發(fā)布時(shí)間：2018-10-05 17:39

【摘要】：本文提出分布意義下的股票價(jià)格動(dòng)量并研究其在證券投資中的應(yīng)用.首先假設(shè)每支股票為一個(gè)多粒子系統(tǒng),引入股票交易籌碼分布,在實(shí)證檢驗(yàn)中利用正態(tài)分布對(duì)其進(jìn)行估計(jì);其次,本文給出一個(gè)迭代算法用來(lái)估計(jì)股票的成本分布;最后,基于成本分布,定義新股票價(jià)格動(dòng)量,并利用反轉(zhuǎn)策略對(duì)其進(jìn)行實(shí)證分析,結(jié)果表明:新動(dòng)量在很多方面優(yōu)于其它動(dòng)量.另外,根據(jù)成本分布還可以定義股票的熵.由新動(dòng)量和熵雙指標(biāo)構(gòu)建的投資組合,其風(fēng)險(xiǎn)-收益優(yōu)于單指標(biāo).
[Abstract]:In this paper, stock price momentum in the sense of distribution is proposed and its application in securities investment is studied. Firstly, assuming that each stock is a multi-particle system, the distribution of stock bargaining chips is introduced, and then the normal distribution is estimated in the empirical test. Secondly, an iterative algorithm is presented to estimate the cost distribution of the stock; finally, an iterative algorithm is proposed to estimate the cost distribution of the stock. Based on the cost distribution, the new stock price momentum is defined, and the empirical analysis is made by using the inversion strategy. The results show that the new momentum is superior to other momentum in many aspects. In addition, the entropy of stock can be defined according to the cost distribution. The combination of new momentum and entropy is better than the single index.
【學(xué)位授予單位】：鄭州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F832.51

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