Semiparametric Estimation for Time-Inhomogeneous Diffusions

摘要：

We develop two likelihood based approaches to semiparametrically estimate the time-inhomogeneous diffusion process: log penalized splines (P-splines) and the local log-linear method. Positive volatility is naturally embedded and this positivity is not guaranteed in most existing diffusion models. We investigate different smoothing parameter selection methods. Separate bandwidths are used for drift and volatility estimation. In the log P-splines approach, different smoothness for different time varying coefficients is feasible by assigning different penalty parameters. We also provide accompanying theorems for both approaches. Finally, we present a case study using the weekly three-month Treasury bill data from 1954 to 2004. We find that the log P-splines approach seems to capture the volatility dips in mid-1960s and mid-1990s the best.

关键词： Bandwidth Selection Kernel Smoothing Local Linear Penalized likelihood Variance Estimation Volatility.

作者: Yan Yu Keming Yu Hua Wang Min Li

作者单位: University of Cincinnati, USA Brunel University, UK Yahoo, USA California State University, Sacramento, USA

会议类型: 国际会议

会议名称: 2006年中国国际金融年会

会议地点: 西安

会议语种:英文

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）