Predicting failure risk using financial ratios: Quantile hazard model approach

This study examines the role of financial ratios in predicting companies’ default risk using the quantile hazard model (QHM) approach and compares its results to the discrete hazard model (DHM). We adopt the LASSO method to select essential predictors among the variables mentioned in the literature. We show the preeminence of our proposed QHM through the fact that it presents a different degree of financial ratios’ effect over various quantile levels. While DHM only confirms the aftermaths of “stock return volatilities” and “total liabilities” and the positive effects of “stock price”, “stock excess return”, and “profitability” on businesses, under high quantile levels QHM is able to supplement “cash and short-term investment to total assets”, “market capitalization”, and “current liabilities ratio” into the list of factors that influence a default. More interestingly, “cash and short-term investment to total assets” and “market capitalization” switch signs in high quantile levels, showing their different influence on companies with different risk levels. We also discover evidence for the distinction of default probability among different industrial sectors. Lastly, our proposed QHM empirically demonstrates improved out-of-sample forecasting performance.     

Adding business value: a strategy for identifying and patenting environment‐related inventions and avoiding patent infringement

For many environmental companies, reaching financial goals is a function of identifying and protecting intellectual property assets, keeping those assets from falling into the hands of competitors and avoiding litigation disputes over the use of those assets. Recognizing that intellectual assets are valuable tangible and intangible assets of a company is the first step in maximizing the value of those assets. However, many environmental companies are not aware that some of their technologies, ideas, concepts and know‐how are potentially patentable and, therefore, fail to maximize the value of those assets by taking advantage of the limited monopolies that patent systems provide to the owners of patents. In the ever‐increasing competitive global market, companies should evaluate their intellectual assets to ensure they are adequately protecting those assets by obtaining patents for ideas that are patentable. As more patents for environmental technologies issue from patent offices around the world, however, the likelihood of infringing one of those patents can increase. Therefore, avoiding infringing others' patents while at the same time identifying and patenting the company's own technologies should be a key business strategy regardless of the size of the environmental company. Copyright © 2003 John Wiley & Sons, Ltd. and ERP Environment     

Demand forecasting and order planning for humanitarian logistics: An empirical assessment

Humanitarian aid organizations are most known for their short-term emergency relief. While getting aid items to those in need can be challenging, long-term projects provide an opportunity for demand planning supported by forecasting methods. Based on standardized consumption data of the Operational Center Amsterdam of Médecins Sans Frontières (MSF-OCA) regarding nineteen longer-term aid projects and over 2000 medical items consumed in 2013, we describe and analyze the forecasting and order planning process. We find that several internal and external factors influence forecast and order planning performance, be it indirectly through demand volatility and safety markup. Moreover, we identify opportunities for further improvement for MSF-OCA, and for humanitarian logistics organizations in general.     

Is bitcoin a safe haven or a hedging asset? Evidence from China

Based on daily data about Bitcoin and six other major financial assets (stocks, commodity futures (commodities), gold, foreign exchange (FX), monetary assets, and bonds) in China from 2013 to 2017, we use a VAR-GARCH-BEKK model to investigate mean and volatility spillover effects between Bitcoin and other major assets and explore whether Bitcoin can be used either as a hedging asset or a safe haven. Our empirical results show that (i) only the monetary market, i.e., the Shanghai Interbank Offered Rate (SHIIBOR) has a mean spillover effect on Bitcoin and (ii) gold, monetary, and bond markets have volatility spillover effects on Bitcoin, while Bitcoin has a volatility spillover effect only on the gold market. We further find that Bitcoin can be hedged against stocks, bonds and SHIBOR and is a safe haven when extreme price changes occur in the monetary market. Our findings provide useful information for investors and portfolio risk managers who have invested or hedged with Bitcoin.     

上市公司风险管理审计研究

按照我国证监会要求,上市公司监事会应当向全体股东负责,保护公司资产安全,降低公司的财务和经营风险。但是,由于股权结构、立法、体制等因素的影响,导致我国上市公司监事会监督失效的现象非常普遍。笔者认为应从法律、上市公司责任意识、监事独立性等方面,增强上市公司监事会的监督作用,允许监事会有权聘请外部审计机构对上市公司的风险管理进行审计。为此,本文分析研究了上市公司风险管理审计的作用、审计步骤及措施。     

Marketing Strategies of Korean MNCs in the US Consumer Electronics Industry

Abstract

This study examines the marketing strategies and management styles of Korean and Japanese multinational corporations in the US consumer electronics industry. Hypotheses are developed with regard to strategic goals and objectives, marketing mix variable emphasis, market orientation and planning focus. The empirical results generally support the research hypotheses that Japanese companies are not only more aggressive in delivering marketing mix but also more-market oriented than Korean counterparts who often base their marketing strategy on short-term profitability rather than long-term market share growth.     

