Dash Financial releases new buy-side trading system

Dash Financial Technologies, the industry leader in order routing transparency, visualization and customization solutions, today announced the launch of its next-generation portfolio trading (PT) algorithm, a highly customizable workflow and execution solution with real-time transparency and analytics, allowing institutional clients to achieve their portfolio trading performance goals, however they choose to define them.

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The algorithm was spearheaded by Dash’s PT group, led by industry veterans Barbara Francis and Jennifer Hubbs, who leveraged their extensive experience consulting and executing for the largest buy-side institutions to design a seamless solution catering to a wide range of benchmarks and workflows.

“No two fund managers’ needs are exactly alike, and that’s especially true with portfolio trading,” said Barbara Francis, Director of Portfolio Trading. “Our goal when developing our new PT algorithm was to create a high-performance solution for managers with risk requirements, cash management needs, style preferences and workflow demands ranging from straightforward to ultra-complex.”

Following an intensive testing process, the algorithm is being rolled out to clients on a variety of FIX-based EMS/OMS systems. Like all of Dash’s algorithmic trading solutions, the new strategy is underpinned by Dash360, the firm’s award-winning, web-based dashboard that provides every aspect of the routing and execution cycle, from pre-trade analytics and cost estimates to advanced TCA.

“Being workflow agnostic is important, and in order to ensure that any client receives real-time transparency with actionable analytics and data visualization, regardless of front-end, we provide Dash360,” added Francis.

Using Dash’s new PT solution in conjunction with Dash360, clients receive summary-level cockpit analytics to immediately recognize outliers and visualize how the strategy intends to execute. Users also have the ability to drill down -- through sector, market capitalization, spread and liquidity measures -- into advanced routing analytics and visualization of the algorithm’s behavior at the child-order level.

“Trading portfolios in today’s complex markets requires an advanced technology solution tailored to each client’s specific needs, and that fits our business model perfectly,” said Peter Maragos, CEO. “While the performance of the algorithm was incredibly important to us, so too was the integration of state-of-the-art analytics to help our clients understand the large amount of data associated with this type of execution and help them shape their performance. We are very excited to extend the Dash platform in this way and bring the same transparency and control benefits that we’ve offered for many years in options and equities into the portfolio trading space.”

The new PT algorithm leverages a proprietary multi-factor risk model, covariance matrix and optimization engine to automatically create trading waves that minimize the risk of the residual portfolio, subject to certain user-defined constraints around ADV, venue selection, benchmark, etc. The algorithm also allows for advanced cash management, providing the clients with the ability to seamlessly manage the spend/raise throughout the execution horizon with optimal, ratio, skew and beta-weighted selections.

The algorithm supports both implementation shortfall (arrival price) and interval VWAP benchmarks and provides flexibility around auctions, dark venue controls and relative limits (versus an ETF, for example). It also offers aggressiveness controls, providing the ability to complete by the close or execute over multiple day if preferred.

“There are a number of complex factors that a buy-side trader must consider when trading a program: trading style, time horizon, risk, and how and when to access dark liquidity. With the launch of this new PT algo, we offer our clients a unique workflow solution to solving for these issues and a highly experienced team to handle the physical workflow if required,” concluded Francis. 

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