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An introduction to univariate GARCH models

Teräsvirta, Timo - 2006

This paper contains a survey of univariate models of conditional heteroskedasticity. The classical ARCH model is mentioned, and various extensions of the standard GARCH model are highlighted. This includes the Exponential GARCH model. Stochastic volatility models remain outside this review.

Persistent link: https://www.econbiz.de/10010281357

FX market volatility modelling : can we use low-frequency data?

Lyócsa, Štefan; Plíhal, Tomáš; Výrost, Tomáš - In: Finance research letters 40 (2021), pp. 1-16

Persistent link: https://www.econbiz.de/10012820071

Long range dependence in an emerging stock market's sectors : volatility modelling and VaR forecasting

Abuzayed, Bana; Al-Fayoumi, Nedal; Charfeddine, Lanouar - In: Applied economics 50 (2018) 23, pp. 2569-2599

Persistent link: https://www.econbiz.de/10011850296

Revisiting the auto-regressive integrated moving average approach to modelling volatility using Bahrain all share index daily returns

Doblas, Mark P.; Natarajan, Vinodh K.; Sankar, Jayendira P. - In: Middle East journal of management : MEJM 10 (2023) 6, pp. 619-636

Persistent link: https://www.econbiz.de/10014424552

Sudden changes in crude oil price volatility : an application of extreme value volatility estimator

Kumar, Dilip - In: American journal of finance and accounting 4 (2015/2016) 3/4, pp. 215-234

Persistent link: https://www.econbiz.de/10011713524

Forecasting energy futures volatility based on the unbiased extreme value volatility estimator

Kumar, Dilip - In: IIMB management review 29 (2017) 4, pp. 294-310

Persistent link: https://www.econbiz.de/10011879691

Deep learning volatility : a deep neural network perspective on pricing and calibration in (rough) volatility models

Horvath, Blanka Nora; Muguruza, Aitor; Tomas, Mehdi - In: Quantitative finance 21 (2021) 1, pp. 11-27

Persistent link: https://www.econbiz.de/10012424629

Forecasting exchange rate volatility : GARCH models versus implied volatility forecasts

Pilbeam, Keith; Langeland, Kjell Noralf - In: International economics and economic policy : IEEP 12 (2015) 1, pp. 127-142

Persistent link: https://www.econbiz.de/10011375830

A fusion of statistical and machine learning methods : GARCH-XGBoost for improved volatility modelling of the JSE Top40 Index

Maingo, Israel; Ravele, Thakhani; Sigauke, Caston - In: International Journal of Financial Studies : open … 13 (2025) 3, pp. 1-30

Volatility modelling is a key feature of financial risk management, portfolio optimisation, and forecasting, particularly for market indices such as the JSE Top40 Index, which serves as a benchmark for the South African stock market. This study investigates volatility modelling of the JSE Top40...

Persistent link: https://www.econbiz.de/10015457865