本文選題：量?jī)r(jià)分布 + 狀態(tài)躍遷��； 參考：《暨南大學(xué)》2014年碩士論文

【摘要】：隨著計(jì)算機(jī)處理能力的提高和大數(shù)據(jù)時(shí)代的到來(lái)，數(shù)學(xué)、物理以及數(shù)據(jù)挖掘的計(jì)算機(jī)方法正逐漸廣泛應(yīng)用于經(jīng)濟(jì)學(xué)和金融學(xué)的研究，在一定程度上解決了傳統(tǒng)經(jīng)濟(jì)學(xué)和金融學(xué)定性研究和定量研究方法不足，以及不符合社會(huì)實(shí)際的理性人假設(shè)與有效市場(chǎng)假說(shuō)的缺陷，給經(jīng)濟(jì)學(xué)和金融學(xué)點(diǎn)亮了新的研究視野和方向。 本文結(jié)合數(shù)理方法和數(shù)據(jù)挖掘的技術(shù)，探討了中國(guó)股市交易的量?jī)r(jià)分布的近似正態(tài)分布形態(tài)，研究了中國(guó)股市交易量?jī)r(jià)分布不同時(shí)間跨度的近似正態(tài)分布形態(tài)結(jié)構(gòu)，并在此基礎(chǔ)上進(jìn)一步提出了中國(guó)股市交易量?jī)r(jià)分布的預(yù)測(cè)模型。 本文的工作主要包括三個(gè)部分：首先，驗(yàn)證了中國(guó)股市日交易量?jī)r(jià)分布拒絕服從正態(tài)分布的假設(shè)，同時(shí)指出，中國(guó)股市日交易量?jī)r(jià)分布由于局部成交量較大，破壞了正態(tài)分布的形態(tài)，但是展現(xiàn)出“尖峰厚尾”的近似正態(tài)分布形態(tài)。然后，經(jīng)過(guò)對(duì)量?jī)r(jià)分布的平滑處理，得到了股市交易量?jī)r(jià)分布的無(wú)標(biāo)度微觀形態(tài)——不同時(shí)間跨度的近似正態(tài)分布形態(tài)結(jié)構(gòu)。最后，，在前兩個(gè)研究的基礎(chǔ)上，提出了股市量?jī)r(jià)分布的狀態(tài)躍遷模型。使用聚類分析，建立基于概率的狀態(tài)躍遷表，預(yù)測(cè)未來(lái)可能出現(xiàn)的近似正態(tài)分布形態(tài)微觀結(jié)構(gòu)。 本文所建立的量?jī)r(jià)分布狀態(tài)躍遷模型可以適當(dāng)?shù)拿枋鲋袊?guó)股市交易中量?jī)r(jià)分布狀態(tài)之間的躍遷網(wǎng)絡(luò)，并在一定概率上預(yù)測(cè)未來(lái)可能出現(xiàn)的量?jī)r(jià)分布狀態(tài)，為具體的股市投資提供一個(gè)具體量化的指標(biāo)。
[Abstract]:With the improvement of computer processing ability and the arrival of big data era, computer methods of mathematics, physics and data mining are being widely used in the research of economics and finance. To some extent, the defects of the traditional qualitative and quantitative research methods in economics and finance are solved, and the rational man hypothesis and the efficient market hypothesis, which do not conform to the social reality, have been solved. To economics and finance to light up a new perspective and direction of research. Combined with mathematical methods and data mining techniques, this paper discusses the approximate normal distribution of volume and price distribution in Chinese stock market, and studies the approximate normal distribution structure of trading volume price distribution in China stock market with different time span. On the basis of this, a forecasting model of the price distribution of trading volume in Chinese stock market is put forward. The work of this paper mainly includes three parts: firstly, it verifies the hypothesis that the daily transaction price distribution of Chinese stock market is based on the normal distribution, and points out that the price distribution of daily trading volume in Chinese stock market is due to the large local volume. The shape of normal distribution is destroyed, but the shape of "peak thick tail" is shown. Then, by smoothing the volume price distribution, the scale-free microscopic morphology of the price distribution of the stock market is obtained, which is the approximate normal distribution structure with different time span. Finally, on the basis of the first two studies, the state transition model of stock price distribution is proposed. Using clustering analysis, a probabilistic state transition table is established to predict the morphology of approximate normal distribution in the future. The model can describe the transition network between the volume and price distribution states in the Chinese stock market, and predict the potential price distribution in the future in a certain probability. For the specific stock market investment to provide a specific quantitative indicators.
【學(xué)位授予單位】：暨南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F224;F832.51

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