Modelling Qualitative Data
In Chapter 11 we described how a fund's cash flows can be scaled to achieve a projected lifetime and a projected TVPI, but we have not discussed how projected TVPIs reflecting the fund's growth prospects could be determined. For investment in a new fund as a blind pool and in young funds with too little significant history, we need to use qualitative inputs to model such multiples. Therefore, we have to deal with the question of how we can use such data in a consistent manner to put funds into different classes according to their growth prospects.
Such classifications could, for example, take the form of what is commonly called a “fund rating”. Another question relevant for this discussion – and to which we will turn in more detail later – is how to translate such a classification into quantification, again to determine ranges for growth rates as inputs for the cash flow models.
13.1 QUANTITATIVE VS. QUALITATIVE APPROACHES
Quantitative approaches are concerned with the statistical analysis of data that are collected from empirical observations. In order to derive meaningful conclusions from the statistical analysis, the data sample must be sufficiently large and representative (i.e., unbiased). Unfortunately, such samples often do not exist as far as alternative assets are concerned. As a result, risk managers face the challenge of working with imperfect data, strictly limiting the application of quantitative techniques regarding the ex-ante assessment ...