Trustless Price Feeds of Cryptocurrencies: Pathfinder

ArXiv ID: 2305.13227 “View on arXiv”

Authors: Unknown

Abstract

Price feeds of securities is a critical component for many financial services, allowing for collateral liquidation, margin trading, derivative pricing and more. With the advent of blockchain technology, value in reporting accurate prices without a third party has become apparent. There have been many attempts at trying to calculate prices without a third party, in which each of these attempts have resulted in being exploited by an exploiter artificially inflating the price. The industry has then shifted to a more centralized design, fetching price data from multiple centralized sources and then applying statistical methods to reach a consensus price. Even though this strategy is secure compared to reading from a single source, enough number of sources need to report to be able to apply statistical methods. As more sources participate in reporting the price, the feed gets more secure with the slowest feed becoming the bottleneck for query response time, introducing a tradeoff between security and speed. This paper provides the design and implementation details of a novel method to algorithmically compute security prices in a way that artificially inflating targeted pools has no effect on the reported price of the queried asset. We hypothesize that the proposed algorithm can report accurate prices given a set of possibly dishonest sources.

Keywords: price feeds, decentralized oracle, consensus algorithm, blockchain, General

Complexity vs Empirical Score

  • Math Complexity: 7.0/10
  • Empirical Rigor: 3.0/10
  • Quadrant: Lab Rats
  • Why: The paper employs advanced mathematical concepts like graph theory and arbitrage triangles to quantify manipulation, but the excerpt lacks backtesting, code, or implementation-heavy details, focusing more on algorithmic design.
  flowchart TD
    A["Research Goal: Design trustless price feed resilient<br>to artificial price manipulation"] --> B["Key Methodology: Algorithmic consensus<br>from multiple data sources"]
    B --> C["Data/Inputs: Historical & real-time<br>price data from various oracles"]
    C --> D["Computational Process: Apply algorithm to<br>filter outliers and compute consensus"]
    D --> E["Outcome: Accurate price feed<br>immune to single-point manipulation"]
    E --> F["Industry Impact: Balances security<br>and speed in DeFi"]