Information and Optimal Trading Strategies with Dark Pools

Article  -  Friday, 29 September 2023

Bayona, A., Dumitrescu, A. and Manzano, C. (2023): "Information and Optimal Trading Strategies with Dark Pools", Economic Modelling

In today's financial markets traders have access to competing trading venues with different levels of transparency for buying or selling assets. In addition to transparent exchanges, market participants can also trade in opaque trading venues such as dark pools. In December 2022, dark pools accounted for 13.75% of the US equity volume in the United States, and 7.50% of the total value traded in European markets. Dark pools often foster price improvement in relation to exchanges, but pose execution risks. In this context, information asymmetries play a fundamental role in investors' decision of where to trade and in the price discovery process. Therefore, a better understanding of the competition between an exchange and a dark pool with the presence of asymmetric information is essential.

The extant empirical literature finds mixed results regarding the impact of dark trading on market quality. Furthermore, the theoretical literature has not fully addressed how prices evolve when a limit order book trades alongside a dark pool, especially in the presence of long-lived and asymmetric information. In this paper, we aim at filling this gap and examine the impact of an opaque dark pool that competes with a transparent exchange organized as a limit order book in a model with asymmetric information about the liquidation value of the asset. We find that the effects of this competition on price informativeness and market performance depend critically on the stock categorization in terms of high/low fundamental volatility and high/low information asymmetry. These factors are determinant when selecting the venue and the type of order and, in turn, these have implications for market quality and traders' profits. As a result, the main conclusion of this study is that regulators should take into account the market conditions in the implementation of policies that aim to curb dark trading.

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