Understanding yfinance auto_adjust=True: What Changed and How to Fix It   

In this short guide, we will learn how to handle the yfinance auto_adjust parameter change and understand what auto_adjust=True actually does to your stock price data. This breaking change in yfinance 0.2.28+ now automatically adjusts historical prices for dividends and splits, which can break existing code expecting unadjusted prices.

Example warning message from yfinnance:

YF.download() has changed argument auto_adjust default to True

Problem: Breaking Change in yfinance

The yf.download() function changed its default auto_adjust parameter from False to True, causing existing scripts to return adjusted prices instead of raw prices, breaking technical analysis, backtesting, and price calculations.

What auto_adjust=True Does

When auto_adjust=True, yfinance:

• Removes the "Adj Close" column
• Adjusts Open, High, Low, Close for splits and dividends
• Adjusts Volume inversely for stock splits
• Returns split-adjusted and dividend-adjusted historical prices

import yfinance as yf

apple = yf.download('AAPL', start='2024-01-01', end='2024-02-01', auto_adjust=True)
print("With auto_adjust=True (NEW DEFAULT):")
print(apple[['Open', 'Close', 'Volume']].head())
print(f"Columns: {list(apple.columns)}")

Output Result:

With auto_adjust=True (NEW DEFAULT):
                  Open       Close     Volume
Date                                         
2024-01-02  187.15000  185.639999  82488800
2024-01-03  184.220001  184.250000  58414800
2024-01-04  182.149994  181.910004  81152300
2024-01-05  181.990005  181.179993  80962700
2024-01-08  181.300003  185.559998  98297300
Columns: ['Open', 'High', 'Low', 'Close', 'Volume']

Solution: Control Price Adjustment Behavior

1. Get Unadjusted Prices (Old Behavior)

Set auto_adjust=False to get raw, unadjusted prices with the Adj Close column included.

import yfinance as yf

microsoft = yf.download('MSFT', start='2024-01-01', end='2024-02-01', auto_adjust=False)
print("With auto_adjust=False (OLD DEFAULT):")
print(microsoft[['Close', 'Adj Close', 'Volume']].head())
print(f"\nDifference: Close - Adj Close = {(microsoft['Close'] - microsoft['Adj Close']).head()}")

Output Result:

With auto_adjust=False (OLD DEFAULT):
                  Close   Adj Close     Volume
Date                                          
2024-01-02  374.579987  372.549286  27842000
2024-01-03  368.049988  366.051849  28832100
2024-01-04  368.899994  366.896271  23169600
2024-01-05  369.540009  367.532806  24042400
2024-01-08  370.369995  368.357849  23334200

Difference: Close - Adj Close = 
Date
2024-01-02    2.030701
2024-01-03    1.998139
2024-01-04    2.003723
2024-01-05    2.007183
2024-01-08    2.012146

2. Migration Strategy for Existing Code

Fix legacy code by explicitly setting auto_adjust=False to maintain backward compatibility.

import yfinance as yf

def get_stock_data_legacy(ticker, start, end):
    return yf.download(ticker, start=start, end=end, auto_adjust=False, progress=False)

tesla = get_stock_data_legacy('TSLA', '2024-01-01', '2024-01-10')
print(f"Columns available: {list(tesla.columns)}")
print(f"Has Adj Close: {'Adj Close' in tesla.columns}")

Output Result:

Columns available: ['Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume']
Has Adj Close: True

Common Use Cases

Backtesting: Use auto_adjust=True for accurate historical total returns

Price Charts: Use auto_adjust=False to show actual traded prices

Technical Analysis: Depends on strategy - RSI/MACD work with either

Dividend Analysis: Use auto_adjust=False to see ex-dividend price drops

Quick Reference