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| import pandas as pd | |
| import yfinance as yf | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import gradio as gr | |
| import io | |
| print("Starting app...") | |
| def sma_crossover_strategy(initial_budget, start_date, end_date, ticker): | |
| try: | |
| df = yf.download(ticker, start=start_date, end=end_date, progress=False) | |
| if df.empty: | |
| return None, "No data available for the specified ticker and date range.", None | |
| except Exception as e: | |
| return None, f"Error fetching data: {str(e)}", None | |
| df = df[['Close']] | |
| df['SMA_50'] = df['Close'].rolling(window=50).mean() | |
| df['SMA_150'] = df['Close'].rolling(window=150).mean() | |
| df['Signal'] = 0 | |
| df['Signal'][df['SMA_50'] > df['SMA_150']] = 1 | |
| df['Signal'][df['SMA_50'] < df['SMA_150']] = -1 | |
| df['Position'] = df['Signal'].diff() | |
| cash = initial_budget | |
| shares = 0 | |
| portfolio_values = [] | |
| for index, row in df.iterrows(): | |
| if pd.isna(row['Close']): | |
| continue | |
| if row['Position'] == 1 and cash > 0: | |
| shares = cash / row['Close'] | |
| cash = 0 | |
| elif row['Position'] == -1 and shares > 0: | |
| cash = shares * row['Close'] | |
| shares = 0 | |
| portfolio_value = cash + (shares * row['Close']) | |
| portfolio_values.append(portfolio_value) | |
| df = df.iloc[149:] | |
| df['Portfolio Value'] = portfolio_values[149:] | |
| plt.figure(figsize=(14, 8)) | |
| plt.plot(df['Portfolio Value'], label='Portfolio Value', color='purple') | |
| plt.xlabel('Date') | |
| plt.ylabel('Portfolio Value ($)') | |
| plt.title(f'Portfolio Value Over Time with 50/150 SMA Crossover Strategy ({ticker})') | |
| plt.legend() | |
| plt.grid() | |
| plt.tight_layout() | |
| plot_file = io.BytesIO() | |
| plt.savefig(plot_file, format='png') | |
| plot_file.seek(0) | |
| plt.close() | |
| final_value = portfolio_values[-1] | |
| profit_loss = final_value - initial_budget | |
| percentage_return = (profit_loss / initial_budget) * 100 | |
| results = f""" | |
| Ticker: {ticker} | |
| Trading Period: {start_date} to {end_date} | |
| Initial Investment: ${initial_budget} | |
| Final Portfolio Value: ${final_value:.2f} | |
| Total Profit/Loss: ${profit_loss:.2f} | |
| Percentage Return: {percentage_return:.2f}% | |
| """ | |
| return plot_file, results, None | |
| with gr.Blocks() as app: | |
| gr.Markdown("# SMA Crossover Trading Strategy Simulator") | |
| with gr.Tabs(): | |
| with gr.Tab("SMA Strategy Simulator"): | |
| with gr.Row(): | |
| initial_budget = gr.Number(label="Initial Investment ($)", value=100, interactive=True) | |
| start_date = gr.Text(label="Start Date (YYYY-MM-DD)", value="1993-01-01", interactive=True) | |
| end_date = gr.Text(label="End Date (YYYY-MM-DD)", value="2023-12-31", interactive=True) | |
| ticker = gr.Dropdown( | |
| label="Stock Ticker Symbol", | |
| choices=["SPY", "TSLA", "GOOGL", "AAPL", "MSFT"], | |
| value="SPY", | |
| ) | |
| run_button = gr.Button("Run Simulation") | |
| with gr.Row(): | |
| portfolio_graph = gr.Image(label="Portfolio Value Over Time") | |
| summary_text = gr.Textbox(label="Simulation Summary", lines=8) | |
| with gr.Tab("Instructions"): | |
| gr.Markdown(""" | |
| ## How to Use: | |
| 1. Enter your initial investment amount. | |
| 2. Specify the trading period (start and end dates). | |
| 3. Select a stock ticker symbol (e.g., SPY, TSLA, GOOGL). | |
| 4. Click "Run Simulation" to visualize the portfolio value over time and view a summary of results. | |
| """) | |
| run_button.click( | |
| sma_crossover_strategy, | |
| inputs=[initial_budget, start_date, end_date, ticker], | |
| outputs=[portfolio_graph, summary_text], | |
| ) | |
| app.launch() | |