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OpenBB/website/content/current/platform/reference/technical/macd.md
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macd Learn about the Moving Average Convergence Divergence (MACD), a powerful technical indicator used in financial analysis. Understand how the MACD signals trend changes, identifies overbought and oversold conditions, and generates buy/sell signals. Explore the parameters and see examples of how to use this indicator in Python.
Moving Average Convergence Divergence
MACD
Exponential Moving Averages
Signal line
trend changes
overbought conditions
oversold conditions
divergence with price
buy signal
sell signal
zero line
parameters
data
target column
fast EMA
slow EMA
signal EMA
calculated data
examples

import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

The Moving Average Convergence Divergence (MACD).

Difference between two Exponential Moving Averages. The Signal line is an Exponential Moving Average of the MACD.

The MACD signals trend changes and indicates the start of new trend direction. High values indicate overbought conditions, low values indicate oversold conditions. Divergence with the price indicates an end to the current trend, especially if the MACD is at extreme high or low values. When the MACD line crosses above the signal line a buy signal is generated. When the MACD crosses below the signal line a sell signal is generated. To confirm the signal, the MACD should be above zero for a buy, and below zero for a sell.

Parameters

data : List[Data] List of data to be used for the calculation. target : str Target column name. fast : int, optional Number of periods for the fast EMA, by default 12. slow : int, optional Number of periods for the slow EMA, by default 26. signal : int, optional Number of periods for the signal EMA, by default 9.

Returns

OBBject[List[Data]] The calculated data.

Examples

from openbb import obb
stock_data = obb.equity.price.historical(symbol="TSLA", start_date="2023-01-01", provider="fmp")
macd_data = obb.technical.macd(data=stock_data.results,target="close",fast=12,slow=26,signal=9)

Parameters

This function does not take standardized parameters.


Returns

This function does not return a standardized model