Statistical arbitrage

Statistical arbitrage – A quantitative market-neutral strategy that exploits pricing inefficiencies across many instruments. Stat-arb algorithms use statistical models to rank hundreds of currency pairs or cross-assets and simultaneously long the relatively cheap and short the expensive ones. For example, a stat-arb robot might pair USD/JPY and EUR/JPY: if EUR/JPY becomes abnormally high relative to USD/JPY, the bot goes long USD/JPY and short EUR/JPY expecting reversion. In MetaTrader, one could write an EA using the Trade class to open offsetting positions (long and short) when a price-spread indicator crosses a threshold. cTrader cBots can achieve this by using its C# API to place concurrent buy and sell orders (PlaceLimitOrder(TradeType.Buy, ...) and PlaceLimitOrder(TradeType.Sell, ...)) on correlated symbols. Stat-arb is heavily algorithmic and often coded in Python as well (using libraries like Pandas to compute z-scores and Zipline for backtesting); Python bots can loop through data and call order_percent() in Zipline for multiple assets. The key is that stat-arb strategies are short-term and diversified, as noted: “Statistical arbitrage strategies are market neutral because they involve opening both a long position and short position simultaneously”. In Forex, stat-arb might include triangular arbitrage or mean-reverting baskets of currencies.

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