Corporate Finance

We develop a dynamic valuation model of private equity (PE) investments by solving the portfolio-choice problem for a risk-averse investor (LP), who invests in a PE fund, managed by a general partner (GP). Key features are illiquidity, leverage, GP value-adding skills (alpha), and compensation, including management fees and carried interest. We find that the costs of management fees, carried interest, and illiquidity are high, and the GP needs to generate substantial value to cover these costs. Leverage substantially reduces these costs.

This paper reviews recent research at the intersection of industrial organization and corporate finance on credit default swap (CDS) markets. These markets have been at the center of the financial crisis of 2007-2009 and many aspects of their operation are not well understood. The paper covers topics such as counterparty risk in CDS markets, the "empty creditor problem," "naked" CDS positions, the super-senior status of credit (and other) derivatives in Chapter 11 bankruptcy, and strategic behavior in CDS settlement auctions.

We examine aggregate idiosyncratic volatility in 23 developed equity markets, measured using various methodologies, and we find no evidence of upward trends when we extend the sample until 2008. Instead, idiosyncratic volatility appears to be well described by a stationary autoregressive process that occasionally switches into a higher-variance regime that has relatively short duration. We also document that idiosyncratic volatility is highly correlated across countries. Finally, we examine the determinants of the time-variation in idiosyncratic volatility.

Using the 2007–2009 financial crisis as a laboratory, we analyze the transmission of crises to country-industry equity portfolios in 55 countries. We use an asset pricing framework with global and local factors to predict crisis returns, defining unexplained increases in factor loadings as indicative of contagion. We find evidence of systematic contagion from US markets and from the global financial sector, but the effects are very small.

We develop an analytically-tractable model integrating the dynamic theory of investment with dynamic optimal incentive contracting, thereby endogenizing financing constraints. Incentive contracting generates a history-dependent wedge between marginal and average q, and both vary over time as good (bad) performance relaxes (tightens) financing constraints. Financial slack, not cash flow, is the appropriate proxy for financing constraints.

We introduce the pathwise optimization (PO) method, a new convex optimization procedure to produce upper and lower bounds on the optimal value (the “price”) of a high-dimensional optimal stopping problem. The PO method builds on a dual characterization of optimal stopping problems as optimization problems over the space of martingales, which we dub the martingale duality approach. We demonstrate via numerical experiments that the PO method produces upper bounds of a quality comparable with state-of-the-art approaches, but in a fraction of the time required for those approaches.

We consider the problem of producing lower bounds on the optimal cost-to-go function of a Markov decision problem. We present two approaches to this problem: one based on the methodology of approximate linear programming (ALP) and another based on the so-called martingale duality approach. We show that these two approaches are intimately connected. Exploring this connection leads us to the problem of finding "optimal" martingale penalties within the martingale duality approach which we dub the pathwise optimization (PO) problem.

Stock returns around security offering announcements are conditional on firms' self selection into a particular security type. We use a switching regression methodology on a data set of U.S. straight debt, convertible debt, and seasoned equity offerings to estimate counterfactual announcement returns that would be obtained had the same firms instead opted for alternative financing. Our evidence is consistent with firms choosing the financing type with the least negative expected announcement effect.

We consider a trader who aims to liquidate a large position in the presence of an arbitrageur who hopes to profit from the trader's activity. The arbitrageur is uncertain about the trader's position and learns from observed price fluctuations. This is a dynamic game with asymmetric information. We present an algorithm for computing perfect Bayesian equilibrium behavior and conduct numerical experiments. Our results demonstrate that the trader's strategy differs significantly from one that would be optimal in the absence of the arbitrageur.