加强区域金融合作 促进资本流动与融合

金融资本在引导产业资本投向和投量、提供经济资源转移以及市场信息发现方面发挥着重要的作用。金融资本的逐利性使其在金融交易体系中通过不断地捕捉经济中可能的赢利机会来实现自身的流动与融合，由此可见，实体经济的差异性和投资回报的非均衡性是金融资本运动的内在要求。泛珠三角各省（区）在地理区位、资源或要素禀赋、产业结构、发展水平等方面具有明显的差异性，在一定范围内，差异性越大，互补性越强，因此经济发展的不平衡性使金融发展的区域性合作具有非常重要的现实意义并成为可能。     

加强长三角金融合作,推进上海国际金融中心建设

11月3O日上海市、江苏省、浙江省人民政府与中国人民银行在沪共同签署推进长江三角洲地区金融协调发展支持区域经济一体化框架协议,标志着长江三角洲地区金融协调发展工作正式启动,为推进上海国际金融中心建设提供了有力支持。     

雄安新区文化金融合作创新与路径

设立雄安新区,是以习近平同志为核心的党中央作出的重大历史性战略选择,是千年大计、国家大事。建设千年雄安必须坚持保护弘扬中华优秀传统文化、延续历史文脉,形成自身特有的文化基因与价值传承。当前,文化金融合作模式的不断深化,其对传统文化的保护、文化创意产业的培育,以及金融业的拓展,均具有至关重要的促进作用。从这个意义上讲,将文化和金融共同纳入到雄安新区的整个建设周期,结合雄安文化产业现状,强化文化金融功能,明晰文化金融合作创新路径,是支撑和保障雄安新区建设发展的应有之义。     

合作金融权视角下的农村合作金融制度完善

农村经济的发展离不开金融,合作金融是支农金融的主要力量,农民是合作金融的主体,赋予农民合作金融权是农村经济发展的需要。现阶段我国农村合作金融制度体系尚不完善,存在着立法缺失、产权不明等问题。农民合作金融权的提出和实现,对于合作金融制度的制度原则、制度安排等具有重要意义,为完善农村合作金融和新农村建设提供重要支持。     

新一轮金融改革需要整体协调推进

金融改革无疑是十八届三中全会一系列改革总体方案的重中之重,但如何有效推动金融改革,使之达到预期效果,则是更为重要的战略性课题。根本而言,当前最关键的问题是要改革金融资源的配置方式,     

金融助推文化创意产业发展繁荣

金融业有义务也有能力充分发挥专业优势,进一步壮大文化创意产业的整体实力,提高其在引领经济转型、推动产业升级方面的作用十二五是我国经济加快转变发展方式的攻坚时期,文化创意产业迎来了大发展大繁荣的关键时期。金融业作为经济发展的催化剂、资源配置的调节器和社会稳定的助推器,有义务也有能力充分发挥专业优势,进一步壮大文化创意产业的整体实力,提高其在引领经济转型、推动产业升级方面的作用。     

稳妥地推进农村合作金融改革的几点意见

本围绕如何稳妥地推进深化信用社改革从十二个方面提出一些看法与具体建议，比如从国际合作运动新进展和我国尚处于社会主义初级阶段来论述我国必须有为“三农”发展服务的合作金融组织；对深化农村信用社改革的目的、区分合作金融还是商业银行的主要标志、对深化信用社改革必须贯彻中央提出的“多予、少取、放活”的方针、信用社构建新的产权关系和选择何种信用社改革摸式必须要坚持因地制宜和认真贯彻自愿原则、深化信用社改革切忌重犯专业银行自上而下行政指令搞改革；办好农村信用社必须要坚持勤俭办社，必须要全力建设一支懂经营会管理、爱岗敬业、恪尽职守、无私奉献、全心全意为农民服务的高素质干部职工队伍。     

优化县域金融生态中的合作与博弈

随着对县域金融发展调研的深入，笔者越来越深刻地感受到，在社会资源越来越金融化的时代，区域间资金的流动性、效益性和安全性更多地取决于金融生态环境，优良的金融生态是一笔巨大的无形资产。县域金融是有别于城市金融的特殊金融形态，域内政府、银行、企业三大金融活动主体选择最优博弈策略，形成良性合作博弈关系，对优化县域金融生态具有至关重要的作用。     

