上市公司财务危机预警的实证研究

以是否被特别处理为财务危机标志,利用我国上市公司近几年的年报财务数据,选取了财务危机和健康企业各50家作为开发样本.首先研究了开发样本财务指标的数据特征和财务危机出现前3年内这两类企业的财务指标的显著性差异,其后利用因子分析法筛选了8个指标作为建立模型的自变量,运用Logistic模型构建了上市公司财务危机预测模型,并对估计样本的40家企业进行了检验.实证分析结果表明:其一,我国上市公司财务比率不服从正态分布;其二,尽管我国资本市场的会计数据质量不尽人意,但财务数据仍具有一定的信息含量;其三,利用开发样本构建的Logistic模型在财务危机发生前1年和前2年有比较高回判准确率,估计样本在财务危机发生前1年和前2年有比较高的预测准确率.     

终极股东超额控制下公司治理环境与股权结构的价值效应研究

公司治理环境和股权结构分别是从公司外部宏观层面和内部微观层面影响公司价值的两类主要因素。在上市公司终极股东普遍存在超额控制权的现实背景下,本文基于终极股东超额控制权中介效应的视角,利用中国上市公司的大样本经验数据和结构方程模型的数理统计方法,实证研究了公司治理环境和股权结构对公司价值的影响机制。研究发现,终极股东的超额控制权会显著损害上市公司价值;公司治理环境和股权制衡基本不具有直接的价值创造效应,但可以通过抑制终极股东的超额控制权进而间接具有价值创造效应;股权集中具有显著的直接价值创造效应,虽然股权集中会促进终极股东的超额控制权从而具有间接的价值损害效应,但大股东与上市公司的利益趋同大于对上市公司的利益侵占,使得股权集中的总价值效应仍表现为价值创造效应。结论表明,通过遏制终极股东的超额控制权,能够有效实现公司治理环境和股权结构的价值创造功能。     

我国上市公司财务状况的非线性主成分分析研究

文章通过对我国上市公司的财务指标进行综合分析 ,构建了我国上市公司财务状况综合分析的非线性主成分分析模型 ,并应用该模型对上市公司财务状况进行了合理的评价 .     

基于财务指标的股票间关联网络结构特征研究

目前关于股票间关联网络结构特征的研究,主要是基于股票价格时间序列间相关关系构建复杂网络.然而,股价只是衡量股票优劣的外在因素,财务指标更能全面地刻画上市公司的运行情况,反映股票背后的经济实力.因此,以中国74家能源上市公司的财务指标为样本,结合复杂网络理论,构建不同阈值下的股票间关联网络,进行结构特征分析.发现,服务类型的股票在网络中影响较大,社团化趋势显著等.     

上市公司资本运营绩效评价及实证研究

从资本运营的角度对上市公司经营绩效进行评价,由于以股价变动为基础的反常收益评估法不适用于我国现实情况,采用以财务指标为基础的评价体系并通过因子分析法构造评价企业并购绩效的综合函数,对上市公司并购前后的业绩情况进行对比;并据此对中国石油天然气股份有限公司2005年并购事件的绩效进行了评价分析.在此基础上,提出一套引入非财务指标定性定量相结合的综合指标评价体系.     

上市公司控制权转移的演化博弈分析

在演化博弈理论的框架下建立了控制权转移的接管机制模型.在具有不完全信息的控制权市场,将控制权争夺的参与者分为两个群体:接管者(进入者)群体和管理者(在位者)群体,他们随机配对进行不对称两人博弈.接管者选择进入和不进入且其特性有强、弱之分,在位者选择合作和抵制.通过建立复制者动态模型并对其均衡点进行分析,得到了控制权转移的路径及接管者与管理者的最优策略.     

基于GA-RS-LR算法的公司财务与个股投资探究

运用遗传算法-粗糙集-逻辑回归方法(GA-RS-LR)探讨我国A股上市公司财务与股票收益的关系.运用GA-RS方法获得财务指标最优约简;运用LR模型探求两者关系.最终,经GA-RS约简,60个财务指标中有17个对股票投资有重要影响;通过LR模型,4个指标具有显著效应;其中,负债与权益市价比为5.82%负效应,其余为正效应.对2015年股票相对波动进行预测得到70%的准确率,验证了GARS-LR模型对中长期投资的有效性.     

基于因子分析的旅游上市公司经营绩效评价研究

为了对旅游上市公司进行更加合理的评价和突出现金流的重要性,在财务指标体系的基础上构建了一个包含偿债能力、营运能力、盈利能力、发展能力和现金流五个方面的旅游上市公司经营绩效评价体系.以沪深上市的20家旅游上市公司2008-2015年的数据为研究样本,用因子分析法对旅游上市公司的经营绩效进行评价和排名.研究发现旅游上市公司经营绩效存在较大的提升空间,建议旅游上市公司从产业链整合、业务多元化、新增投资等三个途径来提高企业的经营绩效.     

