{"title":"我们能从机器学到的东西中学到什么?解释信用风险机器学习模型","authors":"Nehalkumar Bharodia, Wei Chen","doi":"10.21314/jrmv.2020.235","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"66 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"What can we learn from what a machine has learned? Interpreting credit risk machine learning models\",\"authors\":\"Nehalkumar Bharodia, Wei Chen\",\"doi\":\"10.21314/jrmv.2020.235\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":43447,\"journal\":{\"name\":\"Journal of Risk Model Validation\",\"volume\":\"66 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2021-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Risk Model Validation\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.21314/jrmv.2020.235\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Risk Model Validation","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21314/jrmv.2020.235","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
期刊介绍：
As monetary institutions rely greatly on economic and financial models for a wide array of applications, model validation has become progressively inventive within the field of risk. The Journal of Risk Model Validation focuses on the implementation and validation of risk models, and aims to provide a greater understanding of key issues including the empirical evaluation of existing models, pitfalls in model validation and the development of new methods. We also publish papers on back-testing. Our main field of application is in credit risk modelling but we are happy to consider any issues of risk model validation for any financial asset class. The Journal of Risk Model Validation considers submissions in the form of research papers on topics including, but not limited to: Empirical model evaluation studies Backtesting studies Stress-testing studies New methods of model validation/backtesting/stress-testing Best practices in model development, deployment, production and maintenance Pitfalls in model validation techniques (all types of risk, forecasting, pricing and rating)
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