gavindiaz/mt5-correlation
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Used monitoring_threshold to calculate status.

Browse Source
This commit is contained in:
Jamie Cash
2021-03-15 11:30:08 +00:00
parent 21ea7eb809
commit 4fdf4bedc7
4 changed files with 43 additions and 30 deletions
Download Patch File Download Diff File Expand all files Collapse all files
config.yaml
+6 -6
View File
@@ -13,14 +13,14 @@ monitor:
long:
from: 60
min_prices: 2000
max_set_size_diff_pct: 90
overlap_pct: 90
max_set_size_diff_pct: 50
overlap_pct: 50
max_p_value: 0.05
medium:
from: 30
min_prices: 1000
max_set_size_diff_pct: 90
overlap_pct: 90
max_set_size_diff_pct: 50
overlap_pct: 50
max_p_value: 0.05
short:
from: 10
@@ -71,8 +71,8 @@ logging:
developer:
inspection: false
window:
x: 37
y: 42
x: 24
y: 38
width: 1510
height: 956
style: 541072960
mt5_correlation/correlation.py
+23 -8
View File
@@ -59,10 +59,10 @@ class CorrelationStatus:
# All status's for symbol pair from monitoring. Status set from assessing coefficient for all timeframes from last run.
STATUS_NOT_CALCULATED = CorrelationStatus(-1, 'NOT CALC', 'Coefficient could not be calculated')
STATUS_ABOVE_MONITORING_THRESHOLD = CorrelationStatus(1, 'ABOVE', 'All coefficients equal to or above the monitoring '
STATUS_ABOVE_DIVERGENCE_THRESHOLD = CorrelationStatus(1, 'ABOVE', 'All coefficients equal to or above the divergence '
'threshold')
STATUS_BELOW_MONITORING_THRESHOLD = CorrelationStatus(2, 'BELOW', 'All coefficients below the monitoring threshold')
STATUS_INCONSISTENT = CorrelationStatus(3, 'INCONSISTENT', 'Coefficients not consistently above or below monitoring '
STATUS_BELOW_DIVERGENCE_THRESHOLD = CorrelationStatus(2, 'BELOW', 'All coefficients below the divergence threshold')
STATUS_INCONSISTENT = CorrelationStatus(3, 'INCONSISTENT', 'Coefficients not consistently above or below divergence '
'threshold')
@@ -78,6 +78,10 @@ class Correlation:
# coefficient than ths won't be monitored.
monitoring_threshold = 0.9
# Threshold for divergence. Correlation coefficients that were previously above the monitoring_threshold and fall
# below this threshold will be considered as having diverged
divergence_threshold = 0.8
# Toggle on whether we are monitoring or not. Set through start_monitor and stop_monitor
__monitoring = False
@@ -102,7 +106,14 @@ class Correlation:
# Dict: {Symbol: [retrieved datetime, ticks dataframe]}
__monitor_tick_data = {}
def __init__(self):
def __init__(self, monitoring_threshold=0.9, divergence_threshold=0.8):
"""
Initialises the Correlation class.
:param monitoring_threshold: Only correlations that are greater than or equal to this threshold will be
monitored.
:param divergence_threshold: Correlations that are being monitored and fall below this threshold are considered
to have diverged.
"""
# Logger
self.__log = logging.getLogger(__name__)
@@ -115,6 +126,10 @@ class Correlation:
# Create timer for continuous monitoring
self.__scheduler = sched.scheduler(time.time, time.sleep)
# Set thresholds
self.monitoring_threshold = monitoring_threshold
self.divergence_threshold = divergence_threshold
@property
def filtered_coefficient_data(self):
"""
@@ -672,10 +687,10 @@ class Correlation:
if None in values:
status = STATUS_NOT_CALCULATED
elif all(i >= self.monitoring_threshold for i in values):
status = STATUS_ABOVE_MONITORING_THRESHOLD
elif all(i < self.monitoring_threshold for i in values):
status = STATUS_BELOW_MONITORING_THRESHOLD
elif all(i >= self.divergence_threshold for i in values):
status = STATUS_ABOVE_DIVERGENCE_THRESHOLD
elif all(i < self.divergence_threshold for i in values):
status = STATUS_BELOW_DIVERGENCE_THRESHOLD
else:
status = STATUS_INCONSISTENT
mt5_correlation/gui.py
+7 -7
View File
@@ -6,8 +6,7 @@ import matplotlib.dates
import matplotlib
import matplotlib.ticker as mticker
from mt5_correlation import correlation
from mt5_correlation.correlation import Correlation
from mt5_correlation import correlation as cor
from mt5_correlation.config import Config, SettingsDialog
from datetime import datetime, timedelta
import pytz
@@ -52,8 +51,8 @@ class MonitorFrame(wx.Frame):
self.__config = Config()
# Create correlation instance to maintain state of calculated coefficients. Set min coefficient from config
self.__cor = Correlation()
self.__cor.monitoring_threshold = self.__config.get("monitor.monitoring_threshold")
self.__cor = cor.Correlation(monitoring_threshold=self.__config.get("monitor.monitoring_threshold"),
divergence_threshold=self.__config.get("monitor.divergence_threshold"))
