基于RAROC和集中度約束的信貸組合優(yōu)化配置研究
發(fā)布時(shí)間：2018-08-07 14:01
【摘要】：隨著我國(guó)利率市場(chǎng)化進(jìn)程的日益加快以及資本充足率監(jiān)管力度的不斷加強(qiáng),如何進(jìn)行有效的資本配置,即為貸款業(yè)務(wù)確定合理的風(fēng)險(xiǎn)限額成為銀行關(guān)注的重點(diǎn)問題。風(fēng)險(xiǎn)限額是在內(nèi)部評(píng)級(jí)法量化信用風(fēng)險(xiǎn)的基礎(chǔ)上,通過資產(chǎn)組合模型,并根據(jù)風(fēng)險(xiǎn)調(diào)整后的資本收益率最大化原則,確定的風(fēng)險(xiǎn)敞口上限；同時(shí),巴塞爾委員會(huì)明確指出,信貸組合的集中度風(fēng)險(xiǎn)是造成銀行危機(jī)的一個(gè)主要原因,是監(jiān)管資本及經(jīng)濟(jì)資本的重要影響因素。因此,構(gòu)建基于RAROC (即經(jīng)風(fēng)險(xiǎn)調(diào)整后的資本收益率)和集中度約束的信貸組合優(yōu)化配置模型,具有重要的現(xiàn)實(shí)意義和理論價(jià)值。 雖有不少學(xué)者在相關(guān)方面取得了有價(jià)值的研究成果,但仍存在一些有待進(jìn)一步完善之處,如：信貸組合相關(guān)性的估計(jì),受制于數(shù)據(jù)不足、期限長(zhǎng)度不夠及代理變量取值難等現(xiàn)狀；經(jīng)濟(jì)資本的計(jì)量,存在假設(shè)條件多、精確性較差等不足；組合集中度的計(jì)量,存在部分參數(shù)只能由模擬產(chǎn)生等不足；信貸限額的配置,存在視角過于微觀、前瞻性不足等缺陷。 在借鑒現(xiàn)有研究成果的基礎(chǔ)上,本文主要取得了如下研究成果： (1)通過構(gòu)建RAROC因子模型來計(jì)量信貸組合相關(guān)性,以體現(xiàn)宏觀經(jīng)濟(jì)環(huán)境對(duì)銀行資產(chǎn)收益的影響。 基于RAROC涵義,將影響貸款利率的若干經(jīng)濟(jì)因素視為RAROC的系統(tǒng)風(fēng)險(xiǎn)因子,即根據(jù)凱恩斯和希克斯的經(jīng)典理論,通過分析IS-LM模型,提煉出四個(gè)影響銀行資產(chǎn)收益的系統(tǒng)風(fēng)險(xiǎn)因子：經(jīng)濟(jì)增長(zhǎng)、物價(jià)水平、貨幣供給量和投資額度,據(jù)此構(gòu)建了RAROC因子模型,并給出信貸組合協(xié)方差矩陣的計(jì)算公式。進(jìn)一步,以S銀行某分行數(shù)據(jù)進(jìn)行實(shí)證分析,得到了信用評(píng)級(jí)、行業(yè)和企業(yè)規(guī)模三個(gè)維度下信貸組合的RAROC協(xié)方差矩陣及相關(guān)系數(shù)矩陣。 (2)利用S銀行某分行的1448筆對(duì)公貸款數(shù)據(jù)和X銀行總行的4113筆對(duì)公貸款數(shù)據(jù),分別測(cè)度了它們?cè)谛庞迷u(píng)級(jí)、行業(yè)和企業(yè)規(guī)模三個(gè)維度下的集中度,并構(gòu)建了相應(yīng)維度下考慮集中度約束的信貸組合優(yōu)化配置模型。 使用VBA程序設(shè)計(jì)了一個(gè)組合集中度計(jì)量模塊,測(cè)度了S銀行某分行和X銀行總行的信貸組合集中度及其變化狀況,據(jù)此分別構(gòu)建了信用評(píng)級(jí)、行業(yè)和企業(yè)規(guī)模三個(gè)維度下考慮集中度約束的信貸組合優(yōu)化配置模型,并進(jìn)行了壓力測(cè)試。 (3)將上述構(gòu)建的三個(gè)維度下的模型與不考集中度約束的模型進(jìn)行實(shí)證比較,從一個(gè)側(cè)面檢驗(yàn)與對(duì)比分析了上述模型的改進(jìn)效果。 主要結(jié)論為：①各維度下,無論是否考慮集中度約束,隨著銀行設(shè)定的收益目標(biāo)的增加,組合集中度風(fēng)險(xiǎn)總是隨之增加,意味著此時(shí)貸款資源的配置也趨于集中；同時(shí),組合風(fēng)險(xiǎn)與收益目標(biāo)呈正相關(guān)性。②各維度下,集中度約束會(huì)使銀行收益適度變小。③無論是否考慮集中度約束,中間級(jí)別的信貸組合RAROC值最大,對(duì)銀行最具吸引力；批發(fā)和零售、工業(yè)、房地產(chǎn)這三個(gè)行業(yè)類信貸組合的配置權(quán)重相對(duì)較大；值得一提的是：目前利率市場(chǎng)化時(shí)機(jī)尚未成熟,銀行仍可享受息差保護(hù)政策的紅利,導(dǎo)致大型企業(yè)貸款客戶更受銀行青睞,但從企業(yè)規(guī)模維度分析知：RAROC隨企業(yè)規(guī)模的遞減而遞增,表明經(jīng)營(yíng)中小企業(yè)客戶的資本效率遠(yuǎn)高于大企業(yè),因此可以預(yù)計(jì)：伴隨利率市場(chǎng)化和資本約束的加強(qiáng)以及政策的傾斜,銀行的戰(zhàn)略轉(zhuǎn)型必將向中小企業(yè)傾斜。