Utility Token Price Simulator

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.

GUI mode

Prerequisites

• docker
• docker-compose

Setup

$ 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...

Simulation

• Access http://localhost:3000 through a browser.
• Set the parameters and simulate.

Clean Up

After the simulation, you should remove containers with the command below.

$ docker-compose down

CUI mode

Prerequisites

• python3 (It has been confirmed to work with version 3.7.3)

Setup

$ git clone https://github.com/melonattacker/utility-token-price-simulator.git
$ cd utility-token-price-simulator
$ pip install -r requirements.txt

Simulation

• Edit config.json to set the parameters.
• After that, execute the following command.

$ python3 main.py

• Finally, glaph.png is output.

Parameters

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.