Dependency Analysis between Bitcoin and Selected Global Currencies

Szetela, Beata; Mentel, Grzegorz; Gędek, Stanisław

doi:10.12775/dem.2016.009

Cited by 27 publications

(16 citation statements)

References 26 publications

(13 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both practitioners and theorists of financial markets have problems with the clear classification of cryptocurrencies and with indicating that universal mechanisms influence and explain the behavior of cryptocurrencies in the financial space. For further information on bitcoin and other cryptocurrencies, please refer to Liu et al (2015), Szetela et al (2016Szetela et al ( , 2020, Urquhart (2017), Corbet et al (2018).…”

mentioning

confidence: 99%

The relationship between trend and volume on the bitcoin market

et al. 2021

Self Cite

View full text Add to dashboard Cite

The aim of the paper is to verify the existence of short- and long-term relationships between the strength of a trend and the volume in bullish and bearish cryptocurrency markets. We applied the vector error correction model to bitcoin daily data from 14.01.2015 to 22.12.2019. Based on the prices and following Wilder’s algorithm, the average directional movement index was calculated, and upward and downward trend periods were determined. No long-term relationship was found to exist between the strength of a trend and the volume in both bearish and bullish markets. Hence, trends do not react to volume changes. However, a long-term relationship exists between volume and trend—but only for the downward trend—with an adjustment speed of 88%. In the short-term, a statistically significant but very weak dependency is revealed; hence, the conclusion that trend strength is insensitive to volume changes can be reached.

show abstract

mentioning

confidence: 99%

The relationship between trend and volume on the bitcoin market

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Atik et al (2015) investigated the impact of bitcoin on foreign exchange rates and determined that there is a one-way causality from Japanese Yen to Euro, and these two currencies are affected from each other. Szetela, Mentel and Gedek (2016) in their work, according to the results of the ARMA process, Bitcoin acts independently from other currencies in the analysis. The conditional variance of Bitcoin modeled with the GARCH process is affected by the Euro, Dollar and Yuan returns.…”

Section: Literaturementioning

confidence: 99%

Determination Price Volatility of Bitcoin with Autoregressive Conditional Heteroscedasticiy Models

Belliler

Yildirim

2021

Akademik Araştırmalar Ve Çalışmalar Dergisi (AKAD)

View full text Add to dashboard Cite

The purpose of this research is to analyze the price movements of bitcoin, which has become a new phenomenon in financial markets since 2009, the first year of its release, and can be defined as virtual money or crypto money, to be seen as a financial investment tool. Amaç: Bu araştırmanın amacı, ilk çıkış yılı olan 2009'dan günümüze finansal piyasalarda yeni bir fenomen haline gelen, sanal para veya kripto para olarak tanımlanabilen bitcoinin, finansal bir yatırım aracı olarak görülmesi yönündeki fiyat hareketlerinin analiz edilmesidir. Design/Methodology: In the study, volatility, return behavior and reliability as a financial investment tool are examined with autoregressive Conditional Variable Variance modeling. In this context, symmetrical and asymmetrical ARCH models were used.Tasarım/Yöntem: Çalışmada, Otoregresif Koşullu Değişen Varyans modellemeleri ile oynaklık, getiri davranışı ve finansal bir yatırım aracı olarak güvenilirliği incelenmektedir. Bu kapsamda simetrik ve asimetrik etkili ARCH modellemeleri kullanılmıştır. Findings: As a result of the analysis; it has been found that it has an asymmetric effect in the first period for the bitcoin return series examined with symmetric and asymmetric ARCH models. In addition, it has been determined that shocks occurring in the bitcoin return series according to the half-life criteria are exposed to the volatility effect for more than 30 days in each period. It has been determined that bitcoin, which is examined by periods, has higher volatility in its first years. Bulgular: Analizler sonucunda; simetrik ve asimetrik etkili ARCH modellemeleri ile incelenen bitcoin getiri serisi için ilk dönemde asimetrik etkiye sahip olduğu bulunmuştur. Ayrıca half-life ölçütüne göre bitcoin getiri serisinde meydana gelen şoklar her dönemde 30 günden daha fazla oynaklık kalıcılığı etkisine maruz kaldığı tespit edilmiştir. Dönemler itibariyle incelenen bitcoinin ilk yıllarında daha yüksek oynaklığa sahip olduğu tespit edilmiştir. Limitations:The volatility of bitcoin, which has become a new phenomenon in financial markets today, can be defined as virtual money or crypto money, has been analyzed.Sınırlılıklar: Günümüzde finansal piyasalarda yeni bir fenomen haline gelen, sanal para veya kripto para olarak tanımlanabilen bitcoinin oynaklığı analiz edilmiştir. Originality/Value: In fact, there are many virtual currencies or cryptocurrencies traded in the market. However, among many virtual currencies, bitcoin is the most known and the most market volume. Analyzing the price movements of bitcoin, which has started to be seen as a financial investment tool, is of great importance in the framework of reliability. The examination made in this respect constitutes the original value of the research.Özgünlük/Değer: Aslında piyasada ticareti yapılan çok sayıda sanal para veya diğer adıyla kripto para bulunmaktadır. Ancak birçok sanal para biriminin arasında en çok bilineni ve piyasa hacmi en fazla olanı olarak bitcoin karşımıza çıkmaktadır. Finansal bir yatırım aracı olarak görülmeye baş...

show abstract

“…The process of discovery to find out significant patterns, critical figures, or important connections to identify significant points about the relationship of these two concepts has a key role for the financial analysis in this field. Szetela et al (2016) identified the correlation among various currencies (i.e., Euro, Chinese Yuan, US Dollar, and the British pound). Similarly, Özdemir et al (2018) evaluated the price changes of cryptocurrencies and real money in the context of historical value changes in their analysis.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

“…In this research, the correlations of cryptocurrencies with financial assets or commodities other than fiat currencies typically contain gold, silver, stocks, and oil crude market (Cryptocurrency Market Capitalizations; Gajardo et al, 2018;Szetela et al, 2016). Dyhrberg (2016) emphasized the comparison of Bitcoin and gold in terms of hedging capabilities, where Klein et al (2018) analyzed conditional variance properties of Bitcoin and gold to reflect linkages and distinctive properties of these assets.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

An Investigation of Fiat Characterization and Evolutionary Dynamics of the Cryptocurrency Market

et al. 2021

View full text Add to dashboard Cite

Recent developments in global financial markets revealed that cryptocurrencies experienced rapid growth due to the popularity of blockchain technology and its evolving position in the digital finance industry. The rise of cryptocurrencies led economists to question generally accepted financial practices. Particularly the interaction between two different types of financial markets arose as a hot research topic to discover specific relationships and differences between major cryptocurrencies and fiat currencies. Therefore, this article aims to examine analyze by attaching importance to the Bitcoin to investigate significant linkages and analyze critical direct and indirect connections. In this research, Bitcoin—which is known as the most prominent cryptocurrency on the market—and 50 different conventional currencies are taken into consideration by applying cross-correlation, HT (hierarchical tree), and MST (minimum spanning tree) methods. The results of this work can be utilized by academicians and economists for further research related to the subject.

show abstract

Dependency Analysis between Bitcoin and Selected Global Currencies

Cited by 27 publications

References 26 publications

The relationship between trend and volume on the bitcoin market

The relationship between trend and volume on the bitcoin market

Determination Price Volatility of Bitcoin with Autoregressive Conditional Heteroscedasticiy Models

An Investigation of Fiat Characterization and Evolutionary Dynamics of the Cryptocurrency Market

Contact Info

Product

Resources

About