Endpoint Moving Average (EPMA)

get_epma(quotes, lookback_periods)

Parameters

name type notes
quotes Iterable[Quote] Iterable of the Quote class or its sub-class.
See here for usage with pandas.DataFrame
lookback_periods int Number of periods (N) in the moving average. Must be greater than 0.

Historical quotes requirements

You must have at least N periods of quotes to cover the warmup periods.

quotes is an Iterable[Quote] collection of historical price quotes. It should have a consistent frequency (day, hour, minute, etc). See the Guide for more information.

Return

EPMAResults[EPMAResult]

EPMAResult

name type notes
date datetime Date
epma float, Optional Endpoint moving average

Utilities

See Utilities and Helpers for more information.

Example

from stock_indicators import indicators

# This method is NOT a part of the library.
quotes = get_history_from_feed("SPY")

# Calculate 20-period EPMA
results = indicators.get_epma(quotes, 20)

About Endpoint Moving Average (EPMA)

Endpoint Moving Average (EPMA), also known as Least Squares Moving Average (LSMA), plots the projected last point of a linear regression lookback window. [Discuss] 💬

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