【摘要】：隨著我國(guó)匯率在兩次匯改之后由盯住美元制度走向更為市場(chǎng)化的浮動(dòng)外匯管理制度，對(duì)其市場(chǎng)風(fēng)險(xiǎn)的研究顯得尤為必要。本文以美元兌人民幣匯率作為研究對(duì)象，內(nèi)容包括以下四個(gè)方面。 首先，利用長(zhǎng)記憶性參數(shù)估計(jì)方法發(fā)現(xiàn)人民幣美元匯率存在顯著的長(zhǎng)記憶特征。從結(jié)構(gòu)突變、頻率結(jié)構(gòu)和時(shí)間聚合三個(gè)角度考察該市場(chǎng)長(zhǎng)記憶特征的根源，得到以下結(jié)論：（1）結(jié)構(gòu)突變是引起人民幣匯率市場(chǎng)長(zhǎng)記憶特征的一大原因；（2）低頻序列是支撐長(zhǎng)記憶特征的根源，高頻意味著隨機(jī)擾動(dòng)；（3）長(zhǎng)記憶特征存在期限結(jié)構(gòu)特征，即不同周期的數(shù)據(jù)呈現(xiàn)不同的長(zhǎng)記憶動(dòng)態(tài)特征。 其次，為了尋找最優(yōu)的人民幣匯率風(fēng)險(xiǎn)預(yù)測(cè)模型，本文以回測(cè)檢驗(yàn)方法作為評(píng)價(jià)方法，介紹6種刻畫波動(dòng)聚集性、非對(duì)稱性或長(zhǎng)記憶性的風(fēng)險(xiǎn)模型，同時(shí)引入FHS技術(shù)、EVT技術(shù)和EVT-SKT等進(jìn)行全面分析。結(jié)果表明：FIGARCH類模型通過檢驗(yàn)且檢驗(yàn)值處于低位，，但回測(cè)方法無法有效區(qū)別波動(dòng)模型的優(yōu)劣性以及優(yōu)劣程度。 再次，基于傳統(tǒng)回測(cè)方法的不足，本文綜合監(jiān)管成本和超額虧損沖擊風(fēng)險(xiǎn)的概念，構(gòu)造一個(gè)新的風(fēng)險(xiǎn)評(píng)價(jià)指標(biāo)Indic。應(yīng)用結(jié)果表明：Indic指標(biāo)可以提供更為詳細(xì)的局部動(dòng)態(tài)信息，且結(jié)合SPA檢驗(yàn)方法能有效區(qū)別精選長(zhǎng)記憶波動(dòng)模型的優(yōu)劣性和優(yōu)劣程度，對(duì)風(fēng)險(xiǎn)度量模型擇優(yōu)具有一定的指導(dǎo)意義。 最后，目前的風(fēng)險(xiǎn)度量算法缺乏靈活與可控性，模型之間的選擇非此即彼。本文基于Boorstraping算法與模型樣本重構(gòu)的思想，將FHS技術(shù)和EVT技術(shù)相結(jié)合，獲得關(guān)于VaR的穩(wěn)健統(tǒng)計(jì)分布，同時(shí)設(shè)置分位數(shù)水平為滑點(diǎn)，構(gòu)造一類改進(jìn)免疫遺傳算法--Indic-SPA檢驗(yàn)方法尋找最優(yōu)的風(fēng)險(xiǎn)度量模型。結(jié)果表明：改進(jìn)的算法能以最低的Indic成本獲得風(fēng)險(xiǎn)規(guī)避效用。
[Abstract]:With the change of exchange rate from dollar pegging system to more market-oriented floating exchange rate management system, it is necessary to study its market risk. This paper takes the exchange rate of US dollar to RMB as the object of study, including the following four aspects. First, the long memory parameter estimation method is used to find that the RMB dollar exchange rate has significant long memory characteristics. From the three angles of structural mutation, frequency structure and time aggregation, the causes of long memory characteristics in this market are investigated, and the following conclusions are obtained: (1) structural mutation is one of the major causes of long memory characteristics in RMB exchange rate market; (2) low frequency sequence is the root of supporting long memory feature, high frequency means random disturbance; (3) long memory feature exists term structure feature, that is, the data of different period presents different long memory dynamic feature. Secondly, in order to find the best prediction model of RMB exchange rate risk, this paper introduces six risk models which describe volatility aggregation, asymmetry or long memory, and introduces FHS technology. EVT technology and EVT-SKT were comprehensively analyzed. The results show that the FIGARCH model is tested and the test value is low, but the backmeasure method can not effectively distinguish the merits and demerits of the volatility model. Thirdly, based on the deficiency of the traditional method, this paper synthesizes the concepts of supervision cost and excess loss impact risk, and constructs a new risk evaluation index, Indic.. The application results show that the Indic index can provide more detailed local dynamic information, and the combination of SPA test method can effectively distinguish the advantages and disadvantages of the selected long-memory volatility model, which has a certain guiding significance for the risk measurement model to choose the best. Finally, the current risk measurement algorithm lacks flexibility and controllability, and the choice between models is either or. In this paper, based on the idea of Boorstraping algorithm and model sample reconstruction, the robust statistical distribution of VaR is obtained by combining FHS technique with EVT technique, and the quantile level is set as the sliding point. An improved immune genetic algorithm (Indic-SPA test) is constructed to find the best risk measurement model. The results show that the improved algorithm can obtain risk aversion utility at the lowest Indic cost.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP301.6;F832.6

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本文編號(hào)：2364077