基于线性学习函数的泛证券投资组合策略

最优定常再调整策略所产生的收益随时间成指数速度增长, 寻找与最优定常再调整策略的收益具有相同指数增长率的在线序贯投资组合是近年来投资组合研究的一个 热点. 首先提出了基于线性学习函数的在线投资组合策略, 其中线性函数的系数是一个与股票相对价格和收益有关的区间的中点. 用相对熵函数定义两个投资组合向量之 间的距离, 进一步证明了基于线性函数的在线投资组合策略是泛证券投资组合. 最后, 分别在两支股票和三支股票组成的多个投资组合上进行了数值计算, 并 与Cover等人提出的泛证券投资组合策略进行了比较. 结果表明这种基于线性学习函数的在线投资组合策略能获得更多的收益, 从而为投资者提供了新的 在线序贯投资组合决策的方法和依据, 具有重要的现实指导意义.     

From MDR to MXR: new understanding of multidrug resistance systems, their properties and clinical significance

The ATP binding cassette (ABC) superfamily of membrane transporters is one of the largest protein classes known, and counts numerous proteins involved in the trafficking of biological molecules across cell membranes. The first known human ABC transporter was P-glycoprotein (P-gp), which confers multidrug resistance (MDR) to anticancer drugs. In recent years, we have obtained an increased understanding of the mechanism of action of P-gp as its ATPase activity, substrate specificity and pharmacokinetic interactions have been investigated. This review focuses on the functional characterization of P-gp, as well as other ABC transporters involved in MDR: the family of multidrug-resistance-associated proteins (MRP1-7), and the recently discovered ABC half-transporter MXR (also known as BCRP, ABCP and ABCG2). We describe recent progress in the analysis of protein structure-function relationships, and consider the conceptual problem of defining and identifying substrates and inhibitors of MDR. An in-depth discussion follows of how coupling of nucleotide hydrolysis to substrate transport takes place, and we propose a scheme for the mechanism of P-gp function. Finally, the clinical correlations, both for reversal of MDR in cancer and for drug delivery, are discussed.