Forex HFT Deep Learning Robot

Forex HFT Deep Learning Robot review:

Modern techniques like artificial neural networks (ANN) are best used for high-frequency trading for several reasons. First, they mimic human intelligence but they mostly don’t reach a human’s level of intelligence, therefore, there is no point in using those techniques on a time scale at which a human could easily be working. Their advantage comes from the speed of operation and constant activity. Second, we need a lot of data to train neural networks efficiently and this amount of data will only be found in high-frequency trading. Forex has all in all quite few instruments with limited relevant past data on the daily or weekly time-scale.

Furthermore, High-frequency trading is a type of scalping strategy where we identify noise around the true value of the instrument. This is different from long-term trading that attempts to follow meaningful movements of the instrument according to fundamental analysis. A good time-scale to work on is the minute time-scale. This time-scale is full of noise which will be captured by the algorithm in order to sell and buy during the strong movements of the market. That is why it is irrelevant to take old data to predict these movements over a period of one minute.


To improve the performance and robustness of HFTs, the following issues need to be addressed:

  1. Message latency:
    To achieve message latency, the underlying network should be made of high-performance computing elements. Low latency networks are critical for timely message passing. A lot of brokers are providing co-location facilities to minimize network latency. Improving the message latency will also reduce the time taken between the decision making and execution.
  2. High-performance computing:
    A high-performance computing setup is vital for Forex HFT Deep Learning Robot. This will enable the ability to price and calculate risks and positions at portfolio scale in near real time. It will also support the ability to analyze data and performance after the execution to identify and evaluate market strategies thus creating a platform for informed decision making. This is a primary requirement of HFT.


Deposit: $100

Test results:

Forex HFT Deep Learning Robot


  • Take Profit
  • Stop Loss
  • Fixed Lot Size
  • Use Money Management
  • Risk Percent – Risk per trade
  • Candle Size – Minimum candle size for entry in points
  • Magic Number
  • Expert Comment
  • Max Spread In Points
  • Trailing Stop
  • MA Period – Moving average period
  • MA Method – Moving average Method
  • RSI Period
  • Limit Trade Per Candle – Use max number of trades per candle
  • Max Trades Per Candle – Max number of trades per candle
  • Close Trade At End Of Candle
  • Send Push Notification on Entry
  • Hide SL/TP From Your Broker
  • Weight 0… Weight 9 – The weights in an artificial neural network are an approximation of multiple processes combined that take place in biological neurons
  • Trade on Monday
  • Trade on Tuesday
  • Trade on Wednesday
  • Trade on Thursday
  • Trade on Friday
  • Using Trade Hour
  • Start Hour – Start hour for trading
  • End Hour – End hour for trading


Copy and paste the file into the MQL4 Experts folder of the Metatrader 4 trading platform.

You can access this folder from the top menu as follows:

File > Open Data Folder > MQL4 > Experts (paste here)

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