A fund-of-funds’ research and investment process focusses on the managers as opposed to companies, issuers and instruments. One is inherently buying into the fund manager’s ability to generate alpha. However from a data and technical perspective, similar problems will be encountered. I would like to spend this time writing about a standard multi-manager research and investment process, it’s challenges and hurdles.
Like many problems in the financial markets, the key challenge is data. The data I am talking about is data on funds and the associated managers. Various data vendors such as Morningstar , eVestment and Preqin provide data on funds, hedge funds and their associated managers.
That being the case, many managers (hedge funds in particular) are very sensitive about the information they provide about their funds and their alpha generating strategy. They might only provide a pdf document that contains basic information including strategy type (e.g. Long-Short, Risk-Arbitrage etc), Fund Size, and performance over 1,3 and 5 years. I have spoken in previous articles about our powerful datafeeds module and task scheduler, allowing one to rapidly create ETL processes to warehouse all data required in the investment and research process. It is in these cases where easily customisable processes allow one to warehouse generic vendor and specific manager data.
Once the data has been warehoused, a fund-of-funds’ research process will require other views. For example, linking performance across the multiple funds that a specific manager has managed over the years is a very good “index” describing the fund manager. Our simple yet powerful data model and rule based timeseries allow Quintessence to deliver these views.
When the processes have been set up to retrieve and warehouse all the data, the fund-of-funds’ manager will be presented with a large universe of funds and consequently a wide choice.
This is where the investment and research process comes to the fore.
The pyramid below shows the stages of a multi-manager investment process. The number of stages can vary. That said, a fund-of-funds’ research process should at least have all the steps that are stated below.
The initial screening list comprises the bedrock of any multi-manager process. Once the process has been set up to warehouse the investable universe of funds, the manager will require a relatively efficient mechanism to filter out the managers of interest. Managers need the ability to view initial screening data such a the
One methodology is to use Quintessence to automatically generate generic fund factsheets for each fund or manager. Some of the factors that may be included are
Managers are added to an initial screening list either manually or automatically using automatic criteria. These can be funds that:
The Initial Screening List narrows down the managers who merit further investigation and research.
Interviews need to take place with all managers in the initial screening list. All documents and notes associated with the meeting are warehoused and available for review. The initial manager meeting process ends with a manual tick or cross, determining whether deeper analysis is warranted in the manager.
In this stage, detailed quantitative fact sheets are generated. Quantitative factors that can be incorporated in these factsheets include the following information over a specified period :
Fundamental Factors can be
Screening using these factors further narrows the managers under consideration.
At this stage, all due diligence documents are signed and warehoused. Once a manager passes the criteria set up in the due diligence process, they make it onto the Manager Watch List.
The Manager Watch-List comprises all managers that potentially can be included in the Fund of Funds. At this stage, drill down views showing the effect on Country, Sector and even Instrument exposure should this fund be added to the fund of funds at a specific exposure, are used. Risk tools including the correlation with the other portfolios in the fund-of-funds ensure that diversification is achieved and total risk minimised.