multivariate volatility
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2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Afees A. Salisu ◽  
Kingsley Obiora

AbstractThis study examines the hedging effectiveness of financial innovations against crude oil investment risks, both before and during the COVID-19 pandemic. We focus on the non-energy exchange traded funds (ETFs) as proxies for financial innovations given the potential positive correlation between energy variants and crude oil proxies. We employ a multivariate volatility modeling framework that accounts for important statistical features of the non-energy ETFs and oil price series in the computation of optimal weights and optimal hedging ratios. Results show evidence of hedging effectiveness for the financial innovations against oil market risks, with higher hedging performance observed during the pandemic. Overall, we show that sectoral financial innovations provide resilient investment options. Therefore, we propose that including the ETFs in an investment portfolio containing oil could improve risk-adjusted returns, especially in similar financial crisis as witnessed during the pandemic. In essence, our results are useful for investors in the global oil market seeking to maximize risk-adjusted returns when making investment decisions. Moreover, by exploring the role of structural breaks in the multivariate volatility framework, our attempts at establishing robustness for the results reveal that ignoring the same may lead to wrong conclusions about the hedging effectiveness.


2020 ◽  
Vol 36 (3) ◽  
pp. 873-891 ◽  
Author(s):  
Alessandra Amendola ◽  
Manuela Braione ◽  
Vincenzo Candila ◽  
Giuseppe Storti

2020 ◽  
Vol 39 (4) ◽  
pp. 628-641
Author(s):  
Adam Clements ◽  
Mark Bernard Doolan

2019 ◽  
Vol 11 (2) ◽  
pp. 255-283
Author(s):  
Afees A. Salisu ◽  
Kazeem O. Isah ◽  
Alberto Assandri

This study examines probable dynamic spillover transmissions between the Nigerian stock and money markets using the multivariate volatility framework that simultaneously accounts for both returns and shock spillovers. Based on relevant pre-tests, the VARMA-CCC-GARCH framework is selected and consequently employed to model the spillovers. The study finds significant cross-market return and shock spillovers between the two markets. Thus, a shock to one market is more likely to spill over to the other market. It is also observed that shocks have persistent effects on stock market volatility but transitory effects on money market volatility. In other words, shocks to the money market die out over time while shocks to stock market tend to persist over time. In addition, including lagged own shocks and lagged own conditional variance when forecasting the future volatility of both return series may enhance their forecast performance. An alternative approach proposed by Diebold and Yilmaz (2012) is also employed for robustness and the results are consistent with those obtained from the VARMA-CCC-GARCH model.


2018 ◽  
Vol 20 (1) ◽  
pp. 214-237 ◽  
Author(s):  
Debasish Maitra ◽  
Varun Dawar

This article aims to investigate return and volatility spillover among commodity, stock and exchange rate markets. The article further looks into whether there is any change in return and volatility spillover during the crisis and post-crisis periods and whether there is any in the behaviour of spillover changes between agro and non-agro based commodities. The study uses Vector Auto Regression followed along with by Granger causality are to understand the causality of returns. We have performed multivariate volatility model to study the volatility co-movement of different assets. Unidirectional return spillover from the Multi Commodity Exchange (non-agro commodity) to stock indices and exchange rates is found. Stock indices are found to influence exchange rates to return; whereas the only dollar explains the return in stock indices. Equity markets have been found to have a return spillover on NCDEX (agro commodity) during the post-crisis period. However, each asset market is found to have volatility spillover effects on the other asset market. Commodity indices have more spillover effects on stocks.


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