TY - JOUR
T1 - Empirical analysis of ARMA-GARCH models in market risk estimation on high-frequency US data
AU - Beck, Alexander
AU - Aaron Kim, Young Shin
AU - Rachev, Svetlozar
AU - Feindt, M.
AU - Fabozzi, Frank
PY - 2013/4
Y1 - 2013/4
N2 - In this paper, we examine the S&P 500 index log-returns on short intraday time scales with three different ARMA-GARCH models. In order to forecast market risk, we describe the innovation process with tempered stable distributions which we compare to commonly used methods in financial modeling. Value-atrisk backtests are provided where we find that models based on the tempered stable innovation assumption significantly outperform traditional models in forecasting risk on short time-scales. In addition to value-atrisk, the idiosyncratic differences in average value-at-risk are compared between the models.
AB - In this paper, we examine the S&P 500 index log-returns on short intraday time scales with three different ARMA-GARCH models. In order to forecast market risk, we describe the innovation process with tempered stable distributions which we compare to commonly used methods in financial modeling. Value-atrisk backtests are provided where we find that models based on the tempered stable innovation assumption significantly outperform traditional models in forecasting risk on short time-scales. In addition to value-atrisk, the idiosyncratic differences in average value-at-risk are compared between the models.
KW - ARMA-GARCH model
KW - Average value-at-risk (AVaR)
KW - High-frequency.
KW - Tempered stable distribution
UR - http://www.scopus.com/inward/record.url?scp=84888237852&partnerID=8YFLogxK
U2 - 10.1515/snde-2012-0033
DO - 10.1515/snde-2012-0033
M3 - Article
AN - SCOPUS:84888237852
SN - 1081-1826
VL - 17
SP - 167
EP - 177
JO - Studies in Nonlinear Dynamics and Econometrics
JF - Studies in Nonlinear Dynamics and Econometrics
IS - 2
ER -