> For the complete documentation index, see [llms.txt](https://token-engineering-balancer.gitbook.io/balancer-simulations/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://token-engineering-balancer.gitbook.io/balancer-simulations/additional-code-and-instructions/modeling-time.md).

# Modeling Time

In the Balancer Simulations setup V1.0, we model Balancer Pools as discrete-time and discrete-state dynamical systems.

A transaction in a Balancer Pool is modeled as a discrete-time event updating the pool's state. They are referred to internally as Actions.

* similarly, price updates are processed as state updates
* the timestamp of every transaction, included in transaction data such as BigQuery Ethereum-Balancer, is preserved in the simulation output
* the simulation returns a datetime64 in 'change\_datetime'
* datetime allows to use any Python library for analysing and manipulating time series data