MarMix is a serious game for higher education based on a stock market simulation. Various game designs are built in the simulation in order to stepwise increase the difficulty of the game. The most advanced scenarios are developed to be run in parallel of an ERPsim simulation.
You can visit the MarMix website for more information on the product: https://m3.marmix.ch
Currently, MarMix support 4 game designs:
- Introduction
- Advanced
- Live
- Indexed
The introduction game is designed to introduce the players to the platform. A certain number of companies' profits is simulated, whose stocks are available on the stock market. Players are asked to place orders (ASK/BID) based on the variations of the profit. Optional transaction costs or payment of dividends can be added to the game.
The advanced game is the same as the `introduction`_ one but with more information revealed concerning the variations of the companies profits. In this games players are asked to develop a strategy based on the information they get from the market. Optional transaction costs or payment of dividends can be added to the game.
The live game is specifically designed to be run in parallel of an ERPsim simulation. The stock market hosts stocks for all companies active in the ERPsim simulation. Players are the asked to place their orders based on their own valuation of the ERPsim simulation companies. There are some simple interfaces that are built in MarMix in order to ease running each simulation in parallel. Integration is planned but not yet implemented.
The indexed game is based on data from historic ERPsim simulations. This is still under development.
The MarMix documentation is available online or as a PDF document. You can also build the documentation by yourself from the docs directory.
There is currently no installer for MarMix but you can install it following these steps:
- Install Python 3 on your system
- Create a virtualenv
- Checkout from GitHub
- Install the requirements:
$ pip install -r requirements/local.txt - Configure your database (Postgresql is recommended)
- Start the server:
$ manage.py runserver
You can find more information on the initial setup in the wiki.