Moving Average Envelope (MAE)

Warmup Window

Minimum bars needed: period bars (default params: 20 bars (period=20))

The base moving average needs period bars. Bands are a fixed % offset, so they have the same warmup. After warmup, all bands update in real-time.

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

Lagging Indicator

The envelope bands lag behind price because they are offset from a moving average.

Event	Lag	Detail
Middle line reacts to price reversal	≈ `period / 2` bars	Base MA has lag ≈ period/2
Bands shift after a price move	≈ `period / 2` bars	Bands are fixed % offset from the MA; they move in lockstep with the MA

Formula for custom params: lag ≈ period / 2

Moving Average Envelopes are percentage-based envelopes set above and below a moving average. The moving average forms the base, and the envelopes are set at a fixed percentage above and below. This indicator is useful for identifying overbought/oversold conditions, spotting trend direction, and finding support and resistance levels.

def moving_average_envelope(
    data: Union[PdDataFrame, PlDataFrame],
    source_column: str = 'Close',
    period: int = 20,
    percentage: float = 2.5,
    ma_type: str = 'sma',
    middle_column: str = 'ma_envelope_middle',
    upper_column: str = 'ma_envelope_upper',
    lower_column: str = 'ma_envelope_lower'
) -> Union[PdDataFrame, PlDataFrame]:

Example

from investing_algorithm_framework import download

from pyindicators import moving_average_envelope

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 Moving Average Envelope for Polars DataFrame
pl_df = moving_average_envelope(pl_df, source_column="Close", period=20, percentage=2.5)
pl_df.show(10)

# Calculate Moving Average Envelope for Pandas DataFrame
pd_df = moving_average_envelope(pd_df, source_column="Close", period=20, percentage=2.5)
pd_df.tail(10)

MOVING_AVERAGE_ENVELOPE

Chart Parameters

The image above uses the following parameters:

Parameter	Value
`source_column`	`Close`
`period`	`20`
`percentage`	`2.5`