In combination with socio-economic development of China＇s current status, this article analyzes the characteristics of several typical financial behavior of loss listed companies in China. Among them, the debt financ...In combination with socio-economic development of China＇s current status, this article analyzes the characteristics of several typical financial behavior of loss listed companies in China. Among them, the debt financing behavior have a high level, a single means, a short-term structured and other characteristics, the corporate governance behavior have a goal of collaborative, several forms, and a complex environment, the earnings management behavior have diverse motives, many types of means, bigger range and other features, the asset restructuring behavior have a passive subject, methods of differentiation, performance-oriented features such as myopia.展开更多
Using a large dataset obtained from ＂Paipaidai,＂ an online peer-to-peer lending platform in China, we examine whether credit officers＇ mood affects the efficiency of credit approval from a perspective of individual...Using a large dataset obtained from ＂Paipaidai,＂ an online peer-to-peer lending platform in China, we examine whether credit officers＇ mood affects the efficiency of credit approval from a perspective of individual decision-making. Refering to studies in psychology and financial economics, we employ season, temperature and weather as mood proxies, and control the variables related to the quality of the loan to study credit approval behavior under different mood conditions. The results suggest that the efficiency of credit approval by individual credit officers is significantly correlated with their mood--a positive mood improves efficiency, while a negative mood reduces it. Specifically, loans examined under better mood conditions （e.g., during spring, comfortable temperatures, and sunny days） have a significantly higher probability of approval, but a lower probability of default if approved; and those examined under poorer mood conditions show a lower probability of approval and a higher probability of default if approved. This effect of mood is even stronger when a loan application is more complex, atypical, or unusual to evaluate. Moreover, investor sentiment, denoted by closed-end fund premiums, has the same effect on credit approval as well.展开更多
基金The authors are grateful for financial support from the fund of the China National Social Science Fund Project （09CJY085）, China Postdoctoral Science Foundation （20100470109）, and the authors would like to thank to the funding by the Ministry of education of Humanities and social sciences research Youth Project （11YJC630243, 12YJC630010, and ＂Investors＇ expectancy, loss reversibility and the value of negative equity firms＂） Central University basic research funds （SWU1309116, SWU1309202）.
文摘In combination with socio-economic development of China＇s current status, this article analyzes the characteristics of several typical financial behavior of loss listed companies in China. Among them, the debt financing behavior have a high level, a single means, a short-term structured and other characteristics, the corporate governance behavior have a goal of collaborative, several forms, and a complex environment, the earnings management behavior have diverse motives, many types of means, bigger range and other features, the asset restructuring behavior have a passive subject, methods of differentiation, performance-oriented features such as myopia.
文摘Using a large dataset obtained from ＂Paipaidai,＂ an online peer-to-peer lending platform in China, we examine whether credit officers＇ mood affects the efficiency of credit approval from a perspective of individual decision-making. Refering to studies in psychology and financial economics, we employ season, temperature and weather as mood proxies, and control the variables related to the quality of the loan to study credit approval behavior under different mood conditions. The results suggest that the efficiency of credit approval by individual credit officers is significantly correlated with their mood--a positive mood improves efficiency, while a negative mood reduces it. Specifically, loans examined under better mood conditions （e.g., during spring, comfortable temperatures, and sunny days） have a significantly higher probability of approval, but a lower probability of default if approved; and those examined under poorer mood conditions show a lower probability of approval and a higher probability of default if approved. This effect of mood is even stronger when a loan application is more complex, atypical, or unusual to evaluate. Moreover, investor sentiment, denoted by closed-end fund premiums, has the same effect on credit approval as well.
