The approval by regulatory organizations and community decision to de-list ETH from the list of altcoins may also affect its price growth in The NEO project is often included in different cryptocurrency investment ratings for the next year.
This cryptocurrency breaks many stereotypes, including being the first open-source token originated from China. It claims to transform the traditional financial system by combining digital and real assets. Its unique Superconduct trading mechanism allows users to trust the funds through a decentralized platform.
Chinese experts, according to CoinTelegraph , really like to include EOS to the list of the most promising cryptocurrencies for the next few years. The EOS system is free of Ethereum problems with scalability and it is ready to replace other competitive blockchains. EOS achievements become possible thanks to the consensus algorithm of delegated proof of ownership DPoS and an infinite number of similar blockchains.
The successful partnership with major financial market players made the Ripple ecosystem a breakthrough in the crypto industry. Take the latest integration with Western Union and the potential replacement of SWIFT to accelerate and reduce the cost of large money transfers between counterparties. However, do not expect huge profits with XRP in , it is good for long-term investment. Even with the most optimistic approach, XRP price is unlikely to rise above 0.
Besides the obvious choices of popular cryptocurrencies, one of AMarkets experts — Basil Gamov — recommends to take a closer look at cheap but potentially great cryptocurrencies to invest in the next 12 months:. These crypto coins developed a technology that forms channels between different data providers employing smart blockchain technology.
Chainlink allows all network operators, like information providers, to earn their token LINK. From an investment point of view, Chainlink has great potential. It is used only in the Brave browser. The cryptocurrency was launched in Developers offer a various concept of interaction for all network participants. The token has a very active and massive affiliate program, has the support of the Tor browser and DuckDuckGo search engine.
It helps to create synthetic assets Synths for tracking the value of physical assets. People can create and support their Synths and make money with them, without actually being the owners of these assets. The token appeared in and back then it was called Havven. Sure, you are free to pick any cryptocurrency to invest in Remember to diversify and work with reliable exchange services and brokers to protect your investment deals from any fraud.
Make sure to include crypto coins into your asset portfolio as soon as possible while top currencies like Bitcoin and Ethereum are still hot for investment. This article was originally posted on FX Empire. Gold Daily News: Monday, February 3. Markets in Search for the Bottom.
The change to the tax code could allow millions of working families to save thousands on their taxes, but only if they are savvy about how they file this year. The Buffett Indicator has gone haywire of late. The talk has turned to rising interest rates and the specter of inflation against the backdrop of growth powered by Covid fiscal stimulus. According to Goldman Sachs equity strategist, Ryan Hammond, the stock market bull may stick with us for a while.
Hammond notes that interest rates remain low, and sees this as the key factor. With rates and inflation low, this makes the stock market the go-to place for investors seeking higher returns. And within the stock market, penny stocks are sure to attract attention. The former brings a valid argument to the table. As for the latter, the potential for an investment worth only pocket change to appreciate even a seemingly insignificant amount, the result of which could be massive percentage gains, is too enticing to ignore.
The implication for investors? Due diligence is essential, as some penny stocks might not have what it takes to climb their way back up. Checkpoint acquires, develops, and commercializes immune-enhanced combination treatments for solid tumor cancers. Checkpoint has two leading drug candidates, CK and CK The drug has shown promise compared to traditional chemotherapy treatments. Further studies will test CK against tumor progression due to resistance mutations.
The second candidate, CK, is an antibody drug currently in a Phase 1 clinical trial focused on patients with selected recurrent or metastatic cancers. The selected cancers include NSCLC, as well as metastatic melanoma, renal cell carcinoma, head and neck cancer, and urothelial carcinoma. Based on these results, the company is continuing its clinical phase program, including an early registration of patients for a Phase 3 study.
We view this as the key near term focus for CKPT. We expect a positive readout based on what we have viewed as strong interim data that have recently been presented for cosibelimab SITC , ESMO NASH is a fatty liver disease, closely correlated to obesity, for which there are currently no targeted drugs available. Whoever brings a solution into play stands to cash in handsomely.
