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 <[EMAIL PROTECTED]>:
>
> 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 <[EMAIL PROTECTED]>
> 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
> >
>
>
>
