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Problems

Nicholas Platias edited this page Sep 6, 2019 · 1 revision

The following are the core problems we are thinking about at Terra Research. If any of those excite you, please join the discussion at Agora and consider contributing to the core and research repos. If you identify others, please share.

Secure oracle design

How do we design a robust and secure decentralized oracle? Risks lie in multiple layers:

  • Market prices are temporarily manipulated
  • Market prices are accurate, but one or more price feeds report dishonestly
  • Market prices and price feeds are accurate, but oracle votes are centralized or dishonest:
    • All oracles use the same price feed to guarantee maximum rewards
    • Oracles engage in a Keynesian beauty contest that rewards conformity rather than honesty
    • A group of oracles colludes to engage in profitable swaps at manipulated prices

Problems

  • What are the equilibrium behaviors for each agent in this system?
  • How can we use incentives and punishments to steer the system towards optimal equilibrium (decentralized, non-collusive honest voting)?
  • How can we make one-off attacks unprofitable?
  • How do we navigate the robustness-responsiveness tradeoff? The more responsive the oracle to price changes, the better it reflects present market belief but the more susceptible it is to temporary manipulation.

Some of the solutions need to be implemented at the oracle-feeder layer (voting), while others at the protocol layer (tallying).

Material

Optimal swap design

Designing an effective swap mechanism presents significant complexity and tradeoffs.

Problems

  • Should Terra/Luna swap limits be a function of Terra’s or Luna’s market cap?
  • Should swap liquidity be a function of Terra’s market price/divergence from the peg?
  • Validator front-running: validators can front-run swap orders with their own. How do we mitigate the risk and increase front-running cost?
  • Forex market front-running: the significant delay in oracle prices (1 minute+) creates the opportunity to front-run on-chain market prices. This risk is most notable in cross-Terra swaps, which charge significantly lower fees than Terra/Luna swaps. How do we mitigate this?
  • Peg stability vs swap robustness tradeoff: how do we reconcile the opposing needs for negligible swap spreads (peg stability) vs substantial spreads (swap robustness)? How do we quantify the tradeoff, what does the optimum depend on and how do we determine it?
  • Swap-facilitated currency trading/speculation: cross-Terra swaps allow anyone to make directional currency bets and potentially profit against the system. This is an unintended consequence of zero-fee swaps between Terras. How do we mitigate this risk?
  • The “zero-fee” ideal: we have discovered multiple situations where zero or very low fees are perilous to the swap mechanism, including manipulation vulnerability, harmful arbitrage and cheap speculation. Can we reason about this pattern more generally? Is there a lower bound on fees to guarantee a desired level of security?

Material

On vs off-chain market dynamics

The Terra ecosystem, by design, features multiple markets for Terra and Luna that interact in complex and often unpredictable ways:

  • Off-chain forex markets involving Terra-pegged currencies
  • Off-chain Luna markets
  • On-chain cross-Terra market
  • On-chain Terra/Luna market

The above markets often feature vastly different liquidities, transaction fees and investor/trader profiles.

Problems

  • How do liquidities of each market interact? Under what conditions can liquidity be transferred risk free, e.g. via arbitrage? What are the limitations?
  • Are there negative externalities associated with “market synchronization”, i.e. when prices of the same asset in different markets are brought in sync via arbitrage? How do we quantify them? For instance, Luna-based arbitrage between on and off-chain markets creates profit that does not directly contribute to Terra’s stability.
  • Oracle prices are a lagging indicator of off-chain market prices. At the same time they affect off-chain markets when arbitrage arises.
    • Is there at times a recursive relationship between current and previous market prices as a result? Under what conditions does this happen?
    • Does the price of Luna display autocorrelation, and how do we measure it?
    • What are the implications for Luna’s price and market structure?
  • Are there other implications of this market structure that are generalizable?

Material

  • Discussion of uncapitalized arbitrage here

Optimal seigniorage allocation

For the time being, Chai is the only beneficiary of seigniorage. Soon, however, seigniorage disbursement will be the responsibility of the Treasury.

Problems

  • Should the Treasury be algorithmic, governance-driven or both? The design in the white paper is a hybrid between the two.
  • How do we measure the effectiveness of seigniorage allocation?

Governance and power decentralization

Power in the Terra ecosystem is spread across multiple parties, some of whose power is more obvious than others’: Luna holders/delegators, validators, Terra users/holders, e-commerce companies and Terraform Labs. Part of this structure is present in all DPoS networks (delegators and validators), and part is somewhat unique to Terra: Terra users and e-commerce companies.

Problems

  • What is the balance of power between delegators and validators, and how does it relate to network structure and wealth distribution?
  • Under what conditions do delegators have maximum control (e.g. perfect competition between validators)?
  • Under what conditions do validators wield significant power (e.g. high barrier to enter/operate successfully, small number that may collude)?
  • What policies can we implement to achieve a desirable level of power decentralization between delegators and validators? For example:
    • How hard should it be to unstake?
    • How hard should it be to re-delegate?
    • How harsh should penalties be for underperforming validators?
  • What power do Terra users have over the network?
  • What power do e-commerce companies have over the network?
  • Terraform Labs wields notable power as a result of its significant Luna holdings. A substantial portion of this power is currently being shared with validators in the form of widespread delegations.
    • What are the responsibilities of Terraform Labs as a result of its present influence, and specifically its ability to vest certain validators with voting power?
    • What are the responsibilities of validators as a result of the voting power they have been vested with?
    • Based on what criteria does Terraform Labs distribute Luna delegations to validators?
    • Are there other significant implications of this power-sharing arrangement?
  • Does Terraform Labs play a special role in the ecosystem that extends beyond its Luna holdings? If so, what is it and how will it evolve over time?
  • What are the implications of the above structure for network governance, including protocol evolution (e.g. forks) and funding distribution (e.g. Treasury)?
  • Are PoS networks like Terra bound to become plutocracies in the long run? If so, why? If not, how can this be prevented?
  • What is stable state network structure? Can we create policies or incentives that decrease long-term centralization tendencies?
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