本文選題：金融系統(tǒng)風(fēng)險(xiǎn) + 預(yù)警系統(tǒng)　； 參考：《復(fù)旦大學(xué)》2013年碩士論文

【摘要】：金融世界變幻莫測(cè)——每一天都存在新的金融產(chǎn)品、新的金融條例法規(guī)以及新的金融風(fēng)險(xiǎn)不斷涌入金融系統(tǒng)；而對(duì)于金融市場(chǎng)迅猛發(fā)展的新興國(guó)家中國(guó)而言,這些尤其值得重視。宏觀金融系統(tǒng)的安全運(yùn)行關(guān)系到整個(gè)國(guó)家和社會(huì)的穩(wěn)定,如何找到蘊(yùn)藏在金融系統(tǒng)、宏觀經(jīng)濟(jì)系統(tǒng)中的金融風(fēng)險(xiǎn)因子,以及如何根據(jù)這些金融風(fēng)險(xiǎn)因子有效捕捉宏觀金融系統(tǒng)風(fēng)險(xiǎn)信息并構(gòu)建行之有效的風(fēng)險(xiǎn)預(yù)警系統(tǒng)可以對(duì)宏觀金融風(fēng)險(xiǎn)的發(fā)生防患于未然,而這也正是本論文的主旨所在。 論文的中心思想是分別構(gòu)建兩個(gè)模型對(duì)宏觀金融系統(tǒng)風(fēng)險(xiǎn)程度進(jìn)行測(cè)量和預(yù)測(cè)——即預(yù)警系統(tǒng)的構(gòu)建。在國(guó)內(nèi)和國(guó)際學(xué)術(shù)界,曾有多位知名學(xué)者在該領(lǐng)域研究做出卓越貢獻(xiàn),他們提出并試驗(yàn)了諸多模型,這些都將會(huì)在論文伊始的文獻(xiàn)綜述中逐一、簡(jiǎn)要回顧。本論文創(chuàng)新采用了因子分析進(jìn)行宏觀金融系統(tǒng)風(fēng)險(xiǎn)測(cè)量,進(jìn)而又采用BP神經(jīng)網(wǎng)絡(luò)分析進(jìn)行宏觀金融系統(tǒng)風(fēng)險(xiǎn)預(yù)測(cè)及預(yù)警系統(tǒng)構(gòu)建,兩個(gè)模型相輔相成、相得益彰更是本論文的亮點(diǎn)之一。兩個(gè)模型中,因子分析相對(duì)傳統(tǒng),可幫助學(xué)者更準(zhǔn)確挖掘宏觀金融系統(tǒng)的風(fēng)險(xiǎn)因子,同時(shí)實(shí)現(xiàn)輸入變量的降維；而B(niǎo)P神經(jīng)網(wǎng)絡(luò)則是較為新興的統(tǒng)計(jì)研究工具,將其運(yùn)用于金融系統(tǒng)風(fēng)險(xiǎn)的測(cè)量和預(yù)警系統(tǒng)的構(gòu)建在學(xué)術(shù)界更是首屈一指,其在非線性函數(shù)擬合中的卓越表現(xiàn)使其成為金融數(shù)據(jù)分析工具的不二之選。本論文是傳統(tǒng)模型和新興模型的結(jié)合體,但無(wú)論傳統(tǒng)還是新興,模型產(chǎn)生的測(cè)量和預(yù)測(cè)結(jié)果與現(xiàn)實(shí)貼切、令人信服。 構(gòu)建模型的目的在于更明晰地理解現(xiàn)實(shí),然而模型僅僅是手段,而非目的；因此,基于模型的輸出結(jié)果,論文進(jìn)一步闡述宏觀金融體系和宏觀金融子體系的風(fēng)險(xiǎn)因子的經(jīng)濟(jì)意義,其測(cè)量和預(yù)測(cè)結(jié)果的實(shí)際意義和指導(dǎo)性作用。 論文的結(jié)尾部分闡述了論文中所用模型的不完善之處,提出政策建議以增強(qiáng)宏觀金融系統(tǒng)風(fēng)險(xiǎn)預(yù)警系統(tǒng)的有效性、提高其效率。政策建議主要從改善數(shù)據(jù)搜集流程、完善金融數(shù)據(jù)信息化和信息共享系統(tǒng)、建立不同時(shí)域和區(qū)域的預(yù)警機(jī)制三個(gè)方面展開(kāi)討論。
[Abstract]:The financial world is changing-every day there are new financial products, new financial regulations and new financial risks flowing into the financial system, and for China, where financial markets are booming, These are especially worthy of attention. The safe operation of the macro-financial system is related to the stability of the whole country and society. How to find the financial risk factors in the financial system and macroeconomic system, And how to effectively capture the macro financial system risk information and build an effective risk early warning system according to these financial risk factors can prevent the occurrence of macro financial risks, and this is the main purpose of this paper. The main idea of this paper is to construct two models to measure and predict the risk of macro-financial system-namely the construction of early-warning system. In domestic and international academic circles, many famous scholars have made outstanding contributions in this field. They have proposed and tested many models, which will be briefly reviewed one by one in the literature review at the beginning of this paper. In this paper, factor analysis is used to measure the risk of macro financial system, and BP neural network is used to predict the risk of macro financial system and build an early warning system. The two models complement each other. Complementing each other is one of the highlights of this paper. In the two models, factor analysis is relatively traditional, which can help scholars to excavate the risk factors of macro financial system more accurately and to reduce the dimension of input variables at the same time, while BP neural network is a relatively new statistical research tool. Its application in the measurement of financial system risk and the construction of early warning system is even more important in academic circles, and its excellent performance in nonlinear function fitting makes it a good choice for financial data analysis tools. This paper is a combination of the traditional model and the emerging model, but whether traditional or emerging, the results of measurement and prediction produced by the model are cogent with reality. The model is built to understand reality more clearly, but the model is only a means, not an end; therefore, based on the output of the model, The paper further expounds the economic significance of the risk factors of the macro-financial system and the macro-financial sub-system, and the practical significance and instructive effect of the measurement and prediction results. At the end of the paper, the author expounds the imperfections of the models used in the paper, and puts forward some policy suggestions to enhance the effectiveness and efficiency of the risk early warning system of the macro financial system. The policy suggestions are mainly discussed from three aspects: improving the data collection process, perfecting the financial data information and information sharing system, and establishing the early warning mechanism in different time domain and region.
【學(xué)位授予單位】：復(fù)旦大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832

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相關(guān)期刊論文 前2條

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本文編號(hào)：1927903