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2,964 results · page 104 of 124
Gerrit Köchling, Philipp Schmidtke, Peter N. Posch
No abstract is available for this record.
Nidhi Malhotra, Saumya Gupta
Although, the growth in the cryptocurrency market slowed down after the meteoric rise in late 2017, the market is still enjoying steady capital inflow. This has made the study of market dynamics between the cryptocurrencies and equity market indispensable. In this paper, the study of the volatility spillovers and correlation between the two has been undertaken by considering five Asian stock indices and four cryptocurrencies ranging from November 2014 to December 2018, to cover three phenomena- Leverage effect, Volatility spillovers and Time varying correlation using EGARCH, Diagonal BEKK and DCC tests respectively. Firstly, the EGARCH test reveals the absence of leverage effect in the returns of cryptocurrenices. Secondly, the multivariate GARCH test shows, out of all the cryptocurrencies taken, the past innovations in Bitcoin affect the future volatility of the equity market returns the most. Lastly, the DCC model reveals evidence of time varying correlation between the markets and Bitcoin. Keywords: Cryptocurrencies; Asian equity market; Volatility spillovers; Dynamic conditional correlation JEL Classifications: G12, G14, G17, C15, C32 DOI: https://doi.org/10.32479/ijefi.8624
Paolo Giudici, Paolo Pagnottoni
The study of connectedness is key to assess spillover effects and identify lead-lag relationships among market exchanges trading the same asset. By means of an extension of Diebold and Yilmaz (2012) econometric connectedness measures, we examined the relationships of five major Bitcoin exchange platforms during two periods of main interest: the 2017 surge in prices and the 2018 decline. We concluded that Bitfinex and Gemini are leading exchanges in terms of return spillover transmission during the analyzed time-frame, while Bittrexs act as a follower. We also found that connectedness of overall returns fell substantially right before the Bitcoin price hype, whereas it leveled out during the period the down market period. We confirmed that the results are robust with regards to the modeling strategies.
Md Akhtaruzzaman, Ahmet Şensoy, Shaen Corbet
No abstract is available for this record.
Carl Luft, Jin Man Lee, Jin Wook Choi
This paper explores empirically the behavior of the Chicago Mercantile Exchange (CME) bitcoin futures contract. The analysis focuses on the time period between the launch of the CME bitcoin futures contract on December 18, 2017, and September 17, 2018. The behavior of the bitcoin spot market and CME futures market is compared and analyzed along several dimensions: price, volatility and liquidity. By comparing the Garman-Klass volatilities of bitcoin spot and futures prices with those of different assets, we find that both the bitcoin spot and futures markets exhibit relatively high volatility compared to other assets. When the ratio of trading volume over open interest is used to measure liquidity, the bitcoin futures market shows a mid-level liquidity. We also find while the exchange margin is set to meet the normal price volatility that can cover the daily price movements within one standard deviation, the brokerage margin for bitcoin futures is set at beyond two standard deviations. Some brokerage firms impose non-margin requirements such as high net account balance and open position limits in addition to regular margins. We conclude that the brokerage firms' relatively high margin and non-margin requirements impede trading activity such as short-sales and thus, liquidity and efficiency in the bitcoin futures market has been slow to develop.
Leandro Maciel, Rosângela Ballini
Bitcoin has attracted the attention of investors lately due to its significant market capitalization and high volatility. This work considers the modeling and forecasting of daily high and low Bitcoin prices using a fractionally cointegrated vector autoregressive (FCVAR) model. As a flexible framework, FCVAR is able to account for two fundamental patterns of high and low financial prices: their cointegrating relationship and the long memory of their difference (i.e., the range), which is a measure of realized volatility. The analysis comprises the period from January 2012 to February 2018. Empirical findings indicate a significant cointegration relationship between daily high and low Bitcoin prices, which are integrated on an order close to the unity, and the evidence of long memory for the range. Results also indicate that high and low Bitcoin prices are predictable, and the fractionally cointegrated approach appears as a potential forecasting tool forcryptocurrencies market practitioners.
Hao Dong, Liming Chen, Xinyi Zhang, Pierre Failler · 5 authors
In this paper, we measure the asymmetric volatility spillover among six virtual financial asset (VFA) markets from January 1, 2014, to September 30, 2017, using the volatility spillover index based on a Markov regime-switching vector autoregressive (VAR) model and conduct a static and dynamic analysis under different regimes. The static results show that asymmetric effects of total, internal and net volatility spillover, on average, exist in all six VFA markets under different regimes. The dynamic results show that total, directional, and net spillover have significantly asymmetric effects. Thus, the government should monitor the specific VFA regimes and improve market regulation.
