Project Case Study

CAT / Crypto Arbitrage Tracker

Crypto Arbitrage Tracking & Market Opportunity Analysis System

CAT is a crypto market monitoring system designed to compare prices, detect price differences across exchanges, and analyze potential arbitrage opportunities. It focuses on data, speed, transparency, and risk-aware decision-making — considering not only raw spreads but also fees, liquidity, trading paths, and execution constraints.

Arbitrage TrackingMarket DataSpread AnalysisCEX/DEX MonitoringRisk & Fee AnalysisCrypto Intelligence

Project Overview

Technical Summary

Project Type

Crypto market analysis and arbitrage tracking system

Anarchain Role

Product design, data architecture, backend, dashboard, API, opportunity detection logic, risk analysis

Status

MVP / Market Intelligence Tool

Target Users

Traders, market analysts, data teams, professional crypto users

Architecture

Market Data Pipeline + Arbitrage Engine + Dashboard

Core Value

Turning scattered price differences into analyzable opportunities

GoNode.jsReactNext.jsAPIsMongoDBPostgreSQLRedisWebSocketsMarket DataData Processing

Core Challenges

The Problem CAT Solves

In crypto markets, the price of an asset can differ across exchanges and trading venues. But a raw price difference does not automatically mean a real arbitrage opportunity. Trading fees, liquidity, market depth, transfer time, withdrawal limits, slippage, network type, and execution risk must also be considered. CAT was designed to turn price differences into decision-ready analysis.

01

Price fragmentation across exchanges and markets

02

Difficulty comparing prices across multiple sources simultaneously

03

Gap between raw spread and an actually executable opportunity

04

Impact of fees, liquidity, and slippage on final profit

05

Risk of transfer time and price changes during execution

06

Need for a fast, filterable opportunity dashboard

07

Lack of opportunity scoring and prioritization

08

Need for stored data for trend analysis and future backtesting

Data Flow

Market Data Flow Topology

In CAT, price and market data is collected from multiple sources. Symbols and markets are normalized, prices compared, spreads calculated, and potential opportunities — along with risk, fees, and liquidity status — are delivered to the dashboard.

Technical Approach

CAT's Solution

CAT creates an analytical layer over crypto market data. It collects prices from multiple sources, makes them comparable, calculates price differences, and then — by factoring in execution constraints like fees, liquidity, risk, and timing — makes opportunities more understandable.

  • Collect prices from multiple markets and exchanges
  • Normalize symbols and trading pairs
  • Calculate spread between markets
  • Evaluate fees, liquidity, and slippage
  • Prioritize opportunities with scoring
  • Display opportunities in a filterable dashboard
  • Store data for trend analysis and future backtesting

Data Sources

Market Sources & Exchanges

CAT can receive market data from centralized exchanges, decentralized exchanges, price APIs, and network data. Each data source plays a different role in arbitrage analysis.

Centralized Exchanges

BN

Binance

CEX

Price, volume, spot markets, major trading pairs

OX

OKX

CEX

Spot markets, derivatives, liquidity and price data

KC

KuCoin

CEX

Altcoins, diverse pricing, price difference opportunities

BY

Bybit

CEX

Active markets, liquidity, price and trading context

CB

Coinbase

CEX

Major asset prices, reliable markets and reference data

Decentralized Exchanges

UN

Uniswap

DEX

DEX liquidity, on-chain prices, AMM pool data

PS

PancakeSwap

DEX

BSC DEX, token prices, liquidity pool data

Market Data APIs

MA

Market APIs

Data

Network fees, price data, transfer status and risk context

Analysis Engine

Arbitrage Opportunity Engine

CAT's engine does not merely display price differences — it tries to transform price differences into analyzable opportunities. In this process, buy price, sell price, spread, trading fees, liquidity, execution risk, and market status are all evaluated.

