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
quotesprovided. MACDResultsis just a list ofMACDResult.- 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-1slow periods will haveNonevalues since there’s not enough data to calculate.
⚞ Convergence warning: The first
S+P+250periods 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] 💬
