Research On The Cryptocurrency Price Formation And Spillover Effect

In the context of the COVID-19 pandemic and the complicated ever-changing international environment,cryptocurrency has attracted widespread attention as an emerging financial tool.However,due to the lack of government credit endorsement,dissociation from the financial supervision system,and accompanied by excessive speculation,the price of cryptocurrency fluctuates violently.Meanwhile,the correlation between cryptocurrencies is strong since they are all exposed to the same market innovations and macroeconomic shocks.Therefore,the cryptocurrency market contains extremely high levels of risk.With the cryptocurrency market expanding rapidly,the correlation of crypto assets with traditional holdings like stocks has increased significantly.The high risks in the cryptocurrency market may spill over to traditional financial markets,affecting the stability of the financial system.In this context,it is particularly important to study the price formation of cryptocurrency,the correlation between cryptocurrencies,and the correlation between the cryptocurrency market and the traditional financial market.This helps to reveal the mechanism behind the drastic changes in cryptocurrency prices,the laws of internal information transmission,and to understand its impact on the traditional financial market,to provide a reference for market regulators and participants to capture market information,optimize asset allocation,formulate regulatory policies,and prevent financial risks.This paper studies the cryptocurrency from the following aspects: on the one hand,this paper combines theoretical analysis with empirical evidence to explore the cryptocurrency price formation;on the other hand,from the perspective of spillover effects,this paper investigates the information transmission between the most important cryptocurrencies,as well as the risk transmission between the cryptocurrency market and other traditional financial markets in China.This paper also considers the determinants of spillovers.From the perspective of the cryptocurrency price formation.This paper extends the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)to cryptocurrency price analysis,which is a direct,empirical,intuitive,and self-adaptive data processing method specially developed for nonlinear and non-stationary data.Taking Bitcoin as an example,with the CEEMDAN approach,the original Bitcoin price series is decomposed into high-frequency,low-frequency,and trend components.The economic implications of these components are characterized by the short-term fluctuation caused by normal supply and demand imbalance or other market activities,the influence of significant events,and a long-term trend.Combining theoretical and empirical analysis,it is found that the price formation of Bitcoin can be explained as follows: in the long term,bitcoin price depends on the marginal cost of production and the network effect,which is the dominant factor;In the medium term,Bitcoin price would fluctuate dramatically due to major events,but it would return to the trend after the influence of the event is over.In the short term,the price of Bitcoin moves randomly,and there is no significant correlation with the long-term trend,implying it is not the dominant factor.From the perspective of the information transmission between the most important cryptocurrencies.This paper applies the TVP-VAR-DY model to examine connectedness via return and volatility spillovers across cryptocurrencies.The results show that there is a significant bidirectional return and volatility spillover relationship between cryptocurrencies,implying a high degree of association among cryptocurrencies.Further analysis shows that connectedness via negative returns is largely stronger than via positive ones.Furthermore,combined with the analysis of the spillover networks,it is found that the connectedness between cryptocurrencies is significantly affected by their categories.The decentralized application(Dapp)cryptocurrencies are the recipients of return and volatility shocks,while the payment cryptocurrencies and smart contract cryptocurrencies are the transmitters of spillover.Finally,this paper finds that the total spillover degree among the cryptocurrencies is significantly influenced by major events,investor attention,trading volume,global financial environment,uncertainty,and major commodity markets.From the perspective of the risk transmission between the cryptocurrency market and other traditional financial markets in China.This paper applies the TVP-VAR-DY model to measure risk spillovers between the cryptocurrency market and other traditional financial markets in China,including the currency market,stock market,commodity market,foreign exchange market,and gold market.The empirical study reveals that there is a two-way volatility spillover effect between the cryptocurrency market and the financial markets,and the spillover from the cryptocurrency market is stronger to the currency market,foreign exchange market,and gold market than other markets.Furthermore,with the analysis of the volatility spillover networks,it is found that the "cryptocurrency ban" issued by China in 2017 has weakened the degree of volatility spillover from the cryptocurrency market to the Chinese financial markets.Finally,this paper finds that the volatility spillover from the cryptocurrency market to the Chinese financial markets is time-varying and significantly influenced by major events,like cryptocurrency market volatility,uncertainties in the Chinese economic and financial environment,and regulatory policies.The innovations and contributions of this paper are as follows.From the research perspective: first,the existing research mainly focuses on the time domain,ignoring the frequency domain.In this paper,both time-and frequency-domain features are extracted to investigate the cryptocurrency price formation;Second,the existing research treats all cryptocurrencies as homogeneous assets.This paper classifies each cryptocurrency into different categories,and examines whether the connectedness between cryptocurrencies is significantly affected by their categories;Third,the existing research mainly focuses on the financial markets of developed countries in Europe and the United States,and focuses on static perspectives.This paper measures risk spillover effects between cryptocurrencies and China’s financial market from both static and dynamic perspectives.From the perspective of research methods: first,this paper combines the CEEMDAN model with traditional econometric models to analyze the cryptocurrency price formation from both time-and frequency-domain;Second,based on the TVP-VAR-DY model to quantify the static and dynamic spillover effects,this paper constructs the spillover networks,and combines the OLS model to investigate the determinants of spillovers,which is helpful to explain the spillover phenomenon more comprehensively.