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| 投资者情绪对股票市场波动性的影响研究 摘 要 当前，市场利润率逐渐提高了基金与证券的供求比例。这也为表达投资者的信念提供了全新的一种机制和相关的渠道，使得不同投资者之间的信念差异能够更快地转移到市场上。但是，大多数关于投资者情绪或融资问题的研究都是基于一个比较传统的金融框架上的。很少有人真正看待投资者自身情绪的表达渠道的一个重要性，也很少是有科学家从这一方面的角度去分析融资和收益的行为。本文在此背景下，把之前学者的一些分析作为相应的基础，并且将相关的投资者的情绪去作为一个新的研究方向，可以真正的修正投资者方面的一些情绪上的指数，提高了指数构建的有效性。本文主要是采用了TARCH-M的模型，来真正的测试现在中国股市当中出现的一些不对称波动特征，并从一些融资机制的角度进行了比较合理上的分析。毕竟，近年来中国股市当中的牛市和熊市的变化现象较为突出。因此，投资者的情绪在不同的状态下，所产生的一些作用就可能是不同的。那么就非常的有必要来利用一定的马尔可夫的变换模型，来区分现在A股市的一种状态。在此基础上，从而来有效的研究出现在对于投资者方面的情绪对中国股市波动上出现的一个影响。 关键词：投资者情绪；股票；市场波动 ABSTRACT At present, margin trading in the market has gradually magnified the supply and demand relationship between capital and securities. This also provides a new mechanism and channel for investors to express their beliefs, so they can really transfer the belief differences between different investors to the market more quickly and quickly. However, most of the research on investor sentiment or financing is based on the traditional financial framework. Few people really consider the expression of investors' own emotions, and few scholars analyze the behavior of margin trading in this respect. In view of this background, on the basis of the previous analysis framework, this paper takes the difference between margin trading and investors' emotions as a new starting point to revise and optimize the emotional index. Thus, the effectiveness of index construction and empirical analysis is improved. This paper mainly uses the TARCH-M model to test the characteristics of an asymmetric fluctuation of the stock market in China, and to test the asymmetric response of investor sentiment when the government shock occurs. And from the financing mechanism point of view to carry on a reasonable analysis. Lastly, because the phenomenon of bull and bear market alternation in China's stock market in recent years is quite significant, the role of investor sentiment may have different characteristics in different states. Therefore, it is necessary to use the Markov conversion model to distinguish the state of A stock market in the range of analysis samples. Key words: investor sentiment; stock; market volatility |
