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| Titel: |
A Bayesian approach to ranking private companies based on predictive indicators |
| Auteur: |
Dixon, Matthew Chong, Jike |
| Verschenen in: |
AI communications |
| Paginering: | Jaargang 27 (2014) nr. 2 pagina's 173-188 |
| Jaar: |
2014-04-04 |
| Inhoud: |
Private equity investors seek to rank potential investment opportunities in growth stage private companies within an industry sector. The sparsity of historical investment transaction data for many growth stage private companies' may present a major obstacle to using statistical methods to discern industry specific features associated with successful and failed companies. This paper describes a Bayesian ranking approach based on (i) extracting and selecting features; (ii) training support vector machine classifiers from feature pairs of labeled companies in an industry; (iii) non-parametric estimation of posterior probabilities of success and failure; and (iv) ranking unlabeled companies within a cohort based on scores derived from posterior probability estimates. We anticipate that this approach will not only be of interest to statisticians and machine learning specialists with an interest in venture capital and private equity but extend to a broader readership whose interests lie in classification methods where missing data is the primary obstacle. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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