从物流金融发展的视角议企业、银行、物流三方共赢

在经济大背景下,物流金融作为一种新兴的金融创新产品,在物流产业市场中需求旺盛,物流金融为金融机构、供应链企业、第三方物流服务提供商之间提供了良好的发展平台,主要从物流金融发展的视角对融资企业、商业银行、物流企业三方共赢的问题进行简要分析,更好地促进企业、银行、物流三方和谐发展。     

Computing systemic risk using multiple behavioral and keystone networks: The emergence of a crisis in primate societies and banks

What do the behavior of monkeys in captivity and the financial system have in common? The nodes in such social systems relate to each other through multiple and keystone networks, not just one network. Each network in the system has its own topology, and the interactions among the system’s networks change over time. In such systems, the lead into a crisis appears to be characterized by a decoupling of the networks from the keystone network. This decoupling can also be seen in the crumbling of the keystone’s power structure toward a more horizontal hierarchy. This paper develops nonparametric methods for describing the joint model of the latent architecture of interconnected networks in order to describe this process of decoupling, and hence provide an early warning system of an impending crisis.     

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.     

Personalised news filtering and recommendation system using Chi-square statistics-based K-nearest neighbour (χ2SB-KNN) model

Recommendation problem has been extensively studied by researchers in the field of data mining, database and information retrieval. This study presents the design and realisation of an automated, personalised news recommendations system based on Chi-square statistics-based K-nearest neighbour (χ²SB-KNN) model. The proposed χ²SB-KNN model has the potential to overcome computational complexity and information overloading problems, reduces runtime and speeds up execution process through the use of critical value of χ² distribution. The proposed recommendation engine can alleviate scalability challenges through combined online pattern discovery and pattern matching for real-time recommendations. This work also showcases the development of a novel method of feature selection referred to as Data Discretisation-Based feature selection method. This is used for selecting the best features for the proposed χ²SB-KNN algorithm at the preprocessing stage of the classification procedures. The implementation of the proposed χ²SB-KNN model is achieved through the use of a developed in-house Java program on an experimental website called OUC newsreaders’ website. Finally, we compared the performance of our system with two baseline methods which are traditional Euclidean distance K-nearest neighbour and Naive Bayesian techniques. The result shows a significant improvement of our method over the baseline methods studied.     

我国商业银行与创业投资的投贷联动模式研究

金融创新是商业银行核心竞争力的重要来源。近年来创业投资行业发展迅猛,但较之美国等创业投资发达的国家,我国商业银行对创业投资的参与相对有限,与创业投资相关的业务创新缺乏。我国商业银行应借鉴美国硅谷银行投贷联动模式,建立健全创业企业信用担保体系、丰富与创业投资公司的合作模式、建立专业行业金融团队、完善增值服务体系,通过金融创新实现商业银行与创业投资的双赢。     

Forecasting election results by studying brand importance in online news

This study uses the semantic brand score, a novel measure of brand importance in big textual data, to forecast elections based on online news. About 35,000 online news articles were transformed into networks of co-occurring words and analyzed by combining methods and tools from social network analysis and text mining. Forecasts made for four voting events in Italy provided consistent results across different voting systems: a general election, a referendum, and a municipal election in two rounds. This work contributes to the research on electoral forecasting by focusing on predictions based on online big data; it offers new perspectives regarding the textual analysis of online news through a methodology which is relatively fast and easy to apply. This study also suggests the existence of a link between the brand importance of political candidates and parties and electoral results.     