Hayet Ben Haj Hamida, Francesco Scalera
In this paper we explores as to whether cryptocurrency returns exhibit asymmetric reverting patterns and we test the presence of regime changes in the GARCH volatility dynamics of Bitcoin log-returns. For these reason, we uses non-linear autoregressive and Markov-switching GARCH (SETAR-MSGARCH) models. We finds strong evidence of regime changes in the mean and GARCH process. In addition, we conclude that bad news and good news of the same size have same impacts for investors.
Anwar Hasan Abdullah Othman, Adam Abdullah, Razali Haron
As crypto-currencies hold dual nature of a medium of exchange (currency) and an investment asset, some questions may arise about the potentiality of including crypto-currencies as liquid investment asset in financial institutions particularly in the banking sector to enhance their liquidity risk management and improve their portfolio diversification investment strategy. The objective of this study therefore is to examine the characteristics of Bitcoin currency based on the requirements of High-Quality Liquid Assets (HQLA) standards of Basel III and compare its volatility structure with other traditional asset classes that are already recommended by Basle III as HQLA. The study utilizes both descriptive and quantitative analysis using the GARCH family models to examine the volatility structures of these assets. The findings show that Bitcoin currency holds the same characteristics of HQLA, however; the risk of legality and recognition is still under consideration by legal authorities around the world and this risk will be eradicated in the future as crypto-currencies derive their legality from their real intrinsic value, multi-economic usefulness and not by law as in the case of fiat money currency. Furthermore, the symmetric volatility structure analysis shows the continuing persistence of volatility and predictability behavior in return series of Bitcoin currency and other- traditional asset classes in the U.S. market. However, Bitcoin’s stability has gradually improved over time. With regard to the asymmetric informative response, Bitcoin returns respond more to negative shock but it has no statistical significance, thus suggesting the lack of leveraging effect in Bitcoin market but this effect was found to be statistically persistent in other traditional asset class markets. In addition, Bitcoin returns show very low correlation with other traditional asset classes. All these imply that Bitcoin is a potential candidate as a hedge and asset diversifier, which is recommended to be included in the HQLA. This study provides some support to recent theoretical work on crypto asset return behaviour and liquidity risk management. The findings provide appropriate information about Bitcoin asset behaviour compared to other traditional asset classes which will enable them to make the right investment decision with regard to hedging, diversification and liquidity risk management. The findings of this study may assist in evaluating the suitability of including crypto assets into HQLA to improve the liquidity requirement standards and ensure that banks have an adequate amount of HQLA specifically during times of financial turmoil.
Xiao Fan Liu, Zeng-Xian Lin, Xiao-Pu Han
Thousands of cryptocurrencies have been issued and publicly exchanged since Bitcoin was invented in 2008. The total cryptocurrency market value exceeds 300 billion US dollars as of 2019. This paper analyzes the prices, volumes, blockchain transactions, coin difficulties and public opinion popularities of 3607 actively exchanged cryptocurrencies. We aim to reveal and explain the homogeneity, i.e., the strong correlation of market performance, and the heterogeneity, i.e., the imbalance of popularities and sophistications, of the cryptocurrencies.
Mária Bohdalová, Michal Greguš
Nowadays Bitcoin as cryptocurrency takes a significant place on the global financial markets. This paper analyzes the Bitcoin closing prices and traded volume during the period from December 28, 2013 to January 22, 2019. This period is known as a period with rapid increasing of the Bitcoin closing prices, mainly in the second half of the year 2017. The aim of this paper is twofold. First, we compute the Hurst coefficient to discover the close price dynamics and traded volume using a fractal point of view. We have discovered an anti-persistent behavior in the traded volume and random character of bitcoin closing prices. Second, we propose an analysis of the relationship between the close prices and traded volume. Our findings show how changes in the high-price period differ from changes in the low-price period. We also found that high prices caused investors to be afraid to trade due to possible rapid decrease in bitcoin closing prices.
Paraskevi Katsiampa, Κωνσταντίνος Μουτσιάνας, Andrew Urquhart
No abstract is available for this record.
