The rise of algorithmic trading
The action of trading financial instruments has experienced several game-changing jumps in development over the course of its storied history. Regardless of the continuous changes, investing and trading stay a significant subject, though most dealers are comfortable setting busy trading as an art form. Definitely, the impact which the Internet has caused our everyday lifestyle and leisure is unmatched, and its impact on our financial markets has become revolutionary. Just about any task an institutional dealer or retail dealer has been influenced by, or credited to, ever-changing technology.
The late 1990s indicated the conclusion of this physical age of their financial markets. Iconic financial centers like the New York Stock Exchange and Chicago Mercantile Exchange started to promote electronic trading, and in essence, changed the structure of their enterprise. New order-routing systems based on Internet connectivity and electronic trading platforms were constructed. The outdated brick-and-mortar exchanges could provide investors and traders access to the exact same financial products, but on a worldwide scale.
Since net-based technologies continued to advance, the usage of electronic-trading platforms improved quickly. Immediate connectivity, greater number, and falling trade costs all became accessible to the ordinary individual. Obviously, the positions of the individual retail dealer or investor climbed. Volumes jumped in just about any market. For example, on the biggest stocks trade in the world, the NYSE, the average daily volume of shares traded grew from 809 million shares in 1999, to 1.6 billion shares in 2005. The addition of trading programs based upon Internet technologies had augmented quantity, but what’s more, the rate where you can implement a trade was improved radically.
Greatly increased trade rates gave the new digital exchanges, in addition to the present institutional trades, the capability to process larger volumes than ever before. Indirectly, the rising volumes generated markets which were vulnerable to increased volatility and lightning-fast prices changes. In an effort to keep up with the growing market, a few market participants opted to automate trading operations.
As information systems technologies grew, it became possible to carry out complex mathematical computations in real time. Trading systems predicated upon complex statistical formulae were created and executed, and the new field of algorithmic trading has been created.
The expression”algorithmic trading” refers to the custom of using computers to put trades mechanically based on specified criteria included within the program’s programming language. The execution of algorithmic trading, in the context of this digital market, is contingent on the growth of a detailed trading platform. The trading system should incorporate a pair of parameters, both bodily and finite in extent. These parameters are a manifestation of this trading strategy, and also in algorithmic trading, are all predicated upon mathematical computations of diverse complexity.
Whatever the degree of elegance, it isn’t feasible to run algorithmic trading operations without possessing a trading platform.
Automation is utilized in an effort to execute each transaction inside the algorithmic trading platform absolutely, constantly and with no emotion. As put by mythical futures trader Larry Williams,”trading systems work; systems traders do not.”
The ability to enter and exit the market quickly and efficiently can be crucial to the success of an individual trade and to the longevity of a trading system. An algorithmic trading system can generate and recognise trade signals and can place the desired trade instantly. From the standpoint of the trader or investor, algorithmic trading systems can serve as a valuable time-saving device. In a marketplace where order execution times are measured and quantified using milliseconds, saved seconds are at a premium.
In the electronic marketplace, the issue of latency is an important one. Latency, as it pertains to electronic trading, refers to execution time. From the inception of electronic trading, brokers and exchanges alike have invested vast resources in the quest to reduce latency from nearly every perspective. In a 2009 survey studying proprietary trading firms focused on the forex market, it was found that nearly 65% of firms utilised automated trading systems that incorporated algorithms, and 89% planned on increasing capital investment on low latency technologies.
Algorithmic Trading: Challenges And Pitfalls
Several large drawbacks can influence and hinder the effectiveness of an algorithmic trading system. Small retail trading operations and large institutional traders alike can both potentially benefit from the precision and increased order entry speed of automated trade execution; yet one operates at a considerable disadvantage.
Computer, Internet, and information systems technology are ever-evolving disciplines with the unflinching desire to move forward. Technology within the scope of the financial marketplace is no different. Large capital expenditures are undertaken constantly by market participants in an attempt to keep up, or in a few cases, to create an edge. Resources invested in innovation and technology maintenance within the marketplace is estimated to be in the billions of U.S. dollars annually. Unfortunately, not all traders are capitalised to the degree that they can stay on the technological lead lap.
