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An Introduction to Algorithmic Finance, Algorithmic Trading and Blockchain
Type: Book
ISBN: 978-1-78973-894-0

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Article
Publication date: 1 December 2020

Gary Low and Terence Tan

To address recent cases and the applicable legal principles relating to cryptocurrency, and to contribute to legal thought in this developing area of law.

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608

Abstract

Purpose

To address recent cases and the applicable legal principles relating to cryptocurrency, and to contribute to legal thought in this developing area of law.

Design/methodology/approach

This article considers recent cryptocurrency related cases in Singapore, Canada and the United Kingdom, and then considers the implications of the developing law in relation to proper causes of action and issues of practical asset recovery relating to the enforcement of judgments.

Findings

The intangible and highly movable nature of cryptocurrency places a premium on decisive asset recovery. The cases also suggest that injunctions remain a useful and effective debt recovery tool, especially when coupled with quick investigative action to trace cryptocurrency payments. However, the law remains unsettled as to the most appropriate cause of action for a claim in cryptocurrency or how a debt in cryptocurrency can be subject to execution. These issues raise the fundamental question of the nature of cryptocurrency, whether it belongs to an existing category of property, or if it is sui generis.

Practical implications

Cryptocurrency remains relatively novel and usage is increasing but not widespread. Users of cryptocurrency and lawyers involved in transactions or disputes involving cryptocurrency would benefit from a broader understanding of the legal issues

Originality/value

This article provides expert analysis from experienced litigation lawyers familiar with the concepts behind cryptocurrency.

Details

Journal of Investment Compliance, vol. 21 no. 2/3
Type: Research Article
ISSN: 1528-5812

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Article
Publication date: 2 July 2018

Vadim Avdeychik and Justin Capozzi

This paper aims to provide an overview of recent US Securities and Exchange Commission (SEC) Division of Investment Management staff (“Staff”) guidance related to…

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513

Abstract

Purpose

This paper aims to provide an overview of recent US Securities and Exchange Commission (SEC) Division of Investment Management staff (“Staff”) guidance related to investment funds registered under the Investment Company Act of 1940 that seeks to provide exposure to cryptocurrencies or cryptocurrency-related products.

Design/methodology/approach

This paper provides analysis regarding the Staff’s view on registered investment companies that intend to invest in cryptocurrencies or cryptocurrency-related products, including an overview of the questions posed by the Staff with respect to registered investment companies that seek to hold cryptocurrencies or cryptocurrency-related products, which are divided into five categories: valuation, liquidity, custody, arbitrage (for exchange-traded funds) and potential manipulation and other risks.

Findings

The Staff is asking for additional information from industry participants to fully analyze and evaluate registered investment companies that seek to invest in cryptocurrencies.

Practical implications

The industry should continue to provide information to the Staff with the short-term goal of fostering an open dialogue and with the long-term goal of launching a registered investment company that invests in cryptocurrencies or cryptocurrency-related products.

Originality/value

This paper provides practical guidance from experienced lawyers of the Investment Company Act and Securities Act.

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Article
Publication date: 23 November 2021

Kwansoo Kim, Sang-Yong Tom Lee and Saïd Assar

The authors examine cryptocurrency market behavior using a hidden Markov model (HMM). Under the assumption that the cryptocurrency market has unobserved heterogeneity, an…

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14

Abstract

Purpose

The authors examine cryptocurrency market behavior using a hidden Markov model (HMM). Under the assumption that the cryptocurrency market has unobserved heterogeneity, an HMM allows us to study (1) the extent to which cryptocurrency markets shift due to interactions with social sentiment during a bull or bear market and (2) the heterogeneous pattern of cryptocurrency market behavior under these two market conditions.

Design/methodology/approach

The authors advance the HMM model based on two six-month datasets (from November 2017 to April 2018 for a bull market and from December 2018 to May 2019 for a bear market) collected from Google, Twitter, the stock market and cryptocurrency trading platforms in South Korea. Social sentiment data were collected by crawling Bitcoin-related posts on Twitter.

Findings

The authors highlight the reaction of the cryptocurrency market to social sentiment under a bull and a bear market and in two hidden states (an upward and a downward trend). They find: (1) social sentiment is relatively relevant during a bull compared to a bear market. (2) The cryptocurrency market in a downward state, that is, with a local decreasing trend, tends to be more responsive to positive social sentiment. (3) The market in an upward state, that is, with a local increasing trend, tends to better interact with negative social sentiment.

