本文選題：中位數(shù)估計　切入點：AR(1)模型　出處：《中國礦業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：時間序列分析是統(tǒng)計學(xué)中一個重要分支,近些年來各種時間序列模型在各個領(lǐng)域被廣泛用于數(shù)據(jù)分析預(yù)測,特別在金融領(lǐng)域.AR模型是最早的金融時間序列模型,對AR模型自回歸參數(shù)估計方法很多,估計的效果也不盡相同.而GARCH模型可以說是為金融領(lǐng)域量身定做的時間序列模型,不同分布下的GARCH類模型對股市刻畫及風(fēng)險價值預(yù)測中效果和特點不盡相同.因此,對AR模型和GARCH類模型預(yù)測研究具有重要意義.本文主要研究改進(jìn)后的AR(1)模型預(yù)測區(qū)間在模擬中的效果及對AR(1)模型參數(shù)估計方法及預(yù)測研究,同時利用不同GARCH模型對深圳綜指和上證指數(shù)進(jìn)行實證研究.首先,對AR(1)模型自回歸參數(shù)采用中位數(shù)估計構(gòu)造該模型預(yù)測區(qū)間,一種是不帶單位根檢驗的,另一種帶單位根檢驗.然后進(jìn)行蒙特卡羅模擬實驗,通過比較發(fā)現(xiàn)樣帶單位根檢驗的預(yù)測區(qū)間無論從區(qū)間覆蓋率還是平均長度方面效果都好一些.接著在對AR(1)模型采用不同參數(shù)估計方法進(jìn)行建模分析,進(jìn)而采用不同預(yù)測方法進(jìn)行預(yù)測,發(fā)現(xiàn)在平穩(wěn)狀態(tài)下最小二乘估計估計效果良好.其次,基于不同GARCH模型下的深市收益率研究表明該股市具有杠桿效應(yīng),通過比較發(fā)現(xiàn)EGARCH-t模型能夠很好刻畫深市收益率序列特征.同時采用不同分布下的IGARCH和TGARCH模型對上證指數(shù)進(jìn)行研究,發(fā)現(xiàn)GED分布下的TGARCH模型能夠很好的刻畫上證收益率序列特征,進(jìn)而計算出各個模型下的風(fēng)險價值,接著對計算出來的VaR進(jìn)行了Kupiec檢驗,通過檢驗可以看出GED分布下的TGARCH模型在風(fēng)險度量方面效果最好.最后,討論一下目前存在的一些相關(guān)問題及未來研究的展望.
[Abstract]:Time series analysis is an important branch of statistics. In recent years, various time series models have been widely used in data analysis and prediction, especially in the financial field. There are many methods to estimate the autoregressive parameters of AR model, and the effect of the estimation is not the same. The GARCH model can be said to be a time series model tailor-made for the financial field. GARCH models with different distributions have different effects and characteristics on the description of stock market and the prediction of risk value. It is of great significance to study AR model and GARCH model prediction. In this paper, we mainly study the effect of the prediction interval of improved ARH-1 model in simulation, and the estimation method and prediction method of ARQ1 model parameters. At the same time, different GARCH models are used to study the Shenzhen Composite Index and Shanghai Stock Exchange Index. Firstly, the median estimation is used to construct the prediction interval of ARQ1 model, one is without unit root test. Another test with unit roots. Then Monte Carlo simulation, It is found that the prediction interval of sample band unit root test is better in terms of interval coverage and average length. Then different parameter estimation methods are used to model and analyze ARG-1 model. Then different forecasting methods are used to predict, and it is found that the estimation effect of least square estimation is good in stationary state. Secondly, the deep market yield research based on different GARCH models shows that the stock market has leverage effect. It is found that the EGARCH-t model can well describe the characteristics of the yield series of Shenzhen Stock Exchange. At the same time, the IGARCH and TGARCH models under different distributions are used to study the Shanghai Stock Exchange Index. It is found that the TGARCH model under the GED distribution can well describe the characteristics of the yield series of the Shanghai Stock Exchange. Then the risk value of each model is calculated, and then the calculated VaR is tested by Kupiec. It can be seen that the TGARCH model under the GED distribution has the best effect on risk measurement. Finally, This paper discusses some related problems and prospects for future research.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F224;F832.51

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳九生;周孝華;;滬港通背景下滬港股市聯(lián)動性研究[J];北京理工大學(xué)學(xué)報(社會科學(xué)版);2017年02期

2 黃慧;;中國股市波動特征的實證研究——基于GARCH族模型[J];科技創(chuàng)業(yè)月刊;2015年23期

3 王亮;;基于條件自回歸極差模型的滬深300指數(shù)波動性分析[J];內(nèi)江師范學(xué)院學(xué)報;2015年04期

4 陳楊林;劉業(yè);;AR(p)模型參數(shù)估計方法比較和實證分析[J];南昌大學(xué)學(xué)報(理科版);2014年02期

5 徐偉浩;;滬深300股指期貨VaR-GARCH模型風(fēng)險管理研究——基于恒指期貨的比較視角[J];區(qū)域金融研究;2011年08期

6 胡大紅;姚志鵬;;自相關(guān)函數(shù)在時間序列模型識別中的應(yīng)用[J];襄樊學(xué)院學(xué)報;2011年05期

7 侯哲;陳麗英;;次貸危機前后信息沖擊對我國股市波動的影響分析[J];當(dāng)代經(jīng)濟;2011年01期

8 史天雄;錢錦曄;;VaR方法及其在中國股票市場的風(fēng)險度量研究[J];中國地質(zhì)大學(xué)學(xué)報(社會科學(xué)版);2010年04期

9 陳麗娟;;基于EGARCH-M模型和滬深300指數(shù)的股市風(fēng)險分析[J];東北財經(jīng)大學(xué)學(xué)報;2010年02期

10 文忠橋;馮德海;;金融危機下我國股票市場波動非對稱性的實證研究[J];大慶師范學(xué)院學(xué)報;2010年02期

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