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中文摘要：
针对我国债券市场,选取上海证券交易所2006年1月至2011年12月国债和企业债月度交易数据,利用SV模型和遗传算法求得国债和企业债的利率期限结构,进而得到企业债的信用价差.然后利用多元回归模型提取影响我国企业债信用价差的显著宏观经济因素,并将其作为内生变量加入VAR模型当中,最后运用VAR模型对我国债券市场信用价差进行预测,结果表明VAR模型能够很好地预测我国债券市场的信用价差,不同期限的信用价差的时间序列呈现不同的时间序列特征.
英文摘要：
This paper selects some trading information of corporate bonds and treasury bonds on a monthly basis, after sol- ving SV model of term structure of interest rates through genetic algorithm, the more accurate term structure of both types of bonds can be obtained, based on which the credit spreads between them generate. Using multiple regression equations to de- pict significant factors which affect the credit spreads, then it puts them join VAR model and obtain sample static forecast. Then it can be concluded that the VAR model can forecast Chinese bonds market credit spreads well, and credit spreads of different maturities present different time series characteristics.
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