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1- Urmia University
2- Urmia University , a.rezazadeh@urmia.ac.ir
2- Urmia University , a.rezazadeh@urmia.ac.ir
Abstract: (450 Views)
Introduction
In recent years, cryptocurrency analysis has become increasingly popular both in academic research and in the financial system as a whole. Cryptocurrencies are a globally spreading phenomenon that is frequently and also prominently addressed by media, venture capitalists, financial institutions, and governments alike (Glasser et al., 2014). Knowing the relationship of the cryptocurrency market with the stock market or the commodity market will be very useful for managing investors’ portfolios and how much of their investment money will be allocated to cryptocurrencies for their secure.
The possible interdependence of stock markets and cryptocurrencies is a crucial concern in the financial market literature due to its paramount importance for investors and portfolio managers. Although cryptocurrencies are a recent phenomenon, with the first cryptocurrency, Bitcoin, appearing in January 2016, they quickly become a worldwide phenomenon that is broadly discussed in the finance literature (Glaser et al., 2014).
Many scholars in recent times explored the correlation between cryptocurrencies and stock market. Several studies (see Conrad et al., 2018; Jiang et al., 2021; Tiwari et al., 2019; Corbet et al., 2018; Salisu et al., 2019) considered advanced economies to explore the impact of cryptocurrency and stock market, provided important insightful stories. Few others (see Lahiani and Jlassi, 2021; Dasman, 2021; Vardar and Aydogan et al., 2019; Sami and Abdallah, 2020) explored the association in emerging economies. Additionally, the association between cryptocurrency and stock market also received considerable attention among the scholars in the time of COVID-19 (see Mariana et al., 2021; Grobys, 2021; Nguyen, 2021; Kumah, 2021). The issue discussed in these studies is mainly based on the fact that cryptocurrencies are gradually establishing themselves as a new class of assets with unique characteristics, although skepticism and lack of understanding of their nature still exist. These new financial assets (tokens) can offer new opportunities for portfolio diversification and risk hedging. The common consensus regarding weak correlations between cryptocurrencies and stock markets has recently been challenged by their synchronous downturn during the COVID-19 pandemic.
Any financial instrument such as stocks and cryptocurrencies traded in the markets may be subject to price fluctuations based on several factors. Factors such as positive and negative news, financial status of stock companies traded in stock markets, political events, global changes and environmental conditions including market risks. With the globalization of the use of cryptocurrencies, the popularity and use of cryptocurrencies has been steadily increasing in Iran over the past few years. In this new situation, investors are looking to reduce their investment risk and achieve optimal portfolio diversification with the participation of new financial assets. Considering the direct and indirect influence of Iran's economy on global financial markets and the expansion of activities related to cryptocurrencies in the context of international sanctions, the question is raised whether there is a relationship between stock returns and cryptocurrencies returns? This study combines the variational mode decomposition (VMD) method and symmetric and asymmetric copula functions to examine the dependence structure between cryptocurrency and stock markets under different investment horizons.
Methodology
The fundamental aim of this study is to investigate the structural dependence between the cryptocurrency market and the Iran Stock Market Index using daily data (common trading days) during the period from 8 August 2015 to 21 February 2023. This study combines the variational mode decomposition (VMD) method and various symmetric and asymmetric copula functions to examine the short-term and long-term dependence structure between the cryptocurrency markets and the Iran stock markets under different investment horizons. In this study have been used the Normal copula, the student-t copula and the Archimedean copula family functions such as the Frank copula, the Gumbel copula and the Clayton copula. Also, the dependence structure Between the markets is investigated with one subroutines of the Vine Copula functions, namely C-Vine.
Discussion and Results
The results show that there is no structural dependence between the return Bitcoin and Iran stock market using the Archimedean copula function, either in the short term or in the long term. In other words, the changes domain in return of Bitcoin during the low and high ranges on the return of the mentioned index are insignificant. The results indicated that the studied cryptocurrencies are strongly correlated. However, the associations between cryptocurrencies and conventional financial assets are negligible. These results are consistent with the findings of Gil-Alana et al. (2020); Tiwari et al. (2019) and Corbet et al. (2018) show that there is no correlation between the cryptocurrency and stock markets.
Conclusion
The results indicates that the cryptocurrency market is separated from the main class of financial and economic assets and hence offers various benefits to investors. Structural dependence using Vine copula functions is better than Archimedean copula in identifying the structural dependence between cryptocurrency and The Iran Stock Market Index during the period under study. Based on the research findings, the Clayton Copula has been chosen as the suitable model to explain the correlation between the return of Bitcoin and the stock market index on the condition of the growth price Ethereum. This point indicates asymmetric effects the dependence on the negative tail is more than the positive one. The findings in this paper indicate the significant role of cryptocurrencies in investor portfolios since they serve as a diversification option for investors, confirming that cryptocurrency is a new investment asset class
In recent years, cryptocurrency analysis has become increasingly popular both in academic research and in the financial system as a whole. Cryptocurrencies are a globally spreading phenomenon that is frequently and also prominently addressed by media, venture capitalists, financial institutions, and governments alike (Glasser et al., 2014). Knowing the relationship of the cryptocurrency market with the stock market or the commodity market will be very useful for managing investors’ portfolios and how much of their investment money will be allocated to cryptocurrencies for their secure.
