The Journal of Private Markets Investing

Creating Private Equity Waterfall Functions in Excel

Tom Arnold, Professor Liu, Professor Marshall — Fri, 02 Oct 2026 00:00:00 +0000

User-defined waterfall functions are created in Excel using =LAMBDA and =MAKEARRAY functions to assess the benefits of a private equity deal for multiple stakeholders. The three primary waterfall functions calculate the waterfall distributions and associated performance measures, including internal rates of return (IRRs) and multiples of invested capital (MOICs), both with and without carried interest. The functions are readily transferable to new spreadsheets from the downloadable source file.

Bridging Markets: How Informed Debt Drives Stock Predictability

Ivo Reck — Fri, 02 Oct 2026 00:00:00 +0000

This study delves into the dynamic interplay between syndicated loan and equity markets. We uncover the predictive power of non-public debt information on subsequent stock returns up to three months in the future. Around loan negotiation events, the information lead is most pronounced when secondary loan market quotes are highly informative. In addition, we identify key factors shaping the informativeness of loan quotes, including firm risk, monitoring intensity, loan liquidity, and lender structure. Our findings are robust and extend to the industry level, highlighting systematic advantages in the leveraged loan market. In light of our findings, we put forth practical investment strategies that capitalize on this distinctive information advantage.

Buyout Performance with Assets Valued at Marrket

Richard M. Ennis, Daniel Rasmussen — Fri, 02 Oct 2026 00:00:00 +0000

The debate over whether buyout investments generate positive alpha hinges on proper risk measurement. We study buyout volatility, valuation, and performance through the lens of public-market pricing of private equity interests on European stock exchanges. We report that the volatility and stock market correlation of listed private equity (LPE) returns are greater than when determined using cash flows and net asset values (NAVs). We estimate a beta of roughly 1.5 and find no statistically meaningful alpha. Using market-priced buyout vehicles eliminates the appearance of alpha generated by smoothed NAVs and implies standard equity‑like compensation for higher leverage. These results align with those of studies based on secondary market transactions.

A Machine Learning-based Public Market Equivalent Framework for Estimating Default Risk in Private Credit

Ravi Yadav, Anubhab Saha, Saurabh Singh, Gauhar Turmuhambetova, Dhagash Mehta — Fri, 02 Oct 2026 00:00:00 +0000

In this paper, the authors introduce a Public Market Equivalent (PME) framework to estimate default risk for private firms when financial statement fundamentals are unavailable or stale. The approach learns a supervised similarity metric from publicly traded corporate bond (from both public and private issuers) characteristics and risk measures using a Random Forest model, then uses Random Forest Geometry- and Accuracy-Preserving (RF-GAP) proximities to identify a small, sector-consistent set of comparable public issuers for each private issuer. Comparable issuers’ ratings are aggregated into a similarity-weighted implied rating for the private issuer, which is subsequently mapped to a rating-implied probability of default (PD) using transition and default statistics. The framework is designed to balance predictive accuracy with interpretability by providing a transparent, peer-based explanation of each private issuer’s inferred credit quality.

Benchmarking Private Credit for Portfolio Allocators: A Comment on Hooke, Hu, and Imerman (2025)

Jane Carpenter, William P. Kieser, PhD, Joseph Damisch — Fri, 02 Oct 2026 00:00:00 +0000

How private credit is benchmarked can determine whether it appears to outperform public credit. This article revisits recent claims that private credit has delivered little excess performance and that much of its reported value remains exposed to residual valuation risk. We argue that comparisons between drawdown fund total value to paid-in capital and buy-and-hold exchange-traded fund returns do not answer the relevant question facing allocators because they ignore the timing of capital calls, distributions, and remaining net asset value. Using 2015–2020 vintage private credit fund cash flows from MSCI Private Capital Intel and the same indices suggested by the original paper, we construct cash-flow-matched public benchmarks and evaluate performance with Kaplan–Schoar public market equivalent and Direct Alpha measures. Senior direct lending vintages show positive median outperformance versus the Invesco Senior Loan exchange-traded fund, with a median public market equivalent of 1.18x and Direct Alpha of 3.25% annually. Outperformance narrows under leverage-scaled public benchmarks and residual-value haircuts but generally remains positive, especially for subordinated debt vintages.

Private Equity Allocation Decisions: Integrating Liquidity, Active Risk, and Investor Circumstances

Douglas Grim, Ankul Daga, Joana Rocha, Ariana Abousaeedi — Fri, 02 Oct 2026 00:00:00 +0000

Private equity can offer return-enhancement potential through liquidity risk premia and manager alpha, but these benefits come with meaningful liquidity and active risk that are not fully incorporated into certain portfolio construction frameworks. In addition, adjusting appraisal-based valuations reduces the apparent diversification benefits of private equity to levels more consistent with what would be expected for an asset that represents a subset of the equity market. We extend an existing framework which integrates these considerations in the context of traditional drawdown funds to the case of semiliquid (evergreen) fund structures. We find that, similar to the case of drawdown funds, the optimal allocation to semiliquid private equity exposures, varies across investors and depends on assumptions regarding manager skill, systematic and active risk, and tolerance for liquidity constraints. These considerations also have important governance implications for advisors, investment committees, and other decision-makers.

Private markets in retirement plans: A fiduciary framework for evaluation and implementation

Tony Davidow — Fri, 02 Oct 2026 00:00:00 +0000

Recent regulatory initiatives have renewed interest in incorporating private markets into U.S. defined contribution plans. The central question, however, is not whether such assets should be categorically permitted, but how plan fiduciaries can evaluate and implement them prudently. This article develops a practical framework organized around six factors identified in the U.S. Department of Labor’s proposed rule: performance, fees, liquidity, valuation, meaningful benchmarks, and complexity. While defined benefit plans have allocated significant capital to private markets, there are differences between DB plans and DC plans. Research suggests that private-market exposure is appropriate when embedded within professionally managed, diversified vehicles supported by reliable liquidity management, valuation, benchmarking, and monitoring procedures.

Interview with Professor Aswath Damodaran, Stern School of Business at New York University

Michael Imerman — Fri, 02 Oct 2026 00:00:00 +0000

This interview launches a new series in The Journal of Private Markets Investing called “Damodaran on Private Asset Valuation.” Over the next several issues, we will publish articles by world-renowned valuation expert Professor Aswath Damodaran that revisit some of the most persistent challenges in valuing private assets, including the valuation of young and start-up companies, the measurement of illiquidity, and the assumptions that distinguish private-asset valuation from public-market valuation.

In this brief interview, I discuss with Professor Damodaran the current state of private markets, what misconceptions people have (including professional investors) when it comes to valuing private assets, and the role of emerging technologies in valuation. Professor Damodaran’s answers challenge several widely held assumptions about private markets and provide a provocative starting point for the series that follows.