Bitcoin as a new asset class

2019 ◽  
Vol 27 (1) ◽  
pp. 147-168 ◽  
Author(s):  
Asheer Jaywant Ram
Keyword(s):  
Developed Country ◽  
Content Type ◽  
Asset Class ◽  
Prior Literature ◽  
Economic Profile ◽  
Asset Classes ◽  
Sharpe Ratios ◽  
Market Capitalisation ◽  
Class Nature ◽  
Alternative Investment

Purpose Bitcoin is the best-known cryptocurrency which currently holds the largest market capitalisation and is regarded as a standard example of a cryptocurrency. There is, however, no consensus as to the nature of the Bitcoin. The purpose of this paper is to determine whether Bitcoin represents a new asset class by building on prior research. Design/methodology/approach The prior literature on asset classes is explored in detail and then applied to the Bitcoin. Four key criteria of asset classes are discussed, namely, investability, politico-economic profile, correlation of returns and risk-reward profile. Statistical techniques are used to inform the conclusions for the third and fourth criteria. Findings This research finds that the Bitcoin represents a distinct alternative investment and asset class. There are significant opportunities for investment. The politico-economic profile of the decentralised and consensus-based Bitcoin is dissimilar to other asset classes. The Bitcoin shares little or no correlation with other asset classes. Using Sharpe Ratios, it is shown that the Bitcoin provides risk-adjusted returns over and above most asset classes. Research limitations/implications The aim of this research is to present a normative exploration into the asset class nature of the Bitcoin and, as a result, the aim is not to create positivist generalisable conclusions. This paper does not address cryptocurrencies, other than Bitcoin and does not constitute a detailed manual on modern portfolio theory. Originality/value This research adds to finance paradigm research on the Bitcoin by including a developing country perspective on Bitcoin as an asset class as prior studies have concentrated on developed country settings. Further, this research introduces recent economic data (2014 to 2017) in the form of daily observations to enhance prior understanding. It is important to understand if the Bitcoin represents an alternative investment and new asset class as this may affect investment decisions.

Mainstream interest in cryptocurrencies has momentum

2017 ◽  
Keyword(s):  
Venture Capital ◽  
Capital Investment ◽  
Storage Space ◽  
Computing Power ◽  
Content Type ◽  
Venture Capital Investment ◽  
Asset Class ◽  
Market Capitalisation ◽  
Initial Coin Offerings ◽  
Digital Assets

Subject Cryptocurrencies outlook Significance The market capitalisation of cryptocurrencies has increased tenfold from a year ago to more than 120 billion dollars. A bitcoin, at par with an ounce of gold as recently as May, now costs nearly three times as much. This year capital raisings from Initial Coin Offerings have significantly surpassed venture capital investment into blockchain-based technologies. Impacts New cryptocurrencies will be blockchain-based cryptographic tokens that represent digital assets such as storage space or computing power. Cryptocurrencies will become their own asset class as values rise across the board with little correlation to other assets. Bitcoin will continue to undergo the transformation necessary for it to retain its dominance, which is reducing. Cryptocurrencies and Initial Coin Offerings will test the limits of existing laws and regulations.

Emerging Market Sovereign Debts as a Means for Profit Maximization and Portfolio Diversification

2016 ◽  
pp. 334-354
Author(s):  
Abdurahman Jemal Yesuf
Keyword(s):  
Emerging Markets ◽  
Emerging Market ◽  
Descriptive Analysis ◽  
Secondary Data ◽  
Portfolio Diversification ◽  
For Profit ◽  
Asset Class ◽  
Asset Classes ◽  
International Investors ◽  
Sharpe Ratios

The case for emerging markets debts (EMD) has convinced many investors. This is an asset class that has been experiencing an increase in inflows and is getting international investors attention. During the past two decades, cross-border inflows into ‘emerging market' debt instruments have rose rapidly. Over twelve trillion dollar is currently invested in ‘Emerging Markets' debt. This asset classes has delivered strong returns over time and deserves consideration. Therefore, this paper is intended to show how and why Emerging Market debts are vital instrument in portfolio diversification by using descriptive analysis. The performance assessment has made by noting the unique statistical attributes of ‘emerging market' bond returns, such as their correlation with other asset classes and also by taking their annualized volatility rate and Sharpe ratios. The assessment has done based on compiled data from known sources such as JP Morgan, Bloomberg and other well known secondary data sources.

