updated values to match with custom covariance function
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8c159062f5
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@ -169,7 +169,7 @@ class TestBeta:
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sts = pft.TimeSeries(stock_data, "D")
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mts = pft.TimeSeries(market_data, "D")
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beta = pft.beta(sts, mts, frequency="D", return_period_unit="days", return_period_value=1)
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assert round(beta, 4) == 1.6001
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assert round(beta, 4) == 1.5997
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def test_beta_daily_freq_daily_returns(self, create_test_data):
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market_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D)
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@ -177,7 +177,7 @@ class TestBeta:
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sts = pft.TimeSeries(stock_data, "D")
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mts = pft.TimeSeries(market_data, "D")
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beta = pft.beta(sts, mts)
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assert round(beta, 4) == 1.6292
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assert round(beta, 4) == 1.6287
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def test_beta_monthly_freq(self, create_test_data):
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market_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D)
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@ -185,7 +185,7 @@ class TestBeta:
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sts = pft.TimeSeries(stock_data, "D")
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mts = pft.TimeSeries(market_data, "D")
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beta = pft.beta(sts, mts, frequency="M")
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assert round(beta, 4) == 1.629
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assert round(beta, 4) == 1.6137
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def test_beta_monthly_freq_monthly_returns(self, create_test_data):
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market_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D)
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@ -193,4 +193,4 @@ class TestBeta:
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sts = pft.TimeSeries(stock_data, "D")
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mts = pft.TimeSeries(market_data, "D")
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beta = pft.beta(sts, mts, frequency="M", return_period_unit="months", return_period_value=1)
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assert round(beta, 4) == 1.6023
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assert round(beta, 4) == 1.5887
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