一种利用Pls提取因子的财务危机预警模型

为了克服直接使用财务指标建立Logit模型存在的估计和检验不可靠问题,在所有的财务比率指标基础上,通过删除完全共线、意义相同和缺失数据指标,建立海选指标集.利用t检验筛选指标,删除t检验不显著的指标,保留t检验显著的指标,构建财务危机预警指标体系.通过提取互不相关的Pls因子,估计Pls-logit模型对因子赋权.将Pls因子回归代入Pls-logit模型对指标赋权,建立基于Pls-logit模型的财务危机预警模型.以2010年381家制造业上市公司作为建模样本进行了实证分析,表明Pls-logit模型中31个系数在5%的显著性水平下显著,说明建立的财务预警指标体系能够显著解释财务危机.以2010年和2011年随机抽取的制造业公司为检验样本进行回溯检验,检验结果表明预警总准确率达到91.7%以上.2010年危机预警准确率为66.7%;2011年危机预警率为100%.Pls-logit模型的总体预警准确率明显优于财务指标logit模型.     

基于DEA-Malmquist和Tobit regression的物联网上市公司效率评价

物联网的发展已经成为我国实现经济转型的有力支撑,但其发展过程中呈现的波动性问题仍亟需深入研究.从效率的角度,对我国19家物联网公司的发展状况进行了研究.首先,运用DEA模型测算了19家公司2013-2015年的技术效率、纯技术效率、规模效率以及各公司的规模收益状况.计算结果表明物联网上市公司的效率在整体上呈现上升趋势,只有同方股份在三年内规模收益状况为递减.其次,运用DEA-Malmquist测算了19家公司的技术效率变化指数、技术进步指数、纯技术效率变化指数、规模效率变化指数和全要素生产率变化指数.结果表明,技术进步指数低是制约这19家公司生产力发展的关键问题.最后,运用Tobit regression分析了11项财务指标对技术效率、纯技术效率以及规模效率影响的显著性,得出财务指标对规模效率存在显著影响.基于效率和影响因素分析的实际,为物联网上市公司的发展提供合理的建议,推动我国物联网产业实现良性有序发展.     

基于双风险因子调整的剩余收益经营与投资最优决策模型

一般来说,公司净资产基于投向可以分为净经营性资产和净金融性资产。这两种净资产所面临的风险属性是不同的,净经营性资产承担的是经营性风险,而净金融性资产承担的则是金融性风险。作为公司多元化经营的决策者,在公司净资产一定的情况下,如何合理分配经营性投资与金融性投资间的比例并作出最优的投资决策,以达到公司价值最大化？本文基于一般形式的三阶段剩余收益模型,根据净经营性资产具有经营风险,净金融性资产则具有金融风险的风险识别与判断,从理论上构建出双风险因子调整的剩余收益经营与投资决策模型(Operation and Investment Decision Model of Dual-risks RIM, OIDM-DRRIM)。同时,利用中国资本市场1997年到2014年的经验数据进行实证检验,研究结果表明,所构建的OIDM-DRRIM具有非常好的适用性,公司经营决策者可以根据该模型计算出净经营性资产和净金融性资产之间的最优分配比例,进而作出使公司价值最大化的经营与投资决策。     

Prediction of financial distress: An empirical study of listed Chinese companies using data mining

The deterioration in profitability of listed companies not only threatens the interests of the enterprise and internal staff, but also makes investors face significant financial loss. It is important to establish an effective early warning system for prediction of financial crisis for better corporate governance. This paper studies the phenomenon of financial distress for 107 Chinese companies that received the label ‘special treatment’ from 2001 to 2008 by the Shanghai Stock Exchange and the Shenzhen Stock Exchange. We use data mining techniques to build financial distress warning models based on 31 financial indicators and three different time windows by comparing these 107 firms to a control group of firms. We observe that the performance of neural networks is more accurate than other classifiers, such as decision trees and support vector machines, as well as an ensemble of multiple classifiers combined using majority voting. An important contribution of the paper is to discover that financial indicators, such as net profit margin of total assets, return on total assets, earnings per share, and cash flow per share, play an important role in prediction of deterioration in profitability. This paper provides a suitable method for prediction of financial distress for listed companies in China.     

A multidimensional knapsack model for asset-backed securitization

Securitization is a financial operation which allows a financial institution to transform financial assets, for instance mortgage assets or lease contracts, into marketable securities. We focus the analysis on a real case of a bank for the leasing. Once the securitization characteristics, such as size and times of the operation, have been defined, the profit for the financial institution—Italease Bank for the Leasing in our case—depends on how the financial assets to use in the securitization are selected. We show that the selection problem can be modelled as a multidimensional knapsack problem (MDKP). Some formal arguments suggest that there may exist a prevailing constraint in the MDKP. Such an idea is used in the design of some simple heuristics which turn out to be very effective.     

