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Assessment of volatility using exponential generalized autoregressive conditional heteroscedastic model in BSE stock market

Kundu, Amit - In: The Indian journal of economics 97 (2017) 387, pp. 589-605

Persistent link: https://www.econbiz.de/10011991586

How useful are the various volatility estimators for improving GARCH-based volatility forecasts? : evidence from the Nasdaq-100 stock index

Wang, Jying-Nan; Hsu, Yuan-Teng; Liu, Hung-Chun - In: International journal of economics and financial issues … 4 (2014) 3, pp. 651-656

Persistent link: https://www.econbiz.de/10010526918

Do we need stochastic volatility and generalised autoregressive conditional heteroscedasticity? : Comparing squared end-of-day returns on ftse

Allen, David E.; McAleer, Michael - In: Risks : open access journal 8 (2020) 1/12, pp. 1-20

The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional … Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV … standard volatility models if the simple expedient of using lagged squared demeaned daily returns provides a better RV …

Persistent link: https://www.econbiz.de/10012203997

Predicting volatility of bitcoin returns with ARCH, GARCH and EGARCH models

Yildirim, Hakan; Bekun, Festus Victor - In: Future Business Journal 9 (2023), pp. 1-8

market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of … to identify the best fit model that can predict the volatility of return of Bitcoin, which is in high demand as an … the residuals of the average equation model selected have ARCH effect. Volatility of Bitcoin return series after detection …

Persistent link: https://www.econbiz.de/10014382180

Tail estimation and conditional modeling of heteroscedastic time-series

Paolella, Marc S. - 1999 - 1. Aufl.

Persistent link: https://www.econbiz.de/10001388258

Fractional integration and fat tails for realized covariance kernels and returns

Lucas, André; Opschoor, Anne - 2016 - This version: September 1, 2016

We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance...

Persistent link: https://www.econbiz.de/10011531139

Nonparametric estimation and inference for conditional density based Granger causality measures

Taamouti, Abderrahim; Bouezmarni, Taoufik; El Ghouch, Anouar - In: Journal of econometrics 180 (2014) 2, pp. 251-264

Persistent link: https://www.econbiz.de/10010433362

Multivariate asset return prediction with mixture models

Paolella, Marc S. - In: The European journal of finance 21 (2015) 13/15, pp. 1214-1252

Persistent link: https://www.econbiz.de/10011419842

Extreme quantile estimation for β-mixing time series and applications

Chavez-Demoulin, Valérie; Guillou, Armelle - In: Insurance / Mathematics & economics 83 (2018), pp. 59-74

Persistent link: https://www.econbiz.de/10011944097

Estimation of asymmetric stochastic volatility models for stock-exchange index returns

Del Carmen García Centeno, María; Minguez Salido, Román - In: International advances in economic research : IAER ; an … 15 (2009) 1, pp. 71-87

Persistent link: https://www.econbiz.de/10003813391