Time varying correlations and causalities between stock and foreign exchange markets: Evidence from China, Japan and Korea

Park, Young K.; Binh, Ki Beom; Kim, Suk-Joong

doi:10.1080/10293523.2019.1670385

Cited by 7 publications

(3 citation statements)

References 28 publications

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“…Although crypto-currency has been gained great attention in financial markets, little attention has ever been paid in individual investors' perspectives. Furthermore, current researches on the crypto-currencies mostly focus on the expected return, volatility and risk, ignoring the behavior perspectives in crypto-currencies among individual investors [1].…”

Section: Introductionmentioning

confidence: 99%

Switching intention to crypto-currency market: Factors predisposing some individuals to risky investment

et al. 2020

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We investigate factors affecting individual investors' switching intention from traditional financial market to crypto-currency financial market. By sampling factors of individual investors related with crypto-currency (CC), the study applies structural equation modeling method (SEM) to investigate their effects on switching intention by integrating PPM and Reinforcement Sensitivity theories (RST) to form a pulling, pushing and mooring effects model. The investigation indicates that crypto-currency market can be regarded as a kind of beneficial supplement of tradition investment market for those individual investors who are with high innovativeness, reward sensitivity, knowledge and perceived risk. This study proves that the individual investors are not only attracted by significant expected return from crypto-currency but also relevant knowledge and risks disclosed by crypto-currency market regulators and distributors. The findings reinforce major roles for both market regulators and individual investors in considering and providing insights for future policy, management and investigations.

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Section: Introductionmentioning

confidence: 99%

Switching intention to crypto-currency market: Factors predisposing some individuals to risky investment

et al. 2020

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“…3 Oktober 2022P-ISSN: 2622-2191E-ISSN : 2622-2205 1458 Dari hasil olah data yang dilakukan pada penelitian ini dapat diketahui pula bahwa masingmasing variabel memiliki perannya tersendiri jika dikaitkan dengan dasar teori yang diangkat dalam penelitian ini yakni PPM Theory (Push-Pull-Mooring Theory) (Chang et al, 2014). Penelitian sebelumnya tentang pasar fisik aset kripto sebagian besar hanya berfokus pada tingkat pengembalian yang diharapkan, tolatilitas, serta risiko yang dihadapi, dengan minim sekali membahas tentang perilaku investor individu khususnya kaum milenial dalam mengalihkan niat mereka untuk berinvestasi di pasar fisik aset kripto tersebut (Park et al, 2019). Oleh karena itu tujuan utama dalam penelitian ini adalah mengeksplorasi faktor predisposisi yang membuat para investor individu bisa mengalihkan niatnya untuk berinvestasi di pasar fisik aset kripto.…”

Section: Pendahuluanunclassified

Mengalihkan perhatian kepada pasar fisik aset kripto (crypto asset) - faktor predisposisi insvestor milenial kepada investasi beresiko

Akshay

Bertuah

2022

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The purpose of this research is to find out the factors that influence millennial investors in shifting their intentions to the physical market of crypto assets which is growing rapidly in recent times. The method used in this research is a deductive approach to test a hypothesis. Perceived Risk, Reward Sensitivity , Knowledge become independent variables which then affect the Switching Intention.variable Personal Innovativeness is also presented as a moderating variable. The results of this study indicate that the Perceived Risk and Reward Sensitivity have an effect on Switching Intention in the Physical Crypto Asset Market so that the higher the risk perception felt by millennial investors in the financial asset market other than the crypto asset market and the higher the Reward Sensitivity they know when they decide. to invest in the physical market of crypto assets will increasingly affect their intention to participate in investing in the physical market of crypto assets. In addition, the study found a new finding that the effect of Reward Sensitivity on Switching Intention can be weakened by the moderating variable, namely Personal Innovativeness. This research has contributed to providing new Knowledge about the factors that can influence individual investors in the millennial age in Indonesia on their intention to divert their attention to investing in the physical market of crypto assets.

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“…The literature on risk measurement outlines a set of models to estimate the conditional second moments of asset value. For the conditional variance, Engle's (1982) autoregressive conditional heteroskedasticity (ARCH) model and Bollweslev's (1986) generalised ARCH (GARCH) model are the most commonly-used methods (see Thupayagale, 2010;Jung, 2016) while the dynamic conditional correlation (DCC) model, proposed by Engle (2002), is the most popular (see Park et al, 2019) for the conditional correlation. It should be noted that Engle's (2002) DCC model uses a pure and simple time-varying process: it employs the correlations in the past to estimate the future correlations, and thus is unable to identify the common factors which drive the dynamics of conditional correlations.…”

Section: Introductionmentioning

confidence: 99%

Risk of investing in volatility products: A regime-switching approach

2020

Investment Analysts Journal

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Volatility indexes provide a tool for investors to speculate and trade on market sentiment regarding future volatility. The risk of trading on volatility indexes can be measured by their second moments, namely, variance and correlation. This study considers the four representative volatility indexes published by the CBOE: stock market volatility index (VIX), crude oil volatility index (OVX), foreign exchange rate volatility index (EVZ), and gold price volatility index (GVZ). To examine their risk, we develop an extended multivariate Markov switching ARCH (MSARCH) model in which regime-switching variances, correlations, and variancecorrelation relations are designed. Our empirical sample consists of the four volatility indexes from June 2008 to April 2020 for 612 weekly observations (Wednesday to Wednesday). For the conditional variances, we find evidence of regime-switching processes (switching between low and high volatility regimes) for the individual volatility index returns, with the exception of the GVZ. The estimated probability of the high volatility regime may be used to track economic distress and uncertainty shocks. These results provide evidence for volatility-of-volatility risk. For the conditional correlations, we find a regime-switching relation between variances and correlations. That is, the highest correlation appears when the paired volatility markets are simultaneously experiencing a state of high volatility. By contrast, when the paired volatility markets are encountering different volatility states, the correlation is weaker. These results indicate that the volatility-of-volatility risk is a factor affecting the dynamics of correlations between volatility indexes.

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Time varying correlations and causalities between stock and foreign exchange markets: Evidence from China, Japan and Korea

Cited by 7 publications

References 28 publications

Switching intention to crypto-currency market: Factors predisposing some individuals to risky investment

Switching intention to crypto-currency market: Factors predisposing some individuals to risky investment

Mengalihkan perhatian kepada pasar fisik aset kripto (crypto asset) - faktor predisposisi insvestor milenial kepada investasi beresiko

Risk of investing in volatility products: A regime-switching approach

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