Distributionally robust profit opportunities

This paper expands the notion of robust profit opportunities in financial markets to incorporate distributional ambiguity using Wasserstein distance as the ambiguity measure. Financial markets with risky and risk-free assets are considered. The infinite dimensional primal problems are formulated, leading to their simpler finite dimensional dual problems. A principal motivating question is how distributional ambiguity helps or hurts the robustness of the profit opportunity. Towards answering this question, some theory is developed and computational experiments are conducted. Finally some open questions and suggestions for future research are discussed.     

Multivariate option pricing using copulae

The complexity of financial products significantly increased in the past 10 years. In this paper, we investigate the pricing of basket options and more generally of complex exotic contracts depending on multiple indices. Our approach assumes that the underlying assets evolve as dependent GARCH(1, 1) processes. The dependence among the assets is modeled using a copula based on pair‐copula constructions. Unlike most previous studies on this topic, we do not assume that the dependence observed between historical asset prices is similar to the dependence under the risk‐neutral probability. The method is illustrated with US market data on basket options written on two or three international indices. Copyright © 2012 John Wiley & Sons, Ltd.     

A simulation study of IT outsourcing in the credit card business

The use of Monte Carlo simulation for evaluation of financial risk of an information technology project selection decision is described. A major Thai bank considered the opportunity to expand credit card operations through information technology (IT). Alternatives considered were in-house development and outsourcing. There were many strategic reasons for the initiative. However, there were also many risks associated with the proposal. A Monte Carlo simulation spreadsheet model was used to model risk parameters, and to analyze key performance variables of financial performance. Key output variables were the number of cardholders expected, project net present value, net profit, and expected return on investment. The spreadsheet model made entry of model elements transparent, and Monte Carlo simulation provided clear visual display of the financial output variables. The bank used this information in its decision to outsource its credit card operations.     

Closed-loop supply chain network design: A financial approach

The more common approaches used in the SCM consider only the physical logistic operations and ignore the financial aspects of the chain. This paper presents a financial approach to model a closed-loop supply chain design in which financial aspects are explicitly considered as exogenous variables. The model decides to determine the strategic decisions as well as the tactical decisions. The main contribution of this paper is to incorporate the financial aspects (i.e. current and fixed assets and liabilities) and a set of budgetary constraints representing balances of cash, debt, securities, payment delays, and discounts in the supply chain planning. Moreover, the financial approach applies the change in equity (instead of the measure of profit/cost in traditional approaches) as the objective function to be optimized in the presented model.To show the advantages of the presented approach, the results attributed to the financial approach and the traditional approach are compared, where the latter firstly decides on operations and fits finances afterwards. The results indicate that the traditional approach leads to lower change in equity compared to the financial approach. This fact illustrates the inadequacy of treating process operations and finances in isolated environments and pursuing as objective myopic performance indicators such as profit or cost. Moreover, a sensitivity analysis of the parameters using ANOVA for different levels of the parameters under different customer order patterns is performed to enhance the managerial insights of the study. The results clearly reveal the better improvement of using the financial approach over the traditional approach, and convince the decision makers to take advantage of the proposed approach.     

基于动态利率风险免疫的银行资产负债优化模型

本文以CIR动态久期缺口的免疫条件为约束进行多资产和多负债的利率风险控制,通过建立线性规划模型来进行银行资产的最优配置。本文的创新与特色:一是通过引进随时间变化的动态利率久期参数构造利率风险控制条件,建立了控制利率风险的资产负债优化模型。改变了现有研究忽略利率动态变化、进而忽略平均久期动态变化的弊端。事实上,利率的动态变化必然引起平均久期的变动,忽略利率变动的控制条件是无法高精度地控制资产配置的利率风险的。二是通过以银行资产收益最大为目标函数,以动态利率久期缺口免疫为主要约束条件,辅以监管的流动性约束匹配银行的资产负债,回避了利率风险对银行所有者权益的影响,避免了利率变动对银行资产所有者带来的损害。     

基于随机久期利率免疫的银行资产负债优化模型

银行资产负债管理是指商业银行在负债数量和结构一定的条件下、对资产进行优化配置,通过平衡资产的流动性、盈利性和安全性,以实现银行收益的最大化。本文通过Vasicek动态期限结构模型推导出随机久期,以包括存量与增量在内的全部资产随机久期等于全部负债随机久期为约束条件、控制利率风险,辅以现行法律法规等其他约束条件,建立全部资产负债组合的随机久期利率风险免疫模型,并通过算例说明本模型构建过程。本文的创新与特色有三:一是通过建立全部资产负债组合的利率免疫条件,对包括存量与增量在内的全部资产组合利率风险进行控制。改变了现有研究在进行资产配置时,仅对增量组合风险控制的弊端。二是通过资产负债的随机久期缺口等于0的利率风险免疫条件建立资产负债优化模型,确保在利率发生变化时,银行股东的所有者权益不受损失。三是以银行各项资产组合收益率最大化为目标函数,通过随机久期的利率免疫条件控制利率风险,建立了全部资产负债组合的随机久期利率风险免疫模型。改变了现有研究的资产负债管理模型忽略随机久期变动的影响。