Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model. [PDF]
PLoS ONE, 2018 In this paper, we propose a model for forecasting Value-at-Risk (VaR) using a Bayesian Markov-switching GJR-GARCH(1,1) model with skewed Student's-t innovation, copula functions and extreme value theory.
Marius Galabe Sampid +2 more
doaj +4 more sources
How to Promote the Performance of Parametric Volatility Forecasts in the Stock Market? A Neural Networks Approach [PDF]
Entropy, 2021 This study uses the fourteen stock indices as the sample and then utilizes eight parametric volatility forecasting models and eight composed volatility forecasting models to explore whether the neural network approach and the settings of leverage effect ...
Jung-Bin Su
doaj +2 more sources
Modeling Saudi stock index returns and volatility: a dual approach using GARCH and neural networks [PDF]
Frontiers in Artificial IntelligenceThe financial markets are the drivers of economic growth as they organize savings, bring in foreign investment, and they efficiently allocate resources.
Sukainah AL-Besher, Dania AL-Najjar
doaj +2 more sources
Asymmetric Behavior of Inflation Uncertainty and Friedman-Ball Hypothesis: Evidence from Pakistan [PDF]
Lahore Journal of EconomicsThis paper is a first attempt to measure and analyze inflation uncertainty in Pakistan. It makes several contributions to the literature. In the first stage, using quarterly data from 1976:01 to 2008:02, we model inflation uncertainty as a time-varying ...
Syed Kumail Abbas Rizvi, Bushra Naqvi
doaj +2 more sources
Comparing various GARCH-type models in the estimation and forecasts of volatility of S&P 500 returns during Global Finance Crisis of 2008 and COVID-19 financial crisis [PDF]
SHS Web of Conferences, 2023 In this study, we utilize various GARCH-type models to estimate and forecast volatility on S&P 500 returns and compare the results between the two financial crises, the GFC of 2008 (Global Financial Crisis of 2008) and the COVID-19 financial crisis ...
Chen Xuanyu
doaj +1 more source
Dynamical Approach in studying GJR-GARCH (Q,P) Models with Application
Tikrit Journal of Pure Science, 2022 This paper deals with finding stationarity Condition of GJR-GARCH(Q,P) model by using a local linearization technique in order to reduce this non-linear model to a linear difference equation with constant coefficients and then obtain the stationarity ...
Nooruldeen A. Noori, Azher A. Mohammad
doaj +1 more source
Volatility regimes of selected central European stock returns: a Markov switching GARCH approach
Journal of Business Economics and Management, 2022 This paper investigates the weekly stock market data of the Hungarian stock index BUX, the Czech stock index PX and the Polish stock index WIG20 spanning from January 7, 2001 to April 18, 2021.
Michaela Chocholatá
doaj +1 more source
Economic Journal of Emerging Markets, 2011 This study investigates the international price relationship and volatility transmissions between stock index and stock index futures of Malaysia, Hong Kong and Japan. Vector Autoregression (VAR) GJR-GARCH model was applied to the nine years daily price.
ArIsmail bin Ahmad +1 more
doaj +9 more sources
ESTIMASI CVAR PADA PORTOFOLIO SAHAM MENGGUNAKAN METODE GJR-EVT DENGAN PENDEKATAN D-VINE COPULA
E-Jurnal Matematika, 2022 Risk measure using Conditional Value at Risk can be calculate if values that exceeds the p-quantile is known in VaR. The models used to accommodate characteristics of the stock portfolio in this research are EVT-GARCH-D-vine copula and EVT-GJR-D-vine ...
DERY MAULANA +2 more
doaj +1 more source
The Modeling the returns volatility of Indonesian stock indices: The case of SRI-KEHATI and LQ45
Jurnal Ekonomi Modernisasi, 2022 The purpose of this research is to model the volatility of Stock Indices in Indonesian capital market. This research focuses on two stock indices namely SRI-KEHATI and LQ45.
Regi Muzio Ponziani
doaj +1 more source