Namecoin vs bitcoin vs litecoin vs dogecoin
Those who forge ahead, uninformed, stand to learn an expensive lesson. We hope to illuminate certain fundamental concepts here. Cryptocurrencies are digital or virtual currencies, intended to be used as a form of payment similar to government-issued currency, that are encrypted secured using cryptography. Cryptography refers to the use of encryption techniques to secure and verify the cryptocurrency transactions. Bitcoin represents the first decentralized cryptocurrency, which is powered by a public ledger that records and validates all transactions chronologically; this public ledger is called the blockchain. Blockchain generally creates a pseudonymous ledger wherein the creation and each subsequent movement of cryptocurrency is recorded and verified through a decentralized network of computers all around the world.
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Content:
- Five alternatives to Bitcoin
- Stablecoins Vs Altcoins: Difference Between Stablecoins And Altcoins
- Bitcoins and other cryptocurrencies: everything you need to know
- Will Shiba Inu turn the numero uno meme coin despite Musk's cold shoulder?
- High Stakes, High Reward: The Rise of Cryptocurrency and Its Risks in Indonesia
- Mastering Bitcoin by
- What is Cryptocurrency and Does it Affect Cybersecurity?
Five alternatives to Bitcoin
Try out PMC Labs and tell us what you think. Learn More. This paper reviews the empirical literature on the highly popular phenomenon of herding behaviour in the markets of digital currencies. Furthermore, a comparison takes place with outcomes from earlier studies about traditional financial assets.
Moreover, we empirically investigate herding behaviour of cryptocurrencies during bull and bear markets. The present survey suggests that empirical findings about whether herding phenomena have made a significant appearance or not in cryptocurrency markets are split.
Different behaviour is detected in bull periods compared to bear markets. Nevertheless, evidence from primary studies indicates that herding is stronger during extreme situations rather than in normal conditions.
However, our empirical estimations reveal that herding behaviour is evident only in bull markets. These findings cast light on and provide a roadmap for investment decisions with modern forms of liquidity. The worldwide liquidity shortages brought up to the surface by the Global Financial Crisis have prompted traders, policymakers and academics to focus interest on alternative forms of money and investment assets.
The introduction of Bitcoin by Nakamoto has spurred coin offerings of a wide spectrum of digital currencies that have attracted considerable attention by all types of market participants.
A heated debate has aroused concerning whether digital currencies can fulfill the functions of money so be used as means of transactions, store of value and units if account Yermack, ; Ammous, Their decentralized nature and the lack of regulatory authorities have rendered them widespread since and extremely popular across speculators but also uninformed investors.
The risk-return trade-off through the lens of cryptocurrency volatility has been at the epicenter of academic research Beneki et al. The high level of ignorance about fundamentals of cryptocurrencies has made these markets largely susceptible to collective actions of the market even when these are in sharp contrast to beliefs of individual persons.
Behavioural finance constitutes a sub group of behavioural economics and suggests that pychological factors and biases exert impacts on financial decisions of investors and economic units in general. These influences are at the route of anomalies in markets of financial assets and generate bull or bear phenomena in high speed. This is closely related to irrational exuberance as has been analyzed by Robert Shiller Shiller, that leads to over-enthusiasm and the creation of asset price bubbles.
Herding behaviour can be expressed in various forms such as trading in the same direction with others, following the trend in previous trades, imitating or correlation one's behaviour to others' behaviour. Usually investors who lack experience are prone to become risk-lovers without being able to understand the risks that they suffer.
Such thoughtless behaviour is often encouraged by lack of certainty regarding economic conditions and by extreme conditions in markets, such as during turmoil.
It should be noted that rational herding can also take place. Instead of the case where agents follow other agents blindly —as it happens during irrational herding behaviour-externalities, distortions due to information difficulties or incentive matters can emerge Devenow and Welch, Rational herding means that investors learn by observing other investors. They use the publicly available information in order to estimate the risk inhibited in the counterparty. Momemtum is less influential when it comes to rational herding decision-making Zhang and Liu, Herding can be divided into a intentional herding when investors willingly imitate the behaviour of other investors and b spurious herding when investors have a similar information set that is driven by fundamentals Galariotis et al.
To be more precise, intentional herding is mainly about imitation triggered by the expectation of some sort of benefit when asymmetric information exists. The belief of being at an informational disadvantage in relation to others leads to herding providing informational payoffs. For this reason, intentional herding results into the creation of informational cascades in order to collect guidance.
This type of herding may be inefficient and can be characterized by fragility, extreme fluctuations and systemic risk Bikhchandani and Sharma, Moreover, intentional herding brings about professional payoffs concerning fund managers and financial analysts.
Their motives of protecting their reputation and preserving their compensation are satisfied through herding during extreme market conditions. When it comes to spurious unintentional herding, this takes place when investors are receivers of common signaling and present hardly different reactions to these signs.