# Status bar. 2 fields, one for monitoring status and one for general status. On open, monitoring status is not
# monitoring. SetBackgroundColour will change colour of both. Couldn't find a way to set on single field only.
@@ -512,7 +511,7 @@ class DataTable(wx.grid.GridTableBase):
# Is status one of interest
value = self.GetValue(row, col)
if value != "":
if value in [correlation.STATUS_BELOW_MONITORING_THRESHOLD]:
if value in [cor.STATUS_BELOW_DIVERGENCE_THRESHOLD]:
attr.SetBackgroundColour(wx.YELLOW)
else:
attr.SetBackgroundColour(wx.WHITE)
@@ -565,8 +564,9 @@ class GraphPanel(wx.Panel):
# Check what data we have available
price_data_available = prices is not None and len(prices) == 2 and \
prices[0] is not None and prices[1] is not None
tick_data_available = ticks is not None and len(ticks) == 2 and ticks[0] is not None and ticks[1] is not None
prices[0] is not None and prices[1] is not None and len(prices[0]) > 0 and len(prices[1]) > 0
tick_data_available = ticks is not None and len(ticks) == 2 and ticks[0] is not None and ticks[1] is not None \
and len(ticks[0]) > 0 and len(ticks[1]) > 0
history_data_available = history is not None and len(history) > 0
symbols_selected = symbols is not None and len(symbols) == 2
test/test_correlation.py
+7 -9
View File
@@ -173,8 +173,8 @@ class TestCorrelation(unittest.TestCase):
# Mock symbol return values
mock.symbols_get.return_value = self.mock_symbols
# Create correlation class
cor = correlation.Correlation()
# Create correlation class. We will set a divergence threshold so that we can test status.
cor = correlation.Correlation(divergence_threshold=0.8)
# Calculate for price data. We should have 100% matching dates in sets. Get prices should be called 3 times.
# We dont have a SYMBOL2 as this is set as not visible. All pairs should be correlated for the purpose of this
@@ -185,9 +185,6 @@ class TestCorrelation(unittest.TestCase):
cor.calculate(date_from=self.start_date, date_to=self.end_date, timeframe=5, min_prices=100,
max_set_size_diff_pct=100, overlap_pct=100, max_p_value=1)
# Set the monitoring threshold
cor.monitoring_threshold = 0.9
# We will build some tick data for each symbol and patch it in. Tick data will be from 10 seconds ago to now.
# We only need to patch in one set of tick data for each symbol as it will be cached.
columns = ['time', 'ask']
@@ -232,10 +229,11 @@ class TestCorrelation(unittest.TestCase):
'Timeframe': 0.66})),
2, "We should have 2 history records for SYMBOL1:SYMBOL2 using the 0.66 min timeframe.")
# The status should be BELOW for SYMBOL1:SYMBOL2 and SYMBOL1:SYMBOL4. It should be ABOVE for SYMBOL2:SYMBOL4.
self.assertTrue(cor.get_last_status('SYMBOL1', 'SYMBOL2') == correlation.STATUS_BELOW_MONITORING_THRESHOLD)
self.assertTrue(cor.get_last_status('SYMBOL1', 'SYMBOL4') == correlation.STATUS_BELOW_MONITORING_THRESHOLD)
self.assertTrue(cor.get_last_status('SYMBOL2', 'SYMBOL4') == correlation.STATUS_ABOVE_MONITORING_THRESHOLD)
# The status should be BELOW for SYMBOL1:SYMBOL2, and should be ABOVE for and SYMBOL1:SYMBOL4 and
# SYMBOL2:SYMBOL4.
self.assertTrue(cor.get_last_status('SYMBOL1', 'SYMBOL2') == correlation.STATUS_BELOW_DIVERGENCE_THRESHOLD)
self.assertTrue(cor.get_last_status('SYMBOL1', 'SYMBOL4') == correlation.STATUS_ABOVE_DIVERGENCE_THRESHOLD)
self.assertTrue(cor.get_last_status('SYMBOL2', 'SYMBOL4') == correlation.STATUS_ABOVE_DIVERGENCE_THRESHOLD)
@patch('mt5_correlation.mt5.MetaTrader5')
def test_load_and_save(self, mock):