亏损上市公司利用资产减值进行盈余管理的实证研究

本文通过对1999￣2002年度亏损上市公司计提资产减值政策的对比,发现亏损公司在亏损当年计提减值的数额要显著大于未亏损公司;如果公司在第二年扭亏,其在亏损当年计提的数额要显著大于其在扭亏年度的计提数额,而且很多公司在扭亏年度利用资产减值的转回增加当期利润。研究还发现,2001年后上市公司在亏损当年利用资产减值进行盈余管理的动机有增强的趋势。     

Adapting human resource planning in a changing business environment

Contemporary human resource planning (HRP) practice is described on the basis of a survey of 137 companies. Results indicate widespread use of simple forecasting techniques and increased acceptance of HRP during the turbulent 1980s, supporting the notion that HRP adapts to the business environment and has increasingly become a line management process. The forecasting component of HRP was found to serve several functions, the most frequent being developmental. HRP problems have evolved into concerns about the strategic planning role of HRP in the 1990s as opposed to the more technical issues of the past.     

Stability in the inefficient use of forecasting systems: A case study in a supply chain company

Computer-based demand forecasting systems have been widely adopted in supply chain companies, but little research has studied how these systems are actually used in the forecasting process. We report the findings of a case study of demand forecasting in a pharmaceutical company over a 15-year period. At the start of the study, managers believed that they were making extensive use of their forecasting system that was marketed based on the accuracy of its advanced statistical methods. Yet most forecasts were obtained using the system’s facility for judgmentally overriding the automatic statistical forecasts. Carrying out the judgmental interventions involved considerable management effort as part of a sales & operations planning (S&OP) process, yet these often only served to reduce forecast accuracy. This study uses observations of the forecasting process, interviews with participants and data on the accuracy of forecasts to investigate why the managers continued to use non-normative forecasting practices for many years despite the potential economic benefits that could be achieved through change. The reasons for the longevity of these practices are examined both from the perspective of the individual forecaster and the organization as a whole.     

基于超效率DEA和Tobit模型的中国上市煤炭企业经营效率现状分析

本文运用数据包络分析（DEA）方法和Tobit回归模型,首先选取2011年沪深两市具有代表性的18家煤炭上市公司为研究对象,以货币资金、流动资产合计、长期股权投资、固定资产和非流动资产合计为投入变量,主营业务收入、主营业务利润、利润总额为产出变量,运用CCR模型从技术效率、纯技术效率和规模效率等方面对其经营效率进行评价和分析;其次运用超效率DEA模型对CCR模型下DEA有效的决策单元计算其超效率值,从而为所有决策单元提供完整的效率值排序;最后,本文运用Tobit模型,分析影响中国上市煤炭企业经营效率的重要因素,为决策者提供提高企业经营效率的方向和政策。     

造就中国企业界的“中产阶层”

中国经济发展已进入大公司时代。发达国家经验表明,在从工业主导向消费主导的经济转型过程中以大型制造企业为主体的"中产阶层企业"将起到关键作用是否能够持续为员工、股东及其他商业伙伴提供一流的回报,创造出中产阶层占主流的社会结构,促进社会长期和谐发展,大公司的责任尤为重要在垄断产业内,国有企业向民营企业的利益让渡,应成为中国经济深化改革和社会转型的核心政策手段     

A hybrid system-identification method for forecasting telecommunications product demands

A crucial challenge for telecommunications companies is how to forecast changes in demand for specific products over the next 6 to 18 months—the length of a typical short-range capacity-planning and capital-budgeting planning horizon. The problem is especially acute when only short histories of product sales are available. This paper presents a new two-level approach to forecasting demand from short-term data. The lower of the two levels consists of adaptive system-identification algorithms borrowed from signal processing, especially, Hidden Markov Model (HMM) methods [Hidden Markov Models: Estimation and Control (1995) Springer Verlag]. Although they have primarily been used in engineering applications such as automated speech recognition and seismic data processing, HMM techniques also appear to be very promising for predicting probabilities of individual customer behaviors from relatively short samples of recent product-purchasing histories. The upper level of our approach applies a classification tree algorithm to combine information from the lower-level forecasting algorithms. In contrast to other forecast-combination algorithms, such as weighted averaging or Bayesian aggregation formulas, the classification tree approach exploits high-order interactions among error patterns from different predictive systems. It creates a hybrid, forecasting algorithm that out-performs any of the individual algorithms on which it is based. This tree-based approach to hybridizing forecasts provides a new, general way to combine and improve individual forecasts, whether or not they are based on HMM algorithms. The paper concludes with the results of validation tests. These show the power of HMM methods to forecast what individual customers are likely to do next. They also show the gain from classification tree post-processing of the predictions from lower-level forecasts. In essence, these techniques enhance the limited techniques available for new product forecasting.     

