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thanks silverpike for publishing your findings.
The weekly price prediction. Is that the prediction for the closing price at the end of the week?
If this is the case, I think that your right, a weekly prediction of the close would not be much use to anyone and you indicate that longer time frames are not accurate.
Taking it the other way, would it not be possible and would you not have the same accuracy using your model on an hour by hour basis? or even on a 15 min by 15 min basis
If you knew roughly what the close of each bar was estimated at you could make a good trading strategy from this information
Let me know if I am barking up the wrong tree
Since people are interested, I am going to post my data here for people to use. It is up to you to use them, I am not going to hold anyone's hand because I am also a busy grad student and day trader, and I don't have infinite time to devote to this. I will answer simple questions though if I can.
Also, one little detail that wasn't quite right. I actually obtained 511 weeks of data from Dukascopy. However, I needed to use the first 120 weeks just to generate the 120 week MA, so the first week I can use was week 121.
There are 3 files. Read this part carefully to understand each one.
(1) Weekly GBPUSD data downloaded from Dukascopy in .csv format. 511 weeks. Exactly what you get when you go do Dukascopy.
(2) A generated, preprocessed file. It contains 391 lines, and has 6 values per line. These are the 6 inputs I used to my neural net. The data is ordered as follows: CLOSE, MA5, MA10, MA20, MA60, MA120. These 391 lines should correspond to lines 121 to 511 in the original .csv history file (there are no dates in the data).
(3) The second is my neural predicted prices. There are no dates here either, but it is assumed that each line in the output file matches exactly the one in file #2. These also would correspond to lines 121 to 511 in the original history file. They represent the neural output given the 6 inputs used in file #2 (the next week prediction).
Note that this data can be loaded into Excel, and you can find out almost anything you need by playing with it there. You can graph the predictions (which should match my graph posted earlier) and do all other kinds of error assessment also. That should give anyone who wants to asses the validity of this something to play with.sorry, but can you explain how i should use the files you have attached?
Genetic Algorithms
any body have information about Genetic Algorithms in fn markets?
any body have information about Genetic Algorithms in fn markets?
Silverpike, have you tried feeding the network more inputs? For instance some currency pairs lead/follow others, hence it might be worthwhile giving it data from more than one symbol or maybe indicator data. You say you used Matlab? I've used Matlab briefly at Uni not much thou. Do you have any resources on coding NNs in Matlab?
New article was published -
Deep Neural Networks (Part II). Working out and selecting predictors
Contentsand whole the links related to neural network -
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Neural Network
Neural Network: discussion/development threads
Neural Network: Indicators and systems development
Neural Network: EAs
Neural Network: The Books
The article
Deep Neural Networks (Part II). Working out and selecting predictors - MT5
CodeBase