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>>If the system is back-tested on market data which is similar to our recent
>>history, it would most likely provide flat results. The
>>system needs different market conditions to perform better.
That is why I advocate a self optimizing code. The system should analyze its
own trades and trading decisions against real market conditions and optimize
itself to adjust to new market conditions.
A Neural Net working in conjunction with the correct set of data, which
would need to present to the NN a wide variety of input data configurations
(about 30 configurations of input data), and most important, providing a
feedback loop of historical performance versus desired performance, one
should be able to create a self optimizing system.
Treasure
[is where you find it]
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