本文選題：中小板 + 創(chuàng)業(yè)板�。� 參考：《中南大學(xué)》2013年碩士論文

【摘要】：對金融市場風(fēng)險的測量一直是金融理論界和實業(yè)界都非常關(guān)心的課題,如果能夠?qū)κ袌鲲L(fēng)險進行預(yù)測,便能夠從中獲得可觀的收益,于是,對市場價格的預(yù)測便顯得非常重要。本文在總結(jié)近幾年來國內(nèi)外對高低頻時間序列研究的基礎(chǔ)上,以我國中小板、創(chuàng)業(yè)板1分鐘、5分鐘、15分鐘、30分鐘、60分鐘和每日的股票指數(shù)數(shù)據(jù)為研究基礎(chǔ),從對數(shù)收益率及其波動率的角度出發(fā),在運用金融時序分析的基礎(chǔ)上進一步改進模型,通過建立更具有實際應(yīng)用意義的HAR-WRV-GARCH-VaR模型,重點對中國金融市場的中小板、創(chuàng)業(yè)板的高頻時序數(shù)據(jù)進行實證分析,并得出相關(guān)結(jié)論。 本文主要從以下幾個方面進行研究：首先,對我國中小板和創(chuàng)業(yè)板兩市的高頻時間序列進行初步統(tǒng)計分析,發(fā)現(xiàn)我國中小板、創(chuàng)業(yè)板的高頻時間序列具有許多與低頻時間序列不同的特征,因此原有可以在低頻時間序列研究運用的模型和研究方法并不能完全運用于對高頻時間序列的研究。其次,針對我國中小板、創(chuàng)業(yè)板市場指數(shù)進行了ARIMA(1,1,1,)模型的建立及求解,并對模型該模型的效果進行分析,發(fā)現(xiàn)該模型的效果不佳。繼而,通過引入了長記憶性這一概念,逐步對上述模型進行深層次改進,提出了HAR-WRV-GARCH模型。緊接著以創(chuàng)業(yè)板為例,對我國創(chuàng)業(yè)板市場股票波動率進行了實證研究,并建立了HAR-WRV-GARCH(1,1)模型,然后對該模型進行了求解。最后在總結(jié)前面模型的基礎(chǔ)上,建立HAR-WRV-GARCH-VaR模型,并以創(chuàng)業(yè)板市場為例,得出了創(chuàng)業(yè)板每日VaR值的計算公式,使得本文提出的模型具有了實際應(yīng)用的價值及意義。
[Abstract]:The measurement of financial market risk has always been a topic of great concern to the financial theorists and businessmen. If we can predict the market risk, we can get considerable income from it. Therefore, it is very important to predict the market price. On the basis of summing up the research on high and low frequency time series at home and abroad in recent years, this paper studies the stock index data of China's small and medium sized boards, gem's 1 minute / 5 min / 15 min / 30 min / 60 min and daily stock index. From the point of view of logarithmic rate of return and its volatility, the model is further improved on the basis of financial time series analysis. Through the establishment of HAR-WRV-GARCH-VaR model with more practical significance, the emphasis is placed on the small and medium-sized boards of Chinese financial market. The high frequency time series data of gem are analyzed empirically, and the relevant conclusions are drawn. This article mainly carries on the research from the following several aspects: first, carries on the preliminary statistical analysis to our country small and medium-sized board and the growth enterprise board two cities high frequency time series, discovered our country small and medium-sized board, The high frequency time series of gem have many different characteristics from those of low frequency time series, so the models and research methods that can be used in the study of low frequency time series can not be fully applied to the study of high frequency time series. Secondly, aiming at the small and medium scale board of our country, the market index of gem is established and solved by Arima 1 / 1) model, and the effect of the model is analyzed, and it is found that the effect of this model is not good. Then, by introducing the concept of long memory, the HAR-WRV-GARCH model is proposed by improving the above model step by step. Then taking the gem as an example, this paper makes an empirical study on the volatility of the gem in China, and establishes the HAR-WRV-GARCH1) model, and then solves the model. Finally, on the basis of summarizing the previous models, the HAR-WRV-GARCH-VaR model is established, and taking the gem market as an example, the calculation formula of the daily VaR value of the gem is obtained, which makes the model presented in this paper have practical application value and significance.
【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.51;F224

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