基于预测能力的扩展极限边界分析法

本文在传统EBA方法的基础上,将其引入到时间序列中,构建以预测为导向的AEBA模型选择方法。AEBA在模型选择上更注重于模型的预测能力,在稳健性检验上细分为模型稳健性检验与参数稳健性检验两部分,提出了基于时间序列预测能力的检验方法。最后实证示例用AEBA方法对影响石油股票指数收益率的因素进行了研究,表明该方法选择的模型的预测能力,特别是短期预测能力要显著强于CAPM、三因子模型、ARMA以及VAR。     

基于人工智能的设备颜色特性化方法鲁棒性对比研究

设备颜色特性化是色彩管理技术得以顺利实现的关键技术之一,其核心是设备相关颜色空间和与设备无关颜色空间之间的相互转换。本研究首先定义颜色空间转换方法的鲁棒性概念及其评价方法,在此基础上,对基于模糊控制的颜色空间转换方法、基于动态子空间划分的BP神经网络颜色空间转换方法和基于模糊神经辨识的颜色空间转换方法等基于人工智能的颜色空间转换方法的鲁棒性做了比较研究。研究结果显示：基于模糊神经辨识的颜色空间转换方法能够结合BP神经网络和模糊控制的特点,使其鲁棒性得到很大的提高。     

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.     

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。     

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.     

Model-free CPPI

We consider Constant Proportion Portfolio Insurance (CPPI) and its dynamic extension, which may be called Dynamic Proportion Portfolio Insurance (DPPI). It is shown that these investment strategies work within the setting of Föllmer's pathwise Itô calculus, which makes no probabilistic assumptions whatsoever. This shows, on one hand, that CPPI and DPPI are completely independent of any choice of a particular model for the dynamics of asset prices. They even make sense beyond the class of semimartingale sample paths and can be successfully defined for models admitting arbitrage, including some models based on fractional Brownian motion. On the other hand, the result can be seen as a case study for the general issue of robustness in the face of model uncertainty in finance.     

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.     

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.