Similar investment strategies due to commonality among investment professionals and style investing are at the root of spurious herding. Moreover, home bias appears -leading a lot of investors to prefer home market's stocks-that is reinforced by other psychological factors such as familiarity bias, recognition heuristic and conformity for more details see: Kallinterakis and Gregoriou, Herding has made its appearance in a wide spectrum of alternative financial assets through time and has attracted early attention by high-quality academic studies Nofsinger and Sias, To be more precise, herding phenomena have been studied concerning stock markets Chang et al.
Furthermore, academic work about herding has focused on the house market Ngene et al. Analysis has also been conducted in both microeconomic and macroeconomic levels Venezia et al. Moreover, integrated surveys on herding in financial assets have been discussed Hirshleifer and Hong Teoh, ; Belke and Setzer, ; Menkhoff et al.
This study focuses on herding behaviour in the digital currency markets as these innovative forms of liquidity are particularly attractive to investors due to their potential for very high profitability. Bitcoin has been the largest-capitalized digital currency during the last decade and herding phenomena in cryptocurrency markets are mainly attributed to its price fluctuations.
Up to the present, only the seminal review paper of Corbet et al. Moroever, there is a survey paper on the bubble characteristics of cryptocurrencies Kyriazis et al. Our overview and empirical testing adds to relevant literature by casting light on a specific aspect of behaviour in digital currency markets.
Bitcoin's supply is fixed so the demand for Bitcoin is clearly market-determined. It should be emphasized that despite the hegemonic role of Bitcoin in digital currencies being confirmed, there is also academic work that proves lower-capitalization digital currencies being influential as well as regards herding behaviour. The second largest cryptocurrency in terms of market capitalization has been Ethereum that started trading in August and constitutes a smart contract.
Ethereum presents lower market value so is more accessible to investors but is also in a larger extent prone to protocol alterations by a majority of users. Moreover, Ripple is among the highest capitalized digital currencies. It exhibits a very low market value so is accessible to a larger number of investors. Profit-making by holding Ripple can be achieved due to its large fluctuations in prices. Ripple offers an alternative to conventional financial intermediation practices and is considered to be a trading currency Ammous, Furthermore, Litecoin displays high resemblance to Bitcoin and has its supply capped at 84 million coins.
It was introduced at July and has been extremely volatile and attractive to risk-seekers. Special emphasis should be attributed to the Tether stablecoin, which is not mined.
It is pegged to and backed by the US dollar anchored to 1 USD and has recently become one of the major digital currencies traded. It primarily serves for converting and exchanging into other cryptocurrencies, especially on exchanges not accepting traditional fiat currencies Wei, This integrated survey casts light on rational and irrational investor behaviour and herding phenomena in the markets of digital currencies but also traditional assets.
More specifically, the contribution of this paper is threefold. Firstly, understanding of rational and irrational behaviour is enhanced and an overall perspective on herding phenomena in financial markets is provided. Secondly, a comparative analysis of herding behaviour across markets takes place. Thirdly, an empirical estimation of herding is conducted by employing data on a respectable number of cryptocurrencies and comparison takes place between bull and bear periods.
This enables the interested reader to have a compass when investing in digital forms of money and investments and better familiarize with the tendency of such markets to follow signals from other cryptocurrency markets, like that of Bitcoin. In the remainder of this paper, Section 2 provides empirical literature on herding phenomena in a number of categories of traditional financial assets and provides an overview of results.
Furthermore, Section 3 lays out the empirical studies investigating herding phenomena in digital currency markets and summarizes findings. In Section 4 the data and methodology employed for the purposes of our empirical estimations are presented. Section 5 provides the empirical analysis concerning herding phenomena in cryptocurrency markets during bull and bear periods and reveals the economic implications. Finally, Section 6 discusses and comments on economic and policy implications and provides the conclusions.
Moreover, avenues for future research are suggested. It should be noted that Table A2 in the Appendix presents in a brief manner the main elements of the studies about herding in cryptocurrency markets and Table A1 displays the digital currencies used in our empirical estimations. Additionally, Figures A1-A3 show some statistical evidence on the references and citations relevant to the studies about herding in cryptocurrency markets.
Academic work on herding behaviour has been based on seminal papers that have provided with in-depth analysis and innovations concerning the measures of herding phenomena.
Among them, the studies of Christie and Huang, Hwang and Salmon and the integrated survey of Spyrou can be found. To be more precise, Christie and Huang investigate herding behaviour by using the cross-sectional standard deviation of returns.
They emphasize that herding intensity is low when a lot of investors follow the crowd. On the other hand, rational asset pricing models support that when stocks exhibit different levels of of sensitivity to market movements then higher dispersion arouses.
It is argued that during turbulent eras herding expected to be more intense. Despite that, it is revealed that a rational asset pricing model better explains dispersion in such conditions. Moreover, Hwang and Salmon propose a new approach in order to trace herding behaviour. This method is based on the cross-sectional dispersion of the factor sensitivity of assets in a given market and measures deviation from the equilibrium beliefs as measured by CAPM prices.
