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Electronic Trading Special Report: Machine Readable News and Algorithmic Trading

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It may have been a long time coming, but it appears that machine-readable news’ time has come. With today’s emphasis on fast, automated and event-driven markets, the ability to tap events and apply them to computer-based models seems obvious. But until relatively recently, the idea of electronically capturing news–or text-based information–for use in automated processes has been the stuff of science fiction.

Today, machine-readable news is used in a range of supporting roles in trading. Aside from generating trading signals for high frequency traders and other alpha- seekers, it can be used to build sentiment measurement applications, stock screening applications and back-testing systems for trading algorithms. It can be used in support of market surveillance systems. And with more of the major newswire organizations getting in on the act, its use seems set to increase.

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26 Oct 2009
 
New Approaches to Modern Trading Room Design

Download new 8-page briefing from Wey Technology and A-Team Group

In today’s financial markets, trading firms face constant pressures in a fiercely competitive environment. Providing best execution and superlative customer service is fundamental to attracting order flow. Running trading operations efficiently is also an imperative, to minimise costs internally and to offer best value to customers. Despite the increase in recent years of automated and algorithmic trading, the human touch is as important as ever in financial trading. Traders bring a wealth of experience to the art of trading, even when it is driven by computer-generated indicators. Their experience and relationships are vital to seeking out liquidity and efficient execution.

Trading operations overall need to be agile and flexible in order to meet ever changing demands and to rapidly exploit business opportunities. The regrouping of traders to react to – even pre-empt – market demand, requires trading positions that can be immediately configured to individual trader’s preference and information needs. At the same time, management and operational costs of trading operations need to be driven down in reaction to the ever downward pressure on margins. Whether costs are reduced through sharing of information services, through a reduction in maintenance costs, or change management costs, it all adds to the bottom line.

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22 Oct 2009
 
Alternative Trading Systems Directory

Available to Download for Free Now! (Scroll down)

The Who, What, When and Why of the Alternative Liquidity Venues

Welcome to the inaugural edition of the A-Team Alternative Trading Systems Directory. As with our sister publication – the A-Team Algorithmic Trading Directory – we have set out to describe and define a specific segment of the electronic trading marketplace, in the hopes of helping practitioners navigate the increasingly complex world of alternative liquidity venues.

Since we conceived the idea of a directory of alternative trading systems – that is, of electronic trading platforms that offer alternative liquidity venues from the world’s primary exchanges – the execution venue landscape has expanded significantly. This has been particularly true in Europe, where the EU’s Markets in Financial Instruments Directive (MiFID) has spawned a host of Multilateral Trading Facilities (MTFs) and encouraged the proliferation of both independent and broker-sponsored dark liquidity venues, or dark pools. In short, the ATS landscape has become more complex and confusing than ever.

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29 Sep 2009
 
Special Report: Complex Event Processing

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Over the past couple of years, Complex Event Processing has emerged as a hot technology for the financial markets, and its flexibility has been leveraged in applications as diverse as market data cleansing, to algorithmic trading, to compliance monitoring, to risk management. CEP is a solution to many problems, which is one reason why the emerging marketplace is growing, with many vendor options to choose from.

But CEP is not a solution in itself, and so technologists need to concern themselves with how to integrate it within a complete application architecture, how it can best be leveraged, and how to streamline development and deployment. And with multiple vendor choices, choosing the right CEP approach for the job is an important, and early, activity for firms looking to adopt it.

View the full article on Low-Latency.com

18 Jun 2009
 
BACK TO THE FUTURE: Historical Data in High-Frequency Trading

Download new 12-page white paper from the London Stock Exchange and A-Team Group

The adoption of algorithmic trading by the mainstream has created a requirement for high-quality historical data for development, testing and maintenance of trading strategies.

Until recently the exclusive remit of Tier 1 investment banks, algorithmic trading is becoming democratized as smaller brokerages and boutiques implement increasingly affordable high-performance trading platforms. This gives them the opportunity to differentiate their offerings to buy-side clients.

Key to success here is the quality of data. Nowhere is the adage ‘bad data in, bad data out’ more true than in the area of algorithmic and quantitative trading, where the use of highly granular tick and order book data is crucial to producing trading strategies that perform.

Furthermore, increased regulatory scrutiny means firms need to recreate market conditions current during their trading activities, so as to demonstrate due process in meeting their best execution obligations. This all points to the need for a considered approach to sourcing and managing historical data in support of high-performance trading activities.
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11 Jun 2009
 
Algorithmic Trading - Attracting The Buy Side

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et-at-supplement-06-09-150x210Whether they accept it or not, sell-side institutions are finding themselves in the unfamiliar role of information technology vendor. The adoption of algorithmic trading models by buy-side firms of all shapes and sizes is shifting trading strategies, and the technology infrastructure to supply and support them, from the realm of nice-to-have appendage to must-have service offering.

With more sell sides than ever offering both standard benchmarks and their own takes on old favourites, competition between algorithmic trading strategies is heating up. And it’s not all about alpha. The buy side doesn’t like surprises. What many fund managers are seeking from their sell-side suppliers is certainty of execution, low market impact and some degree of accuracy on hitting stated targets.

As a result, brokers and their technology suppliers are all working furiously to help differentiate algorithmic offerings, launching custom and so-called ‘adaptive’ algorithms, and taking great lengths to prove that their models perform as stated on the tin.

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09 Jun 2009
 

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