Results 11 to 20 of about 13,849,659 (169)
Value at Risk Prediction for the GJR-GARCH Aggregation Model [PDF]
, 2022 Volatility is the level of risk faced due to price fluctuations. The greater the volatility brings, the greater the risk. We need a measure such as Value at Risk (VaR) and volatility modeling to overcome this. The most frequently used volatility model in
Nurhayati, Nurhayati +2 more
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International Journal of Financial Studies, 2022 Over the past years, cryptocurrencies have drawn substantial attention from the media while attracting many investors. Since then, cryptocurrency prices have experienced high fluctuations. In this paper, we forecast the high-frequency 1 min volatility of
Apostolos Ampountolas
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Asymmetry and Leverage in Conditional Volatility Models
Econometrics, 2014 The three most popular univariate conditional volatility models are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle ...
Michael McAleer
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Estimasi Nilai AVaR Menggunakan Model GJR dan Model GARCH [PDF]
, 2015 Dalam pemodelan harga saham, sering dihadapkan pada suatu pertanyaan, apakah model GARCH atau GJR yang lebih tepat merepresentasikan pergerakan harga saham?
Komang Dharmawan
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Modeling crude oil price volatility in Nigeria: using GARCH (1,1), EGARCH (1,1), and GJR-GARCH (1,1) models [PDF]
مجلة العلوم التجارية والبيئيةThis study investigates the performance of various GARCH models for volatility forecasting, focusing on the GARCH (1,1), EGARCH (1,1), and GJR-GARCH (1,1) frameworks, each tested with normal and Student’s t-distributions.
Frederick A. Omoruyi +2 more
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International Journal of Financial Studies, 2022 This paper attempted to apply an EVT-based pairwise copula method for modelling risk interaction between foreign exchange rates and equity indices of the Johannesburg Stock Exchange (JSE) and to model the dependence structure of the underlying assets ...
Joel Hinaunye Eita +1 more
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Estimation of tail thickness parameters from GJR-GARCH models [PDF]
, 2009 We propose a method of estimating the Pareto tail thickness parameter of the unconditional distribution of a financial time series by exploiting the implications of a GJR-GARCH volatility model.
Iglesias, Emma M., Linton, Oliver
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Day-of-the-week and month-of-the-year effects on French Small-Cap Volatility: the role of asymmetry and long memory [PDF]
Eastern Journal of European Studies, 2019 Small-cap stocks are characterized by high volatility and offer investors the opportunity to earn higher returns. This paper empirically investigates the impact of the day-of-the-week and the month-of-the year effects on the volatility of daily and ...
Mohamed CHIKHI +2 more
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Forecasting Performance of Asymmetric GARCH Stock Market Volatility Models
East Asian Economic Review, 2009 We investigate the asymmetry between positive and negative returns in their effect on conditional variance of the stock market index and incorporate the characteristics to form an out-of-sample volatility forecast.
Hojin Lee
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Copernican Journal of Finance & Accounting, 2015 The modelling of market returns can be especially problematical in emerging and frontier financial markets given the propensity of their returns to exhibit significant non-normality and volatility asymmetries.
Heitham Al-Hajieh +3 more
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