Integrated thinking, earnings manipulation and value creation: Malaysian empirical evidence

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nor Farizal Mohammed ◽  
Nor Aqilah Sutainim ◽  
Md. Shafiqul Islam ◽  
Norhayati Mohamed
Keyword(s):  
Empirical Evidence ◽  
Value Creation ◽  
Earnings Manipulation ◽  
Fraud Triangle ◽  
Integrated Reporting ◽  
Content Type ◽  
Prior Literature ◽  
Triangle Theory ◽  
Market Capitalisation ◽  
The Relationship

PurposePrior literature proposes that integrated reporting (IR) drives integrated thinking (IT), enabling an organisation to create value for stakeholders in both quantitative (economic performance) and qualitative manners (beyond financially-oriented information). Fraud triangle theory also predicts that earnings manipulation may also affect the creation of value. Thus, this study seeks to provide empirical evidence on the relationship between IT, earnings manipulation and value creation.Design/methodology/approachThis data sample comprises of 497 observations from 2014 to 2018 of the top 100 market capitalisation of Malaysian public listed companies (PLCs) in Bursa Malaysia. This study used an index score for IT variable and Beneish’s M-score as a proxy to detect earnings manipulations and to classify the companies into non-manipulators and manipulator companies. Value creation measurements consist of four variables under shareholder's value creation and one variable represents value creation through innovation.FindingsThe findings show that IT is significantly related to value creation, whereas earnings manipulation had no significant relationship with value creation except for value creation measured using Tobin's Q ratio. The alarming finding is that a fraud predictor, namely earning manipulation, measured by Beneish-M, is not a predictor of whether companies are creating better or less value.Originality/valueThis study is among the early literature that provides empirical evidence of the relationship between IT and value creation. Furthermore, this paper adds to look at the association of earning manipulation and value creation.

Emerging Market Sovereign Debts as a Means for Profit Maximization and Portfolio Diversification

2017 ◽  
pp. 2278-2298
Author(s):  
Abdurahman Jemal Yesuf
Keyword(s):  
Emerging Markets ◽  
Emerging Market ◽  
Descriptive Analysis ◽  
Secondary Data ◽  
Portfolio Diversification ◽  
For Profit ◽  
Asset Class ◽  
Asset Classes ◽  
International Investors ◽  
Sharpe Ratios

The case for emerging markets debts (EMD) has convinced many investors. This is an asset class that has been experiencing an increase in inflows and is getting international investors attention. During the past two decades, cross-border inflows into ‘emerging market' debt instruments have rose rapidly. Over twelve trillion dollar is currently invested in ‘Emerging Markets' debt. This asset classes has delivered strong returns over time and deserves consideration. Therefore, this paper is intended to show how and why Emerging Market debts are vital instrument in portfolio diversification by using descriptive analysis. The performance assessment has made by noting the unique statistical attributes of ‘emerging market' bond returns, such as their correlation with other asset classes and also by taking their annualized volatility rate and Sharpe ratios. The assessment has done based on compiled data from known sources such as JP Morgan, Bloomberg and other well known secondary data sources.

A global investment opportunity in non-listed infrastructure for institutional investors

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Jufri Marzuki ◽  
Graeme Newell
Keyword(s):  
Institutional Investors ◽  
Investment Strategy ◽  
The Other ◽  
Portfolio Diversification ◽  
Content Type ◽  
Trade Offs ◽  
Smoothing Effects ◽  
Asset Class ◽  
Asset Classes

PurposeInfrastructure investment is one of the few high-calibre real alternative assets with a strong prominence in the portfolios of institutional investors, especially those with a liability-driven investment strategy. This has seen increased institutional investor interest in infrastructure for reasons such as diversification benefits and inflation hedging abilities, resulting in the substantial growth in non-listed and listed investment products offering access to the infrastructure asset class, and complementing the existing route via direct investment. This paper aims to assess the investment attributes of non-listed infrastructure over Q3:2008–Q2:2019, compared with other global listed assets of infrastructure, property, stocks and bonds.Design/methodology/approachQuarterly total returns were derived from the valuation-based MSCI global non-listed quarterly infrastructure asset index over Q2:2008–Q:2019, which were then filtered to decrease the valuation smoothing effects. A similar set of returns data was also collected for the other global asset classes. The average annual return, annual risk, risk-adjusted performance and portfolio diversification benefits for non-listed infrastructure and other asset investment classes were then computed and compared. Lastly, a constrained optimal asset allocation analysis was performed to validate the performance enhancement role of global non-listed infrastructure in a mixed-asset investment framework.FindingsGlobal non-listed infrastructure delivered the strongest average annual total return performance, outperforming the other asset classes and provided investors with total returns that linked strongly with inflation. Global non-listed infrastructure also provided investors with one of the least volatile investment returns because of its ability to ensure predictable total returns delivery. This means that on the Sharpe ratio risk-adjusted return basis, non-listed infrastructure was also the strongest performing asset. This performance was also delivered with significant portfolio diversification benefits with all assets, resulting in non-listed infrastructure contributing to the mixed-asset portfolios across the entire portfolio risk spectrum.Practical implicationsAside from better risk-return trade-offs, institutional investors are getting more secular with their portfolios for alternative assets that are able to provide other investment benefits such as predictable long-term performance and inflation-linked returns. A further improvement in performance and diversification benefits could be achieved by enriching existing investment portfolios with real alternative assets, one of which is the infrastructure asset class. For institutional investors, having exposure to and being part of the development, delivery and management of infrastructure assets are important, as they are one of the few real assets having considerable significance in the context of society, economy and investment needs.Originality/valueThis is the first research paper that empirically investigates the investment attributes of the non-listed infrastructure at a global level. This research enables empirically validated, more informed and practical decision-making by institutional investors in the infrastructure asset class, especially via the non-listed pathway. The ultimate aim of this paper is to empirically validate the strategic role of non-listed infrastructure as an important alternative asset in the institutional real asset investment space, as well as in the overall portfolio context.

