Moving Average Convergence / Divergence (MACD)

get_macd(quotes, fast_periods=12, slow_periods=26, signal_periods=9)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`fast_periods`	int, default 12	Number of periods (`F`) for the faster moving average. Must be greater than 0.
`slow_periods`	int, default 26	Number of periods (`S`) for the slower moving average. Must be greater than `fast_periods`.
`signal_periods`	int, default 9	Number of periods (`P`) for the moving average of MACD. Must be greater than or equal to 0.
`candle_part`	CandlePart, default CandlePart.CLOSE	Specify candle part to evaluate. See CandlePart options below.

Historical quotes requirements

You must have at least 2×(S+P) or S+P+100 worth of quotes, whichever is more, to cover the convergence periods. Since this uses a smoothing technique, we recommend you use at least S+P+250 data points prior to the intended usage date for better precision.

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.

CandlePart options

from stock_indicators.indicators.common.enums import CandlePart

type	description
`CandlePart.OPEN`	`open` price
`CandlePart.HIGH`	`high` price
`CandlePart.LOW`	`low` price
`CandlePart.CLOSE`	`close` price
`CandlePart.VOLUME`	`volume`
`CandlePart.HL2`	`(high+low)/2`
`CandlePart.HLC3`	`(high+low+close)/3`
`CandlePart.OC2`	`(open+close)/2`
`CandlePart.OHL3`	`(open+high+low)/3`
`CandlePart.OHLC4`	`(open+high+low+close)/4`

Returns

MACDResults[MACDResult]

This method returns a time series of all available indicator values for the quotes provided.
MACDResults is just a list of MACDResult.
It always returns the same number of elements as there are in the historical quotes.
It does not return a single incremental indicator value.
The first S-1 slow periods will have None values since there’s not enough data to calculate.

⚞ Convergence warning: The first S+P+250 periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.

MACDResult

name	type	notes
`date`	datetime	Date
`macd`	float, Optional	The MACD line is the difference between slow and fast moving averages (`macd = fast_ema - slow_ema`)
`signal`	float, Optional	Moving average of the `macd` line
`histogram`	float, Optional	Gap between of the `macd` and `signal` line
`fast_ema`	float, Optional	Fast Exponential Moving Average
`slow_ema`	float, Optional	Slow Exponential 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_historical_quotes("SPY")

# calculate MACD(12,26,9)
results = indicators.get_macd(quotes, 12, 26, 9)

About Moving Average Convergence / Divergence (MACD)

Created by Gerald Appel, MACD is a simple oscillator view of two converging/diverging exponential moving averages. [Discuss] 💬