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# System prepended metadata

title: Hyperdrive Todos

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# Hyperdrive Todos

## Simulations

### Milestones

1. [x] Minimum Crappy Simulation
    - Timeline
        - EOW
    - Deliverables
        - Random Agents
        - GBM market APR
        - Basic Visualizations
    - Expectations
        - Change as little as possible about the current framework. 
        - Hack together these features using the current framework.
2. [ ] Minimum Viable Simulation
    - Timeline
        - 1-2 weeks
    - Deliverables
        - Can be run forever
        - Improved data pipeline
    - Expectations
        - Improve the data pipeline so notebooks can attach to a simulation that runs forever.
3. [ ] LP Profitability Analysis
    - Timeline
        - A few days to a week
    - Deliverables
        - A set of dashboards that model LP returns of an active MVP simulations
4. [ ] Trader Profitability Analysis
    - Timeline
        - A few days to a week
    - Deliverables
        - A set of dashboards that model trader returns of an active MVP simulation.

### Tasks

    This task list is incomplete.

1. [x] Use stochastic processes to model market APR in the simulator.
    - Add a fixture for geometric brownian motion.
2. [ ] Postprocessing & plotting -- Mihai
    - create helper functions that run calculations in post-processing
        - Operations are performed in-place on pandas dataframe input & add computed columns
    - create display functions that visualize the results
        - limited functionality is okay for demo (plotly, matplotlib, proplot)
    - make it easy for researchers to iterate
        - by regularly iterating on outputs => tell us what to fix
        - shorten feedback loop: change code then inspect output
        - if you want something to be easy to use, use it a lot
4. [ ] Add random trader and LP agents.
    - Traders long and short randomly.
    - LPs join and leave randomly.
    - Probably best to start from scratch.
5. [ ] Create MVP data visualization notebooks.
    - The simulation should be able to run forever, so we may need to store data in a database so that it can be pulled into dataframes and manipulated/visualized by dashboards.
    - Create sample dashboards in a Jupyter notebook that can be used to visualize a running simulation.
        - Base Reserves
        - Bond Reserves
        - LP Total Supply
        - Pool APR
        - Spot Price
        - Long/Short Volume

## Research

1. [ ] Solidify the Hyperdrive accounting system.
    - Assignee: Alex, Jonny, Mihai, Dylan, Matt
    - Tasks:
        1. Nail down an initial version of the accounting. Ensure that the simulation framework is using it correctly.
        2. Investigate edge cases that occur with different long and short combinations. 
        3. Investigate netting and ensure that solvency is ensured, that shorts receive the full amount of interest they are owed, and that it improves LP capital efficiency.
        4. Ensure that shorts can be counter-balanced by longs (in other words, the buffer shouldn't prevent longs from trading).
3. [ ] Produce a paper that proves that the flat+curve pricing model upholds the no-arbitrage constraint.
    - Assignee: Tim Roughgarden and Maryam Bahrani
4. [ ] Produce a paper that analyzes Hyperdrive LP profitability and categorizes regimes in which LPs lose money and make money.
    - Assignee: Tim Roughgarden and Maryam Bahrani
5. [ ] Attempt to formalize the properties that we'd like the Hyperdrive fee model to have.
    - Assignee: TBD
6. [ ] Address the issue that flat+curve provides a higher interest rate to users that continually buy and sell bonds in small time increments.
    - Assignee: Alex Towle
    - Idea: Instead of using $t$ for the flat part and $1 - t$ for the curved part in our trading functions, we can use $\frac{e^t - 1}{e - 1}$ for the flat part and $\frac{e - e^t}{e - 1}$ for the curved part. Now what remains is to formulate the problem in such a way that I can prove the new methodology solves the issue.