Follow blockchain research across journals, conferences, and preprint repositories.
4,843 results · page 115 of 202
Rabeh Khalfaoui, Sami Ben Jabeur, Buhari Doğan
No abstract is available for this record.
Syed Jawad Hussain Shahzad, Muhammad Anas, Elie Bouri
No abstract is available for this record.
Jan-Oliver Strych
No abstract is available for this record.
Toan Luu Duc Huynh
We present a textual analysis that explains how Elon Musk's sentiments in his Twitter content correlates with price and volatility in the Bitcoin market using the dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity model, allowing less sensitive to window size than traditional models. After examining 10,850 tweets containing 157,378 words posted from December 2017 to May 2021 and rigorously controlling other determinants, we found that the tone of the world's wealthiest person can drive the Bitcoin market, having a Granger causal relation with returns. In addition, Musk is likely to use positive words in his tweets, and reversal effects exist in the relationship between Bitcoin prices and the optimism presented by Tesla's CEO. However, we did not find evidence to support linkage between Musk's sentiments and Bitcoin volatility. Our results are also robust when using a different cryptocurrency, i.e., Ether this paper extends the existing literature about the mechanisms of social media content generated by influential accounts on the Bitcoin market.
Sitara Karim, Muhammad Abubakr Naeem, Nawazish Mirza, Jéssica Paule-Vianez
Purpose This study quantified the hedge and safe haven features of bond markets for multiple cryptocurrency indices from June 2014 to April 2021 to highlight whether bond markets offer hedging facilities to uncertainty indices of cryptocurrencies. Design/methodology/approach The authors employed the methodology of Baur and McDermott (2010) and AGDCC-GARCH model to measure the hedge and safe-haven characteristics of three bond markets (BBGT, SPGB and SKUK) for three uncertainty indexes of cryptocurrencies (UCRPR, UCRPO and ICEA). Findings The authors find that bond markets are neither hedge nor safe havens except for SKUK which is a safe haven investment for cryptocurrency indices and offers substantial diversification during the periods of economic fragility. In addition, the hedge effectiveness of SPGB outperforms other bonds during crisis periods and provides sufficient diversification potential for cryptocurrency indices. Practical implications The findings are important for policymakers, regulatory bodies, financial firms and investors in assessing hedge and safe haven characteristics of bond markets against cryptocurrency indices. Originality/value Employing the novel methodology of AGDCC-GARCH with three different bond markets and three uncertainty indices of cryptocurrencies, the current study adds to the existing strand of literature in terms of quantifying hedge and safe-haven attributes of bond markets for cryptocurrency uncertainty indexes.
Shailesh Rastogi, Jagjeevan Kanoujiya
Purpose The main aim of the study is to explore the volatility spillover effect of cryptocurrencies (Bitcoin, Ethereum and Litecoin) on inflation volatility in India. Design/methodology/approach A popular tool, the Bivariate GARCH model (BEKK-GARCH), to study the volatility spillover effect, is applied in the study. Monthly data of cryptocurrencies and inflation (WPI and CPI indices) are gathered from 2015 to 2021. Findings Significant short-term responsiveness of volatility of cryptocurrencies on the inflation volatility is found. In addition to this, the significant volatility spillover effect from the cryptocurrencies to the inflation volatility is found. Practical implications The findings of the current paper can be of use for inflation management, target inflation policies and policies to contain the volatility of cryptocurrencies. The significance of the current paper is relevant as governments worldwide are officially recognizing cryptocurrencies and starting the process of launching their official virtual currency. Originality/value No other study is observed on the topic. Hence, the contribution and novelty of the findings of the current paper are very high and add value to the nonexistent literature on the topic. Lack of the number of inflation observations (data of CPI and WPI are available only in monthly frequency) crimps the model estimation. As the cryptocurrencies become old, more data points will be available by design, and such problems can be resolved, and better model estimation may be possible.
Tao Tang, Yanchen Wang
No abstract is available for this record.
Erkan USTAOĞLU
The aim of the study investigates the return and volatility spillovers and conditional correlations between Borsa Istanbul Stock Exchange 100 Index (BIST100) and Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTH) using daily data for the period between August 07, 2015 and May 20, 2021 with VAR-DCC-GARCH model. We find no bidirectional return spillovers between BIST100 and cryptocurrencies. In line with the volatility spillover results of the study, it has been determined that there is a unidirectional shock transmission from BIST100 to BTC, XRP and LTH, and a unidirectional volatility spillover from BIST100 to BTC and ETH. Also, in the study, it has been determined that the dynamic conditional correlations between BIST100 and four cryptocurrencies have a highly variable over time and their average is very close to zero. However, in possible panic periods, the situation is reversed
Mieszko Mazur
Bitcoin market capitalization recently surpassed $1 trillion. While popular belief holds that a key characteristic of bitcoin is its excessive volatility, this article provides evidence that this is largely a misperception. We show that bitcoin return fluctuations are lower than those of roughly 900 stocks in the S&P1500 and 190 stocks in the S&P500. Moreover, we find that bitcoin is less volatile than commodities such as oil and silver, US Treasuries, AAA-rated corporate bonds, EU carbon credits, and some of the most popular technology and media stocks, including Apple, Twitter, and Netflix. Equally important, we find that during the March 2020 stock market crash triggered by COVID-19, the volatility of bitcoin was lower than that of most of these asset classes. The significant decline in bitcoin volatility over the past decade renders it more investable for conservative investors.
