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Because we are working with ownscale charts that is a good idea, Thomas.
herman
Monday, June 11, 2007, 1:20:37 AM, you wrote:
> Good hints, Herman! In addition, I included two lines in my Portfolio.afl:
> RelPerf=eq/C;
> if(ParamToggle("Show Rel.Perf Equity", "No|Yes",0)) Plot(RelPerf, "Rel.Perf.",
> colorBlack,styleThick|styleOwnScale);
> This line makes it very easy to recognise in which market situations your
> system under- or overperforms and to spot its weaknesses . Just one
> additional tool for the visual evaluation.
> Thomas
>> this is jmo but if you have enough trades and you don't have too many Opt
>> variables, by far the easiest way to optimize is to use visual
>> optimizations.
>> We do this by running the system in an Indicator and plot the equity.
>> Substitute the Optimize() with a Param() and simply drag the Param slider
>> left and right. This is a hundreds times faster than optimizing and you'll
>> automatically reject over-optimization because these conditions don't last
>> over many consecutive opt values. You can also immediately see how optimum
>> values for one ticker apply to other tickers simply by clicking on the
>> tickers in your work space. This, btw, gives you a real good impression on
>> how robust (market wise) your system is. You can also immediately pick up
>> on any system bias towards stock price, sectors, markets, time periods,
>> Long vs Short, etc. And all that is minutes...
>> I find the visual feedback is very effective, catches a lot more
>> invalid/over-optimized results, and splits etc. Performance is immediately
>> obvious from the equity chart. Not only that, if your equity jumps up/down
>> you can immediately zoom in on the event and analyze that happened.
>> I like it simple less surprise that way.
>> herman
>> Saturday, June 9, 2007, 11:48:15 AM, you wrote:
>> > The linearity of the equity curve is probably one of the best measures
>> > of predictable future performance, if you have enough data samples. I
>> > believe one way to check for the linearity of the equity curve is the
>> > standard error provided in the optimization table and backtest
>> > report. I'd like to know what the precise definition of this standard
>> > error criteria is, by the way.
>> >
>> > The data I am working with is 1-minute bars, but part of it was
>> > collected some time ago when IB was not providing after-market data
>> > (last fall?), so my bars per day is not uniform, and therefore
>> > the equity line will have a lower slope in recent months, so my
>> > standard error measure is higher than it would be with uniform data.
>> >
>> > Consequently, I've been experimenting with a variation that allows the
>> > trades to be less uniformly distributed over time, but I want the
>> > profit per trade average to be consistent. I average the profits from
>> > the last 50 trades, for example, and compute the linearity of that
>> > instead of the equity curve.
>> >
>> > For both of these, we don't just want a straight equity line - it
>> > should be a straight line that rises, so we really want a combination
>> > of the net profit and this linearity measure, and one way of computing
>> > that is netProfit / stdErr.
>> >
>> > There is a lot more to this. Some other factors to consider are how
>> > much of your equity you are risking with each trade, how long it is
>> > tied up not doing something else, and the magnitude of your potential
>> > loss.
>> >
>> > Daniel LaLiberte
>> > liberte@xxxxxxxxxxxxx
>> >
>> > On Monday 04 June 2007 03:00 pm, Dennis Brown wrote:
>> >> Alex,
>> >>
>> >> What you might be looking for is how straight the equity curve is. I
>> >> have not tried this yet in automatic mode, but when I plot the equity
>> >> curve I look for the gain and how straight the curve is. As a single
>> >> number, that would likely be the correlation to a straight line
>> >> between the start and ending equity values. That way you are not
>> >> fooled by a single rare event.
>> >>
>> >> Dennis
>> >>
>> >> On Jun 4, 2007, at 2:50 PM, dralexchambers wrote:
>> >> > I am currently testing and optimising a trading system over 1 year of
>> >> > data, and sorting the results by Gross Profit Made.
>> >> >
>> >> > What I am finding is that by sorting the results by Gross Profit
>> >> > Made, the system has long periods of small losses then one big gain.
>> >> > Although over a year this provides a good return, drawdowns in the
>> >> > interim are bad - and I am looking for regular cashflow with lower
>> >> > drawdowns rather than the largest gain made over a year.
>> >> >
>> >> > Can anyone think of a way to optimise results for maximal cash-flow
>> >> > each month rather than Gross Profit Made in a year? Is there a
>> >> > mathematical formula I can use?
>> >> >
>> >> > I tried using a average of x bars, but this still doesn't solve the
>> >> > problem, eg:
>> >> >
>> >> > Week 1: -$40
>> >> > Week 2: -$40
>> >> > Week 3: $8000
>> >> >
>> >> > whereas I would like more:
>> >> >
>> >> > Week 1: $900
>> >> > Week 2: $1500
>> >> > Week 3: $2000
>> >> >
>> >> > (this is a very simplified example but illustrates what I am after).
>> >> >
>> >> > Many thanks,
>> >> > Alex
>> >
>> > Please note that this group is for discussion between users only.
>> >
>> > To get support from AmiBroker please send an e-mail directly to
>> > SUPPORT {at} amibroker.com
>> >
>> > For NEW RELEASE ANNOUNCEMENTS and other news always check DEVLOG:
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>> >
>> > For other support material please check also:
>> > http://www.amibroker.com/support.html
>> >
>> > Yahoo! Groups Links
>> >
>> >
>> >
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