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Fractional integration and asymmetric volatility in European, American and Asian bull and bear markets : application to high-frequency stock data
Yaya, OlaOluwa S.; Gil-Alaña, Luis A.; Shittu, … - In: International journal of finance & economics : IJFE 20 (2015) 3, pp. 276-290
Persistent link: https://www.econbiz.de/10011348408
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The volatility of daily tug-of-war intensity and stock market returns
Bai, Fan; Zhang, Yaqi; Chen, Zhonglu; Li, Yan - In: Finance research letters 55 (2023) 1, pp. 1-6
Persistent link: https://www.econbiz.de/10014473224
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International spillovers of output growth and output growth volatility : evidence from the G7
Antonakakis, Nikolaos; Badinger, Harald - In: International economic journal 26 (2012) 4, pp. 635-653
Persistent link: https://www.econbiz.de/10009734508
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Sign- and volatility-switching ARCH models : theory and applications to international stock markets
Fornari, Fabio - 1995
Persistent link: https://www.econbiz.de/10013452468
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A switching ARCH model for German DAX index
Kaufmann, Sylvia (contributor);  … - In: Studies in nonlinear dynamics and econometrics : SNDE ; … 10 (2006) 4, pp. 1-35
Persistent link: https://www.econbiz.de/10003559162
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On the Invertibility of EGARCH(p,q)
Martinet, Guillaume Gaetan; McAleer, Michael - 2015 - Revised: February 2015
Persistent link: https://www.econbiz.de/10011346214
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A one line derivation of EGARCH
McAleer, Michael; Hafner, Christian M. - 2014
One of the most popular univariate asymmetric conditional volatility models is the exponential GARCH (or EGARCH …) specification. In addition to asymmetry, which captures the different effects on conditional volatility of positive and negative … subsequent shocks to volatility. However, there are as yet no statistical properties available for the (quasi-) maximum …
Persistent link: https://www.econbiz.de/10010362978
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On the invertibility of EGARCH
Martinet, Guillaume Gaetan; McAleer, Michael - 2014
Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH …) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative … shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH …
Persistent link: https://www.econbiz.de/10010384390
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Stock returns and risk : evidence from quantile
Chiang, Thomas C.; Li, Jiandong - In: Journal of risk and financial management : JRFM 5 (2012) 1, pp. 20-58
This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four major stock indexes in the US market and finds some evidence in favor of a positive relation between the mean of the excess returns and expected risk. However, by using...
Persistent link: https://www.econbiz.de/10011555867
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On the invertibility of EGARCH(p,q)
Martinet, Guillaume Gaetan; McAleer, Michael - 2015 - Revised version: February 2015
Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH …) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative … shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH …
Persistent link: https://www.econbiz.de/10010477092