PredictWallStreet pairs real-time quotes with trader sentiment

PredictWallStreet pairs real-time quotes with trader sentiment

Source: PredictWallStreet

PredictWallStreet, the global online stock prediction community, today announced the pairing of real-time stock and index quotes with real-time trader sentiment based on daily polls to facilitate faster data delivery which can result in more powerful intraday trading insights.

Predictions from PredictWallStreet’s online community of thousands of traders and investors are aggregated and processed via proprietary collective intelligence algorithms to produce daily forecasts of stock and index movements.

“While these patented prediction and forecasting technologies are designed to give investors a powerful edge in the market, we continually strive to sharpen that edge,” notes Craig Kaplan, CEO. He adds that “while these forecasts, alone, can be valuable trading tools, combining them with real-time quotes distributed by Interactive Data will enable more insightful trading decisions throughout the day.”

“We are pleased to provide the real-time market data delivery component to PredictWallStreet to support important investment decisions for their subscribers,” said Bill Chambers, Vice President and General Manager for Wealth Solutions at Interactive Data.

High-frequency trading concerns return to the fore

High-frequency trading concerns return to the fore

High-frequency trading has risen to the forefront of hedge fund regulatory concerns, according to a new report.

High-frequency trading concerns return

High-frequency trading concerns return

While the level of regulatory concern remains far from 2011 levels, it has increased since last year, according to the report, which was published yesterday by research firm Tabb Group. The research was based on conversations with 63 head traders of US hedge funds, managing $301 billion in total assets.

The research said: “In light of the public debate and media scrutiny of market structure issues, such as exchange order type disclosure, the hash crash, and early looks at machine readable economic indicators, concerns over high frequency trading have risen. Meanwhile, with initial registration costs in the rearview mirror, compliance costs concerns have dropped off.” (See graph bottom-right)

Top of the list is uncertainty regarding how hedge funds will be treated under mandatory registration with the US Securities and Exchange Commission for managers running $100 million or more, and the implications of Form PF, which requires them to provide information on the hedge funds they run to the Financial Stability Oversight Council, the report found.

Fluent Trade Technologies Selects Solace Systems to Fuel Automated Trading Systems and Broker |

See on Scoop.itThe FIX Protocol and multi asset electronic trading.
Fluent Trade Technologies Selects Solace Systems to Fuel Automated Trading Systems and Broker
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Informatica Highlights Performance of SMX Messaging

Informatica Highlights Performance of SMX Messaging

blog | June 18, 2013 – 2:34am | By Pete Harris

Following on from last month’s announcement of Ultra Messaging SMX, Informatica has published a range of latency and throughput performance figures for the shared memory transport, covering a number of programming languages. Messaging latency as low as 39 nanoseconds was recorded, with overall latency more than 16 times lower than tests conducted on an earlier version of the transport, conducted in May 2010.

Ultra Messaging SMX is designed for messaging within a single server – in fact within a single multi-core chip, an architecture that has become increasingly adopted as Intel has rolled out its Sandy Bridge (and now Ivy Bridge) microprocessors – with up to 12 cores on certain Ivy Bridge chips. On chip cache memory is leveraged by SMX, since it is faster than fetching data from standard RAM.

Latency tests were conducted between threads running on the same core (2 threads per core are supported by Intel) and between cores on the same chip. Throughput tests were conducted from one thread to threads across many cores on the same chip. Informatica did not test latency between cores across sockets, since it would have been higher than for a single socket.  

Informatica tested its transport against C, C# and Java APIs, noting that trading systems are often built using a number of languages and so such support is a typical requirement. The test systems for latency included one server with an Intel Xeon E5-1620, with 4 cores, clocked at 3.6 GHz, while for throughput tests a server with a (pre-release) 10 core Ivy Bridge chip, operating at 2.8 GHz, was used. CentOS and Red Hat Linux operating systems were hosts for the C and Java tests, with Microsoft Windows 7 Professional SP1 supporting the C# tests.  

Some highlights from the tests are:

* Thread to thread latency on same core, for the C API, and 16 byte messages, was 39 nanoseconds. The same for 128 byte messages was 48 nanoseconds, for 512 byte messages was 81 nanoseconds. 

* Thread to thread latency on a sibling core, for the C API, was 103 nanoseconds for 16 byte messages, 111 nanoseconds for 128 byte messages, and 135 nanoseconds for 512 byte messages.

* C# and Java latencies were a bit higher.  For example, latency for 512 byte messages between threads on the same core was 135 nanoseconds for C# and 106 nanoseconds for Java.

* As an example of a throughput test, 16 byte messages were transmitted from one thread to up to 19 other threads on the same chip. With 19 receivers and the C API, throughput of 133.92 million messages/secomd was achieved, without batching of messages. Batching – which increases latency – increased this to 305.34 million messages/second. Informatica found that throughput increased nearly linearly as receivers were added.

While the significant decrease in high frequency trading has reduced the overall need for such low latency transports, Informatica notes that it is still required for other trading operations and strategies, such as arbitrage, market making and smart order routing.

DataFluidics™, Reflex™, a revolutionary data processing platform for financial institutions.

DataFluidics Releases Reflex, Changes the Landscape of Ultra-Low Latency Data Processing

DataFluidics™, the innovative provider of ultra-low latency technology today announced the general availability of Reflex™, a revolutionary data processing platform for financial institutions. In increasingly fragmented markets where volume-driven automated strategies span time zones and hunt razor-thin windows of opportunities, modern trading desks can no longer be satisfied with the ability to make split-second decisions based on a single market data feed. Traders can no longer rely on single-exchange connectivity either. The new frontier of profitability dictates that advanced trading firms combine and analyze several data sources to reach a decision and instantly dispatch orders to multiple destinations. Yet many current infrastructures remain tied to legacy paradigms of single-input / single-destination whose performance dramatically erodes if multi-channel logic is retrofitted into them. Firms can no longer capture profits.