Daniel Cerecedo Hernández, Carlos Armando Franco Ruiz, Mario Iván Contreras-Valdez, Jovan Axel Franco Ruiz
El objetivo de esta investigación es analizar la presencia de burbujas financieras o un comportamiento explosivo en cuatro criptomonedas: Ethereum, Ripple, Bitcoin Cash y EOS. La selección de los activos se basó en la capitalización de mercado. La metodología implementada fue una prueba simple y generalizada (SADF y GSADF) de una variación de la prueba aumentada de Dickey-Fuller propuesta por Phillips et al. (2011, 2015). Encontramos diez, siete, seis y siete comportamientos exuberantes en los activos mencionados, respectivamente. Esta metodología ha sido en gran parte inexplorada y podría emplearse de manera estándar en el sector financiero para cualquier otro activo. Esta es la primera investigación que detecta este tipo de comportamiento para un grupo de criptomonedas con frecuencia diaria. Con el presente trabajo y el artículo de Li et al. (2018), el 68,47% del mercado ha sido analizado bajo la metodología. En consecuencia, este comportamiento podría estar disperso en todo el sector.
Carol Alexander, Jaehyuk Choi, Heungju Park, Sungbin Sohn
Abstract BitMEX is the largest unregulated bitcoin derivatives exchange, listing contracts suitable for leverage trading and hedging. Using minute‐by‐minute data, we examine its price discovery and hedging effectiveness. We find that BitMEX derivatives lead prices on major bitcoin spot exchanges. Bid–ask spreads, interexchange spreads, and relative trading volumes are important determinants of price discovery. Further analysis shows that BitMEX derivatives have positive net spillover effects, are informationally more efficient than bitcoin spot prices, and serve as effective hedges against spot price volatility. Our evidence suggests that regulators prioritize the investigation of the legitimacy of BitMEX and its contracts.
Iqbal Thonse Hawaldar, T M Rajesha, Lolita Jane Dsouza
This study examines the weak form of efficiency of the exchange rate of cryptocurrencies against US Dollar. The study is based on the exchange rate of Bitcoin and Litecoin against US Dollar from 2013 to 2017. The data is tested for heteroscedasticity, and the efficiency of these coin market is analysed using unit root and stationary tests such as Augmented Dickey Fuller (ADF) test, Philips Perron (PP) test and Kwiatkowski Phillips Schmidt Shin (KPSS) tests. The results of the study reveal that the Bitcoin and Litecoin exchange rate exhibit a random walk. Speculation helps for the rapid growth of these currency markets. It is advisable for the investors to invest for short term to get higher returns rather than for the long term. Investment in cryptocurrencies involves market shocks due to its unpredictable nature.
Tian Xie
In this paper, we study forecasting problems of Bitcoin-realized volatility computed on data from the largest crypto exchange—Binance. Given the unique features of the crypto asset market, we find that conventional regression models exhibit strong model specification uncertainty. To circumvent this issue, we suggest using least squares model-averaging methods to model and forecast Bitcoin volatility. The empirical results demonstrate that least squares model-averaging methods in general outperform many other conventional regression models that ignore specification uncertainty.
Sheela Sathyanarayana, Sudhindra Gargesa
A digital currency in which encryption techniques are used to regulate the generation of units of currency and verify the transfer of funds, operating independently of a central bank. Therefore, Bitcoin is a form of digital currency that was designed by Satoshi Nakamoto (an unknown author of Bitcoin white paper 2008) and since then it has able to generate a considerable attention from investors due to its decentralized characteristics and the technology (block-chain) behind it. Bitcoin is a form of digital peer-to-peer currency system where transactions take place without a central bank. The transactions are verified by the nodes of the network and recorded in the Blockchain. Since the popularization of Bitcoin, this technology has caught attention of several technology companies who started to do research on the applications and opportunities of this technology. In this paper, an attempt has been made to capture the time varying variance of most prominent Cryptocurrency Bitcoin with world’s top traded currencies such as USD, GBP, Euro, Yen and CHF. In order to realise the stated objectives the researchers have collected the data from Prowess and Yahoo finance database from September 2013 till March 2018. In the first phase the collected data has been for normality and stationarity. Bitcoin was modelled for GARCH and EGARCH tests to capture the time varying volatility and leverage effect. Later the Johansen cointegration test has been conducted to find out the existence of cointegration between the top global currencies with Bitcoin. In the last phase the VECM has been run to capture the both long run and short relationship between Bitcoin and top five traded currencies. In the last phase Variance Decomposition has been run to capture the variance explained by the prominent global currencies on Bitcoin. Both USD and GBP share long run relationship with Bitcoin. Finally, the results have been compared with the possible evidence.
Nidhaleddine Ben Cheikh, Younes Ben Zaied, Julien Chevallier
No abstract is available for this record.
