Search results

1 – 10 of 175
Article
Publication date: 12 July 2019

Cynthia Miglietti, Zdenka Kubosova and Nicole Skulanova

This paper aims to empirically investigate the volatility of Bitcoin, Litecoin and the Euro.

Abstract

Purpose

This paper aims to empirically investigate the volatility of Bitcoin, Litecoin and the Euro.

Design/methodology/approach

The authors use quantitative methodologies to assess the annualized volatility of two cryptocurrencies and one international fiat currency. The exchange rate of the currencies is monitored on a daily basis using 1,460 observations from January 1, 2014 to December 31, 2017. The models used include the augmented Dickey–Fuller test, Akaike Information Criteria, autocorrelation function and exchange rate changes determining which currency is the most volatile.

Findings

The findings indicate, based on the statistical measures used, including the standard deviation of selected currencies and annualized volatility, that Litecoin is more volatile than Bitcoin and the Euro and that Bitcoin is more volatile than the Euro. This furthers previous research on cryptocurrency volatility.

Originality/value

The paper provides compelling evidence about the volatility of Litecoin and Bitcoin. The volatility of cryptocurrencies is furthered with data that are more current. The findings are important for investors, financial markets and central banks.

Details

Studies in Economics and Finance, vol. 37 no. 2
Type: Research Article
ISSN: 1086-7376

Keywords

Article
Publication date: 27 May 2021

Onur Polat and Eylül Kabakçı Günay

The purpose of this study is to investigate volatility connectedness between major cryptocurrencies by the virtue of market capitalization. In this context, this paper…

447

Abstract

Purpose

The purpose of this study is to investigate volatility connectedness between major cryptocurrencies by the virtue of market capitalization. In this context, this paper implements the frequency connectedness approach of Barunik and Krehlik (2018) and to measure short-, medium- and long-term connectedness between realized volatilities of cryptocurrencies. Additionally, this paper analyzes network graphs of directional TO/FROM spillovers before and after the announcement of the COVID-19 pandemic by the World Health Organization.

Design/methodology/approach

In this study, we examine the volatility connectedness among eight major cryptocurrencies by the virtue of market capitalization by using the frequency connectedness approach over the period July 26, 2017 and October 28, 2020. To this end, this paper computes short-, medium- and long-cycle overall spillover indexes on different frequency bands. All indexes properly capture well-known events such as the 2018 cryptocurrency market crash and COVID-19 pandemic and markedly surge around these incidents. Furthermore, owing to notably increased volatilities after the official announcement of the COVID-19 pandemic, this paper concentrates on network connectedness of volatility spillovers for two distinct periods, July 26, 2017–March 10, 2020 and March 11, 2020–October 28, 2020, respectively. In line with the related studies, major cryptocurrencies stand at the epicenter of the connectedness network and directional volatility spillovers dramatically intensify based on the network analysis.

Findings

Overall spillover indexes have fluctuated between 54% and 92% in May 2018 and April 2020. The indexes gradually escalated till November 9, 2018 and surpassed their average values (71.92%, 73.66% and 74.23%, respectively). Overall spillover indexes dramatically plummeted till January 2019 and reached their troughs (54.04%, 57.81% and 57.81%, respectively). Etherium catalyst the highest sum of volatility spillovers to other cryptocurrencies (94.2%) and is followed by Litecoin (79.8%) and Bitcoin (76.4%) before the COVID-19 announcement, whereas Litecoin becomes the largest transmitter of total volatility (89.5%) and followed by Bitcoin (89.3%) and Etherium (88.9%). Except for Etherium, the magnitudes of total volatility spillovers from each cryptocurrency notably increase after – COVID-19 announcement period. The medium-cycle network topology of pairwise spillovers indicates that the largest transmitter of total volatility spillover is Litecoin (89.5%) and followed by Bitcoin (89.3%) and Etherium (88.9%) before the COVID-19 announcement. Etherium keeps its leading role of transmitting the highest sum of volatility spillovers (89.4%), followed by Bitcoin (88.9%) and Litecoin (88.2%) after the COVID-19 announcement. The largest transmitter of total volatility spillovers is Etherium (95.7%), followed by Litecoin (81.2%) and Binance Coin (75.5%) for the long-cycle connectedness network in the before-COVID-19 announcement period. These nodes keep their leading roles in propagating volatility spillover in the latter period with the following sum of spillovers (Etherium-89.5%, Bitcoin-88.9% and Litecoin-88.1%, respectively).

