Early warning models against bankruptcy risk for Central European and Latin American enterprises

This article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warning models for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange and 60 companies listed on Stock Exchange markets in Mexico, Argentina, Peru, Brazil and Chile. This population of firms was divided into learning and testing setdata. Each company was analyzed using the absolute values of 14 financial ratios and the dynamics of change of these ratios.The author's developed models are characterized by high efficiency. These studies are one of the world's first attempts at comparing differences in forecasting this phenomenon between the regions of Latin America and Central Europe. Additionally, a comparison of the effectiveness of discriminant analysis, decisional trees, and artificial neural networks models was made.     

知识型员工心理契约预测方法研究——基于回归树和RBF神经网络的学习算法

以知识型员工心理契约为研究对象,结合在国内三家知识型员工企业调研的实测数据,建立基于RBF神经网络的心理契约预测模型,同时为实现对RBF神经网络预测效率的优化,选择回归树与RBF神经网络相结合的方式,力求实现两者的优势互补,建立一个高效便捷的回归树与RBF神经网络相结合的知识型员工心理契约预测模型。结果表明:通过回归树、RBF神经网络预测数据结果与在三家知识型员工企业实际施测数据结果比较后发现,回归树与RBF结合的神经网络预测数据结果具有较高的准确性。因此,我们可以认为基于回归树的RBF神经网络的学习算法和以该算法为核心的知识型员工心理契约水平预测模型是有效的,该模型对知识型员工心理契约水平的预测具有较高的准确性。该模型能够替代以往对知识型员工心理契约主观预测的方法,使心理契约的预测过程更为高效,预测结果更加科学。     

A novel time-series model based on empirical mode decomposition for forecasting TAIEX

Stock price prediction is regarded as a challenging task of the financial time series prediction process. Time series models have successfully solved prediction problems in many domains, including the stock market. Unfortunately, there are two major drawbacks in stock market by time-series model: (1) some models cannot be applied to the datasets that do not follow the statistical assumptions; and (2) most time-series models which use stock data with many noises involutedly (caused by changes in market conditions and environments) would reduce the forecasting performance. For solving the above problems and promoting the forecasting performance of time-series models, this paper proposes a hybrid time-series support vector regression (SVR) model based on empirical mode decomposition (EMD) to forecast stock price for Taiwan stock exchange capitalization weighted stock index (TAIEX). In order to evaluate the forecasting performances, the proposed model is compared with autoregressive (AR) model and SVR model. The experimental results show that the proposed model is superior to the listing models in terms of root mean squared error (RMSE). And the more fluctuation year (2000–2001) occurs, the better accuracy of proposed model will be obtained.     

Modelling sovereign credit ratings: The accuracy of models in a heterogeneous sample

The accuracy of sovereign credit ratings renewed interest toward sovereign credit ratings in the aftermath of the 2008 financial crisis. The controversy over the accuracies encouraged internal credit scoring systems to reduce reliance on sovereign credit ratings. By employing classification and regression trees (CART), multilayer perceptron (MLP), support vector machines (SVM), Bayes Net, and Naïve Bayes; we explore the prediction performance of several artificial intelligence (AI) techniques in predicting sovereign credit ratings in a heterogeneous sample. The results suggest that AI classifiers outperform the conventional statistical technique in terms of accurate prediction. According to within one notch and two notches accurate prediction measure, the prediction performances of the AI classifiers exceed 90% accuracy whereas the performance of the conventional statistical method is around 70%. The results further reveal that the prediction performance of the models declines around the threshold rating that is located between investment grade and speculative grade which is not necessarily the result of inadequacy of the models. Rather, this is potentially due to CRAs' cautious behaviour toward those countries around threshold rating which can be interpreted as the certification price of upgrading to investment grade.     

On the determinants of happiness: a classification and regression tree (CART) approach

This article studies the determinants of the individual’s subjective well-being by applying a classification and regression tree (CART) analysis to data from the Survey on Household Income and Wealth (SHIW) provided by the Bank of Italy. The results support the primary importance of economic conditions but show that their effect is heterogeneously dependent on other individual characteristics.     

