LogoLogo
Website
  • Introduction
    • Welcome to Alchemis
      • Important links
      • Vision
  • How Analys works
    • Introducing Analys
      • Protocols Analysis
      • Tokens analysis
    • Machine learning
      • Expected yield calculation
      • Risk calculation
      • Protocol deposit requirements
      • Aggregating the results
  • Getting Started
    • Understand the risks
    • Documentation in progress
  • Smart contract interactions
    • ALS token deposit
    • Multi-protocol interactions
    • Withdrawal process
  • Liquidity pool
    • Documentation in progress
  • ALS token
    • Tokenomics
    • Utility
    • Burn mechanism
  • Resources
    • Security
    • Legal
    • Roadmap
    • Glossary
    • Litepaper
    • FAQs
Powered by GitBook
On this page
  • Introduction
  • Data collection
  • Data storage
  • Data analysis
  • Dataset
Export as PDF
  1. How Analys works
  2. Introducing Analys

Protocols Analysis

How Analys evaluates different protocols.

PreviousIntroducing AnalysNextTokens analysis

Introduction

The goal at this point is to assess a multi-factorial grading of each token of each protocol and store these information in a transparent, cheap and decentralized way.

Data collection

Analyis communicates with to collect the primary data it needs about all DeFi yield-earning protocols on Solana. Secondly, Analys communicates with to access real-time price feeds of the different TAFs.

Additionally, to access specific data about each protocol such as their yield, liquidity depth, deposit requirements or minimum staking period (if existing), Analys interacts with the different smart contracts in order to collect these information. It then send this data off-chain to store the final data as well as its evolution.

Data storage

To minimize costs and offer a seamless user experience, Analys stores the data previously collected off-chain, in secure servers. This enables Alchemis to drastically reduce its costs, only storing critical information on-chain.

Data analysis

By storing the data, Analys can evaluate the evolution of the different metrics, separately and together to assess a general grade for each TAF. Complementing these data with temporality enables Analys to determine metrics such as mean yield as well as standard deviations to analyze the volatility of different metrics. Additionally, Analys combines price feeds to determine if the yield is market dependent (which would decrease the protocols' rating).

Note: To reduce costs whilst ensuring a maximal quality, Analys runs a data collection and storage for each TAF every 5 minutes.

Dataset

Ultimately, considering the 3 main criteria (TVL, liquidity, yield) as well the multiple secondary criteria mentioned above as well as other, Analys assesses a multi-factorial grade (multiple gradings for multiple analysis angles) of each TAF on the protocol side, that will later be used to assess yield expectation as well as risk.

The Graph
Pyth network