行为资产组合理论：理论基础、内容及对异象的解释

行为金融理论于20世纪80年代兴起，它通过将行为因素引入决策过程从而对传统的金融理论做出补充。谢夫林(Shefrin)和斯特曼(Statman)在现代资产组合理论的基础上提出了行为资产组合理论，该理论是行为金融的理论基础之一。行为资产组合理论的基础包括安全第一组合理论和安全、潜力和期望理论。内容分为单一账户资产组合理论和多重账户资产组合理论。行为资产组合理论能够对市场中的一些异象做出合理的解释。     

Can the Risks of the Kyoto Mechanisms be Reduced Through Portfolio Diversification? Evidence from the Swedish AIJ Program

Through Joint Implementationand the Clean Development Mechanism, reductionsof greenhouse gas emissions achieved abroad canbe credited to domestic firms. However, thetechnical, economic and political risksinvolved may prevent the private sector frominvesting in such projects. This paperdescribes three types of risks which emissionreduction projects are exposed to. Eleven pilotprojects carried out under the ActivitiesImplemented Jointly (AIJ) program and financedby Sweden are evaluated. Actual project costsare found to exceed projected costs in allcases. Annual emission reductions also deviatefrom their expected values and vary stronglyover time, supporting the hypothesis that suchprojects are risky business. The riskmanagement tool portfolio diversification isapplied to a sample of Swedish AIJ projects.The results indicate that diversification canreduce the risks of greenhouse gas mitigationprojects significantly. Thus, carbon funds area promising way of lowering the risks of theKyoto Mechanisms for private sector investors.     

The optimal portfolio for the two-pillar mandatory pension system: the case of Poland

In the recent decade, there has been observed across the Central and Eastern European states the regulatory trend towards the increase of the non-financial (first) pension pillar size at the expense of the financial (second) pillar. It tends to question the consequences of this shift for the future retirement benefits. Applying the portfolio approach we address this issue by running a series of simulations to find out how to allocate pension contributions between both pillars in an optimal way. Our study contributes to the existing literature as follows. First, we do not perform the assessment of the predetermined regulatory solutions, but we look for an optimal one. Moreover, we allow our optimal rule to be time-varying, if necessary, which would be a true novelty in this research area. Second, we do not base our estimates on historical trends; rather, we apply the long-term economy’s projection to account for the society’s ageing impact, which is a crucially important factor for the solvency of the pension system. Adapting some of the simulation assumptions to fit the Polish case, our results confirm that current regulations underestimate the role of the capital pillar and the optimal allocation between both pillars should be time-varying.     

中国粮食生产区域分化特征和成因的实证研究

对中国在1990年和2002年粮食生产的区域分化状况进行统计分析的结果表明,工业化和城市化的发展,以及农产品市场形成条件下,稻米生产的区域分散特征、小麦生产的区域集中特征以及玉米播种面积的集中和生产产量的分散特征日益明显。计量检验显示,人均承包经营耕地面积和种植业收入比率是影响粮食生产区域分化的最主要的两个因素。     

上市公司主业鲜明率的修正方法

指出了常用的主业鲜明率在实际使用中遇到的问题,主要问题是计算值会出现无意义的结果,并且对真实主营业务比率的反映会有不真实的情况,提出了修正的方法,即通过修正企业经营总体规模的方法进行修正,最后通过实际计算证明修正结果消除了无意义的结果,也更加真实地反映了主营业务的比率.     

熵指数的可分解特性及其在多元化测度中的应用

熵是对不确定性的度量,被广泛应用于多个学科领域。可分解特性是熵统计量的良好品质,它使事件的总体熵可以分解为类间熵和平均的类内熵。这种特性应用到公司多元化水平的测度中,可以有效地解决多元化指数在统计分析中的多重共线性问题。     

房地产开发项目投资组合的均值——信息熵模型

以方差作为风险度量指标存在着计算复杂、计算结果不稳定等缺陷,本文并将信息熵度量风险的方法引入房地产开发项目投资组合中,建立了房地产投资组合的均值-信息熵模型。实例证明,该模型计算简单,具有较强的有效性和实用性。     

“Itô's Lemma” and the Bellman Equation for Poisson Processes: An Applied View

Using the Hamilton-Jacobi-Bellman equation, we derive both a Keynes-Ramsey rule and a closed form solution for an optimal consumption-investment problem with labor income. The utility function is unbounded and uncertainty stems from a Poisson process. Our results can be derived because of the proofs presented in the accompanying paper by Sennewald (2006). Additional examples are given which highlight the correct use of the Hamilton-Jacobi-Bellman equation and the change-of-variables formula (sometimes referred to as ``Itô's Lemma'') under Poisson uncertainty.     

Hedging Housing Risk*

An unusually rich source of data on housing prices in Stockholm is used to analyze the investment implications of housing choices. This empirical analysis derives market-wide price and return series for housing investment during a 13-year period, and it also provides estimates of the individual-specific, idiosyncratic, variation in housing returns. Because the idiosyncratic component follows an autocorrelated process, the analysis of portfolio choice is dependent upon the holding period. We analyze the composition of household investment portfolios containing housing, common stocks, stocks in real estate holding companies, bonds, and t-bills. For short holding periods, the efficient portfolio contains essentially no housing. For longer periods, low-risk portfolios contain 15 to 50 percent housing. These results suggest that there are large potential gains from policies or institutions that would permit households to hedge their lumpy investments in housing. We estimate the potential value of hedges in reducing risk to households, yet yielding the same investment returns. The value is surprisingly large, especially to poorer homeowners.     

Farmland Investment Under Conditions of Certainty and Uncertainty

This study investigates the potential for farmland to improve mixed-asset portfolio efficiency. Three major conclusions are drawn from the research. First, in a world with certainty, farmland can be shown to statistically improve mixed-asset portfolio efficiency. Second, with the introduction of uncertainty into the portfolio allocation model, investors can justify small or no allocations of farmland in a mixed-asset portfolio, although it appears that even with uncertainty prudent investors should evaluate the asset class. Third, with respect to farmland investment and geographic diversification, the results question the ability of an optimized mean–variance portfolio to provide substantial improvement in comparison to a naïve portfolio. The marginal improvement in portfolio efficiency of an optimized farmland portfolio versus a naïve farmland portfolio is not statistically significant.