EconPapers    
Economics at your fingertips  
 

Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity

Isao Ishida and Virmantas Kvedaras

Econometrics, 2015, vol. 3, issue 1, 1-53

Abstract: We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor’s 500 (S&P 500) and several other indices, we obtained good performance using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear heterogeneous autoregressive and other models of realized volatility.

Keywords: forecasting; moving quantiles; non-linearity; realized volatility; test (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://www.mdpi.com/2225-1146/3/1/2/pdf (application/pdf)
https://www.mdpi.com/2225-1146/3/1/2/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:3:y:2015:i:1:p:2-54:d:44835

Access Statistics for this article

Econometrics is currently edited by Prof. Dr. Kerry Patterson

More articles in Econometrics from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().

 
Page updated 2020-08-03
Handle: RePEc:gam:jecnmx:v:3:y:2015:i:1:p:2-54:d:44835