A-Team IQ talks to SunGard’s Harold Finders and Yassine Brahim about the takeover of GL Trade; what the Oracle-Sun tie up means for the fintech industry; Why Brazil is becoming the offshore location of choice for the European financial sector; following Lehman’s collapse, why knowing your counterparty is essential for risk management; market data platforms for the real world; can Twitter deliver results for fintech companies, and more…
Download Issue 8 of A-Team Insight Quarterly here
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On 11 Jun 2009 |
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.
Sponsored by:

DOWNLOAD THE WHITE PAPER
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On 09 Jun 2009 |
Download this special report for FREE now! Click the link below.
Whether 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.
In essence, the world of algorithmic trading is entering a new phase as models’ acceptance by the wider marketplace is increasing pressure on firms to perform and, to some extent, productize their offerings. Expect more innovation, more customization and more choice.
Download the special report now by clicking the link below — no registration required.
Algorithmic Trading - Attracting The Buy Side (1.6 MiB)
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| On 19 May 2009 |
Some four months after its Version 1.0 product release, Marketcetera has updated its open source automated trading platform to improve P/L reporting, add functionality to address increasingly fragmented liquidity, enhance multi-user controls and provide support for co-location, while offering statistics that point to significant interest not only in the platform itself, but also to the adoption of open source technologies in general in the financial markets.
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| On 18 May 2009 |
News analysis provider RavenPack has partnered with complex event processing (CEP) platform supplier Aleri to develop what they are calling the first news-based signal generation machine.
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| On 24 Apr 2009 |
Swedish agency broker Neonet has added algorithmic models and other trading tools for equities and futures from Credit Suisse Advanced Execution Services (AES). The deal gives Credit Suisse’s buy-side clients access to Neonet’s Execution Management Solution, enabling traders to manage programme and single name orders for best execution results.
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| On 24 Apr 2009 |
Credit Suisse’s Advanced Execution Services (AES) unit has introduced direct market access and algorithmic trading in five new markets. The Bank will execute trades on the Abu Dhabi Securities Exchange (ADX), the Cairo and Alexandria Stock Exchanges (CASE), the Dubai Financial Market (DFM), the Istanbul Stock Exchange (ISE) and the Tel Aviv Stock Exchange (TASE).
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| On 24 Apr 2009 |
Agency broker Investment Technology Group (ITG) has added Dynamic Implementation Shortfall (Dynamic IS) to its ITG Algorithms suite of trading tools in Europe. This list-based algorithm is designed for portfolio and quantitative traders whose main objective is to minimise implementation shortfall and manage risk while optimising their entire portfolio, especially in volatile conditions.
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| On 23 Apr 2009 |
CEP specialist Progress Apama has released an enhanced Parallel Correlator that leverages multi-core, multi-processor functionality to deliver superior processing performance. In particular, internal benchmark testing using real-world customer scenarios revealed a seven-fold increase in event processing performance on an eight core machine. In a separate development, Apama has integrated its Algorithmic Trading Accelerator with Vhayu Technologies’ historical data platform.
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| On 22 Apr 2009 |
Data management and analytics specialist OneMarketData has integrated its OneTick database with QuantHouse’s QuantFactory trading strategy toolkit. The OneTick Database leverages a proprietary low-latency architecture that collects and processes millions of ticks per second on a single CPU and archives billions of ticks per day globally, providing uniform access to tick data, up to and including the latest tick.
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