Understanding private equity performance : a review of dynamics driving fund performance
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In recent years, more papers on private equity performance have emerged, casting light over a market that earlier was characterised by privacy and secrecy. Early studies mostly use VentureXpert as a data provider, however, data from this provider has been under a lot of criticism lately, and new data providers have emerged. In this thesis, we study the performance of buyout and venture funds from 1990 to 2008 using a dataset from Preqin. Previous studies have mostly focused on IRR or a modification of this metric. We have compared these findings with our results and use a widely reported investment multiple to see if there are discrepancies that can explain the differences in results. Based on findings from other papers, the dataset is of high quality and is less prone to bias compared to datasets previously used in private equity research. In our study of fund types, we see a general tendency of buyout outperforming venture. We have also looked more closely at sequence numbers and see that there is a negative correlation between performance and sequence numbers. This suggests that experience is not necessarily a contributing factor for good performance. We find indications that past performance may be well suited for risk reduction, but is not necessarily indicative for future performance. As Preqin has been little used in private equity research, our results contribute to this field by showing that Preqin, as a data provider, is well suited for academic research. We also test the validity of past research and show that, although the concepts are still valid, an update based on newer data points is warranted.