The possible interdependence of stock markets and cryptocurrencies is a crucial concern in the financial market literature due to its paramount importance for investors and portfolio managers. Although cryptocurrencies are a recent phenomenon, with the first cryptocurrency, Bitcoin, appearing in January 2016, they quickly become a worldwide phenomenon that is broadly discussed in the finance literature (Glaser et al., 2014).
Many scholars in recent times explored the correlation between cryptocurrencies and stock market. Several studies (see Conrad et al., 2018; Jiang et al., 2021; Tiwari et al., 2019; Corbet et al., 2018; Salisu et al., 2019) considered advanced economies to explore the impact of cryptocurrency and stock market, provided important insightful stories. Few others (see Lahiani and Jlassi, 2021; Dasman, 2021; Vardar and Aydogan et al., 2019; Sami and Abdallah, 2020) explored the association in emerging economies. Additionally, the association between cryptocurrency and stock market also received considerable attention among the scholars in the time of COVID-19 (see Mariana et al., 2021; Grobys, 2021; Nguyen, 2021; Kumah, 2021). The issue discussed in these studies is mainly based on the fact that cryptocurrencies are gradually establishing themselves as a new class of assets with unique characteristics, although skepticism and lack of understanding of their nature still exist. These new financial assets (tokens) can offer new opportunities for portfolio diversification and risk hedging. The common consensus regarding weak correlations between cryptocurrencies and stock markets has recently been challenged by their synchronous downturn during the COVID-19 pandemic.
Any financial instrument such as stocks and cryptocurrencies traded in the markets may be subject to price fluctuations based on several factors. Factors such as positive and negative news, financial status of stock companies traded in stock markets, political events, global changes and environmental conditions including market risks. With the globalization of the use of cryptocurrencies, the popularity and use of cryptocurrencies has been steadily increasing in Iran over the past few years. In this new situation, investors are looking to reduce their investment risk and achieve optimal portfolio diversification with the participation of new financial assets. Considering the direct and indirect influence of Iran's economy on global financial markets and the expansion of activities related to cryptocurrencies in the context of international sanctions, the question is raised whether there is a relationship between stock returns and cryptocurrencies returns? This study combines the variational mode decomposition (VMD) method and symmetric and asymmetric copula functions to examine the dependence structure between cryptocurrency and stock markets under different investment horizons.
Methodology
The fundamental aim of this study is to investigate the structural dependence between the cryptocurrency market and the Iran Stock Market Index using daily data (common trading days) during the period from 8 August 2015 to 21 February 2023. This study combines the variational mode decomposition (VMD) method and various symmetric and asymmetric copula functions to examine the short-term and long-term dependence structure between the cryptocurrency markets and the Iran stock markets under different investment horizons. In this study have been used the Normal copula, the student-t copula and the Archimedean copula family functions such as the Frank copula, the Gumbel copula and the Clayton copula. Also, the dependence structure Between the markets is investigated with one subroutines of the Vine Copula functions, namely C-Vine.
Discussion and Results
The results show that there is no structural dependence between the return Bitcoin and Iran stock market using the Archimedean copula function, either in the short term or in the long term. In other words, the changes domain in return of Bitcoin during the low and high ranges on the return of the mentioned index are insignificant. The results indicated that the studied cryptocurrencies are strongly correlated. However, the associations between cryptocurrencies and conventional financial assets are negligible. These results are consistent with the findings of Gil-Alana et al. (2020); Tiwari et al. (2019) and Corbet et al. (2018) show that there is no correlation between the cryptocurrency and stock markets.
Conclusion
The results indicates that the cryptocurrency market is separated from the main class of financial and economic assets and hence offers various benefits to investors. Structural dependence using Vine copula functions is better than Archimedean copula in identifying the structural dependence between cryptocurrency and The Iran Stock Market Index during the period under study. Based on the research findings, the Clayton Copula has been chosen as the suitable model to explain the correlation between the return of Bitcoin and the stock market index on the condition of the growth price Ethereum. This point indicates asymmetric effects the dependence on the negative tail is more than the positive one. The findings in this paper indicate the significant role of cryptocurrencies in investor portfolios since they serve as a diversification option for investors, confirming that cryptocurrency is a new investment asset class
Keywords: Cryptocurrencies, Variational mode Decomposition, Copula function Stock market Index, Dependence Structure
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