Originality/value

The proposed HMM model contributes to a theoretically grounded understanding of how cryptocurrency markets respond to social sentiment in bull and bear markets through varied sequences adjusted for cryptocurrency market heterogeneity.

Details

Industrial Management & Data Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-5577

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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. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1398

Keywords

Content available
Article
Publication date: 29 November 2021

Ruby Khan and Tahani Ali Hakami

The objective of this study is to examine the nature of cryptocurrencies, risks involved in using it due to its volatile nature, advantages, disadvantages and its…

Abstract

Purpose

The objective of this study is to examine the nature of cryptocurrencies, risks involved in using it due to its volatile nature, advantages, disadvantages and its functions as money.

Design/methodology/approach

This is an inductive approach to a descriptive analysis (Qualitative research). In order to come to an adequate conclusion, we reviewed several studies and articles previously published in this field related to our research questions, and then explored the nature of Cryptocurrencies, their advantages and disadvantages, risks associated with cryptocurrency usage and their user-friendliness in Saudi Arabia.

Findings

The findings of this study reveal that anonymity and concealment are important aspects of cryptocurrencies. This system does not follow a transparent process that can make it parallel to conventional fiat currency.

Research limitations/implications

Although this study focuses on the issue of trust, it fails to recognize more technological factors hampering its transaction mechanism instead of enhancing it, owing to a lack of facts and knowledge.

Practical implications

Like conventional transaction system users must sign their crypto transactions that others must duly verify easily. Once a promise is made, one will not be able to back out of it until it is protected from revocation by the signer.

Originality/value

In comparison with reviewed literature, this study focuses more on the issue of volatility, which accounts for the fact that cryptocurrency has not been accepted as a permanent tool of monetary policy. Additionally, the study finds that the Saudi public is largely pessimistic toward such currencies.

Details

Journal of Money and Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-2596

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Article
Publication date: 5 November 2021

M. Kabir Hassan, Fahmi Ali Hudaefi and Rezzy Eko Caraka

This paper aims to explore netizen’s opinions on cryptocurrency under the lens of emotion theory and lexicon sentiments analysis via machine learning.

Abstract

Purpose

This paper aims to explore netizen’s opinions on cryptocurrency under the lens of emotion theory and lexicon sentiments analysis via machine learning.

Design/methodology/approach

An automated Web-scrapping via RStudio is performed to collect the data of 15,000 tweets on cryptocurrency. Sentiment lexicon analysis is done via machine learning to evaluate the emotion score of the sample. The types of emotion tested are anger, anticipation, disgust, fear, joy, sadness, surprise, trust and the two primary sentiments, i.e. negative and positive.

Findings

The supervised machine learning discovers a total score of 53,077 sentiments from the sampled 15,000 tweets. This score is from the artificial intelligence evaluation of eight emotions, i.e. anger (2%), anticipation (18%), disgust (1%), fear (3%), joy (15%), sadness (3%), surprise (7%), trust (15%) and the two sentiments, i.e. negative (4%) and positive (33%). The result indicates that the sample primarily contains positive sentiments. This finding is theoretically significant to measure the emotion theory on the sampled tweets that can best explain the social implications of the cryptocurrency phenomenon.

Research limitations/implications

This work is limited to evaluate the sampled tweets’ sentiment scores to explain the social implication of cryptocurrency.

Practical implications

The finding is necessary to explain the recent phenomenon of cryptocurrency. The positive sentiment may describe the increase in investment in the decentralised finance market. Meanwhile, the anticipation emotion may illustrate the public’s reaction to the bubble prices of cryptocurrencies.

Social implications

Previous studies find that the social signals, e.g. word-of-mouth, netizens’ opinions, among others, affect the cryptocurrencies’ movement prices. This paper helps explain the social implications of such dynamic of pricing via sentiment analysis.

Originality/value

This study contributes to theoretically explain the implications of the cryptocurrency phenomenon under the emotion theory. Specifically, this study shows how supervised machine learning can measure the emotion theory from data tweets to explain the implications of cryptocurrencies.

Details

Studies in Economics and Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1086-7376

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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

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Article
Publication date: 21 September 2021

Mahdi Ghaemi Asl, Muhammad Mahdi Rashidi and Seyed Ali Hosseini Ebrahim Abad

The purpose of this study is to investigate the correlation between the price return of leading cryptocurrencies, including Bitcoin, Ethereum, Ripple, Litecoin, Monero…

Abstract

Purpose

The purpose of this study is to investigate the correlation between the price return of leading cryptocurrencies, including Bitcoin, Ethereum, Ripple, Litecoin, Monero, Stellar, Peercoin and Dash, and stock return of technology companies' indices that mainly operate on the blockchain platform and provide financial services, including alternative finance, democratized banking, future payments and digital communities.