Aramchol has completed Phase 2a and Phase 2b trials and is currently in Phase 3. Raymond James analyst Steven Seedhouse thinks the company has been playing its cards right. Disclaimer: The opinions expressed in this article are solely those of the featured analysts.
The content is intended to be used for informational purposes only. It is very important to do your own analysis before making any investment. Marijuana stocks rose a bit after hours on the Aurora Cannabis earnings report. Tilray led Thursday's sell-off following a huge run on U.
Congress is keeping the same stimulus check formula, though that could change. The Canadian cannabis sector has a long history of companies shifting from product segments to only rush straight into another competitive segment without any margin power in an oversupplied market.
The management team clearly thought the lower stock prices warranted a good price to sell shares. Investors should cash out before the stock falls like GameStop previously. The view from the Street is hardly any rosier. Disclaimer: The information contained herein is for informational purposes only. Nothing in this article should be taken as a solicitation to purchase or sell securities.
Recent action in marijuana stocks involving Reddit traders makes it hard to predict day-to-day moves, especially with the more-liquid Canadian growers. Marijuana stocks have moved higher as hopes increase for wider U. Are any pot stocks good buys? Virgin Galactic could redo a test flight of its SpaceShipTwo as early as Saturday, a key step needed before commercial flights can start.
Buying a stock is easy, but purchasing the right stock without a proven strategy is incredibly hard. Here are the best Robinhood stocks to buy now. Sun founded blockchain business Tron in and has since expanded into other decentralization technologies and platforms such as BitTorrent Inc. Sun said he advised Buffett to buy Bitcoin and Tesla when he dined with him last year.
DLive, the live-streaming platform that was bought by BitTorrent late last year, has also come under scrutiny from American lawmakers for its role in broadcasting the U. Capitol riots. Sun declined to comment on the controversies. For more articles like this, please visit us at bloomberg. Shell's plan to roll out , electric charging stations in just four years is the latest sign of an EV charging infrastructure boom that has prompted investors to pour cash into the industry and inspired a few companies to become public companies in search of the capital needed to meet demand.
Since the beginning of the year, three companies have been acquired by special purpose acquisition vehicles and are on a path to go public, while a third has raised tens of millions from some of the biggest names in private equity investing for its own path to commercial viability. Bloomberg -- Stefan Qin was just 19 when he claimed to have the secret to cryptocurrency trading.
Buoyed with youthful confidence, Qin, a self-proclaimed math prodigy from Australia, dropped out of college in to start a hedge fund in New York he called Virgil Capital. He told potential clients he had developed an algorithm called Tenjin to monitor cryptocurrency exchanges around the world to seize on price fluctuations.
Last week, Qin, now 24 and expressing remorse, pleaded guilty in federal court in Manhattan to a single count of securities fraud. District Judge Valerie E. Caproni, who could sentence him to more than 15 years in prison. I am profoundly sorry for the harm my selfish behavior has caused to my investors who trusted in me, my employees and my family. Ponzi schemes like that show how investors eager to cash in on a hot market can easily be led astray by promises of large returns.
We can see the exponential increase in the Bitcoin value and the dramatic decline during the cryptocurrency crash of January In the Nakamoto manifesto outlining the idea of Bitcoin and blockchain, a low-cost secure payment system has been proposed that does not involve a central authority or trusted third party. As explained further in Velde , Bitcoin is not a claim to a physical object or to a currency; rather, it aims to be a currency itself to replace the usual physical object of a currency with a computer file.
Bitcoin and other cryptocurrencies use the blockchain network but they differ in from each other terms in terms of the difficulty in mining the specific currency. Bitcoin has a specific hash rate of verifying transactions, a certain number of miners and a goal of six blocks to be created per hour for an average transaction speed of ten minutes , making it organically fit the blockchain network. Overall, Bitcoin has been primarily utilized as a means to transfer funds within the blockchain environment, but also as a speculative investment opportunity given that the cryptocurrency derives its value from exchange.