Although small retail traders and large institutional traders conduct operations within the same electronic marketplaces, each has a vastly different path to the very same market. Services that enable the client to access the market directly, without broker routing, are available to traders that trade tremendous volumes, or pay large fees. This service is known as direct market access, or DMA.
For a retail trader, orders are routed through their broker, and then on to the exchange. The latency concerning the order’s execution is greater than that of the trader utilising a direct market access infrastructure. The prevalence of algorithmic trading systems create this scenario. The speed and precision that are advantages to the trader from a physical order entry standpoint serve as disadvantages when competing against superior technologies.
Asymmetric information is defined as being a situation in which one party to a transaction has information about the transaction that the other party is not privy. The electronic marketplace, specifically the implementation of algorithmic trading systems, provides market participants the ability to act on economic information instantaneously. Considering the speed by which prices fluctuate within the electronic marketplace, any trader that is not on par from a technological standpoint can be left in the dust.
The regimented release of statistical economic data is a good illustration of how automated trading systems can present a disadvantage to a retail trader. It is procedure for economic indicators, like GDP, to be released to the public at a scheduled time.
Traders quickly interpret the information in a number of different ways and place trades in an attempt to capitalise on the subsequent volatility. It stands to reason that a trader who receives the information first has an advantage over those who do not. Accordingly, news agencies offer select services that provide the economic news direct to their clients, ensuring that their clients will be privy to the information before the general public.
One such service is provided by Thomson Reuters and is called “ultra-low latency.” The package is priced at US$2,000 per month and guarantees the economic data release be delivered to the client two seconds ahead of the public. Without the ability to act substantially within a two-second window, the gap in time is insignificant. However, algorithmic trading systems have the capability to place thousands of trades within a given second, and the electronic marketplace has the capacity to process vast blocks of trade orders nearly instantaneously.
Getting a”leap” on other traders has been around since the inception of trading itself. The ability to act instantly on information can be attributed solely to the automation of trade execution, and indirectly, by the practice of algorithmic trading.
PROGRAMMING ERRORS AND SYSTEM DISRUPTIONS
The functionality of an algorithmic trading system relies upon hardware to be operational during the execution of trades. Dedicated computers, servers and Internet connections are required to facilitate proper function of the system. Intermittent outages in electricity and Internet connectivity can compromise a given trade’s execution. Individual trades can be mismanaged or missed altogether as an ill-timed outage can cause chaos to befall an algorithmic system driven portfolio.
Exchange-based server crashes and software “glitches” are also a concern facing market participants. The botched IPO launch of Facebook on the Nasdaq exchange in 2012 was an example of an automated programming glitch producing chaotic market conditions. Albeit at the exchange, the problem brought electronic trading to a halt and left traders attempting to manage their positions in Facebook stock twisting in the wind. The Nasdaq exchange was fined US$10 million for the meltdown.
In 2011, Knight Capital experienced a software “glitch” in one of its proprietary trading systems. Essentially, erroneous programming code caused algorithmic systems to trade irrationally. The result was devastating as Knight lost US$440 million in one trading session. From a retail trader’s perspective these exchange meltdowns exist beyond control. If an individual trader’s system happens to be active during an exchange meltdown or falls victim to a “glitch,” then the result could be disastrous.
Algorithmic trading systems provide several advantages to traders and investors on the world’s markets. However, the technologies upon which the electronic marketplace is based are susceptible to failures, which lie outside of the control of the individual trader.
The word”exchange” is described as being the action of exchanging something to get something different. The choice of whether to embrace an algorithmic trading system is based inside every industry player. In case the need to boost order entry rate, accuracy, and consistency outweighs the chance of working at a competitive disadvantage or becoming trapped in an exchange-based collapse, then the dealer might wish to think about making the transaction.
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