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Added support for inverse correlations

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This commit is contained in:
Jamie Cash
2021-03-16 15:02:19 +00:00
parent 4fdf4bedc7
commit d0049546fe
4 changed files with 143 additions and 59 deletions
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mt5_correlation/correlation.py
+60 -18
View File
@@ -10,7 +10,6 @@ from scipy.stats.stats import pearsonr
import pickle
import inspect
import sys
import numpy as np
from mt5_correlation.mt5 import MT5
@@ -82,6 +81,9 @@ class Correlation:
# below this threshold will be considered as having diverged
divergence_threshold = 0.8
# Flag to determine we monitor and report on inverse correlations
monitor_inverse = False
# Toggle on whether we are monitoring or not. Set through start_monitor and stop_monitor
__monitoring = False
@@ -106,13 +108,14 @@ class Correlation:
# Dict: {Symbol: [retrieved datetime, ticks dataframe]}
__monitor_tick_data = {}
def __init__(self, monitoring_threshold=0.9, divergence_threshold=0.8):
def __init__(self, monitoring_threshold=0.9, divergence_threshold=0.8, monitor_inverse=False):
"""
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.
:param monitor_inverse: Whether we will monitor and report on negative / inverse correlations.
"""
# Logger
self.__log = logging.getLogger(__name__)
@@ -126,19 +129,28 @@ class Correlation:
# Create timer for continuous monitoring
self.__scheduler = sched.scheduler(time.time, time.sleep)
# Set thresholds
# Set thresholds and flags
self.monitoring_threshold = monitoring_threshold
self.divergence_threshold = divergence_threshold
self.monitor_inverse = monitor_inverse
@property
def filtered_coefficient_data(self):
"""
:return: Coefficient data filtered so that all base coefficients >= monitoring_threshold
"""
filtered_data = None
if self.coefficient_data is not None:
return self.coefficient_data.loc[self.coefficient_data['Base Coefficient'] >= self.monitoring_threshold]
else:
return None
if self.monitor_inverse:
filtered_data = self.coefficient_data \
.loc[(self.coefficient_data['Base Coefficient'] >= self.monitoring_threshold) |
(self.coefficient_data['Base Coefficient'] <= self.monitoring_threshold * -1)]
else:
filtered_data = self.coefficient_data.loc[self.coefficient_data['Base Coefficient'] >=
self.monitoring_threshold]
return filtered_data
def load(self, filename):
"""
@@ -495,7 +507,7 @@ class Correlation:
if self.coefficient_data is not None and len(self.coefficient_data.index) > 0:
data = self.coefficient_data.copy()
# Filter by symols if specified
# Filter by symbols if specified
data = data.loc[data['Symbol 1'] == symbol1] if symbol1 is not None else data
data = data.loc[data['Symbol 2'] == symbol2] if symbol2 is not None else data
@@ -511,6 +523,23 @@ class Correlation:
return last_calc
def get_base_coefficient(self, symbol1, symbol2):
"""
Returns the base coefficient for the specified symbol pair
:param symbol1:
:param symbol2:
:return:
"""
base_coefficient = None
if self.coefficient_data is not None:
row = self.coefficient_data[(self.coefficient_data['Symbol 1'] == symbol1) &
(self.coefficient_data['Symbol 2'] == symbol2)]
if row is not None and len(row) == 1:
base_coefficient = row.iloc[0]['Base Coefficient']
return base_coefficient
def __monitor(self):
"""
The actual monitor method. Private. This should not be called outside of this class. Use start_monitoring and
@@ -664,8 +693,11 @@ class Correlation:
(self.coefficient_data['Symbol 2'] == symbol2),
'Last Calculation'] = now
# Are we an inverse correlation
inverse = self.get_base_coefficient(symbol1, symbol2) <= self.monitoring_threshold * -1
# Calculate status and update
status = self.__calculate_status(coefficients=coefficients)
status = self.__calculate_status(coefficients=coefficients, inverse=inverse)
self.coefficient_data.loc[(self.coefficient_data['Symbol 1'] == symbol1) &
(self.coefficient_data['Symbol 2'] == symbol2),
'Status'] = status
@@ -676,22 +708,32 @@ class Correlation:
data=[[symbol1, symbol2, coefficients[key], key, date_to]])
self.coefficient_history = self.coefficient_history.append(row)
def __calculate_status(self, coefficients):
def __calculate_status(self, coefficients, inverse):
"""
Calculates the status from the supplied set of coefficients
:param coefficients: Dict of timeframes and coefficients {timeframe: coefficient} to calculate status from
:param: Whether we are calculating status based on normal or inverse correlation
:return: status
"""
status = None
status = STATUS_NOT_CALCULATED
values = coefficients.values()
if None in values:
status = STATUS_NOT_CALCULATED
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
if None not in values:
if self.monitor_inverse and inverse:
# Calculation for inverse calculations
if all(i <= self.divergence_threshold * -1 for i in values):
status = STATUS_ABOVE_DIVERGENCE_THRESHOLD
elif all(i > self.divergence_threshold * -1 for i in values):
status = STATUS_BELOW_DIVERGENCE_THRESHOLD
else:
status = STATUS_INCONSISTENT
else:
# Calculation for standard correlations
if 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
return status
mt5_correlation/gui.py
+21 -8
View File
@@ -52,7 +52,8 @@ class MonitorFrame(wx.Frame):
# Create correlation instance to maintain state of calculated coefficients. Set min coefficient from config
self.__cor = cor.Correlation(monitoring_threshold=self.__config.get("monitor.monitoring_threshold"),
divergence_threshold=self.__config.get("monitor.divergence_threshold"))
divergence_threshold=self.__config.get("monitor.divergence_threshold"),
monitor_inverse=self.__config.get("monitor.monitor_inverse"))
