Classification systems and selection systems: The risks of radical innovation and category spanning

This paper looks at the relations between classification and competition, using the theoretical framework of selection system theory. In a particular competitive arena more than one classification system can be in use. The proportion of classification systems in use by consumers that are also in use by the dominant selectors is a determinant of the risks of category spanning and radical innovation. Furthermore, these risks can be better understood by taking into account whether the selection system has different stages occupied by selectors of different types and by looking at the relations between the selectors of the primary market and the selectors of these selectors.     

To Witness CIEF Changing

From 1957 to now, the Canton Fair has witnessed the great development of China import and export trading and has recorded the pace of the country＇s growth since it established at that special period. Looking back the over fifty years, the fair has experienced four phrases： establishment, growing exploration and spanning.     

Owner-Occupied Housing and the Composition of the Household Portfolio: The Case of France

This paper investigates the impact of housing demand on the composition of the optimal portfolios of homeowners in France, following the methodology developed by Flavin and Yamashita (NBER Working Paper 6389, 2002). We use historical data on housing prices and financial assets returns to estimate the mean return and covariance matrix of a set of assets including housing. We then calculate mean-variance efficient frontiers associated to various levels of the housing-to-net wealth ratio, corresponding to the average ratios observed for different age groups in the 1998 French Wealth Survey sample. Our numerical results fit the average portfolios in different age brackets quite well. Also, returns of housing and its covariance with the other assets indicate there is room in France for housing price derivatives.     

银行信贷资产证券化信用风险度量及传染研究——基于修正KMV模型和MST算法的实证

精准科学地度量和描述信用风险及传染机制有利于银行信贷资产证券化的高效健康发展和货币市场系统性风险的防范.运用修正KMV模型测度银行信贷资产证券化产品在不同时期的信用风险,并采用最小生成树(MST)算法考察银行间信用风险的传染机制.结果显示:政策性银行和大型商业银行发行的产品在各个时期信用风险均处于较低水平;股份制银行、城商行和农商行发行的产品违约率前期略高于前两类银行,但后期明显下降;后三类银行位于银行股票收益率网络的中心位置,具有传递信息和维系网络稳定的重要作用.     

区域农业生态安全的综合评价研究——以河北省为例

本文以河北省11个地区为例，利用2005年的截面数据，采用均方差法确定评价指标的权重，通过构建生态农业安全评价指标体系，对地区农业生态安全进行了评价。评价结果显示，河北各地区的生态农业安全状态处于非安全期。     

Multi-asset portfolio optimization and out-of-sample performance: an evaluation of Black–Litterman,mean-variance,and naïve diversification approaches

The Black–Litterman model aims to enhance asset allocation decisions by overcoming the problems of mean-variance portfolio optimization. We propose a sample-based version of the Black–Litterman model and implement it on a multi-asset portfolio consisting of global stocks, bonds, and commodity indices, covering the period from January 1993 to December 2011. We test its out-of-sample performance relative to other asset allocation models and find that Black–Litterman optimized portfolios significantly outperform naïve-diversified portfolios (1/N rule and strategic weights), and consistently perform better than mean-variance, Bayes–Stein, and minimum-variance strategies in terms of out-of-sample Sharpe ratios, even after controlling for different levels of risk aversion, investment constraints, and transaction costs. The BL model generates portfolios with lower risk, less extreme asset allocations, and higher diversification across asset classes. Sensitivity analyses indicate that these advantages are due to more stable mixed return estimates that incorporate the reliability of return predictions, smaller estimation errors, and lower turnover.     

Risk Reduction and Mean-Variance Analysis: An Empirical Investigation

Abstract:  I examine the performance of global minimum variance (GMV) and minimum tracking error variance (TEV) portfolios in UK stock returns using different models of the covariance matrix. I find that both GMV and TEV portfolios deliver portfolio risk reduction benefits in terms of significantly lower volatility and tracking error volatility relative to passive benchmarks for every model of the covariance matrix used. However, the GMV (TEV) portfolios do not provide significantly superior Sharpe (1966) (adjusted Sharpe) performance relative to passive benchmarks except for the restricted GMV portfolios. I find that a number of alternative covariance matrix models can improve the performance of the restricted TEV portfolio formed using the sample covariance matrix but not the restricted GMV portfolio. I also find that simpler covariance matrix models perform as well as the more sophisticated models.     

Mean-Variance Hedging for Stochastic Volatility Models

In this paper we discuss the tractability of stochastic volatility models for pricing and hedging options with the mean-variance hedging approach. We characterize the variance-optimal measure as the solution of an equation between Doléans exponentials; explicit examples include both models where volatility solves a diffusion equation and models where it follows a jump process. We further discuss the closedness of the space of strategies.     

基于均值-方差准则下的套期保值问题研究

当有重大信息出现时,股票价格会呈现不连续的跳跃,在股票价格服从跳-扩散过程时,研究了均值-方差准则下的套期保值问题。运用倒向随机微分方程及随机控制理论得到了均值-方差准则下的最优套期保值策略。     

效用函数意义下证券组合投资问题的改进决策树方法

基于Markowitz证券组合投资决策模型,运用效用理论中的均值-方差效用函数与决策理论中的决策树方法,提出了一种证券组合投资问题的改进决策树方法;探讨与分析了改进决策树方法的构造与求解过程。改进决策树方法不但可以对证券组合投资问题的决策方案集进行最优投资策略的选择,而且可以对该决策方案集按照一定的标准进行排序。