另外,④壓力測(cè)試表明：信用評(píng)級(jí)為7的借款企業(yè)、房地產(chǎn)行業(yè)的借款企業(yè)或小型借款企業(yè)在遭遇極端危機(jī)時(shí),給銀行信貸組合帶來的風(fēng)險(xiǎn)最大,應(yīng)引起S銀行特別關(guān)注,需結(jié)合風(fēng)險(xiǎn)偏好及差異化經(jīng)營(yíng)策略,對(duì)貸款資源進(jìn)行優(yōu)化配置。 總之,本文的創(chuàng)新點(diǎn)主要包括： (1)為刻畫信貸組合收益的相關(guān)系數(shù)矩陣并考察銀行資本效率的影響因素,構(gòu)建了考慮若干宏觀經(jīng)濟(jì)指標(biāo)的RAROC因子模型,相應(yīng)指標(biāo)有：經(jīng)濟(jì)增長(zhǎng)、物價(jià)水平、貨幣供給量和投資額度等。 (2)將RAROC和集中度風(fēng)險(xiǎn)作為約束條件引入信貸組合優(yōu)化配置模型,并分別從信用評(píng)級(jí)、行業(yè)和企業(yè)規(guī)模三個(gè)維度對(duì)比分析了信貸組合最優(yōu)配置方案,有力地保證了銀行貸款不至于過度集中于某些信用級(jí)別的行業(yè)或某種規(guī)模的企業(yè),同時(shí)保障銀行貸款組合獲得較好的收益。 (3)考慮了銀行貸款對(duì)各行業(yè)經(jīng)濟(jì)增長(zhǎng)的貢獻(xiàn)率及與區(qū)域經(jīng)濟(jì)結(jié)構(gòu)的差異性、協(xié)調(diào)性,據(jù)此給出了兼顧銀行自身發(fā)展和有利于促進(jìn)區(qū)域經(jīng)濟(jì)增長(zhǎng)的銀行貸款優(yōu)化配置方法。
[Abstract]:With the acceleration of the process of interest rate marketization and the continuous strengthening of capital adequacy regulation, how to carry out effective capital allocation, that is, to determine a reasonable risk limit for the loan business has become the focus of the bank. The risk limit is based on the internal rating method to quantify the credit risk and through the portfolio model, At the same time, the Basel Committee clearly points out that the risk of the centralization of the credit portfolio is a major cause of the bank crisis and an important factor in the regulatory capital and economic capital. Therefore, the construction of the RAROC (i.e., after the risk adjustment) It is of great practical significance and theoretical value to optimize the allocation model of credit portfolios constrained by concentration ratio.
Although many scholars have obtained valuable research results in related aspects, there are still some problems to be further improved, such as the estimation of the correlation of the credit combination, the shortage of data, the lack of time limit and the difficulty of obtaining the value of the proxy variables, the measurement of economic capital, the many hypothetical conditions, the poor accuracy, and so on. In the measurement of portfolio concentration, there are some shortcomings, such as some parameters can only be generated by simulation, and the allocation of credit limits, there are some shortcomings, such as too microscopic perspective, lack of forward-looking.
