Contrarian Investment in the Dutch Stock Market

The efficient markets hypothesis states that at any times security prices fully reflect all available information. Contrarian investment strategies do not recognize the efficiency of capital markets. They call for buying undervalued stocks, i.e. stocks with a low price relative to their fundamentals. The idea behind such a strategy is to take advantage of the extrapolation behaviour of naive investors. Using a fresh and extensive data set from the Dutch stock market, we found that these strategies yield an outperformance without a higher risk. Our results make it hard to maintain the efficient market hypothesis.     

Beyond Single-Factor Affine Term Structure Models

This article proposes a new approach to testing for the hypothesisof a single priced risk factor driving the term structure ofinterest rates. The method does not rely on any parametric specificationof the state variable dynamics or the market price of risk.It simply exploits the constraint imposed by the no-arbitragecondition on instantaneous expected bond returns. In order toachieve our goal, we develop a Kolmogorov-Smirnov test and applyit to data on Treasury bills and bonds for both the United Statesand Spain. We find that the single risk factor hypothesis cannotbe rejected for either dataset.     

Relative risk aversion, relative prudence and comparative statics under uncertainty: The case of (μ, σ)‐preferences

From the expected‐utility approach, relative risk aversion being smaller than one and relative prudence being smaller than two emerge as preference restrictions that fully determine the optimal responses of decisions under uncertainty to certain shifts in probability distributions. We characterize the magnitudes of relative risk aversion and relative prudence in terms of the two‐parameter, mean‐standard deviation approach. We demonstrate that this characterization is instrumental in obtaining comparative static results in the two‐parameter setting. We further relate our findings to the results in the expected‐utility framework.     

我国外汇储备：安全性、成本风险及对策

我国外汇储备狭义上的安全性，即外汇储备资产本身的安全令人担忧。我国已经为高额的外汇储备付出巨大成本和承担了很高的风险，同时，高额外汇储备也对我国经济发展产生了一系列负面影响和风险。从这个意义上来看，我国外汇储备的现状已成为威胁金融安全的一个重要隐患。因此，我国外汇储备政策的调整已经刻不容缓。     

我国国债的风险评估与防范

从国债的可持续性、国债的货币扩张效应、国债对经济增长的影响三个层面评估了我国当前的国债风险，并针对我国的国债特点，提出了防范国债风险的措施。     

基于Elman神经网络的商业银行信贷风险识别及评估模型

建立了基于Elman神经网络的商业银行信贷风险识别及评估模型，并通过实例验证了模型的准确性和可靠性。研究过程及结果表明，基于Elman神经网络的商业银行信贷风险识别及评估模型能够很好地反映信贷过程中的非线性因素，准确地预测出完整的信贷风险评估指标和信用等级之间的映射关系，能快速评估和有效减低商业的信贷风险。一组实例结果显示该评估模型的准确率接近90％。     

Hedging,Financing and Investment Decisions: A Simultaneous Equations Framework

We empirically investigate the interactions among hedging, financing, and investment decisions. We argue that the way in which hedging affects a firm's financing and investing decisions differs for firms with different growth opportunities. We find that high growth firms increase their investment, but not leverage, by hedging. However, we also find that firms with few investment opportunities use derivatives to increase their leverage.     

以风险协议为框架的化工措施管理机制探索与实践

以西方经济学中的代理理论为基础．建立了一套以风险协议为框架、对化工措施全过程进行控制的管理机制和相应的保证体系，提高了化工措施现场实施的成功率和有效率。     

基于粗糙集理论的决策树方法在贷款客户信用评估中的应用

决策树是数据挖掘中常用的分类技术，其生成的规则便于决策者理解和应用。然而面对较多的属性且含有冗余和噪声属性的记录集生成的决策树时，无法删除冗余属性，造成运算过程复杂。本文旨在通过应用粗糙集理论，将其与决策树方法进行结合，对属性进行约简，降低运算复杂度，并生成相对简化的规则形式，并将其应用到银行个人贷款客户信用评估之中。