本文選題：國(guó)際油輪運(yùn)價(jià)指數(shù)　切入點(diǎn)：隨機(jī)波動(dòng)模型(SV)　出處：《上海交通大學(xué)》2012年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：近年來(lái),作為體現(xiàn)國(guó)際油輪運(yùn)輸市場(chǎng)運(yùn)價(jià)走勢(shì)的運(yùn)價(jià)指數(shù)波動(dòng)越來(lái)越劇烈,而航運(yùn)界對(duì)運(yùn)價(jià)指數(shù)波動(dòng)風(fēng)險(xiǎn)的研究主要集中在干散貨市場(chǎng),傳統(tǒng)的油輪運(yùn)價(jià)指數(shù)波動(dòng)風(fēng)險(xiǎn)度量方法已經(jīng)無(wú)法滿(mǎn)足新競(jìng)爭(zhēng)形勢(shì)下的要求,因此從理論上尋找更優(yōu)的模型來(lái)度量國(guó)際油輪運(yùn)價(jià)指數(shù)波動(dòng)風(fēng)險(xiǎn),更加充分的認(rèn)識(shí)其波動(dòng)性,從而為油輪運(yùn)輸企業(yè)進(jìn)行風(fēng)險(xiǎn)控制提供更好理論依據(jù)顯得十分重要。 隨機(jī)波動(dòng)(SV)模型在刻畫(huà)金融序列波動(dòng)特征方面優(yōu)于傳統(tǒng)的廣義自回歸條件異方差(GARCH)模型,因此本文嘗試引入SV模型來(lái)刻畫(huà)國(guó)際油輪運(yùn)價(jià)指數(shù)波動(dòng)及其特征,結(jié)合廣義帕累托分布GPD分布的極值理論,建立起度量國(guó)際油輪運(yùn)價(jià)指數(shù)波動(dòng)風(fēng)險(xiǎn)的動(dòng)態(tài)VaR模型,主要內(nèi)容如下: 首先主要介紹了國(guó)際油輪運(yùn)價(jià)指數(shù)的概況、構(gòu)成、計(jì)算和主要特征,指出油輪運(yùn)價(jià)指數(shù)波動(dòng)的尖峰厚尾性,波動(dòng)集聚性,長(zhǎng)記憶性和持續(xù)性,以及對(duì)正、負(fù)沖擊產(chǎn)生不同回應(yīng)的杠桿效應(yīng),為后文做模型的對(duì)比分析奠定基礎(chǔ)。 其次從理論上分別介紹了三類(lèi)SV和GARCH模型,即標(biāo)準(zhǔn)模型,厚尾模型和杠桿模型,重點(diǎn)闡述了SV模型參數(shù)估計(jì)的MCMC方法和模型判別的DIC準(zhǔn)則,在此基礎(chǔ)上結(jié)合基于GPD的極值理論和VaR方法建立起動(dòng)態(tài)風(fēng)險(xiǎn)度量模型,并給出模型適用性的失敗率驗(yàn)證方法。 最后選取一定數(shù)量BDTI和BCTI指數(shù)進(jìn)行實(shí)證研究,分別構(gòu)建SV模型和GARCH模型,并對(duì)兩模型進(jìn)行對(duì)比分析,指出SV類(lèi)模型在刻畫(huà)油輪運(yùn)價(jià)指數(shù)波動(dòng)特征方面的優(yōu)勢(shì),得出L-SV模型為最優(yōu)模型,而T分布條件下,GARCH-T模型最優(yōu)的結(jié)論,后采用L-SV模型進(jìn)行最終的動(dòng)態(tài)VaR值計(jì)算,失敗率驗(yàn)證結(jié)果表明L-SV模型能夠很好的度量出油輪運(yùn)輸市場(chǎng)的波動(dòng)風(fēng)險(xiǎn),特別適用于原油運(yùn)輸市場(chǎng),并且國(guó)際原油運(yùn)輸市場(chǎng)的波動(dòng)風(fēng)險(xiǎn)要大于國(guó)際成品油運(yùn)輸市場(chǎng)。
[Abstract]:In recent years, as a reflection of the trend of the international tanker transportation market, the fluctuation of the freight rate index is becoming more and more intense, while the research on the risk of the fluctuation of the freight rate index in the shipping industry is mainly focused on the dry bulk cargo market. The traditional risk measurement method of oil tanker price index fluctuation has been unable to meet the requirements of the new competitive situation, so we can find a better model to measure the fluctuation risk of international tanker price index in theory, and fully understand its volatility. Therefore, it is very important to provide better theoretical basis for oil tanker transportation enterprises to carry out risk control. The stochastic volatility model is superior to the generalized autoregressive conditional heteroscedasticity (GARCH) model in describing the volatility characteristics of financial series. Therefore, this paper attempts to introduce SV model to describe the volatility and its characteristics of international tanker freight index. Combined with the extreme value theory of the generalized Pareto distribution GPD distribution, a dynamic VaR model is established to measure the volatility risk of the international tanker price index. The main contents are as follows:. First of all, the general situation, composition, calculation and main characteristics of the international tanker freight index are introduced. It is pointed out that the peak, thick tail, agglomeration, long memory and persistence of the fluctuation of the oil tanker price index are positive. The leverage effect of different responses is produced by negative shock, which lays a foundation for the comparative analysis of the later models. Secondly, three kinds of SV and GARCH models are introduced theoretically, that is, standard model, thick tail model and lever model. The MCMC method of SV model parameter estimation and the DIC criterion of model discrimination are discussed in detail. On this basis, a dynamic risk measurement model is established by combining the extreme value theory based on GPD and the VaR method, and the failure rate verification method for the applicability of the model is given. Finally, a certain number of BDTI and BCTI indices are selected for empirical research, SV model and GARCH model are constructed, and the two models are compared and analyzed, and the advantages of SV model in characterizing the fluctuation characteristics of tanker price index are pointed out. The conclusion that L-SV model is the optimal model and the GARCH-T model is optimal under the condition of T distribution is obtained. Then the L-SV model is used to calculate the final dynamic VaR value. The result of failure rate verification shows that the L-SV model can measure the fluctuation risk of tanker transportation market very well. It is especially suitable for the crude oil transportation market, and the fluctuation risk of the international crude oil transportation market is greater than that of the international refined oil transportation market.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類(lèi)號(hào)】：F551;F224

【引證文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前2條

1 梁瑋;上海出口集裝箱運(yùn)價(jià)指數(shù)衍生品適用性及估價(jià)研究[D];上海交通大學(xué);2013年

2 尹棟;國(guó)際油輪運(yùn)輸市場(chǎng)的周期波動(dòng)及預(yù)測(cè)[D];大連海事大學(xué);2013年

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本文編號(hào)：1588460