On the basis of the existing research results, this paper has achieved the following research results:
(1) Establishing RAROC factor model to measure the correlation of credit portfolio to reflect the impact of macroeconomic environment on bank asset returns.
Based on the meaning of RAROC, some economic factors that affect the loan interest rate are considered as the systemic risk factor of RAROC. That is, according to the classical theory of Keynes and Hicks, through the analysis of the IS-LM model, four system risk factors are extracted, which are economic growth, price level, money supply and investment quota, and then the R is constructed. The AROC factor model and the calculation formula of the covariance matrix of the credit combination are given. Further, the empirical analysis of the data of a branch of S bank is carried out, and the RAROC covariance matrix and the correlation coefficient matrix of credit rating, industry and enterprise scale are obtained under the three dimensions of credit rating, industry and enterprise scale.
(2) using 1448 pairs of public loan data of a branch of S bank and 4113 pairs of public loan data of X bank general bank, the concentration degree of their credit rating, industry and enterprise scale in three dimensions is measured respectively, and the optimal allocation model of credit combination considering the degree of concentration constraint under the corresponding dimension is constructed.
A VBA program is used to design a combination concentration measurement module. The credit portfolio concentration and the change status of a branch of S bank and X bank are measured. According to this, the credit portfolio optimization allocation model with three dimensions of credit rating, industry and enterprise scale is constructed, and the pressure test is carried out.
(3) to compare the model of the three dimensions constructed above and the model which is not restricted by the degree of concentration, and analyze the improvement effect of the above model from a side test and comparison.
The main conclusions are as follows: (1) under each dimension, whether or not the concentration constraints are considered or not, the risk of combination concentration increases with the increase of the goal of the bank's income, which means that the allocation of loan resources tends to concentrate at this time; at the same time, there is a positive correlation between the portfolio risk and the income target. No matter whether the concentration constraints are considered or not, the maximum RAROC value of the intermediate level of credit combination is the most attractive to the bank; the allocation weight of the three sectors of the credit combination of wholesale and retail, industry and real estate is relatively large; it is worth mentioning that the current market timing is not ripe and the banks can still enjoy interest rates. The dividend of the policy of differential protection makes large enterprise loan customers more favored by the bank, but it is known from the scale of enterprises that RAROC increases with the decline of enterprise scale, which indicates that the capital efficiency of small and medium-sized enterprises is far higher than that of large enterprises. At the same time, the strategic transformation of the bank will be inclined to the small and medium enterprises. Besides, the pressure test shows that the credit rating is 7 of the borrowing enterprises, the loan enterprises of the real estate industry or the small loan enterprises have the greatest risk to the bank credit combination in the extreme crisis, which should cause the S bank to pay special attention to the risk preference and differentiation. Management strategy to optimize the allocation of loan resources.
In a word, the innovation of this article mainly includes:
(1) to describe the correlation coefficient matrix of the credit portfolio income and investigate the factors affecting the bank's capital efficiency, a RAROC factor model, which considers a number of macroeconomic indicators, is constructed. The corresponding indexes are economic growth, price level, money supply and investment quota.
(2) introducing RAROC and concentration risk as constraints into the optimal allocation model of credit portfolio, and comparing the optimal allocation of credit portfolio from three dimensions of credit rating, industry and enterprise scale, which effectively guarantees that bank loans are not overly concentrated in a certain credit level or a certain scale of enterprises. The bank loan portfolio is guaranteed to gain better returns.
(3) considering the contribution rate of bank loans to the economic growth of each industry and the difference between the regional economic structure and the regional economic structure, the method of optimal allocation of bank loans, which takes into account the development of the bank itself and is beneficial to the promotion of regional economic growth, is given.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.4;F224
本文編號(hào)：2170250
[Abstract]:With the acceleration of the process of interest rate marketization and the continuous strengthening of capital adequacy regulation, how to carry out effective capital allocation, that is, to determine a reasonable risk limit for the loan business has become the focus of the bank. The risk limit is based on the internal rating method to quantify the credit risk and through the portfolio model, At the same time, the Basel Committee clearly points out that the risk of the centralization of the credit portfolio is a major cause of the bank crisis and an important factor in the regulatory capital and economic capital. Therefore, the construction of the RAROC (i.e., after the risk adjustment) It is of great practical significance and theoretical value to optimize the allocation model of credit portfolios constrained by concentration ratio.
