特质波动率与股票收益——基于Fama-French五因子模型的研究北大核心CSCD

股票收益与风险之间的关系一直以来都是金融学理论研究的核心问题.近年来,针对股票收益与特质风险之间的关系的研究受到了越来越多的学者的关注.在有效市场的理论下,通过构建多样化投资组合,投资者可以分散公司的特质风险,使组合收益更多的与市场风险相关.然而由于投资者之间信息不对称、市场政策差异化、资金成本不均衡等因素的影响,往往无法构建其目标组合,于是无法分散的特质风险就会在一定程度上影响股票收益.该文章以沪深A股自2000年1月4日至2015年12月31日共计3871个交易日的日收益率数据作为研究样本,通过滚动窗口分析的方法,以最新的五因子模型为切入点,研究发现了在中国股票市场中特质波动率与股票收益之间的负相关关系,并通过构建高特质风险与低特质风险股票组合进一步发现特质波动率与收益之间的负相关关系在经济意义上显著.     

中国股票市场收益率分布曲线的实证

股票价格行为的随机理论认为市场收益服从正态分布 ,但在现实中这一假设不一定成立 ,市场收益率更多地呈现出偏离正态分布的形式。本文检验中国市场的收益率分布形态。     

Concepts for safety stock determination under stochastic demand and different types of random production yield

We consider a manufacturer’s stochastic production/inventory problem under periodic review and present methods for safety stock determination to cope with uncertainties that are caused by stochastic demand and different types of yield randomness. Following well-proven inventory control concepts for this problem type, we focus on a critical stock policy with a linear order release rule. A central parameter of this type of policy is given by the safety stock value. When non-zero manufacturing lead times are taken into account in the random yield context, it turns out that safety stocks have to be determined that vary from period to period. We present a simple approach for calculating these dynamic safety stocks for different yield models. Additionally, we suggest approaches for determining appropriate static safety stocks that are easier to apply in practice. In a simulation study we investigate the performance of the proposed safety stock variants.     

Optimizing routes and stock

This work is motivated by a problem proposed to the authors by a bakery company in Northern Spain. The objective is to design the daily routes over the week in order to minimize the total traveled distance. For reducing this total distance, some flexibility in the dates of delivery is introduced, which will cause a stock. Therefore, we study the problem under the bi-objective perspective, “minimizing” simultaneously the total traveled distance and the stock. A bi-objective mixed-integer linear model for the problem is formulated and two methodologies of solution are presented. The first one is based on a series of linked variable neighborhood searches and the second one is based on NSGA-II provided of specific operators. Numerical results showing the obtained estimated Pareto front in both cases are presented.     

艾滋疫情控制中的资金预警机制与分配策略研究

在艾滋病疫情控制的过程中,存在着诸多可能影响艾滋病疫情蔓延进而导致疫情控制目标无法实现的不确定因素,因而疫情控制的决策机构必须能够及时针对疫情变化调整方案.为此,首先,本文提出了一种艾滋病疫情控制中的资金预警机制.在疫情蔓延趋势即将偏离理想目标时发出预警,并给出需追加资金的需求估值.其次,对于控制区域下包括多个分区域的情况,利用数据包络分析方法给出了一种综合考虑疫情危险程度与经济状况的资金分配策略.从而在项目实施的不同阶段出现实际可用资金无法满足疫情控制的需求时,实现了项目可用资金的合理分配,提高了资金在疫情控制上的利用效率.最后,以一个数值例子说明了所提资金预警机制及分配策略的必要性及其有效性.     

Heuristic for the rectangular two-dimensional single stock size cutting stock problem with two-staged patterns

Two-staged patterns are often used in manufacturing industries to divide stock plates into rectangular items. A heuristic algorithm is presented to solve the rectangular two-dimensional single stock size cutting stock problem with two-staged patterns. It uses the column-generation method to solve the residual problems repeatedly, until the demands of all items are satisfied. Each pattern is generated using a procedure for the constrained single large object placement problem to guarantee the convergence of the algorithm. The computational results of benchmark and practical instances indicate the following: (1) the algorithm can solve most instances to optimality, with the gap to optimality being at most one plate for those solutions whose optimality is not proven and (2) for the instances tested, the algorithm is more efficient (on average) in reducing the number of plates used than a published algorithm and a commercial stock cutting software package.     

Employee stock ownership and diversification

A small to moderate size investment in company stock results in a relatively small increase in the riskiness of an employee’s portfolio, even if the company’s volatility is substantially greater than that of a diversified portfolio which we assume the employee would hold otherwise. Thus the employee suffers relatively little loss in “expected utility” from such an investment, whether or not the extra motivation due to this investment by the employee and his or her colleagues leads to an increase in productivity. However, increasing the investment beyond certain limits leads to substantial, and increasingly large, increments in the riskiness of the portfolio. This article presents the theory behind these assertions, and presents a plausible numerical example of the effects described. This example implies that the optimal investment in company stock in a diversified portfolio is 8\frac23%8\frac{2}{3}\% while a higher amount of ten or even fifteen percent would not be imprudent.     

股票配股权的价值估计

本文利用股票的期权定价理论研究了我国股票市场上股票的配股权价值问题 ,并给出了具体的计算公式。     

A behavioral stock market model

Stock exchanges are modeled as nonlinear closed-loop systems where the plant dynamics is defined by known stock market regulations and the actions of agents are based on their beliefs and behavior. The decision of the agents may contain a random element, thus we get a nonlinear stochastic feedback system. The market is in equilibrium when the actions of the agents reinforce their beliefs on the price dynamics. Assuming that linear predictors are used for prediction of the price process, a stochastic approximation procedure for finding market equilibrium is described. The proposed procedure is analyzed using the theory of Benveniste et al. (Adaptive algorithms and stochastic approximations. Springer, Berlin, 1990). A simulation result is also presented.     

Empirical Bayes stock market portfolios

We exhibit a compound sequential Bayes portfolio selection algorithm based solely on the past which not only lives off market fluctuations but follows the drift as well. In fact, this sequential portfolio performs as well (up to first order terms in the exponent) as the optimal portfolio based on advance knowledge of the n-period empirical distribution of the market. Moreover, to first order in the exponent, the capital resulting from this portfolio will be no less than the best of the available stocks. This is a result that holds for every sample sequence. Thus bull markets and bear markets can not fool the investor into over-committing or under-committing his capital to the risky alternatives available to him. The goal is accomplished by a choice of portfolio which is robust with respect to futures that may differ drastically from the past.