银行信贷顺周期性的微观行为特征与优化控制——基于青岛市大数据平台  

The Microscopic Behavior Characteristics and Optimizing Control of Bank Loan Management Pro-cyclicality——Based on Qingdao Big Data Platform

作　　者：时东[1] 赵映光[2] 鞠卫华[2] 辛俊杰[2] 

机构地区：[1]中国人民银行,北京100032 [2]中国人民银行青岛市中心支行,山东青岛266071

出　　处：《金融发展研究》2014年第12期33-39,共7页Journal Of Financial Development Research

摘　　要：银行信贷管理具有明显的周期性,尤其是在经济下行期银行的"避险"行为比较突出。基于青岛市大数据平台,本文对经济下行期银行信贷管理行为进行研究,力图总结出银行的微观行为特征。本文认为银行的风险敏感度和预见度并不高,行为多表现出短期应激性,主要表现是前置性强势和风险处置弱势的双重特征,并且银行在对待周期性行业和非周期性行业方面呈现出较大差异。银行的行为特征有其内在组织和市场根源因素,通过对根源因素开展可控性分析,对其优化控制可以缓解银行信贷的顺周期性。The loan management of bank is of obvious pro-cyclicality, especially in the down period. Based on the big data platform of Qingdao, this article researches the loan management of bank in the down period, and summarizes the character of bank’s behavior. The sensitiveness and foresight of bank for risk is low, and the behavior is just a simple and short-term reaction for risk, showing as twofold：prefixing mighty as well as weakness in risk disposal. In addition, bank’s policy for cyclical industry and non-cyclical industry is different. The character of behavior roots from factors of bank’s inner organization and market. Through the analysis for the controllability of these factors, this article puts forward the suggestion of optimizing control.

关 键 词：顺周期性 行为特征 短期应激性 优化控制 大数据 

分 类 号：F832.4[经济管理—金融学]