Cross-Exchange Arbitrage
An asset is purchased on a lower-priced exchange and sold on a higher-priced exchange.
The Blinko Arbitrage Engine is designed to observe cryptocurrency prices, compare supported markets, evaluate liquidity and costs, and identify potential trading spreads.
This page explains crypto arbitrage and provides an educational simulation of how a lower purchase price and higher sale price may create a trading result.
Engine status
Market Scanner
Exchange A
$68,000
Exchange B
$68,310
Exchange C
$68,510
Selected buy
Exchange A
Selected sell
Exchange C
Basic concept
Cryptocurrency markets operate across many exchanges, blockchains and liquidity pools. Each market has different buyers, sellers and liquidity, so the same asset may temporarily trade at different prices.
An arbitrage strategy attempts to purchase an asset where the price is lower and sell it where the price is higher before the price difference disappears.
The visible price difference is called the spread. The spread is not automatically profit because trading fees, slippage, network charges and execution time must also be considered.
Simple example
Exchange A
$68,000
Lower reference price
Exchange B
$68,680
Higher reference price
Visible spread
$680
Example costs
-$150
Example net result
$530
Strategy categories
An asset is purchased on a lower-priced exchange and sold on a higher-priced exchange.
Price differences between three trading pairs are evaluated inside the same market.
Prices between decentralised liquidity pools and centralised exchanges are compared.
Opportunities across multiple blockchain networks and liquidity routes are evaluated.
Market reference feed
Market prices may be loaded from an external reference feed. Exchange-specific chart lines are simulated for educational demonstration and are not executable trading quotes.
Feed status
Connecting to market feed...
BTC simulated exchange comparison
Animated demonstration based on the selected reference price
Simulated range
$67,877.60 – $68,496.40
Configure an educational example and view how spread, trading fees and network costs may affect the final result.
Simulation settings
Educational simulation only. No trade is executed and no actual return is predicted.
Engine terminal
Configure the trade and run the engine simulation to compare markets, calculate costs and display an educational result.
These modules represent future development direction and should not be interpreted as completed or guaranteed features.
AI-based models may rank opportunities using spread quality, liquidity, volatility and historical execution data.
Orders may be divided across multiple markets to reduce price impact and improve execution quality.
Automated controls may pause routes when liquidity, volatility or network conditions exceed defined limits.
The engine may continuously adapt filters and strategy allocation according to changing market conditions.
Important risk notice
Price movement, low liquidity, slippage, exchange failure, blockchain congestion and technical issues may reduce or prevent a trading result.