Algorithmic Trading Firms Trigger Outages on Major Cryptocurrency Exchanges
Widespread outages recently experienced by some of the world’s largest centralized cryptocurrency exchanges are being attributed to the surge in activity from algorithmic trading firms. Notable platforms, including Binance, Coinbase, Kraken, and Bybit, encountered technical glitches just days after Bitcoin’s bull run over $62,000, reaching a milestone not seen in over two years on Feb. 28.
The heightened retail interest in cryptocurrencies due in part to the high interest in Bitcoin ETF’s launched by the likes of Blackrock and ARK Invests, combined with the swift movements in prices, has led algorithmic trading firms to significantly increase the rate of order placements and cancellations. During peak trading times, it is not uncommon for trading firms to amplify their output of orders and cancellations, sometimes by factors as high as 10 or even 20 times.
These intensified activities, crucial for the firms to adjust and maintain their positions in the rapidly changing crypto market, have presented challenges for centralized exchanges. Unlike decentralized exchanges (DEXs) such as Uniswap and HootDex, some centralized exchanges have the flexibility to set custom trading limits for individual market makers based on trust assumptions. However, this practice has added to the growing workload, especially during bull market conditions.
Centralized exchanges may establish specific trading limits for known market makers, setting their rate limits higher based on established relationships. While reasonable under normal circumstances, these preset limits become problematic during bullish market conditions when market makers seek to trade at an accelerated pace. This acceleration can essentially can cause a bottleneck and potential an outage.
In contrast, decentralized exchanges operate differently. The rate limits on DEXs are set by the underlying protocol and DEXs just do not maintain direct relationships with market makers. This distinction provides a more stable, predictable and somewhat fairer trading environment on decentralized platforms.
The recent technical disruptions have highlighted the vulnerability of centralized exchanges, which, despite being optimized for performance and efficiency, face challenges during periods of extreme market activity. Once a centralized matching engine experiences an outage, it leads to a halt in trading activities on the affected platform.
The comparison with decentralized exchanges emphasizes that the latter’s operational model helps mitigate the risk of such outages. Decentralized exchanges, for the most part, are not subject to the same types of technical failures that can disrupt centralized platforms.