我国城市商业银行市场定位问题——基于金融共生理论的研究

市场定位是商业银行发展战略的永恒主题,现阶段我国城市商业银行客户定位"缺"位和区域定位"错"位的战略缺陷以及发展困境,主要在于城市商业银行与政府、企业、居民、银行同业间金融共生关系的不和谐性。依据金融共生理论,城市商业银行的正确定位依托于和谐有序的金融共生界面,实现其内涵可持续发展,提高对地区经济的贡献度,就需要综合考虑并合理平衡金融共生体内各要素的利益,从制度层面引导其正确定位于中小企业和本土社区。     

我国商业银行中间业务发展存在问题及其对策研究

中间业务经营成本低、风险小、收益高,因而得到迅速发展。伴随着我国金融体系的完善与全球金融一体化进程的进一步加快,我国商业银行面临的竞争将空前剧烈,因而大力发展中间业务是我国商业银行的必然选择。通过对我国商业银行中间业务存在问题进行分析,针对性地提出了发展我国商业银行中间业务的若干对策。     

我国商业银行个人理财业务探讨

近几年来,我国商业银行的个人理财业务已有了一定程度的发展。但从各商业银行个人理财业务的运作情况可以看出,我国商业银行的个人理财业务尚处于新兴阶段,真正能与外资银行相抗衡的理财业务内容并未能开展。本文通过对目前的个人理财理念及业务发展存在问题的研究,提出了相应的对策,希望可以促进商业银行个人理财业务的不断完善与发展。     

Modeling node heterogeneity in latent space models for multidimensional networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This article introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models.     

Swiss National Bank communication and investors’ uncertainty

This paper analyzes the effects of Swiss National Bank communication on stock investors’ uncertainty. Monetary policy news is identified via changes in short- and medium-term futures prices as well as by applying methods from computational linguistics and dictionary approaches to policy statements. Surprises in policy rate changes and regarding the future path of the policy rate exhibit an asymmetric effect on stock investors’ uncertainty. Moreover, by taking into account various topics addressed in the statements, I show that investors’ uncertainty decreases due to an optimistic tone in communications about economic growth. Increased uncertainty expressed in policy statements translate into increasing stock investors’ uncertainty. The results explain how news contained in monetary policy statements reduce noise in financial markets and therefore contribute to financial stability.     

Crude oil price forecasting incorporating news text

Sparse and short news headlines can be arbitrary, noisy, and ambiguous, making it difficult for classic topic model LDA (latent Dirichlet allocation) designed for accommodating long text to discover knowledge from them. Nonetheless, some of the existing research about text-based crude oil forecasting employs LDA to explore topics from news headlines, resulting in a mismatch between the short text and the topic model and further affecting the forecasting performance. Exploiting advanced and appropriate methods to construct high-quality features from news headlines becomes crucial in crude oil forecasting. This paper introduces two novel indicators of topic and sentiment for the short and sparse text data to tackle this issue. Empirical experiments show that AdaBoost.RT with our proposed text indicators, with a more comprehensive view and characterization of the short and sparse text data, outperforms the other benchmarks. Another significant merit is that our method also yields good forecasting performance when applied to other futures commodities.     

国有商业银行固定资产管理问题探析

银行的固定资产是银行开展各项业务、持续经营的实物载体,在为银行创造良好的经营环境、拓展业务空间及提高竞争力等方面发挥了重要作用。固定资产管理作为银行财务管理的组成部分,纳入了银行内部控制体系。文章从国有商业银行管理现状出发,对国有商业银行固定资产管理中存在的问题及成因进行阐述并提出对策。     

商业银行信贷风险的监督管理途径

深化金融体制改革的背景下,商业银行在发展上需要更好的业务开展与管理活动开展。商业银行在持续经营发展中需要面临多种风险,其中,信贷风险的管理十分重要。商业银行信贷风险的监督管理虽然得到了很多关注,但信贷风险监督管理状况并不良好,信贷风险监督管理层面更是存在诸多不足和问题。论文分析了新时期商业银行信贷风险监督管理的具体状况、存在的具体问题等,并就如何更好地进行信贷风险监督管理提出合理建议。     

