > very good curve-fitting results. And the more complex the
> rules,
> > the more
> > > chances there is to get a very lucky result! Well, this was
my
> > whole point:
> > > in the walk-forward I only get to see the absolute best
return,
> and
> > if there
> > > is no random optimization I can't rule out the luck factor!
> > >
> > > Thanks!
> > >
> > > Louis
> > >
> > > p.s. Mike, thanks for the suggestion. Is Pardo's book really
> good
> > and is
> > > using afl code or codes that can be implemented easily to
> Amibroker?
> > >
> > > 2008/4/22, Howard B <howardbandy@>:
> > > >
> > > > Hi Louis --
> > > >
> > > > If the system you are working with is actually the
crossover
> of
> > two simple
> > > > moving averages, the results you get will probably not be
> very
> > good. I
> > > > often suggest a simple system when I am trying to make a
> point
> > that requires
> > > > a system and I do not want the definition of the system to
> > confuse the other
> > > > point. You will need a system that is more sophisticated to
> show
> > good
> > > > results. Try the CMO Oscillator in the code posted below.
> > > >
> > > > // CCT CMO Oscillator.afl
> > > > //
> > > > // A CMO Oscillator
> > > > //
> > > > //
> > > >
> > > > // Two variables are set up for optimizing
> > > > CMOPeriods=Optimize("pds",61,1,101,5);
> > > > AMAAvg=Optimize("AMAAvg",36,1,101,5);
> > > >
> > > > // The change in the closing price is summed
> > > > // into two variables -- up days and down days
> > > > SumUp = Sum(IIf(C>Ref(C,-1),(C-Ref(C,-1)),0),CMOPeriods);
> > > > SumDown = Sum(IIf(C<Ref(C,-1),(Ref(C,-1)-C),0),CMOPeriods);
> > > >
> > > > // The CMO Oscillator calculation
> > > > CMO = 100 * (SumUp - SumDown) / (SumUp + SumDown);
> > > >
> > > > //Plot(CMO,"CMO",colorGreen,styleLine);
> > > >
> > > > // Smooth the CMO Oscillator
> > > > CMOAvg = DEMA(CMO,AMAAvg);
> > > > // And smooth it again to form a trigger line
> > > > Trigger = DEMA(CMOAvg,3);
> > > > // Buy when the smoothed oscillator crosses
> > > > // up through the trigger line
> > > > Buy = Cross(CMOAvg,Trigger);
> > > > // Sell on a downward cross, or 6 days,
> > > > // whichever comes first
> > > > Sell = Cross(Trigger,CMOAvg) OR BarsSince(Buy)>=6;
> > > >
> > > > Buy = ExRem(Buy,Sell);
> > > > Sell = ExRem(Sell,Buy);
> > > >
> > > > Plot(C,"C",colorBlack,styleCandle);
> > > >
> > > > PlotShapes(Buy*shapeUpArrow+Sell*shapeDownArrow,
> > > > IIf(Buy,colorGreen,colorRed));
> > > > Plot (CMOAvg,"CMOAvg",colorGreen,
> > > > style=styleLine|styleOwnScale|styleThick,-100,100);
> > > > //Figure 20.2 CMO Oscillator
> > > >
> > > > Now -- back to the issue of validating a trading system --
> > > >
> > > > Tomorrow is out-of-sample. You want to increase your
> confidence
> > that your
> > > > trading system will be profitable when you trade it
tomorrow.
> In
> > order to
> > > > do this, observe what happens after you have optimized a
> system
> > over an
> > > > in-sample period, then tested it on the immediately
following
> out-
> > of-sample
> > > > data. The automated walk forward process helps you do this.
> > Every step
> > > > gives one more observation of the in-sample to out-of-
sample
> > transition. If
> > > > the cumulative out-of-sample results are satisfactory to
you,
> > then you have
> > > > increased confidence that your real trades are likely to be
> > profitable. No
> > > > guarantees. The best we can hope for is a high level of
> > confidence.
> > > >
> > > > At this point, do not worry about Monte Carlo.
> > > >
> > > > Just concentrate on:
> > > >
> > > > 1. Select the objective function that You feel most
> comfortable
> > with.
> > > > 2. Design and test the systems of interest to You.
> > > > 3. Experiment to find the length of the in-sample period.
> > > > 4. Perform the automated walk forward analysis.
> > > > 5. Examine the out-of-sample results.
> > > > 6. Decide whether or not to trade your system.
> > > >
> > > > Thanks for listening,
> > > > Howard
> > > > www.quantitativetradingsystems.com
> > > >
> > > >
> > > >
> > > > On Tue, Apr 15, 2008 at 7:03 PM, Louis Préfontaine
> > <rockprog80@>
> > > > wrote:
> > > >
> > > > > Hi,
> > > > >
> > > > > I've been experimenting with walking-forward, and I have
> some
> > questions
> > > > > regarding how it works.
> > > > >
> > > > > I ran a complete random optimization or buying/selling
> using the
> > > > > variables I set (a MCS in fact), and systematically OOS
> results
> > were worst
> > > > > than IS. I don't understand how it works, because
whatever
> if
> > the sampling
> > > > > is IS or OOS it is always the same variables that are in
> place.
> > > > >
> > > > > Anyone could explain how this work?
> > > > >
> > > > > Thanks,
> > > > >
> > > > > Louis
> > > > >
> > > >
> > > >
> > > >
> > >
> >
>
------------------------------------
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