OHLC

class quantflow.ta.ohlc.OHLC(*, serie: str, period: str | timedelta, index_column: str = 'index', parkinson_variance: bool = False, garman_klass_variance: bool = False, rogers_satchell_variance: bool = False, percent_variance: bool = False)

Aggregates OHLC data over a given period and serie

Optionally calculates the range-based variance estimators for the serie. Range-based estimator are called like that because they are calculated from the difference between the period high and low.

Methods:

garman_klass	Adds Garman Klass variance estimator column to the dataframe
parkinson	Adds parkinson variance column to the dataframe
rogers_satchell	Adds Rogers Satchell variance estimator column to the dataframe
var_column	Returns a polars expression for the OHLC column

Attributes:

garman_klass_variance	add Garman Klass variance column
index_column	column to group by
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
parkinson_variance	add Parkinson variance column
percent_variance	log-transform the variance columns
period	down-sampling period, e.g. 1h, 1d, 1w.
rogers_satchell_variance	add Rogers Satchell variance column
serie	serie to aggregate

garman_klass(df: DataFrame | DataFrame) → DataFrame

Adds Garman Klass variance estimator column to the dataframe

This requires the serie high and low columns to be present.

parkinson(df: DataFrame | DataFrame) → DataFrame

Adds parkinson variance column to the dataframe

This requires the serie high and low columns to be present

rogers_satchell(df: DataFrame | DataFrame) → DataFrame

Adds Rogers Satchell variance estimator column to the dataframe

This requires the serie high and low columns to be present.

var_column(suffix: str) → Expr

Returns a polars expression for the OHLC column

garman_klass_variance: bool

add Garman Klass variance column

index_column: str

column to group by

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

parkinson_variance: bool

add Parkinson variance column

percent_variance: bool

log-transform the variance columns

period: str | timedelta

down-sampling period, e.g. 1h, 1d, 1w

rogers_satchell_variance: bool

add Rogers Satchell variance column

serie: str

serie to aggregate