mt5-correlation

Calculates correlation coefficient between all symbols in MetaTrader5 Market Watch.

Setup

1. Set up your MetaTrader 5 environment ensuring that all symbols that you would like to assess for correlation are shown in your Market Watch window;
2. Set up your python environment; and
3. Install the required libraries.

pip install -r mt5-correlation/requirements.txt

Usage

If you set up a virtual environment in the Setup step, ensure this is activated. Then run the script.

python -m mt5_correlations/get_correlations.py

A .csv file containing the correlation coefficient for all combinations of sybmols from the MetaTrader market watch will be produced in the current directory.

Symbol 1	Symbol 2	Coefficient	UTC Date From	UTC Date To	Timeframe
OIL-MAR21	OILMn-MAR21	1.0	2021-01-29 11:54:29	2021-02-05 11:54:29	15
EURUSD	EURHKD	0.99980	2021-01-29 11:54:29	2021-02-05 11:54:29	15
OILMn-MAR21	BRENT-APR21	0.99894	2021-01-29 11:54:29	2021-02-05 11:54:29	15
OIL-MAR21	BRENT-APR21	0.99894	2021-01-29 11:54:29	2021-02-05 11:54:29	15
GSOIL-FEB21	BRENT-APR21	0.99605	2021-01-29 11:54:29	2021-02-05 11:54:29	15
GSOIL-FEB21	OILMn-MAR21	0.99543	2021-01-29 11:54:29	2021-02-05 11:54:29	15
GSOIL-FEB21	OIL-MAR21	0.99543	2021-01-29 11:54:29	2021-02-05 11:54:29	15
EU50Cash	FRA40Cash	0.99072	2021-01-29 11:54:29	2021-02-05 11:54:29	15

Customising

Edit get_correlations.py to customise.

The coefficients are calculated only if:

• The smallest set of price data is no less than 90% of the size of the largest set;
• The overlapping prices between both sets of price data contains no less than 90% of the prices in the smallest set;
• The pearsonr p-value for the calculated coefficient is less than 0.05.

These settings can all be changed in the call to Correlation.calculate_coefficient by passing values for max_set_size_diff_pct; overlap_pct; or max_p_value.

coefficient = Correlation.calculate_coefficient(symbol1_prices=symbol1_price_data,
                                                        symbol2_prices=symbol2_price_data, max_set_size_diff_pct=90,
                                                        overlap_pct=90, max_p_value=0.05)

The price data compared is 15 minute price data for the last 7 days. This can be changed by changing the values for the following variables:

utc_to = datetime.now(tz=timezone)
utc_from = utc_to - timedelta(days=7)
timeframe = mt5.TIMEFRAME_M15

The possible values for timeframe are:

Timeframe	Description
TIMEFRAME_M1	1 minute
TIMEFRAME_M2	2 minutes
TIMEFRAME_M3	3 minutes
TIMEFRAME_M4	4 minutes
TIMEFRAME_M5	5 minutes
TIMEFRAME_M6	6 minutes
TIMEFRAME_M10	10 minutes
TIMEFRAME_M12	12 minutes
TIMEFRAME_M12	15 minutes
TIMEFRAME_M20	20 minutes
TIMEFRAME_M30	30 minutes
TIMEFRAME_H1	1 hour
TIMEFRAME_H2	2 hours
TIMEFRAME_H3	3 hours
TIMEFRAME_H4	4 hours
TIMEFRAME_H6	6 hours
TIMEFRAME_H8	8 hours
TIMEFRAME_H12	12 hours
TIMEFRAME_D1	1 day
TIMEFRAME_W1	1 week
TIMEFRAME_MN1	1 month