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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.

Parameters​

data: list[openbb_core.provider.abstract.data.Data]

The data to use for the calculation.

• Optional: False

index: str

Index column name to use with data, by default 'date'

• Default: date

• Optional: True

lower_q: float

The lower quantile value for calculations

• Default: 0.25

• Optional: True

upper_q: float

The upper quantile value for calculations

• Default: 0.75

• Optional: True

model: Literal['std', 'parkinson', 'garman_klass', 'hodges_tompkins', 'rogers_satchell', 'yang_zhang']

The model used to calculate realized volatility

• Default: std

• Optional: True

is_crypto: bool

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

• Optional: True

trading_periods: int

Number of trading periods in a year.

• Optional: True

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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