主  題：Predicting Credit Rating Changes in Bull and Bear Markets

內(nèi)容簡(jiǎn)介：Credit rating transitions over time are typically assumed to be generated by a simple Markov process and dependent on the dynamics of the economic regimes. Incorporating the dynamics of the economic regimes characterized by economic indicators, this paper proposes a new structural model for predicting changes in corporate credit ratings. Specifically, our first objective is to develop a regime-switching multivariate autoregressive model to characterize the dynamics of the economic market. A hidden Markov model captures the changing pattern of critical market situations, such as bull and bear markets. The second objective of this paper is to develop a model that predicts the likelihood of changes in firms' credit ratings for different regimes of macro economy using typical firm financial data. It is statistically significant that firms are more probably to be downgraded in bear markets than in bull markets. On the other hand, chances for firms to be upgraded are greater in bull markets than in bear markets.

報(bào)告人：趙永淦    教授

                  加拿大達(dá)爾豪斯大學(xué)金融學(xué)院教授

時(shí)  間：2014年9月17號(hào)（周三）15：00

地  點(diǎn)：敏達(dá)樓516

舉辦單位：金融學(xué)院、科研與研究生部