ex-stock-return-ai

This plots shows the return of three AI darlings of 2025. Total return (%) since January 2025 adjusted for dividends and splits. Source: Yahoo Finance

🟧 PLTR

YTD Return: 104%

Palantir is selling AI driven software for government and defence.

🟦 NRG

YTD Return: 67%

NRG is providing energy solutions and has seen an AI driven demand surge.

🟥 STX

YTD Return: 341%

Seagate is providing data storage solutions for data hungry AI models.

Source code

import inspect
import sys
import yfinance as yf
import pandas as pd
from novem import Plot

# We show the returns of three AI Stocks that have performed strongly in 2025 
AI_STOCKS = {
    'PLTR': 'Palantir is selling AI driven software for government and defence. ',
    'NRG': 'NRG is providing energy solutions and has seen an AI driven demand surge.',
    'STX': 'Seagate is providing data storage solutions for data hungry AI models.'
}

ICONS = '🟧🟦🟥'


# Function to get total return data from Yahoo Finance
def get_total_return(start_date):
    data = yf.download(list(AI_STOCKS.keys()), start=start_date, end=None, auto_adjust=True)['Close']
    total_return = data.divide(data.iloc[0]).multiply(100)
    return total_return   

total_return = get_total_return(start_date='2025-01-01')

# Code to make the novem plot 
plt = Plot('ex-stock-return-ai')
plt.data = total_return-100
plt.type = 'line'
plt.name = 'Returns from AI darlings '
plt.shared = 'public'

plt.description = 'This plots shows the return of three AI darlings of 2025. Total return (%) since January 2025 adjusted for dividends and splits. Source: _Yahoo Finance_ '

for i, (ticker, story) in enumerate(AI_STOCKS.items()):
    ytd = total_return[ticker].iloc[-1] - 100
    plt.description += (
        f"\n\n---\n\n"
        f"### {ICONS[i]} {ticker}\n\n"
        f"**YTD Return:** {ytd:.0f}%\n\n"
        f"{story}\n"
    )

plt.description += '\n\n## Source code\n\n'
plt.description += '\n\n```python' + ' ' + inspect.getsource(sys.modules[__name__]) + '```'