【摘要】：本文采用成分期望損失CES方法,基于公開市場數(shù)據(jù),對我國16家上市商業(yè)銀行的系統(tǒng)性風(fēng)險進(jìn)行度量。基于CES的方法無論從時間維度還是橫截面維度上,都與我國銀行業(yè)的實(shí)際情況有著較好的契合。本文還采用貝葉斯模型平均BMA方法,廣泛納入現(xiàn)有相關(guān)文獻(xiàn)中選取的影響因子作為解釋變量,解決傳統(tǒng)回歸中的模型不確定性。研究結(jié)果表明,對于我國上市商業(yè)銀行而言,銀行規(guī)模、股權(quán)市賬比及是否處于系統(tǒng)重要性地位與銀行系統(tǒng)性風(fēng)險呈現(xiàn)出顯著的正相關(guān)關(guān)系,而非利息收入的提高能夠有效地分散系統(tǒng)性風(fēng)險;在行業(yè)層面,銀行系統(tǒng)的波動率越高,單個機(jī)構(gòu)面臨的系統(tǒng)性風(fēng)險也越大。以上結(jié)論可以為銀行監(jiān)管部門政策制定提供較為明確的啟示及實(shí)證支持。
[Abstract]:Based on the open market data, this paper measures the systemic risk of 16 listed commercial banks in China by using the component expectation loss (CES) method. The method based on CES has a good agreement with the actual situation of China's banking industry in terms of both time dimension and cross section dimension. In this paper, the Bayesian model average BMA method is also used to solve the uncertainty of the traditional regression model by incorporating the influence factors selected in the existing literature as explanatory variables. The results show that, for the listed commercial banks in China, there is a significant positive correlation between the size of the banks, the equity market / book ratio and whether they are systemically important to the systemic risk of the banks. The increase in non-interest income can effectively disperse systemic risk; at the industry level, the higher the volatility of the banking system, the greater the systemic risk faced by individual institutions. The above conclusions can provide clear enlightenment and empirical support for bank regulatory policy formulation.
【作者單位】： 武漢大學(xué)經(jīng)濟(jì)與管理學(xué)院;
【基金】：國家社科基金重大項(xiàng)目(15ZDC020) 國家自然科學(xué)基金面上項(xiàng)目(71673205) 武漢大學(xué)自主科研項(xiàng)目(人文社會科學(xué))的階段性研究成果
【分類號】：F832.33
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本文編號：2210729