Asymmetric Dynamics in Stock Market Volatility

Karunanayake, Indika; Valadkhani, Abbas

doi:10.1111/j.1759-3441.2011.00101.x

Cited by 9 publications

(4 citation statements)

References 22 publications

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“…During the pandemic, a two-way GARCH effect was detected between Singapore and Thailand. Previous studies conclude that volatility transmission is unidirectional from bigger markets to smaller markets (Karunanayake and Valadkhani, 2011). The Singaporean market is larger than the Thai market and the short-term shock spillover follows this conventional path in the pre-crisis period.…”

Section: Resultsmentioning

confidence: 97%

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: Resultsmentioning

confidence: 97%

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 because the outcomes of these studies enhance the ability to forecast equity market time varying volatility for portfolio selection and asset management. Also, the analysis of information asymmetry as a result of market spillovers helps in understanding the behavior of investors (Yeh and Lee, 2000, p. 130).Recent empirical developments in the field of global stock price spillovers and contagion have led to renewed interest in intra-regional and inter-/intra-market spillovers (Weber, 2013;Karunanayake and Valadkhani, 2011).…”

Section: Introductionmentioning

confidence: 98%

“…Volatility impulse response function analysis is relied upon to assess the effect of financial crises on expected conditional volatility, with various magnitudes of impact across the markets considered Karunanayake and Valadkhani (2011). assess the asymmetric effects of stock market volatility transmission using weekly data (January 1992-June 2010) for Australia, Singapore, US and UK using a multivariate GARCH model.…”

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confidence: 99%

Dynamic spillovers between Nigerian, South African and international equity markets

Fowowe

Shuaibu

2016

International Economics

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“…Among the abundant empirical studies, Maqsood, et al (2017) determined asymmetric GARCH estimations are a better fit for the Nairobi Stock Exchange whilst Karunanayake and Valadkhani (2011) analysed the influence of United States, United Kingdom, Australian and Singapore stock markets' volatility on one another. Conducting empirical studies on developing and emerging markets, Arsalan, et al, (2022) stated that emerging markets are prone to high volatilities and slower mean reversions compared to the lower volatilities and swifter mean reversions in the developing markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Sri Lankan Stock Market Volatility Analysis: An Arma- Garch Approach

Samarawickrama I.D.W.,

Pallegedara A.

2023

SLJBE

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Beyond its role in capital generation, a stock market is emulated as a facet in economic development indication. Sri Lankan stock market, the Colombo Stock Exchange (CSE) is a languidly developing market known for instability and periodical fluctuations increasing the volatility risk for the investors. Toward market development, it is imperative in attracting and retaining long term investors. Thus, the study aimed to identify the dynamics of the CSE through volatility estimation of the Sri Lankan stock market during a high volatile period. Further, the use of ARMA-GARCH models aims to contribute to the local empirical studies on the applicability of ARMA-GARCH models in the Sri Lankan context. The study used the daily closing prices of the All-Share-Price Index (ASPI) from January 2018 to December 2022 in log return volatility. Owing to the non-normality and serial dependence conditions inherent in the data, the study developed an ARMA (2,2) mean equation and separate volatility equation applying symmetric models of GARCH, and TGARCH and asymmetric GARCH models of EGARCH, and GJR-GARCH. The study findings identified that asymmetric GARCH models are more reliable in volatility estimation and forecasting. Further, ASPI indicated a leverage effect where negative information caused idiosyncratic volatility. Keywords: ARMA-GARCH, GARCH, Leverage Effect, Stock Markets, Volatility

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Asymmetric Dynamics in Stock Market Volatility

Cited by 9 publications

References 22 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

Dynamic spillovers between Nigerian, South African and international equity markets

Sri Lankan Stock Market Volatility Analysis: An Arma- Garch Approach

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