Excerpt
A dark pool is defined by Banks (2010) as an alternative trading system for the anonymous trade of standardised financial products. Pan (2017) specifies it as mainly an equity trading venue. The trades in a dark pool are, according to Ye (2016), concluded outside of any display order. This differs from lit markets, such as traditional stock exchanges, as the trade, according to Comerton-Forde and Putniņš (2015), is only made public after it has been executed. Dark pools are a highly unregulated market sector and not subjected to the rules and regulations of the European stock exchanges, as Baxter (2017) highlights. Petrescu and Wedow (2017) therefore assumed that the key feature of dark pools is less transparency compared to lit markets, i.e. market participants do not have an overview of the supply and demand of the products. The traders purchase and sell on dark pools without showing their identities or exposing transactions to the public market; therefore, the available liquidity in the dark pool is anonymous, as pointed out by Kratz and Schöneborn (2014). The price of a successful order is calculated, as claimed by Banks (2014), as the midpoint of the bid and offer. Zhu (2014) states that the execution of an order in a dark pool is not guaranteed, unlike the traditional stock exchange.
Dark pools should not be prohibited due to the fact that much higher levels of market quality can be reached with dark pool trading. It is my belief that market quality and dark trading activities have a linear relationship, which implies that dark trading could be harmful to the market quality. This advantage can be justified on the basis of two supporting arguments.
First, dark trading is advantageous for the financial system because of less transparency against the traditional exchanges, as argued by Garvey, Huang and Wu (2016). Dark pools allow participants to execute trades with delayed public disclosure, as described by Zhu (2014), and Baxter (2017) emphasis the benefits of keeping trade strategies from competitors thorough the use of dark pools. Comerton-Forde and Putniņš (2015) illustrate this by showing how, even after the execution, the market does not know the time at which a limit order was submitted, any revisions to the order price, the original size of the limit order or the venue at which it was executed. All of these can be informative for the price discovery in the lit market. This transparency can also be useful for the competitor for countersteering. Research by Preece and Rosov (2014) makes this characteristic of dark pools particularly interesting for the execution of large block orders. Karstadt (2011) argues that fluctuations in share prices, because of pre-trade information leakage, can be one of the main cost factors for institutional investors and pension funds, which are reinforced by information leakage. If submitted to an order book, large orders would cause significant price impact, and thus increase the indirect trading costs, as highlighted by Karstadt (2011). The potentially unfavourable resulting move of stock prices can have, according to Banks (2010), negative effects on the profit of the investor while buying or selling equities. Through dark pools, these investors can gain anonymous access to liquidity without risking the associated negative market reaction. As argued by Zhu (2014), traders reduce the level of noise in the lit market while choosing dark pools due to the aforementioned properties. Mercurio (2013), goes on to say that “participants [can] trade without alerting competitors to their actions” (p.69).
The second advantage of dark pools, as pointed out by Aubrey (2009), is the lower trading fees compared to traditional exchange charges, also known as direct costs. Davies and Sirri (2017) outline how investors have never before had such low trading costs. For example, investors at the London Stock Exchange (2017a) have to pay 0.45 basis points variable trading fees for an equity exchange of up to GBP 2.5 billion. On the other hand, they only pay 0.3 basis points variable trading fees, according to London Stock Exchange (2017b), for an equivalent trade on the Dark Pool Turquoise, which is also operated by the London Stock Exchange. This price structure makes cost savings possible while trading GBP 2.5 billion of equities at the cost of GBP 37,500. As found by Crudele (2015), the price decreases as the competition increases. In my view, greater competition is good for every market because of the fair price determination and the avoidance of an oligopoly of the traditional stock exchange. Banks (2010) argues that investors can avoid paying exchange fees while trading on the dark pool. The brokers can preserve more of the spread and split the savings with their clients. All participants can strive with this behaviour, according to the Pareto optimality state where everyone gets better and no one gets worse, as pointed out by Cowell (1993). Karstadt (2011) suggests that trading large quantities of stock is more cost effective for the investor on the dark pool. Crisafi and Macrina (2016) justify this with the price determination of the execution, which is the midpoint between the bid and the asking price compared to other markets. These price determinations can save, according to Preece and Rosov (2014), the respective counterparties from exchange fees and half the bid-offer spread. In my view, the execution price in a dark pool should match without exceeding the National Best Bid and Offer to be attractive. This is only possible if the broker gives a discount, even if it is marginal.
The possibility of trading confidentially and more cost-effectively leads me to conclude that dark pools are a benefit to the financial system as a counterpart of traditional exchanges. Specific market needs that require dark pools will, according to Mensah (2017), never go away. Crisafi and Macrina (2016) highlight that the simultaneous existence of lit markets and dark pools is more attractive to all market participants. Consequently, the existence of dark pools is not detrimental to market quality, as pointed out by Aquilina et al. (2017). Therefore, the volume of trades in dark pools has increased, as researched by Buti, Rindi and Werner (2017), over recent years and will continue to do so, in my opinion.
References
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