上市公司财务危机预警模型的演变

本文回顾了国内外上市公司财务危机预警模型的发展,介绍、分析了各种财务危机预警模型,包括Z值计分模型、人工神经网络预警等,最后指出了运用现有财务危机预警模型应该注意的问题和进一步深入研究的方向.     

上市公司中长期财务危机预警模型的构建

本文选用2005年被ST的A股上市公司为研究对象,根据行业和总股本规模选择配对样本,运用费雪判别准则,通过实证研究建立三个线性判别函数,以期构建实用有效的中长期预警模型来预测上市公司的财务危机.     

投资者关系管理及其对我国上市公司的启示

投资者关系管理是"通过有效沟通,增强公司价值"的一种机制,它在提高证券市场有效性、改善公司治理机制、促进机构投资者与上市公司的战略对应、维护上市公司形象和市场价值、降低上市公司的资本成本等方面发挥着重要作用,受到发达资本市场上市公司的一贯支持和高度重视.它对于处于发展时期的我国资本市场和上市公司具有很好的借鉴意义.     

基于上市公司财务危机的生存分析

文章引用统计分析方法--生存分析方法来建立财务预警模型.与其他研究不同,文中不仅研究了上市公司财务指标在预警模型中的作用,而且引入了公司治理结构方面的指标以及一些影响企业生产经营环境的宏观变量,试图建立一个综合模型,来探索导致企业产生财务危机的真正因素.研究发现:现金流动负债比率、流动资产周转率以及第三大股东持股比例对上市公司是否进入"ST"具有决定性的作用.     

Analysis of the probability of deletion of S&P 500 companies: Survival analysis and neural networks approach

We examine the probability of deletion of a firm from the S&P 500 index due to a decision of the index committee because the firm did not satisfy the index committee criteria. We study the probability of deletion with survival analysis and neural networks methods. We document that deletion might be predictable, which is contrary to the findings of most studies that the market cannot predict the timing of a company deletion from the S&P 500 index. It might also be beneficial to know ahead of time which company might be deleted from an index, to supplement the arbitrage opportunities that exist already in the announcement-effective date event window.     

Detecting falsified financial statements: a comparative study using multicriteria analysis and multivariate statistical techniques

Falsifying financial statements involves the manipulation of financial accounts by overstating assets, sales and profit, or understating liabilities, expenses or losses. This paper explores the effectiveness of an innovative classification methodology in detecting firms that issue falsified financial statements (FFS) and the identification of the factors associated to FFS. The methodology is based on the concepts of multicriteria decision aid (MCDA) and the application of the UTADIS classification method (UTilités Additives DIScriminantes). A sample of 76 Greek firms (38 with FFS and 38 non-FFS) described over ten financial ratios is used for detecting factors associated with FFS. A jackknife procedure approach is employed for model validation and comparison with multivariate statistical techniques, namely discriminant and logit analysis. The results indicate that the proposed MCDA methodology outperforms traditional statistical techniques which are widely used for FFS detection purposes. Furthermore, the results indicate that the investigation of financial information can be helpful towards the identification of FFS and highlight the importance of financial ratios such as the total debt to total assets ratio, the inventories to sales ratio, the net profit to sales ratio and the sales to total assets ratio.     

Macroeconomic news and the returns of financial companies

This research is concerned with the response of the NASDAQ Financial 100 index to macroeconomic news. The paper employs the newly developed technique of generalized impulse response analysis to examine how macroeconomic shocks affect the performance of the financial sector. The results identify the magnitude and persistence of the response of financial companies stock returns arising from shocks to the stance of monetary policy, real output, inflation, and risk. The findings add to the literature on the determinants of financial sector stocks and on the relationship between the stock market and the macroeconomy. Copyright © 2002 John Wiley & Sons, Ltd.     

上市公司年报审计结果评析

2004年年报审计工作已经结束,与历年相比,非标意见审计报告数量和比例有所回升;非标意见与年报披露日期、盈利水平、是否为ST公司存在明显的相关关系;后任注册会计师保持了应有的执业谨慎;国际"四大"会计师事务所出具的非标意见审计报告少于非"四大".从总体上看,审计意见在定性上基本恰当,但仍有以轻代重的现象.     

