本文關(guān)鍵詞：基于高頻金融數(shù)據(jù)的已實現(xiàn)賦權(quán)中位數(shù)方法及其應(yīng)用　出處：《重慶理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 中位數(shù)已實現(xiàn)波動率(MedRV) 已實現(xiàn)賦權(quán)中位數(shù)波動率(WMedRV) 分?jǐn)?shù)階自回歸移動平均模型(ARFIMA)

【摘要】：金融市場信息連續(xù)影響著證券市場價格的運動過程,因此數(shù)據(jù)采集的離散程度會導(dǎo)致信息丟失的程度。但隨著存儲和計算技術(shù)的快速發(fā)展,使采集市場實時交易的飽含豐富信息的高頻數(shù)據(jù)成為可能,所以對高頻數(shù)據(jù)的度量與應(yīng)用逐漸成為金融分析領(lǐng)域的重要趨勢之一。金融資產(chǎn)收益波動率的度量是風(fēng)險評估的核心,它直接決定著對風(fēng)險管理的有效識別。常見的風(fēng)險度量方法是在值風(fēng)險法(VaR),且計算在值風(fēng)險(VaR)的模型也在不斷完善,國內(nèi)外學(xué)者對已有的在值風(fēng)險法(VaR)博采眾長,先后提出各種風(fēng)險度量模型。本文旨在：通過理論分析尋找較優(yōu)的風(fēng)險度量模型；比較我國深市和滬市兩個證券市場間的異同，，其創(chuàng)新點如下： 結(jié)合“已實現(xiàn)波動率(RV)、已實現(xiàn)二次冪變差(BV)、已實現(xiàn)三次冪變差(TV)、已實現(xiàn)中位數(shù)波動率(MedRV)”理論,提出了包含已實現(xiàn)中位數(shù)波動率(MedRV)和已實現(xiàn)賦權(quán)波動率(RRV)的已實現(xiàn)賦權(quán)中位數(shù)波動率(WMedRV),并證明了該波動率的的無偏性和最小方差性;通過比較不同波動率的描述統(tǒng)計量,證明了該波動率具有良好的穩(wěn)定性。最后將不同的已實現(xiàn)波動率度量方法應(yīng)用于我國兩個證券市場的VaR值計算。 另外，為了能夠通過對比來觀察已實現(xiàn)賦權(quán)中位數(shù)波動率(WMedRV)方法的有效性,本文設(shè)計了經(jīng)典的VaR方法在我國兩個證券市場中的應(yīng)用。
[Abstract]:Financial market information continuously affects the movement of the stock market price, so the discrete degree of data acquisition will lead to the degree of information loss. However, with the rapid development of storage and computing technology. It is possible to collect high-frequency data with rich information for real-time trading in the market. Therefore, the measurement and application of high-frequency data has gradually become one of the important trends in the field of financial analysis. The measurement of volatility of financial assets returns is the core of risk assessment. It directly determines the effective identification of risk management. Domestic and foreign scholars have put forward a variety of risk measurement models. The purpose of this paper is to find a better risk measurement model through theoretical analysis; Comparing the similarities and differences between Shenzhen and Shanghai stock markets, the innovations are as follows: Based on the theory of "realized fluctuation rate (RV), second power variation difference (BV), third power variation difference (TVV) and median fluctuation rate (MedRV)". The realized weighted median volatility rate (WMedRV) including realized median volatility (MedRV) and realized weighted volatility (RRV) is proposed. The unbias and minimum variance of the volatility are proved. It is proved that the volatility has good stability by comparing the description statistics of different volatility. Finally, different realized volatility measurement methods are applied to the calculation of VaR value in two stock markets in China. In addition, in order to observe the effectiveness of the weighted median volatility (WMedRV) method by comparison, this paper designs the application of the classical VaR method in two securities markets in China.
【學(xué)位授予單位】：重慶理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F830.9;F224

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