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PythonLSTM

240 USD

Demo downloaded: 92

Published: 19 April 2023

Current version: 3.2

PythonLSTM

Experts
Yevhen Chystiukhin
Version: 3.2
Updated: 3 April 2024
Activations: 5

This multi-currency Expert Advisor uses 28 currency pairs. For forecasts, the EA uses recurrent neural networks of the LSTM type, models trained in the python language environment, and imported into the EA using a new function in mql5 to load ONNX models

Finally it happened, mql5 developers have recently introduced the ability to load ONNX models in the mql5 language. And this format supports most modern libraries for training neural networks, and this now opens up an unlimited number of possibilities for using artificial intelligence in trading.

Hurry up to be the first to use this powerful tool in trading, because soon neural network advisors will be out of competition, now neural networks and artificial intelligence are developing by leaps and bounds.

How is this Expert Advisor better than the rest on neural networks in the mql5 market? - Previously, it was generally not possible to use neural networks directly in the mql5 language, and all other Expert Advisors are mainly made on self-made neural networks, which cannot compete with neural networks trained using modern machine learning libraries that have been developed and improved over many years. years and developed by a huge number of developers.

The profitability of currency pairs can be viewed in the strategy tester after the test in the "Journal" tab, and disable unprofitable pairs as needed in the adviser settings, or select the most profitable, the Active option. Before the test, set Active = True for all pairs and after the test, turn off the unprofitable pairs Active = False, and you can start trading.

By default, the most profitable 9 pairs out of 28 are selected

The EA was trained from 2016 to 2023, it is necessary to test in the strategy tester from 2022 for Model2 = True, from this period the EA did not know anything about the history during training

Before testing, it is advisable to select the EUR USD currency pair and the H1 hour period

In the strategy tester, set the "Open prices only " trading mode, this will not greatly affect the testing results, but will noticeably speed up the process.

Also, for quick testing, you can turn off the visualization of the strategy tester.

At the end of testing, in the log tab, you can view information on the profitability and maximum drawdown of each pair separately

Description of some of the EA settings

UseSameLotSizeForAllPairs - the ability to select the lot size for each pair separately, true by default, one lot size for all specified by the parameter above
UseMaxAllTakeProfitProcent - enables the global take profit as a percentage of the current profit specified in the MaxAllTakeProfitProcent parameter, after its execution all current orders are closed. Test only on all ticks or 1 minute OHLC
UseMaxStopLossProcent - turns on the global stop loss as a percentage of the current profit specified in the MaxAllStopLossProcent parameter, after its execution, all current orders are closed. Test only on all ticks or 1 minute OHLC
IsDynamicLot - enable automatic formation of the lot size depending on the balance or free margin
is_koef_for_each - if true, then the lot size is formed from the balance for each currency pair separately, if false, then from the total balance or free margin
koef - coefficient for forming the lot size, the larger, the greater the risks
from - formation of the lot size depending on the balance or free margin
CountOfGrid - the number of pending orders in the grid
CountGridBars - the number of last bars in history from which the lowest and highest prices are found to calculate the interval between orders for the grid: MaxPrice and MinPrice
GridKoef - the distance between pending orders in the grid is calculated using the formula (MaxPrice - MinPrice)/ GridKoef
GridKoefBegin, GridKoefEnd - distribution of coefficients for multiplying the price of a pending order in the grid

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This multicurrency Expert Advisor uses 28 currency pairs. For predictions, the advisor uses models trained by the machine learning algorithm in the Python language environment. All signals of this advisor in real time and settings for it can be downloaded from my website forexvisible.com - copy and paste into the browser The Expert Advisor can work with two time intervals H1 and H2 together or separately parameters in the Use Time Intervals group The profitability of currency pairs can be view

240 USD

QBotAI is a trading robot designed to automate trading in financial markets. It uses a reinforcement learning technique called Q-learning to optimize its trading strategies. Q-learning allows the robot to learn from experience through trial and error. The robot constantly interacts with the trading environment, makes trade transactions and receives a reward or penalty depending on the result of the transaction. Over time, QBotAI learns to choose the optimal actions to maximize the reward receive

240 USD

This multi-currency expert advisor uses 28 currency pairs. For predictions, the advisor uses recurrent neural networks of the LSTM type, models trained in the Python language environment, and imported into the advisor using a new function in MQL5 for loading ONNX models. The algorithm of the advisor works simultaneously with two timeframes H15 and H1. Separate neural network models have been trained for each of the 28 pairs for both timeframes. The idea is that the advisor places orders only whe

240 USD

This multicurrency expert uses 29 currency pairs. For forecasts, the advisor uses recurrent neural networks of the LSTM type, models trained in the Python language environment using the reinforcement learning algorithm. You can view and download the advisor's performance results and signal settings here: forexvisible.com and myfxbook.com/members/MUSBREATH The advisor uses 4 different packages of neural network models trained for 29 pairs, the first two models work on the H1 interval and the oth

240 USD

AlphaAI — Multi-Currency AI Expert Advisor for MetaTrader AlphaAI is a multi-currency trading expert advisor using LSTM neural networks trained with reinforcement learning to analyze market data and generate trading decisions. The advisor can trade 29 currency pairs simultaneously, distributing trading activity and reducing dependence on a single market. The models were trained in Python using financial time series analysis. AlphaAI Advantages LSTM machine learning models Trading with 29 cur

240 USD

BetaAI — Multi-Currency AI Expert Advisor for MetaTrader BetaAI is a multi-currency trading expert advisor that uses machine learning models to analyze market data and generate trading decisions. The advisor can simultaneously work with 29 currency pairs , allowing trading activity to be distributed across multiple instruments and reducing dependence on the behavior of a single market. The system is based on machine learning models built with XGB (gradient boosting) . The models were trained in

240 USD

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