Average True Range (ATR)

Warmup Window

Minimum bars needed: period bars (default params: 14 bars (period=14))

Wilder's RMA needs period bars for the initial average true range. After warmup, ATR updates in real-time on every new bar.

✅ After the warmup window is filled, this indicator produces a new value on every incoming bar in real-time.

Lagging Indicator

ATR readings lag behind actual volatility changes.

Event	Lag	Detail
ATR reacts to a volatility spike	≈ period / 2 bars	Wilder's RMA smoothing over the specified period
ATR reacts to volatility contraction	≈ period / 2 bars	Same smoothing; contractions are also detected late

Formula for custom params: lag ≈ period / 2

The Average True Range (ATR) is a volatility indicator that measures the average range between the high and low prices over a specified period. It helps traders identify potential price fluctuations and adjust their strategies accordingly.

def atr(
    data: Union[PdDataFrame, PlDataFrame],
    source_column="Close",
    period=14,
    result_column="ATR"
) -> Union[PdDataFrame, PlDataFrame]:

Example

from investing_algorithm_framework import download

from pyindicators import atr

pl_df = download(
    symbol="btc/eur",
    market="binance",
    time_frame="1d",
    start_date="2023-12-01",
    end_date="2023-12-25",
    save=True,
    storage_path="./data"
)
pd_df = download(
    symbol="btc/eur",
    market="binance",
    time_frame="1d",
    start_date="2023-12-01",
    end_date="2023-12-25",
    pandas=True,
    save=True,
    storage_path="./data"
)

# Calculate average true range for Polars DataFrame
pl_df = atr(pl_df, source_column="Close")
pl_df.show(10)

# Calculate average true range for Pandas DataFrame
pd_df = atr(pd_df, source_column="Close")
pd_df.tail(10)

Chart Parameters

The image above uses the following parameters:

Parameter	Value
source_column	Close
period	14