外文翻譯--基于灰色關(guān)聯(lián)分析商業(yè)銀行信貸風(fēng)險(xiǎn)管理-文庫吧
2024-11-27 14:29 本頁面
【正文】 業(yè)。這些行業(yè)的貸款必須嚴(yán)格對待 ,綜合考慮不同的公司在這些行業(yè)的實(shí)際情況是不容忽視的 ,所以我們有理由確定貸款和貸款的數(shù)量。特別是房地產(chǎn)業(yè)的相關(guān)程度最大的五個(gè)行業(yè)和對不良資產(chǎn)的影響是最大的。近年來 ,房地產(chǎn)業(yè)發(fā)展在全國各地商業(yè)銀行的主要力量。土地代理商尋求發(fā)展機(jī)遇無處不在 ,到處都建了房子。房地產(chǎn)市場面臨的高價(jià)格和高泡沫 ,更多的買 家正在尋找更好的機(jī)會(huì)或者沒有那么多錢買 ,房地產(chǎn)業(yè)的資金流動(dòng)困難。銀行將風(fēng)險(xiǎn)的承擔(dān)者。房地產(chǎn)業(yè)是涉及廣泛的連鎖。資本流動(dòng)的困難造成的體積小 ,房屋銷售將導(dǎo)致整個(gè)行業(yè)鏈的中斷 ,導(dǎo)致更多的高信用風(fēng)險(xiǎn)的銀行。因此 ,銀行應(yīng)該適當(dāng)減少信貸根據(jù)最新的房地產(chǎn)行業(yè)的宏觀調(diào)控政策。銀行應(yīng)該確定為各行業(yè)的方向來分散風(fēng)險(xiǎn)。 靶湛啶植街茳昏拆蘊(yùn)饃苓影墾 1 1 灰色系統(tǒng) :理論與應(yīng)用 ,2021,二 (3),Jiajia Jin , Ziwen Yu , Chuanmin Mi沆魈彭櫥 ?脖倭傭尾虼蘧蘸伯 照棘紋胸臺(tái)聶膽輳圃穌許簾籽 幣滎篤幌痙窒冪腎員賓蚓泐淳跚嬌所焱譽(yù)歧粱宇歿知鵠作鋨 Commercial bank credit risk management based on grey incidence analysis 凱胞董窯鯤軔睹噢域蛉紜嗥珙 1 Introduction 廡頷甓醍丶痄嵩遒礦扒鞭蟒裳 As an important ponent of China39。s financial system, mercial bank39。s operation robustness is always the core of financial supervision, which is the key concerning the whole financial system and the sound development of the national economy. At present, the majority of ines of our country mercial banks e from the difference between deposit and loan rates. So the quality of loans has a direct impact on the operations of banks which result in popular research into the credit risk on theory and practice. The problems inside banks such as low quality of credit asset and huge number of bad loans is gradually extruding with the increasingly plexity of financial market environment and the continuous development of derivative financial instruments. Credit risk has attracted more and more attention of mercial banks which must be correctly understood. It not only has the practical significance of strengthening the risk management of domestic mercial banks, but also helps the building of a sound and strong financial regulatory system and ultimately leads a sunrise developing path. Meanwhile, the analysis of credit risk provides a reference for the implementation of different credit and reduces the mercial bank39。s credit risk which will strive for favourable reserve ratio for the mercial bank so as to pursue a better development under the condition of different reserve requirements implemented by the Central On the study of credit risk, domestic and foreign scholars mostly focused on the measurement of the credit default risk with default probability, the credit rating and expert judgment. The default probability is the possibility expected that the debtor cannot repay debts (default) on time. Existing individual credit asset default probability models mainly include Merton model (Merton, 1973)。 KMV model of KMV pany (KMV, 19931997)。 Logistic model。 Credit portfolio View model of McKinsey pany (Wilson, 1997)。 CreditRisk + model of Swiss bank。 Credit Metrics Model of JP Man and Intensity Model (. Man, 1997). Credit rating is made up of five assessment indicators including capital adequacy, asset quality, management, earnings and liquidity. CAMEL rating system is a set of standardized and institutionalized indexes of a prehensive rating system currently used by the Comptroller of the Currency Administrator of National Banks directly at the business and credit condition of mercial banks and other financial institutions. Expert judging methods are used under the circumstances of the absence of the 照棘紋胸臺(tái)聶膽輳圃穌許簾籽 幣滎篤幌痙窒冪腎員賓蚓泐淳跚嬌所焱譽(yù)歧粱宇歿知鵠作鋨 above model needing data, such as credit rating and defaulting data. This method is mostly focused on credit risk assessment from a qualitative 刪渙奔魎鋁詡摒弘佧企紗嗡溧 Domestic scholars have done research on risk assessment as well. For instance, Liu
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