Historical Background and Electronification of Securities Trading The electronification of securities trading commenced 40 years ago, when the National Association of Securities Dealers (NASD) started its computer-assisted market making system for automated quotation (AQ) in the U.S., forming what is nowadays known as NASDAQ (Black 1971a; Black 1971b). In Europe, the first computer-assisted equities exchanges launched their trading services in the 1980s, but not until the 1990s securities trading was organized in fully automated exchanges. The majority of market models of those fully automated equities exchanges are implemented as electronic central limit order books (CLOB), which store market participants‘ trading interests visible to and executable for all other connected traders. According to Pagano and Roell (1996) and Jain (2005), the transparency induced by the introduction of CLOBs reduces information asymmetry, enhances liquidity and supports efficient price determination. While prices were determined manually in floor trading, orders are matched automatically according to price-time priority in electronic trading systems.4 By applying uniform rules to all market participants, operational fairness and fair access to the respective trading venue shall be ensured (Harris 2003). Thereby, the electronification of securities markets and the electronic connectivity of market participants went hand in hand, leading to decentralized market access. Physical trading floors were not required any longer and have mostly been replaced by electronic trading systems. Investors can submit their orders electronically to a market‘s backend from remote locations. On the investors‘ side, human trading processes have been substituted by electronic systems, too. While systems generating automated quotes and stop-loss orders were the first technological artifacts that conquered the trading process, in recent years information technology (IT) has successively established and can nowadays be found on every stage of trading and post-trading processes. State-of-the-art technology has developed as a crucial competitive factor for market operators in recent decades and market participants themselves continued to further automate and optimize their trading processes along the entire value chain. 4 Although slight modifications exist, price-time priority has established as a de-facto standard in securities trading globally.
2.2 Drivers for Widespread Usage of Algorithmic/High-Frequency Trading The emergence of AT and HFT in the past went hand in hand with other market structural developments in European securities trading. In the following, multiple drivers for the rise of AT and HFT are identified, i.e. new market access models and fee structures, a significant reduction of latency and an increase in competition for and fragmentation of order flow5. In most markets, only registered members are granted direct access.6 Hence, those members are the only ones allowed to conduct trading directly, leading to their primary role as market access intermediaries for other investors. Market members performing that function are referred to as brokers7. In the past, those access intermediaries transformed their clients‘ general investment decisions into orders that were allocated to appropriate market venues. As the cost awareness of the buy side has increased over the years, brokers have begun to provide different market access models, i.e. direct market access (DMA) and sponsored access (SA). When an investor makes use of DMA, his orders are no longer touched by the broker, but rather forwarded directly to the markets through the broker‘s infrastructure. One key characteristic of DMA presents the fact that the respective broker can conduct pre-trade risk checks. Sponsored access (SA) represents a slightly different possibility for the buy side to access a marketplace. Here, an investment firm (that is not a member of the respective market) is enabled to route its orders to the market directly using a registered broker‘s member ID without using the latter‘s infrastructure (in contrast to DMA). Resulting from this setup, the sponsor can conduct pre-trade risk checks only if the option to conduct those checks is provided by the trading venue (filtered SA). In case of unfiltered (also referred to as naked) SA, the sponsor only receives a drop copy of each order to control his own risk exposure. A reduction in latency represents the main advantage of SA over DMA from a non-member firm‘s perspective and therefore is highly attractive for AT or HFT based trading strategies. Another driver for the success of AT and HFT is the new trading fee structures found in Europe. Market operators try to attract order flow that is generated automatically (i) by applying special discounts for algorithmic orders within their fee schedules. MTFs 5 Obviously, this list of drivers is not exhaustive. Other drivers that could be listed additionally include, e.g., the growing number of proprietary trading firms founded by former investment bank staffers and other mathematically/technically oriented traders. 6 Access is restricted to registered market members mainly due to post-trading issues, i.e. clearing and settlement. A pre-requisite for trading directly in a market is an approved relationship with the respective clearing house(s). 7 As brokers basically offer their services to other market participants they are also referred to as the sell side. Respective clients purchasing those services are referred to as the buy side (Harris 2003). implemented (ii) fee schedules with very aggressive levels to compete with incumbent exchanges. Furthermore, some MTFs like e.g. Chi-X, BATS or Turquoise started offering pricing schemes that are a novelty to European exchange fee schedules: (iii) asymmetric pricing (Jeffs 2009; Mehta 2008). With asymmetric pricing, market participants removing liquidity from the market (taker) are charged a higher fee while traders that submit liquidity to the market (maker) are charged a lower fee or are even provided with a rebate. Such an asymmetric fee structure is supposed to incentivize liquidity provision. Faced with the MTFs‘ aggressive pricing strategies, many European exchanges were urged to lower their fee levels as well, while others even adopted the asymmetric pricing regime. As will be further explained in section 4, market participants have specialized in making profits from those fee structures by applying trading algorithms. Although latency has always been of importance in securities trading, its role is more intensely stressed by market participants with AT/HFT on the rise. In traditional trading involving human interaction on trading floors, a trader could also profit from trading faster than others. Traders often benefited from their physical abilities, e.g. when they could run faster across the trading floor or shout louder than their counterparts and thus drew a market maker‘s or specialist‘s attention to their trading intentions. With algorithms negotiating on prices nowadays, those physical advantages are no longer needed. Nevertheless, in markets trading at high speed, the capability to receive data and submit orders at lowest latency is essential. When the market situation at the arrival of an order differs significantly from the market situation, which led to that particular trading decision, there is a risk that the order is no longer appropriate in terms of size and/or limit (Harris 2003; Brown and Holden 2005; Liu 2009). Hence, an order bears the risk of being executed at an improper price or not being executed at all. To minimize that risk, reducing the delay of data communication with the market‘s backend is of utmost importance to AT/HFT based strategies concerning market data receipt, order submissions and execution confirmations. In order to reduce latency8, automated traders make use of co-location or proximity services that are provided by a multitude of market operators.9 By co-locating their servers, market participants can place their trading machines directly adjacent to the market operator‘s infrastructure. Regulation in European securities trading has promoted the market penetration of AT/HFT as well: with the advent of MiFID (European Commission 2004), the European equity trading landscape became more complex. As intended by the regulator, competition among market venues has increased, and the available liquidity in a security is scattered among different market venues (Gomber et al. 2011b). This fragmentation of markets is a direct consequence of the harmonized level playing field for different types of trading venues intended by MiFID. In order to attract market share, new venues challenged the incumbent exchanges by lower trading fees and forced them to adapt their pricing schemes as well. These recently emerged MTFs steadily increased their market penetration. The lowered costs of trading (both explicit and implicit10) are beneficial for all market participants including issuers, as lower trading costs increase liquidity and thereby lower the cost of capital. However, Over the Counter (OTC)-trading11 represents a high and stable market share around 40% (see Figure 112). 0%20%40%60%80%100%OTCRMMTF Figure 1: Distribution of trading among regulated markets, MTFs and OTC, based on Thomson Reuters (2008, 2009, 2010) Market participants are urged to compare potential prices offered as well as different fee regimes across a multitude of market venues, which imposes increased search costs for the best available price. In addition, dark pools and OTC trading, which are exempted from pre-trade transparency, distort the clear picture of available prices. Against this background, algorithms support market participants to benefit from competition between markets and help to overcome negative effects from fragmentation of order flow
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