电子商务环境下的企业财务危机预警研究

本文通过对国内外财务危机预警模型的比较,运用二值多元logistic回归方法构建了电子商务环境下企业财务危机的预警模型。测试结果表明,模型对估计样本的准确判别率为92．2％,对控制样本的准确判别率为81．25％,说明了该模型具有较好的预警能力,且预警效果具有一定的稳定性。     

A Research on the Domain of Sport Tourism

Sport-based travel has grown dramatically over the past two decades but it has only recently become the focus of concentrated academic inquiry. This paper contributes to the emerging body of literature by conceptualizing sport in the context of tourism＇s activity, spatial and temporal dimensions. The context of this paper includes current lines of inquiry, the domain of tourism and the domain of sport.     

磁悬浮变频驱动离心式冷水机组经济性分析

选用高效的冷水机组是空调系统节能减排的有效途径。磁悬浮变频驱动离心式冷水机组有着较高的综合部分负荷效率。文章针对医院空调系统,依据整个制冷期内空调冷负荷的变化,通过对冷水机组的选型分析,结合工程实例,对磁悬浮变频驱动离心式冷水机组进行简单的经济性分析及CO2减排量的计算。     

一种新话语的孕育：刑法知识的进阶与转型——也读陈兴良之作《刑法知识论》

我国现行刑法体系从其本源上看,发端于20世纪50年代的前苏联.尤其是作为刑法根基的犯罪构成理论,更是＂饱受＂前苏联刑法犯罪构成理论的＂滋养＂.在当时引入该犯罪构成理论对我国刑法的萌生产生了巨大的影响,其价值自不待言.而现今这一＂嫁接＂的理论正在接受着来自欧陆德日刑法、英美法系刑法等更新的、多元的、＂嫁接＂的文化际的反复冲击,已显出退却之势;再加之国内复杂的个案频发,又从另一个层面对这一刑法知识提出了挑战与要求.故而一种新的知识进阶与转型,正在悄然促成.     

Moral Opinions are Conditional on the Behavior of Others

In social dilemmas individual behavior creates external effects on others. In such situations, a person's opinions concerning right and wrong might influence his behavior. Understanding moral opinions therefore is important. This paper reports on an experiment which shows that moral opinions are conditional on the behavior of others. This is demonstrated by the finding that a large majority of subjects in a public good game experiment report personal normative beliefs that increase with the actual contributions made by group members. This finding is important for the design of policies attempting to sustain public good provisions.     

信息披露质量对分析师预测的影响

作为连接上市公司与外部投资者的重要信息中介,分析师预测质量的高低对降低信息不对称,提高资本市场效率具有重要作用,而所获公司信息的质量是影响其正确分析判断的因素之一。文章利用2009-2013年我国上市公司数据,以深交所信息披露考评结果作为信息披露质量的代理变量,考察了信息披露质量提升对分析师预测误差、预测分歧度的影响。实证结果发现:信息披露质量较高的公司及信息披露质量水平提升的公司,分析师预测分歧度和预测误差也较低。这意味着,作为一个公开的重要信息来源,上市公司的信息披露质量显著影响了分析师预测。此研究结论不仅有助于监管者了解信息披露政策对资本市场参与者的现实影响,也为其合理引导公司信息披露,完善相关规范政策提供新的决策参考。     

供货频次和需求配比视角下考虑动机公平的供应链

将Rabin构建的同时包含物质效用和动机公平的效用函数引入在供货频次和需求配比视角下构建的供应链模型,研究供应方间的互惠性非理性行为。研究表明:考虑动机公平后,供应方会获得更为均等的需求配比;需求方只要与动机公平偏好程度尽可能大的供应方合作,就能尽可能地降低仓储成本。     

供货频次和需求配比视角下的供应链最优价格决策

以供货频次和需求配比为视角,构建了一个供应链动态博弈模型,研究了在需求方为先决策者和供应方为先决策者两种情形下供应链系统的最优价格决策机制,分别给出了两种情形下的最优价格决策方案,指出产品是最优价格决策中的根本性影响因素。     

Forecasting the price of gold

This article seeks to evaluate the appropriateness of a variety of existing forecasting techniques (17 methods) at providing accurate and statistically significant forecasts for gold price. We report the results from the nine most competitive techniques. Special consideration is given to the ability of these techniques to provide forecasts which outperforms the random walk (RW) as we noticed that certain multivariate models (which included prices of silver, platinum, palladium and rhodium, besides gold) were also unable to outperform the RW in this case. Interestingly, the results show that none of the forecasting techniques are able to outperform the RW at horizons of 1 and 9 steps ahead, and on average, the exponential smoothing model is seen providing the best forecasts in terms of the lowest root mean squared error over the 24-month forecasting horizons. Moreover, we find that the univariate models used in this article are able to outperform the Bayesian autoregression and Bayesian vector autoregressive models, with exponential smoothing reporting statistically significant results in comparison with the former models, and classical autoregressive and the vector autoregressive models in most cases.     

