# -*- coding: utf-8 -*-
"""therollercoasterstrategy.195

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/1Pn8vxMsTuQGWNoH9Bqo7XTJ1stXjNDHx
"""

!pip install neuralprophet

from neuralprophet import NeuralProphet
import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt

stock_symbol = 'DAL'
start_date = '2020-11-01'
end_date = '2024-12-01'

stock_data = yf.download(stock_symbol, start = start_date, end=end_date)

print(stock_data.head())
stock_data.to_csv('stock_data.csv')

stocks = pd.read_csv('stock_data.csv')
stocks['Date'] = pd.to_datetime(stocks['Date'])
stocks = stocks[['Date', 'Close']]
stocks.columns = ['ds', 'y']

plt.plot(stocks['ds'], stocks['y'], label = 'actual', c = 'g')
plt.show()

model = NeuralProphet()
model.fit(stocks)

future = model.make_future_dataframe(stocks, periods = 300)

forecast = model.predict(future)
actual_prediction = model.predict(stocks)

plt.title(".159 Est. 1367")
plt.plot(actual_prediction['ds'], actual_prediction['yhat1'], label = "prediction_Actual", c = 'r')
plt.plot(forecast['ds'], forecast['yhat1'], label = 'future_predictions', c = 'b')
plt.plot(stocks['ds'], stocks['y'], label = 'actual', c = 'g')
plt.legend()
plt.show()

"""S&P 500"""

model.plot_components(forecast)