摘要
当今世界正经历百年未有之大变局,新一轮科技革命和产业变革深入发展,在我国当前经济内循环为主、双循环促进发展的新格局下,加之疫情带来的影响,金融监管日趋严厉,金融行业需要不断的进行改革发展以应对各种因素带来的金融风险。由于金融不良资产所处的环境复杂多变,各因素影响程度及权重确定主观性强,缺少科学依据,从而使得评估方法在运用中存在问题。因此,本文通过对金融不良资产影响因素进行识别并进行因子分析,确定评估模型,从而对金融不良资产评估方法中的综合因素分析法进行优化,解决该方法存在的问题,使该方法更具科学性与实用性。
Nowadays,the world is experiencing a great change that has not happened in a century.A new round of scientific and technological revolution and industrial reform are developing in depth.Under the new pattern of China’s current economic internal circulation and double circulation promoting development,coupled with the impact of the epidemic situation,financial supervision is becoming increasingly strict.The financial industry needs to carry out continuous reform and development to deal with the financial risks brought by various factors.As the environment of non-performing financial assets is complex and changeable,the influence degree and weight determination of various factors are subjective and lack of scientific basis,so there are problems in the application of evaluation methods.Therefore,this paper identifies the influencing factors of non-performing financial assets and carries out factor analysis to determine the evaluation model,so as to optimize the comprehensive factor analysis method in the evaluation method of non-performing financial assets,solve the problems existing in the method,and make the method more scientific and practical.
作者
张志红
贾敏敏
张雷
Zhang Zhihong;Jia Minmin;Zhang Lei(Shandong University of Finance and Economics,School of Accountancy,Ji Nan Shan Dong 250014;Shandong Zhonglu Real Estate Land Capital Evaluating Co.,Ltd,Ji Nan Shan Dong 250117)
出处
《中国资产评估》
2021年第7期4-9,共6页
Appraisal Journal of China
基金
山东省自然科学基金(ZR2019MG032):财务信息披露形式对非专业投资者判断决策影响研究-从可视化到文本可读性
山东省重点研发计划(软科学)重大项目(2020RZB01074):山东加速培育数字经济生态战略研究
2020年山东省专业学位研究生教学案例库:“数智”转型下MPAcc教学案例库开发
山东高速集团科技创新项目
山东省社会科学规划研究项目(17CGLJ07):共享理念下新创企业社会责任的价值创造机制研究
山东省注册会计师协会:数字经济评价创造、价值评估的理论基础及评估框架研究
关键词
金融不良资产
金融不良资产评估
综合因素分析法
因子分析
Non-Performance Loans
Evaluation of Non-Performance Loans
Comprehensive Factor Analysis
Factor Analysis