Lihua Qian, Jiqian Wang, Feng Ma, Ziyang Li
No abstract is available for this record.
Feng Han, Shuai Ma, Jiheng Zhang
Financial data are expensive and highly sensitive with limited access. We aim to generate abundant datasets given the original prices while preserving the original statistical features. We introduce the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) into the field of the stock market, futures market and cryptocurrency market. We train our model on various datasets, including the Hong Kong stock market, Hang Seng Index Composite stocks, precious metal futures contracts listed on the Chicago Mercantile Exchange and Japan Exchange Group, and cryptocurrency spots and perpetual contracts on Binance at various minute-level intervals. We quantify the difference of generated results (836,280 data points) and original data by MAE, MSE, RMSE and K-S distances. Results show that WGAN-GP can simulate assets prices and show the potential of a market simulator for trading analysis. We might be the first to look into multi-asset classes in a systematic approach with minute intervals across stocks, futures and cryptocurrency markets. We also contribute to quantitative analysis methodology for generated and original price data quality.
Berna Aydoğan, Gülin Vardar, Caner Taçoğlu
Purpose The existence of long memory and persistent volatility characteristics of cryptocurrencies justifies the investigation of return and volatility/shock spillovers between traditional financial market asset classes and cryptocurrencies. The purpose of this paper is to investigate the dynamic relationship between the cryptocurrencies, namely Bitcoin and Ethereum, and stock market indices of G7 and E7 countries to analyze the return and volatility spillover patterns among these markets by means of multivariate (MGARCH) approach. Design/methodology/approach Applying the newly developed VAR-GARCH-in mean framework with the BEKK representation, the empirical results reveal that there exists an evidence of mean and volatility spillover effects among Bitcoin and Ethereum as the proxies for the cryptocurrencies, and stock markets reviewed. Findings Interestingly, the direction of the return and volatility spillover effects is unidirectional in most E7 countries, but bidirectional relationship was found in most G7 countries. This can be explained as the presence of a strong return and volatility interaction among G7 stock markets and crypto market. Originality/value Overall, the results of this study are of particular interest for portfolio management since it provides insights for financial market participants to make better portfolio allocation decisions. It is also increasingly important to understand the volatility transmission mechanism across these markets to provide policymakers and regulatory bodies with guidance to eliminate the negative impact of cryptocurrency's volatility on the stability of financial markets.
Lehlohonolo Letho, Grieve Chelwa, Abdul Latif Alhassan
Purpose This paper examines the effect of cryptocurrencies on the portfolio risk-adjusted returns of traditional and alternative investments within an emerging market economy. Design/methodology/approach The paper employs daily arithmetic returns from August 2015 to October 2018 of traditional assets (stocks, bonds, currencies), alternative assets (commodities, real estate) and cryptocurrencies. Using the mean-variance analysis, the Sharpe ratio, the conditional value-at-risk and the mean-variance spanning tests. Findings The paper documents evidence to support the diversification benefits of cryptocurrencies by utilising the mean-variance tests, improving the efficient frontier and the risk-adjusted returns of the emerging market economy portfolio of investments. Practical implications This paper firmly broadens the Modern Portfolio Theory by authenticating cryptocurrencies as assets with diversification benefits in an emerging market economy investment portfolio. Originality/value As far as the authors are concerned, this paper presents the first evidence of the effect of diversification benefits of cryptocurrencies on emerging market asset portfolios constructed using traditional and alternative assets.
Mudassar Hasan, Muhammad Abubakr Naeem, Muhammad Arif, Syed Jawad Hussain Shahzad · 5 authors
We examine the dynamics of liquidity connectedness in the cryptocurrency market. We use the connectedness models of Diebold and Yilmaz (Int J Forecast 28(1):57-66, 2012) and Baruník and Křehlík (J Financ Econom 16(2):271-296, 2018) on a sample of six major cryptocurrencies, namely, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Ripple (XRP), Monero (XMR), and Dash. Our static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies, whereas BTC and LTC play a significant role in connectedness magnitude. A distinct liquidity cluster is observed for BTC, LTC, and XRP, and ETH, XMR, and Dash also form another distinct liquidity cluster. The frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium- and long-run time horizons. In the short run, BTC, LTC, and XRP are the leading contributor to liquidity shocks, whereas, in the long run, ETH assumes this role. Compared with the medium term, a tight liquidity clustering is found in the short and long terms. The time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time, pointing to the possible effect of rising demand and higher acceptability for this unique asset. Furthermore, more pronounced liquidity connectedness patterns are observed over the short and long run, reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time-frequency connectedness.
