This project is a simplified stock market simulator built using multi-agent systems (SMA). The goal is to replicate the behavior of market participants (traders and market makers) in a stock exchange, allowing us to analyze different trading strategies and market dynamics.
- Multi-Agent Systems (SMA): The simulator uses multiple agents (market maker and traders) to model real-world trading behaviors, including buying, selling, and price adjustments.
- Market Maker: Always ready to buy and sell. Adjusts prices at each iteration while ensuring buy prices are lower than sell prices.
- Traders:
- One trader alternates between buying and selling.
- The other trader can follow a strategy of your choice.
- The simulation runs in discrete time steps (iterations).
- During each iteration:
- The market maker updates prices.
- Traders decide to either buy or sell.
- The profit and loss (PnL) for each trader is updated accordingly.
- Simulate trading in a simplified stock market to observe market trends and dynamics.
- Analyze the performance of different trading strategies and their impact on profits.
- Experiment with adding more complexity, like multiple traders or smarter trading strategies.
- PnL Tracking: Traders’ profits and losses are tracked and updated after every trade.
- Market Maker Pricing: Dynamic pricing by the market maker based on trading conditions.
- Data Export: Output key simulation variables into CSV for further analysis.
- You can expand the simulation with more participants, smarter agents, and even create a dashboard to visualize market behavior.
Feel free to explore, modify, and test different scenarios to see how market dynamics evolve!