TORA, provider of the industry’s most advanced cloud-based order and execution management system (OEMS), and OTAS Technologies, a Liquidnet company and specialist provider of market analytics and trader intelligence, announced today that TORA has integrated OTAS Portfolio and Trading Analytics applications into its OEMS platform to help clients generate alpha and meet MiFID II best execution requirements. This development is the latest in a series of enhancements TORA has made to ease the burden on clients as they transition to this new regulatory regime.

Today, portfolio managers and traders are inundated with market data and information on which to base investment and trading decisions. OTAS’ real-time analytics, in combination with TORA’s suite of pre-, in- and post-trade TCA tools, help clients overcome this challenge. OTAS Analytics use artificial intelligence and big data techniques to alert portfolio managers and traders to hidden risks and opportunities that would otherwise be difficult to identify.

OTAS Portfolio Analytics take the challenging work out of monitoring holdings by highlighting exceptional moves in a stock’s price relative to price history and sector peers. OTAS Trading Analytics seek to minimize trading costs by monitoring ongoing market conditions and alerting traders in real-time to exceptional occurrences in volume, price, liquidity and spread.

Commenting on the partnership, Chris Jenkins, Managing Director at TORA said: “The pressure to outperform the market and meet regulatory best execution requirements has never been greater. I’m excited to offer our clients integrated access to the OTAS Portfolio and Trading Analytics applications which will streamline their workflows, help improve their overall performance and enable them to meet MiFID II demands”

“OTAS is committed to delivering the most advanced suite of analytics to help our clients meet regulatory requirements, ensure best execution, and benefit from sophisticated market intelligence to drive better trading decisions in an increasingly competitive market,” said Tom Doris, CEO of OTAS Technologies. “By integrating OTAS Analytics into the TORA OEMS platform, we can give our joint clients access to the most up-to-date information they need to make fast and informed trading decisions whilst improving transparency and efficiency.”

TS strengthens buy-side trading offering with OTAS Integration

Partnership ensures pre and post trade best execution requirements are fulfilled

LONDON, 29 June 2017OTAS Technologies, a Liquidnet company and specialist provider of market analytics and trader intelligence and TS (formerly TradingScreen), the leader in electronic trading platforms, today announced that TS has integrated OTAS Analytics into TradeSmart, their multi-asset OEMS platform. TS clients will now have access to the latest real-time analytics and critical, actionable market intelligence from OTAS to fulfil their pre and post trade best execution requirements.

Operating in the cloud for nearly two decades, TS is a leading expert on SaaS trading technology. TradeSmart OEMS is the standard for workflow efficiency, offering seamless integration with the buy-side, connecting with markets globally and providing traders the access and information they need to optimize their trading performance. By integrating with OTAS, TradeSmart users can minimise total trading costs and respond quickly to live market events. It also serves as another best in class service to help fulfill regulatory obligations, like MiFID 2, in a transparent and seamless manner.

OTAS Trading Analytics provides real-time alerts, standard TCA metrics, a breakdown of market conditions and dynamic alerts allowing orders to adjust according to changing circumstances. The OTAS integration is the newest addition to the TS Partner Program, which was designed to expand TS client offerings and respond to the needs of the buy-side community.

“OTAS is dedicated to helping buy-side firms meet and prove their best execution requirements, improve trading productivity and efficiency and gain the best competitive advantage possible,” said Tom Doris, CEO of OTAS. “We’re excited to join the TS Partner Program and ensure TradeSmart users can reap the benefit of our sophisticated market analytics without any complicated upgrades or infrastructure changes.”

Chief Strategy Officer for TS, Varghese Thomas said “We are thrilled to include OTAS Analytics as the newest member of the TS Partner Program. This strategic network drives collaborative solutions for a simpler more straightforward workflow. The combination of our TradeSmart OEMS multi-asset platform with OTAS’ robust market data analytics equips TS clients with the insights and connectivity for an added advantage to their trading day.”

Discretionary Managers Seek Alpha in Alternative Data

Alternative data providers see huge potential in providing their data to discretionary asset managers who are losing assets to quantitative and systematic funds.

