Multivariate generalized autoregressive conditional heteroscedasticity (GARCH) modeling of sector volatility transmission: A dynamic conditional correlation (DCC) model approach

2012 ◽  
Vol 6 (27) ◽  
Author(s):  
Marcelo Brutti Righi
Keyword(s):  
Conditional Correlation ◽  
Conditional Heteroscedasticity ◽  
Dynamic Conditional Correlation ◽  
Volatility Transmission ◽  
Garch Modeling ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Model Approach

scholarly journals POSSIBILITY OF RUSSIAN BONDSPOTFOLIO DIVERSIFICATION THROUGH THE USE OF ISLAMIC BONDS DURING THE COVID-19 PANDEMIC

2021 ◽  
pp. 201-209
Author(s):  
Галина Львовна Толкаченко ◽  
Павел Андреевич Карасев
Keyword(s):  
Correlation Analysis ◽  
Negative Correlation ◽  
Sovereign Debt ◽  
Corporate Bonds ◽  
Suitable Model ◽  
Investment Management ◽  
Conditional Correlation ◽  
Conditional Heteroscedasticity ◽  
Dynamic Conditional Correlation ◽  
Autoregressive Conditional Heteroscedasticity

Диверсификация - один из важнейших элементов в инвестиционной деятельности. Инвесторы пытаются найти баланс при формировании портфеля и его реструктуризации, стремясь одновременно максимизировать доходность и минимизировать риски. Целью данной работы является оценка возможности диверсификации портфеля облигаций российского рынка с помощью включения альтернативной традиционным облигациям формы - сукук в условиях пандемии COVID-19. Представленный в статье анализ такой возможности составляет определенный элемент новизны. В качестве наиболее подходящей модели для корреляционного анализ выбрана «DCC-MGARCH» модель (динамическая модель авторегрессионной условной гетероскедастичности). Результаты исследования показывают, что инвесторы, предпочитающие долговые суверенные ценные бумаги России и корпоративные облигации российских компаний, имеют возможность диверсифицировать портфель путем включения исламских облигаций. Данный вывод объясняется наличием отрицательной корреляционной связи между индексом сукук и индексами российских облигаций, как корпоративных, так и суверенных. Diversification is one of key elements in investment management. Investors strive to find a balance in the formation of a portfolio and its restructuring, simultaneously maximizing profitability and minimizing risks. The purpose of this work is to assess the possibility of diversification of the Russian bonds portfolioby including an alternative to traditional bonds-sukuk. The DCC-MGARCH model (Dynamic Conditional Correlation Multivariate General Autoregressive Conditional Heteroscedasticity Model) was chosen as the most suitable model for correlation analysis. The results of the study show that investors who prefer Russian sovereign debt securities or corporate bonds of Russian companies couldeffectively diversify their portfolio by including Islamic bonds during the COVID-19 pandemic. This conclusion is explained by the presence of a negative correlation between the Dow Jones Sukuk Index as a proxy for sukuk market and the indices of Russian bonds, both corporate and sovereign.

scholarly journals When Elon Musk Changes his Tone, Does Bitcoin Adjust Its Tune?

2022 ◽  
Author(s):  
Toan Luu Duc Huynh
Keyword(s):  
Social Media ◽  
Textual Analysis ◽  
Causal Relation ◽  
Window Size ◽  
Media Content ◽  
Conditional Correlation ◽  
Conditional Heteroscedasticity ◽  
Dynamic Conditional Correlation ◽  
The Relationship ◽  
Autoregressive Conditional Heteroscedasticity

AbstractWe present a textual analysis that explains how Elon Musk’s sentiments in his Twitter content correlates with price and volatility in the Bitcoin market using the dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity model, allowing less sensitive to window size than traditional models. After examining 10,850 tweets containing 157,378 words posted from December 2017 to May 2021 and rigorously controlling other determinants, we found that the tone of the world’s wealthiest person can drive the Bitcoin market, having a Granger causal relation with returns. In addition, Musk is likely to use positive words in his tweets, and reversal effects exist in the relationship between Bitcoin prices and the optimism presented by Tesla’s CEO. However, we did not find evidence to support linkage between Musk’s sentiments and Bitcoin volatility. Our results are also robust when using a different cryptocurrency, i.e., Ether this paper extends the existing literature about the mechanisms of social media content generated by influential accounts on the Bitcoin market.

scholarly journals Does Gold Act as a Hedge or a Safe Haven against Equity and Currency in Asia?

