%0 Journal Article
%T 基于LSSC的商业银行资产负债组合优化模型研究<br>An Optimization Model of Asset-Liability Portfolio of Commercial Banks Based on LSSC Model
%A 刘睿宸
%A 熊晓炼
%J Operations Research and Fuzziology
%P 103-117
%@ 2163-1530
%D 2024
%I Hans Publishing
%R 10.12677/ORF.2024.141010
%X 利率市场化后，灵活的市场调控要求商业银行加快提升经营管理水平，在实现利润增长的同时防范风险，优化资金配置。根据我国借贷市场短期收益率波动大于长期的特点，对动态Nelson-Siegel模型引入第二个斜率因子，扩展至LSSC模型，并且将构成LSSC模型的4个维度因子参数引入DNS久期向量，推导出LSSC模型的久期向量，构造以银行月收益最大化为目标、4个维度零久期缺口，以流动性约束为条件的资产负债组合优化模型。实证结果表明：相比于传统Nelson-Siegel模型，改进的LSSC模型近端拟合效果具有明显优势，计算得出的短期利率预测误差较小，并且通过实例应用发现基于LSSC模型实现资产负债组合优化更能有效抵御利率风险。<br />
After the marketization of interest rates, the flexible market regulation requires commercial banks to accelerate the improvement of operation and management, to prevent risks and optimize the allocation of funds while achieving profit growth. According to the characteristics of China’s lending market where short-term yield fluctuations are greater than long-term ones, a second slope factor is introduced to the dynamic Nelson-Siegel model and extended to the LSSC model, and the parameters of the four dimensional factors constituting the LSSC model are introduced into the DNS duration vector, which is derived to construct a duration vector of the LSSC model, which takes the maximisation of the bank’s monthly return as the goal, has a zero duration gap in the four dimensions and an asset-liability portfolio optimisation model conditional on liquidity constraints. The empirical results show that compared with the traditional Nelson-Siegel model, the improved LSSC model has an obvious advantage in its proximal fitting effect, the short-term interest rate prediction error is smaller, and it is found that the optimization of asset-liability portfolios based on the LSSC model is more effective against interest rate risk through the application of examples.
%K 商业银行，资产负债管理，利率风险免疫<br>Commercial Banks
%K Asset-Liability Management
%K Interest Rate Risk Immunity
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=80763