Overview

 

forward look's research focuses on the interplay between portfolio implementation shortfalls and the management of transactional data. By tracking how data is assembled by various counterparties to structure the transactions that flow between them, we determine what dynamically enables efficient information transfer in support of STP and ultimately, alpha retention.

 

We focus on how differing terminologies (eg, variants of XML or in-house data dictionaries) and varied application contexts (eg, front vs back office processes) result in syntactic and semantic breaks. More importantly, we try to ascertain how these differences can be programatically bridged by spanning the implicit ontological gaps. As Michael Stonebraker noted, the challenge is enabling 'integration on demand' to supplant the prevailing but more brittle approach of 'integration in advance'.

 

To that end, we actively explore how evolving schema and data mapping techniques can be used to automatically harmonize information contexts. We critically examine how semantics (data meanings and usage) and ontologies (contextual maps between related terms across the industry) capture the industry's processes and workflows, with particular attention to the differing information requirements of various trading counterparties across the life cycles of cross-border transactions.

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We achieve our goals by evaluating transactional data from actual portfolios managed commercially by institutional portfolio managers. Likewise, we conduct periodic meta-analysis from both published, as well as private research sources, to help guide our understanding of real-world implementation shortfalls.

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