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The digital revolution, which started in the late s, was the catalyst that helped meet these expectations. It found expression, inside the dealing room, in the installation of a digital data display system, a kind of local network. Incoming flows converged from different data providers,  and these syndicated data were distributed onto traders' desktops.
One calls a feed-handler the server that acquires data from the integrator and transmits them to the local distribution system. This infrastructure is a prerequisite to the further installation, on each desktop, of the software that acquires, displays and graphically analyses these data.
Two software package families were belonging to this new generation of tools, one dedicated to Windows-NT platforms, the other to Unix and VMS platforms. However Bloomberg and other, mostly domestic, providers, shunned this movement, preferring to stick to a service bureau model, where every desktop-based monitor just displays data that are stored and processed on the vendor's premises.
The approach of these providers was to enrich their database and functionalities enough so that the issue of opening up their datafeed to any spreadsheet or third-party system gets pointless.
This decade also witnessed the irruption of television inside trading rooms. Press conferences held by central bank presidents are henceforth eagerly awaited events, where tone and gestures are decrypted. The trader has one eye on a TV set, the other on a computer screen, to watch how markets react to declarations, while having, very often, one customer over the phone. The development of the internet triggered the fall of the cost of information, including financial information.
It hit a serious blow to integrators who, like Reuters, had invested a lot the years before to deliver data en masse and in real time to the markets, but henceforth recorded a wave of terminations of their data subscriptions as well as flagging sales of their data distribution and display software licences.
Moreover, the cable operators' investors lead to a huge growth of information capacity transport worldwide. Institutions with several trading rooms in the world took advantage of this bandwidth to link their foreign sites to their headquarters in a hub and spoke model. The emergence of technologies like Citrix supported this evolution, since they enable remote users to connect to a virtual desktop from where they then access headquarters applications with a level of comfort similar to that of a local user.
While an investment bank previously had to roll out a software in every trading room, it can now limit such an investment to a single site. The implementation cost of an overseas site gets reduced, mostly, to the telecoms budget. And since the IT architecture gets simplified and centralised, it can also be outsourced. Indeed, from the last few years, the main technology providers [ who?
From the late s, worksheets have been rapidly proliferating on traders' desktops while the head of the trading room still had to rely on consolidated positions that lacked both real time and accuracy. The diversity of valuation algorithms, the fragility of worksheets incurring the risk of loss of critical data, the mediocre response times delivered by PCs when running heavy calculations, the lack of visibility of the traders' goings-on, have all raised the need for shared information technology, or enterprise applications as the industry later called it.
But institutions have other requirements that depend on their business, whether it is trading or investment. Within the investment bank, the trading division is keen to implement synergies between desks, such as:. Hence a number of package software come to the market, between and Though Infinity died, in , with the dream of the toolkit that was expected to model any innovation a financial engineer could have designed, the other systems are still well and alive in trading rooms.
Born during the same period, they share many technical features, such as a three-tier architecture , whose back-end runs on a Unix platform, a relational database on either Sybase or Oracle , and a graphical user interface written in English, since their clients are anywhere in the world. These functions will be later entrenched by national regulations, that tend to insist on adequate IT: Telephone, used on over-the-counter OTC markets, is prone to misunderstandings.
Should the two parties fail to clearly understand each other on the trade terms, it may be too late to amend the transaction once the received confirmation reveals an anomaly. The first markets to discover electronic trading are the foreign-exchange markets. Reuters creates its Reuter Monitor Dealing Service in Contreparties meet each other by the means of the screen and agree on a transaction in videotex mode, where data are loosely structured.
Its next generation product, an electronic trading platform called Dealing , ported on Windows, is launched in Like EBS , which competes with it head-on from , it mostly handles spot trades.
Several products pop up in the world of electronic trading including Bloomberg Terminal , BrokerTec , TradeWeb and Reuters Xtra for securities and foreign exchange. More recently other specialised products have come to the market, such as Swapswire , to deal interest-rate swaps, or SecFinex and EquiLend, to place securities loans or borrowings the borrower pays the subscription fee to the service.
However, these systems also generally lack liquidity. Contrarily to an oft-repeated prediction, electronic trading did not kill traditional inter-dealer brokerage. Besides, traders prefer to mix both modes: For organised markets products, processes are different: Orders are subsequently executed, partially of fully, then allocated to the respective customer accounts.
