發(fā)布時(shí)間：2018-05-15 04:31

  本文選題：符號時(shí)間序列分析 + “已實(shí)現(xiàn)”波動(dòng)��； 參考：《天津大學(xué)》2014年碩士論文

【摘要】：金融波動(dòng)是金融市場風(fēng)險(xiǎn)的晴雨表。面對尚在發(fā)展中的國內(nèi)金融市場，金融時(shí)間序列數(shù)值的起伏詮釋了金融市場的內(nèi)在屬性穩(wěn)定性。在現(xiàn)有的金融市場中，需要利用金融波動(dòng)研究來分析金融風(fēng)險(xiǎn)，以期增強(qiáng)投資者的風(fēng)險(xiǎn)意識，引導(dǎo)投資者進(jìn)行理性投資，促使金融市場有序健康地發(fā)展。因此，金融波動(dòng)的相關(guān)預(yù)測與分析對我國金融市場具有重要的理論和實(shí)踐意義。金融市場本身是一個(gè)時(shí)變、復(fù)雜的非線性系統(tǒng)，影響因素較多、結(jié)構(gòu)復(fù)雜、變化多端�；趯ι鲜銮闆r的考慮，符號時(shí)間序列應(yīng)用于金融波動(dòng)分析能夠更好地?cái)M合復(fù)雜多變的金融市場，為國內(nèi)外學(xué)者在金融市場領(lǐng)域的研究提供重要依據(jù)，對國內(nèi)外金融市場的健康發(fā)展起著促進(jìn)作用。因此，本文通過利用灰色馬爾科夫模型預(yù)測金融波動(dòng)來引導(dǎo)投資者行為，并通過聚類分析來歸類風(fēng)險(xiǎn)，，幫助投資者實(shí)現(xiàn)風(fēng)險(xiǎn)規(guī)避、風(fēng)險(xiǎn)對沖。 首先，本文介紹了金融波動(dòng)的研究背景，提出金融波動(dòng)研究的現(xiàn)實(shí)意義，總結(jié)了金融波動(dòng)、“已實(shí)現(xiàn)”波動(dòng)、符號時(shí)間序列分析的研究成果，從而指明論文的創(chuàng)新點(diǎn)、目的與研究意義。其次，本文提出了灰色馬爾科夫模型、“已實(shí)現(xiàn)”波動(dòng)、符號時(shí)間序列分析和聚類分析的具體方法理論，重點(diǎn)介紹了灰色馬爾科夫模型和聚類分析的理論框架和工作步驟，為論文的相關(guān)研究提供理論依據(jù)。最后基于我國國內(nèi)金融市場中上證指數(shù)和深證成指的“已實(shí)現(xiàn)”波動(dòng)時(shí)間序列，利用灰色馬爾科夫模型預(yù)測金融波動(dòng)并利用聚類分析方法將現(xiàn)有金融市場的金融波動(dòng)序列進(jìn)行分類，從而能夠使投資者全方位地了解我國金融市場，根據(jù)自己的風(fēng)險(xiǎn)偏好進(jìn)行理性投資。 本文僅為國家自然科學(xué)基金項(xiàng)目“基于符號時(shí)間序列分析的金融波動(dòng)研究”(項(xiàng)目編號：70971097)研究工作的一部分。
[Abstract]:Financial fluctuation is a barometer of financial market risk. In the face of the developing domestic financial market, the fluctuation of financial time series value interprets the inherent property stability of financial market. In the present financial market, it is necessary to analyze the financial risk by using the financial fluctuation research, in order to enhance the risk consciousness of the investors, guide the investors to make rational investment, and promote the orderly and healthy development of the financial market. Therefore, the prediction and analysis of financial fluctuation is of great theoretical and practical significance to China's financial market. The financial market itself is a time-varying and complex nonlinear system with many influencing factors and complex structure. Based on the above situation, the application of symbolic time series to the analysis of financial volatility can better fit the complex and changeable financial markets, and provide an important basis for the research of domestic and foreign scholars in the field of financial markets. It plays an important role in promoting the healthy development of financial markets at home and abroad. Therefore, this paper uses grey Markov model to predict financial volatility to guide investor behavior, and cluster analysis to classify risk, help investors achieve risk aversion, risk hedging. First of all, this paper introduces the research background of financial volatility, puts forward the practical significance of financial volatility research, summarizes the research results of financial volatility, "realized" volatility, symbolic time series analysis, and points out the innovation of the paper. Purpose and significance of research. Secondly, this paper puts forward the theory of grey Markov model, "realized" fluctuation, symbol time series analysis and clustering analysis, and introduces the theoretical framework and working steps of grey Markov model and cluster analysis. To provide the theoretical basis for the related research. Finally, based on the "realized" volatility time series of Shanghai Stock Exchange Index and Shenzhen Stock Exchange Index in the domestic financial market, The grey Markov model is used to predict the financial fluctuation and the cluster analysis method is used to classify the financial fluctuation sequence of the existing financial market, so that the investors can understand the financial market in all aspects. Make rational investment according to your risk preference. This paper is only a part of the research work of the National Natural Science Foundation of China, "Research on Financial volatility based on symbolic time Series Analysis" (item No.: 70971097).
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F832.5;F224

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 房振明,王春峰;上海股票市場收益日內(nèi)效應(yīng)的研究[J];北京理工大學(xué)學(xué)報(bào)(社會(huì)科學(xué)版);2004年03期

2 王春峰;張蕊;房振明;李曄;;高頻數(shù)據(jù)下投資組合風(fēng)險(xiǎn)預(yù)測模型比較[J];系統(tǒng)工程;2007年03期

3 佟光霽;張林;;基于灰色馬爾科夫模型的農(nóng)民收入質(zhì)與量預(yù)測[J];商業(yè)研究;2012年09期

4 王禎;周溪召;;平面信號交叉口綜合服務(wù)水平的灰色定權(quán)聚類分析[J];科技和產(chǎn)業(yè);2013年08期

5 劉宗明;賈志絢;李興莉;;基于灰色馬爾科夫鏈模型的交通量預(yù)測[J];華東交通大學(xué)學(xué)報(bào);2012年01期

6 熊正德;張潔;;“已實(shí)現(xiàn)”波動(dòng)率理論研究與評價(jià)[J];湖南大學(xué)學(xué)報(bào)(社會(huì)科學(xué)版);2007年04期

7 昝勝鋒;行為金融與我國股票價(jià)格異常波動(dòng)[J];經(jīng)濟(jì)與管理;2004年07期

8 苗曉宇;;上證180指數(shù)已實(shí)現(xiàn)波動(dòng)率測度與特性分析——基于股改前后數(shù)據(jù)的對比[J];經(jīng)濟(jì)論壇;2011年12期

9 梁麗珍;王茂斌;孔東民;;交易沖擊與資產(chǎn)的非對稱波動(dòng):基于“已實(shí)現(xiàn)波動(dòng)率”[J];金融評論;2010年03期

10 丁林江;;時(shí)間序列方法和衍生品定價(jià)模型在套期保值中的應(yīng)用與績效比較[J];金融與經(jīng)濟(jì);2011年01期

本文編號：1890989