梯度推进亚洲金融合作

以史为鉴,把握趋势,灵活应变,是亚洲参与全球竞争的必备功课。面对今日区域金融合作遇到的种种困难,亚洲需要深刻思考的是,如何在面临经济发展模式调整的情况下,将刚刚起步的亚洲区域金融合作稳妥推进。     

梯度推进亚洲金融合作

以史为鉴,把握趋势,灵活应变,是亚洲参与全球竞争的必备功课。面对今日区域金融合作遇到的种种困难,亚洲需要深刻思考的是,如何在面临经济发展模式调整的情况下,将刚刚起步的亚洲区域金融合作稳妥推进。     

CLINICAL AUDIT,GUIDELINES AND STANDARDS: A PRODUCTIVE RELATION FOR MANAGING CLINICAL PRACTICES

This paper contributes to the knowledge about the process of standardisation within the domain of medicine. Standardisation has become an important form of governance and co‐ordination, and there is limited empirical knowledge about its nature and consequences ( Brunsson et al., 2000 ). This paper aims to explore the development, circulation and standardisation process of a specific clinical audit programme: the Scottish Hip Fracture Audit. This audit started as a local initiative and now has developed into a sophisticated arena (Sahlin‐Andersson, 2000) which provides Scottish hospitals with monthly ‘real‐time reports’ outlining their performance against Scottish government targets. The paper argues that the interrelation between clinical audit and evidence‐based medicine (EBM) can become a ‘productive relation’ (Mykhalovskiy, 2003), that opens up spaces of intervention, in which the clinical communities engage with processes of change of clinical procedures, and in these spaces, clinicians and managers are in a position to refine clinical practice and service organisation, to reflect upon their own actions and to allow insight into the rationalities of their work (Berg, 1997).     

EVIDENCE ON DELTA HEDGING AND IMPLIED VOLATILITIES FOR THE BLACK‐SCHOLES,GAMMA, AND WEIBULL OPTION PRICING MODELS

Modifying the distributional assumptions of the Black‐Scholes model is one way to accommodate the skewness of underlying asset returns. Simple models based on the compensated gamma and Weibull distributions of asset prices are shown to produce some improvements in option pricing. To evaluate these assertions, I construct and compare delta hedges of all S&P 500 options traded on the Chicago Board Options Exchange between September 2001 and October 2003 for the Weibull, Black‐Scholes, and gamma models. I also compare implied volatilities and their smiles (i.e., nonlinearities) among the three models. None of the three models improves over the others as far as delta hedging is concerned. Volatilities implied by all three models exhibit statistically significant smiles.     

INTEGRATION OF RANDOM SAMPLE SELECTION,SUPPORT VECTOR MACHINES AND ENSEMBLES FOR FINANCIAL RISK FORECASTING WITH AN EMPIRICAL ANALYSIS ON THE NECESSITY OF FEATURE SELECTION

Financial risk forecasting (FRF) is an effective tool to help people forecast whether or not a company will fail in future. Among all techniques of FRF, the support vector machine (SVM) is the most newly developed, and one of the most accurate and effective techniques. This study is devoted to investigating an ensemble model of FRF by integrating bagging with an SVM to generate a data‐driven SVM ensemble. Bagging is used to produce diverse training datasets on which multiple SVM classifiers are trained to make FRF for a target company. Simple voting is employed to produce a final decision from the SVM model committee. The empirical study has two objectives. One is to verify whether the data‐driven SVM ensemble can produce a more dominating performance than the most frequently used techniques in the area of FRF, i.e. multivariate discriminant analysis, logistics regression and a single SVM. The other is to verify whether feature selection is necessary to help the SVM make more precise FRF, although the SVM can handle high‐dimensional data. The results indicate that the data‐driven SVM ensemble significantly improves the predictive ability of SVM‐based FRF. Meanwhile, feature selection can effectively help the SVM achieve better predictive performance, which means that use of feature selection is necessary in SVM‐based FRF. Copyright © 2012 John Wiley & Sons, Ltd.