Forecasting industrial production in the Euro area

The creation of the Euro area has increased the importance of obtaining timely information about short-term changes in the area's real activity. In this paper we propose a number of alternative short term forecasting models, ranging from simple ARIMA models to more complex cointegrated VAR and conditional models, to forecast the index of industrial production in the euro area. A conditional error-correction model in which the aggregate index of industrial production for the area is explained by the US industrial production index and the business confidence index from the European Commission harmonised survey on manufacturing firms achieves the best score in terms of forecasting capacity. First version received: Jan. 2000/Final version received: March 2000     

科技型中小企业的业务外包战略分析

业务外包是近年来在国内外流行的管理模式 ,其管理思想是使企业将主要精力放在核心业务上 ,充分发挥优势 ,企业中的非核心业务外包给合作企业来完成。正是基于这种背景 ,本文首先分析了科技型中小企业使用外包战略对其成长的重要影响 ,其次分析了科技型中小企业业务外包的内在条件。同时本文进一步探讨了科技型中小企业常用的业务外包模式以及企业如何更好地使用业务外包的策略。     

Maximal Domain of Preferences in the Division Problem

The division problem consists of allocating an amount of a perfectly divisible good among a group of n agents. Sprumont (1991) showed that if agents have single-peaked preferences over their shares, then the uniform allocation rule is the unique strategy-proof, efficient, and anonymous rule. We identify the maximal set of preferences, containing the set of single-peaked preferences, under which there exists at least one rule satisfying the properties of strategy-proofness, efficiency, and strong symmetry. In addition, we show that our characterization implies a slightly weaker version of Ching and Serizawa's (1998) result. Journal of Economic Literature Classification Numbers: D71, D78, D63.     

马尔柯夫预测法在经济工作中的应用

马尔柯夫预测法在产品市场占有量的预测中具有较好的预测效果。利用此方法,对一实际商场中某一类商品市场占有量作了预测,实际反馈也与预测比较一致。     

俄罗斯经济发展形势的分析与预测

本文采用俄罗斯2002-2013年的季度数据作为样本,主要分析了季节性差分自回归模型——SARIMA模型在俄罗斯季度GDP预测中的应用,通过相应的分析最终得到了SARIMA(1,1,0)(1,1,0)4为俄罗斯季度GDP的最优预测模型.通过该模型对俄罗斯短期和长期经济发展形势进行了预测,得出俄罗斯未来四年的GDP年增长率在2.3％左右,长期的经济增长率在2.1％左右,经济形势依然不容乐观.     

Forecasting the realized volatility: the role of jumps

This article investigates the role of jump components dependent on the ABD-LM jump test in forecasting volatility. Our out-of-sample forecasting results show that compared with the ABD-LM jump component, its decomposition forms based on signed returns can significantly improve the models’ forecasting performance and our findings have important implications for investors and policymakers.     

Forecasting the yield curve and the role of macroeconomic information in Turkey

In this study we investigate the yield curve forecasting performance of Dynamic Nelson–Siegel Model (DNS), affine term structure VAR model (ATSM VAR) and principal component model (PC) in Turkey. We also investigate the role of macroeconomic variables in forecasting the yield curve. We have reached numbers of important results: 1—Macroeconomic variables are very useful in forecasting the yield curve. 2—The forecasting performances of the models depend on the period under review. 3—Considering the structural break which associates with change in monetary policy leads models to produce better forecasts than the random walk. 4—The role of exchange rate should not be ruled out in forecasting the yield curve in an emerging market like Turkey.     

Forecasting the aggregate stock market volatility in a data-rich world

ABSTRACT

In this article, we utilize the basic lasso and elastic net models to revisit the predictive performance of aggregate stock market volatility in a data-rich world. Motivated by the existing literature, we determine several candidate predictors that have 22 technical indicators and 14 macroeconomic and financial variables. Our out-of-sample results reveal several noteworthy findings. First, few macroeconomic and financial variables and most of technical indicators have superior performance relative to the benchmark model. Second, combination forecasts are able to significantly beat the benchmark and some signal predictors Third, the lasso and elastic models with all predictors can generate more accurate forecasts than the benchmark and some other predictors in both the statistical and economic sense. Fourth, the lasso and elastic models exhibit higher forecast accuracy during periods of expansions and recessions. Finally, our findings are robust to several tests, such as different forecasting windows, forecasting models, and forecasting evaluations.     

基于GARCH-BP模型的股指预测及实证分析

本文通过建立BP神经网络预测模型和GARCH-BP神经网络预测模型,对2004￣2005年间深圳成分指数的日收盘价进行了预测分析,经过实证比较,发现GARCH-BP模型较BP模型的收敛速度快,学习能力强,预测精度较高,误差率较小。     

上市公司财务危机预警实证研究

从20世纪60年代起,国内外的学者对上市公司财务危机预警问题就进行了大量研究,从方法上看,主要有线性判别分析、多元线性回归分析和Logistic三种,大量的实践证明,运用Logistic模型判定上市公司财务危机预警的准确性相对较高。