pivot_points

Compute pivot-point support and resistance bands under multiple methods.

Examples

from openbb import obb
# Classic daily pivot points on TSLA.
data = obb.equity.price.historical(symbol='TSLA', start_date='2023-01-01', provider='fmp').results
pivots = obb.technical.pivot_points(data=data, method='classic', anchor='day')
obb.technical.pivot_points(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

• standard

data: Data | DataFrame | Series | dict | list | list[DataFrame] | list[Data] | list[Series] | ndarray
OHLC price series.

index: str
Default: date
Index column name in data, by default "date".

method: str
Default: classic
Pivot-point family. camarilla is the only one that fills r4/s4.

anchor: str
Default: day
Resample anchor for the pivot calculation.

---

Returns

results: list[PivotPointsData]

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
Period start date of the resampled pivot.

pivot: float
Central pivot price.

r1: float
First resistance band above the pivot.

r2: float
Second resistance band above the pivot.

r3: float
Third resistance band above the pivot.

r4: float
Only populated for camarilla.

s1: float
First support band below the pivot.

s2: float
Second support band below the pivot.

s3: float
Third support band below the pivot.

s4: float
Only populated for camarilla.