• Overview
  • Reviews (6)
  • Comments (30)
  • What's new


This utility is designed to increase the efficiency of manual trading and practicing methods of automatic trading using neural networks, without the need to resort to third-party programs, using import/export of working data. The forward period allows not only testing the strategy on time segments unavailable for optimization, but also stopping the automatic trading under unfavorable conditions.

The genetic algorithm searches for the best parameters of stop loss, take profit, trailing stop for 20 different strategies, or separately for each.

It includes a trade panel for quick work in manual mode without being distracted from working with the program. New method of placing pending orders allows placing orders in two clicks, focusing only on the price chart, disregarding the long figures of the market. The ability to save templates will allow you to quickly assess the market situation without leaving the program.

Visual assessment of indicators from the market has never been so fast. Method for quick visual assessment of indicators allows changing the indicator parameters using a slider, without the need to call the indicator properties window.

  • Sample

Training and testing of the neural network is divided into three stages: training, test, trade.

Training - Network training.

Test - testing the network after each training epoch (if the error is less than the previous, the network is stored).

Trade - this shows the responses of the network to data that the network has not seen during training and testing.

  • Indicators

The network can be fed any indicators normalized to values from -1 to 1. The indicator values must not exceed the extreme values during training.

You can create a set of up to 100 indicators.

  • Supervisor

As a training set, you can select any indicator, built-in Zig Zag or an output of another network.

  • Training

Before training, it is necessary to determine the type of network, each of which has its own special qualities.

Simply put

MLP - a back propagation network, it has good predictive qualities.

GRNN - network with absolute memory.

SOM - separates into the specified number of classes.

  • Trading panel

It is necessary to allow automated trading for the panel to work. To set the price of a pending order, simple click the price chart and press the button of the required order.

  • Optimization

Before starting the optimization, it is necessary to select the strategies to optimize.

Stop Loss, Take Profit, Trailing Stop and trade signal levels are available in optimization.

  • Visual assessment of indicators

The indicator parameters can be changed using the slider. The indicator will be instantly recalculated.

Detailed description

Gennadiy Voltornist
Gennadiy Voltornist 2018.02.09 17:34 

User didn't leave any comment to the rating

Ali irwan
Ali irwan 2017.07.24 15:05   

simple,I like.

Nork 2017.07.21 14:54 

User didn't leave any comment to the rating

Green Tester
Green Tester 2017.03.07 17:53   

Высоко качественный продукт, позволяет создавать и тестировать торговые стратегии

tallman1969 2016.11.05 00:31 

Very interesting! I hope there soon will be an option to export as an indicator/EA.

Rodrigo da Silva Boa
Rodrigo da Silva Boa 2016.01.31 02:27 

User didn't leave any comment to the rating

Version 4.16 2018.03.27
Fixed the zero division error, which occurred in rare cases. The general optimization results for the 10 results of each pass are written to a file, recording the average values.
Version 4.15 2018.03.20
Fixed push notifications. Remote disabling of autotrading.
Version 4.14 2017.11.27
Send Push and Email notifications.
Version 4.13 2017.10.26
Fixed errors.
Version 4.12 2017.09.12
Fixed an error in training of MLP
Version 4.11 2017.03.14
Bug fixes in trade requests.
Version 4.1 2017.03.06
Built-in optimization using 20 possible strategies.
Version 4.0 2016.09.05
Added for learning:
Kohonen neural network,
Hybrid Perceptron.
Version 2.0 2016.04.08
Added GRNN network
Version 1.17 2015.12.18
Fixed errors.
Version 1.16 2015.12.03
Genetic weight search.
Version 1.15 2015.11.10
Autoload, auto-trade.
Version 1.13 2015.10.26
Automatic search for levels for trade signals
Version 1.11 2015.10.22
The input of a neural network can be filled with the outputs of other networks.