Second in the market capitalization in the cryptocurrency market is Ethereum, created in Ether, the digital coin of Ethereum, is rival to Bitcoin due to the promise of the technology it is built in. Instead of being used as a digital currency, or an alternative to fiat money, Ethereum has been built for smart contracts and for decentralized applications. Smart contracts are agreements in the blockchain network that function like software programs that can bind obligations based on predetermined conditions.
The Ethereum network has the potential to host numerous functions such as social networks, public utility applications, crowd-sourced prediction markets and investment companies. The third cryptocurrency in market capitalization is Ripple, created in with the primary purpose of helping banks transfer cash faster and cheaper, especially internationally. Traditional methods of cross-border payments are slow, of low value, of high volume and have high transaction costs. Ripple is primarily meant to be used as a currency translation tool, and to be a catalyst, setting it apart from other cryptocurrencies.
The fourth popular cryptocurrency is Litecoin, created in , mainly as an alternative and as an improvement to Bitcoin with faster settlement times for transactions and with lower fees. Litecoin is used for the same purpose like Bitcoin as a method of payment and as an exchange of funds but with better performance for micropayments.
There are studies that look into the effects of using Bitcoin to diversify an investment portfolio, such as Wu and Pandey , Klabbers and Andrianto and Diputra These studies primarily focus only on Bitcoin. Using dated and limited sample periods from to in Wu and Pandey , from to in Andrianto and Diputra and from to in Klabbers , the usefulness of Bitcoin as an investment asset in enhancing the efficiency of an investment portfolio were documented.
Lack of sufficient information and the novelty of cryptocurrencies lead to discomfort in the opinions of different investors and financial experts in using Bitcoin and other cryptocurrencies in an investment portfolio Burgess, Burgess documents one expert recommending allocations of no more than 2 percent of a portfolio to Bitcoin due to high-volatility, and not recommending for anyone nearing retirement.
Investors generally consider cryptocurrencies as high risk investments and tend to keep some in the portfolio only as an insurance policy: in order to settle ransomware attacks with these cryptocurrencies. The academic studies mentioned above demonstrate the usefulness of Bitcoin in portfolio efficiency; however, the attitude of investors in general has been lukewarm. To reconcile these contrasting views, we use a more recent and longer sample period ranging from August through January Furthermore, we use multiple cryptocurrencies and broad traditional asset classes.
We document the dynamic nature of the contribution of cryptocurrencies in a portfolio. We demonstrate that all cryptocurrencies contribute to an efficient portfolio, regardless of the type of cryptocurrency. Our results emphasize the evolving dynamics of return-risk characteristics, while Bitcoin and Ripple held larger positions in optimal portfolios, Litecoin has taken over in recent years, especially after the cryptocurrency crash of January Briere et al.
Over the period of the analysis, Bitcoin had an exceptionally high average return and volatility, and correlation with other assets was low, proving that it had high diversification benefits. However, the conclusion made clear that these results should be looked at cautiously, as the data in this study reflected the early-stage behavior of Bitcoin and might not appropriately represent the performance of the portfolio in the long or even medium run.
Overall, there have been some studies conducted on the effect of Bitcoin in enhancing portfolio diversification. But these studies focus only on Bitcoin and not on a combination of other cryptocurrencies; are mostly outdated; and use short sample periods with a short-term outlook, not taking into account the long-term volatility effects nor the possibility of increased regulation.
Along the lines of portfolio diversification with more than one cryptocurrency, Brauneis and Mestel focus on a portfolio made up of only cryptocurrencies and they present evidence of substantial risk reduction. In an attempt to address and quantify the portfolio effects in the cryptocurrency investment universe, they rely on the traditional mean-variance framework as proposed by Markowitz There is a considerable body of literature that proposes alternatives to the mean-variance optimization when returns are not normal.