This enables them to separate herding from market sentiment and distinguish the latent herding component in asset prices. In contrast to estimations of Christie and Huang , they concentrate interest on the cross-sectional variability of factor sensitivities instead of returns and examine market-wide herding. More specifically, the US, UK, and the Korean markets are under scrutiny, Evidence presents that herding towards the market exhibits significant movements and persistence irrespectively of and given market conditions as is shown in returns and volatility.
Herding towards the market portfolio is found during bull and bear markets. Spyrou conducts a review about herding phenomena in financial markets at a theoretical or an empirical level.
Alternative theories and perspectives about herding as well as measures are presented. The metrics of Lakonishok et al. Furthermore, some general conclusions have been reached. Firstly, the empirical evidence does not lead to overall accurate conclusions.
Secondly, existing measures of herding have to overcome limitations. Thirdly, empirical tests do not abide by the speed of theoretical advances about herding behaviour of investors. Moreover, further emphasis should be put on the investigation of whether spurious or intentional herding appears. Furthermore, passive herding is not examined by empirical studies. Finally, it is supported that relevant academic work should focus more intensely on herding phenomena in emerging stock markets and institutional investors in these markets.
Alternatively, more focus should be made on commodity, derivative and real estate markets. An important number of academic studies have focused on the market of financial assets and irrational behaviour of investors that mimic other investors' actions which is contrary to their own beliefs.
Stablecoins Vs Altcoins: Difference Between Stablecoins And Altcoins
This page lists the top proof of work coins. These cryptocurrency projects all have their own blockchains. They are listed by market capitalization with the largest first and then descending in order. Watchlist Portfolio. Show rows Market Cap.
Bitcoins and other cryptocurrencies: everything you need to know
Topics: Cyber Liability. Search for:. Solutions Small Commercial. Industries Industries. Services Resources. Company About AmTrust. Legal Legal.
Will Shiba Inu turn the numero uno meme coin despite Musk's cold shoulder?
This is assuming that you invested in the top 10 altcoins a year ago without doing any due diligence. Yes, without any research. Just simply picking the coins which are the biggest in size according to their market capitalizat. Just simply picking the coins which are the biggest in size according to their market capitalization. I just want to show you that you can make a lot of money with Altcoins, only if you know what you are doing.
High Stakes, High Reward: The Rise of Cryptocurrency and Its Risks in Indonesia
Buy, sell, trade today! Dogecoin is one of the oldest cryptocurrencies, being used by cryptocurrency enthusiasts all over the world for over six years. Dogecoin was a part of a mini alt-coin boom that was created in the wake of a huge Bitcoin bull run in Whenever a technology, company, or person has success you can almost guarantee there will be a round of copy cats trying to capture a part of that success. The first altcoin was Namecoin, next came Litecoin, then came our beloved alt-coin boom in that bequeathed us Dogecoin. Much wow.
Mastering Bitcoin by
In this paper, we research and analyse the main characteristics, the evolution of the Bitcoin and of the Alternative Coins Alt-Coins digital currencies, their numerous applications and ramifications. We make an in depth analysis of the Bitcoin digital currency and of the most significant Alternative Coins, taking into account their technical characteristics, their main advantages and limitations. Just as it happened in the past decades with the personal computers and Internet, the impact of these digital currencies will gradually increase in the future, leading to major changes in our lifestyle, redefining our everyday life, economy and society. The digital currency also known as digital money represents an online mean of payment that differs significantly from the classic means of payments such as cash, cheque, credit, debit or bank transfer. The digital money preserves a series of properties from the physical currencies, having the advantages of allowing instant transactions and transfers to be made. Similar to the classic means of payment, the digital currencies can be used to pay for a wide range of goods and services. From a historical point of view, the digital money have emerged consequently to the development of the cryptography. Obviously, when a sequence of bits becomes a digital representation of a monetary value that can be used for paying different goods or services, users might have their own doubts regarding the security of their money and of the associated transactions.
What is Cryptocurrency and Does it Affect Cybersecurity?
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This is assuming that you invested in the top 10 altcoins a year ago without doing any due diligence. Yes, without any research. Just simply picking the coins which are the biggest in size according to their market capitalization. I just want to show you that you can make a lot of money with Altcoins, only if you know what you are doing.
Dogecoin is a community-driven cryptocurrency that was inspired by a Shiba Inu meme. The Dogecoin Core software allows anyone to operate a node in the Dogecoin blockchain networks and uses the Scrypt hashing method for Proof of Work. It is adapted from Bitcoin Core and other cryptocurrencies. For information about the default fees used on the Dogecoin network, please refer to the fee recommendation. Website: dogecoin.
By now, you've no doubt heard about the massive bitcoin rally this year. And you may also have read about other cryptocurrencies, such as litecoin and Ethereum , surging too. But there are over 1, cryptocurrencies in existence.
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