# 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.
@@ -221,12 +222,8 @@ class MonitorFrame(wx.Frame):
"""
self.__log.debug(f"Refreshing grid. Timer running: {self.timer.IsRunning()}")
# Get coefficient data and join to history data
coef_data = self.__cor.coefficient_data.copy()
hist_data = self.__cor.get_coefficient_history()
# Update data
self.table.data = self.__cor.coefficient_data.copy()
self.table.data = self.__cor.filtered_coefficient_data.copy()
# Format
self.table.data.loc[:, 'Base Coefficient'] = self.table.data['Base Coefficient'].map('{:.5f}'.format)
@@ -426,7 +423,9 @@ class MonitorFrame(wx.Frame):
# Display if we have any data
self.__log.debug(f"Refreshing history graph {symbol1}:{symbol2}.")
self.__graph.draw(prices=[symbol_1_price_data, symbol_2_price_data], ticks=[symbol_1_ticks, symbol_2_ticks],
history=[history_data_short, history_data_med, history_data_long], symbols=[symbol1, symbol2])
history=[history_data_short, history_data_med, history_data_long], symbols=[symbol1, symbol2],
divergence_threshold=self.__cor.divergence_threshold,
monitor_inverse=self.__cor.monitor_inverse)
# Un-hide and layout if hidden
if not self.__graph.IsShown():
@@ -552,13 +551,17 @@ class GraphPanel(wx.Panel):
self.__axes = None
self.__fig = None
def draw(self, prices=None, ticks=None, history=None, symbols=None):
def draw(self, prices=None, ticks=None, history=None, symbols=None, divergence_threshold=None,
monitor_inverse=False):
"""
Plot the correlations.
:param prices: Price data used to calculate base coefficient. List [Symbol1 Price Data, Symbol 2 Price Data]
:param ticks: Ticks used to calculate last coefficient. List [Symbol1, Symbol2]
:param history: Coefficient history data. List of data for one or more timeframes.
:param symbols: Symbols. List [Symbol1, Symbol2]
:param divergence_threshold: The divergence threshold. Will be plotted on the coefficients charts if specified.
:param monitor_inverse: Are we monitoring inverse correlations. If so, a line for the inverse threshold will be
plotted if the divergence threshold is specified.
:return:
"""
@@ -638,6 +641,10 @@ class GraphPanel(wx.Panel):
f"{Config().get('monitor.calculations.medium.from')} Minutes",
f"{Config().get('monitor.calculations.short.from')} Minutes"]]
# lines
horiz_lines = [None, None, None, None, [divergence_threshold, divergence_threshold * -1
if divergence_threshold is not None and monitor_inverse else None]]
# Draw 5 charts
for index in range(0, len(self.__axes)):
# Titles and axis labels
@@ -679,6 +686,12 @@ class GraphPanel(wx.Panel):
else:
self.__axes[index].set_xticklabels([])
# Lines
if horiz_lines[index] is not None and isinstance(horiz_lines[index], list):
for line_pos in horiz_lines[index]:
if line_pos is not None:
self.__axes[index].axhline(y=line_pos, color="red", label='_nolegend_', linewidth=1)
# Legends
if legends[index] is not None:
self.__axes[index].legend(legends[index])