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Greetings all --
I received the following email privately. I think the discussion is important enough to post it to the group.
//--------------------------------------
Dear Howard,
Thanks for your reply in the Amibroker forum. The topic of how to
sort optimisation results is an important one.
You mention several statistics:
KRatio, RRR, UPI, CAR/MDD, RAR/MDD, Recovery Ratio.
Do you have any experience in using trading systems optimised to one
of these?
I'm finding that by optimising for highest account value, I go
through long periods of drawdown, then a small % of trades make a
killing (eg: 46% wins, 2:1 Win to Loss ratio overall). This is not
what I'm looking for.
I'd like to try and smooth out the equity curve to give more of a
balance between making a large capital gain and also regular
cashflow. I have the following stats:
- % Wins
- Win:Loss Ratio (All profits/All losses)
- Risk:Reward
I have found that by sorting results by Risk:Reward does not give
good overall account balances.
//-----------------------------------------------
The experience that writer has is exactly the point I am making when I say that net profit is usually a poor objective function to use when developing trading systems.
Each of the metrics I mentioned have three positive characteristics:
1. they reward equity growth
2. they penalize drawdowns
3. when used as The objective function for walk forward testing, they tend to select systems that perform well out-of-sample
My feeling is that the choice of objective comes very early on in the design, test, and validation process. The objective function incorporates the features that the trader wants in his or her trading, so systems that rank well by using the score of that objective function are systems that the person knows they will be comfortable with.
If one of those metrics already built in to AmiBroker is not satisfactory, it is easy to create your own metric and have AmiBroker report it for every run and use it in the walk forward testing. The custom metric can include setting limits on percent winners, win to loss ratio, and so forth.
There are several posts over the past few days that discuss this and show examples of how to do it.
Try out whatever you think might work for you. Keep in mind that
optimizing using an objective function that does not include some penalty
for drawdowns and / or reward for equity smoothness is likely to result in systems that have very strange
results and do not perform well out-of-sample.
As always, be sure to
evaluate the results by examining out-of-sample results -- in-sample
results have no value in estimating the likely out-of-sample
performance. NO value. Trading based on in-sample results alone is a certain way to lose your trading account. (Running Monte Carlo permutations on in-sample results does Nothing to improve the likelihood of out-of-sample profitability.)
Thanks for listening,
Howard
www.quantitativetradingsystems.com
On Fri, Mar 14, 2008 at 8:00 AM, dralexchambers < dralexchambers@xxxxxxxxx> wrote:
Does anyone use other Optimisation statistics to rank optimisations
by?
For example, instead of using raw profit gained, does anyone use
Win:Loss Ratio or Risk:Reward ratio - and what have been your
experiences.
Thanks,
Alex
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