However, seminal papers such as Levy and Markowitz and Kroll et al. In this study, we follow the same principles laid out in Brauneis and Mestel and provide preliminary evidence on the portfolio effects of multiple cryptocurrency investments. However, our portfolio structure, unlike theirs, is more flexible and general: we examine the most important cryptocurrencies, but we include them in a portfolio of traditional asset classes: equity, bond, real estate and volatility, mainly considering a US based investor equity is represented by the US stock market , who is somewhat sophisticated with a derivatives proxy based on volatility index.
We examine this overall portfolio through the mean-variance framework. Anyfantaki et al. Their empirical analysis covers a two-year period from mid to mid, which is significantly shorter than ours, but provides similar evidence of diversification benefits of cryptocurrencies both in- and out-of-sample.
Klein et al. They find that Bitcoin exhibits very different properties with respect to gold in that, while gold is useful during down times, Bitcoin is hardly helpful during those same periods. Limited number of previous studies finds that in the short-term investment horizon, cryptocurrencies may offer diversification benefits.
For example, Corbet et al. Results from the Corbet et al. Therefore, cryptocurrencies do present diversification benefits as they are disconnected from the general financial markets. However, the cryptocurrency market contains its own idiosyncratic risks that are not easy to hedge against. The Corbet et al. In our study, we focus on the optimal portfolio characteristics with cryptocurrencies as part of portfolios.
Elendner et al. They examine numerous portfolios of cryptocurrencies, as well as the cryptocurrency index, CRIX and evaluate the performance of these portfolios. They also consider equally weighted and value-weighted broad portfolios made up of cryptocurrencies and traditional assets. They provide evidence of diversification benefits of cryptocurrencies because of their limited co-movements with traditional financial securities. However, the optimal portfolio construction is not part of the Elendner et al.
Focusing on ten major cryptocurrencies, Liu examines the role of diversification amongst cryptocurrencies. Evaluation of the out-of-sample performance of this cryptocurrency-only investment spectrum shows that portfolio diversification across different cryptocurrencies is beneficial, implying that each cryptocurrency has unique characteristics.
Borri examines contagion and flight-to-quality characteristics of cryptocurrencies amongst themselves focusing on the tail-risk events and provides evidence that cryptocurrency portfolios offer better risk-adjusted and conditional returns than individual cryptocurrencies. On the other hand, Bouri et al.
This paper aims to answer should, and if yes how, cryptocurrencies can be used to diversify an investment portfolio. Additionally, we ask how cryptocurrencies correlate with each other and with other asset classes, and how cryptocurrencies rank as individual investments, taking both risk and return properties into account.
In the portfolio optimization framework, we follow the mean-variance optimization technique outlined in Kroll et al. The Kroll et al. They conclude under standard portfolio constraint sets faced by a wide variety of professional and individual investors that the mean-variance portfolio estimation is a good procedure to determine the optimal portfolio for investment purposes.
We follow the portfolio optimization methods based on the Merton proposition involving envelope portfolios Merton, This method finds the optimal weights of each asset class on the tangent portfolio of the efficient frontier. Using the average daily returns and the variance-covariance characteristics of the financial assets through linear algebra and matrix operations, the optimal weights are assigned to each asset in the portfolio to establish the most efficient portfolio possible.
We also conjecture that amongst themselves, cryptocurrencies have been quite different; therefore, all three that we examine in this paper would have contributions to the optimal portfolio. Daily price data for seven different asset classes are used in the analyses. We consider cryptocurrencies as financial securities for investment portfolios.
For the three cryptocurrencies, the data are obtained from Coin Metrics. The price data for the other four asset classes are collected from FactSet. We focus on Bitcoin, Ripple and Litecoin because they have been in existence the longest. Our sample period with daily frequency is from August 5, through January 17, , covering the majority of s. It should be noted that Ethereum was not used in the study since, although it is a popular cryptocurrency, it came into existence quite recently in Once the price data on all the seven asset classes were collected from the two different sources, they were compiled into one cohesive data frame and incomplete information due to differences in the dates of the data for the cryptocurrencies was eliminated.