As active managers trail the performance of passive index funds and exchange-traded funds (ETFs), discretionary fund managers are scrambling to consume big data analytics into their decision making process.

While early movers in the big data analytics industry have mainly been quant hedge funds and systematic fund managers, the next wave is going to be discretionary fund managers, according to panelists at an event sponsored by Wall Street Horizon, Estimize, OTAS Technologies and FlexTrade Systems.

“We’re at the point of crossing the chasm. The early adopters have adopted it. And [now we’re] crossing that barrier between early adopters and the mainstream,” said Vinesh Jha, founder and CEO at ExtractAlpha, who spoke at “Uncovering Alpha in Alternative Data Sets” held on May 17.

There’s been an explosion of alternative data sources, such as satellite imagery data and credit card data that didn’t exist 10 years ago, said Leigh Drogen, founder and CEO of Estimize, an open earnings estimates platform, speaking at the event.

However, discretionary asset managers have more difficulty incorporating big data sets because they lack a process, said several panelists.

“The challenge is to provide this content into the trader workflow of the discretionary managers who are not even quants who have a hypothesis about how the market works,” said Tom Doris, founder and CEO at OTAS. Technologies, on the panel. “They look at those signals and data sources in an ad hoc fashion,” said Doris.

Quantitative hedge funds such as Bridgewater and Renaissance Technologies have invested in big data analytics and generated higher returns than many of their peers. “Everybody wants to be them because they want to have returns like them in the systematic quant space,” said Jamie Benincasa, senior vice president and head of global sales at FlexTrade. These firms are household names in the hedge fund space that are probably on an 8-10 year run.

But these firms are not going to reveal which data sets are of value, “or precisely tell you how it works,” said Benincasa. “They want as much data as they can get and they will spend the money to do so,” he said.

Pointing to Quantopian, a platform for quants to create and test their own algorithms, Benincasa predicts that the next generation of alpha generation is going to come from that crowd. Anyone can open an account on Quantopian’s network and create its own algorithms. Quantopian then monitors performance and allocates capital to quants with the best performing strategies.

Defining Alternative Data
While big data is a nebulous term, perceptions are also shifting on what constitutes alternative data. “There has been a bunch of data sets sitting out there but no one thought of them as data,” said Jha. News analytics and social media analytics companies are turning text from 10Qs and 10K filings and earning call transcriptions into data that computers understand. That means turning this data into sentiment or extracting data from them. “Fundamental investors have been using this data for years, but this is alternative data for quants,” said Jha.

Even some of the older data such as earnings estimates has been optimized and is now perceived as alt data. “Our data is the quintessential example of an old data set, an earnings calendar,” said Barry Star, Wall Street Horizon’s founder and CEO. ”We reinvented it,” said Star. “Individually the events that we track could be considered old alpha, but people are constantly coming up with new ways to utilize the data, “ he said. Take the case of date breaks— if the earnings date for a company moves from Monday to Thursday there’s all kinds of information involved in how many days the date moved. Does it move forward? Does it move backward? There is alpha all over that information,” Star said.

Challenges with Workflow Integration
But it can be challenging for hedge funds and asset managers to integrate big data into their front-end investment and trading processes.

Drogen said he’s been contacted by discretionary funds that want to build a quantitative process. Someone with “a good quantitative background in a discretionary firm takes our data, reads our research and takes our factor model and figures out if it would have added alpha.” But the decision is left to the portfolio managers. “The PMs have to buy into it. It is religion vs. a science problem. If they don’t solve this, they’re going to get left behind,” insists Drogen.

According to Doris, the difference between systematic and discretionary manager is mainly that one is process driven, and the other is non-process driven. “So-called systematic managers tweak their models more than discretionary firms alter their portfolio holdings,” he argued. “If they’re already systematic about their approach, they can use the data. It’s not onerous for them to change their process.” The problem then is to get the big data and analytics into the trader’s workflow, said Doris.

“Quants will take the signals directly into a black box, then push out trades via an API to the market because they don’t want anybody to see them,” said FlexTrade’s Benincasa. However, “discretionary managers are looking to funnel the data through their order and execution management systems.”

