This paper aims to examine the stochastic behavior of green bond premiums that can characterize the benefits of green bonds. We propose a novel affine model of green bond pricing with mean-reverting interest rates and green bond premiums and a new model parameter estimation method using conventional and green bond prices to capture the stochastic behavior. Then, the model parameter estimation results demonstrate mean-reverting stochastic behavior for conventional bond yield and green bond premium using the US and EU green bond indices for Corporate and three corporate bond indices for intermediate, total, and long-term periods of the Bloomberg Fixed Income Indices from November 3, 2014 to December 11, 2020. Comparative statics using simulated green bond premiums show that green bond premiums orient toward negative values in nature. Moreover, the stochastic behavior of green bond premiums demonstrates that the greenness of green bonds has a downward effect on interest rates in COVID-19 and has a mitigating impact on liquidity risk in corporate bond markets. These results confirm the benefits of green bonds. Finally, the discussions secure the validity of the green bond pricing model by conducting econometric analyses of the regime-switching model, principal component analyses, and the GARCH (1,1) model.

中文翻译：

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绿色债券溢价的随机行为


本文旨在研究绿色债券溢价的随机行为，这些行为可以表征绿色债券的好处。我们提出了一种新的绿色债券定价仿射模型，具有均值回归利率和绿色债券溢价，以及一种新的模型参数估计方法，使用传统和绿色债券价格来捕捉随机行为。然后，模型参数估计结果显示了传统债券收益率和绿色债券溢价的均值回归随机行为，使用美国和欧盟的公司绿色债券指数以及 2014 年 11 月 3 日至 2020 年 12 月 11 日彭博固定收益指数的中期、总期和长期三个公司债券指数。使用模拟绿色债券溢价的比较统计数据表明，绿色债券溢价在自然界中趋向于负值。此外，绿色债券溢价的随机行为表明，绿色债券的绿色性对 COVID-19 中的利率有下行影响，并对公司债券市场的流动性风险有缓解影响。这些结果证实了绿色债券的好处。最后，讨论通过对制度转换模型、主成分分析和 GARCH （1,1） 模型进行计量经济学分析，确保绿色债券定价模型的有效性。