Nowcasting Net Asset Values: The Case of Private Equity

Important: This thesis is part of the ALTQNT Private Equity Flagship Track and can only be pursued after completing the ALTQNT Data Phase.

 

Advisor: Dr. Sara Boni
Type: Master’s Thesis

 

Overview

Valuing illiquid assets accurately is hard but necessary for many critical investment decisions made by institutional investors. Private equity (PE) investments are a prime example. Various stakeholders rely heavily on infrequently reported net asset values (NAVs) provided by fund managers. However, investors observe additional information that can be used to generate unbiased and more timely higher-frequency estimates of the true value of a fund.

Objective

This thesis aims to replicate the methodology implemented by Brown, G. W., Ghysels, E., Gredil, O. R., 2023 (see below) as well as placing it in the relevant literature.

Requirements

Advanced skills in financial econometrics and in general applied econometrics, as well as in coding (with Matlab). Experience with State-Space Models is a plus. 

Literature

Brown, G. W., Ghysels, E., Gredil, O. R., (2023), Nowcasting Net Asset Values: The Case of Private Equity,The Review of Financial Studies, 36(3): 945–986, https://doi.org/10.1093/rfs/hhac045

Contact & Application

If you are interested in writing your thesis on this topic, please indicate “ALTQNT Private Equity Flagship Track” in your thesis application. The specific topic can be aligned with your supervisor before the start of the research phase and can be further expanded or adapted based on your interests and ideas.