GARCH Parameter Estimation Using High-Frequency Data

Modal parameter estimation from ambient data using time-frequency analysis

Abstract Modal parameter estimation of randomly and ambient excited structures using output-only system identification techniques has become a recently essential issue for assessment of engineering structures, structural health monitoring and structural control. A number of mathematical models on the output-only identification techniques have been developed in the time domain, in the frequency ...

Parameter estimation in nonlinear AR - GARCH models

This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a general nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a general nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. We do not require the rescaled errors to be ind...

ARCH–GARCH approaches to modeling high-frequency financial data

We model the power-law stability in distribution of returns for S&P500 index by the GARCH process which we use to account for the long memory in the variance correlations. Precisely, we analyze the distributions corresponding to temporal aggregation of the GARCH process, i.e., the sum of n GARCH variables. The stability in the power-law tails is controlled by the GARCH parameters. We model the ...

The effect of parameter estimation on Phase II control chart performance in monitoring financial GARCH processes with contaminated data

The application of control charts for monitoring financial processes has received a greater focus after recent global crisis. The Generelized AutoRegressive Conditional Heteroskedasticity (GARCH) time series model is widely applied for modelling financial processes. Therefore, traditional Shewhart control chart is developed to monitor GARCH processes. There are some difficulties in financial su...

Estimation of Continuous–Time Financial Models Using High–Frequency Data