Stock Price Prediction Game

This Streamlit-based application challenges users to predict future stock closing prices after reviewing the last 90 days of generated OHLC (Open-High-Low-Close) data. By simulating realistic price movements and volatility via Geometric Brownian Motion (GBM), the app provides a fun and educational environment to test your market intuition.

Features

• Realistic Data Generation:
  Utilizes a custom RandomOHLC class to generate minute-level price data and then aggregates it into daily OHLC bars for display.

• Difficulty Levels:

  • Easy: Predict the closing price 1 day in the future.
  • Medium: Predict the closing price 7 days in the future.
  • Hard: Predict the closing price 30 days in the future.

• Game States:

  • START: Prompting the user to select difficulty and begin.
  • INITIAL: Displaying past 90 days of data, waiting for the user's first guess.
  • SHOW_RESULT: After a guess, showing correctness and allowing progression.
  • FINISHED: Displaying final results after 5 attempts.

• Dynamic Scoring and Feedback:
  Shows correct/wrong counts, calculates accuracy, uses a progress bar, provides encouraging messages, and compares performance to a hypothetical average. Also plots guess correctness over attempts.

• Interactive Candlestick Chart:
  Displays historical prices, helping users spot patterns before making their predictions.

How It Works

1. Data Simulation:
   The application uses minute-level simulations (via GBM) to produce realistic intraday volatility. This minute data is then resampled into daily OHLC bars to provide more authentic daily patterns.

2. User Prediction:
   Based on difficulty, the user selects a future closing price from several options. The chosen difficulty determines how far into the future the guess projects.

3. Scoring & Final Results:
   Each guess updates the user's score. After 5 attempts, the results page shows accuracy, average error, and a chart comparing guesses to actual prices.

Getting Started

Prerequisites

• Python 3.8+
• pip for installing dependencies

Installation

git clone https://github.com/yourusername/stock-prediction-game.git
cd stock-prediction-game
python3 -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -r requirements.txt

Running the App

streamlit run streamlit_app.py

Then open http://localhost:8501 in your browser.

Gameplay Instructions

1. Start Page:
   Choose a difficulty (Easy, Medium, Hard) and press Start Game.

2. Make a Guess:
   Review the candlestick chart of the past 90 days. Select a predicted future closing price and submit.

3. View Feedback:
   After submitting, see if you were correct. Continue until all attempts are completed.

4. Final Results:
   Review your performance metrics (accuracy, average error) and a chart showing your guesses vs. actual prices. Use this feedback to improve in future rounds.

Customization

• Adjust Days:
  Modify num_bars in the code to simulate more or fewer days.

• Volatility and Drift:
  Adjust the random ranges for volatility and drift to produce different price dynamics.

• UI Enhancements:
  Since it's a Streamlit app, you can easily modify layout, colors, and text.

Contributing

Contributions are welcome! Please open an issue or submit a pull request with improvements or new features.

License

This project is licensed under the MIT License. See the LICENSE file for details.