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Browsing by Subject "GARCH model"

Browsing by Subject "GARCH model"

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  • Examining the volatility spillover in leading cryptocurrencies and investigating the hedge/safe haven properties of Ethereum 
    Baz, Roland (Notre Dame University-Louaize, 2020-12)
    Purpose: This paper investigates the interconnectedness of the five largest cryptocurrencies in terms of market capitalization namely, Bitcoin, Ethereum, Ripple, Bitcoin Cash and Litecoin through a volatility spillover inspection. It also studies the hedging and/or safe haven capabilities of Ethereum, the second largest cryptocurrency in terms of market capitalization, against the main conventional currencies and the traditional assets in the United States and the European markets. Design/methodology/approach: In the first part of the research, univariate general autoregressive conditional ...
  • Impact of news announcements on stock market returns and volatility spillover across north America, European Union and Pacific Asia 
    Saliba, Karim Khalil (Notre Dame University-Louaize, 2020-02)
    Purpose – This thesis has two objectives. The first one is to test empirically the level of interdependence across major stock markets returns, namely, US, EU, and Asia in terms of return and volatility spillover. The second one is to evaluate the impact of news announcements on their stock market volatility. Design/methodology/approach – To model the volatility of the three above mentioned stock markets we apply a battery of univariate time series models from the GARCH family. Dickey Fuller unit root test is used in order to ensure that the three return series are stationary. The mean equation ...
  • Modeling the crude oil volatility : Garch & EVT 
    Azar, Milad Fouad (Notre Dame University-Louaize, 2018-04)
    Purpose: This study has two main purposes. First, Assess and compare the predictive ability of the Exponentially Weighted Moving Average EWMA, the Generalized Autoregressive Conditional Heteroscedasticity EGARCH (1, 1), the Exponential Generalized Autoregressive Conditional Heteroscedasticity EGARCH (1, 1), and the Glosten, Jagannathan, and Runkle Generalized Autoregressive Conditional heteroscedasticity GJR-GARCH. Second, Value at Risk is calculated using the Historical Simulation approach and the Extreme Value Theory. Methodology, Design and Approach: The models’ parameters are estimated from ...
  • Modeling the volatility and value at risk of cryptocurrencies and fiat currencies using GARCH models 
    Haddad, Omar (Notre Dame University-Louaize, 2020-05)
    Purpose: The purpose of this thesis is to investigate and assess the predictive ability of the GARCH (1,1), IGARCH (1,1), EGARCH (1,1), GJR-GARCH (1,1), APARCH (1,1), TGARCH (1,1) and CGARCH (1,1) models in forecasting the volatilities of six major cryptocurrencies: Bitcoin, Ripple, Litecoin, Monero, Dash, Dogecoin and six world currencies: Euro, British Pound, Canadian Dollar, Australian Dollar, Swiss Franc and the Japanese Yen. The optimal volatility model selected for each virtual and hard currency is then integrated into the Volatility Update Historical Simulation approach to evaluate the ...
  • Volatility and value at risk : crypto versus Fiat currencies 
    El Chidiac, Johnny (Notre Dame University-Louaize, 2019)
    Purpose: The purpose of this thesis is to investigate the ability of EWMA, GARCH (1, 1), GARCH (p, q) and EGARCH (1, 1) to forecast volatilities of Bitcoin, Ripple, EURUSD, GBPUSD and CNYUSD. The optimal volatility model for each fiat and virtual currency is used to measure the accuracy of VaR by incorporating the volatility update into the Historical Simulation approach. Design/Methodology/Approach: In-sample returns are calculated from daily closing prices and are used in estimating the parameters of the selected models. The calculated in-sample parameters are applied to estimate and forecast ...