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Song,
Thankyou.
A little piece of the puzzle I was looking for.
I don't think it is from this archive so I probably wouldn't have
found it by myself.
For my own use I would convert to % profit or loss, which would also
mean changing the range
I prefer to use standardised units.
BrianB2.
--- In amibroker@xxxxxxxxxxxxxxx, "drsquar" <drsong123@xxx> wrote:
>
> Hi,
> I found following post regarding MCS for amibroker during my
googling:
>
> In "Casino Trading," Phil Abel presents methods of evaluating
trading
> system robustness using Monte Carlo simulation. To perform a Monte
> Carlo simulation, we would need a "decision tree" -- a set of data
> showing probabilities of profits in a given range.
>
> As the author suggests, we could derive such a decision tree from
an
> individual trade list produced by the backtester, but we will show
a
> slightly more automatic method that involves using AmiBroker's
> exploration mode.
>
> Listing 1 shows the exploration formula to be applied in the
> Automatic Analysis window. In our example, we have used a very
simple
> EMA crossover system, but the user can replace it with any other
> system. The code produces a table that shows the number of
> winning/losing trades, total number of trades, and percentage
> probabilities of profits in user-defined ranges. In the sample code
> below, we have used 25 ranges for winning trades (0..100,
> 100..200, .., 2400...infinity), and a similar 25 ranges for losing
> trades. The user can modify both the number of ranges evaluated and
> the size of the range by modifying appropriate variables in the
code.
> Once the exploration is complete, the results can be exported to a
> CSV file for further analysis in Excel.
>
> LISTING 1
> ///// Trading system to be evaluated
> Buy = Cross( Close, EMA(Close, 15) );
> Sell = Cross( EMA(Close, 15), Close );
> ///////////////////////////////////
> e = Equity(1);
> tradeend = Sell;
> profit = e - ValueWhen( Buy, e );
> endprofit = IIf( tradeend , profit, 0 );
> LosingTrades = LastValue( Cum( endprofit < 0 ) );
> WiningTrades = LastValue( Cum( endprofit > 0 ) );
> TotalTrades = LastValue( Cum( tradeend ) );
> AddColumn( LosingTrades, "Losing trades", 1 );
> AddColumn( WiningTrades, "Wining trades", 1 );
> AddColumn( TotalTrades, "Total trades", 1 );
> Filter = Status("lastbarinrange");
> // now we will count the number of
> // count trades winning in given $ ranges
> NumRanges = 25; // number of ranges to generate
> RangeSize = 100; // controls $ size of the range
> for( i = 0; i < NumRanges; i++ )
> {
> rangestart = i * RangeSize;
> rangeend = (i+1)*RangeSize;
> if( i == NumRanges - 1 ) rangeend = 999999;
> AddColumn(
> LastValue( 100* Cum( endprofit > rangestart AND endprofit <
> rangeend ) /TotalTrades ),
> "% with profit " + rangestart + ".." + rangeend );
> }
> for( i = 0; i < NumRanges; i++ )
> {
> rangestart = (-i - 1 ) * RangeSize;
> rangeend = -i*RangeSize;
> if( i == NumRanges - 1 ) rangestart = -999999;
> AddColumn(
> LastValue( 100* Cum( endprofit > rangestart AND endprofit <
> rangeend ) /TotalTrades ),
> " % with loss " + rangeend + ".." + rangestart );
> }
>
> A sample Monte Carlo spreadsheet for AmiBroker can be found in the
> files area of AmiBroker's mailing list at
> http://groups.yahoo.com/group/amibroker/files/.
>
> --Tomasz Janeczko, AmiBroker.com
> www.amibroker.com
>
> Song
>
> --- In amibroker@xxxxxxxxxxxxxxx, "brian.z123" <brian.z123@> wrote:
> >
> > Hello Whitne,
> >
> > Thanks for your post.
> > Two of your leads provided new material for me.
> >
> > I am not using MCP but I have it under consideration.
> > Conceptually, if not practically, I have rejected the walk
forward
> > method, which means I am bound to consider all methods that
> validate
> > single sample tests.
> >
> > So far I am considering three approaches and measurements for
each:
> > error, significance and symptoms of overfitting.
> > Obviously something from amongst those groups will have to do
> better
> > than the walk forward hypothesis for me to accept it.
> >
> > It might end up that none of them will provide a conclusive
answer
> > but *in the land of the blind, the one eyed person is King*.
> >
> > At the least study, in this area will improve my depth of
knowledge
> > of evaluation techniques.
> >
> > BrianB2.
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, "whitneybroach"
<WhitneyBroach@>
> > wrote:
> > >
> > > While reading David Aronson's book _Evidence-based Technical
> > > Analysis_, I stumbled across a modified Monte Carlo permutation
> > > (MCP) procedure that compensates for data mining bias, assuming
> that
> > > the "best" permutation of rules was not selected with a
directed
> > search.
> > >
> > > From Aronson's perspective, this is good news. He views data
> mining
> > > as a useful procedure in the discovery phase of research.
Plus,
> MCP
> > > does not require out-of-sample data. Thus it is possible to
use
> > more
> > > data for mining and still minimize data mining bias in test
> > results.
> > > The likely result: fewer false positives for systems that are
> > > worthless, and fewer false negatives for systems that are
> valuable.
> > >
> > > The paper with discussion and C# code is here:
> > > <http://www.evidencebasedta.com/MonteDoc12.15.06.pdf>.
> > >
> > > Aronson's book site, including a link to Amazon, is:
> > > <http://www.evidencebasedta.com>. Separately, I'm looking
> forward
> > to
> > > the imminent books from Howard
> > > <http://www.quantitativetradingsystems.com/> and Ralph Vince
> > > <http://tinyurl.com/2os2p7>.
> > >
> > > Not being a user of IO (or other AB add-ons), I have no idea if
> this
> > > MCP approach is already being used in the AB community. It
looks
> > > interesting to me. MCP appears to require market data and
trade
> > data
> > > from every run, not simply the trade data. That suggests to me
> that
> > > an AB add-on, rather than a completely external program, would
be
> a
> > > more straightforward implementation.
> > >
> > > Aronson also refers to a patented boostrap procedure that
> > accomplishes
> > > much the same thing, White's Reality Check, named for Halbert
> White,
> > > the patent holder. Apparently WRC is not available
commercially.
> > >
> > > Best,
> > >
> >
>
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