我国上市公司使用外汇衍生品的影响因素研究

本文利用2005-2010年我国上市公司使用外汇衍生品的数据,分析公司使用外汇衍生品行为的影响因素,从而对破产成本等假设进行验证。研究发现,财务状况、投资机会等指标是使用衍生品的影响因素。本文还分析了公司的股权结构、产权性质、市场化程度、政治关联度对使用衍生品的影响,使用连续变量的稳健性检验支持了本文的结论。论文拓展了外汇衍生品使用动机的研究,在规范上市公司衍生品信息披露和加强公司衍生品行为监管方面提出了相应的政策建议。     

Robustness of stable volatility strategies

The paper analyzes the robustness of stable volatility strategies, i.e. strategies in which the portfolio weight of the stock is inversely proportional to its local volatility. These strategies are optimal for a CRRA investor if the stock follows a diffusion process, the expected excess return is proportional to its volatility, and the hedging demand is zero. We assess the performance of stable volatility strategies when these restrictive assumptions do not hold, in particular, when the risk premium is not proportional to volatility and when the stock price is subject to jumps. We find that stable volatility strategies are indeed robust or close to robust under a maxmin decision rule. In addition to our theoretical results, we perform a simulation analysis to evaluate strategies that scale the portfolio weight by the volatility, variance or a constant portfolio weight, and also analyze the strategies using empirical excess returns. Both analyses confirm the robustness of stable volatility strategies.     

Stochastic optimization models for the airport gate assignment problem

Uncertainties inherent in the airport traffic may lead to the unavailability of gates for accommodating scheduled flights. Incorporating random disruptions is crucial in constructing effective flight-gate assignments. We consider the gate assignment problem under uncertainty in flight arrival and departure times and develop stochastic programming models incorporating robustness measures based on the number of conflicting flights, idle and buffer times. The proposed models are formulated as large-scale mixed-integer programming problems and tabu search algorithms are implemented to obtain assignments of reasonable quality. We conduct a computational study to analyze the proposed alternate models and show the effectiveness of the solution methods.     

Four types of ignorance

This paper studies alternative ways of representing uncertainty about a law of motion in a version of a classic macroeconomic targetting problem of Milton Friedman (1953). We study both “unstructured uncertainty” – ignorance of the conditional distribution of the target next period as a function of states and controls – and more “structured uncertainty” – ignorance of the probability distribution of a response coefficient in an otherwise fully trusted specification of the conditional distribution of next period׳s target. We study whether and how different uncertainties affect Friedman׳s advice to be cautious in using a quantitative model to fine tune macroeconomic outcomes.     

考虑技术中介的相互依存创新网络系统鲁棒性研究

创新网络系统已成为当前创新领域的研究热点之一。技术中介能够实现不同企业或组织技术需求与技术投入的最优匹配。相互依存网路将创新网络、技术中介网络和技术服务支持网络整合为有机整体。为此,构建了节点负载的相互依存创新网络系统级联失效鲁棒性模型。研究发现,容限系数越高的系统,其鲁棒性越好。在随机失效方式下,随机网络结构比其它两种组织网络结构任务完成效率高;在优先失效方式下,一定比例的组织节点优先失效即可导致整个网络完全瘫痪。该结论为研究创新网络结构以及关键创新技术节点冗余机制的采用提供了新的思路和视角,具有一定的探索意义和实践价值。     

Solution of macromodels with Hansen–Sargent robust policies: some extensions

We summarize some methods useful in formulating and solving Hansen–Sargent robust control problems, and suggest extensions to discretion and simple rules. Matlab, Octave, and Gauss software is provided. We illustrate these extensions with applications to the term structure of interest rates, the time inconsistency of optimal monetary policy, the effects of expectations on the variances of inflation and output, and on whether central banks should make their forecasts public.     

Poverty measurement with contaminated data: A robust approach

We examine the sensitivity of poverty indices to data contamination using the concept of the influence function, and demonstrate that an important commonly used subclass of poverty measures will be robust under data contamination. This is illustrated using simulations. In this respect poverty and inequality indices have fundamentally different robustness properties. We investigate both the case where the poverty line is exogenously fixed and where it must be estimated from the data.     

Challenging the robustness of optimal portfolio investment with moving average-based strategies

The aim of this paper is to compare the performance of a theoretically optimal portfolio with that of a moving average-based strategy in the presence of parameter misspecification. The setting we consider is that of a stochastic asset price model where the trend follows an unobservable Ornstein–Uhlenbeck process. For both strategies, we provide the asymptotic expectation of the logarithmic return as a function of the model parameters. Then, numerical examples are given, showing that an investment strategy using a moving average crossover rule is more robust than the optimal strategy under parameter misspecification.     

When and why? A critical survey on coordination failure in the laboratory

Coordination games with Pareto-ranked equilibria have attracted major attention over the past two decades. Two early path-breaking sets of experimental studies were widely interpreted as suggesting that coordination failure is a common phenomenon in the laboratory. We identify the major determinants that seem to affect the incidence, and/or emergence, of coordination failure in the lab and review critically the existing experimental studies on coordination games with Pareto-ranked equilibria since that early evidence emerged. We conclude that there are many ways to engineer coordination successes.      

Robust reinsurance contracts in continuous time

We investigate reinsurance contract problems in a continuous-time principal-agent framework, where the reinsurer (principal) is concerned about potential model ambiguity in the claims process, but the insurer (agent) trusts the claims process, or vice versa. The reinsurer designs a robust reinsurance contract that maximizes his exponential utility of terminal wealth under the worst-case distribution, subject to the insurer’s incentive constraint. Optimal reinsurance contracts are explicitly derived in different ambiguity situations. We first show that the reinsurer’s robustness preference makes him become more conservative, which induces him to raise the reinsurance price, which then decreases the demand for reinsurance. However, the insurer’s robustness preference increases both the reinsurance price and the demand. Furthermore, the reinsurer continuously adjusts the reinsurance price, leading the insurer to always purchase a constant proportion of reinsurance, no matter who faces ambiguity, or whether ambiguity exists. Finally, the economic implications of model ambiguity are illustrated using numerical examples.