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import yfinance as yf
import matplotlib.pyplot as plt
# Download historical data for the S&P 500
sp500 = yf.Ticker('^GSPC')
hist = sp500.history(start='2009-01-01', end='2023-12-31')
# Calculate the growth of $100 invested with dividends reinvested
initial_investment = 100
hist['Dividends'] = hist['Dividends'].fillna(0)
hist['Daily Return'] = hist['Close'].pct_change() + (hist['Dividends'] / hist['Close'])
hist['Cumulative Return'] = (1 + hist['Daily Return']).cumprod()
# Adjust the cumulative return to the initial investment
hist['Investment Value'] = initial_investment * hist['Cumulative Return']
# Plot the investment growth
plt.figure(figsize=(12, 6))
plt.plot(hist.index, hist['Investment Value'], label='S&P 500 with Dividends Reinvested')
plt.title('Growth of $100 Invested in S&P 500 (2009-2023)')
plt.xlabel('Year')
plt.ylabel('Investment Value ($)')
plt.legend()
plt.grid(True)
plt.show()
import yfinance as yf
import matplotlib.pyplot as plt
# Download historical data for the S&P 500
sp500 = yf.Ticker('^GSPC')
hist = sp500.history(start='2009-01-01', end='2023-12-31')
# Calculate the growth of $100 invested with dividends reinvested
initial_investment = 100
hist['Dividends'] = hist['Dividends'].fillna(0)
hist['Daily Return'] = hist['Close'].pct_change() + (hist['Dividends'] / hist['Close'])
hist['Cumulative Return'] = (1 + hist['Daily Return']).cumprod()
# Adjust the cumulative return to the initial investment
hist['Investment Value'] = initial_investment * hist['Cumulative Return']
# Plot the investment growth
plt.figure(figsize=(12, 6))
plt.plot(hist.index, hist['Investment Value'], label='S&P 500 with Dividends Reinvested')
plt.title('Growth of $100 Invested in S&P 500 (2009-2023)')
plt.xlabel('Year')
plt.ylabel('Investment Value ($)')
plt.legend()
plt.grid(True)
plt.show()
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