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fixes line too long

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Danglewood
2023-02-23 20:20:37 -08:00
parent bcee3aa0c7
commit 64eca4c85c
3 changed files with 19 additions and 11 deletions
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16
openbb_terminal/common/technical_analysis/volatility_model.py
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@@ -208,13 +208,15 @@ def cones(
It is useful for capturing large price movements during the day.
Garman-Klass volatility extends Parkinson volatility by taking into account the opening and closing price.
As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
As markets are most active during the opening and closing of a trading session,
it makes volatility estimation more accurate.
Hodges-Tompkins volatility is a bias correction for estimation using an overlapping data sample.
It produces unbiased estimates and a substantial gain in efficiency.
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero).
Rogers-Satchell is an estimator for measuring the volatility with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term,
mean return not equal to zero.
Yang-Zhang volatility is the combination of the overnight (close-to-open volatility).
It is a weighted average of the Rogers-Satchell volatility and the open-to-close volatility.
@@ -278,7 +280,8 @@ def cones(
def garman_klass(data, window=30, trading_periods=n_days, clean=True):
"""Garman-Klass volatility extends Parkinson volatility by taking into account the opening and closing price.
As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
As markets are most active during the opening and closing of a trading session.
It makes volatility estimation more accurate.
"""
log_hl = (data["High"] / data["Low"]).apply(np.log)
log_co = (data["Close"] / data["Open"]).apply(np.log)
@@ -317,8 +320,9 @@ def cones(
return result
def rogers_satchell(data, window=30, trading_periods=n_days, clean=True):
"""Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero).
"""Rogers-Satchell is an estimator for measuring the volatility with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term,
mean return not equal to zero.
"""
log_ho = (data["High"] / data["Open"]).apply(np.log)

11
openbb_terminal/common/technical_analysis/volatility_view.py
View File

@@ -380,7 +380,8 @@ def display_cones(
sheet_name: Optional[str] = None,
external_axes: Optional[List[plt.Axes]] = None,
):
"""Plots the realized volatility quantiles for the loaded ticker. The model used to calculate the volatility is selectable.
"""Plots the realized volatility quantiles for the loaded ticker.
The model used to calculate the volatility is selectable.
Parameters
----------
@@ -405,13 +406,15 @@ def display_cones(
It is useful for capturing large price movements during the day.
Garman-Klass volatility extends Parkinson volatility by taking into account the opening and closing price.
As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
As markets are most active during the opening and closing of a trading session;
it makes volatility estimation more accurate.
Hodges-Tompkins volatility is a bias correction for estimation using an overlapping data sample.
It produces unbiased estimates and a substantial gain in efficiency.
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero).
Rogers-Satchell is an estimator for measuring the volatility with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term,
mean return not equal to zero.
Yang-Zhang volatility is the combination of the overnight (close-to-open volatility).
It is a weighted average of the Rogers-Satchell volatility and the open-to-close volatility.

3
openbb_terminal/stocks/technical_analysis/ta_controller.py
View File

@@ -1663,7 +1663,8 @@ class TechnicalAnalysisController(StockBaseController):
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="cones",
description="""
Calculates the realized volatility quantiles over rolling windows of time, with a selectable model for calculating the volatility.
Calculates the realized volatility quantiles over rolling windows of time.
The model for calculating volatility is selectable.
""",
)
parser.add_argument(