Hedge Fund Enhances Performance Through Better Data

Enhanced performance though better data

The Customer

A Hong Kong-based Hedge fund with AUM over 40m USD, founded in 2010, was reaching the limits of their chosen software solutions by late 2011, and started seeking an alternative platform to manage their portfolio.

The Challenge

The Hedge Fund had initially picked Bloomberg’s AIM platform as its portfolio management tool. However, AIM’s limited flexibility soon pushed them to start developing an in-house Excel based solution to supplement it.

Their in-house solution included:

  • One file listing all their transactions
  • One file containing all their position history
  • One file containing month-end prices for all the stocks they held at each month-end
  • One file containing latest prices on all the stock they held ( so that spreadsheets would work even without an active Bloomberg Terminal available
  • A blotter system to enter trades into their transaction and position file
  • Various output spreadsheets linked to the above files

The problems they were encountering:

  • Data files were bloating beyond 15MB, at which point Excel started becoming very unstable
  • Double entry of trade data. Every trade had to be entered both on AIM and into their spreadsheets, and required time to reconcile and make sure both systems agreed
  • Excessive manual operations: saving daily/month-end prices
  • Difficult to correct or amend data once it was entered, leading to an increasing number of data consistency problems
  • Difficult reconciliation with broker and custodian
  • Difficult output for reporting purposes

In short, the system was inflexible, slow and increasingly prone to problems.

The Solution

Phase 1

scheduled for June 2012, included:

  • Integrated Blotter module, with additional business logic checking to ensure clean data
  • Portfolio Live module, with breakdown of active portfolio by asset type, by market and by fund
  • Portfolio Attribution model, for analysis of the client’s monthly performance by asset type, market and fund
  • Portfolio Dashboard, for intraday, MTD, YTD performance summaries by market, asset type and strategy
  • Back-end registration with Bloomberg DL services for intraday and day-end prices, as well as other information such as Betas and Option Deltas

Phase 2

scheduled for September 2012, included:

  • Monthly Report module, to aid in the monthly investor newsletter
  • Improved Blotter module, with AIM trade integration
  • Turnover Module, for analysis of monthly turnover since inception
  • Retirement of the old Trade Reconcile system

Phase 3

completed in November 2012, included:

  • Daily Risk Report module, for daily custodian reports
  • Risk Monitor module for live views on advanced risk-related portfolio variables

The Result

By Phase 2, EFAdrin had full feature parity with the client’s original system, and they stopped using the old tools altogether. The final rollout was complete by November 2012, offering new analysis that their original system was incapable of producing.

The client’s monthly net returns have averaged 2.4% since then, compared to an average of -0.4% in the preceding year.

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