Introduction

Basic Structure of the Process
MATLAB R2014B for Mac OS and MT5 are used in this demonstration. The proposed method has two major parts; MQL5 script that copies the symbol data from the MT5 terminal to CSV files. The other part is a Matlab script that reads the CSV files and imports the data to the Matlab workspace as a table data structure variable.The MQL5 Script
The first thing is to load the ‘writedatatofile’ script on the respective chart you wish to download data. Ensure the historical data you wish to copy to CSV file is visible on the chart. The script has inputs that specify the various options of copying the method. Below is the screenshot after loading the script.
Choose
the data date range you wish to send to Matlab and the date format of choice.
The script provides the option to copy only the data of the current chart or
all the symbols in the market watch. The script shows the progress of copying
the data to CSV file.
The
CSV file is stored in the common data folder, that is (‘/MQL5/Files/DATA_OHLC/Symbol'). The
script creates the DATA_OHLC folder. Inside that folder contains a folder for
each symbol that is copied. The file created has an extension of the time
frame. For example, if the script is run on a EURUSD daily chart, the file is
named as EURUSD_D1 and if it is on a 4-hour chart, it is named EURUSD_H4.
The Matlab Script
The other step is to extract the CSV data files
on the mql5 common folder to the Matlab workspace. A unique script, like the
one below (EURUSD) is developed to extract data for each symbol.
The second line
of the script directs Matlab to the file path where the CSV file of the symbol
is stored. Replace the file path given to the appropriate one. The appropriate
file path depends on where Metatrader 5 is installed. The script is named after
the name of the symbol; for instance, EURUSD, GBPJPY etcetera. When you type
EURUSD on Matlab’s command window, the script requests the time frame you wish
to import from the CSV files. If you require the daily OHLC, type EURUSD_D1.
Conclusion
When the script
runs smoothly without errors/warnings, the OHLC data and respective dates and
time are imported. The data is stored as a table data structure. The data can
now be pre-processed for further analysis. The proposed method is useful since
it eliminates the repetitive process of having to copy the data from excel
files into Matlab workspace. It is suitable when you require to importing huge
data from MT5 to Matlab frequently.
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