python code

import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
from statsmodels.tsa.arima.model import ARIMA
from datetime import datetime, timedelta
symbol = "^NSEI" 
start_date = "2010-01-01"
end_date = datetime.today().strftime('%Y-%m-%d')
data = yf.download(symbol, start=start_date, end=end_date)
data = data['Close'].dropna()  
train_size = int(len(data) * 0.8)
train_data = data[:train_size]
test_data = data[train_size:]
model = ARIMA(train_data, order=(5, 1, 0))  
model_fit = model.fit()
forecast_steps = 30
forecast = model_fit.forecast(steps=forecast_steps)
print(forecast)
plt.figure(figsize=(10,6))
plt.plot(data.index, data, label='Historical Nifty 50')
plt.plot(test_data.index, test_data, label='Test Data', color='green')
plt.plot(test_data.index[-forecast_steps:], forecast, label='Forecast', color='red')
plt.title('Nifty 50 Forecast using ARIMA')
plt.legend()
plt.show()