教学课程资源库 更多>>

关键词： 护城河理论   运输服务企业   盈利能力  

摘要： 本文以我国运输服务行业12家上市公司2010—2013年财务数据为样本,分析了企业过去四年的盈利状况,并采用"护城河"理论对其长期盈利能力进行了分析,结果表明运输服务企业"护城河"普遍较窄,长期盈利能力较弱。最后就如何拓宽企业的护城河、提高企业的竞争力和盈利能力提出了建议。

关键词： MVC   编制系统   增量编制浅析   MVC模式  

摘要： 针对软件行业较为流行的MVC架构,探讨MVC在财务预算编制系统中的应用。阐述MVC模式及财务预算编制系统的架构,探讨MVC模式在预算编制系统中的应用。

关键词： 中国银行   盈利能力   实证分析  

摘要： 经济全球化加快背景下,我国商业银行最根本、最重要的任务就是如何提高我国商业银行的盈利能力。本文选取了我国四大国有商业银行之一的中国银行2005年至2012年数据为样本,利用多元回归法探寻影响我国中国银行盈利能力的因素,并从中找寻提升中国银行盈利能力的途径,以增强中国银行的竞争力,从而在国际竞争中立于不败之地。

关键词： 燕京啤酒   投资   盈利能力  

摘要： 啤酒业近年来一直是我国的支柱产业之一,它的发展对我国酿酒行业的发展具有深远意义。文章对比整个啤酒行业的发展介绍了燕京啤酒的发展概况,在此基础之上选取燕京啤酒近五年的年报数据,对其盈利能力的相关指标做了简要的分析,从而为广大投资者提供借鉴。

关键词： 因子分析法   盈利能力   零售业  

摘要： 对公司盈利能力评价的指标很多,采用某个指标往往顾此失彼,因子分析就为综合评价企业盈利能力提供了思路和方法。本文选取84家零售业上市公司,利用这些上市公司2014年年报数据,通过因子分析的方法,衡量其综合盈利能力。

关键词： STOCKS (Finance) -- Prices   STOCK price indexes   NEURAL networks (Computer science)   ECONOMIC forecasting   NONLINEAR models (Statistics)  

摘要： The researchers have been working on determining predictable patterns to forecast stock prices. But owing to nonstationary and nonlinear patterns of the data, the detection of new models and forecasting techniques have become an extremely intricate task. Artificial Neural Network (ANN) models are highly flexible functional algorithms, developed using machine's cognitive learning. In recent years, there has been an exponential increase in neural network applications in finance for the tasks such as pattern recognition, classification and time series forecasting. ANNs provide a considerably accurate means to examine nonlinearity in stock prices. However, large numbers of parameters need to be selected in order to develop an appropriate neural network forecasting model. The present study aims at predicting the stock prices of CNX Nifty 500 using assorted independent variables using ANNs. The variables used in the study are USD-INR exchange rate, crude oil price and major stock indices of USA (S&P 500), Euro Zone (Euro Stoxx 50), China (Shanghai Composite Index) and Japan (Nikkei 225). The paper considers daily data from January 2004 to December 2013. The series have been divided into training data and testing data to arrive at the most accurate model to be further used for predicting the stock prices for the next 10 months. The frequency of the given variables is daily, hence it would provide for a more efficient model incorporating smaller details such as daily volatility effect. The stock exchange data from foreign stock markets which open before and after the stock markets in India provide for change in market sentiments overnight. The preliminary data testing yielded encouraging results for the model. The predicted values of stock have a testing accuracy of more than 85%. [ABSTRACT FROM AUTHOR]

关键词： Quantile autoregression   Stock returns   Asymmetric dynamic dependence  

摘要： The paper provides an overview of the asymmetric dynamic dependency of the conditional return distribution using a quantile autoregression model for three indexes, namely the Shenzhen Component (SZC), the Standard & Poor's 500 (S&P 500) and Stoxx Europe 600 (S&E 600) indexes. Our findings can be summarized as follows. For SZC index, lagged extreme positive returns display more impact on current returns than that of lagged other returns at median and high quantiles;at median and high quantiles lagged positive returns display more impact on current returns than that of lagged negative returns;at lower quantiles lagged positive returns display less impact on current returns than that of lagged negative returns. For S&E 600 index, at low quantiles lagged extreme positive returns display less impact on current returns than that of lagged other returns;at high quantiles lagged extreme positive returns display more impact on current returns than that of lagged other returns;at low quantiles lagged positive returns display less impact on current returns than that of lagged negative returns;at high quantiles lagged positive returns display more impact on current returns than that of lagged negative returns. For S&P 500 index, at low quantiles lagged extreme positive returns display less impact on current returns than that of lagged other returns;at high quantiles lagged extreme positive returns display more impact on current returns than that of lagged other returns;at low quantiles lagged positive returns display less impact on current returns than that of lagged negative returns;and at high quantiles lagged positive returns display more impact on current returns than that of lagged negative returns. We find insignificant asymmetric dynamic dependency of middle returns for the three indexes. The sensitivity of our results is evaluated by a robustness check. The findings of this paper should help investors make appropriate decisions to maintain control of stock returns. (C)

关键词： 财务管理   目标异化   成因对策  

摘要： 企业财务管理目标是企业财务管理活动所希望实现的结果,是企业在组织财务活动和处理财务关系时所要达到的根本目的,而企业财务管理目标制约着财务活动的基本特征和发展方向,是企业财务活动的一种驱动力。如若这种重要的导向力发生了异化偏差,那么企业财务管理的运行机制就很难合理发展。因此,研究财务管理目标问题,既是建立科学的财务管理理论结构的需要,也是优化我国财务管理行为的需要,在理论和实践上都具有重要意义。

关键词： 企业   财务管理   目标   选择   实现  

摘要： 企业财务管理目标,是在一定市场环境及企业内部环境等综合作用下所期望实现的一种预期性结果,其在确定企业财务管理工作,提高企业整体经济效益与成本控制效率等方面发挥着重要现实性意义。不同财务管理目标其对企业发展的导向作用存在着不同,在分析财务管理目标重要性的基础上,探究不同财务管理目标的差异,提出以利润最大化理财目标相爱企业财务管理的实现策略,以保障企业长期稳定发展,实现其综合效益。