The increasing number of listed products and trading venues have made it necessary to manage this order book with an adequate software. Stock exchanges and futures markets propose their own front-end system to capture and transmit orders, or possibly a programming interface, to allow member institutions to connect their order management system they developed in-house.
But software publishers soon sell packages that take in charge the different communication protocols to these markets; The UK-based Fidessa has a strong presence among LSE members; Sungard Global Trading and the Swedish Orc Software are its biggest competitors. In program trading , orders are generated by a software program instead of being placed by a trader taking a decision. More recently, it is rather called algorithmic trading. It applies only to organised markets, where transactions do not depend on a negotiation with a given counterparty.
A typical usage of program trading is to generate buy or sell orders on a given stock as soon as its price reaches a given threshold, upwards or downwards. A wave of stop sell orders has been largely incriminated, during the financial crises, as the main cause of acceleration of the fall in prices.
However, program trading has not stopped developing, since then, particularly with the boom of ETFs , mutual funds mimicking a stock-exchange index, and with the growth of structured asset management; an ETF replicating the FTSE index, for instance, sends multiples of buy orders, or of as many sell orders, every day, depending on whether the fund records a net incoming or outgoing subscription flow.
Such a combination of orders is also called a basket. Moreover, whenever the weight of any constituent stock in the index changes, for example following an equity capital increase, by the issuer, new basket orders should be generated so that the new portfolio distribution still reflects that of the index. If a program can generate more rapidly than a single trader a huge quantity of orders, it also requires monitoring by a financial engineer , who adapts its program both to the evolution of the market and, now, to requirements of the banking regulator checking that it entails no market manipulation.
Some trading rooms may now have as many financial engineers as traders. The spread of program trading variants, many of which apply similar techniques, leads their designers to seek a competitive advantage by investing in hardware that adds computing capacity or by adapting their software code to multi-threading , so as to ensure their orders reach the central order book before their competitors'.
The success of an algorithm therefore measures up to a couple of milliseconds. This type of program trading, also called high-frequency trading , conflicts however with the fairness principle between investors, and some regulators consider forbidding it. With order executions coming back, the mutual fund's manager as well the investment bank's trader must update their positions. However, the manager does not need to revalue his in real time: Still, the manager needs to check that whatever he sells is available on his custodial account; he also needs a benchmarking functionality, whereby he may track his portfolio performance with that of his benchmark ; should it diverge by too much, he would need a mechanism to rebalance it by generating automatically a number of buys and sells so that the portfolio distribution gets back to the benchmark's.
In most countries the banking regulation requires a principle of independence between front-office and back-office: Both services must report to divisions that are independent from each at the highest possible level in the hierarchy. In Germany, the regulation goes further, a "four eyes' principle" requiring that every negotiation carried by any trader should be seen by another trader before being submitted to the back-office.
In Continental Europe, institutions have been stressing, since the early s, on Straight Through Processing STP , that is, automation of trade transmission to the back-office. Their aim is to raise productivity of back-office staff, by replacing trade re-capture by a validation process.
Publishers of risk-management or asset-management software meet this expectation either by adding back-office functionalities within their system, hitherto dedicated to the front-office, or by developing their connectivity, to ease integration of trades into a proper back-office-oriented package. Anglo-Saxon institutions, with fewer constraints in hiring additional staff in back-offices, have a less pressing need to automate and develop such interfaces only a few years later.
On securities markets, institutional reforms, aiming at reducing the settlement lag from a typical 3 business days, to one day or even zero day, can be a strong driver to automate data processes.
As long as front-office and back-offices run separately, traders most reluctant to capture their deals by themselves in the front-office system, which they naturally find more cumbersome than a spreadsheet, are tempted to discard themselves towards an assistant or a middle-office clerk.
An STP policy is then an indirect means to compel traders to capture on their own. Moreover, IT-based trade-capture, in the shortest time from actual negotiation, is growingly seen, over the years, as a "best practice" or even a rule.
Banking regulation tends to deprive traders from the power to revalue their positions with prices of their choosing. However, the back-office staff is not necessarily best prepared to criticize the prices proposed by traders for complex or hardly liquid instruments and that no independent source, such as Bloomberg, publicize. The ADA does not directly or indirectly practice medicine or dispense dental services.
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