独立审计意见对上市公司盈余管理影响的比较静态分析——来自上市公司截面经验研究的证据

独立审计意见对盈余管理的净影响分别大于其与规模和当期损失交叉对盈余管理的混合影响;公司规模与独立审计意见对盈余管理的影响具有显著关联性;当公司发生损失情形下,独立审计意见具有影响,但是其影响受到损失情形的制约.     

基于混合所有制发展模式的国有资产流失风险防范策略探讨

混合所有制因以实现资本协作共赢和包容性发展而获得了众多专家学者的推崇,但在现实操作中却面临种种难题.本文着重探讨国有企业发展混合所有制经济模式时,所应采取的科学机制和策略,实现各利益相关方在积极合作、共存共赢共发展的基础上,有效识别并防范国有资产流失风险.     

远程协同监管 我国政府采购项目监管的现实选择

长期以来,各行业部门机构和专业部门机构建立了各自独立的纵向垂直职能监管系统。从监管对象层面看,各部门的监督管理机构分兵把口,各管一摊,监管职能分散,不能形成监管合力。各监管主体职能交叉重叠,形成条块分割,多头重复监管,职责不清,增加了各监管手段之间的协调难度。而解决上述问题的根本出路是建立政府采购项目的协同监管,实现从分散采集、各自为政、交叉重叠的多元独立监管体系向集中监测、分布处理、结果导向、多元协同的统一监管体系转变。     

有噪复杂度寻踪的新算法

复杂度寻踪是投影寻踪向时间序列数据,即具有时间结构信号的扩展.该方法是和具有时间依赖特性的源信号的盲分离和独立成分分析紧密联系的.在源信号是具有时间依赖特性和存在高斯噪声的情况下,现有的有噪复杂度寻踪算法没有给出自回归系数的估计方法,影响了算法的实际应用,提出了有噪复杂度寻踪的新算法,该算法给出了自回归系数的估计方法.对自然图像和人工信号的仿真表明了提出算法的有效性,和现有的肓源分离算法相比较,提出算法具有好的信号分离性能.     

影响独立董事制度有效性分析及其完善探讨

独立董事制度是完善我国上市公司治理结构的一项重要举措,本文从内部因素和外部环境两个方面分析了独立董事制度的有效性.并从制度建设的角度出发,时独立董事的独立性、选聘机制等方面对完善我国上市公司独立董事制度进行了探讨.     

商业银行渠道交叉营销管理模式研究

渠道交叉营销管理是西方国家银行业提升核心竞争力的主要手段.随着金融市场竞争的加剧,国内商业银行越来越重视渠道交叉营销.我国四大商业银行近几年对渠道交叉营销管理进行了初步探索,但仍然存在诸多制约因素.推行渠道交叉营销管理是一项复杂的系统工程,商业银行需坚持"以客户为中心"的基本原则,进一步整合渠道资源要素,对各分渠道进行...     

交叉销售与价值创新——商业银行零售业务发展战略中的蓝海

本文提出以价值创新为视角，实施以客户为中心的交叉销售，通过差异化和成本领先，达到银行和客户价值的双重提升，实现价值创新，从而开辟竞争中的“蓝海”。本文分析了中国零售银行业务实施交叉销售以及价值创新的可行性，提出顾客盈利性分析是实现交叉销售目的的关键，并从目标顾客识别、销售产品识别、销售时间识别、营销关键点识别四个方面提出交叉销售实施和改进的具体策略。     

房地产上市公司财务状况分析

本文随机选取深沪上市的40家房地产公司,根据公司的财务数据,对公司的财务状况进行评价分析.通过运用主成分分析的方法,本文从企业的获利能力、营运能力、偿债能力、投资报酬能力和成长能力五个方面选取少数几个彼此独立不相关的指标来替代较多的指标,通过分析,综合这五个方面的影响,得到各企业的综合能力得分,运用主成分分析方法对企业的综合能力做一个定量分析.     

