Optimal stopping made easy

This paper presents a simple discrete time model for valuing real options. A short and simple proof of optimal exercise rules for the standard problems in the real options theory is given in the binomial and trinomial models, and, more generally, when the underlying uncertainty is modelled as a random walk on a lattice. The method of the paper is based on the use of the expected present value operators. With straightforward modifications, the method works in discrete time-continuous space, continuous time-continuous space and continuous time-discrete space models.     

Exit problems in regime-switching models

This paper provides a general framework for pricing of perpetual American and real options in regime-switching Lévy models. In each state of the Markov chain, which determines switches from one Lévy process to another, the payoff stream is a monotone function of the Lévy process labeled by the state. This allows for additional switching within each state of the Markov chain (payoffs can be different in different regions of the real line). The pricing procedure is efficient even if the number of states is large provided the transition rates are not very large w.r.t. the riskless rates. The payoffs and riskless rates may depend on a state. Special cases are stochastic volatility models and models with stochastic interest rate; both must be modeled as finite-state Markov chains. As an application, we solve exit problems for a price-taking firm, and study the dependence of the exit threshold on the interest rate uncertainty.     

Nonparametric estimation of conditional VaR and expected shortfall

This paper considers a new nonparametric estimation of conditional value-at-risk and expected shortfall functions. Conditional value-at-risk is estimated by inverting the weighted double kernel local linear estimate of the conditional distribution function. The nonparametric estimator of conditional expected shortfall is constructed by a plugging-in method. Both the asymptotic normality and consistency of the proposed nonparametric estimators are established at both boundary and interior points for time series data. We show that the weighted double kernel local linear conditional distribution estimator has the advantages of always being a distribution, continuous, and differentiable, besides the good properties from both the double kernel local linear and weighted Nadaraya–Watson estimators. Moreover, an ad hoc data-driven fashion bandwidth selection method is proposed, based on the nonparametric version of the Akaike information criterion. Finally, an empirical study is carried out to illustrate the finite sample performance of the proposed estimators.     

Reliable inference for the Gini index

Although attention has been given to obtaining reliable standard errors for the plug-in estimator of the Gini index, all standard errors suggested until now are either complicated or quite unreliable. An approximation is derived for the estimator by which it is expressed as a sum of IID random variables. This approximation allows us to develop a reliable standard error that is simple to compute. A simple but effective bias correction is also derived. The quality of inference based on the approximation is checked in a number of simulation experiments, and is found to be very good unless the tail of the underlying distribution is heavy. Bootstrap methods are presented which alleviate this problem except in cases in which the variance is very large or fails to exist. Similar methods can be used to find reliable standard errors of other indices which are not simply linear functionals of the distribution function, such as Sen’s poverty index and its modification known as the Sen–Shorrocks–Thon index.     

负债来源、会计信息质量与企业投资

本文以中国上市公司为研究对象,考察了在高风险项目企业中会计信息质量对企业新增投资支出的影响,揭示了会计信息质量在债权人保护中的作用。实证结果表明:高质量的会计信息能够抑制高风险项目企业的新增投资支出,这样的抑制效果在高风险项目企业的主要负债来源为非商业银行时表现的更加显著。     

Risk aversion for variational and multiple-prior preferences

The objective of this paper is to identify variational preferences and multiple-prior (maxmin) expected utility functions that exhibit aversion to risk under some probability measure from among the priors. Risk aversion has profound implications on agents’ choices and on market prices and allocations. Our approach to risk aversion relies on the theory of mean-independent risk of Werner (2009). We identify necessary and sufficient conditions for risk aversion of convex variational preferences and concave multiple-prior expected utilities. The conditions are stability of the cost function and of the set of probability priors, respectively, with respect to a probability measure. The two stability properties are new concepts. We show that cost functions defined by the relative entropy distance or other divergence distances have that property. Set of priors defined as cores of convex distortions of probability measures or neighborhoods in divergence distances have that property, too.     

Financial market equilibria with cumulative prospect theory

The paper first shows that financial market equilibria need not to exist if agents possess cumulative prospect theory preferences with piecewise-power value functions. This is due to the boundary behavior of the cumulative prospect theory value function, which might cause an infinite short-selling problem. But even when a non-negativity constraint on final wealth is added, non-existence can occur due to the non-convexity of CPT preferences, which might cause discontinuities in the agents’ demand functions. This latter observation also implies that concavification arguments which has been used in portfolio allocation problems with CPT preferences do not apply to our general equilibrium setting with finite many agents. Existence of equilibria is established when non-negativity constraints on final wealth are imposed and there is a continuum of agents in the market. However, if the original prospect theory is used instead of cumulative prospect theory, then other discontinuity problems can cause non-existence of market equilibria even in this case.     

The effects of information about health hazards in food on consumers’ choice process

This study examines the effects of context (health hazard), direction (positive versus negative) and intensity of information about health hazards on consumers’ choice processes. We propose that choice of frequently purchased food commodities, ceteris paribus, is based on a single dimension—taste. We develop a set of hypotheses regarding the type of choice process to be employed in various information types and empirically test them in a field experiment design. Our results indicate that a single-dimension choice process is employed under a nonsevere message and a multidimensional process under high-intensity negative information.     

Trade credit versus bank credit: Evidence from corporate inventory financing

In this study, I introduce capital market imperfections into a structure framework of inventory investments and investigate impacts of trade credit on firms’ inventory dynamics and analyze the relationship between trade credit and bank loans. As a result, firms end up using a mix of trade credit and bank loans. I find that the use of trade credit and bank credit can be either complements or substitutes. During tight monetary periods, trade credit operates mainly as a substitute for bank borrowing while during looser monetary episodes even when the economy is weak, trade credit and bank loans are dominated by a complementary effect.     

Efficient venture capital financing combining debt and equity

I present a model of venture capital contracting in which contracts that involve a mixture of both debt and equity are efficient and dominate pure-equity and pure-debt financing. The optimal contract balances the venture capitalist's incentive to intervene in the project and the entrepreneur's desire for control. Received: 9 September 1997 / Accepted: 3 April 1998     

Edgeworth expansions and normalizing transforms for inequality measures

Finite sample distributions of studentized inequality measures differ substantially from their asymptotic normal distribution in terms of location and skewness. We study these aspects formally by deriving the second-order expansion of the first and third cumulant of the studentized inequality measure. We state distribution-free expressions for the bias and skewness coefficients. In the second part we improve over first-order theory by deriving Edgeworth expansions and normalizing transforms. These normalizing transforms are designed to eliminate the second-order term in the distributional expansion of the studentized transform and converge to the Gaussian limit at rate O(n⁻¹)$O\left(n^{-1}\right)$. This leads to improved confidence intervals and applying a subsequent bootstrap leads to a further improvement to order O(n^−3/2)$O\left(n^{-3/2}\right)$. We illustrate our procedure with an application to regional inequality measurement in Côte d’Ivoire.