Results 21 to 30 of about 13,808,600 (300)
A Copula-Garch Modelcopula-Garch Model [PDF]
Economic Research-Ekonomska Istraživanja, 2010 AbstractIn the present study we develop a new two-dimensional Copula-GARCH model. This type of two-dimensional process is characterized by a dependency structure modeled using a copula function. For the marginal densities we employ a GARCH(1,1) model with innovations drawn from a t-Student distribution.
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Theory and Inference for a Markov-Switching GARCH Model [PDF]
We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switch in time from one GARCH process to another. The switching is governed by a hidden Markov chain. We provide sufficient conditions for geometric ergodicity
Jeroen V.K. Rombouts +2 more
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PERAMALAN VOLATILITAS SAHAM MENGGUNAKAN MODEL EXPONENTIAL GARCH DAN THRESHOLD GARCH
E-Jurnal Matematika, 2019 In financial data there is asymmetric volatility, which denotes the different movements on conditional volatility of increase and decrease financial asset returns.
SITI RAHAYU NINGSIH +2 more
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GARCH models without positivity constraints: Exponential or log GARCH? [PDF]
Journal of Econometrics, 2013 This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, which both rely on multiplicative volatility dynamics without positivity constraints. We compare the main probabilistic properties (strict stationarity, existence of moments, tails) of the EGARCH model, which are already known, with those of an asymmetric
Francq, Christian +2 more
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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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Comparing GARCH Models by Introducing Fuzzy Asymmetric Realized GARCH [PDF]
مدلسازی اقتصادسنجی, 2018 Estimation of conditional variance has lots of application reflecting economic, especially financial economics, social economics and political economics’ risk and volatility research.
Esmaiel Abounoori, Mohammad Amin Zabol
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Forecasting Inflation Applying ARIMA Model with GARCH Innovation: The Case of Pakistan
Journal of Accounting and Finance in Emerging Economies, 2021 Purpose: The research aims to build a suitable model for the conditional mean and conditional variance for forecasting the rate of inflation in Pakistan by summarizing the properties of the series and characterizing its salient features.
Tahira Bano Qasim +3 more
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Policy uncertainty, geopolitical risks and China’s carbon neutralization
Carbon Management, 2023 In the present study, it was explored how the volatility of the carbon neutrality concept index (CNCI) was affected by China economic policy uncertainty (CEPU) index, climate policy uncertainty (CPU) index, and geopolitical risk (GPR) index. According to
Liping Liu, Zheng Lü
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Modeling time-varying coffee price volatility in Ethiopia
Journal of Applied Economics, 2020 Recently, modeling and forecasting of high-frequency data (such as daily price) volatility using GARCH-MIDAS attract the attention of many researchers. Thus, the objective of this study is to model the average daily coffee price volatility from 1 January
Teshome Hailemeskel Abebe
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Calculating Value at Risk: DCC-GARCH-Copula Approach [PDF]
فصلنامه پژوهشهای اقتصادی ایران, 2020 In this paper, in order to calculate portfolio market risk of 10 selected industries indices in Tehran Stock Exchange, two models of Value Risk (VaR) and Expected shortfall (ES) have been used.
Reza Taleblou, Mohammad Mahdi Davoudi
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