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基于RBF网络的商业银行信用风险控制研究 总被引:3,自引:0,他引:3
对信用风险的有效控制与管理,在现代商业银行日常运行过程中具有举足轻重的地位。基于信用风险系统是一个高度复杂的非线性动态系统,利用神经网络的自适应学习、并行分布处理和较强的鲁棒性及容错性等特性,建立基于RBF神经网络的信用风险预测控制模型,从理论上探寻信用风险非线性智能控制。仿真试验表明,信用风险度能被控制在以最佳风险度为中心的一定范围内。因此,该预测控制系统适合于商业银行信用风险的控制。 相似文献
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对信用风险的有效控制与管理,在现代商业银行日常运行过程中具有举足轻重的地位。基于信用风险系统是一个高度复杂的非线性动态系统,利用神经网络的自适应学习、并行分布处理和较强的鲁棒性及容错性等特性,建立基于RBF神经网络的信用风险预测控制模型,从理论上探寻信用风险非线性智能控制。仿真试验表明,信用风险度能被控制在以最佳风险度为中心的一定范围内。因此,该预测控制系统适合于商业银行信用风险的控制。 相似文献
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为监测评价商业银行信用风险,在对其成因进行深入阐述后,借助聚类分析选取32个单项指标构成评价指标体系.由此建立基于BP算法的三层前向神经网络,通过网络训练,利用网络的自适应、自学习能力,自动获取合适的网络权值与阚值,并采用附加动量法加快网络的收敛速度,基于此对商业银行所面临的信用风险进行评价.仿真试验及实证研究表明了该方法的适用性与可行性. 相似文献
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有效市场假说认为,金融市场上金融资产的价格变化是对各种信息的反应,如果这种反应是即刻而充分的,那么市场就是有效的。本文基于我国上市公司股票和债券的价格数据,应用KMV模型和信用价差模型度量上市公司股票和债券价格变化所反映的公司信用风险大小,在此基础上检验并比较上市公司股票和债券价格对其信用风险信息反应的效率。结果表明,从短期信息有效性方面看,股票价格能够更加及时有效地反映公司信用风险信息,公司债券价格对信用风险信息的反应存在滞后性,但随着实际信用风险增加,滞后时差缩短;从长期来看,股票价格和债券价格在反映公司信用风险信息上存在一致性,公司的实际信用风险大小是影响两者存在一致性的重要因素,实际的信用风险越大,两者的一致性越强。 相似文献
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《武汉金融》2018,(2)
近年来我国P2P网络借贷业务快速发展,然而行业内的信用风险也日益凸显,持续性的平台倒闭以及借款人违约等事件屡见不鲜,因而对网贷信用风险的事前有效评估将直接关乎我国网贷行业的未来可持续发展。本文根据网贷业务特点,筛选出对网贷借款人行为具有影响的特征指标,建立网贷借款人信用风险评估指标体系,构建基于BP神经网络的信用风险评估模型,选取拍拍贷和人人贷的借款人交易数据进行训练仿真。实证结果表明BP神经网络模型能较好拟合网络信用环境下对网贷借款人信用风险的评估,模型具备较高的预测准确率,适用于平台和投资者甄选优质借款人。基于实证分析结果,文章进一步提出了规范网贷平台健康可持续发展的对策建议。 相似文献
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信用卡信用风险评估方法主要包括专家系统法、判别分析法、Logistic回归方法、决策树法、神经网络法、信用风险附加模型等六种。这六种方法各具特点,对我国商业银行信用卡的信用风险管理具有一定的借鉴意义。通过比较分析可知,我国商业银行信用卡信用风险度量的最佳方法为LoDstic回归法。 相似文献
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Institutional investors are supposed to assess credit risk by using a combination of quantitative information such as option models and qualitative assessments. Although option models can be easily constructed, they are not so suitable for the assessment of long-term credit risk that is required by institutional investors. This is mainly because the probability of bankruptcy varies so widely depending on the timing of assessment. We propose a new set of assessment models for long-term credit risk which does not necessarily use stock prices and may incorporate business cycles. The new grand model consists of the two pillars: a long-term cash flow prediction model and a credit risk spread assessment model. The calculated values derived from these models are effectively usable for reasonable calculation of risk spreads. It is quite interesting to see that our investigation indicates that rating bias may exist in the credit risk assessment of the market. 相似文献
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Forecasting credit default risk has been an important research field for several decades. Traditionally, logistic regression has been widely recognized as a solution because of its accuracy and interpretability. Although complex machine learning models may improve accuracy over simple logistic regressions, their interpretability has prevented their use in credit risk assessment. We introduce a neural network with a selective option to increase interpretability by distinguishing whether linear models can explain the dataset. Our methods are tested on two datasets: 25,000 samples from the Taiwan payment system collected in October 2005 and 250,000 samples from the 2011 Kaggle competition. We find that, for most of samples, logistic regression will be sufficient, with reasonable accuracy; meanwhile, for some specific data portions, a shallow neural network model leads to much better accuracy without significantly sacrificing interpretability. 相似文献