To bring alternative data into the trader’s workflow, Benincasa cites the integration of the FlexTRADER EMS with OTAS’s market analytics delivered with natural language processing technology, and the Symphony messaging system. From OTAS, traders can capture the natural language, highlight it and send it via Symphony to the PMs. Then the PMs can send an order back, and the trader highlights the order, clicks, and the order lands on FlexTRADER’s blotter. Additionally, social media is available as heat maps and ticks on the blotter, so a trader can now run an alert saying a particular name spiked, get social media sentiment in this name, and determine what is going on, he said. “We’re in the business of consuming these analytics and providing traders with the ability to feed it back from the market to the PMs who may not have access to these data sets,” said Benincasa.

Despite some of these hurdles, discretionary firms are striving to harness alternative forms of data. “The main variable is how they build their teams,” said Drogen. Some firms make the mistake of building a data science/quantitative research team in a separate building and then selling Excel spreadsheets and research reports to the PMs. Those that have done it right build a trading desk with a quant, two engineers, a data analyst, the PM and fundamental analysts sitting together, suggests Drogen. Then there’s a data acquisition and repository team on top of that responsible for buying data and other things. “The PM needs to operate as a pod where those quants and engineers understand the process,” said Drogen.

Liquidnet further enhances trading platform with acquisition of OTAS Technologies

Addition of trader analytics accelerates firm’s Virtual High Touch™ offering while also delivering MiFID II solutions tailored for the buy side

Liquidnet, the global institutional trading network, today announced its acquisition of OTAS Technologies–a market-leading analytics platform that delivers actionable market intelligence and context directly to institutional traders and portfolio managers. OTAS’s industry-leading analytics and market insight, combined with Liquidnet’s Virtual High Touch decision-support trading platform, will help enhance the buy-side trader’s decision making process and give the trader more control over achieving best execution.

Uncovering Alpha Using Alternative Datasets

We cordially invite you to attend our cocktail reception and panel discussion…

The asset management industry is in a period of profound change. A confluence of factors – downward pressure on fees, increased technology and regulatory compliance costs, and difficulty generating alpha due to steadily rising markets, to name a few – have created a situation where managers are being forced to look long and hard at all aspects of their business.

On the trading desk, this obviously creates challenges, but at the same time the advent of new technologies have resulted in clear opportunities as well. Nowhere is this more apparent than with the rise of Alternative Data sources that institutional traders, for the first time, have been able to harness to contribute meaningful alpha through the trading process.

Join us for a panel discussion moderated by Dan Furstenberg, managing director at Jefferies & Co. and featuring several of the industry’s leading market data, analytics and trading technology providers, as well as [TBD BUY SIDE TRADER], to debate the role that alternative data is playing on the buy side trading desk today and beyond. Complimentary registration!

When : Wednesday, May 17 | 5:00 – 7:00pm
Where : The Yale Club | 50 Vanderbilt Avenue | New York City
Panel Members : Tom Doris, CEO and Founder, OTAS Technologies
Bruce Fador, Chief Commercial Officer, Wall Street Horizon
Andy Mahoney, Business Development Director, Flextrade UK Ltd
Leigh Drogen, CEO, Estimize
Vinesh Jha, CEO, ExtractAlpha

Networking/cocktail reception followed by panel and Q&A sessions.

Charles River and Otas combine for trade transparency

Charles River Development announced it has partnered with OTAS Technologies and incorporated OTAS’s global equity trading analytics in the Charles River Investment Management Solution (Charles River IMS). The partnership makes OTAS’s trade analytics available as a separately licensed add-in to Charles River’s portfolio management workspace and combined order and execution management system (OEMS).

“OTAS can be a real alpha generator,” said Lee Garf, VP, Product Management, Charles River Development. “It gives portfolio managers and traders real-time access to the best market intelligence and improves communication throughout the front office. Portfolio managers can monitor their trades, and traders can recognize opportunities sooner and respond more quickly to changing market conditions.”

“Incorporating advanced analytics from OTAS into the portfolio management and trading workflows provides actionable signals that support instant decision making and improve front office efficiency,” said Tom Doris, CEO of OTAS Technologies. “This provides constant insight into what’s happening with trades, which improves both transparency and productivity for buy-side firms.”