Sayantan Bandhu Majumder
Purpose This paper aims to evaluate the hedging and safe haven properties of gold, cryptocurrency and commodities against the Indian equity market. Design/methodology/approach First, the authors estimate the hedging and safe haven abilities of gold, cryptocurrency and commodities for the Indian stock market and further verify whether such properties vary across the broad stock market indices and over the different degrees of market volatility. Second, the authors use the multivariate GARCH framework to calculate the dynamic hedge ratios and hedging efficiencies to compare the hedging properties of the alternative asset classes. Third, the authors verify the robustness of the general findings during the recent crisis emanating from the outbreak of the COVID-19 pandemic. Findings Gold, cryptocurrency and most commodities have significant hedging abilities. Only natural gas, crude oil and aluminum, on the other hand, have safe haven property. Neither gold nor cryptocurrency qualifies as a safe haven asset. On the other hand, the financialization of the Indian commodities market provides a significant dividend to investors in terms of hedging and safe haven capabilities. The authors find the least negative hedge ratio and the highest positive hedging effectiveness for the stock-crude oil and stock-natural gas portfolios. The central observations of the paper remain immune to the COVID crisis. Originality/value Focusing on the Indian equity market, the paper compares the diversification abilities of traditional assets like gold with those of the modern class of assets, including cryptocurrency and other commodities.
Michael Dempsey, Huy Pham, Vikash Ramiah
We consider the performance of cryptocurrencies in the light of fundamental asset pricing and portfolio theory. We observe how a traditional focus on reducing asset return volatility with Markowitz diversification misses the significance of such volatility for growth. The recognition that asset growth is more likely subject to exponential or continuously compounding growth characteristics reveals that asset volatility can be exploited both across assets and across investment periods to deliver superior returns.
Sunitha Kumaran
The appealing features of cryptocurrency in the digital money sector have put them into the category of investable assets. Investment professionals have begun to consider their investability and diversification benefits. It is vital for investors to understand the return-risk behaviour among investable assets to reap the benefits of diversification. This paper considers a proxy of cryptos, specifically Bitcoin, Litecoin, Ethereum, Ripple & Neo, and the Middle East stock market indices, to examine the dynamic relationship among them using the vector error correction model. This study found evidence to suggest that cryptos exhibit a co-integrated relationship while there is no evidence of significant cointegrated movements occurring between the cryptos and the market indices. The latter finding implies that cryptos are decoupled from the market indices and can serve as a diversification option for investors. The mean-variance approach confirms that cryptocurrencies fit into an optimal portfolio and involve an enhanced return-risk reward for investors.
Viviane Y. Naïmy, Omar Haddad, Rim El Khoury
No abstract is available for this record.
Ruixin Hu, Xuecheng Wang
Bitcoin is currently the most widely used encryption currency in the world, and the Nasdaq Index, as the world's first stock market to use electronic trading, has a certain impact on the price of Bitcoin.Based on the Bitcoin closing price and Nasdaq index data from January 2020 to May 2022, this paper predicts the price of Bitcoin by using ARIMA and ARIMAX models respectively.The linkage was confirmed by the correlation test, and the fitting and prediction effect of the ARIMAX model with the Nasdaq index as the input variable were better than the ARIMA model.
N.V. Tskhadadze
Учёным советом ФНИСЦ РАН
Debesh Bhowmik
The paper endeavour to explore the nexus between Bitcoin Rouble exchange rate and the Russian capital market using cointegration and vector error correction analysis taking the capital market indicators namely US Dollar Rouble exchange rate, MOEX index, RTX index, Moscow exchange trade turn over and RUONIA of Russia using daily data from 1/11/2021 to 18/4/2022 as a consequence of post pandemic recovery and sets back from war between Russia and Ukraine. The paper found that the trend line of Bitcoin Rouble rate is cyclical with four phases whose Wavelet threshold signal curve is explosive oscillatory. There are no short run causalities from the indicators of capital market to the Bitcoin Rouble price but there is insignificant and converging cointegrating long run causalities from those indicators where the relation between Bitcoin Rouble and US Dollar Rouble rate and MOEX index are significantly negative and the relation with RTX index is significantly positive. It was evident that there is little significant influence of Bitcoin Rouble pricing on the Russian capital market in the long run.
Nathaphat Na Chiangmai, Nathee Naktnasukanjn, Piyachat Udomwong
No abstract is available for this record.
Ch. Likhitha Sree, M. Meghana, R. Manjula, D. Mohan
No abstract is available for this record.
José Antonio García Pereáñez
No abstract is available for this record.