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KMV模型对我国上市公司信用风险度量的实证研究 总被引:2,自引:0,他引:2
信用风险已成为当今金融市场的重要风险。随着金融市场许多新情况和新问题的出现.建立新的适用我国信用风险管理水平的度量模型显得十分重要。本文针对我国特有的经济环境,运用并修正KMV模型,基于市场价格变动信息评价我国证券市场上绩优公司与绩差公司的信用风险.通过实证来检验模型识别上市公司信用风险的能力,结果表明该模型能较好的识别这两类公司的信用风险,最后对我国建立信用风险管理体系提出政策建议。 相似文献
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科学高效的商业银行信用风险测度模型,是实现商业银行信用风险监测目标的重要保障。商业银行信用风险主要来源于贷款企业层面,贷款企业信用质量状况将对应着商业银行信用风险水平。对此,从贷款企业的财务与非财务两个层面设计信用风险的测度指标体系,运用模糊综合评判法构建信用平稳下商业银行信用风险测度模型,并给出信用风险测度模型的应用实例。研究发现,在信用平稳下,依赖于专家评判及打分方式,使得模糊综合评判法对于解决商业银行信用风险测度问题具有很好的操作便利性;也可为我国商业银行体系构建科学高效的信用风险监测机制提供重要的理论指导与决策参考。 相似文献
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We develop a switching regime version of the intensity model for credit risk pricing. The default event is specified by a Poisson process whose intensity is modeled by a switching Lévy process. This model presents several interesting features. First, as Lévy processes encompass numerous jump processes, our model can duplicate the sudden jumps observed in credit spreads. Also, due to the presence of jumps, probabilities do not vanish at very short maturities, contrary to models based on Brownian dynamics. Furthermore, as the parameters of the Lévy process are modulated by a hidden Markov chain, our approach is well suited to model changes of volatility trends in credit spreads, related to modifications of unobservable economic factors. 相似文献
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Chulwoo Han 《European Journal of Finance》2017,23(15):1572-1588
In this article, a generic severity risk framework in which loss given default (LGD) is dependent upon probability of default (PD) in an intuitive manner is developed. By modeling the conditional mean of LGD as a function of PD, which also varies with systemic risk factors, this model allows an arbitrary functional relationship between PD and LGD. Based on this framework, several specifications of stochastic LGD are proposed with detailed calibration methods. By combining these models with an extension of CreditRisk+, a versatile mixed Poisson credit risk model that is capable of handling both risk factor correlation and PD–LGD dependency is developed. An efficient simulation algorithm based on importance sampling is also introduced for risk calculation. Empirical studies suggest that ignoring or incorrectly specifying severity risk can significantly underestimate credit risk and a properly defined severity risk model is critical for credit risk measurement as well as downturn LGD estimation. 相似文献
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本文试图对几种有代表性的模型进行比较,来分析由于建模方式的不同,而导致的对信用期权定价和对冲的结果的不同.如果将违约风险传染考虑进去,类似德隆帝国崩溃的事件,或许就能避免. 相似文献
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基于企业规模的信贷决策支持:运用外部信用评级的一个试验 总被引:1,自引:0,他引:1
中小企业作为一个整体,需要根据企业的风险度来确定对它的信贷规模,风险度以企业信用级别来表示,信用级别通过外部评级来确定。为此本文介绍了一个外部评级体系,利用一个地区的评级样本——59家中小企业,反映外部评级体系对中小企业风险度的独特揭示,在此基础上建立了一个对中小企业的、基于信用级别的最高授信额度测算模型。 相似文献