scholarly journals Cryptocurrencies: applications and investment opportunities

2019 ◽  
Vol 3 (2) ◽  
pp. 98-112 ◽  
Author(s):  
A. Can Inci ◽  
Rachel Lagasse
Keyword(s):  
Optimization Technique ◽  
Optimal Portfolio ◽  
Complete Analysis ◽  
Sample Period ◽  
Optimal Portfolios ◽  
Content Type ◽  
Investment Opportunities ◽  
Asset Class ◽  
Asset Classes

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.

scholarly journals The determinants of securities trading activity: evidence from four European equity markets

2019 ◽  
Vol 3 (1) ◽  
pp. 47-67
Author(s):  
Silvio John Camilleri ◽  
Francelle Galea
Keyword(s):  
Empirical Evidence ◽  
Generation Process ◽  
Trading Activity ◽  
Cross Sectional ◽  
Content Type ◽  
Listed Firms ◽  
Rigorous Approach ◽  
Prior Literature ◽  
Market Capitalisation ◽  
Securities Trading

Purpose The purpose of this paper is to obtain new empirical evidence about the connections between equity trading activity and five possible liquidity determinants: market capitalisation, dividend yield, earnings yield, company growth and the distinction between recently listed firms as opposed to more established ones. Design/methodology/approach The authors use a sample of 172 stocks from four European markets and estimate models using the entire sample data and different sub-samples to check the relative importance of the above determinants. The authors also conduct a factor analysis to re-classify the variables into a more succinct framework. Findings The evidence suggests that market capitalisation is the most important trading activity determinant, and the number of years listed ranks thereafter. Research limitations/implications The positive relation between trading activity and market capitalisation is in line with prior literature, while the findings relating to the other determinants offer further empirical evidence which is a worthy addition in view of the contradictory results in prior research. Practical implications This study is of relevance to practitioners who would like to understand the cross-sectional variation in stock liquidity at a more detailed level. Originality/value The originality of the paper rests on two important grounds: the authors focus on trading turnover rather than on other liquidity proxies, since the former is accepted as an important determinant of the liquidity-generation process, and the authors adopt a rigorous approach towards checking the robustness of the results by considering various sub-sample configurations.

Evolution of REITs in the Nigerian real estate market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Ibrahim Dabara
Keyword(s):  
Real Estate ◽  
Investment Decisions ◽  
Real Estate Market ◽  
Individual Investors ◽  
Government Bonds ◽  
Content Type ◽  
Holding Period ◽  
Sharpe Ratios ◽  
Market Capitalisation ◽  
Property Markets

PurposeThis study aims to examine the performance of real estate investment trusts (REITs) in emerging property markets. The paper used the Nigerian REIT (N-REIT) as a case study of an African REIT market, to provide information for investment decisions.Design/methodology/approachSeven years quarterly returns data (from 2013 to 2019) were obtained and used to analyse the holding period returns, return–risk ratio, coefficient of variation and Sharpe ratios of N-REIT, All Share Index of stocks (ASI) and the Federal Government Bonds (FGB) in Nigeria.FindingsThe study reveals that N-REIT outperformed stocks but underperformed bonds. Concerning risk, stocks provided the highest level of risk (7.69), followed by bonds (2.78), while N-REIT provided the lowest risk (2.7). The Sharpe ratios showed that N-REIT is the second-best performing asset, while bond is the first and stocks the last on the risk-adjusted basis.Practical implicationsN-REIT is the second-largest REIT market in Africa with a market capitalisation of about US$136m. The N-REIT market has provided investment benefits to institutional and individual investors such as liquidity, transparency and ease of transaction. This study shows the peculiarity of N-REITs; this can guide investors in making informed investment decisions.Originality/valueThis study is one of the first to empirically analyse in a comparative context, the risk-adjusted performance of N-REITs, ASI and FGB. The study will add to the limited research in this field and equip investors with valuable information for informed investment decisions.

