The cryptocurrency market is fragmented: the same asset on different exchanges can be valued differently at any given moment. This gap—the spread—is the source of profit for an arbitrageur. However, in practice, it is more complex: discrepancies rarely exceed fractions of a percent and vanish within seconds. Manual trading loses to the speed of algorithms here.
The Arbitron platform solves this problem by automating the entire cycle. The service monitors order books and funding rates on 20 exchanges, independently placing both sides of the trade—the so-called "legs." Meanwhile, funds remain on the trader's exchange accounts, eliminating custodial risks.
Realized Spread vs. Theoretical Spread
The key challenge of arbitrage is filtering out false signals. Scanners often show quote differences that are unattainable in practice. Four factors eat into potential profit: taker fees on both legs, insufficient order book depth, slippage during execution, and the decay of the spread itself.
Arbitron approaches this systematically. The platform processes about 10,000 order books simultaneously, keeping the full order book in memory rather than just the best price. This is critical: often the top of the order book holds only a couple of dollars in volume, and a real $500 order will execute at a much worse price. The service calculates the execution price for a specific volume—$25, $100, $500, or $1000.
Speed as a Decisive Factor
Latency in arbitrage is lost money. While a trader analyzes data, the order book updates. The Arbitron team solved this problem infrastructurally: each account gets a dedicated AWS server with a static IP in the region closest to the exchanges. Measurements show that a request to Binance from Tokyo takes about 23 ms versus 206 ms from Singapore. A 10-fold difference can mean the difference between a profitable trade and a loss.
The trading core is written in Rust—a language that provides predictable performance without sudden pauses on the critical execution path.
Backtest Instead of a Showcase
The approach to the scanner deserves special attention. Instead of real-time quotes, the platform shows backtest results with a 5-minute delay. The simulation runs the last 8 hours of recorded data through the same strategy as real trading cards, with fees already deducted according to the trader's individual rate.
Each opportunity receives a reliability score from 0 to 100, accounting for market depth, the number of successful cycles, and profit margin. This filters out illusory signals that would not survive real execution.
Protection Against Delisting and Risk Management
The most dangerous scenario for an arbitrageur is contract delisting. When an exchange removes an instrument, one leg of the position disappears, leaving the other unhedged. Arbitron tracks such events through three independent channels: official announcement APIs, periodic reconciliation of instrument lists, and data feed monitoring. When a threat is detected, the platform stops position accumulation and notifies the trader.
The built-in protection system includes a hard stop-loss, a soft limit on opening new cycles, and automatic exit at 3% before the liquidation price.
Payment Model: Commission Only on Profit
The platform's monetization deserves special mention. Arbitron charges a commission only on realized profit, not on trading volume. Losing weeks are not billed, and losses are carried forward to future periods until fully recovered. This aligns the interests of the platform and the trader.
Plans differ by functionality: Scanner at $39 per month provides data without execution, Trader at $99 adds trading bots and a dedicated server, and Prime at $299 (in development) expands limits to 50 strategies.
My conclusion: Arbitron is not just another scanner, but a full-fledged infrastructure for systematic arbitrage. The key advantage is attention to execution details that are usually ignored. However, it is important to remember: even the best automation does not eliminate the need to understand the market. It is worth starting with small volumes, carefully tuning thresholds and limits to your strategy.