Reflex was built differently. The fruit of several years of cutting-edge research, Reflex leverages the latest architectural paradigms combined with field knowledge of founder and CEO Daniel Kopko at some of the largest and most profitable firms on Wall Street.

“Reflex was built on the tangible requirement to reshape the way firms process data in today’s trading landscape”, says Kopko. “For many years I observed how firms were prevented from enacting trading ideas because the legacy platforms their execution systems were built on could not accommodate the complex interwoven streams of analytics data and real-time prices which they required.”

Reflex is optimized to enable the combination and correlation of several streaming data feeds to produce composite decisions based on highly-advanced scheduling and processing rules. With reactions capable of achieving ultra-low latency of 1.6 microseconds (with a 99 percentile of 2.5 microseconds), Reflex sets a new standard for software-based solutions which can now directly compete with more expensive alternatives such as custom FPGAs.

“The financial industry is a critical juncture: as the markets recover, some firms will reap the profits of technological choices that will pave the way to substantial gains while others will be left behind”, says Kopko. “We are delighted to make Reflex available as a credible counterpoint to costly, intractable technologies.”

Reflex can be licensed stand-alone or through OEM agreement as embedded technology to enable ultra-low latency trading decisions. The technology can also be purchased or distributed by third-party firms.

For more information or to start a free evaluation of the software, visit or contact



Seeing in the Dark: The Rise of Dark Pools, and the Danger Below the Surface :: TabbFORUM – Where Capital Markets Speak

Seeing in the Dark: The Rise of Dark Pools, and the Danger Below the Surface :: TabbFORUM – Where Capital Markets Speak.

Julian King, Commercial Director of VOLTA talks to ATMonitor

Julian King, Commercial Director of VOLTA talks to ATMonitor

NovaSparks releases test results showing 1.4 microsecond performance at deterministic speeds

NovaSparks releases test results showing 1.4 microsecond performance

First Published 3rd June 2013

NovaSpark said it processed market data at deterministic speeds of 1.4 microseconds, based on testing by the Securities Technology Analysis Center.–performance

Paris – NovaSparks, an FPGA market data company, said it was releasing audited performance benchmarks that showed its ability to process market data at deterministic speeds of 1.4 microseconds.

The 1.4 microseconds mean latency rate is maintained when market data is accelerated 20 times actual market speed and equate to a millisecond peak rate of 18.9 million messages per second, the company said.

“Deterministic processing of market data at ultra-low latency rates is a breakthrough for an industry that is constantly re-assessing their ability to trade across all market conditions,” said Michal Sanak, CIO at proprietary trading firm RSJ, which is listed as the largest NYSE Liffe trader.

The accelerated data was replayed from NASDAQ TotalView ITCH 4.1 feed during the Open and Close periods of the day. These periods are considered the most challenging time of day to maintain a full depth of book at deterministic speed, the company said.

Conducted by the Securities Technology Analysis Center (STAC), the detailed latency benchmark, called STAC-M1 is available to the public.

The benchmark includes all the tasks to receive, build and maintain a full depth of book starting at the time the first byte of the packet is received by the system. The specification provides a reproducible framework for measuring the performance of traditional software-based solutions as well as pure FPGA solutions like the NovaSparks Market Data Matrix.”The tests are specified by trading firms and represent challenging scenarios based on their experiences in the real world,” said Peter Lankford, STAC Director. “The tests rigorously measure ‘wire-to-memory’ latency, leaving nowhere to hide.”

“As an industry, we need to cut back on the amount of duplicative testing that takes place and start to share more best practices” states Olivier Baetz, chief operating officer of NovaSparks North America. “We believe that full performance transparency will help trading firms determine the business case for deterministic market data processing.”

The Market Data Matrix is available for 27 feeds covering major equities and futures exchanges which exhibit similar deterministic microsecond speeds. The Market Data Matrix Feed Handlers include a distribution layer in the FPGA architecture that allows connection of up to 21 trading servers without any loss of performance, the company said.

NovaSparks said the benchmark tests were available at and

Top tier investment bank chooses Fixnetix

Top tier investment bank chooses Fixnetix

First Published 29th May 2013

Leading non-EU regulated investment bank selects Fixnetix managed services provider for centralised data management and order routing in Europe.

Hugh Hughes, Chief Executive, Fixnetix

Hugh Hughes, Chief Executive, Fixnetix

“Our customer chooses Fixnetix for operational efficiency, support, speed and reliability.”

London – Fixnetix, the managed services provider for low latency market data, trading and risk control, has announced that a leading non-EU regulated tier one bank has signed a multi-million pound three year contract for Fixnetix to deliver market data, trading execution and post trade services to the enterprise in Europe.

The company says the advantages of outsourcing market data and trading management are to alleviate complexities with increasing amounts of data and to support operational demands for tighter efficiency.

“The complexity of managing market data has increased with the rising volume of electronic communications,” says Hugh Hughes, Chief Executive, Fixnetix. “Our customer chooses Fixnetix for operational efficiency, support, speed and reliability,” says Hughes.

“We established ourselves as market data and trading vendors when the company was founded seven years ago. Since then, Fixnetix has worked hard to deliver multiple formats of data integrated with seamless trading execution solutions and we are still to this day constantly innovating to ensure the best end product,” comments Hughes.

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