Modeling the unintended consequences of short selling for innovation investment

We develop an innovation investment decision model for firms facing a short selling threat. We find that an endogenous agency problem may arise as an unintended consequence of short selling under the prevailing compensation structure. Specifically, the manager has strong incentives to seek better compensation at the expense of decreasing firm value by reducing long-term innovation investment to save cash reserves to protect the short-term price because the manager’s compensation is closely tied to this value. Finally, our model predicts that both the lending supply and short selling will induce the manager to underinvest and have a negative effect on firm value and the manager’s private benefit because they exacerbate agency conflicts.     

Text-based crude oil price forecasting: A deep learning approach

This study proposes a new, novel crude oil price forecasting method based on online media text mining, with the aim of capturing the more immediate market antecedents of price fluctuations. Specifically, this is an early attempt to apply deep learning techniques to crude oil forecasting, and to extract hidden patterns within online news media using a convolutional neural network (CNN). While the news-text sentiment features and the features extracted by the CNN model reveal significant relationships with the price change, they need to be grouped according to their topics in the price forecasting in order to obtain a greater forecasting accuracy. This study further proposes a feature grouping method based on the Latent Dirichlet Allocation (LDA) topic model for distinguishing effects from various online news topics. Optimized input variable combination is constructed using lag order selection and feature selection methods. Our empirical results suggest that the proposed topic-sentiment synthesis forecasting models perform better than the older benchmark models. In addition, text features and financial features are shown to be complementary in producing more accurate crude oil price forecasts.     

品牌权益影响上市公司赢利水平的实证研究

品牌权益是公司一项重要的无形资产,也是公司重要的竞争优势;营业润是上市公司利润总额的主要来源,能够比较恰当地反映公司管理层的经营业绩。选取营业利润作为衡量公司赢利水平的主要指标,研究建设品牌能为企业带来的效用,即:在总体市场情况下,品牌权益对企业赢利水平的提高具有正向的促进作用;在不同行业条件下,品牌权益对企业赢利水平的影响效果有所不同。     

Government-Owned Businesses: Market Presence, Competitive Advantages and Rationales for Their Support by the State

A bstract . In the aggregate, within industries and within non-socialist countries, the market presence of State-owned businesses is large and growing. Such concerns accounted for 15 percent of world trade in 1979 and they produced 70 percent of world oil production , 40 percent of world iron and bauxite and they accounted for 40 percent of the world's banking assets. Certain governments tend to accord them competitive advantages. Reasons given for doing so range from the belief that they foster economic growth and employment , that they equalize the domestic businesses' power to compete with big multinational companies , that they make national planning possible, to the idea that government favor should not go to benefit private owners , even domestic ones, and that the country, rather than the corporation, is the relevant unit of competition.     

融资时机选择与资本结构变动——基于中国上市公司的研究

利用市场时机选择理论,以中国A股市场进行配股和增发的上市公司作为研究样本,对上市公司在配股和增发过程中是否存在着融资时机选择行为以及这种行为对公司的资本结构是否造成持续的影响进行检验,结果表明上市公司存在着股权融资时机选择的行为,这种行为在短期内影响了公司的资本结构,但对公司长期的资本结构没有显著的持续影响。     

Forecasting the US housing market

The recent housing market boom and bust in the United States illustrates that real estate returns are characterized by short-term positive serial correlation and long-term mean reversion to fundamental values. We develop an econometric model that includes these two components, but with weights that vary dynamically through time depending on recent forecasting performances. The smooth transition weighting mechanism can assign more weight to positive serial correlation in boom times, and more weight to reversal to fundamental values during downturns. We estimate the model with US national house price index data. In-sample, the switching mechanism significantly improves the fit of the model. In an out-of-sample forecasting assessment the model performs better than competing benchmark models.     

老字号企业无形资产对经营绩效影响的实证研究

以在我国沪深两市2007年—2009年发行A股的24家老字号上市公司为研究样本,考察样本公司无形资产的发展状况,并运用线性回归分析法检验无形资产对经营绩效的影响。试图分析无形资产在我国老字号上市公司经营活动中所起的作用,改进我国老字号企业的绩效实现途径。研究结果发现:无形资产对老字号企业的经营活动发挥了一定的贡献,老字号上市公司披露的无形资产对企业经营绩效的贡献是显著的正向的,但贡献的程度较小。即样本公司拥有的无形资产越多,公司的经营绩效越多,但是无形资产的变化引起绩效变化的程度较小。在此基础上,提出了针对性的建议。     

Long-Term or Short-Term Managerial Incentive Contracts

This paper deals with the strategic role of the temporal dimension of contracts in a duopoly market. Is it better for a firm to sign long-term incentive contracts with managers or short-term contracts? For the linear case, with strategic substitutes (complements) in the product market, the incentive variables are also strategic substitutes (complements). It is shown that a long-term contract makes a firm a leader in incentives, while a short-term contract makes it a follower. We find that, under Bertrand competition, in equilibrium one firm signs a long-term contract and the other firm short-term incentive contracts; however, under Cournot competition, the dominant strategy is to sign long-term incentive contracts.