Trade Informatics: The Alpha Preservation System
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Trade Informatics: The Alpha Preservation System

CIO VendorMatthew Celebuski, CEO Disruption in capital markets is nothing new. Industry realities—fee pressures, lower volatility, and crowded strategies—demand that asset and wealth managers adopt innovative solutions to adapt to challenging circumstances. Traders are at the center of many of the technological initiatives that have transformed asset management companies over the last decade, yet in many cases these initiatives have made traders the victims of their own successes.

Buy-side traders have traditionally been in a unique organizational position, able to collect, analyze, and leverage data to the benefit of their company and clients. Because they sit between the idea generation and execution processes, traders have access to more data and investment technology systems than most company personnel. However, somewhat ironically, traders are under significant pressure to justify their contributions to their employer.

"We believe that through research and big data analysis, traders can minimize their trading costs, helping their clients and ultimately their firm"

To reassert the trader’s role in the company’s investment process, a number of small financial technology companies have attempted to bridge the gap between idea generation and execution. Their software sits neatly between a portfolio management system and execution management system and ultimately reduces the noise and risk associated with the transmission of an idea to the ultimate venue of execution.

As add-ons to standard pieces of the investment technology stack, these applications augment current systems and don’t require new personnel or workflows. They utilize trading data to match a portfolio strategy to an execution strategy, reducing the risk that a good idea on paper becomes a bad idea upon implementation.

As Matt Celebuski, the CEO of Trade Informatics explains, “Through research and big data analysis, traders can minimize their trading costs, helping their firm and ultimately their clients.”

The trader looks at their own system, and they have an instinct on how to trade. We provide the strategy based on quality research, not bias


Matching an asset manager’s historical trade details to market data allows firms like Trade Informatics to construct a robust history of the decision made by each contributor in the transaction relay. Such analyses were typically the domain of transaction cost analysis (TCA) providers, but they weren’t used to tie a stock idea to an algo made for such an idea. That’s changing as firms look to mitigate the transmission risk between portfolio managers and venues, and traders are well-positioned to understand and articulate this risk and how it can be best controlled.

Prior to 2009, TCA providers were largely viewed as a relevant but untrusted source of actionable trading data. Rather than offer a clear path toward cost reduction and more efficient trading, these providers would report trade cost data and leave the optimization up to the trader. Taking transaction cost analysis to another level, certain TCA firms in the last 5-7 years have helped their clients uncover optimal trading strategies through big data analytics. As Celebuski explains, “We deliver a plan, a customized trading strategy in a consistent framework, refining the strategy over time as needed. We do so through a process of research, visualization, and reporting.”

Alpha Preservation in Practice

In 2011, a large asset manager came to Trade Informatics in search of a way to retain more of its performance. TI analyzed two years of the manager’s historical data, including security-level alpha estimates, and ultimately matched execution strategies to order sources. Eventually, TI integrated with the client’s trading platform and helped the asset manager realize a cost reduction of nearly 20 basis points. In addition to cost savings, the manager was able to more than double assets under management, without the need to add traders to manage the additional flow.

Celebuski attributes Trade Informatics' ability to achieve significant results for its clients to the company's core understanding of capital markets. He states, “If buy-side trading desks can achieve zero cost on the implicit side, you’re going to end up in a place where the market makers’ ability to exploit inefficiencies becomes decreasingly viable. And these efficiencies benefit all capital markets participants.”

The Process and Products

Trade Informatics has three software products that help asset management companies address their cost centers—Trading Analysis Program (TAP), Strategic and Tactical Analytic Research and Trading (START), and a simplified comPLIAnce tool (PLIA). TAP is Trade Informatics’ TCA product. The program transforms myriad data portfolio and trading data into meaningful output that drives actionable insights. START, then, gives asset managers the ability to personalize and optimize systematic trading strategies that align with their overarching investment process. The ultimate goal of offering both products together is to create frictionless markets, eliminating those inefficiencies that drag down performance. As Celebuski states, “The asset manager looks at their own system and has an instinct on how to trade. We provide the strategy based on quality research.”

As a focus on best execution takes hold, Trade Informatics has added PLIA, a compliance simplification tool, to its product suite. PLIA offers routing and delivery of counter-party information within a single platform, giving clients a way to manage risk and create a due diligence trail through simple permissioning and retrieval functions. All of this is disruptive technology that helps asset managers control their costs.

A Look Ahead

The vast majority of the alpha preservation conversation lies in the analysis of historical fills and orders, which is a process better suited to big data technologies than to conventional desktop applications. This is perhaps why TCA providers have been called upon to fill this particular gap in the investment technology stack. As new technologies, including machine learning and AI, become available, many in the industry expect firms like the ones mentioned here to forward the conversation regarding the efficient use of data to inform execution strategies.

- Brian Jackson
    February 20, 2017