Utility Token Price Simulator is a simulator that simulates general token price when setting parameters.
It is implemented based on the theory of "Tokenomics: Dynamic Adoption and Valuation".
CUI mode or GUI mode can be used.
You can't use this tool for speculative purposes.
- docker
- docker-compose
$ git clone https://github.com/melonattacker/utility-token-price-simulator.git
$ cd utility-token-price-simulator
$ docker-compose build
$ docker-compose up # may take some time...
- Access
http://localhost:3000
through a browser. - Set the parameters and simulate.
After the simulation, you should remove containers with the command below.
$ docker-compose down
- python3 (It has been confirmed to work with version 3.7.3)
$ git clone https://github.com/melonattacker/utility-token-price-simulator.git
$ cd utility-token-price-simulator
$ pip install -r requirements.txt
- Edit
config.json
to set the parameters. - After that, execute the following command.
$ python3 main.py
- Finally,
glaph.png
is output.
Below is a description of the parameters.
Parameters | Type(python) | Default value | Description |
---|---|---|---|
period | int | 365 | Period(days) you simulate the price. |
agents | int | 1000 | Number of people who may hold tokens. |
times | int | 1 | Number of simulations. |
beta | float | 0.3 | Related to number of users and price. |
chi | float | 1.0 | Scaling effect on Productivity. |
interest_rate | float | 0.05 | Risk-free rate. |
token_supply | int | 1000000000 | Token supply amount (fixed). |
mu (price) | float | 0.03 | Expected rate of return. |
initial_value (productivity) | float | 100.0 | Initial value of productivity. |
mu (productivity) | float | 0.02 | Average of productivity. |
sigma (productivity) | float | 2.0 | Standard deviation of productivity. |
mu (utility) | float | 1.0 | Average utility of agents. |
sigma (utility) | float | 10.0 | Standard deviation of the utility of the agents. |