Get forex signal mor than 90% to real signal
ABM Trader signals is a different method than the other common signals in the Forex world. You will receive ABM Trader a month as a general forecast that in this prediction unlike Forex signals that offer their signals by placing diagram in position (transaction) status. ABM Trader signal is a signal that you will receive monthly prediction diagram . in this diagram you will observe predicted flow until next month and based on a flow that will happen you can make the best decision because you will see future market movement that this method is unique in Forex forecasts.
We will ensure you that ABM Trader signal are the most low-risk and the best forecasts in the Forex market.
In this method we will use artificial intelligence (neural network) forecast that we can have closest and most similar diagram than the main market flow.
How to handle position (transact) is that you will be aware of the flow witch will happen in the future by seeing forecast.
This flow in prediction diagram must be considered as a general market flow that you must avoid small (slight) market movement and buy or sell with the general market flow.
Max and min points in this forecast will be determined by us .
how to lot is that you will enter the market with 1/20 capital it means if you have 10000$ investment you can enter the market with 0.5 lot . with this amount of turnover you will get over 40% in a month.
More details:
Put a series of observations in tandem in overtime so called Time series witch can be expressed as vectorial or numerical . in the general case a time series can represent the properties like nonlinearity, chaotic, Non stationarity and alternative such as seasonality . in addition to these done observation witch can be polluted by noise. Since many natural and industrial process are time-varying nature , can be used for modeling of time series that their prediction of engineers and scientists favorite subjects for study. In the general case you can regard the prediction topic by seeing the model of black box (input-output) in identifying systems and you can predict time series by using of estimation function methods. In this case model inputs are past and present of time series and its outputs are future of time series .
In the general case consecutive samples of a time series are dependent to values of past samples , so , we can use of past values to predict future values of samples. this fact can be expressed in the following equation :

Where x(t) the time series samples at the moment f , t is also a function between time series value at the moment t+1
And time series past values and (N1) is also the number of time series values witch are suitable to predict a step ahead x(t+1)
Prediction issues can be assumed as identification nonlinear dynamic systems
Issue and we can utilize algorithms and Criterion used in this field .
a time series nature , being dependent or independent observation is, and therefore , the sequence of observations in that is important . so , statistical methods and techniques , no longer apply and the different method are needed. The statistical methodology configuration refers to Time Series Analysis .
To study the time series , there are different objectives which contain understanding and expression of the production mechanism , predicting future value and control a system .
Mechanism description
When a mechanism is shown by a time series , the first step in analyzing is drawing data and thereupon receiving a series of major series properties.
For example, the regular seasonal changes can be seen in Figure 2.
For some of the time series that their variation is associated with such clear features and a sample model that is only trying to describe these trends and
Seasonal variations.
For other series, more sophisticated techniques are required to provide more accurate analysis.

A time series with seasonal variation : fig 2
Mechanism Analysis
When observations are received in two or more variables we analyze a series of time according to other series variations . this leads us to a deeper understanding of producer data mechanism. For example , this can be interesting if you know how the sea surface affected by the temperature and pressure. And or selling a product or how it is affected by price and economic conditions.
prediction
with a time series may be that we want to predict its future values .that is very considered as a very important matter in economic and industrial prediction. The issue raised here is.
Use word "prediction " or " forecasting " is interchangeably . word "prediction" is used to describe non- objective method and to do its systematic process while word "forecasting" is used for objective methods and look to the future.
Prediction in many application is closely related to the control .
For example we can predict whether a productive process is running or stopped, and if so, corrective action should be done.
Multilayer neural networks
Overview of a neural network is shown in below Fig.

Fig 5:Overview of a neural network
The general structure of a neural network multilayer perceptron neural network is the most used type of neural network structures . they use comprehensive basic functions that is toward nonlinear parameter .
Multilayer neural network for a wide range of issues can be used with different specifications , that it may not show the efficient performance of their own about most of them. One of the most important feature of this network is auto tuning it in the different directions in nonlinear that is available in the process that in fact , most especial benefit is about its issue with high dimensions .
One of the most important activities of ABM trader group is developing and providing relating accurate prediction for the currency trading market that are used of intelligent techniques of neural network and signal s statistical studies .
Currently , prediction of 15 minutes signals Euro to Dollar , (EURUSD, M15) is offered a week prediction.

