Front-Office Decision Making and Support

A key differentiator for an investment firm is how it makes investment decisions and employs the tools used to make these decisions.  There are many tools available today to support the front office, but we have found the limitations of a successful front office operation often boils down to available data. A key part of our business has been working with the products and supporting data providers such as Reuters, Factset, Vestek, Bloomberg, ITG, and Multex.  We believe our ability to understand both the functional and technical side of a problem is particularly important when dealing with front-office systems.  Portfolio managers often have very little time to devote to development projects and want to work with individuals who already understand their business.

Integration of Quantitative Portfolio Optimizer

The quantitative investment team for an Investment Manager with $20 billion in assets under management required a industry leading portfolio optimizer to be integrated into their existing decision support architecture.  Before integrating the optimizer into their existing portfolio accounting and trading systems, the team would spend 3 days at the beginning of the month manually loading data from various sources.  This process was time-consuming, prone to error and failed to allow the team to load data on a daily basis, as they desired.  Varden architected and developed an integration framework that allowed the manual process to be fully automated in order to support the daily load of data as follows:

• Security characteristics loaded from various industry sources and stored in database or text files.
• 70+ Benchmark constituents loaded.
• Start of Day Positions loaded from the portfolio accounting system.
• Start of Day Cash positions loaded from trading system.

Additionally, a web-based interface was designed to expose specific features of the optimizer based on the defined needs of the investment team.

Utilizing Bloomberg for Real-Time Data Enhancement

A global fixed income fund manager required enhancements to their existing security master data to support timely updates of characteristic data such as yields, durations, and convexities.  Varden provided a ‘run-on-demand' application that can be configured to request the specific data required for any security type.  To keep consistent with the firm's internal pricing policies, the application allows the firm to pass overridden settlement dates and prices to Bloomberg such that the characteristics are calculated on the firm's internal prices.

A second phase to the project required the use of the Bloomberg real-time API to obtain up-to-the-second security trading characteristics to a report which displays trade executions in relation to the market.  This report has been developed using .Net web services and provides the framework for merging trade data obtained from the OMS with the real-time data obtained from Bloomberg.

Manager Desktop Portfolio Analyzer

As part of a large corporate intranet site, portfolio managers required an easy-to-use tool that allowed users to drill down into the asset allocation and performance of their portfolios.  The users had previously used FactSet and Vestek and although useful, found that neither application provided the web-based, drill-down functionality that they demanded.  Based on interactive sessions with the portfolio management team, Varden prototyped and presented an overall design to end-users.  From there, we managed the development of the application, data-model, and interfaces necessary to support the application.  The completed application provides the following capabilities:

• Asset allocation, Attribution, top/bottom analysis using various characteristic breakdowns such as region/country, currency, sector/industry, duration, earnings, and risk.
• Views of data can be transformed from text to graphical display at the touch of a button.
• Extensive drilldown functionality allows the users to drill down and across the data to quickly key in on interesting areas.
• User-defined preferences allow a user to personalize their environment such that data is always presented in a manner that is most effective for their needs.