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有效市场假设与资产定价模型的关系之探讨 总被引：1，自引：0，他引：1
有效市场假设与资产定价模型的关系由于联合检验问题的存在一直备受关注,也产生了一些混淆。本文从对有效市场假设和资产定价模型进行实证检验时存在的联合检验问题、资产定价模型的假设条件是否包含有效市场假设以及有效市场假设是否意味着风险证券的收益率服从正态分布三个方面研究了有效市场假设与资产定价模型之间的关系。本文的研究表明:联合检验问题的存在产生了一个逻辑悖论--检验有效市场需要一个正确的资产定价模型,而检验资产定价模型又必须在有效的资本市场中进行;资产定价模型的假设条件确实隐含了有效市场假设;在资产定价模型中被广泛采用的正态性假设并不是有效市场假设的必然结果。 相似文献
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有效市场假设与分形市场假设 总被引：3，自引：0，他引：3
本文主要是比较了有效市场假设与分形市场假设,也即比较了证券市场的线性与非线性的观点,有效市场假设对应于正态分布,分形市场假设对应于“肥尾”分布。我们发现沪深股指的周和日收益率不服从正态分布,而月收益率因为数据太少结论有所不同。最后通过比较周收益率与日收益率发现指数的分形特征。 相似文献
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本文采用深圳综合指数检验了一种使用广泛的技术分析准则——移动平均准则。与随机漫步类型的检验不同，技术分析检验不依赖于时间，并且可以包括线性模式与非线性模式各种可能，因而具有很大的优越性。同时，为了避免股票收益分布的正态性假设，本文还采用Ｂｏｏｔｓｔｒａｐ方法与常规检验进行对比。经验结果表明：在现阶段中国股市，技术分析具有一定的预测能力，但对技术分析准则所指出的“买”、“卖”及“买－卖”条件收益来说，随机漫步模型不具备解释能力，也就是说，随机漫步模型尚不能正确描述现阶段中国股票市场行为的特征 相似文献
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新兴股票市场有效性及诚实性检验方法和实证分析 总被引：4，自引：0，他引：4
本文介绍了新兴股票市场有效性及诚实性检验方法，通过检验上市公司新发布的公告是否能引起股市交易量的增加和收益率的波动量增加来检验股票市场的有效性及是否存在内部交易的问题。如果在公告发布期间股市没有任何异常变动，市场可能是效率低下的或是存在内部交易。如果进一步分析能够证实在同一公司发布的针对不同持有群体的股票之间,如A股和B股或H股之间，存在滞后的引导关系，则可以基本判定股市存在内部交易。Utpa Bhattacharya已经对墨西哥的Bolsa Mexicana de Valores市场做过类似的研究并且发现该股票市场存在内部交易。本文对中国的股票市场进行研究。结果表明中国股市不存在明显的内部交易，但同时也发现中国股市的A股和B股市场之间的联动性较弱，中国股市有效性较差，尤其是B股市场对市场信息公告的反映很不明显。这些都在一定程度上反映了中国股市作为成长中的股市发展还不成熟，B股市场的发展尤其需要进一步努力。 相似文献
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中国央行降息对股市影响的一类干预分析模型 总被引：4，自引：0，他引：4
本文应用时间序列建模方法，对反映中国市场经济睛雨表的股市进行了实证研究，不仅使用大家熟知的平稳时序建模过程，而且更重要的是，在考察政府干预——央行降息对股市影响方面，这里并未采用以往的假设统计检验，而是通过一种定量分析模型——干预模型来进行研究。从而得出与股价、利息率呈反向变动这一理论相吻合的实证结果。 相似文献
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赫斯特指数的分析与应用 总被引：2，自引：0，他引：2
基于重标极差(R／S)分析基础上的赫斯特指数(H)是用来描述和标度传统的有效市场假说(EMH)是否成立的一个指标，本文以我国深圳成分指数为研究对象，通过对深成指的赫斯特指数的研究，结果表明该股票指数遵循有偏的随机游走(分形布朗运动)而非传统的随机游走模式。 相似文献
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上海股票市场有效性实证检验 总被引：28，自引：0，他引：28
本文以上海股票市场的指数和选取的一些股票的价格行为对象,用单位根和方差比方法检验其是否服从随机游走过程,从而判断其弱式市场有效性。结果发现除个别小公司股票价格行为不服从单位根过程外,指数和大多数股票价格的行为均显示出其具有一定程度的弱式市场有效性的特征。 相似文献
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上海证券市场的分形结构 总被引：27，自引：0，他引：27
本文应用赫斯特提出的Ｒ／Ｓ分析方法研究了上海证券市场股票收益的波动规律。结果显示上海的股票收益遵循有偏的随机游走过程或分析布朗运动,人格不能对信息做出及时充分地反映,收益序列呈现出持久性,今天的股票价格影响未来,时间是重要的,就像一块卵石落入水中,今天的事件在时间中像涟漪那样向前扩散,涟漪逐渐减弱直至在实际上消失。 相似文献
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《Information processing & management》2016,52(4):670-681
General graph random walk has been successfully applied in multi-document summarization, but it has some limitations to process documents by this way. In this paper, we propose a novel hypergraph based vertex-reinforced random walk framework for multi-document summarization. The framework first exploits the Hierarchical Dirichlet Process (HDP) topic model to learn a word-topic probability distribution in sentences. Then the hypergraph is used to capture both cluster relationship based on the word-topic probability distribution and pairwise similarity among sentences. Finally, a time-variant random walk algorithm for hypergraphs is developed to rank sentences which ensures sentence diversity by vertex-reinforcement in summaries. Experimental results on the public available dataset demonstrate the effectiveness of our framework. 相似文献
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The task of answering complex questions requires inferencing and synthesizing information from multiple documents that can be seen as a kind of topic-oriented, informative multi-document summarization. In generic summarization the stochastic, graph-based random walk method to compute the relative importance of textual units (i.e. sentences) is proved to be very successful. However, the major limitation of the TF*IDF approach is that it only retains the frequency of the words and does not take into account the sequence, syntactic and semantic information. This paper presents the impact of syntactic and semantic information in the graph-based random walk method for answering complex questions. Initially, we apply tree kernel functions to perform the similarity measures between sentences in the random walk framework. Then, we extend our work further to incorporate the Extended String Subsequence Kernel (ESSK) to perform the task in a similar manner. Experimental results show the effectiveness of the use of kernels to include the syntactic and semantic information for this task. 相似文献