基于判别分析的内部控制重大缺陷预测研究

公司破产风险、财务舞弊事件通常与内部控制重大缺陷存在密切关系,研究内部控制重大缺陷判别方式具有重要意义和价值。本文以深交所2007—2008年138家内部控制重大缺陷公司与138家非重大缺陷公司为样本,采用逐步判别分析法构建内部控制重大缺陷判别模型,帮助监管方、外部投资者等更好地预测内部控制重大缺陷。研究表明,相比非重大缺陷公司,内部控制重大缺陷公司上市年限较长、规模较小、外部审计师变更更加频繁,盈利能力和成长性较差,但流动性、营运能力指标的检验结果是混合性的。交互验证结果表明,模型预测准确率达到70%以上。     

经营困境、政治关系与银行贷款差异——基于持续经营不确定上市公司的经验证据

笔者以2002年~2005年获得非标审计意见上市公司为样本,以上市公司各年度银行贷款占资产总额比例以及贷款的自然对数作为银行贷款决策的替代变量,考察持续经营存在重大不确定对银行贷款决策的影响。多元回归分析发现,民营上市公司在持续经营不确定情况下,银行贷款决策更加严格,而国有上市公司没有因此受到明显影响,但持续经营不确定的国有上市公司债务违约现象比该类民营上市公司更严重。这说明政治关系、政府干预影响了银行向国有上市公司的贷款决策。     

Forecasting and analyzing the competitive diffusion of mobile cellular broadband and fixed broadband in Taiwan with limited historical data

Taiwan experienced the rapid growth of mobile cellular broadband from 2005 by introducing 3G operations and had higher penetration than the average of the developing countries, the world, and even the developed countries. There are many forecasting models which were developed and successfully predicted the diffusion of long lifecycle product, but there are very few forecasting models which were developed for predicting new products with short lifecycle. Assumption of these models is always the growth of products follows an S-shaped curve. As for the products which were just introduced to the market, it is very difficult to identify if they follow an S-shaped curve with their limited historical data. This research aims to apply Grey system theory to predict the diffusion of mobile cellular broadband and fixed broadband in Taiwan since Grey system theory has a characteristic which requires very limited primitive data (the least 4 data) to build a differential forecasting model. We use penetration as an indicator to describe the diffusion of new products. The numerical data show that the Grey forecasting models GM(1,1) built in this paper have higher prediction accuracy than logistic models and grey Verhulst models. Moreover, we apply Lotka–Volterra model to analyze the competitive relationship between mobile cellular broadband and fixed broadband. The empirical data show that the relationship is commensalism rather than predator–prey. These results can be extended to contribute to other researches.     

财务独立董事、公司治理与经营业绩关系——基于中国民营上市公司面板数据的研究

独立董事与企业经营业绩之间相关性研究是公司治理研究中的一个重要问题,本文以2004~2006年在深沪交易所上市的民营企业为样本,采用面板数据,应用固定效应回归技术,从会计业绩(ROA)和市场业绩(TQ)的角度分别对财务独立董事对经营业绩的影响进行了实证分析。实证检验结果发现在民营上市公司中,财务独立董事与公司经营业绩之间不存在显著的相关关系,财务独立董事对公司经营业绩的改善没有起到促进作用。     

上市公司财务报表粉饰识别

上市公司财务报表粉饰现象是一个世界性难题。有必要借助一定的技术手段,对上市公司的财务报表粉饰行为进行识别,以便更好地对上市公司进行监管。相比传统的财务分析方法,关联挖掘技术在识别上市公司财务报表粉饰行为方面具有更好的效果。文章以特定期间微利企业的财务报表为研究对象,从沪深两市选取50家微利公司作为样本,利用关联挖掘技术中的Apriori算法,对其财务报表中的八大指标进行逐层搜索和迭代,找出具有强相关性的财务指标并对其关联规则进行分析和测试,从而识别出标识报表粉饰行为的关联特征指标值。分析表明：与良性发展的企业相比,那些连续亏损的企业具有更强的报表粉饰动机和可能性,这些企业往往通过关联交易等线下项目途径达到微利的目的。文章最后提出了更为有效地利用关联挖掘技术对这种行为进行识别的建议。     