The particular portfolio optimization analysis involves linear algebra and matrix operations. Any constant c leads to an envelope frontier portfolio. The denominator of the right hand side of Equation 2 normalizes the numerator and makes sure that the optimal weights add up to 1.
The Merton proposition gives a specific method of finding the tangency portfolio, given c. In that specific optimization, the constant c is economically interpreted as the risk-free rate of return, r f. The variance-covariance matrix, S , represents the risk characteristics of the investment portfolio. It is defined as a diagonal and symmetric matrix, where the diagonal elements are variances of the individual financial securities, and the off-diagonal elements are the covariances between financial security pairs.
Hence, the formal name of the S is the variance-covariance matrix. The steps in this portfolio optimization procedure are: creation of the return vector where each element is the average of the daily returns of the financial securities in the portfolio;. Once the initial optimization was completed using all of the data collected, multiple other robustness analyses were conducted with different portfolios through the inclusion and exclusion of asset classes.
Further tests were also conducted by covering different sample periods. These tests and their results are discussed in the following section. The portfolio with the traditional asset classes in equity, fixed income, real estate, along with the volatility index representing derivatives market for sophisticated investors is further enhanced with the cryptocurrencies, Bitcoin, Ripple and Litecoin.
Table I presents the summary statistics of the return characteristics of these financial securities for the sample period covering August —January We see that the cryptocurrencies generate the highest daily average raw returns during the period of investigation. Ripple has the highest return, followed by Litecoin and Bitcoin. Volatility index average return is also high in fact, higher than the Bitcoin return.
Thus, we can say that during most of the s, traditional asset classes have generated lower returns than the popular cryptocurrencies. Examination of the volatilities of these investments also shows, however, that the cryptocurrencies have higher volatilities compared to those of other investment alternatives. In order to take into account the volatility of the assets as well as the returns, we focus on CV — the coefficient of variation, which is defined as the ratio of standard deviation of daily returns to the average of the returns.
The lower the CV, the better the investment, taking both risk and return into account. As we can see from Table I , the popular cryptocurrencies have the lowest CVs compared to the other asset classes during the s, indicating their superiority as investment alternatives.
The best cryptocurrency in this regards is Ripple, followed by Bitcoin and then by Litecoin. The remaining asset classes in terms of attractiveness are US equities, volatility index, bonds and real estate. Before moving on with the construction of the optimal portfolio, it is useful to get an overall view of the correlations between the financial securities during the s. Table II presents the correlation matrix, where the Pearson correlation coefficient for every asset pair is listed.
As one can observe from the correlation matrix, there are indeed benefits to forming portfolios during the investigation period. The low correlations within the asset pairs, the negative correlation values and the evidence of no relationship between equity returns and cryptocurrency returns are all indications of the advantages and the rational necessity of forming portfolios of these securities during the majority of the s period.
Volatility-based investment opportunities such as VIX based financial products naturally have high negative correlations with equity markets. As for cryptocurrency correlations between themselves, the highest positive correlations have been between Bitcoin and Litecoin. The results from the correlation table enable the construction of portfolios enhancing return and reducing risk, potentially at the same time. According to this conjecture, the CV of such portfolios should be lower than any of the individual asset classes examined in this paper during the same sample period.
To explore this conjecture, we follow the Merton approach and construct the optimal portfolio using these seven three popular cryptocurrencies, three traditional investments and one derivatives proxy investment alternatives. The optimal portfolio would be an efficient portfolio with as much profit and as little risk as possible. By taking into account the risk free rate during the sample period of the portfolio creation, the optimal portfolio would also be the tangent portfolio residing on a straight line starting from the risk free rate and is tangent to the efficient frontier according to portfolio theory.
