Ex-post full surplus extraction,straightforwardly

Consider an estimate of the common value of an auctioned asset that is symmetric in the bidders’ types. Such an estimate can be represented solely in terms of the order statistics of those types. This representation forms the basis for a pricing rule yielding truthful bidding as an equilibrium, whether bidders’ types are affiliated or independent. We highlight the link between the estimator and full surplus extraction, providing a necessary and sufficient condition for ex-post full surplus extraction, including the possibility of independent types. The results offer sharp insights into the strengths and limits of simple auctions by identifying the source of informational rents in such environments. Harstad acknowledges hospitable accommodation by the Fuqua School of Business, Duke University, and the Olin School of Business, Washington University in St. Louis, during parts of this research. We are grateful for comments and suggestions from Richard McLean and Jeroen Swinkels.     

Morgan Stanley's Risk‐Reward Views: Unlocking the Full Potential of Fundamental Analysis

Since 2008, Risk‐Reward Views have been the basis for the recommendations on all the stocks covered by Morgan Stanley's equity research analysts globally. The firm's analysts use this systematic approach to communicate a broader range of fundamental insights about expected returns and risks, and to articulate more clearly the logic underlying their price targets and calls, and the level of conviction associated with them. The rationale for this approach is to align the firm's research product with its clients' thinking and investment discipline while also creating a link between traditional equity analysis and widely accepted principles of modern portfolio management. Too many sell‐side analysts still try to manifest expertise and conviction with one‐sided investment theses backed by single‐point estimates and “table pounding.” That does a disservice to investors who are looking to sell‐side analysts for an ongoing dialogue about the future with experts on company fundamentals. Risk‐Reward Views are designed to produce a more complete view of the risk‐reward trade‐off in a given stock. They are meant to supplement the use of quant‐only risk models that, while offering at least the illusion of precision, are also often opaque and backward looking. The approach aims to increase transparency while avoiding unnecessary complexity by focusing on a handful of critical uncertainties and modeling a manageable number of coherent scenarios that are relevant to investor debates and cover a full range of plausible outcomes. This article focuses on the theoretical underpinnings of the department's Risk‐Reward initiative. For a more detailed discussion of the institutional setting and the processes followed to implement these ideas, readers are referred to the recently published Harvard Business School case study, “The Risk‐Reward Framework at Morgan Stanley Research” (Harvard Business School Case N9–111–011).     

Exporting, capital investment and financial constraints

Many firms cite financial constraints as some of the most important impediments to their investment and growth. Using a unique data set from the Czech Republic this paper investigates the importance of financing constraints in the context of exporters. It finds that exporters are less financially constrained than non-exporters. However, after carefully correcting for possible endogeneity and selection issues, the evidence points to less constrained firms self-selecting into exporting rather than exporting alleviating firms’ financial constraints.     

A mixed PDE-Monte Carlo approach for pricing credit default index swaptions

Abstract The problem of numerically pricing credit default index swaptions on a large number of names is considered. We place ourselves in a stochastic intensity framework, where Ornstein-Uhlenbeck-type correlated processes are used to model both firms’ distance to default and a macroeconomic state variable. Here the default of the firms’ follows the reduced-form approach and the (random) intensity of the default depends on the behavior of the diffusion processes. We propose here a numerical method based on both a Monte Carlo and a deterministic approach for solving PDEs by finite differences. Numerical tests demonstrate the efficiency and the robustness of the proposed procedure.     

Industry concentration in common value auctions: theory and evidence

We examine theoretically and experimentally two countervailing effects of industry concentration in common value auctions. Greater concentration of information among fewer bidders reduces competition but increases the precision of private estimates. We demonstrate that this generally leads to more aggressive bidding. However, the reduction in competition dominates the informational effects, resulting in lower prices. We examine these hypothesized effects experimentally by conducting a series of auctions with constant informational content but distributed among a varying number of bidders. The experimental results are consistent with our theoretical predictions. The authors would like to thank Octavian Carare, Eric Friedman, Luke Froeb, Ron Harstad, Toshi Iizuka, Mike Rothkopf, Charles Thomas, and two anonymous referees, for many useful comments and suggestions.     

From “Broad Studies” to Internet-based “Expert Knowledge Aggregation”. Notes on the methodology and technology of knowledge integration

The article takes as a starting point Herman Kahn's concept of a process-based approach to future-oriented knowledge aggregation and integration and discusses the opportunities created by Internet technologies to achieve the goal envisioned by such a model. The article briefly introduces a general framework for analyzing knowledge aggregation, the use of various aggregation mechanisms as well as aggregation systems that rely either on human facilitators (meta-experts) or on computer algorithms. Available online instruments for knowledge aggregation and expert challenge are presented and the possibility of using them for setting up “virtual think tanks” for foresight studies is explored.     

Information concentration in common value environments

We consider how information concentration affects a seller’s revenue in common value auctions. The common value is a function of $n$ random variables partitioned among $m \le n$ bidders. For each partition, the seller devises an optimal mechanism. We show that whenever the value function allows scalar sufficient statistics for each player’s signals, the mechanism design problem is well-defined. Additionally, whenever a common regularity condition is satisfied, a coarser partition always reduces revenues. In particular, any merger or collusion among bidders reduces revenue.     

Rules of evidence and liability in contract litigation: The efficiency of the General Dynamics rule

We examine rules of evidence and liability in contract litigation. When a contractor fails to perform, it has a legal defense that the buyer withheld private information relevant to the performance of the contract. Suppose the buyer claims that admitting evidence for the defense would compromise a valuable secret, for example, a state secret, what should the legal rule be? We show that the evidentiary rules introduced by the Supreme Court in General Dynamics v. U.S. lead to a more efficient outcome than either a strict liability rule or an evidentiary rule requiring the disclosure of the buyer's private information.