A SIMULATOR FOR STUDYING AUTOMATED BLOCK TRADING ON A COUPLED DARK/LIT FINANCIAL EXCHANGE WITH REPUTATION TRACKING

摘要

We describe a novel simulation of a contemporary real-world financial exchange: London Stock Exchange (LSE) Turquoise, and we also introduce a newly-created adaptive automated trading strategy called ISHV, which exhibits realistic behavior in situations where large orders can radically shift prices before transactions occur. LSE Turquoise is a recently-introduced platform where buying and selling takes place on a pair of coupled trading pools: a lit pool that is visible to all traders; and a dark pool where large "block" orders are hidden from sight until they are automatically matched with a counterparty, after which the transaction is then revealed. Orders from traders are routed to the lit or dark pool depending on their size, and on the reputation of the trader issuing the order. Unlike all other public-domain adaptive trading strategies, ISHV can alter the prices it quotes in anticipation of adverse price changes that are likely to occur when orders for block-trades are publicly visible: so-called market impact. LSE Turquoise is intended to reduce the negative effects of market impact; something that we test with our simulator. We extend the existing BSE open-source exchange simulator to incorporate coupled lit and dark pools, naming the new system BSELD. We show ISHV exhibiting market impact in a lit-only pool, and discuss how a Turquoise-style coupled dark pool reduces or eliminates that impact. We also show results from a Turquoise-style reputation-tracking mechanism, which can be used for modulating trader access control to the dark pool.