Dynamic correlation multivariate stochastic volatility with latent factors

Modeling the correlation structure of returns is essential in many financial applications. Considerable evidence from empirical studies has shown that the correlation among asset returns is not stable over time. A recent development in the multivariate stochastic volatility literature is the application of inverse Wishart processes to characterize the evolution of return correlation matrices. Within the inverse Wishart multivariate stochastic volatility framework, we propose a flexible correlated latent factor model to achieve dimension reduction and capture the stylized fact of ‘correlation breakdown’ simultaneously. The parameter estimation is based on existing Markov chain Monte Carlo methods. We illustrate the proposed model with several empirical studies. In particular, we use high‐dimensional stock return data to compare our model with competing models based on multiple performance metrics and tests. The results show that the proposed model not only describes historic stylized facts reasonably but also provides the best overall performance.     

新形势下对我国商业银行内部控制建设的分析与思考

加入WTO以后,随着金融全球化进程和金融市场开放程度的不断扩大,我国商业银行面临更加激烈的竞争环境和更加复杂多样的风险。在此新形势下,虽然我国商业银行内部控制制度建设步伐明显加快,但与国际先进商业银行相比,国内商业银行风险管理水平仍存在较大差距,内控薄弱是普遍存在的突出问题。从当前我国商业银行内部控制的现状着手,简析了我国商业银行内部控制制度的现存问题,并结合实际提出了完善内控制度的对策建议。     

An approach to define semantics for BPM systems interoperability

This article proposes defining semantics for Business Process Management systems interoperability through the ontology of Electronic Business Documents (EBD) used to interchange the information required to perform cross-organizational processes. The semantic model generated allows aligning enterprise’s business processes to support cross-organizational processes by matching the business ontology of each business partner with the EBD ontology. The result is a flexible software architecture that allows dynamically defining cross-organizational business processes by reusing the EBD ontology.

For developing the semantic model, a method is presented, which is based on a strategy for discovering entity features whose interpretation depends on the context, and representing them for enriching the ontology. The proposed method complements ontology learning techniques that can not infer semantic features not represented in data sources. In order to improve the representation of these entity features, the method proposes using widely accepted ontologies, for representing time entities and relations, physical quantities, measurement units, official country names, and currencies and funds, among others. When the ontologies reuse is not possible, the method proposes identifying whether that feature is simple or complex, and defines a strategy to be followed. An empirical validation of the approach has been performed through a case study.     

Equity‐Liabilities Distinction: The case for Co‐operatives*

Members' shares in co‐operative entities are financial instruments with particular characteristics. In this paper we analyse the relation between firm leverage and systematic risk to provide empirical evidence on the economic substance of the member shares of members of cooperatives. We have studied the characteristics of members' shares in six European countries: France, Germany, Italy, Portugal, Spain and United Kingdom. We have also conducted tests on co‐operatives of these countries over the period 1993–2005. The study reports that in global terms the economic substance of the redeemable part of equity in co‐operatives is not the same across countries. Therefore if accounting standards setters want to develop a global standard for co‐operatives, a recommendation derived from this study would be to follow a probabilistic model to classify the redeemable part of co‐operative financial instruments, where the entity does not have the unconditional right to refuse the redemption, or to report this part as an intermediate item with characteristics of debt and equity.     

基于DEA与BSC相结合的上市商业银行绩效评价研究

2008年金融风暴给全球的金融市场带来很大的冲击,商业银行在艰难发展中越来越重视绩效管理,本文提出基于平衡计分卡视角的绩效评价体系,运用数据包络分析法对我国上市商业银行2005年至2009年的绩效水平进行评价,并对评价结果进行分析。     

非利息收入对我国上市商业银行绩效的影响研究

本文采用我国14家上市商业银行2003-2007年披露的年报数据,对商业银行非利息收入进行研究,表明我国商业银行经过多年的发展,打破原先单一主要依靠存贷差产生利润的局面,非利息收入不论在绝对数还是占比上都得到了长足的发展,并且产品结构日趋丰富,满足了人们日益增长的金融服务需求;同时,回归分析表明,提升非利息收入的比重,有利于提高商业银行的绩效。