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Forecasting Volatility: A Google Trends Augmented EGARCH Model
SSRN Electronic Journal, 2018Accurately forecasting volatility is key in many financial applications. In this study, I suggest that individuals gather information online before implementing their trading decisions. In periods of higher investor concern, online information seeking intensifies.
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Revisiting natural resources volatility via TGARCH and EGARCH
Resources Policy, 2022Yunpeng Luan +4 more
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Forecasting VIX using two-component realized EGARCH model
The North American Journal of Economics and Finance, 2023Xinyu Wu, An Zhao, Li Liu
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Analyzing CBRT's FOREX interventions using EGARCH (2001-2006) [PDF]
, 2007 The post-2001 period in the Turkish economy witnessed many stabilization efforts and regulations applied by policy makers so as to eliminate the effects of the economic crisis on the economy. Dealing with the monetary policy, these policies were conducted in favor of just-in-time interventions when the volatilities in some main monetary aggregates were
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Forecasting Volatilities and Correlations with EGARCH Models
The Journal of Derivatives, 1993Robert Cumby +2 more
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Pemodelan Volatilitas Harian Menggunakan Pendekatan Realized EGARCH-CJ
This study compares the performance of Realized Exponential GARCH (REGARCH) and REGARCH with Continuous and Jump components (REGARCH-CJ) models in modeling the volatility of financial assets based on daily data from Tokyo Stock Prince Index (TOPIX) over the period January 2004 to December 2011.openaire +1 more source