Research limitations/implications

The study can be extended by including more cryptocurrencies and high-frequency data.

Originality/value

The study is original and contributes to the extant literature threefold. First, this paper identifies connectedness between major cryptocurrencies on different frequency bands by using a novel methodology. Second, this paper estimates volatility connectedness between major cryptocurrencies before and after the announcement of the COVID-19 pandemic and thereby to concentrate on its impact on the cryptocurrency market. Third, this paper plots network graphs of volatility connectedness and herewith picture the intensification of cryptocurrencies due to a major financial distress event.

Details

Studies in Economics and Finance, vol. 38 no. 5
Type: Research Article
ISSN: 1086-7376

Keywords

Open Access
Article
Publication date: 4 October 2019

A. Can Inci and Rachel Lagasse

This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period…

12148

Abstract

Purpose

This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period covering not only the large value increases but also the dramatic declines during the beginning of 2018, the purpose of this paper is to provide a more complete analysis of the dynamic nature of cryptocurrencies as individual investment opportunities, and as components of optimal portfolios.

Design/methodology/approach

The mean-variance optimization technique of Merton (1990) is applied to develop the risk and return characteristics of the efficient portfolios, along with the optimal weights of the asset class components in the portfolios.

Findings

The authors provide evidence that as a single investment, the best cryptocurrency is Ripple, followed by Bitcoin and Litecoin. Furthermore, cryptocurrencies have a useful role in the optimal portfolio construction and in investments, in addition to their original purposes for which they were created. Bitcoin is the best cryptocurrency enhancing the characteristics of the optimal portfolio. Ripple and Litecoin follow in terms of their usefulness in an optimal portfolio as single cryptocurrencies. Including all these cryptocurrencies in a portfolio generates the best (most optimal) results. Contributions of the cryptocurrencies to the optimal portfolio evolve over time. Therefore, the results and conclusions of this study have no guarantee for continuation in an exact manner in the future. However, the increasing popularity and the unique characteristics of cryptocurrencies will assist their future presence in investment portfolios.

Originality/value

This is one of the first studies that examine the role of popular cryptocurrencies in enhancing a portfolio composed of traditional asset classes. The sample period is the largest that has been used in this strand of the literature, and allows to compare optimal portfolios in early/recent subsamples, and during the pre-/post-cryptocurrency crisis periods.

Details

Journal of Capital Markets Studies, vol. 3 no. 2
Type: Research Article
ISSN: 2514-4774

Keywords

Article
Publication date: 4 March 2021

Vaibhav Aggarwal

Bitcoin and Ethereum, although the most prominent cryptocurrencies, carry a high ticker price. Many investors carry an inherent bias against high price ticker securities…

Abstract

Purpose

Bitcoin and Ethereum, although the most prominent cryptocurrencies, carry a high ticker price. Many investors carry an inherent bias against high price ticker securities and prefer only low prices securities. This paper aims to help market players generate adequate risk-adjusted returns by investing in only lower-priced cryptocurrencies.

Design/methodology/approach

The pairwise bivariate BEKK-GARCH (1,1) model is deployed to capture the short- and long-term volatility linkages between Litecoin, Stellar and Ripple from August 2015 to June 2020.

Findings

Litecoin is the most influential volatility sender in the basket of these three cryptocurrencies. The portfolio weights indicate that investors can create an optimized two asset portfolio with the lowest exposure to Stellar with Litecoin and Ripple. Market players with a long position in Ripple can have the cheapest hedge by shorting Stellar.

Originality/value

This study adds to the scant literature on the association between emerging cryptocurrencies and finding optimum portfolio weight and hedge ratios.