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《Information processing & management》2020,57(2):102052
Finding structural and efficient ways of leveraging available data is not an easy task, especially when dealing with network data, as is the case in telco churn prediction. Several previous works have made advancements in this direction both from the perspective of churn prediction, by proposing augmented call graph architectures, and from the perspective of graph featurization, by proposing different graph representation learning methods, frequently exploiting random walks. However, both graph augmentation as well as representation learning-based featurization face drawbacks. In this work, we first shift the focus from a homogeneous to a heterogeneous perspective, by defining different probabilistic meta paths on augmented call graphs. Secondly, we focus on solutions for the usually significant number of random walks that graph representation learning methods require. To this end, we propose a sampling method for random walks based on a combination of most suitable random walk generation strategies, which we determine with the help of corresponding Markov models. In our experimental evaluation, we demonstrate the benefits of probabilistic meta path-based walk generation in terms of predictive power. In addition, this paper provides promising insights regarding the interplay of the type of meta path and the predictive outcome, as well as the potential of sampling random walks based on the meta path structure in order to alleviate the computational requirements of representation learning by reducing typically sizable required data input. 相似文献
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Myeonggu Son Gyudo Lee Jongsang Son Seungyeop Choi Youngho Kim Sei-Young Lee Young-Ro Yoon Dae Sung Yoon Sang Woo Lee 《Biomicrofluidics》2015,9(1)
The random walk of spherical living cells on a silicon dioxide glassy substrate was studied experimentally and numerically. This random walk trajectory exhibited erratic dancing, which seemingly obeyed anomalous diffusion (i.e., Lévy-like walk) rather than normal diffusion. Moreover, the angular distribution (−π to π) of the cells'' trajectory followed a “U-shaped pattern” in comparison to the uniform distribution seen in the movements of negatively charged polystyrene microspheres. These effects could be attributable to the homeostasis-driven structural resilient character of cells and physical interactions derived from temporarily retained nonspecific binding due to weak forces between the cells and substrates. Our results provide new insights into the stochastic behavior of mesoscopic biological particles with respect to structural properties and physical interactions. 相似文献
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The norm of practice in estimating graph properties is to use uniform random node (RN) samples whenever possible. Many graphs are large and scale-free, inducing large degree variance and estimator variance. This paper shows that random edge (RE) sampling and the corresponding harmonic mean estimator for average degree can reduce the estimation variance significantly. First, we demonstrate that the degree variance, and consequently the variance of the RN estimator, can grow almost linearly with data size for typical scale-free graphs. Then we prove that the RE estimator has a variance bounded from above. Therefore, the variance ratio between RN and RE samplings can be very large for big data. The analytical result is supported by both simulation studies and 18 real networks. We observe that the variance reduction ratio can be more than a hundred for some real networks such as Twitter. Furthermore, we show that random walk (RW) sampling is always worse than RE sampling, and it can reduce the variance of RN method only when its performance is close to that of RE sampling. 相似文献
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利用证券市场有效性理论,运用随机游走方法,以我国深圳基金市场价格指数为样本,对我国投资基金市场的效率作以检验与分析,得出目前我国投资基金市场为非有效市场的结论,并在此基础上提出提高我国投资基金市场效率的对策。 相似文献
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P2P(peer-to-peer)模式是互联网的重要应用之一,资源定位是实现P2P网络资源共享的前提条件。本文首先介绍国内外P2P资源定位的研究现状,接着介绍了P2P网络的四种模型,然后介绍目前P2P资源定位的一些方法以及对这些方法的优化,如泛洪、随机漫步、基于分布式哈希表的查找等。 相似文献