Multiple criteria decision support for private equity secondary transactions
Ortiz, Giana (2023)
Pro gradu -tutkielma
Ortiz, Giana
2023
School of Business and Management, Kauppatieteet
Kaikki oikeudet pidätetään.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2023050340475
https://urn.fi/URN:NBN:fi-fe2023050340475
Tiivistelmä
The main financial topic is private equity secondary transactions. Private secondaries give general partners and limited partners flexibility to extend the time horizon of an investment or exit early. This flexibility is valuable because private markets are illiquid, so these transactions almost always close at a discount. This thesis describes motivations, transaction details, and expected financial outcomes for the general partner, existing limited partners, and potential new limited partners in a GP-led secondary transaction.
When studying private markets, data availability is always a concern. The best possible data for this thesis is behind significant paywalls or non-disclosure agreements. Nonetheless, a sample was collected based on the top fundraisers, reported by Secondaries Investor, and the Amadeus database key financial information. Multiple criteria decision making analysis was conducted using this data in a decision matrix. With four criteria and two performance measures, there was clear differences between the top, middle, and bottom ranked fund managers.
The goal of this thesis is to provide a methodology for investment professionals to use a decision matrix and multiple criteria decision making to support investment decisions. On a deal-by-deal basis, deals can be entered into a decision matrix and the analyst would see if the new deal is more similar to deals that get passed or deals that get investment capital. On a fund manager level, an institutional investor can use the methodology to rank fund managers for potential investment. The multiple criteria analysis would provide one tool to support the decision makers in these situations.
When studying private markets, data availability is always a concern. The best possible data for this thesis is behind significant paywalls or non-disclosure agreements. Nonetheless, a sample was collected based on the top fundraisers, reported by Secondaries Investor, and the Amadeus database key financial information. Multiple criteria decision making analysis was conducted using this data in a decision matrix. With four criteria and two performance measures, there was clear differences between the top, middle, and bottom ranked fund managers.
The goal of this thesis is to provide a methodology for investment professionals to use a decision matrix and multiple criteria decision making to support investment decisions. On a deal-by-deal basis, deals can be entered into a decision matrix and the analyst would see if the new deal is more similar to deals that get passed or deals that get investment capital. On a fund manager level, an institutional investor can use the methodology to rank fund managers for potential investment. The multiple criteria analysis would provide one tool to support the decision makers in these situations.