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Asymmetry, realised volatility and stock return risk estimates
Grané, Aurea; Veiga, Helena - In: Portuguese economic journal 11 (2012) 2, pp. 147-164
Persistent link: https://www.econbiz.de/10009581964
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The predictability, volatility persistence, and leverage effects in stock market returns : a study of BRICS stock market indices
Joo, Bashir Ahmad; Ghulam, Younis Ahmed - In: American journal of finance and accounting 7 (2023) 3/4, pp. 188-213
Persistent link: https://www.econbiz.de/10014490945
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Evaluating an EGARCH model with fat tails, skewness and leverage in forecasting VaR
Benito Muela, Sonia - In: Journal of contemporary management : JMC 4 (2015) 3, pp. 67-80
Persistent link: https://www.econbiz.de/10011392904
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Overnight news and daily equity trading risk limits
Ahoniemi, Katja; Fuertes, Ana María; Olmo, Jose - In: Journal of financial econometrics : official journal of … 14 (2016) 3, pp. 525-551
Persistent link: https://www.econbiz.de/10011623670
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The role of trading volume in forecasting market risk
Slim, Skander - In: Inventi impact: international trade (2016) 3, pp. 169-181
Persistent link: https://www.econbiz.de/10011567980
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Comparison of semi-parametric and benchmark value-at-risk models in several time periods with different volatility levels
Buczyński, Mateusz; Chlebus, Marcin - In: E-Finanse : finansowy kwartalnik internetowy 14 (2018) 2, pp. 67-82
-GARCH(1,1), CAViaR and historical simulation models in periods with contrasting volatility trends (increasing, constantly high … volatility trend. However, GARCH-st (1,1) and QML-GARCH(1,1) were found to be the most robust models in the different volatility … periods. The results show as well that the CAViaR model forecasts were less appropriate in the increasing volatility period …
Persistent link: https://www.econbiz.de/10011967246
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Prediction of financial downside-risk with heavy-tailed conditional distributions
Mittnik, Stefan; Paolella, Marc S. - 2003
The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution...
Persistent link: https://www.econbiz.de/10009765347
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Forecasting volatility with many predictors
Ke, Tsung-han; Hu, Yu-pin - In: Journal of forecasting 32 (2013) 8, pp. 743-754
Persistent link: https://www.econbiz.de/10010344461
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Forecasting financial volatility of the Athens stock exchange daily returns : an application of the asymmetric normal mixture GARCH model
Drakos, Anastassios A.; Kouretas, Georgios P.; … - In: International journal of finance & economics : IJFE 15 (2010) 4, pp. 331-350
Persistent link: https://www.econbiz.de/10008811307
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Empirical testing of models of autoregressive conditional heteroscedasticity used for prediction of the volatility of Bulgarian investment funds
Petrova, Mariana; Todorov, Teodor - In: Risks : open access journal 11 (2023) 11, pp. 1-30
forecasting the daily volatility of Bulgarian investment funds, which will support the investment community in making adequate ….1) are adapted to predict the volatility of investment funds. The current development focuses on forecasting the risk … group. The object of the study includes quantitative analysis, estimation and forecasting of daily volatility through the …
Persistent link: https://www.econbiz.de/10014436423