Nonparametric and Semiparametric Volatility Models: Specification, Estimation, and Testing
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.
nonparametric semiparametric volatility models, nonparametric semiparametric multivariate volatility models, error density specification
Handbook of volatility models and their applications
Luc Bauwens, Christian Hafner & Sebastien Laurent
City or Country
SU, Liangjun; ULLAH, Aman; MISHRA, Santosh; and WANG, Yun.
Nonparametric and Semiparametric Volatility Models: Specification, Estimation, and Testing. (2012). Handbook of volatility models and their applications. 269-291. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1366