The daily return of the optimal portfolio is 5. The volatility is Most importantly, the coefficient of variation is 6. Panel B provides the optimal weights of the portfolio as percentages. The optimal portfolio for the — sample period of the study for the s primarily includes stocks and bonds. Bitcoin and Ripple do have a part in the optimal portfolio with 2. Litecoin has a short position with a small negative weight. Given that Bitcoin and Ripple enhance the optimal portfolio in the s period with their positive weights, and Litecoin with a nonzero negative weight, we can conclude that the popular cryptocurrencies have had a role in portfolio construction and in investments, in addition to their original purposes for which they were created.
Finally, Panel C of Table III provides the variance-covariance matrix, which summarizes the risk features of the components of the optimal portfolio. The diagonal elements of the matrix are the variances of the individual components, while the off-diagonal elements the covariances between investment pairs. We also conducted some bootstrap analysis following the recommendation of an anonymous referee to determine the weights in an optimal portfolio for a fixed time horizon of business days.
By selecting the daily returns randomly, the cross-sectional covariance structure would be preserved, but we get a better picture of a possible return distribution. Our bootstrapping process has indeed emphasized the importance of the cryptocurrencies: the optimal weights are 5. The optimal portfolio in Table III contained all three popular cryptocurrencies investigated in this study.
While in the Table I discussion we have concluded that as a single investment, Ripple is the best cryptocurrency with its smallest CV, followed by Bitcoin and Litecoin, we now investigate how each cryptocurrency individually and separately contributes to the optimal portfolio. In Table IV , we create optimal portfolios with a single cryptocurrency as the fifth portfolio component in addition to the equity, fixed income, real estate and volatility index components. First, the optimal portfolio without any cryptocurrency is presented in Panel A.
In addition to the weights of the portfolio components, the return and the standard deviation are provided. Summarizing all, the CV of this portfolio is 7. Panel B depicts the results of the portfolio augmented with Bitcoin. The weight of Bitcoin in this optimal portfolio is 3. Panels C and D are for portfolios augmented with Ripple 1.
These portfolios have CVs of 6. Overall, we can conclude that adding a cryptocurrency has consistently helped the optimal portfolio to achieve a better return and risk combination summarized with a lower CV; Bitcoin has been the best cryptocurrency enhancing the characteristics of the portfolio because the optimal portfolio with Bitcoin has the lowest CV during the sample period; Litecoin has been the least useful cryptocurrency: the CV of the optimal portfolio is lower than the CV of the original no cryptocurrency portfolio, but higher than the CVs of the portfolios with the other cryptocurrencies.
Are the portfolio contributions of cryptocurrencies static or dynamic over time? To investigate this issue, we split the entire sample into two subsamples: the early subsample from August 4, through April 26, and the recent subsample from April 27, through January 17, We construct the optimal portfolio using the cryptocurrencies and the traditional assets for each subsample separately.
The results reported in Table V provide some interesting observations. The early subsample results in Panel A depict the attractiveness of all the cryptocurrencies. All three cryptocurrencies have positive weights in the optimal portfolio. Bitcoin has the largest weight, followed by Ripple and Litecoin. In the recent subsample, the contributions of the cryptocurrencies become more selective.
Bitcoin weight increases, Ripple weight stays positive, while Litecoin weight is negative in the optimal portfolio in Panel B. We see that the contributions of the cryptocurrencies to an optimal portfolio evolve over time, indicating the highly dynamic nature of these investments.
For further verification of the dynamic evolution of optimal weights and cryptocurrency, we split our sample period into three sub-samples early: August —May , middle: June —March , recent: April —January and executed the optimization process to get the optimal weights, return, risk and CV.
The Bitcoin weights change as 0. Moreover, using the optimal portfolio weights of the previous sub-sample for the next sub-sample generates a portfolio return of 3. All these out-of-sample analyses indicate the evolving and dynamic nature of the markets where the conclusions of this study provide a guideline into the future, but no guarantees. For robustness, we explore two different avenues.