2018 ◽  
Vol 20 (1) ◽  
pp. 105-118 ◽  
Author(s):  
Muhammad Aftab ◽  
Syed Zulfiqar Ali Shah ◽  
Izlin Ismail
Keyword(s):  
Financial Markets ◽  
National Currency ◽  
Currency Markets ◽  
Safe Haven ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
The Us ◽  
Us Dollar ◽  
Managing Risk ◽  
Autoregressive Conditional Heteroscedasticity

In recent years, uncertainty in financial markets has stimulated the need to explore alternative avenues for safeguarding wealth and managing risk. In this strand of research, gold has been particularly important due to its potential to mitigate risk and preserve wealth. This study investigates gold behaviour against equities and currencies in three regions across Asia. We follow Engle’s (2002) dynamic conditional correlation-multivariate generalized autoregressive conditional heteroscedasticity (DCC-MGARCH) model to test the gold link with equity and currency markets. We use a weekly series of exchange rate (national currency/the US dollar), equity and gold prices in national currency over the weekly period, 1995–2013. The sample consists of 12 countries covering East Asia, South Asia and Southeast Asia. Findings suggest that gold is just a diversifier against stocks in the Asian economies except in Korea, Singapore and Thailand. However, gold acts as a hedge and safe haven against Asian currencies—except China and Hong Kong—thus still preserving its monetary role.

scholarly journals Time-Varying Conditional Co-movement between Inter-Sector Stock Returns: Evidence from Ghana Stock Market

2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Thomas Appiah ◽  
Abednego Forson
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Time Varying ◽  
Conditional Correlation ◽  
Domestic Markets ◽  
Dynamic Conditional Correlation ◽  
Fund Managers ◽  
Diversification Strategies ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Sector Returns

Investors generally exhibit home bias with regards to their investment destinations. To diversify their portfolio, such investors invest in different sectors within the domestic economy. However, such behaviour could be counter-productive in periods of increased co-movement of assets returns.  In this paper, we examine the inter-sector stock return co-movement among the major sectors of the Ghanaian economy with the view to shedding some light on the nature of assets return correlations and its implications for portfolio diversification.  A sample of 332 weekly observations of stock returns of five major sectors within the Ghanaian economy is used to undertake the analysis. Dynamic Conditional Correlation - Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) techniques are applied to the weekly stock return series from January 2010 to June 2017. The DCC-GARCH model was estimated with correlation targeting and asymmetric DCC. We find dynamic conditional correlation among stock returns of all the sectors, implying that the correlation between the sector returns is time-varying. This result challenges the assumption of constant correlation among stock returns of different sectors in the domestic markets. We also find that the conditional correlation between returns of the various sectors ranges from 0.234 to 0.998, which indicates medium to very high interdependence among the stock returns. Based on the result of this study, we propose that fund managers and investors should not limit their diversification strategies to inter-sector investments since in periods of uncertainty, the ability of the investor to enjoy diversification benefits is seriously undermined.

scholarly journals Price Volatility Transmission in China’s Hardwood Lumber Imports

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1147
Author(s):  
Xiudong Wang ◽  
Zhonghua Yin ◽  
Ruohan Wang
Keyword(s):  
Price Volatility ◽  
Forest Products ◽  
Tectona Grandis ◽  
Policy Implications ◽  
Conditional Correlation ◽  
Price Fluctuations ◽  
Dynamic Conditional Correlation ◽  
Volatility Transmission ◽  
Hardwood Lumber ◽  
Timber Trade

Hardwood lumber is the principal part of the global hardwood timber trade. China has become the largest importer of hardwood lumber in the world. However, China’s hardwood lumber imports are affected by price volatility. Thus, we investigated the price volatility transmission of China’s hardwood lumber imports. We aimed to detect the source, path, and intensity of the volatility transmission in China’s hardwood lumber imports, and reveal the intrinsic interactions between price volatilities. To date, there is little research on the price fluctuations of forest products. This paper provides an empirical analysis on the volatility transmission in China’s forest product imports. We selected four types of major hardwood lumber imports to China; that is, teak (Tectona grandis L.F.), merbau (Merbau), sapele (Entandrophragma), and casla (Terminalia spp.) (The Latin names of tree species are given in parentheses), and used their daily prices from 4 August 2010 to 15 April 2020. The Baba–Engle–Kraft–Kroner (BEKK) multivariate models and dynamic conditional correlation (DCC) models were employed. The empirical results indicate that there is an intrinsic relationship between the price fluctuations in China’s hardwood lumber imports. The volatility transmission chain originates from casla; it is transmitted along the casla→sapele→merbau→teak pathway. The direction of transmission is from lower prices to higher prices. The dynamic conditional correlation of each link in the chain does not exhibit any particular time trend. This suggests that volatility transmission is a crucial price mechanism in China’s hardwood lumber imports. Our findings have important policy implications for hedging timber price risks and designing timber trade policies.

Sign in / Sign up

Export Citation Format

Share Document