Advisor Uni Bot MT5

For this variant of the Expert Advisor to work, there is no need to download the file of the trained neural network, since for the ease of use by the end user of the neural network forex bot, most users encoded a number of neural networks in the body of the bot. Currently, the effectiveness of neural network automated trading systems is applicable to the results of technical analysis. Ideally, a neural network adviser should go through all the stages of the trading process on its own, completely without human participation. Ordinary robots are periodically subject to optimization, you need to correctly configure everything for a profitable result. The combination of the advantages of automatic trading (follow the rules of the strategy, cold calculation) and learning (standard Forex trading programs lack this) will allow the use of the Uni Bot neural network system. According to optimists, neural network advisors are the future of trading. The price does not move chaotically, as the chart does not come close to a straight line. The Forex market still has its own algorithms. Just neural networks will be able to allow even closer approach to their understanding. Despite the variety of robots for the electronic currency market, there is still a temptation to delegate even this role to a computer. The Uni Bot automatic Forex advisor based on a neural network can make this option a reality.

 

How does a neural network robot work?

A neural network Forex trading system must accurately classify events based on incoming data. Conventional Expert Advisors leave the criteria for this approach unchanged. As a result, when the trend changes, he continues to trade according to the old rules and successfully drains your entire Forex account. A robot based on a neural network should automatically recognize the rate update and change the trading rules without the participation of a trader. The neural network of the Uni Bot expert is based on a specially developed architecture (T-INN) Target-IntelNeuroNet. This architecture has advanced learning capabilities on large data sets. The T-INN architecture is distinguished by the fact that it can efficiently train on an unlimited data set while retaining the extrapolation properties of the data. With an increase in the data set, the training time increases, but it is incomparably less than with classical architectures (such as RBF, PNN, GRNN, MADALINE, MLP). And most importantly, with a set of input data of an unlimited size, the neural network will find acceptable solutions to the problem! Consultations on the formation of neural network files and their use by the bot can be obtained in private messages or in the product discussion.

 

• Timeframe - M15.
• The symbol is the majority.
• Leverage - 1:100 or less.
• Spread is not important.
• The commission is irrelevant.
• Testing - all modes.
• The passage of history is complete.
• Optimization is not needed.
• Account type - while hedging.

 

Money Management.

The bot works with a deposit of $1,000 But if you work with a deposit of $10,000, you will significantly reduce the risks. The parameters responsible for money management can be left unchanged for a $1000 deposit.

• MinDeposit,
• LotRounding,
• Lot,
• LevelManyManagement,
• ManyManagement,
• LimitMaxLot.

 

• StopLoss,
• TakeProfit,
• TrailingStart,
• TrailingStop,
• TotalEquityLoss,
• TotalEquityProfit.

• ActiveTF - timeframe of the bot.
• LimitOrders - limits on orders.
• TypeSeries - series type.
• SeriaTrendOn – the series is re-buyed following the trend.
• SeriaAntyTrendOn – the series is re-buyed against the trend.
• BalanceTime - balancing the influence of time on the session.
• BalanceAction - Balancing the active close per series.
• BalanceSynchronization - active close synchronization.
• GridStepSynchronization - synchronization of the distance between the ornedarms of the series.