Short-term effect of COVID-19 pandemic on cryptocurrency markets: A DCC-GARCH model analysis. [PDF]
Heliyon, 2023 This research examines the impact of the coronavirus index on the returns and volatility of ten major cryptocurrencies during the COVID-19 pandemic. For this purpose, we applied a multivariate volatility GARCH model with an integrated dynamic conditional correlation (DCC) approach to daily cryptocurrency values observed data during the January-December,
Ben-Ahmed K, Theiri S, Kasraoui N.
europepmc +5 more sources
An empirical investigation of investor sentiment and volatility of realty sector market in India: an application of the DCC-GARCH model. [PDF]
SN Bus Econ, 2023 Understanding how an irrational investors' sentiment affects the realty market returns, especially during the pandemic, is imperative to take any financial decisions. The effect of investor sentiment on the movement of the realty market leading to market volatility is dynamically represented in a numerical form. The study incorporates daily market data
Pillada N, Rangasamy S.
europepmc +3 more sources
Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework [PDF]
Mathematics, 2021 The research paper is devoted to developing a mathematical approach for dealing with time-varying parameters in rolling window logit models for credit risk assessment. Forecasting coefficients yields a better model accuracy than a trivial approach of using computed past statistics parameters for the next time period.
Nikita Moiseev +2 more
exaly +3 more sources
On the hedge and safe-haven abilities of bitcoin and gold against blue economy and green finance assets during global crises: Evidence from the DCC, ADCC and GO-GARCH models. [PDF]
PLoS ONEThis paper investigates the diversification, hedging, and safe-haven capabilities of Bitcoin and gold against blue economy and green finance assets using three different MGARCH models (DCC, ADCC, and GO-GARCH) during adverse events such as the COVID-19 ...
Yasmine Snene Manzli +4 more
doaj +2 more sources
Impact of the COVID-19 pandemic on return and risk transmission between oil and precious metals: Evidence from DCC-GARCH model. [PDF]
Resour Policy, 2022 Yıldırım DÇ, Esen Ö, Ertuğrul HM.
europepmc +2 more sources
Cogent Economics & FinanceThis study explores the volatility spillover effects between clean and dirty cryptocurrencies and key financial indices, specifically focusing on Green Finance Indices (such as solar, wind, and nuclear) and Economic Indices (like the Baltic Dry Index and
Iulia Cristina Iuga +2 more
doaj +3 more sources
Using Multivariate Dynamic Conditional Correlation GARCH model to analysis financial market data [PDF]
Maǧallaẗ Al-Buḥūṯ Al-Tiǧāriyyaẗ, 2023 In financial markets, understanding the dynamic relationships between assets is crucial for effective portfolio management. This study highlights the importance of using the DCC-GARCH (Dynamic Conditional Correlation - Generalized Autoregressive ...
Fatma Alshenawy, Doaa A. Abdo
doaj +1 more source
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
doaj +1 more source
Application of futures in calculating optimal hedge ratio in crude oil market: Comparison between static and dynamic approaches [PDF]
مدلسازی اقتصادسنجی, 2020 Futures are used as the most important risk hedge tools to reduce the risk of the crude oil market. The optimal hedging risk strategy is determined by calculating the optimal hedging risk ratio.
Simin Aleali +3 more
doaj +1 more source
Journal of Mathematical FinanceThe paper selects the daily trading data of three stocks in the agricultural sector of the Chinese stock market from 1st September 2015 to 31st August 2021. It uses the DCC-GARCH model to study the correlation between these stocks to examine the volatility and conductivity of their risks.
Simin Wu
exaly +3 more sources