Volume Discovery: Leveraging Liquidity in the Depth of an Order Driven Market

Abstract

A b s t r a c tElectronic order book trading has evolved in being recognized as the best-practice for trading small and mid-sized orders. Yet, this mechanism does not properly address the needs of large-sized orders which tend to execute off order book in over-the-counter markets. Order book trading provides for public price discovery but not for quantity discovery. Off book executions generally fragment the order flow which again adversely impacts price discovery.We propose a market model innovation to close this gap: 'Volume Discovery' introduces the new order type 'volume order' to integrate large sized orders into the book. The volume order builds on the concept of iceberg order but is enhanced by two parameters 'hidden limit' and 'minimum volume', which continuously search order book depth for matching quantity.For large orders, Volume Discovery leverages already existent liquidity to benefit block trading by increased likelihood of execution and reduced opportunity costs. For all orders, Volume Discovery promotes the integration of OTC markets and order book trading in order to improve liquidity while protecting price/time priority.

Sports betting as a new asset class—current market organization and options for development

“…The introduction of CCP services to a market should also increase its liquidity (Gomber et al 2006b). Market participants that may not be accepted as bet layers on a bilateral basis-either because of a lack of trust or because of prohibitive verification costs on an international basis-can prove their eligible counterparty status with clearing membership.…”

Athena: Smart order routing on centralized crypto exchanges using a unified order book

“…In our considerations, we rely on the XLM measure, as it captures the idea of implicit costs that arise as price deviations from a reference price. 6 Given a snapshot of an order book, where l ask,i ¼ p ask,i , v ask,i À Á and…”

“…In traditional finance, it is known that those implicit costs significantly impact the overall return more than explicit costs, for example, trading fees. 6 However, in most research papers, implicit costs that arise from the order book are not considered; the analysis primarily relies on a reference price, for example, the average between best ask and best bid or tick data, for example, price-volume pairs that are added to a list every time a trade is executed, as shown in Figure 1. The main reason for this is the complicated collection and processing of order book data.…”