Inputs

  • Price at Market A
  • Price at Market B
  • Volume & Liquidity
  • Trading Fee
  • Withdrawal / Network Fee
  • Estimated Slippage
  • Transfer Time
  • Market Constraints

Outputs

  • Spread %
  • Estimated Profit
  • Risk Level
  • Liquidity Status
  • Opportunity Priority
  • Suggested Path
  • Alert / Watchlist

Risk Analysis

Arbitrage Is Not Just a Price Difference

One of the goals of CAT is to ensure users do not make decisions based on a spread number alone. In real markets, an arbitrage opportunity may disappear due to fees, slippage, low liquidity, withdrawal limits, rapid price changes, or transfer time.

MED

Trading Fees (Buy + Sell)

Typically 0.1–0.5%+ depending on exchange

MED

Withdrawal / Network Fee

Variable by network and time

HIGH

Liquidity & Market Depth

Low volume eliminates the opportunity

MED

Slippage

Higher in thin markets

HIGH

Asset Transfer Time

Price may shift during transfer

MED

Withdrawal / Deposit Limits

Some exchanges have restrictions

HIGH

Rapid Price Change

Opportunity may close in seconds

MED

Network Differences

EVM vs non-EVM adds complexity

HIGH

Partial Execution Risk

Order partially filled or network error

MED

Low Market Volume

Spread valid only for small size

System Output

Opportunity Dashboard

The output of CAT must be displayed in a fast, readable, and filterable dashboard — where users can sort and review opportunities by trading pair, exchange, spread %, risk level, liquidity, timing, and market status.

Technical Architecture

CAT Technical Architecture

CAT is designed with a multi-layer architecture so data from multiple sources can be received, made comparable, processed quickly, and displayed meaningfully in the dashboard.

Data Models

Data Models & System Complexity

To analyze arbitrage opportunities, the system must manage data across multiple sources, trading pairs, exchanges, prices, fees, liquidity, users, watchlists, and opportunity history.

Historical Data

Historical Analysis & Backtesting

By storing market snapshots and identified opportunities, CAT can be used for historical analysis, evaluating spread persistence, assessing opportunity quality, and optimizing scoring models.

  • Store price and market snapshots
  • Store identified opportunities with timestamps
  • Measure how long opportunities persist
  • Compare raw profit vs post-fee profit
  • Analyze spread behavior over time
  • Optimize filters and scoring models
  • Prepare data for future prediction models

Scope of Work

What Anarchain Built

The Anarchain team worked on product design, data architecture, price collection, pair normalization, opportunity detection logic, analytics dashboard, APIs, data storage, and product roadmap for CAT.

01

Product design and user journey

02

Data architecture and market sources

03

Market API connection and management

04

Symbol and trading pair normalization

05

Spread calculation and opportunity analysis

06

Dashboard design and filters

07

Data models and snapshot storage

08

Backtesting infrastructure and historical analysis

09

SaaS roadmap and subscription model path

10

Integration with Anarchain data and crypto ecosystem

Strategic Importance

Why CAT Matters for Anarchain

CAT demonstrates that Anarchain can build data-driven tools for the crypto market — tools that require data collection, normalization, fast processing, risk analysis, historical storage, and decision-support display.

  • Proves Anarchain's capability in Crypto Market Data Engineering
  • Direct connection to the AI/Data and market analysis path
  • Foundation for SaaS and subscription-based tools
  • Suitable for content production at Coinbazan
  • Complement to Crypto Data & Decision Assistant
  • Strong reference for attracting FinTech and Crypto Intelligence projects

Development Stages

CAT Product Roadmap

01

MVP Market Tracker

Connect price sources, display price differences, initial dashboard

02

Arbitrage Engine

Spread, fees, liquidity, risk calculation and opportunity prioritization

03

Alerts & Watchlist

Alerts, watchlist, advanced filters, user preferences

04

Historical Data

Store snapshots, historical analysis, spread persistence review

05

Backtesting

Compare opportunities against market behavior, optimize scoring

06

AI/Data Integration

Connect to intelligent analysis layer for opportunity narration

07

SaaS Expansion

Subscription plans, API access, professional dashboard, team tools

Collaboration

Need a Market Analytics or Financial Data Tool?

If you need a market dashboard, opportunity tracking system, arbitrage tool, financial data analytics platform, trading alerts, or crypto data infrastructure, Anarchain can support you from architecture to development, backtesting, and deployment.