Although many scholars have obtained valuable research results in related aspects, there are still some problems to be further improved, such as the estimation of the correlation of the credit combination, the shortage of data, the lack of time limit and the difficulty of obtaining the value of the proxy variables, the measurement of economic capital, the many hypothetical conditions, the poor accuracy, and so on. In the measurement of portfolio concentration, there are some shortcomings, such as some parameters can only be generated by simulation, and the allocation of credit limits, there are some shortcomings, such as too microscopic perspective, lack of forward-looking.
On the basis of the existing research results, this paper has achieved the following research results:
(1) Establishing RAROC factor model to measure the correlation of credit portfolio to reflect the impact of macroeconomic environment on bank asset returns.
Based on the meaning of RAROC, some economic factors that affect the loan interest rate are considered as the systemic risk factor of RAROC. That is, according to the classical theory of Keynes and Hicks, through the analysis of the IS-LM model, four system risk factors are extracted, which are economic growth, price level, money supply and investment quota, and then the R is constructed. The AROC factor model and the calculation formula of the covariance matrix of the credit combination are given. Further, the empirical analysis of the data of a branch of S bank is carried out, and the RAROC covariance matrix and the correlation coefficient matrix of credit rating, industry and enterprise scale are obtained under the three dimensions of credit rating, industry and enterprise scale.
(2) using 1448 pairs of public loan data of a branch of S bank and 4113 pairs of public loan data of X bank general bank, the concentration degree of their credit rating, industry and enterprise scale in three dimensions is measured respectively, and the optimal allocation model of credit combination considering the degree of concentration constraint under the corresponding dimension is constructed.
A VBA program is used to design a combination concentration measurement module. The credit portfolio concentration and the change status of a branch of S bank and X bank are measured. According to this, the credit portfolio optimization allocation model with three dimensions of credit rating, industry and enterprise scale is constructed, and the pressure test is carried out.
(3) to compare the model of the three dimensions constructed above and the model which is not restricted by the degree of concentration, and analyze the improvement effect of the above model from a side test and comparison.
The main conclusions are as follows: (1) under each dimension, whether or not the concentration constraints are considered or not, the risk of combination concentration increases with the increase of the goal of the bank's income, which means that the allocation of loan resources tends to concentrate at this time; at the same time, there is a positive correlation between the portfolio risk and the income target. No matter whether the concentration constraints are considered or not, the maximum RAROC value of the intermediate level of credit combination is the most attractive to the bank; the allocation weight of the three sectors of the credit combination of wholesale and retail, industry and real estate is relatively large; it is worth mentioning that the current market timing is not ripe and the banks can still enjoy interest rates. The dividend of the policy of differential protection makes large enterprise loan customers more favored by the bank, but it is known from the scale of enterprises that RAROC increases with the decline of enterprise scale, which indicates that the capital efficiency of small and medium-sized enterprises is far higher than that of large enterprises. At the same time, the strategic transformation of the bank will be inclined to the small and medium enterprises. Besides, the pressure test shows that the credit rating is 7 of the borrowing enterprises, the loan enterprises of the real estate industry or the small loan enterprises have the greatest risk to the bank credit combination in the extreme crisis, which should cause the S bank to pay special attention to the risk preference and differentiation. Management strategy to optimize the allocation of loan resources.
In a word, the innovation of this article mainly includes:
(1) to describe the correlation coefficient matrix of the credit portfolio income and investigate the factors affecting the bank's capital efficiency, a RAROC factor model, which considers a number of macroeconomic indicators, is constructed. The corresponding indexes are economic growth, price level, money supply and investment quota.
(2) introducing RAROC and concentration risk as constraints into the optimal allocation model of credit portfolio, and comparing the optimal allocation of credit portfolio from three dimensions of credit rating, industry and enterprise scale, which effectively guarantees that bank loans are not overly concentrated in a certain credit level or a certain scale of enterprises. The bank loan portfolio is guaranteed to gain better returns.
(3) considering the contribution rate of bank loans to the economic growth of each industry and the difference between the regional economic structure and the regional economic structure, the method of optimal allocation of bank loans, which takes into account the development of the bank itself and is beneficial to the promotion of regional economic growth, is given.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.4;F224
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