The recurrence of financial distress: A survival analysis

Companies often suffer periods of financial distress before filing for bankruptcy. Unlike one-off bankruptcies, financial distress can occur repeatedly within the same individual firm. This paper is focused on the recurrence of financial distress and studies the Chinese stock market, where Special Treatment – an official indicator of financial distress – can be repeatedly applied to a listed company. We employ a stratified hazard model to predict the probability of subsequent distress with variables, including duration dependency, event-based factors, institutional variables, financial ratios, market-based variables and macroeconomic conditions. Our empirical results show that accounting and market-based variables have limited power in predicting the recurrence of distress, whereas the duration of recovery, restructuring events and their interaction terms with the accounting and macroeconomic factors affect the recurrent risk significantly. Tested on out-of-time samples, our proposed hazard models show a robust performance in the prediction of recurrent risk over time.     

An analysis of non-financial factors associated with financial distress

This article examines factors associated with financial distress among 1006 Spanish manufacturings (SMEs), distinguishing high and low technology industries. Financial distress is analysed using industrial organizational theory through the Porter's five competitive forces model (external factors) and the resource based view through strategic variables (internal factors), such as training, planning, innovation, technology and quality. Two different sources of information were used in the study: Qualitative information related to environmental conditions and strategic variables was gathered through a questionnaire addressed to the firm manager. Quantitative information to identify whether the firm was in financial distress was gathered from the balance sheets and earning statements of the firms. Evidence from this study shows that environmental conditions and some strategic variables are associated with financial distress. The results found that young SMEs with low technology and in a highly competitive environment had a higher probability of financial distress. High bargaining power of buyers and high degree of rivalry among existing competitors were positively associated with financial distress. Financial distress in high-technology industries was not affected by external factors. However, firms with a quality certification have better quality control procedures that ultimately improve financial performance of firms in the technology industries.     

财务指标在我国上市公司分析中的作用

通过对资本市场的历史和上市公司财务分析的综述,文章介绍了基本的财务分析方法,以及具体的操作公式,能够运用在日常的分析工作中。     

Financial distress prediction based on SVM and MDA methods: the case of Chinese listed companies

How to accurately predict financial distress is an important issue for enterprise managers, investors, creditors and supervisors. In this paper we develop SVM models (Support Vector Machine) and MDA (Multivariate Discriminant Analysis) models, using Chinese listed companies as our sample. The empirical results show that the prediction ability of SVM models outperforms the MDA models. Additionally, internal governance and external market variables, as well as macroeconomic variables are added as the predictive variables. The results indicate that these variables have theoretical and empirical linkage with the financial distress of Chinese listed companies.     

Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series

In this study, we addressed the problem of point and probabilistic forecasting by describing a blending methodology for machine learning models from the gradient boosted trees and neural networks families. These principles were successfully applied in the recent M5 Competition in both the Accuracy and Uncertainty tracks. The key points of our methodology are: (a) transforming the task into regression on sales for a single day; (b) information-rich feature engineering; (c) creating a diverse set of state-of-the-art machine learning models; and (d) carefully constructing validation sets for model tuning. We show that the diversity of the machine learning models and careful selection of validation examples are most important for the effectiveness of our approach. Forecasting data have an inherent hierarchical structure (12 levels) but none of our proposed solutions exploited the hierarchical scheme. Using the proposed methodology, we ranked within the gold medal range in the Accuracy track and within the prizes in the Uncertainty track. Inference code with pre-trained models are available on GitHub.¹     

Capitalization,population movement,and the local public sector: a probabilistic analysis

Using data collected from household interviews in a 1965 San Francisco Bay Area Transportation Study, a probabilistic model is developed to explain the relationship between population movement and the capitalization of changes in the public sector in the price of housing. This model is constructed to compare 2 competing explanations for the flight of higher income households to the suburbs: 1) the accessibility model and 2) the flight from blight model. The accessibility model explains the decay of cities as a natural outgrowth of decreasing transportation costs, whereas the flight from blight model suggests that the wealthy leave the central city for the suburbs because of urban decay. An analysis of the San Francisco data demonstrates that high income households are more sensitive than the rest of the population to changes in the median income of the neighborhood and in expenditures and general government and education, but less sensitive to changes in property tax rate and expenditures on public safety, parks, and recreation. It is unlikely that undesirable changes in the public sector will result in a mass exodus of higher income households; capitalization in the price of housing appears sufficient to prevent this. The 2 models combined help explain the flight from the central cities, while the combined variables increase the logit estimation's prediction of bids for housing.     

