Keywords and Phrases
CARR; Financial Volatility; GARCH; Heteroscedastic; Modeling And Forecasting; Time Series
"Models with a conditional heteroscedastic variance structure play a vital role in many applications, including modeling financial volatility. In this dissertation several existing formulations, motivated by the Generalized Autoregressive Conditional Heteroscedastic model, are further generalized to provide more effective modeling of price range data well as count data. First, the Conditional Autoregressive Range (CARR) model is generalized by introducing a composite range-based multiplicative component formulation named the Composite CARR model. This formulation enables a more effective modeling of the long and short-term volatility components present in price range data. It treats the long-term volatility as a stochastic component that in itself exhibits conditional volatility. The Generalized Feedback Asymmetric CARR model presented in this dissertation is a generalization of the Feedback Asymmetric CARR model, with lagged cross-conditional range terms added to allow complete feedback across the two equations that model upward and downward price ranges. A regime-switching Threshold Asymmetric CARR model is also proposed. Its formulation captures both asymmetry and non-linearity, which are two main characteristics that exist in the price range data. This model handles asymmetry and non-linearity better than its range-based competitors, based on the Akaike’s Information Criteria. In addition to the above models, a Time Varying Zero Inflated Poisson Integer GARCH model is introduced. This model enables the modeling of time series of count data with excess number of zeroes where this excess varies with time. In this model, the zero inflation component is modeled either as a deterministic function of time or as a vector of stochastic variables"--Abstract, page iv.
Samaranayake, V. A.
Olbricht, Gayla R.
Paige, Robert L.
Gelles, Gregory M.
Mathematics and Statistics
Ph. D. in Mathematics
Missouri University of Science and Technology
Journal article titles appearing in thesis/dissertation
- Modeling and forecasting financial volatility using composite CARR models
- A generalized feedback asymmetric conditional autoregressive range model
- Threshold asymmetric conational autoregressive range (TACARR) model
- An integer GARCH model for poisson processes with time varying zero inflation
xviii, 197 pages
© 2021 Ratnayake Mudiyanselage Isuru Panduka Ratnayake, All rights reserved.
Dissertation - Open Access
Electronic OCLC #
Ratnayake, Ratnayake Mudiyanselage Isuru Panduka, "Modeling time series with conditional heteroscedastic structure" (2021). Doctoral Dissertations. 2982.