Hedge effectiveness of put replication, gold, and oil on ASEAN-5 equities

Robiyanto, Robiyanto; Nugroho, Bayu Adi; Handriani, Eka; Huruta, Andrian Dolfriandra

doi:10.1186/s40854-020-00199-w

Cited by 13 publications

(7 citation statements)

References 56 publications

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“…However, the unique characteristic is country-specific and questionable in emerging markets (Baur and McDermott, 2010;Beckmann et al, 2015). Robiyanto et al (2020) argue that the ineffectiveness of gold as a hedging instrument in the region is due to its positive correlation with regional equity markets and suggest put replication as a better strategy. Wen and Cheng (2018) argue that the US dollar is a better safe haven than gold in the emerging market.…”

Section: Gold For Risk-averse Investorsmentioning

confidence: 99%

Nexus between Southeast Asian stock markets, bitcoin and gold: spillover effect before and during the COVID-19 pandemic

Kakinuma

2021

JABS

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Purpose This study aims to provide empirical evidence on the return and volatility spillover effects between Southeast Asian stock markets, bitcoin and gold in the periods before and during the COVID-19 pandemic. The interdependence among different asset classes, the two leading stock markets in Southeast Asia (Singapore and Thailand), bitcoin and gold, is analyzed for diversification opportunities. Design/methodology/approach The vector autoregressive-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity model is used to capture the return and volatility spillover effects between different financial assets. The data cover the period from October 2013 to May 2021. The full period is divided into two sub-sample periods, the pre-pandemic period and the during-pandemic period, to examine whether the financial turbulence caused by COVID-19 affects the interconnectedness between the assets. Findings The stocks in Southeast Asia, bitcoin and gold become more interdependent during the pandemic. During turbulent times, the contagion effect is inevitable regardless of region and asset class. Furthermore, bitcoin does not provide protection for investors in Southeast Asia. The pricing mechanism and technology behind bitcoin are different from common stocks, yet the results indicate the co-movement of bitcoin and the Singaporean and Thai stocks during the crisis. Finally, risk-averse investors should ensure that gold constitutes a significant proportion of their portfolio, approximately 40%–55%. This strategy provides the most effective hedge against risk. Originality/value The mean return and volatility spillover is analyzed between bitcoin, gold and two preeminent stock markets in Southeast Asia. Most prior studies test the spillover effect between the same asset classes such as equities in different regions or different commodities, currencies and cryptocurrencies. Moreover, the time-series data are divided into two groups based on the structural break caused by the COVID-19 pandemic. The findings of this study offer practical implications for risk management and portfolio diversification. Diversification opportunities are becoming scarce as different financial assets witness increasing integration.

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Section: Gold For Risk-averse Investorsmentioning

confidence: 99%

Nexus between Southeast Asian stock markets, bitcoin and gold: spillover effect before and during the COVID-19 pandemic

Kakinuma

2021

JABS

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“…This is due to the assumption that gold prices will continue to increase in the future (Hoang and Syed, 2021). Investor awareness of market risk in equity causes gold to be the best choice for hedging their investment portfolios (Robiyanto et al, 2020). In the study of Jareno et al (2020), the return of gold prices has a significant influence on Bitcoin in the short and long terms.…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

The effect of hashrate, transaction volume, social media and macroeconomics on Bitcoin before and during the COVID-19 pandemic

Sun

Amanda

Centana

2023

AJAR

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PurposeThis research aims to determine the factors that affected Bitcoin price return in the period before and during the COVID-19 pandemic.Design/methodology/approachThe independent variables used in this study are hashrate, transaction volume, social media and some macroeconomics variables. The data are processed using the vector error correction model (VECM) to determine the short-term and long-term relationships between variables.FindingsThe research shows that (1) Twitter and Gold significantly affected Bitcoin in the short term before the COVID-19 pandemic; (2) hashrate, transaction volume, Twitter and the financial stress index had a significant effect on Bitcoin in the long term before the COVID-19 pandemic; (3) the volatility index had a significant effect on Bitcoin in the short term during the COVID-19 pandemic; and (4) hashrate, transaction volume, Twitter and CHF/USD had a significant effect on Bitcoin in the long term during the COVID-19 pandemic.Research limitations/implicationsThis research provides explanation about factors affecting Bitcoin so investors and regulators can pay more attention and prepare for the potential risks as well as to get a good understanding of market conditions for greater crypto adoption in the future.Originality/valueThe novelty in this study is the various factors driving the Bitcoin price were analyzed before and during the COVID-19 pandemic including the social media, as sentiment, interestingly, is being a predictive power for Bitcoin price return.

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“…Scholars continue to use foreign scholars' methods in static model research, but the majority of them use the OLS calculation method. To test OLS and create a revised model, Robiyanto et al [20] used the CSI 300 simulation contract [21]. Canyakmaz et al [22] conducted an empirical study of China's copper futures market hedging performance.…”

Section: Related Workmentioning

confidence: 99%

A Minimum Variance Hedging Ratio Model Based on Nonlinear Grey Classification Model

Xia¹,

Zhao²

2022

Wireless Communications and Mobile Computing

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The risk transfer function of futures market is mainly realized by hedging strategy. Futures price yield and spot price yield tend to show different fluctuations before and during hedging, which leads to the distortion of hedging ratio, that is, the calculated hedging effect is weaker than the traditional hedging effect. On the basis of MV (minimum variance) hedging model, this paper introduces NGCM (nonlinear grey classification model) to solve the nonlinear correlation between futures and spot returns, which can improve the hedging effect. The results show that, due to the existence of basis, the price change model violates the linear assumption of OLS (ordinary least squares) parameters, and there is a problem of model missetting. It is estimated that HR (hedging ratio) should choose the price model, which can better depict the linkage between futures price and spot price. The effectiveness of HR in this study is higher than that of existing models. Applying this model to hedge can effectively avoid the spot price risk. Investors can reasonably choose the hedging model according to their own needs.

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Hedge effectiveness of put replication, gold, and oil on ASEAN-5 equities

Cited by 13 publications

References 56 publications

Nexus between Southeast Asian stock markets, bitcoin and gold: spillover effect before and during the COVID-19 pandemic

Nexus between Southeast Asian stock markets, bitcoin and gold: spillover effect before and during the COVID-19 pandemic

The effect of hashrate, transaction volume, social media and macroeconomics on Bitcoin before and during the COVID-19 pandemic

A Minimum Variance Hedging Ratio Model Based on Nonlinear Grey Classification Model

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