本文選題：上市國(guó)有銀行 + 長(zhǎng)期風(fēng)險(xiǎn)　； 參考：《遼寧大學(xué)》2017年碩士論文

【摘要】：中國(guó)與世界經(jīng)濟(jì)的聯(lián)系越來(lái)越緊密,這在促進(jìn)金融業(yè)之間相互交流取長(zhǎng)補(bǔ)短的基礎(chǔ)上,也促進(jìn)了國(guó)際銀行業(yè)的發(fā)展。但是,隨之而來(lái)的風(fēng)險(xiǎn)也日趨加劇,尤其是2008年金融危機(jī)以來(lái),給世界金融業(yè)敲響了警鐘。國(guó)際金融的自由化和金融的不斷開放使得銀行作為金融體系的核心風(fēng)險(xiǎn)不斷加劇,很容易由于某個(gè)國(guó)家區(qū)域性風(fēng)險(xiǎn)引發(fā)整個(gè)世界的金融危機(jī)。因此,如何有效的防范和規(guī)避銀行風(fēng)險(xiǎn),并制定策略減少銀行風(fēng)險(xiǎn)對(duì)于實(shí)體經(jīng)濟(jì)的影響,已經(jīng)成為中國(guó)各個(gè)監(jiān)管機(jī)構(gòu)關(guān)注的焦點(diǎn)。加之中國(guó)處于經(jīng)濟(jì)轉(zhuǎn)型重要時(shí)期,如何防范國(guó)際乃至國(guó)內(nèi)銀行之間的風(fēng)險(xiǎn)傳染,已經(jīng)成為銀行業(yè)風(fēng)險(xiǎn)檢測(cè)的重要組成部分。首先,文章以中國(guó)工商銀行為例,利用銀行日收益率數(shù)據(jù)對(duì)工商銀行的短期風(fēng)險(xiǎn)值進(jìn)行模擬。在分析中,對(duì)數(shù)據(jù)是否滿足ARCH類模型進(jìn)行分析,最后分析得出符合ARCH類模型要求。最終對(duì)ARCH、GARCH、EGARCH等進(jìn)行模擬,并列表分析了各個(gè)模型處理數(shù)據(jù),最終選取EGARCH模型的整個(gè)過(guò)程,得出具體的風(fēng)險(xiǎn)值。在分析中,我們以中國(guó)五家國(guó)有上市銀行作為研究對(duì)象,分析各個(gè)銀行股票日收益、上證指數(shù)和銀行指數(shù)的長(zhǎng)短期風(fēng)險(xiǎn)。其次,文章利用模型分析影響銀行長(zhǎng)期風(fēng)險(xiǎn)的各個(gè)宏觀經(jīng)濟(jì)影響因素。在總結(jié)前人分析基礎(chǔ)和結(jié)合當(dāng)今經(jīng)濟(jì)發(fā)展現(xiàn)狀基礎(chǔ)上,選取了六個(gè)宏觀經(jīng)濟(jì)指標(biāo),并構(gòu)建了向量自回歸模型,對(duì)影響銀行長(zhǎng)期風(fēng)險(xiǎn)波動(dòng)的宏觀經(jīng)濟(jì)影響因素進(jìn)行實(shí)證分析。最后,具體分析各個(gè)變量對(duì)風(fēng)險(xiǎn)的具體影響,以及傳導(dǎo)過(guò)程。最后,通過(guò)對(duì)五家銀行進(jìn)行模擬和銀行業(yè)長(zhǎng)期風(fēng)險(xiǎn)和宏觀影響因素進(jìn)行分析,我們可以分析風(fēng)險(xiǎn)研究結(jié)果:第一,ARCH類模型通過(guò)各個(gè)種類的比較分析,很好的解釋了自2010年至2016年的風(fēng)險(xiǎn)狀況,并很好的模擬了中國(guó)經(jīng)濟(jì)轉(zhuǎn)型時(shí)期的風(fēng)險(xiǎn)。即當(dāng)前五家上市國(guó)有銀行長(zhǎng)期風(fēng)險(xiǎn)較為穩(wěn)定,并處于國(guó)家銀監(jiān)會(huì)合理范圍內(nèi)。通過(guò)短期和長(zhǎng)期風(fēng)險(xiǎn)的分別測(cè)量,我們可以很好的應(yīng)對(duì)風(fēng)險(xiǎn),采取有針對(duì)性的措施。第二,對(duì)五大國(guó)有銀行進(jìn)行對(duì)比,風(fēng)險(xiǎn)均值相差不多,但是風(fēng)險(xiǎn)波動(dòng)情況相差很大,尤其是交通銀行,應(yīng)該加大風(fēng)險(xiǎn)防范,其他銀行根據(jù)自己實(shí)際情況進(jìn)行適當(dāng)調(diào)整,爭(zhēng)取把風(fēng)險(xiǎn)控制在合理范圍內(nèi)。最后的實(shí)證分析顯示:GDP、CPI、HP及匯率的增長(zhǎng)率對(duì)長(zhǎng)期風(fēng)險(xiǎn)影響較大,對(duì)整個(gè)經(jīng)濟(jì)運(yùn)行有較大影響。
[Abstract]:China and the world economy are more and more closely linked, which not only promotes the mutual exchange between the financial industry, but also promotes the development of the international banking industry. However, the attendant risks are becoming more and more serious, especially since the 2008 financial crisis, which has sounded the alarm bell for the world financial industry. The liberalization of international finance and the continuous opening of finance make banks as the core risk of the financial system continuously aggravated, it is easy to cause the whole world financial crisis because of the regional risk of a country. Therefore, how to effectively prevent and avoid bank risk, and formulate strategies