Ana Pavković, Mihovil Anđelinović, Ivan Pavković
Abstract Background: Cryptocurrencies represent a specific technological innovation in financial markets that keeps getting more and more popular among investors around the world. Given the specific characteristics of the cryptocurrencies, this paper examines the possibility of their use as a diversification instrument. Objectives: This paper examines the direction and strength of the relationship between the selected cryptocurrencies and important financial indicators on the European Union market. Since cryptocurrencies are a novelty in the financial system, the empirical literature in this area is rather scarce. Methods/Approach: In order to assess diversification properties of cryptocurrencies for European traders, a comprehensive econometric analysis was carried out. The first part of the analysis refers to the estimation of the multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, whereas the second part focuses on wavelet transforms. Results: Bitcoin and Ripple proved as a possible diversification instrument on most of the observed European markets since corresponding coefficients of unconditional correlation are negative. Conclusions: The relationship between the value of the cryptocurrencies and selected indices is generally very weak and slightly negative, indicating that some cryptocurrencies can serve as a means of diversification. However, investors need to take into account the extreme volatility, exhibited in all existing cryptocurrencies.
Gang‐Jin Wang, Yanping Tang, Chi Xie, Shou Chen
Based on daily data about Bitcoin and six other major financial assets (stocks, commodity futures (commodities), gold, foreign exchange (FX), monetary assets, and bonds) in China from 2013 to 2017, we use a VAR-GARCH-BEKK model to investigate mean and volatility spillover effects between Bitcoin and other major assets and explore whether Bitcoin can be used either as a hedging asset or a safe haven. Our empirical results show that (i) only the monetary market, i.e., the Shanghai Interbank Offered Rate (SHIIBOR) has a mean spillover effect on Bitcoin and (ii) gold, monetary, and bond markets have volatility spillover effects on Bitcoin, while Bitcoin has a volatility spillover effect only on the gold market. We further find that Bitcoin can be hedged against stocks, bonds and SHIBOR and is a safe haven when extreme price changes occur in the monetary market. Our findings provide useful information for investors and portfolio risk managers who have invested or hedged with Bitcoin.
Eric Masanet, Arman Shehabi, Nuoa Lei, Harald Vranken · 6 authors
Bitcoin mining is becoming an increasingly energy-intensive process whose future implications for energy use and CO2 emissions remain poorly understood. This is in part because—like many IT systems—its computational efficiencies and service demands have been evolving rapidly. Therefore, scenario analyses that explore these implications can fill pressing knowledge gaps, but they must be approached with care. History has shown that poorly constructed scenarios of future IT energy use—often due to overly-simplistic extrapolations of early rapid growth trends—can do more harm than good by spreading misinformation and driving ill-informed decisions. Indeed, the utility of an energy demand scenario is directly proportional to its credibility, which is typically demonstrated through careful attention to technology characteristics and evolution, analytical rigor and transparency, and designing scenarios that align with plausible future outcomes.
Toan Luu Duc Huynh, Mei Wang, Xuan Vinh Vo
This paper investigates the prediction power of Economic Policy Uncertainty on three aspects of Bitcoin, particularly the return, volume, and volatility. We employed the Transfer Entropy model with two different regimes: (i) stationary and (ii) non-stationary assumption. We constructed different algorithm calculations for returns, volume, and volatility to test how this proxy impacts. We find that the Global Economic Policy Uncertain negatively causes Bitcoin volumes and volatilities. Therefore, under uncertain regimes, investors are risk-averse to trade, which makes the market less volatile. Our findings confirm the existence of pessimistic risk premium and the theory of deteriorating liquidity under uncertainties in the Bitcoin market.
Imad A. Moosa
No abstract is available for this record.
Νikolaos Kyriazis, Paraskevi Prassa
This paper investigates the level of liquidity of digital currencies during the very intense bearish phase in their markets. The data employed span the period from April 2018 until January 2019, which is the second phase of bearish times with almost constant decreases. The Amihud’s illiquidity ratio is employed in order to measure the liquidity of these digital assets. Findings indicate that the most popular cryptocurrencies exhibit higher levels of liquidity during stressed periods. Thereby, it is revealed that investors’ preferences for trading during highly risky times are favorable for well-known virtual currencies in the detriment of less-known ones. This enhances findings of relevant literature about strong and persistent positive or negative herding behavior of investors based on Bitcoin, Ethereum and highly-capitalized cryptocurrencies in general. Notably though, a tendency towards investing in the TrueUSD stablecoin has also emerged.