Eze Software Integrates OTAS Analytics to Help Traders with Best Execution

Eze Software Group, a global leading provider of investment technology, has partnered with OTAS Technologies to integrate OTAS’ real-time data analytics and market intelligence into its execution workflows. OTAS specializes in exceptional activity analysis, using artificial intelligence and big data techniques to translate unusual market movements into actionable real-time alerts and signals.

Complementing the existing in-trade analytics native to the Eze EMS (RealTick), the partnership positions Eze Investment Suite to deliver the latest in pre- and in-trade analysis to help buy-side traders achieve best execution. The integration embeds OTAS’ latest capabilities directly into the Eze EMS, allowing traders to monitor their entire order blotter and watchlist using OTAS’ apps and features such as the pre-trade TCA “Schedule” app, Intraday Screener and dark/off-book volume alerts. By combining OTAS analytics with the advanced trading capabilities and deep access to liquidity of Eze EMS, traders are empowered with insightful information and can react to market abnormalities instantly using a wide range of advanced execution tools.

The OTAS integration is part of continued investment into the award-winning EMS, which recently saw advancements such as enhanced crossing and deeper integration with Eze OMS.

“We’re excited to be bringing the latest innovations in the world of trade analytics from OTAS to our clients,” said Robert Keller, CFA, Executive Managing Director, Product Management and Development at Eze Software Group. “Today, traders are monitoring enormous amounts of information, and need a way to filter out the noise and home in on market and order conditions that require immediate attention or may materially impact trading decisions. As highlighted by the extent of the forthcoming MiFID II regulations in 2018, these capabilities, combined with the advanced order execution of Eze EMS, are critical tools in today’s quest for best execution.”

“At OTAS we are committed to giving investment professionals the competitive advantage needed to enhance their performance, allowing them to be active by exception. With our intelligence and real-time alerts, users can pursue the best transactions and returns while ensuring regulatory obligations such as MiFID II are met,” said Tom Doris, CEO of OTAS Technologies. “We are thrilled to have the opportunity to bring our advanced market analytics to Eze’s client base and look forward to further developing this strategic partnership.”

Firms consider NLP usage, purpose

Natural language processing is making use of the explosion of big data that once consumed, and confused, fund managers.

Natural language processing (NLP) is a computer’s ability to make sense of natural language by understanding statistics, most commonly generated from unstructured data. The rise of big data has brought with it the needs for technology to sort through massive amounts of unstructured data. A notable source of unstructured data…

Outlook 2017: Tom Doris, OTAS

Which hot topics/hype should be retired at the end of 2016?

Some of the hype around artificial intelligence (AI) has died down and now we’re seeing more serious and sensible attempts to use the new methods as a tool to deliver real value to the investment process. Getting past the buzz will allow firms to focus on defining what role AI will play and how traders can best work with these technologies.

As we move away from the far-fetched sci-fi ideas, the focus can move to how these technologies can solve specific problems, and just as importantly, to understand where they should not be applied.

The important point is that market data volume and information overload has been one of the main challenges faced by traders for many years, we now have tools that really can provide good solutions to extract the important information, which is a huge breakthrough. But like any new technology, once the hype dies down, there’s a lot of work to be done on the awkward problems of getting the technology into the right platforms, and into the workflow of the users, and feeding into the firms’ audit trails.

What changes do you expect to see in regards to machine learning and analytics in 2017?

As an industry we have been moving towards more of an ecosystem model for the first time. Thinking has evolved with a rapid change in attitude from keeping everything in-house to placing a priority on innovation and collaboration.

Firms want to focus on the work and look towards a collective ecosystem with third-party provider content in their workflows. We are also seeing a democratization of technology across the industry where everything is much more open and standards-based. This creates a more even playing field and opens up access for startups to innovate and deliver scalable solutions. As the regulatory environment changes and firms work to adhere to new requirements, this ecosystem and collaborative approach is even more vital to success. We need to work together to build solutions to fix these problems and create a healthier, even playing field.