from datetime import datetime import pandas as pd import plotly.graph_objects as go import yfinance as yf ticker = 'NVDA' start_date = '2023-01-01' end_date = '2024-01-01' df = yf.download(ticker, start=start_date, end=end_date) df.index = df.index.tz_localize(None) df.index = df.index.tz_localize('UTC') fig = go.Figure(data=[go.Candlestick(x=df.index, open=df['Open'], high=df['High'], low=df['Low'], close=df['Close'])]) fig.update_layout( title=f'{ticker} Stock Price', xaxis_title='Date', yaxis_title='Price (USD)', xaxis_rangeslider_visible=False ) fig.show()

import numpy as np

ticker = 'AAPL' start_date = '2023-01-01' end_date = '2024-01-01' data = yf.download(ticker, start=start_date, end=end_date) # Calculate moving averages short_window = 50 long_window = 200 data['Short_MA'] = data['Close'].rolling(window=short_window).mean() data['Long_MA'] = data['Close'].rolling(window=long_window).mean() # Generate buy/sell signals data['Signal'] = 0 data['Signal'][short_window:] = np.where(data['Short_MA'][short_window:] > data['Long_MA'][short_window:], 1, 0) data['Position'] = data['Signal'].diff() # Plot the stock price with moving averages and signals fig = go.Figure() fig.add_trace(go.Scatter(x=data.index, y=data['Close'], mode='lines', name='Close Price')) fig.add_trace(go.Scatter(x=data.index, y=data['Short_MA'], mode='lines', name=f'{short_window}-Day MA')) fig.add_trace(go.Scatter(x=data.index, y=data['Long_MA'], mode='lines', name=f'{long_window}-Day MA')) # Add buy/sell signals to the plot buy_signals = data[data['Position'] == 1] sell_signals = data[data['Position'] == -1] fig.add_trace(go.Scatter(x=buy_signals.index, y=buy_signals['Close'], mode='markers', marker=dict(color='green', size=8), name='Buy Signal')) fig.add_trace(go.Scatter(x=sell_signals.index, y=sell_signals['Close'], mode='markers', marker=dict(color='red', size=8), name='Sell Signal')) #Layout fig.update_layout(title=f'{ticker} Moving Average Crossover Strategy', xaxis_title='Date', yaxis_title='Price', legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01)) fig.show()