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.     

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.     

Analysis and Forecast of the State of Environmental Protection in Russia

The main purpose of the present study is to analyse the emission dynamics of atmospheric and water pollutants in Russia and cost of their removal in the 1980s and early 1990s, and to forecast them by means of a Dynamic Input–Output Model according to different scenarios of future economic development till 1998. Main results of the work are:– methodological principles have been elaborated for singling out the environmental protection sector within the national economy;– a method has been offered for including the ecological block into a Dynamic Input–Output Model of the Russian economy;– a method of data preparation has been elaborated for the ecological block of the above-named model, the data base which characterizes the ecological situation in Russia has been formed and analysed;– calculations for 1994–1998 have been executed for forecasting the economic and ecological development of Russia using the above-mentioned model and the results obtained have been analysed. The results showed that if the existing tendencies towards low environmental protection capital costs remain the same, then the negative environmental impact will increase. In order to implement ecological programs and international agreements, to increase the proportion of removed pollutants, it is necessary to increase substantially expenditures on purifying water and air resources. The proportion of environmental protection investments in the total amount of the national economy capital costs should increase by up to 12–40% according to different scenarios of the economic development and different purposes of the environmental protection policy.     

Spatial Heterogeneity in Mortgage Terminations by Refinance, Sale and Default

This article investigates the impact of spatially correlated unobservable variables on the refinancing, selling and default decisions of mortgage borrowers. Virtually the entire mortgage literature acknowledges that borrower-specific characteristics, such as culture, education or access to information, play an important role in mortgage termination decisions. While we do not observe these variables directly, we note that borrowers of similar background tend to cluster together in neighborhoods. We estimate a competing risks hazard model with random effects using a three-stage maximum likelihood estimation approach. We utilize the space-varying coefficient method to modify the covariance structure according to the spatial distribution of the observations. Beyond a significant improvement of the model performance, this yields a number of insightful implications for mortgage termination behavior. For instance, borrowers of the affluent "West Side" of Los Angeles County both refinance and move at a higher rate than predicted by the standard maximum likelihood estimation method. At the same time, borrowers from some lower-valued neighborhoods tend to stay longer than expected with their mortgages and properties.     

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).     

Subprime Lending and Real Estate Prices

This article establishes a theoretical and empirical link between the use of aggressive mortgage lending instruments, such as interest‐only, negative‐amortization or subprime mortgages, and the underlying house prices. Such instruments, which come into existence through innovation or financial deregulation, allow more borrowing than otherwise would occur in previously affordability‐constrained markets. Within the context of a model with an endogenous rent‐buy decision, we demonstrate that the supply of aggressive lending instruments temporarily increases the asset prices in the underlying market because agents find it more attractive to own or because their borrowing constraint is relaxed, or both. This result implies that the availability of aggressive mortgage lending instruments magnifies the real estate cycle and the effects of fundamental demand shocks. We empirically confirm the predictions of the model using recent subprime origination experience. In particular, we find that regions that receive a high concentration of aggressive lending instruments experience larger price increases and subsequent declines than areas with low concentration of such instruments. This result holds in the presence of various controls and instrumental variables.     

Homeownership as a Constraint on Asset Allocation

Personal preferences and financial incentives make homeownership desirable for most families. Once a family purchases a home they find it impractical (costly) to frequently change their ownership of residential real estate. Thus, by deciding how much home to buy, a family constrains their ability to adjust their asset allocation between residential real estate and other assets. To analyze the impact of this constraint on consumption, welfare, and post-retirement wealth, we first investigate an individual’s optimal asset allocation decisions when they are subject to a “homeownership constraint.” Next, we perform a “thought experiment” where we assume the existence of a market where a homeowner can sell, without cost, a fractional interest in their home. Now the housing choice decision does not constrain the individual’s asset allocations. By comparing these two cases, we estimate the differences in post-retirement wealth and the welfare gains potentially realizable if asset allocations were not subject to a homeownership constraint. For realistic parameter values, we find that the homeowner would require a substantial increase in total net worth to achieve the same level of utility as would be achievable if the choice of a home could be separated from the asset allocation decision. The robustness of the analysis is evaluated with respect to the model’s parameters and initial state variables. We find that changes in the values of the constraint (i.e., the value of the home) and the expected real rate of home value appreciation are the only state variables or parameter that is associated with a large change in asset allocation and/or the burden imposed by the housing constraint. This finding suggests the importance of a detailed examination of the impact of inter-regional differences in home prices and expected rates of appreciation on asset allocation and post-retirement wealth.     

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.     

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.     

Investment Timing for Dynamic Business Expansion

We investigate the timing of business expansion. With an indefinite sequence of growth opportunities that have constant returns to scale, current investment neither displaces nor impairs future returns. In a dynamic setting with expansion restricted to a fraction of firm size, the endogenously determined cost of capital uniformly exceeds the value maximizing return threshold for expansion. Taking this into account, a manager accelerates investment to facilitate larger and more valuable future investments when earnings stochastically improve. This result is the opposite of deferral that the investment literature recommends due to irreversibility. This means that the managerial application of the cost of capital as an expansion hurdle rate is improperly conservative.