to reduce the impact of bank risk on the real economy, has become the focus of Chinese regulators. In addition, China is in an important period of economic transition, how to prevent the risk contagion between international and domestic banks has become an important part of banking risk detection. Firstly, taking ICBC as an example, the paper simulates the short-term risk value of ICBC by using the data of daily rate of return. In the analysis, whether the data meets the ARCH class model is analyzed, and finally, it is found that the data meets the requirements of the ARCH class model. Finally, the paper simulates the EGARCH model, and analyzes the processing data of each model in parallel table. Finally, the whole process of EGARCH model is selected, and the specific risk value is obtained. In the analysis, we take five state-owned listed banks in China as the research object, and analyze the long-term and short-term risk of each bank's stock daily income, Shanghai stock index and bank index. Secondly, the paper uses the model to analyze the macro-economic factors that affect the long-term risks of banks. On the basis of summing up the previous analysis basis and combining with the present economic development situation, this paper selects six macroeconomic indicators, and constructs a vector autoregressive model to make an empirical analysis of the macroeconomic impact factors that affect the long-term risk volatility of banks. Finally, the specific impact of each variable on the risk, as well as the conduction process. Finally, through the simulation of five banks and the analysis of the long-term risk and macroscopical factors of banking, we can analyze the results of risk research: first, through the comparative analysis of various types of arch model, A good explanation of the risks from 2010 to 2016, and a good simulation of the risks of China's economic transition. That is, the five listed state-owned banks have a stable long-term risk and are within the reasonable scope of the CBRC. Through the short-term and long-term risk measurement, we can deal with the risk well, take targeted measures. Second, comparing the five major state-owned banks, the average value of risk is not much different, but the fluctuation of risk is very different. Especially the Bank of Communications, we should step up risk prevention, and other banks should make appropriate adjustments according to their actual situation. Try to keep the risk within a reasonable range. Finally, the empirical analysis shows that the growth rate of the CPIHP and the exchange rate have a great influence on the long-term risk and the whole economic operation.
【學(xué)位授予單位】：遼寧大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F832.33

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