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                                                   Ranking Signals in MMScripts

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Vangelis M.
2013-01-13 00:08:57


Hello,
Nice work on the new Globals tab and the DLL importing. These are proving to be very useful.
Few questions:
1. I am defining a system using only the c# Money Managment script. The "Strategy" tab is empty.
I need to rank the buy signals. Should I use the "Ranking" tab and define my rules there or do I need to do my own sorting in the MM script using C# lists?
2. Let's say I have data with bid and ask values only. Sure, I can place those in a custom database. But how to I place an order in the MM script that executes next bar at the ask.
3. Dlls: I successfully hooked up to an outside dll. Can I use a "import ThisDLL" type of statement to shorten the code.
4. Is it possible for the Genetic optimizer to be trained on a mixture of On and Out-of-sample data, the way the Neural Net is trained?

Thanks



QuantShare
2013-01-14 11:44:50

  0

Best Answer
Hi,

1- You have to use your own ranking using C# lists.

2- Use the simulated order:
Example:
Orders.AddLongPosition("AA", 10, Orders.SimulatedOrder(askPrice));

3- It is not possible yet to use "import ThisDLL"

4- You can run the genetic optimizer for a specific period (Let us say 2000-2008) then in the report run an out-of-sample testing for another period (Let us say 2008-2013)




Vangelis M.
2013-01-14 17:25:52

  0

Thanks for the response. Will do.
As for the Genetic Optimizer, I do see that we can test an out-of-sample period once the optimizer is finished. That works fine in order to check if our solutions are acceptable out of sample.
Maybe in the future, the GA's fitness function could be weighted from an in sample performance + Out of sample (evaluation period) performance, so that it provides more robust results. Just an idea.



QuantShare
2013-01-15 11:33:03

  0

In the "Optimize Item" form, click on "Show Report" then use the right panel for "Out-of-sample" testing.
After performing the out-of-sample testing, you will be able to compare the fitness of the in-sample and the fitness of the out-of-sample period.



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