Details

International Journal of Innovation Science, vol. 14 no. 3/4
Type: Research Article
ISSN: 1757-2223

Keywords

Article
Publication date: 3 May 2022

Syed Ali Raza, Larisa Yarovaya, Khaled Guesmi and Nida Shah

This article aims to uncover the impact of Google Trends on cryptocurrency markets beyond Bitcoin during the time of increased attention to altcoins, especially during the…

Abstract

Purpose

This article aims to uncover the impact of Google Trends on cryptocurrency markets beyond Bitcoin during the time of increased attention to altcoins, especially during the COVID-19 pandemic.

Design/methodology/approach

This paper analyses the nexus among the Google Trends and six cryptocurrencies, namely Bitcoin, New Economy Movement (NEM), Dash, Ethereum, Ripple and Litecoin by utilizing the causality-in-quantiles technique on data comprised of the years January 2016–March 2021.

Findings

The findings show that Google Trends cause the Litecoin, Bitcoin, Ripple, Ethereum and NEM prices at majority of the quantiles except for Dash.

Originality/value

The findings will help investors to develop more in-depth understanding of impact of Google Trends on cryptocurrency prices and build successful trading strategies in a more matured digital assets ecosystem.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 27 September 2021

Thomas Dimpfl and Dalia Elshiaty

Cryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, the aim of this paper is to investigate which one of the…

Abstract

Purpose

Cryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, the aim of this paper is to investigate which one of the cryptocurrency markets contributes the most to the common volatility component inherent in the market.

Design/methodology/approach

The paper extracts each of the cryptocurrency's markets' latent volatility using a stochastic volatility model and, subsequently, models their dynamics in a fractionally cointegrated vector autoregressive model. The authors use the refinement of Lien and Shrestha (2009, J. Futures Mark) to come up with unique Hasbrouck (1995, J. Finance) information shares.

Findings

The authors’ findings indicate that Bitfinex is the leading market for Bitcoin and Ripple, while Bitstamp dominates for Ethereum and Litecoin. Based on the dominant market for each cryptocurrency, the authors find that the volatility of Bitcoin explains most of the volatility among the different cryptocurrencies.

Research limitations/implications

The authors’ findings are limited by the availability of the cryptocurrency data. Apart from Bitcoin, the data series for the other cryptocurrencies are not long enough to ensure the precision of the authors’ estimates.

Originality/value

To date, only price discovery in cryptocurrencies has been studied and identified. This paper extends the current literature into the realm of volatility discovery. In addition, the authors propose a discrete version for the evolution of a markets fundamental volatility, extending the work of Dias et al. (2018).

Details

The Journal of Risk Finance, vol. 22 no. 5
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 14 January 2022

Shailesh Rastogi and Jagjeevan Kanoujiya

The main aim of the study is to explore the volatility spillover effect of cryptocurrencies (Bitcoin, Ethereum and Litecoin) on inflation volatility in India.

Abstract

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.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1026-4116

Keywords

Article
Publication date: 26 November 2021

Mutaju Isaack Marobhe

This article examines the susceptibility of cryptocurrencies to coronavirus disease 2019 (COVID-19) induced panic in comparison with major stock indices.

Abstract

Purpose

This article examines the susceptibility of cryptocurrencies to coronavirus disease 2019 (COVID-19) induced panic in comparison with major stock indices.

Design/methodology/approach

The author employs the Bayesian structural vector autoregression to examine the phenomenon in Bitcoin, Ethereum and Litecoin from 2nd January 2020 to 30th June 2021. A similar analysis is conducted for major stock indices, namely S&P 500, FTSE 100 and SSE Composite for comparison purposes.

Findings

The results suggest that cryptocurrencies returns suffered immensely in the early days of the COVID-19 outbreak following declarations of the disease as a global health emergency and eventually a pandemic in March 2020. However, the returns for all three cryptocurrencies recovered by April 2020 and remained resistant to further COVID-19 panic shocks. The results are dissimilar to those of S&P 500, FTSE 100 and SSE Composite values which were vulnerable to COVID-19 panic throughout the timeframe to June 2021. The results further reveal strong predictive power of Bitcoin on prices of other cryptocurrencies.