Forecasting exchange rates using feedforward and recurrent neural networks

In this paper we investigate the out-of-sample forecasting ability of feedforward and recurrent neural networks based on empirical foreign exchange rate data. A two-step procedure is proposed to construct suitable networks, in which networks are selected based on the predictive stochastic complexity (PSC) criterion, and the selected networks are estimated using both recursive Newton algorithms and the method of nonlinear least squares. Our results show that PSC is a sensible criterion for selecting networks and for certain exchange rate series, some selected network models have significant market timing ability and/or significantly lower out-of-sample mean squared prediction error relative to the random walk model.     

国内外财务公司比较研究

本文通过对国内外企业财务公司(以下简称"财务公司")在产生背景、客观环境、形成特点以及发挥作用等方面的比较,发现我国财务公司在现阶段存在的主要问题有:监管政策与配套措施不够完善,财务公司整体发展不平衡.笔者认为,促进财务公司健康发展的主要举措是:中央银行需改善财务公司的外部环境,企业集团应重视财务公司作用的发挥,财务公司应努力提高自身素质和水平.     

论我国金融控股公司的模式选择

在全球金融混业浪潮中,金融控股公司成为混业经营首选的组织模式.同时,入世后我国金融业将面临着前所未有的挑战.文中结合美日等国金融业发展状况,提出构建以银行为主体的金融控股公司模式.     

Short and long-run cost efficiency in Indian public bus companies using Data Envelopment Analysis

State Transport Undertakings (STUs) are key players in providing mass road transport in India. Given that they operate under high levels of government imposed regulatory constraints, it is imperative to study their efficiency levels. Given that capital is a relatively scarce resource in developing countries like India, it is important to obtain efficiency in the short-run where some inputs are fixed as well as over the long run, where all inputs are variable. The technique used for capturing efficiency is Data Envelopment Analysis (DEA). A key possible limitation of DEA models based on physical inputs and outputs is that for an inefficient firm, reduction in some or all inputs may be recommended. It may often be desirable for an inefficient firm to increase some less expensive inputs while reducing the use of relatively expensive ones. Hence, when market price data is available, it is advisable to use the cost variant of DEA. Also, it is possible to determine variable cost efficiency in the short run when some inputs cannot be varied. Such inputs are referred to as “quasi-fixed” inputs. In this paper, we examine short and long term efficiencies of select bus companies in India known as State Transport Undertakings (STUs) over a period of 10 years. Fleet strength has been used as the quasi-fixed input. It is possible to ascertain, through a comparison of shadow price of the quasi-fixed input, vis-à-vis its market price, as to whether the quantity of this input is sub-optimally small or large. It is found that by adopting efficiency enhancing practices, STUs can cumulatively reduce their operating costs to the extent of 9123.35 million dollars. Also the tendency to minimize costs is found to be declining over time. In the short run some STUs are found to operate with a sub optimally low fleet size.     

Credit allocation and the financial crisis: evidence from Spanish companies

The worldwide financial crisis of 2007–2008 raised serious concerns about the soundness of banks’ activities and about the extent to which banking regulation should supervise banks’ investment decisions. We contribute to this topic by examining the Spanish case, which has been emblematic of the bubble and burst dynamics in the credit market. In particular, we study the allocation of bank credit among Spanish companies from 1999 to 2014, showing that larger companies accumulated greater amounts of bank loans per unit of total assets, thus leading to a notable concentration. We also find that, during the Spanish boom period, bank loans shifted from the manufacturing to the construction industry, and in particular to the largest companies of the latter sector. This happened in spite of the high leverage of large construction firms, which was increasing also due to their growing debt. We argue that the higher operating benefits, reflecting the increase of the housing price during the boom period, overvalued construction firms as potential borrowers. The bankruptcy of several large construction companies during the Spanish crisis supports the need for monitoring and regulation, to avoid an excessive concentration of bank credit to a few large companies, especially if they belong to a specific sector.

     

上市公司信息披露研究综述

本文从上市公司信息披露动机、信息披露方式、信息披露质量及其经济后果三个角度对国内外有关上市公司信息披露的文献进行了回顾和评析,并针对我国信息披露研究的不足,提出了信息披露的研究方向。