Time-varying correlation between agricultural commodity and energy price dynamics with Bayesian multivariate DCC-GARCH models

YA Shiferaw - Physica A: Statistical Mechanics and Its Applications, 2019 - Elsevier
This article investigates the dependence structure between the agricultural commodity
prices (white maize, yellow maize, wheat, sunflower and soya) and energy prices (oil …

Emerging digital economy companies and leading cryptocurrencies: insights from blockchain-based technology companies

M Ghaemi Asl, MM Rashidi… - Journal of Enterprise …, 2021 - emerald.com
Purpose The purpose of this study is to investigate the correlation between the price return
of leading cryptocurrencies, including Bitcoin, Ethereum, Ripple, Litecoin, Monero, Stellar …

Relationships among the fossil fuel and financial markets during the COVID-19 pandemic: evidence from bayesian DCC-MGARCH models

C Tang, K Aruga - Sustainability, 2021 - mdpi.com
This study examined how the relationships among the fossil fuel, clean energy stock, gold,
and Bitcoin markets have changed since the COVID-19 pandemic took place for hedging the …

[HTML][HTML] A garch tutorial with R

MS Perlin, M Mastella, DF Vancin… - Revista de Administração …, 2020 - SciELO Brasil
Context: modeling volatility is an advanced technique in financial econometrics, with several
applications for academic research. Objective: in this tutorial paper, we will address the topic …

Dynamic relationship between oil price and inflation in South Africa

M Balcilar, J Uwilingiye, R Gupta - The Journal of Developing Areas, 2018 - JSTOR
The oil price-inflation relationship has been at the center of attention among economists and
policy analysts, especially after 1970's oil shocks that resulted in a significant increase in the …

Multivariate GARCH models for large-scale applications: A survey

K Boudt, A Galanos, S Payseur, E Zivot - Handbook of statistics, 2019 - Elsevier
This chapter provides a survey of various multivariate GARCH specifications that model the
temporal dependence in the second moment of multivariate return series processes. The …

[HTML][HTML] Volatility spillovers between ethanol and corn prices: A Bayesian analysis

S Yosthongngam, R Tansuchat, W Yamaka - Energy Reports, 2022 - Elsevier
The relationship between corn and ethanol markets has become a popular topic and has
been investigated in various studies. However, examining the co-volatility spillover between …

The dynamic relationship among bank credit, house prices and carbon dioxide emissions in China

G Chen, K Dong, S Wang, X Du, R Zhou… - International Journal of …, 2022 - mdpi.com
This paper explores the dynamic relationship among bank credit, house prices and carbon
dioxide emissions in China by systematically analyzing related data from January 2000 to …

Reaction trend system with GARCH quantiles as action points

JA Fiorucci, GN Silva, F Barboza - Expert Systems with Applications, 2022 - Elsevier
Most trading systems developed from technical indicators are designed to operate in either
trending or non-trending markets but they are rarely useful for both markets. A reaction trend …

Information flows between the US and China's agricultural commodity futures markets—based on VAR–BEKK–Skew-t model

Q Chen, X Weng - Emerging Markets Finance and Trade, 2018 - Taylor & Francis
The information flow in the volatility and the skewness of returns are two factors closely
influences the hedging risks for cross-border transactions. This article adopts a VAR–BEKK …