hma
Calculate Alan Hull's lag-reduced moving average.
Examples
from openbb import obb
obb.technical.hma(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}], length=4)
Parameters
- standard
data: Data | DataFrame | Series | dict | list | list[DataFrame] | list[Data] | list[Series] | ndarray
Price series.
target: str
Default: close
Column to smooth, by default "close".
index: str
Default: date
Index column name in data, by default "date".
length: int
Default: 50
HMA period.
offset: int
Default: 0
Output offset; positive values shift the series forward, by default 0.
chart: bool
Default: False
Whether to create a chart or not, by default False.
Returns
results: list[HmaData]
Serializable results.
provider: str
Provider name.
warnings: Optional[list[Warning_]]
List of warnings.
chart: Optional[Chart]
Chart object.
extra: dict[str, Any]
Extra info.
Data
- standard
date: date | datetime | str
Observation date.
hma: float
Hull moving average — lag-reduced WMA blend.