Does the vector error correction model perform better than others in forecasting stock price? An application of residual income valuation theory

This paper employs a multi-equation model approach to consider three statistic problems (heteroskedasticity, endogeneity and persistency), which are sources of bias and inefficiency in the predictive regression models. This paper applied the residual income valuation model (RIM) proposed by Ohlson (1995) to forecast stock prices for Taiwan three sectors. We compare relative forecasting accuracy of vector error correction model (VECM) with the vector autoregressive model (VAR) as well as OLS and RW models used in the prior studies. We conduct out-of-sample forecasting and employ two instruments to assess forecasting performance. Our empirical results suggest that the VECM statistically outperforms other three models in forecasting stock prices. When forecasting horizons extend longer, VECM produces smaller forecasting errors and performs substantially better than VAR, suggesting that the ability of VECM to improve VAR forecast accuracy is stronger with longer horizons. These findings imply that an error correction term (ECT) of the VECM contributes to improving forecast accuracy of stock prices. Our economic significance analyses and robustness tests for different data frequency are in favor of the superiority of VECM estimator.     

上市公司财务困境的串联和并联组合预测

利用单一判别分析方法对上市公司财务困境进行预测具有片面性和不稳定性。本文尝试通过多种判别分析方法的串联和并联组合来提高预测效果。以我国上市公司为对象的实证研究表明：在预测公司财务困境方面,串联组合的平均预测准确率最高,预测准确率最稳定。但是并联组合预测效果不够理想,有待改进以提高预测效果。     

不同所有制下管理者过度自信与公司债务融资的关系

本文以2002—2008年我国沪深两市A股上市公司为样本,利用OLS回归模型考察了在不同所有制公司中管理者过度自信与债务融资之间的关系。研究结果显示:在不同所有制的上市公司中,管理者过度自信对公司债务融资的影响存在差异。与非国有上市公司相比,国有上市公司的管理者更加过度自信,更倾向于选择债务融资;在债务期限方面,不同所有制公司的过度自信管理者都倾向于使用长期债务,但在国有上市公司中这种倾向表现得更为显著。     

Rational conjectures and evolutionary beliefs in public goods games

This paper applies conjectural variations (CVs) to a model of public good provision and shows that CVs are superior to Nash beliefs. In addition to imposing consistency, as Bresnahan, I show that consistent conjectures (CCs) are obtained from individual payoff maximization. CCs emerge as the unique subgame perfect Nash equilibrium (NE) in a two-stage game in which beliefs are chosen in Stage 1 and quantities in Stage 2. There is an individual payoff advantage to non-Nash behavior, generating a Prisoner's Dilemma in conjectures in addition to the usual free-rider problem associated with public goods. The correct and payoff maximizing conjecture is the unique equilibrium in an evolutionary framework against a player with Nash conjectures. The consistent conjecture equilibrium is the unique evolutionary equilibrium when both players conjectures evolve. Hence, the NE prediction is too optimistic when players have rational conjectures.     

Decentralized and concentrated investments in China and the performance of Taiwanese listed electronic companies

Ever since China surpassed Taiwan to become the largest exporter of electronic products, dependence between the two sides has deepened, which prompts Taiwanese companies to go public in China. This study conducted the data envelopment analysis (DEA) and regression analysis to analyse the impacts of the depth and breadth of investments in China on the performance of Taiwanese listed electronic companies. The empirical results show that, the breath of the investments in China has a positive correlation with the performance of Taiwanese companies; while the depth of investments in China has a negative and significant effect on the performances due to the companies’ lack of know-how, which leads to a high-learning cost. In summary, companies should strategize their decentralized and concentrated investments in China.     

