Search Results - subject:"leverage effects"

Towards examining the volatility of top market-cap cryptocurrencies throughout the COVID-19 outbreak and the Russia-Ukraine war : empirical evidence from GARCH-type models

Gherghina, Ştefan Cristian; Constantinescu, … - In: Risks : open access journal 13 (2025) 3, pp. 1-43

models (GARCH, EGARCH, TGARCH, and DCC-GARCH). This research aims to examine the persistence of leverage effects, volatility … future volatility for most cryptocurrencies, although leverage effects became evident during market anomalies. Stablecoins …

Persistent link: https://www.econbiz.de/10015358888

Forecasting the volatility of crude oil futures : new evidence from jump-induced volatility

Dutta, Anupam; Bouri, Elie - In: Energy strategy reviews 56 (2024), pp. 1-8

This paper proposes an augmented heterogenous autoregressive (HAR) model with time-varying jumps to forecast the realized volatility (RV) of crude oil futures. Jump-induced volatility of crude oil futures is obtained from a GARCH-jump process, then used to augment the HAR model. The results...

Persistent link: https://www.econbiz.de/10015422154

Performance attribution analysis for derivatives

Feibel, Bruce J.; Fabozzi, Frank J. - In: Derivatives Applications in Asset Management : From …, (pp. 173-192). 2025

Persistent link: https://www.econbiz.de/10015434586

Modeling and forecasting the volatility of NIFTY 50 using GARCH and RNN models

Mahajan, Vanshu; Thakan, Sunil; Malik, Aashish - In: Economies 10 (2022) 5, pp. 1-20

's volatility is asymmetric, and leverage effects are evident in the results of the EGARCH (1, 1) model. Asymmetric GARCH models …

Persistent link: https://www.econbiz.de/10015469405

Do ESG Ratings Reduce the Asymmetry Behavior in Volatility?

Zarafat, Hashem; Liebhardt, Sascha; Eratalay, Mustafa Hakan - In: Journal of Risk and Financial Management 15 (2022) 8, pp. 1-32

It is well noted in the literature that volatility responds differently to positive and negative shocks. In this paper, we explore the impact of ESG ratings on such asymmetric behavior of volatility. For this analysis, we use the return data, ESG ratings, and solvency ratios of the constituent...

Persistent link: https://www.econbiz.de/10014332521

Modeling and forecasting the volatility of NIFTY 50 using GARCH and RNN models

Mahajan, Vanshu; Thakan, Sunil; Malik, Aashish - In: Economies : open access journal 10 (2022) 5, pp. 1-20

's volatility is asymmetric, and leverage effects are evident in the results of the EGARCH (1, 1) model. Asymmetric GARCH models …

Persistent link: https://www.econbiz.de/10013199403

Do ESG Ratings Reduce the Asymmetry Behavior in Volatility?

Zarafat, Hashem; Liebhardt, Sascha; Eratalay, Mustafa Hakan - In: Journal of risk and financial management : JRFM 15 (2022) 8, pp. 1-32

Persistent link: https://www.econbiz.de/10013371062

Decoding herding dynamics in the generative AI investment amid key technological advancements : a timeline perspective

Wang, Haibo - In: Finance research letters 64 (2024), pp. 1-10

Persistent link: https://www.econbiz.de/10014531720

Beta observation-driven models with exogenous regressors : a joint analysis of realized correlation and leverage effects

Gorgi, Paolo; Koopman, Siem Jan - 2020

autoregressive model with leverage effects to analyze realized correlations for several sets of stock returns. We find that the … that our model with leverage effects can enhance the accuracy of point and density forecasts of realized correlations. …

Persistent link: https://www.econbiz.de/10012161059

Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects

Gorgi, Paolo; Koopman, Siem Jan - 2020

Persistent link: https://www.econbiz.de/10012233966

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