Stock Trading Simulation Game – Detailed Description

Overview

This project is a stock trading simulation game designed to provide a realistic yet accessible experience of financial markets.
Players manage virtual assets by buying and selling stocks while responding to market trends, news events, rumors, and economic fluctuations.

The game combines elements of financial strategy, risk management, and simulation-based learning, allowing players to understand how markets behave over time.

The goal is to increase total assets within a limited time period while managing volatility and uncertainty.

Core Concept

The simulation models a simplified financial market where stock prices evolve dynamically according to:

• stochastic price fluctuations
• company fundamentals (EPS, BPS, PBR)
• market tier characteristics
• news-driven shocks
• mean-reversion or trend-following behaviors

Players must interpret market information and make investment decisions under uncertainty.

Main Features

1. Real-time Market Simulation

Stock prices change continuously during gameplay.

Price movement is calculated using mathematical models including:

• volatility-based random noise
• drift components depending on company growth potential
• market tier effects (Prime / Standard / Growth)
• sudden price shocks triggered by news events

Example model behavior:

• Growth market stocks tend to have higher volatility
• Prime market stocks tend to have more stable price movements

2. News and Rumor System

The game includes a dynamic news generation system that affects stock prices.

Examples of events:

• positive earnings announcements
• industry regulation changes
• economic recession signals
• company scandals
• technological breakthroughs

Higher player skill levels unlock rumor hints before official news is released.

This introduces strategic advantages for informed decision-making.

3. Financial Indicators

Each stock includes simplified financial metrics:

• EPS (Earnings Per Share)
• BPS (Book Value Per Share)
• PBR (Price Book Ratio)
• volatility level
• growth tendency

These indicators help players evaluate whether a stock is undervalued or overvalued.

4. Order System

Players can trade stocks using realistic order types:

• Market Order
• Limit Order

Future expansion may include:

• morning and afternoon trading sessions
• transaction costs
• portfolio risk metrics

5. Multi-window UI Environment

The user interface is designed to resemble a desktop operating system.

Features include:

• draggable windows
• maximize / minimize functions
• taskbar with application icons
• multiple panels such as:
  • stock list
  • price chart
  • news feed
  • portfolio view

This design improves usability and immersion.

6. Time Scaling System

Game time progresses faster than real time.

Example: 1 in-game day progresses in approximately 24 minutes of real time.

This allows players to observe long-term market behavior within a short play session.

7. Strategy and Victory Conditions

Possible objectives include:

• achieve a target asset value within a limited number of days
• survive a market crash event
• succeed using only a restricted set of stocks
• outperform benchmark indices

Players must balance:

• risk vs return
• diversification vs concentration
• short-term speculation vs long-term investment

Educational Value

The simulation helps players develop intuition for:

• market volatility
• behavioral finance effects
• risk management
• diversification strategies
• impact of information timing

It can be used as a learning tool for:

• finance beginners
• students studying economics
• individuals interested in trading

Technical Implementation

Current versions are being developed using:

Python version:

• Tkinter GUI
• numpy
• matplotlib
• pygame (for audio)
• local data storage

Web version:

• HTML
• JavaScript
• LocalStorage persistence
• responsive UI components

The system architecture allows expansion of additional financial mechanics.