基于BX灰色马尔科夫模型的商业银行资本充足率预测——以交通银行为例

Prediction of Loan-to-Deposit Ratio of Banks Based on BX Grey Markov Model——Bank of Communications as an Example

资本充足率是保证银行正常运营所必需的资本比率,是衡量银行综合风险的重要指标,对抑制风险资产的过度膨胀,保证银行等金融机构良性发展具有重要意义。科学预测商业银行资本充足率,对监控商业银行的经营行为,防控金融风险,促进商业银行健康发展具有重要意义。本文运用BX灰色马尔科夫模型预测交通银行资本充足率,发挥两种方法的优势,取得了较为理想的效果,平均预测比传统GM(1,1)模型减小81.450%,比BXGM(1,1)模型减小67.56%。

The adequacy ratio is necessary for ensuring the normal operation of the bank capital ratio which is an important index to measure the comprehensive risk of banks, which plays an important role in inhibiting the excessive expansion of risk assets and the healthy development of banks and other financial institutions. Scientific prediction of the capital adequacy ratio of commercial banks plays an important role in monitoring commercial banks＇ behavior, preventing and controlling financial risks and promoting the healthy development of commercial banks. Prediction of the capital adequacy ratio of the Bank of communications BX using grey Markov model in this paper, the advantages of two methods, achieving the ideal effect, the average prediction than traditional GM （1,1） model is reduced by 81.450%, compared with BXGM （1, 1） model is reduced by 67.56%.