上市公司财务困境预测模型的再比较

该文将中国上市公司因财务状况异常而被特别处理(ST)作为企业陷入财务困境的标志,采用主成分分析方法确定模型变量,并利用多元判别分析、Logistic 回归和改进型 BP 神经网络三种方法进行财务困境预测.比较其预测结果发现,BP 神经网络模型的预测准确率明显优于多元判别分析和Logistic 回归模型,而后两者的判别效果接近,可见改进型 BP 神经网络模型更适合于企业财务困境预测.但三种模型的长期预警能力均不够理想,需要建立以定量模型为主、定性分析为辅的上市公司财务困境预测方式,以提高预测的准确性.     

海峡两岸证券业经营效率比较研究:基于Metafrontier方法

本文将Metafrontier思想与BCC-DEA模型相结合,综合应用Metafrontier DEA方法、Malmquist全要素生产率指数和Tobit模型,客观地评价具有不同生产技术的两岸证券商的经营效率。结果表明:台湾证券商发展水平趋同,大陆证券商良莠不齐,但竞争力逐渐提升;台湾证券商技术水平落后于大陆;大陆全要素生产率逐渐改善,台湾逐渐衰退;资产总额、负债比、地区生产总值是影响技术效率的关键因素,负债比、经济自由度、地区生产总值是影响技术落差的关键因素;金融危机对两岸证券业冲击显著。     

Examining the heterogeneity of treatment patterns in attention deficit hyperactivity disorder among children and adolescents in the Texas Medicaid population: modeling suboptimal treatment response

Objectives: To examine suboptimal responses (SR) in attention deficit hyperactivity disorder (ADHD) among pediatric patients in the Texas Medicaid program receiving osmotic-release oral system methylphenidate (OROS-MPH) or lisdexamfetamine (LDX) and apply an SR prediction model to identify patients most likely to experience an SR to either OROS-MPH or LDX therapies.

Methods: A retrospective cohort study was conducted using Texas Medicaid claims data of ADHD children and adolescents (6–17?years of age) initiating OROS-MPH or LDX. Primary SR endpoints were drug discontinuation, switching, and augmentation 12-months post-ADHD drug initiation. Logistic regression models were developed to predict SR to OROS-MPH and LDX in 1:1 matched groups of children and adolescent cohorts.

Results: A total of 3,633 children and 1,611 adolescents were matched for each cohort. SR was observed among more children (76.4% vs 72.3%; p?p?=?0.002) initiating OROS-MPH compared to LDX. Patient sub-groups with the highest predicted risk of OROS-MPH SR experienced significantly lower observed SR rates (p?Conclusions: This study demonstrated how a personalized medicine approach using administrative claims data can be used to identify sub-groups of child and adolescent ADHD patients with different risks for suboptimal response with OROS-MPH or LDX in a Medicaid population.     

Does microtherm boost pharmaceutical companies’ market capitalization returns?

The purpose of this study was to survey the relationship between the temperature factors and market capitalization returns of pharmaceutical companies by analysing both the daily and weekly frequency data in Taiwan. The threshold regression model with the GJR-GARCH process was applied for examination in this study; we found that pharmaceutical companies’ market capitalization returns could be boosted after exposure to extremely low temperatures for a period of time. Besides, the delayed effect of cold weather is demonstrated to exist. This phenomenon can be illustrated by epidemiological evidence-related mental factors, not by traditional behavioural finance. Moreover, lower weekly average temperatures are beneficial for investors to gain weekly pharmaceutical companies’ market capitalization returns. We are of the opinion that our findings offer an insightful suggestion for investors to buy pharmaceutical stocks at an opportune moment.     

Overlooked alternatives in managerial investment decisions: a reply

Some empirical evidence on the question of product differentiation in the market for audits is presented. Using agency cost and signalling frameworks we posit that there will be a demand for varying levels of audit quality. Because audit quality is not directly observable to investors we postulate that quality will be proxied by the auditor's brand name reputation. Big Eight auditors are categorized as being high quality producers. Using data on companies newly listing on the New Zealand Stock Exchange we test the derived models of auditor choice. Auditor choice is a dummy variable (0,1) partitioned on the basis of non Big Eight and Big Eight accounting firms. The results provide support for the idea of product differentiation in the market for audits.