In the optimal portfolio construction, it is natural for some securities to have negative weights, i. The short positions for these inferior securities would enable the portfolio to place heavier weight on more attractive securities. While short selling is an organic part of free and efficient markets, it is prohibited by regulators in some markets due to ethical benefiting from the decline of security prices may be frowned upon , psychological leading to herding behaviors of excessive selling , or other reasons.
In markets where short selling is not allowed, securities cannot have negative weights in portfolios. As the first robustness investigation, we explore optimal portfolios with this extra constraint of no short selling. Litecoin and Real Estate do not have any contribution to the portfolio and have zero weights, but Bitcoin and Ripple do have positive contributions to the optimal portfolio during the sample period.
As expected, with the extra no-short restriction, the CV of the portfolio is worse than that of the portfolio reported in Table III. Second, we examine the dynamic behavior of the optimal portfolio before and after the cryptocurrency crash. Throughout the beginning of , from January to the mid of February, all cryptocurrencies lost significant value.
This cryptocurrency crash, also known as the Bitcoin crash or the great crypto crash, was the sell-off of many cryptocurrencies during the month from January 6, to February 6, , during when the Bitcoin value fell by about 65 percent. Panel B of Table VI first reports the features of the optimal portfolio constructed during pre-crash period from August through December Consistent with Panel A of Table V , all the cryptocurrencies with their positive weights contribute to the formation of the optimal portfolio.
The period after the Bitcoin crash period of , March through January , has been of poor performance for equity markets and real estate markets. This is reflected to the negative weights of equity and real estate in the post-crisis portfolio. The largest weight goes to bonds. As for cryptocurrencies, both Bitcoin and Ripple have large negative weights, while Litecoin has a positive weight in the portfolio — while the then popular Bitcoin and Ripple lose confidence, the demand for the upcoming Litecoin increases.
The results in Panel B again indicate the dynamic and evolving characteristics of the cryptocurrency market. The crash has clearly led to reduction in the attractiveness of cryptocurrencies as investment alternatives; however, the dynamic characteristics of cryptocurrencies warrant their future demand in investment portfolios. In this study, we investigate popular cryptocurrencies as individual investment opportunities and as components of the construction of an optimal portfolio.
We examine three popular cryptocurrencies: Bitcoin, Ripple and Litecoin. As an independent single investment, Ripple has had the highest return, followed by Litecoin and Bitcoin during the sample period. Combining risk and return together, coefficient of variations reveal that the best cryptocurrency has been Ripple, followed by Bitcoin and then by Litecoin.
All these cryptocurrencies have been better than the traditional asset classes in the s for investment purposes. We examine the role of cryptocurrencies in an optimal portfolio. We document that adding a cryptocurrency has consistently helped the optimal portfolio achieve a better return-and-risk combination.
Bitcoin has been the best cryptocurrency in this regard, followed by Ripple and Litecoin. We report that the contribution of the cryptocurrencies to an optimal portfolio is dynamic and, therefore, evolves over time: when we split our entire sample into two subsamples, we find that all three cryptocurrencies have a positive role in the optimal portfolio in the early subsample.
In the recent subsample, the role of the cryptocurrencies is not unidirectional. The Bitcoin crash has led to reduction in the attractiveness of cryptocurrencies as investment alternatives but their dynamic characteristics warrant their future demand for investment portfolios.
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|Explore tips on betting||The Litecoin Foundation said that the launch of the game caused transactions to triple in less than a the best cryptocurrency to invest in research and more than three-quarters of those were from the game. Sun declined to comment the best cryptocurrency to invest in research the controversies. Those who do this are rewarded ether similar to an interest account. For starters, investing in crypto has always been a contentious topic - in the same way how there have always been people who support cryptocurrencies, there were also always those that opposed this topic, altogether. So if you find a coin that looks like an MLM scheme or a pyramid, get the hell out of there! As we can see from Table Ithe popular cryptocurrencies have the lowest CVs compared to the other asset classes during the s, indicating their superiority as investment alternatives.|
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