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cones

Calculate the realized volatility quantiles over rolling windows of time.

The cones indicator is designed to map out the ebb and flow of price movements through a detailed analysis of volatility quantiles. By examining the range of volatility within specific time frames, it offers a nuanced view of market behavior, highlighting periods of stability and turbulence.

The model for calculating volatility is selectable and can be one of the following:

  • Standard deviation
  • Parkinson
  • Garman-Klass
  • Hodges-Tompkins
  • Rogers-Satchell
  • Yang-Zhang

Read more about it in the model parameter description.

Examples​

from openbb import obb
# Realized Volatility Cones.
stock_data = obb.equity.price.historical(symbol='TSLA', start_date='2023-01-01', provider='yfinance')
cones_data = obb.technical.cones(data=stock_data.results, lower_q=0.25, upper_q=0.75, model='std')
obb.technical.cones(data='[{'date': '2023-01-02', 'open': 110.0, 'high': 120.0, 'low': 100.0, 'close': 115.0, 'volume': 10000.0}, {'date': '2023-01-03', 'open': 165.0, 'high': 180.0, 'low': 150.0, 'close': 172.5, 'volume': 15000.0}, {'date': '2023-01-04', 'open': 146.67, 'high': 160.0, 'low': 133.33, 'close': 153.33, 'volume': 13333.33}, {'date': '2023-01-05', 'open': 137.5, 'high': 150.0, 'low': 125.0, 'close': 143.75, 'volume': 12500.0}, {'date': '2023-01-06', 'open': 132.0, 'high': 144.0, 'low': 120.0, 'close': 138.0, 'volume': 12000.0}]')

Parameters​

data: list[openbb_core.provider.abstract.data.Data]
The data to use for the calculation.

index: str
Default: date
Index column name to use with data, by default 'date'

lower_q: float
Default: 0.25
The lower quantile value for calculations

upper_q: float
Default: 0.75
The upper quantile value for calculations

model: Literal['std', 'parkinson', 'garman_klass', 'hodges_tompkins', 'rogers_satchell', 'yang_zhang']
Default: std
The model used to calculate realized volatility

is_crypto: bool
Whether the data is crypto or not. If True, volatility is calculated for 365 days instead of 252

trading_periods: int
Number of trading periods in a year.

Returns​

results: list[Data]

Serializable results.

provider: None

Provider name.

warnings: Optional[list[Warning_]]

list of warnings.

chart: Optional[Chart]

Chart object.

extra: dict[str, Any]

Extra info.

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