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Direct estimation of the risk neutral factor dynamics of Gaussian term structure models

机译:直接估计高斯期限结构模型的风险中性因子动力学

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This paper proposes panel data tests of Gaussian affine term structure models. Yield curve data for different moments in time are pooled with the factors treated as fixed effects. With fixed effects the time series properties of the price of risk canbe ignored. Results of tests with US interest rate data show that the Gaussian model is able to capture the cross sectional structure of yields as well as unrestricted factor loadings from principal components analysis. However, estimates of the mean reversion parameters in a 3-factor model differ significantly when the model is estimated from yield levels or forward differences, which is inconsistent with the Gaussian model.
机译:本文提出了高斯仿射项结构模型的面板数据检验。将不同时间点的收益率曲线数据与固定效应因素合并。如果具有固定效应,则可以忽略风险价格的时间序列属性。美国利率数据的测试结果表明,高斯模型能够从主成分分析中捕获收益的横截面结构以及不受限制的因素负荷。但是,当根据产量水平或正向差异估算模型时,三因子模型中的均值回归参数的估算存在显着差异,这与高斯模型不一致。

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