Football stocks: a new asset class attractive to institutional investors? Empirical results and impulses for researching investor motivations beyond return

2020 ◽  
Vol 10 (4) ◽  
pp. 471-494 ◽  
Author(s):  
Stefan Prigge ◽  
Lars Tegtmeier
Keyword(s):  
Statistical Significance ◽  
Efficient Frontier ◽  
Content Type ◽  
Market Participants ◽  
Risk Return ◽  
Low Correlation ◽  
Football Clubs ◽  
Investment Opportunity Set ◽  
Asset Class ◽  
Sharpe Ratios

PurposeThe aims of the research are twofold: (1) exploring whether football club stocks can be considered an asset class of their own; (2) investigating whether football stocks enable well-diversified investors to achieve more efficient risk-return combinations.Design/methodology/approachUsing efficient frontier optimization, a base portfolio, with standard stocks and bonds, and a corresponding enhanced portfolio, which includes football stocks in the investment opportunity set, are defined. This procedure is applied to four portfolio composition rules. Pairwise comparisons of portfolio Sharpe ratios include a test for statistical significance.FindingsThe results indicate a low correlation of football stocks and standard stocks; thus, football stocks could be considered an asset class of their own. Nevertheless, the addition of football stocks to a well-diversified portfolio does not improve its risk-return efficiency because the weak performance of football stocks eliminates their advantage of low correlation.Research limitations/implicationsThis study contributes to the evidence that investments in football are different from ‘ordinary’ investments and need further research, particularly into market participants and their investment motives.Practical implicationsFootball stocks are not attractive to pure financial investors. Thus, football clubs need to know more about which side benefits are appreciated by which kind of investor and how much it costs to produce these side benefits.Originality/valueTo the best of authors’ knowledge, this is the first study to analyse the risk-return efficiency of football stocks from the perspective of a pure financial investor, i.e. an investor in football stocks who does not earn side benefits, such as strategic investors or fan investors.

Index correlation: implications for asset allocation

2015 ◽  
Vol 41 (11) ◽  
pp. 1236-1256
Author(s):  
Allen Michel ◽  
Jacob Oded ◽  
Israel Shaked
Keyword(s):  
Standard Deviation ◽  
Asset Allocation ◽  
Market Performance ◽  
Portfolio Risk ◽  
Market Returns ◽  
Content Type ◽  
Shape Distribution ◽  
Asset Class ◽  
Asset Classes ◽  
Equity Indices

Purpose – The cornerstone of Modern Portfolio Theory with implications for many aspects of corporate finance is that reduced correlation among assets and reduced standard deviation are key elements in portfolio risk reduction. The purpose of this paper is to analyze the conditional correlation and standard deviation of a broad set of indices with the S & P 500 conditioned on market performance. Design/methodology/approach – The authors examined volatility and correlation for a set of indices for a 19-year period based on weekly data from July 2, 1993 to June 30, 2012. These included the NASDAQ, MSCI EAFE, Russell 1000, Russell 2000, Russell 3000, Russell 1000 Growth, Russell 1000 Value, Gold, MSCI EM and Dow Jones UBS Commodity. The data for the Wilshire US REIT, Barclays Multiverse, Multiverse 1-3, Multiverse 3-5 and Multiverse 10+ became available starting July 2, 2002. For these indices the authors used weekly data from July 1, 2002 through June 30, 2012. For the iBarclays TIPS, the authors used weekly data from the time of availability, namely, for the period December 12, 2003 through June 29, 2012. Findings – The findings demonstrate that both the conditional correlations and standard deviations vary as a function of market performance. Moreover, the authors obtain a U-shape distribution of correlations conditioned on market performance for equity indices, such as NASDAQ, as well as for the Wilshire REIT. Namely, correlations tend to be high when market returns are at low or high extremes. For more typical market performance, correlations tend to be low. A modified U-shape is found for bond indices and the Dow Jones UBS Commodity Index. Interestingly, the correlation between gold and the S & P 500 is unrelated to the return on the S & P. Originality/value – While it has been observed that asset classes move together, this paper is the first to systematically analyze the nature of these asset class correlations.

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