Results 81 to 90 of about 11,730 (214)
Modeling the Interactions between Volatility and Returns using EGARCH‐M
Journal of Time Series Analysis, 2018 An EGARCH‐M model, in which the logarithm of scale is driven by the score of the conditional distribution, is shown to be theoretically tractable as well as practically useful. A two‐component extension makes it possible to distinguish between the short‐ and long‐run effects of returns on volatility, and the resulting short‐ and long‐run volatility ...
Lange, Rutger-Jan, Harvey, AC
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The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk [PDF]
, 2018 The aim of this study is to analyze the relevance of recently developed news-based measures of economic policy and equity market uncertainty in causing and predicting the conditional quantiles of crude oil returns and risk.
Bonaccolto, G. +2 more
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Multivariate range-based EGARCH models
International Review of Financial Analysis, 2022 Lili Yan +2 more
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Tail risk forecasting using Bayesian realized EGARCH models
, 2020 This paper develops a Bayesian framework for the realized exponential generalized autoregressive conditional heteroskedasticity (realized EGARCH) model, which can incorporate multiple realized volatility measures for the modelling of a return series. The realized EGARCH model is extended by adopting a standardized Student-t and a standardized skewed ...
Tendenan, Vica +2 more
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MEMBANDINGKAN RISIKO SISTEMATIS MENGGUNAKAN CAPM-GARCH DAN CAPM-EGARCH
E-Jurnal Matematika, 2017 In making stock investments, investors usually pay attention to the rate of return and risk of the stock investment. To calculate risk using capital asset pricing model (CAPM), GARCH, and EGARCH.
VIKY AMELIAH +2 more
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Improving Value-at-Risk Estimation from the Normal EGARCH Model
Contemporary Economics, 2017 Returns in financial assets display consistent excess kurtosis and skewness, implying the presence of large fluctuations not forecasted by Gaussian models. This paper applies a resampling method based on the bootstrap and a bias-correction step to improve Value-at-Risk (VaR) forecasting ability of the n-EGARCH (normal EGARCH) model and correct the VaR ...
Gorji, Mahsa, Sajjad, Rasoul
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VOLATILITY ANALYSIS USING THE EGARCH METHOD: CASE STUDY OF BBCA, BMRI, BRIS
Assets: Jurnal Akuntansi dan PendidikanThis study aimed to test the volatility model of BBCA and BMRI stocks on the IDX. The research problem is whether there is an influence of BBCA and LQ45 volatility on BMRI and vice versa.
Suhendro Suhendro, Purnama Siddi
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"Daily Tourist Arrivals, Exchange Rates and Volatility for Korea and Taiwan" [PDF]
Both domestic and international tourism are a major source of service export receipts for many countries worldwide, and is also increasingly important in Taiwan. One of the three leading tourism source countries for Taiwan is the Republic of Korea, which
Chia-Lin Chang, Michael McAleer
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Modelos ARCH, GARCH y EGARCH: aplicaciones a series financieras
Cuadernos de Economía, 2008 En este artículo se incluye una descripción de los modelos<br />ARCH, GARCH y EGARCH, y de los procesos de estimación de sus<br />parámetros usando máxima verosimilitud. Se propone un modelo<br />alternativo para el análisis de series financieras y se estudian<br />las series de precios y de retornos de las acciones de<br ...
Casas Monsegny, Marta +1 more
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International Journal of Financial StudiesVolatility 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.
Israel Maingo +2 more
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