Analysing Perceived Downside Risk: the Component Value‐at‐Risk Framework

Multinational companies face increasing risks arising from external risk factors, e.g. exchange rates, interest rates and commodity prices, which they have learned to hedge using derivatives. However, despite increasing disclosure requirements, a firm's net risk profile may not be transparent to shareholders. We develop the ‘Component Value‐at‐Risk (VaR)’ framework for companies to identify the multi‐dimensional downside risk profile as perceived by shareholders. This framework allows for decomposing downside risk into components that are attributable to each of the underlying risk factors. The firm can compare this perceived VaR, including its composition and dynamics, to an internal VaR based on net exposures as it is known to the company. Any differences may lead to surprises at times of earnings announcements and thus constitute a litigation threat to the firm. It may reduce this information asymmetry through targeted communication efforts.     

Use of Statistics in the Monetary Policy of the Czech National Bank: The Case of a Country in Transition

In the presented text the authors judge the importance of statistics in the monetary policy of the Czech National Bank (CNB) over the course of the economic transformation process, with particular consideration of changing statistical needs and the possibilities and limits of statistical data exploitation in the monetary analyses. The importance of statistics lies on the level of collection and processing of statistical information and on the level of use of statistical methods to analyse data. Since the start of the 1990s the requirements for statistics were significantly influenced by monetary policy. In the period 1990–1997, monetary targeting was the primary influential factor. Since 1998, the monetary policy is influenced by inflation targeting. Statistical priorities switched from monetary data to economy and financial market data. Much progress has been made in the use of statistical methods for analysing data. Statistics available at present cover the CNB's standard monetary-policy requirements and are on par with those in developed countries. Its further development will reflect the standard changes taking place in the more advanced countries.     

The Measurement of Consumption Efficiency Considering the Discrete Choice of Consumers

In this study we propose a mathematical definition of the consumption efficiency of multi-attribute products in the price–quality space. A new model, the discrete Range Adjusted Measure (RAM) model, is suggested as an empirical tool to measure the level of consumption efficiency. We further discuss the effect of consumption efficiency on the innovation incentive. Empirical work is made for the mobile phone market. We expect that the consumption efficiency concept will contribute to the extension of the traditional framework of production efficiency analysis on the one hand and to the understanding of the nature of innovation in a technology-intensive market on the other hand.JEL Classification: C67, D11, D12, D21     

现代企业委托代理问题的“中庸之道”

孔子提出的“中庸之道”从根本上说是一种管理思想和方法,它要求人们作任何事情都要遵循适度原则,这对现代企业中的委托代理问题同样具有重要意义。在这一思想方法的指导下,本文论证了解决委托代理问题的最优激励机制设计,寻找激励与监督的均衡点。     

独立董事的相对独立性与发挥作用的途径

本文的实证结果表明独立董事报酬无论与内部董事,还是与管理高层的整体报酬之间都呈现显著的正相关关系,这说明独立董事具有相对独立性是不以人的意志为转移的客观事实。在此基础上,研究了相对独立性对监督有效性带来的影响。结果表明,尽管独立董事只具有相对的独立性,但只要能挖掘出符合相对独立性要求的机制来激励独立董事做更多实实在在的工作,具有高认知能力的独立董事依然能在上市公司的治理中有效地发挥作用。     

Blocked-Error-R 2: A Conceptually Improved Definition of the Proportion of Explained Variance in Models Containing Loops or Correlated Residuals

Bentler and Raykov (2000, Journal of Applied Psychology 85: 125–131), and Jöreskog (1999a, http://www.ssicentral.com/lisrel/column3.htm, 1999b http://www.ssicentral. com/lisrel/column5.htm) proposed procedures for calculating R ² for dependent variables involved in loops or possessing correlated errors. This article demonstrates that Bentler and Raykov’s procedure can not be routinely interpreted as a “proportion” of explained variance, while Jöreskog’s reduced-form calculation is unnecessarily restrictive. The new blocked-error-R ² (beR ²) uses a minimal hypothetical causal intervention to resolve the variance-partitioning ambiguities created by loops and correlated errors. Hayduk (1996) discussed how stabilising feedback models – models capable of counteracting external perturbations – can result in an acceptable error variance which exceeds the variance of the dependent variable to which that error is attached. For variables included within loops, whether stabilising or not, beR ² provides the same value as Hayduk’s (1996) loop-adjusted-R ². For variables not involved in loops and not displaying correlated residuals, beR ² reports the same value as the traditional regression R ². Thus, beR ² provides a conceptualisation of the proportion of explained variance that spans both recursive and nonrecursive structural equation models. A procedure for calculating beR ² in any SEM program is provided.     

企业资产结构的影响因素及模式研究

资产结构是指企业资本在不同资产形态上分布状况及分配比例。资产结构一般具有整体性、封闭性、动态性等特征;资产结构的形成受到诸多内外部因素的影响。本文研究了影响企业资产结构的因素,分析了资产结构的类型,并根据资产变现性的特征,将资产结构模式分为三种类型。     

应用期权方法构建商业银行贷款利率模型

以分析公司普通股所具有的看涨期权特性为出发点，以Black—Scholes看涨期权定价模型为基础，根据不同企业资本结构和资产回报风险的差别，构造了一个商业银行基本贷款利率模型。从期权角度来设计贷款利率模型，除考虑了企业的经营风险因责外，还同时考虑了企业融资结构所带来的财务风险，能更加全面地反映出商业银行贷款的保障程度。     

高职教育实践性教学初探

加强高等职业教育的实践性教学,是高等职业教育教学改革的一个关键的突破口。只有加强实践性教学的探讨和创新,才能突出高职教育的特色。要积极探讨建立实践性教学为主的模式和运行机制,如实践性教学导师制、学生模拟实习公司等。同时,要处理好理论教学与实践教学的关系,处理好培养人才"宽"与"窄"的关系。     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.