جستجوی مقالات مرتبط با کلیدواژه "رویکرد بیزی" در نشریات گروه "مالی"

The effect of the contagion between financial assets is one of the most important challenges that investors are faced with. Financial markets have been severely affected by economic, political, and social events and they are subject to volatility and turmoil that causes financial investors and analysts to be disturbed. Therefore, the main objective of the present study is to investigate the effect of shocks on the return volatility of the selected indices. The main objective of this study is to use random simulation techniques for GARCH models considering multivariate skewed distributions using the Bayesian approach. For this purpose, we used the daily return data of selected Tehran Stock Exchange (TSE) indices during the period from December 13, 2009 to Jan 29, 2003 and also the flexible types of multivariate distributions that can model both skewedness and fat tail. The results of the Bayesian DCC GARCH (1.1) model showed that the effect of shocks on the return volatility is not the same  for the selected indices and this situation implies different risk conditions and uncertainty in the returns of these groups. The results also showed that the stock returns of the automotive group spread more volatility from the previous day to the current day in comparison to Banking group and Petroleum group respectively. Shocks on variables affects the correlations among them. Also, GED distribution was identified as an appropriate distribution in line with the characteristics of the skewedness of the studied indices. Therefore, in estimating the risk of assets and portfolio optimization, one can exploit the main idea used in this study.

Cash adequacy in banks’ branches is considered as the significant issues for branch managers; because the daily cash shortage in branches’ funds might lead to the lack of fulfilling customers’ needs. On the other hand, cash surplus in branches will increase the expenses which arise from its transfer to the banks’ treasuries. Therefore, banks have always been attempting to estimate their required cash according to their daily operations and. In this regard, iIn this article, branches of Tejarat Bank, with regard to their diversity, have been classified in similar clusters with the two methods of hierarchical clustering and clustering based on Bayesian approach .Then, based on the results obtained from the clustering, the input cash to the branches as well as the cash consumption in the branches were estimated through the neural networks, which made it possible to calculate the required cash in branches. The results show that the estimation of input and consumed cash of branches using neural network and regarding the results obtained from Bayesian approach for branches clustering enjoys higher precision in comparison to the results obtained from the classic methods of clustering.