« Back to Results

Private Equity and Valuation

Paper Session

Friday, Jan. 5, 2024 2:30 PM - 4:30 PM (CST)

Marriott Rivercenter, Conference Room 14
Hosted By: American Real Estate and Urban Economics Association
  • Chair: Mariya Letdin, Florida State University

Catering and Return Manipulation in Private Equity

Blake Jackson
,
University of Florida
David Ling
,
University of Florida
Andy Naranjo
,
University of Florida

Abstract

We provide evidence that private equity (PE) fund managers manipulate returns to cater to their investors. Using a large dataset of PE real estate funds, we show PE fund managers boost and smooth their funds' returns if doing so has a larger effect on their investors' reported returns. Additional results are inconsistent with models in which investors punish or are deceived by manipulations. In contrast, our results highlight an underlying tension in PE performance: the "phony happiness'' some PE investors receive from boosted and smoothed interim returns due to agency frictions within their organizations.

Smooth Return Drivers: Evidence from Private Equity Real Estate Funds

Spencer Couts
,
University of Southern California

Abstract

Illiquid assets have stale prices and spurious return autocorrelation. It is important to understand what drives this autocorrelation. I provide evidence that the fundamental driver of this phenomenon is the difficulty in valuing illiquid assets and not managerial manipulation. Specifically, I find that autocorrelations, risk factor loadings, and risk-adjusted returns, are all statistically and economically equivalent, regardless of whether valuations are completed internally or externally. I do find, however, that market pricing information is incorporated at a slower rate when managers complete the valuation updates, but this does not increase return smoothing.

Good versus Bad Networking in Private Equity Pension Fund Investment

Da Li
,
University of Wisconsin-Madison
Timothy J. Riddiough
,
University of Wisconsin-Madison

Abstract

We investigate how pension fund networks influence private equity investment performance, and further explore the mechanisms behind network formation. Pension funds with access to parts of the overall network that others do not have (stronger networks) generate superior performance relative to pension funds that simply have more network connections or have connections with influential fund managers (weaker networks). Strong networking correlates positively with less fund manager lock-in, better first-time fund manager selection, and lower risk investments that ultimately deliver better performance. Pension funds that target high expected returns, generate lower past returns, require higher employee retirement contributions, and experience higher CEO and board turnover rates form weaker networks that impair their performance. Those pension funds get locked into the pre-existing GP networks, and a vicious cycle forms with weaker-networked pension funds adopting riskier investment strategies that fail to perform well. This results in greater funding gaps that lead to more aggressive investment strategies. These effects are attenuated somewhat if pension funds link to well-connected consultants that improve access to better-performing GPs. In contrast, pension funds that are well-connected across the whole network structure experience a more virtuous cycle that results in a more solvent fund.

Disagreement in Collateral Valuation

Jordan Martel
,
Indiana University
Michael Woeppel
,
Indiana University

Abstract

We develop a model in which borrowers and lenders agree to disagree about the value of collateral. We establish conditions under which returns on collateralized assets exhibit momentum (or reversal) and investigate how default risk exacerbates (or attenuates) return predictability. To illustrate the model's empirical relevance, we test its predictions in the market for U.S. single-family homes and find evidence consistent with such a disagreement channel. We find that sale prices reflect lender's appraisals more in riskier loans (lower equity, higher LTVs, lower FICO scores). Finally, we show that the well-documented return autocorrelation is strongest exactly when loans are riskier.

Discussant(s)
Joseph Nichols
,
Federal Reserve Board
Stace Sirmans
,
Auburn University
Zipei Zhu
,
University of North Carolina
Darren K. Hayunga
,
University of Georgia
JEL Classifications
  • G2 - Financial Institutions and Services
  • R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location