Research limitations/implications

The article provides evidence to support the cryptocurrency as a safe haven during COVID-19 school of thought given their resistance to subsequent shocks during COVID-19. Thus, the author stresses the need for diversification of investment portfolios by including cryptocurrencies given their uniqueness and resistance to shocks during crises.

Originality/value

The author makes use of the novel corona virus panic index to examine the magnitude of shocks in prices of cryptocurrencies during COVID-19.

Details

China Finance Review International, vol. 12 no. 1
Type: Research Article
ISSN: 2044-1398

Keywords

Article
Publication date: 6 September 2019

Calvin W. H. Cheong

This study aims to examine the properties of four major cryptocurrencies and how they can be used as a simpler alternative mode of hedging foreign exchange (FX) risks as…

1840

Abstract

Purpose

This study aims to examine the properties of four major cryptocurrencies and how they can be used as a simpler alternative mode of hedging foreign exchange (FX) risks as compared to existing mainstream financial risk management techniques.

Design/methodology/approach

This study uses a combination of visual data representations and the classic Fama and Macbeth (1973) two-pass procedure regressions.

Findings

The findings show that cryptocurrencies can be a more effective hedge against FX risks as compared to other common hedging instruments and/or techniques such as gold or a diversified currency portfolio.

Research limitations/implications

The conclusions were arrived at based only on a small group of cryptocurrency, i.e. Bitcoin, Ethereum, Litecoin and Ripple. Other cryptocurrencies such as Dogecoin or ZCash might exhibit different properties.

Practical implications

Cryptocurrencies can be cost-effective and cost-efficient instruments that provide a solid hedge for investors and/or firms that are exposed to global FX volatility. Its ease of trade and virtually zero barriers to entry makes it an easily accessible alternative hedge instrument as compared to more complex items such as derivatives.

Originality/value

If cryptocurrencies are to be accepted into mainstream usage, a detailed examination of its various uses is necessary. In particular, as they are often touted to be the future of currency, its properties and price behavior relative to other mainstream financial instruments need to be well-understood, not only by finance professionals but also by laypersons.

Details

The Journal of Risk Finance, vol. 20 no. 4
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 19 June 2020

Yaman Omer Erzurumlu, Tunc Oygur and Alper Kirik

Considering the different motivation for the creation of each of these cryptocurrencies, the purpose of this paper is to examine whether there is a dominant external…

Abstract

Purpose

Considering the different motivation for the creation of each of these cryptocurrencies, the purpose of this paper is to examine whether there is a dominant external factor in the cryptocurrency world. Using a novel two-step time and frequency independent methodology, the authors examine a large scope of cryptocurrencies and external factors within the same period, and analytical framework.

Design/methodology/approach

The examined cryptocurrencies are Bitcoin, Ethereum, Ripple, Litecoin, Monero and Dash. In total, 18 external factors from 5 factor families are selected based on the mining motivation of these cryptocurrencies. The study first examines discrete wavelet transform-based (WTB) correlations, reduce the dimension and focuson relevant pairs. Selected pairs are further examined by wavelet coherence to capture the intermittent nature of the relationships allowing the most needed “Flexibility of frequency and time domains”.

Findings

Each coin appears to operate as a unique character with the exception of Bitcoin and Litecoin. There is no prominent external driver. The cryptocurrency market is not a clear substitute for a specific factor or market. Two-step WTB filtered wavelet coherence analysis help us to analyze a large number of factor without the loss of focus. The co-movements within the cryptocurrencies spillover from Ethereum to altcoins and later to Bitcoin.

Originality/value

The study presents one of the first examples of two-step WTB filtered wavelet coherence analysis. The methodology suggests an approach for simultaneous examination of large number of variables. The scope of the study provides a rather holistic view of the co-movements of external factors and major cryptocurrencies.

Details

Studies in Economics and Finance, vol. 37 no. 3
Type: Research Article
ISSN: 1086-7376

Keywords

1 – 10 of 175