We propose two nonparametric transition density-based speciÞcation tests for continuous-time models. Unlike the marginal density used in the literature, the transition density can capture the full dynamics of a continuous-time process. To address the concerns of the Þnite sample perfor- mance of nonparametric methods in the literature, we introduce an appropriate data transfor- mation and correct the boundary bias of kernel estimators. As a result, our tests are robust to persistent dependence in data and provide reliable inferences for sample sizes often encountered in empirical Þnance. Simulation studies show that even for data with highly persistent depen- dence, our tests have reasonable size and good power against a variety of alternatives in Þnite samples. Besides one-factor diffusion models, our tests can be applied to a broad class of dynamic models, including discrete-time dynamic models, time-inhomogeneous diffusion models, stochas- tic volatility models, jump-diffusion models, and multi-factor diffusion models. When applied to Eurodollar interest rates, our tests overwhelmingly reject a variety of popular one-factor diffusion models. We Þnd that introducing nonlinear drift does not signiÞcantly improve the goodness of Þt, and the main reason for the rejection of one-factor diffusion models is the violation of the Markov assumption. Some popular non-Markovian models with GARCH, regime switching and jumps perform signiÞcantly better than one-factor diffusion models, but they are still far from being adequate to fully capture the interest rate dynamics. Our study shows that, contrary to the general perception in the literature, nonparametric methods are a reliable and powerful tool for analyzing Þnancial data.

This paper examines both the time series and cross-country patterns in the development of stock markets around the world. It adopts a flexible modeling framework that allows for the breakdown of changes in equity market capitalization into changes in macroeconomic and financial fundamentals, shifts in valuation technology and market sentiment, and improvement in valuation efficiency. Using panel data on 32 countries, I show that for developed countries, the size of their equity markets is positively related to the correlation of these markets with the global portfolio, and is negatively related to government consumption. For developing countries, the level of financial intermediary development and openness to trade are found to be conducive to the development of local equity markets. For given levels of market fundamentals, developed countries with greater economic freedom and stronger shareholder protections are associated with more highly valued equity markets, while the French or German civil law countries and countries with insider trading legislation tend to have relatively poorly valued equity markets. For developing countries, ceteris paribus, high quality of accounting standards is found to be associated with higher valuation of their equity markets. I find that only equities in emerging markets become more highly valued, indicating an improvement in valuation efficiency over time. Australia, Canada, the United States, Hong Kong, and Singapore have the most highly valued equity markets in the developed world, while Malaysia has the mostly highly valued equity market in the developing world. It appears that favorable shifts in valuation technology and market sentiment contribute the lion’s share of the growth of global equity markets.

从20世纪90年代以来, 中国对外资本流动最引人注目的特点就是大规模的国内储蓄与大规模的国际资本流入与国内资本流出的同时并存, 以及对外资本净输出的资金循环模式。本研究结合美国及新兴市场(Emerging Markets)国家的国际资本流动的外部环境, 以及中国加入WTO之后面临着开放资本市场的现实, 依据资金循环分析的基本理论, 运用资金流量统计及国际收支等统计数据,探讨中国对外资金循环的特点及问题

随着中国加入世界贸易组织（WTO），中国的保险市场的发展、保险公司的运营以及保险业监管，都面临着国际规范运作的挑战。而保险市场的培育与监管关键还在于参与竞争的保险企业的素质。面临激烈的市场竞争，如何客观评价自己在市场中的竞争能力，并有针对性地加以调整和完善，形成企业核心竞争力，这对面临国际化竞争的保险企业至关重要。建立保险公司竞争力评价体系，不仅是保险公司自身发展的需要，也是促进整个保险市场健康有序发展的需要。以往对保险公司的评价主要停留在财务指标和信用指标，是不全面的。本文试图通过对竞争环境与竞争要素的分析，利用系统工程理论与技术，建立一套具有可操作性的保险公司竞争力评价体系的框架。

路桥区民营企业在经历了原始积累和快速发展阶段后，正处于二次飞跃阶段。民营企业涉足的领域不断扩大，资本及技术含量大为提高，对融资及金融服务在规模和方式上均有了更高的要求。认真分析我区民营企业融资现状，并在现有条件下如何进一步拓宽融资渠道，是本文的主旨。

金融市场价格波动预测是一个举世公认的国际性科学难题，打破长期徘徊在以线性的、完全理性的均衡范式的现代（主流）金融学为基础的经验性预测局面，转向研究以非线性动力学为基础的金融市场价格波动数值预测，将非线性金融市场动力学的理论、模拟试验和实际观测，数据同化和计算软件的开发作为今后研究的重点，并借助数值分析天气预报、物理建模地震预测和航位推算弹道导弹等学科领域的经验，强化多学科，多部门的组织协调，在中国股市和期市开展金融市场价格波动动力学数值预测的科学试验，金融市场价格波动数值预测研究将极大地促进中国金融市场基础研究和金融风险预警系统的进一步发展。

基于分形市场假说的股价并不完全反映所有信息的观点，认为历史股价信息是不完备的群体型模糊信息，提出了线性信息分配条件下的信息守恒定理，建立了基于模糊信息分配理论的股价涨跌短期预测的模糊模式识别模型，通过对上证综合指数日线数据的短期预测，表明该模型具有能够动态捕捉股价短期分布特征、有效描述股价序列内蕴的短期非线性因果关系，进而具有较高的股价涨跌识别精度，并提出了金融市场收益率可能性分布的概念，最后提出了基于该模型的短期股价涨跌识别决策支持系统的框架。

本文讨论了均值回归水平按连续时间有限状态马尔可夫链变化的双因子Vasicek模型。在货币当局能够正常制定随时间变化的参照利率的情况下，该模型可以很好的反映其政策行为表现。在此基础上，根据包含一个基础矩阵的债券价格分解表达式，推导得出了期限结构。最后，通过远期利率变动过程对债券价格近似解的有效性进行了验证。

摘要：文章发现在中国股票市场中投资者对于市场信息的反应，早期表现为反应迟钝，后期表现为反应过度，并且以反应迟钝行为为主。投资者的这些行为不仅与投资者的心理因素有关，而且与上市公司的信息非对称程度以及交易制度也有关。投资者对信息反应过度的强度与股价的均值回复行为正相关。

资产市场均衡价格高于其真实价格的部分即为泡沫，泡沫破灭将导致财富幻觉的消失，进而导致需求萎缩、投资不足、经济增长放缓等不良后果。本文的研究表明，制度缺陷将导致资产市场存在理性的泡沫。在资产市场配额供给、商业银行承担两类代理成本、央行实施价格管制、监管当局实施资产比例管理等制度背景下，存在私人利益和正的边际私人利益的银行家，倾向于向资产市场过度供给贷款，从而导致风险资产价格相对于银行家无私人利益时的均衡资产价格而言，系统性地被高估。在商业银行与银行监管当局仅根据风险资产最近成交价格预测银行贷款组合或贷款抵押物未来价值这一信息结构下，一次交易中所形成的资产市场泡沫，可能会随着时间的延续而逐渐积累。