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Reexamining the likelihood of extreme returns in international stock market
Wang, Yun-Yi; Kao, Tzu-Chuan; Lin, Chu-Hsiung; Wei, Tsun-Jen - In: Investment management and financial innovations 12 (2015) 4, pp. 106-114
Persistent link: https://www.econbiz.de/10011575057
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GARCH models, tail indexes and error distributions : an empirical investigation
Šopov, Boril; Horváth, Roman - 2015
We perform a large simulation study to examine the extent to which various generalized autoregressive conditional heteroskedasticity (GARCH) models capture extreme events in stock market returns. We estimate Hill's tail indexes for individual S&P 500 stock market returns ranging from 1995-2014...
Persistent link: https://www.econbiz.de/10010529886
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GARCH models, tail indexes and error distributions : an empirical investigation
Horváth, Roman; Šopov, Boril - In: The North American journal of economics and finance : a … 37 (2016), pp. 1-15
Persistent link: https://www.econbiz.de/10011672845
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Stock Index Returns' Density Prediction Using GARCH Models : Frequentist or Bayesian Estimation?
Hoogerheide, Lennart F. - 2017
provided between frequentist and Bayesian estimation. No significant difference is found between the qualities of the forecasts …
Persistent link: https://www.econbiz.de/10012976219
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Volatility behavior of asset returns based on robust volatility ratio : empirical analysis on global stock indices
Shaik, Muneer; Maheswaran, S. - In: Cogent economics & finance 7 (2019) 1, pp. 1-27
value robust volatility estimator with respect to the standard robust volatility estimator as proposed in the paper by … Muneer & Maheswaran (2018b). We show that the robust volatility ratio is unbiased both in the population as well as in finite … samples. We empirically test the robust volatility ratio on 9 global stock indices from America, Asia Pacific and EMEA markets …
Persistent link: https://www.econbiz.de/10012023869
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Revisiting the auto-regressive integrated moving average approach to modelling volatility using Bahrain all share index daily returns
Doblas, Mark P.; Natarajan, Vinodh Kesavaraj; Sankar, … - In: Middle East journal of management : MEJM 10 (2023) 6, pp. 619-636
Persistent link: https://www.econbiz.de/10014424552
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Modeling stock market return volatility : GARCH evidence from Nifty Realty Index
Jain, Dhara; Mittal, Sachin K.; Choudhary, Vipin - In: Finance India : the quarterly journal of Indian … 36 (2022) 1, pp. 159-169
Persistent link: https://www.econbiz.de/10013349014
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Tail index estimation in the presence of covariates : stock returns' tail risk dynamics
Nicolau, João; Rodrigues, Paulo M. M.; Stoykov, Marian Z. - In: Journal of econometrics 235 (2023) 2, pp. 2266-2284
Persistent link: https://www.econbiz.de/10014471455
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GARCH models in value at risk estimation : empirical evidence from the Montenegrin stock exchange
Cerovic Smolovic, Julija; Lipovina-Božović, Milena; … - In: Economic research 30 (2017) 1,1, pp. 477-498
Persistent link: https://www.econbiz.de/10012223947
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Estimating conditional value at risk in the Tehran stock exchange based on the extreme value theory using GARCH models
Tabasi, Hamed; Yousefi, Vahidreza; Tamošaitienė, Jolanta - In: Administrative Sciences : open access journal 9 (2019) 2/40, pp. 1-17
results of the study showed that in the estimation of model parameters, assuming T-student distribution function gave better … Risk. Since the Conditional Value at Risk is a tail-related measure, Extreme Value Theory has been utilized to estimate the … volatility-clustering feature, and to estimate the parameters of the model, the Maximum Likelihood method was applied. The …
Persistent link: https://www.econbiz.de/10012137016