Nonparametric and Semiparametric Volatility Models: Specification, Estimation, and Testing

• Main Authors: SU, Liangjun, ULLAH, Aman, MISHRA, Santosh, WANG, Yun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2012
• Subjects: nonparametric semiparametric volatility models; nonparametric semiparametric multivariate volatility models; error density specification; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1366; https://search.library.smu.edu.sg/primo-explore/fulldisplay?docid=TN_wilbooks10.1002/9781118272039.ch11&context=PC&vid=SMU_NUI&search_scope=Everything&tab=default_tab&lang=en_US
• Institution: Singapore Management University

In recent years, an extensive literature has developed on studying the volatility in financial markets. The simplest approach in this literature regards volatility as a time-invariant constant parameter σ. However, this is contradicted in some of the real world financial data, where a specific pattern of return variability is observed. These changes are often referred to as the volatility clustering and as first noted by Mandelbrot (1963), this is the property of prices that "large changes tend to be followed by large changes—of either sign—and small changes tend to be followed by small changes." As a consequence, there has been a concerted attempt to model this time-varying volatility.