Included diverging and converging status calculation
This commit is contained in:
Jamie Cash
+9
-9
@@ -8,23 +8,23 @@ calculate:
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overlap_pct: 90
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max_p_value: 0.05
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monitor:
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interval: 10
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interval: 20
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calculations:
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long:
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from: 60
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min_prices: 2000
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from: 30
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min_prices: 300
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max_set_size_diff_pct: 50
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overlap_pct: 50
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max_p_value: 0.05
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medium:
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from: 30
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min_prices: 1000
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from: 10
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min_prices: 100
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max_set_size_diff_pct: 50
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overlap_pct: 50
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max_p_value: 0.05
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short:
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from: 10
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min_prices: 200
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from: 2
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min_prices: 30
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max_set_size_diff_pct: 50
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overlap_pct: 50
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max_p_value: 0.05
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@@ -72,8 +72,8 @@ logging:
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developer:
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inspection: false
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window:
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x: 24
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y: 38
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x: 101
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y: 9
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width: 1510
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height: 956
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style: 541072960
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@@ -58,11 +58,20 @@ class CorrelationStatus:
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# All status's for symbol pair from monitoring. Status set from assessing coefficient for all timeframes from last run.
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STATUS_NOT_CALCULATED = CorrelationStatus(-1, 'NOT CALC', 'Coefficient could not be calculated')
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STATUS_ABOVE_DIVERGENCE_THRESHOLD = CorrelationStatus(1, 'ABOVE', 'All coefficients equal to or above the divergence '
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'threshold')
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STATUS_BELOW_DIVERGENCE_THRESHOLD = CorrelationStatus(2, 'BELOW', 'All coefficients below the divergence threshold')
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STATUS_CORRELATED = CorrelationStatus(1, 'CORRELATED', 'Coefficients for all timeframes are equal to or above the '
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'divergence threshold')
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STATUS_DIVERGED = CorrelationStatus(2, 'DIVERGED', 'Coefficients for all timeframes are below the divergence threshold')
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STATUS_INCONSISTENT = CorrelationStatus(3, 'INCONSISTENT', 'Coefficients not consistently above or below divergence '
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'threshold')
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'threshold and are neither trending towards divergence or '
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'convergence')
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STATUS_DIVERGING = CorrelationStatus(4, 'DIVERGING', 'Coefficients, when ordered by timeframe, are trending '
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'towards convergence. The shortest timeframe is below the '
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'divergence threshold and the longest timeframe is above the '
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'divergence threshold')
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STATUS_CONVERGING = CorrelationStatus(5, 'CONVERGING', 'Coefficients, when ordered by timeframe, are trending '
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'towards divergence. The shortest timeframe is above the '
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'divergence threshold and the longest timeframe is below the '
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'divergence threshold')
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class Correlation:
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@@ -223,7 +232,7 @@ class Correlation:
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# Loop through all symbol pair combinations and calculate coefficient. Make sure you don't double count pairs
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# eg. (USD/GBP AUD/USD vs AUD/USD USD/GBP). Use grid of all symbols with i and j axis. j starts at i + 1 to
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# avoid duplicating. We will store all coefficients in a dataframe for export as CSV.
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# avoid duplicating. We will store all coefficients in a dataframe.
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index = 0
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# There will be (x^2 - x) / 2 pairs where x is number of symbols
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num_pair_combinations = int((len(symbols) ** 2 - len(symbols)) / 2)
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@@ -387,8 +396,8 @@ class Correlation:
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symbol1_prices_filtered = symbol1_prices[symbol1_prices['time'].isin(intersect_dates)]
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symbol2_prices_filtered = symbol2_prices[symbol2_prices['time'].isin(intersect_dates)]
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# Calculate coefficient. Only use if p value is < 0.01 (highly likely that coefficient is valid and null
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# hypothesis is false).
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# Calculate coefficient. Only use if p value is < max_p_value (highly likely that coefficient is valid
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# and null hypothesis is false).
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coefficient_with_p_value = pearsonr(symbol1_prices_filtered['close'], symbol2_prices_filtered['close'])
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coefficient = None if coefficient_with_p_value[1] > max_p_value else coefficient_with_p_value[0]
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@@ -716,23 +725,36 @@ class Correlation:
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:return: status
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"""
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status = STATUS_NOT_CALCULATED
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values = coefficients.values()
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if None not in values:
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# Only continue if we have calculated all coefficients, otherwise we will return STATUS_NOT_CALCULATED
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if None not in coefficients.values():
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# Get the values ordered by timeframe descending
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ordered_values = []
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for key in sorted(coefficients, reverse=True):
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ordered_values.append(coefficients[key])
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if self.monitor_inverse and inverse:
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# Calculation for inverse calculations
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if all(i <= self.divergence_threshold * -1 for i in values):
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status = STATUS_ABOVE_DIVERGENCE_THRESHOLD
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elif all(i > self.divergence_threshold * -1 for i in values):
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status = STATUS_BELOW_DIVERGENCE_THRESHOLD
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if all(i <= self.divergence_threshold * -1 for i in ordered_values):
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status = STATUS_CORRELATED
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elif all(i > self.divergence_threshold * -1 for i in ordered_values):
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status = STATUS_DIVERGED
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elif all(ordered_values[i] <= ordered_values[i+1] for i in range(0, len(ordered_values)-1, 1)):
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status = STATUS_CONVERGING
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elif all(ordered_values[i] > ordered_values[i+1] for i in range(0, len(ordered_values)-1, 1)):
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status = STATUS_DIVERGING
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else:
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status = STATUS_INCONSISTENT
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else:
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# Calculation for standard correlations
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if all(i >= self.divergence_threshold for i in values):
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status = STATUS_ABOVE_DIVERGENCE_THRESHOLD
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elif all(i < self.divergence_threshold for i in values):
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status = STATUS_BELOW_DIVERGENCE_THRESHOLD
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if all(i >= self.divergence_threshold for i in ordered_values):
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status = STATUS_CORRELATED
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elif all(i < self.divergence_threshold for i in ordered_values):
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status = STATUS_DIVERGED
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elif all(ordered_values[i] <= ordered_values[i+1] for i in range(0, len(ordered_values)-1, 1)):
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status = STATUS_DIVERGING
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elif all(ordered_values[i] > ordered_values[i+1] for i in range(0, len(ordered_values)-1, 1)):
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status = STATUS_CONVERGING
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else:
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status = STATUS_INCONSISTENT
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@@ -510,8 +510,10 @@ class DataTable(wx.grid.GridTableBase):
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# Is status one of interest
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value = self.GetValue(row, col)
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if value != "":
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if value in [cor.STATUS_BELOW_DIVERGENCE_THRESHOLD]:
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attr.SetBackgroundColour(wx.YELLOW)
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if value in [cor.STATUS_DIVERGING]:
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attr.SetBackgroundColour(wx.RED)
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elif value in [cor.STATUS_CONVERGING]:
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attr.SetBackgroundColour(wx.GREEN)
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else:
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attr.SetBackgroundColour(wx.WHITE)
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