Price forecast using neural networks
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  1. #1
    Senior Member fxtester's Avatar
    Join Date
    Nov 2008

    Default Price forecast using neural networks

    Neural Networks - adjustable model in which way - this input function. It consists of several layers:

    - input level, which contains the input data;
    - a hidden layer containing the processing units, which are called neurons
    - output level, consisting of one or more neurons, which output data are output across the network.

    All nodes of adjacent layers are interconnected. These connections are called synapses. Each synapse has a designated rate at which data is transmitted across the synapse, multiplied. This ratio is called a weight (w [i] [j] [k]). The neural network of direct distribution (Feed-Forward Neural Network, FFNN) data distributed from inputs to outputs. Here FFNN example with one input layer, one output and two hidden layers.

    Source : http://Ценовой прогноз с использован...; MetaTrader 4

    Put BPNN.dll into MQL4 > Libraries.
    BPNN_Predictor.mq4 and BPNN_Predictor_with_Smoothing.mq4 into MQL4 > indicators.
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    Last edited by fxtester; 06-16-2016 at 07:35.

  2. #2


    thank you for this indicator

  3. #3
    Junior Member
    Join Date
    Feb 2009


    I tried to back-test this BPNN indicator to check the accuracy to predict the color(Green = Bull, Red = Bear) of the current Bar at the opening for GBPUSD H1 chart. I found that it is about 54% over 239 bars. This number varies for each back testing run because it is based on neural network and that is quite ok. But the predictability appears to be in low fifties. Just wanted to let people know my results of back-testing.

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Price forecast using neural networks