完善风险识别与预防机制

依据信贷风险的形成、控制、处置流程特征,初始风险的形成,隐藏较深、分布分散,难以识别、揭露、发现,需创新风险识别方式,强化初始风险的事前监管,把好风险准入关。1.开展多方式、多层次的贷前外围调查,在营销的前端识别风险。贷前调查,位于风险识别的最前端,独立、真实、全面     

2001年度科技型中小企业重点项目指南

6.移动通信基站功率混合设备功率混合设备是移动通信基站必不可少的部分,功能是将多个不同频率的大信号功率以低插入损耗混合在一条传输线上,要求各频率之间有足够的隔离度,谐振器件具备优良的频率温度系数.目前技术发展趋势是设备体积缩小、频率间隔减小,远程遥控频率调整等.     

Cryptocurrency price prediction using traditional statistical and machine-learning techniques: A survey

Cryptocurrencies are decentralized electronic counterparts of government-issued money. The first and best-known cryptocurrency example is bitcoin. Cryptocurrencies are used to make transactions anonymously and securely over the internet. The decentralization behavior of a cryptocurrency has radically reduced central control over them, thereby influencing international trade and relations. Wide fluctuations in cryptocurrency prices motivate the urgent requirement for an accurate model to predict its price. Cryptocurrency price prediction is one of the trending areas among researchers. Research work in this field uses traditional statistical and machine-learning techniques, such as Bayesian regression, logistic regression, linear regression, support vector machine, artificial neural network, deep learning, and reinforcement learning. No seasonal effects exist in cryptocurrency, making it hard to predict using a statistical approach. Traditional statistical methods, although simple to implement and interpret, require a lot of statistical assumptions that could be unrealistic, leaving machine learning as the best technology in this field, being capable of predicting price based on experience. This article provides a comprehensive summary of the previous studies in the field of cryptocurrency price prediction from 2010 to 2020. The discussion presented in this article will help researchers to fill the gap in existing studies and gain more future insight.     

The unsung impact of currency risk on the performance of international real property investment

The paper revisits the currency risk debate to ascertain the statistical significance of currency risk on the return of international real property investment, especially in a period of increased exchange rate volatility. After statistical analyses of the returns of a portfolio of office investments in seven Asia Pacific cities over the 1986 to 2007 period, it was found that currency risk had a statistically significant positive impact on the performance of the portfolio of office investments. This is confirmed by the results of stochastic dominance test. If the results of this study are verified by subsequent studies, and the past reliably presages the future, they would imply that investors holding portfolios of real property investments in the sample markets might not need to be unduly concerned with currency risk.     

Grey Relational Analysis and Neural Network Forecasting of REIT returns

This study employs the Grey Relational Analysis (GRA) and Artificial Neural Network (ANN) to measure the impact of key elements on the forecasting performance of real estate investment trust (REIT) returns. To manage risks from a real estate price bubble, the findings of GRA suggest that the REIT is best influenced by industrial production index, lending rate, dividend yield, stock index and its own lagged performance. Consequently, this paper adjusts the parameters from GRA and inserts the key elements into the fitted ANN model by comparing the learning effect of the Back-propagation Neural Network (BPN). This study found that the ranking provided by the GRA is significant in correcting prediction errors using the learning outcome of the BPN. The neural network model proved to minimize error function and was able to adjust weighted values in order to enhance prediction accuracy.     

Ratio Analysis Using Rank Transformation

This paper presents an alternate method for transforming financial ratios. Ratios are ranked and scaled into a uniform distribution with boundaries between 0 and 1. Conceptually, we suggest that this method solves a number of methodological problems associated with ratios, including constrained choice of regression models, ratio outliers, negative ratios, and non-normal distributions. Scaled ranks of financial ratios are also conceptually appealing because they appear to capture comparative ordinal data about cross-sectional relationships between firms.The study empirically tests scaled rank transformations by examining the association of the transformations with stock returns. Results show that models using relative ranked accounting ratios have more explanatory and predictive power than untransformed, log-transformed and square-root transformed ratios.     

Central bank digital currency and the effectiveness of negative interest rate policy: A DSGE analysis

Implementing a negative interest rate policy (NIRP) in the traditional fiat system is less effective than desired because of the zero lower bound (ZLB) constraint on interest rates and the cash barrier. Would this problem be solved if a new form of currency was introduced, i.e., central bank digital currency (CBDC), in the economy? To answer this question, we construct a dynamic stochastic general equilibrium (DSGE) model to analyze the effectiveness of NIRP upon the introduction of CBDC. The results suggest that: (i) The CBDC can eliminate the ZLB constraint and stabilize the economic fluctuations caused by NIRP. (ii) The central bank can implement NIRP by directly adjusting the interest rate of digital currency to stimulate consumption, investment, and output and to accelerate macroeconomic recovery. (iii) Welfare analysis shows that the central bank can effectively choose different NIRP rules according to the economic objectives.     

