Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries

By B. Awartani, Valentina Corradi. 2005

285 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. J. De Gooijer
2. Liangjun Su
3. Aman Ullah
4. S. Mishra
5. Dana Al-Najjar
6. Gloria González-Rivera
7. Rob J Hyndman
8. Xiangdong Long

In Finance

1. Aman Ullah
2. Xiangdong Long
3. S. Mishra
4. Dana Al-Najjar
5. Gloria González-Rivera
6. Rob J Hyndman
7. J. De Gooijer
8. Liangjun Su

In Management Science and Operations Research

1. J. De Gooijer
2. S. Mishra
3. Dana Al-Najjar
4. Gloria González-Rivera
5. Rob J Hyndman
6. Xiangdong Long
7. Liangjun Su
8. Tae-Hwy Lee

Citations in the corpus

• Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood (2004, methodology): “More recently, Awartani and Corradi (2003) have provided a comparison of the relative out-of-sample ability of various volatility models, with particular attention to the role of asymmetries.”
• 25 years of time series forecasting (2006, background): “Brooks (1998) finds no clear-cut winner when comparing one-stepahead forecasts from standard (symmetric) GARCHtype models with those of various linear models and ANNs. At the estimation level, Brooks, Burke, and Persand (2001) argued that standard econometric software packages can produce widely var”
• GARCH Models (2010, unknown): “Recent comparisons of asymmetric GARCH models were proposed by Awartani and Corradi (2006), Chen, Gerlach and So (2006) and Hansen and Lunde (2005).”
• Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model (2009, methodology): “comparing the predictability of univariate GARCH models, Awartani and Corradi (2005) substitute the unobservable volatility by the squared observed returns because of the rank-preserving property of this”
• 25 Years of IIF Time Series Forecasting: A Selective Review (2005, background): “Awartani & Corradi (2005) investigated the impact of asymmetries on the out of sample forecast ability of different GARCH models, at various horizons.”
• Modelling and Estimation of Volatility Using ARCH/GARCH Models in Jordan's Stock Market (2016, methodology): “Regarding the studies of Gokan (2000), Awartani and Corradi (2005), Yalami and Sevil (2008), Miron and Tudor (2010), and Su (2010); their methodologies depended on comparing between various asymmetric models proposed previously such as TGARCH, PGARCH, EGARCH, and GARCH-M; their main findings support”