344 – Methods in Financial Econometrics
A Generalized Feedback Asymmetric Conditional Autoregressive Range Model
Isuru Ratnayake
Missouri University of Science and Technology
The Conditional Autoregressive Range (CARR) model is an alternative to the Generalized Autoregressive Conditionally Heteroscedastic (GARCH) approach of modeling volatility. The former models the price range while the latter focuses on modeling the price returns. The Asymmetric CARR (ACARR) model was introduced to allow for separate modeling of upward and downward ranges observed within each day, with the actual range expressed as the sum of these two components. This formulation, however, ignores any feedback from one type of range to another. The Feedback Asymmetric Conditional Autoregressive Range (FACARR) was introduced in 2017 to remedy this drawback. The FACARR, however, limits this cross feedback to past ranges and do not include past conditional means. The proposed Generalized Feedback Asymmetric Conditional Autoregressive Range Model (GFACARR) removes this limitation and allows the upward range model to include both past upward and past downward ranges along with their respective conditional means. A similar model is defined for modeling downward range as well. The proposed model is more in line with the multivariate CARR model. The use of the GFACARR model is illustrated by its application to several price series, including the S&P 500.