中国贸易条件变动趋势分析——基于1993-2017年月度数据的研究

基于1993-2017年月度数据研究发现:中国三大贸易条件指数(2010=100)中价格贸易条件上下波动明显,标准差为6.0;收入贸易条件长期稳步上升,近三年相对于最高点下降了15%~20%;要素贸易条件一直呈上升趋势,标准差为66.2.人民币汇率一次性大幅度变动时,中国价格贸易条件有显著变动.人民币显著升值时,价格贸易条件马上明显改善,但维持时间不长,随后又发生逆转.人民币一次性大幅度贬值导致价格贸易条件长期恶化有一定的时滞.国外发生经济或金融危机而中国宏观经济较稳定发展期间,中国价格贸易条件改善.为此,我国应积极推动人民币汇率向均衡汇率靠拢,针对性地采取限产计划,以提升国际分工地位,从根本上改善贸易条件和增加经济福利.     

Takeover bids, unconditional offer price and investor protection

In this paper, we develop a contingent claim analysis on shareholders' right to sell unconditionally their shares at the acquisition bid price during a takeover bid procedure. Compared with a situation without any guarantee, this regulation brings about wealth transfer towards outside shareholders. Why, in an apparently irrational way, do outside shareholders, who may benefit from a price guarantee, not systematically sell their shares? That question emphasizes the outside shareholders' behavior. Using a real option valuation model to evaluate the price guarantee opportunity, we show that an equal treatment rule between controlling and outside shareholders may lead outside shareholders to sell their shares.     

A Pricing and Hedging Comparison of Parametric and Nonparametric Approaches for American Index Options

This article investigates the extent to which options on theAustralian Stock Price Index can be explained by parametricand nonparametric option pricing techniques. In particular,comparisons are made of out-of-sample option pricing performanceand hedging performance. The dataset differs from many of thoseused previously in the empirical options pricing literaturein that it consists of American options. In addition, a broaderspectrum of techniques are considered: a spline-based nonparametrictechnique is considered in addition to the standard kernel techniques,while the performance of a Heston stochastic volatility modelis also considered. Although some evidence is found of superiorperformance by nonparametric techniques for in-sample pricing,the parametric methods exhibit a markedly better ability toexplain future prices and show superior hedging performance.     

The link between the current international monetary non-system,financialization and the Washington consensus

The main purpose of the present work is to build a bridge between three concepts: the current international monetary system, financialization and the Washington consensus. Under this approach, the current international monetary non-system (that replaced the Bretton Woods system) imposed by Nixon in 1971 led to the oil shocks that in turn intensified the inflationary pressures of the rest of the decade. The bold resolution to end inflation in 1979 via high interest rates brought about a process of financialization that was cause and consequence of trade and financial liberalization. Interest rates eventually went back to levels comparable to those prevailing before the Volcker shock, which brought about a decline in firms’ demand for credit that obliged banks to seek for other clients, i.e. the rest of the world and households. The ideas embedded in the Washington consensus contributed to the development of this financialization/liberalization process, and these gained strength as the previous regime (characterized by low unemployment rates and high inflation) was being replaced by the current regime paradoxically called the ‘Great Moderation’. The process of financialization can be explained by the analysis of the capital structure of U.S. firms.     

Controllers’ role in managerial sensemaking and information trust building in a business intelligence environment

This study explores how an organization’s controllers (management accountants) give sense to the information provided by its business intelligence (BI) system, and thus shape the construction of information trust. A qualitative case study was conducted within a Finnish food manufacturing company, building on the notion of trust related to management accounting information and sensemaking theory. The study was informed through open-ended interviews and an examination of internal accounting and management reports. The authors found that the company used an integrated BI system that enabled the production of information in a timely and perceivably standardized manner. Controllers managed this accounting information and gave sense to it, helping deliver a shared understanding of the daily business situation. The findings show that controllers play a pivotal role in building information trust by giving sense to the information provided by the BI system.