农业与证券市场的发展

农业企业通过在证券市场发行股票和债券,能够迅速地把分散在社会上的闲散货币集中起来,形成巨额的、可供长期使用的资本,用于生产和经营,从而开辟了不同于间接融资（银行贷款）的直接融资渠道。证券市场还具有促使公司转换经营机制的功能。证券市场对农业经营主体有一定的要求,公司要成为上市公司,必须先改制成为股份公司,按照股份公司的机制来运作。农业企业要在证券市场发行证券,也要经过严格的审查程序,要有良好的业绩。     

我国资产证券化发展的现状与风险防范分析

证券化已成了世界现代经济生活中的普遍现象,对现代经济产生了巨大影响。我国从2005年12月起对银行业信贷资产进行证券化试点,正经受着"美国次贷危机"经验教训的洗礼。本文介绍了我国大陆在资产证券化领域近12年的摸索、讨论和试点情况,并在分析了资产证券化对我国金融体制建设的现实意义之后,提出了我国目前信贷资产证券化及资产支持证券风险防范的6个主要方面。     

基于期权思想的融券费率定价方法研究

证券融资融券交易是成熟证券市场普遍实施的一种交易制度。融券与融资不同,其标的不是资金而是证券,但两者都是信用业务,需要为相关交易支付一定的费用,融资的利率相对容易确定,而融券费率则比较复杂一些,目前各类管理规定中对此并没有明确的说法。本文借鉴了我国台湾地区的经验,计算出我国大陆地区试行融资融券可行的融券费率。     

我国证券投资基金处置效应检验

本文首先介绍了前景理论,将研究期间分为业绩上涨和业绩下降两个阶段,对基金份额赎回的外部效应进行了推导,并将前景理论与外部效应结合分析了基金赎回的处置效应。提出3条假设,利用2007—2009年季度数据,建立基金赎回率与收益率、基金分红等因素之间的面板数据模型,对基金赎回的处置效应进行了实证检验。研究发现:无论是在基金业绩上涨时期还是下降阶段,基金的收益率与基金的赎回率呈显著负相关,特别是在基金业绩下降阶段,投资者选择了赎回基金份额,并没有体现出处置效应。最后,从稳定基金规模的角度出发,本文认为牛市中的净申购与熊市中的净赎回均不利于基金份额的稳定,会给基金的运作带来困难。     

住房抵押贷款支持证券的利率风险度量——基于"建元2005-1 MBS"A证券的实证

住房抵押贷款支持证券中隐含期权的存在导致未来现金流不确定,久期和凸度等利率风险管理工具不再适用。本文基于OAS理念建立了住房抵押贷款支持证券的利率风险度量过程:采用多项式样条函数法构建零息票收益率曲线,采用Vasicek模型描述动态利率期限结构,通过蒙特卡罗方法模拟利率路径并确定未来现金流,采用ARMA模型描述和预测提前偿付率,进而计算出OAS、有效久期和有效凸度的值。最后以建元2005-1MBSA证券为对象进行了实证研究。     

融资融券对我国银行股的影响研究

2011年11月融资融券业务正式开展,标志着我国证券市场做空时代的到来。以银行板块的16只股票为标的,首先进行了银行指数在事件前后的纵向对比,然后对银行指数与上证综指两组数据进行双重差分模型进行深度研究,分析融资融券业务对A股中银行板块的影响。研究证实,融资融券起到了抑制样本指数波动的作用。     

Determinants of corporate debt securities in the Euro area

Abstract

This study examines the macroeconomic determinants of corporate debt securities in the euro area. The financing costs, as approximated by the cost of debt securities vis-à-vis other sources of corporate finance, and financing needs, as captured by mergers and acquisitions and gross domestic product, are found to be significant determinants in the short and long run. The empirical results are also supportive of substitution between debt security and internal financing unrelated to cost of differentials in the short run and of differences in the determination of long- and short-term debt securities. These findings are robust across different samples and specifications.     

The next tick on Nasdaq

The Nasdaq stock market provides information about buying and selling interest in its limit order book. Using a vector autoregressive model of trades and returns, I assess the effect of the entire order book on the next tick. I also determine the influence of individual market makers and electronic networks and find evidence that the identity of market participants can be useful information. Finally, I produce a set of dynamic market price responses to buy and sell orders, and I find that these estimates vary with standard measures of liquidity.     

Identifying small mean-reverting portfolios

Given multivariate time series, we study the problem of forming portfolios with maximum mean reversion while constraining the number of assets in these portfolios. We show that it can be formulated as a sparse canonical correlation analysis and study various algorithms to solve the corresponding sparse generalized eigenvalue problems. After discussing penalized parameter estimation procedures, we study the sparsity versus predictability trade-off and the significance of predictability in various markets.     

A mean/variance approach to long-term fixed-income portfolio allocation

Abstract

Long-term investments in bonds offer known returns, but with risks corresponding to defaults of the underwriters. The excess return for a risky bond is measured by the spread between the expected yield and the risk-free rate. Similarly, the risk can be expressed in the form of a default spread, measuring the difference between the yield when no default occurs and the expected yield. For zero-coupon bonds and for actual market data, the default spread is proportional to the probability of default per year. The analysis of market data shows that the yield spread scales as the square root of the default spread. This relation expresses the risk premium over the risk-free rate that the bond market offers, similarly to the risk premium for equities. With these measures for risk and return, an optimal bond allocation scheme can be built following a mean/variance utility function. Straightforward computations allow us to obtain the optimal portfolio, depending on a pre-set risk-aversion level. As for equities, the optimal portfolio is a linear combination of one risk-free bond and a risky portfolio. Using the scaling law for the default spread allows us to obtain simple expressions for the value, yield and risk of the optimal portfolio.