本文選題：中國(guó)出口集裝箱運(yùn)價(jià)指數(shù)　切入點(diǎn)：小波分析　出處：《大連海事大學(xué)》2013年碩士論文

【摘要】：作為國(guó)際貿(mào)易的派生市場(chǎng),集裝箱班輪運(yùn)輸市場(chǎng)受世界經(jīng)濟(jì)的影響十分嚴(yán)重,后金融危機(jī)時(shí)期的集裝箱班輪運(yùn)輸市場(chǎng)運(yùn)價(jià)備受關(guān)注。由于集裝箱運(yùn)輸市場(chǎng)受到多種因素的影響,由中國(guó)出口集裝箱運(yùn)價(jià)指數(shù)(CCFI)的歷史數(shù)據(jù)構(gòu)成的時(shí)間序列信號(hào)中含有很多噪聲。因此,本文將小波分析和ARIMA模型相結(jié)合,運(yùn)用小波分析提取運(yùn)價(jià)指數(shù)信號(hào)中的低頻成分,并剔除高頻成分,從而使得ARIMA模型能夠更好地進(jìn)行擬合及預(yù)測(cè)。 本文開(kāi)篇闡述了論文的研究背景、研究意義、國(guó)內(nèi)外研究現(xiàn)狀以及研究的主要內(nèi)容和方法。其次分別從集裝箱運(yùn)輸市場(chǎng)格局、集裝箱運(yùn)輸船舶運(yùn)營(yíng)、集裝箱運(yùn)輸航線布局以及集裝箱運(yùn)價(jià)概述等四個(gè)方面分析了集裝箱運(yùn)輸市場(chǎng)的發(fā)展與現(xiàn)狀。接下來(lái)簡(jiǎn)單地介紹了國(guó)內(nèi)外運(yùn)價(jià)指數(shù)及中國(guó)出口集裝箱運(yùn)價(jià)指數(shù)(CCFI)。然后介紹了小波理論的發(fā)展足跡與小波分析的理論基礎(chǔ),隨后對(duì)中國(guó)出口集裝箱運(yùn)價(jià)指數(shù)(CCFI)的原始數(shù)據(jù)進(jìn)行了去噪處理。緊接著介紹了時(shí)間序列及其相關(guān)概念以及時(shí)間序列模型,繼而根據(jù)經(jīng)過(guò)小波分析并去噪處理后的中國(guó)出口集裝箱運(yùn)價(jià)指數(shù)(CCFI)的時(shí)間序列數(shù)據(jù),建立了ARIMA模型,對(duì)中國(guó)出口集裝箱運(yùn)價(jià)指數(shù)(CCFI)進(jìn)行了預(yù)測(cè),并對(duì)預(yù)測(cè)結(jié)果進(jìn)行了分析。最后對(duì)全文進(jìn)行了總結(jié),針對(duì)不足之處,對(duì)今后的研究進(jìn)行了展望。 根據(jù)經(jīng)過(guò)小波分析并處理后的中國(guó)出口集裝箱運(yùn)價(jià)指數(shù)(CCFI)的時(shí)間序列數(shù)據(jù),建立ARIMA模型,有效地提升了ARIMA模型的擬合度及預(yù)測(cè)效果。本文的研究將對(duì)船公司、貨主、代理等航運(yùn)相關(guān)者了解集裝箱班輪運(yùn)輸市場(chǎng)形勢(shì),判斷市場(chǎng)走向,及時(shí)做出相應(yīng)調(diào)整,規(guī)避市場(chǎng)風(fēng)險(xiǎn)提供有益的參考。
[Abstract]:As a derivative market of international trade, the container liner transportation market is seriously affected by the world economy.Because the container transportation market is affected by many factors, the time series signal composed of the historical data of China's export container freight index CCFI contains a lot of noise.Therefore, this paper combines wavelet analysis with ARIMA model, using wavelet analysis to extract the low frequency component of the freight rate index signal, and eliminating the high frequency component, so that the ARIMA model can fit and predict better.At the beginning of this paper, the research background, research significance, domestic and foreign research status, main contents and methods of research are described.Secondly, the development and present situation of container transport market are analyzed from four aspects: container transport market pattern, container shipping vessel operation, container shipping route layout and container freight rate overview.Then it briefly introduces the domestic and foreign freight price index and China's export container price index CCFI.Then, the development footprint of wavelet theory and the theoretical basis of wavelet analysis are introduced, and then the original data of China Export Container Freight Index (CCFI) are de-noised.Then it introduces the time series and its related concepts as well as the time series model. Then according to the time series data of China's export container price index (CCFI) after wavelet analysis and de-noising, the ARIMA model is established.This paper forecasts China's export container price index (CCFI) and analyzes the forecast results.In the end, the paper summarizes the whole paper and looks forward to the future research aiming at the deficiency.According to the time series data of China Export Container Freight Index (CCFI) after wavelet analysis, the ARIMA model is established, which can effectively improve the fit degree and prediction effect of the ARIMA model.The research in this paper will provide a useful reference for shipping companies, shippers, agents and other shipping related parties to understand the market situation of container liner transportation, judge the market trend, make corresponding adjustments in time, and avoid market risks.
【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：U695.22

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