Design/methodology/approach

This study employs a Bayesian asymmetric dynamic conditional correlation multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (BADCC-MGARCH) model with skewness and heavy tails on daily sample ranging from August 11, 2015, to February 10, 2020, to investigate the dynamic correlation between price return of several cryptocurrencies and stock return of the technology companies' indices that mainly operate on the blockchain platform. Data are collected from multiple sources. For parameter estimation and model comparison, the Markov chain Monte Carlo (MCMC) algorithm is employed. Besides, based on the expected Akaike information criterion (EAIC), Bayesian information criterion (BIC), deviance information criterion (DIC) and weighted Deviance Information Criterion (wDIC), the skewed-multivariate Generalized Error Distribution (mvGED) is selected as an optimal distribution for errors. Finally, some other tests are carried out to check the robustness of the results.

Findings

The study results indicate that blockchain-based technology companies' indices' return and price return of cryptocurrencies are positively correlated for most of the sampling period. Besides, the return price of newly invented and more advanced cryptocurrencies with unique characteristics, including Monero, Ripple, Dash, Stellar and Peercoin, positively correlates with the return of stock indices of blockchain-based technology companies for more than 93% of sampling days. The results are also robust to various sensitivity analyses.

Research limitations/implications

The positive correlation between the price return of cryptocurrencies and the return of stock indices of blockchain-based technology companies can be due to the investors' sentiments toward blockchain technology as both cryptocurrencies and these companies are based on blockchain technology. It could also be due to the applicability of cryptocurrencies for these companies, as the price return of more advanced and capable cryptocurrencies with unique features has a positive correlation with the return of stock indices of blockchain-based technology companies for more days compared to the other cryptocurrencies, like Bitcoin, Litecoin and Ethereum, that may be regarded more as speculative assets.

Practical implications

The study results may show the positive role of cryptocurrencies in improving and developing technology companies that mainly operate on the blockchain platform and provide financial services and vice versa, suggesting that managers and regulators should pay more attention to the usefulness of cryptocurrencies and blockchains. This study also has important risk management and diversification implications for investors and companies investing in cryptocurrencies and these companies' stock. Besides, blockchain-based technology companies can add cryptocurrencies to their portfolio as hedgers or diversifiers based on their strategy.

Originality/value

This is the first study analyzing the connection between leading cryptocurrencies and technology companies that mainly operate on the blockchain platform and provide financial services by employing the Bayesian ssymmetric DCC-MGARCH model. The results also have important implications for investors, companies, regulators and researchers for future studies.

Details

Journal of Enterprise Information Management, vol. 34 no. 5
Type: Research Article
ISSN: 1741-0398

Keywords

Content available
Article
Publication date: 28 July 2021

Emna Mnif and Anis Jarboui

After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the stock markets leading to a…

Abstract

Purpose

After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the stock markets leading to a misunderstanding on the cryptocurrency market response. This paper aims to evaluate the effects of the Federal Reserve monetary policy on the Islamic and conventional cryptocurrency dynamics during the COVID-19 pandemic. We, specifically, examine the associate bubbles and feedbacks effects.

Design/methodology/approach

This paper developed a novel methodology that detects market bubbles using the statistical indicators defined by Psychological (PSY) tests. It also investigated the effect of the Federal Open Market Committee (FOMC) announcements on conventional and Islamic cryptocurrencies compatible with Islamic laws “Shari’ah” by using the event-driven regression.

Findings

The empirical results show that the FOMC announcements have a positive significant effect after one day of the event and a negative effect before two days of the announcement on the conventional cryptocurrency markets. However, the reaction of Islamic cryptocurrencies to these events is not significant except for Hello Gold after one day of the announcement. Besides, the Hello Gold and X8X cryptocurrencies present no bubbles during this period. However, Bitcoin and Ethereum markets have short-lived bubbles.

Research limitations/implications

The main contribution of this study is the investigation of the response and vulnerability to pandemic shocks of a new category of cryptocurrencies backed by tangible assets. This work has practical implications as it provides new insights into trading opportunities and market reactions.

Originality/value

To our knowledge, this work is the first study that compares the response of Islamic and conventional cryptocurrency markets to FOMC announcements during the COVID-19 pandemic and examines the presence of bubbles in these markets. Besides, the originality of this work is derived from the novelty of the data employed and the method used (PSY tests) in this study.

Details

Asian Journal of Accounting Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2443-4175

Keywords

1 – 10 of over 1000