It uses block chain technology. It is a very brilliant technology because both the buyer and seller details are viewable to each other and so no broker is needed. For example if we need to buy a share from a stock market we can do it easily with the help of a broker. We will confirm the exchange order and then we will receive the shares. This is known as principle of novation. In cryptocurrency involvement of third person is not needed because all the transactions are stored in a common location and it is viewable.
The identity of the person who made the transaction is encrypted. Blockchain — document that tracks all the transactions. The answer for the above question is yes. For example one of the cryptocurrency Bitcoin can be exchange into cash on a crypto exchange. There are platforms such as coinbase and kraken that helps the users to convert digital money to physical cash. There is a chance of earning huge amount when compared to mutual funds or share market but it comes with a high risk. Because the volatility of cryptocurrency is very high.
Either we earn high return or lose what we have. Every coin has two faces, similarly there are both good and bad about investing in cryptocurrency. One should know both the faces before investing. Let us consider only the good side about investing. Returns may be massive and everything is instant. So you can buy or sell when there is a fluctuation in the market very easily. There is a cold wallet storage option where we can control our own private key.
This key helps us to access our coin in the block chain. Next problem is volatility. For example in cryptocurrency like Bitcoin increased suddenly upto percentage and then came down. It varies from one country to another. In some countries it is legal and some countries have banned it. It is also legal in developing country like India but it does not have any regulatory framework. Countries like Algeria, morocco, Nepal, Pakistan and Vietnam have banned it.
Most are the banks are against the idea of cryptocurrencies because it is a treat to most of the traditional banks. One of the biggest drawback of cryptocurrency is the security. There are stories where exchanges are hacked and peoples who held coins in those exchanges lost everything.
If you are ready to take risk and if you are ready for investing then be ready for all kind of high and low. Yes Bitcoin may crash. But the gains achieved using Bitcoin are higher when compared to the losses. A Cryptocurrency is a digital currency that is created through mathematical engineering algorithm.
It is designed to. Similar presentations. Upload Log in. My presentations Profile Feedback Log out. Log in. Auth with social network: Registration Forgot your password? Download presentation. Cancel Download. Presentation is loading. Please wait. Copy to clipboard. Presentation on theme: "Cryptocurrencies by. Download ppt "Cryptocurrencies by.
IntroductionThe Bitcoin  is a potential alternative currency to the standard fiat currencies e. Of course, where there is an upside, there is often a downside as well. Simultaneously with its increasing popularity and public attention, the Bitcoin system has been labelled as an environment for organized crime and money laundering, and it has been a target of repeated hacker attacks that have caused major losses to some bitcoin owners [2, 3].
However, it should be noted that all of these issues can be a concern for standard cash currencies as well. Further, they show that the wealth in bitcoins is accumulating in time and that such accumulation is tightly related to the ability to attract new connections in the network.
They find positive feedback loops for social media use and the user base. In our previous study , we focus on a speculative part of the Bitcoin value as measured by the search queries on Google and searched words on Wikipedia, showing that both the bubble and bust cycles of Bitcoin prices can be at least partially explained by interest in the currency. Gox exchange, historically the most prominent of the Bitcoin markets, after which the Bitcoin price started a slow stable decreasing trend with rather low volatility.
Here, we address the price of the Bitcoin currency, taking a wider perspective. We focus on various possible sources of price movements, ranging from fundamental sources to speculative and technical sources, and we examine how the interconnections behave in time but also at different scales frequencies.
To do so, we utilize continuous wavelet analysis, specifically wavelet coherence, which can localize correlations between series and evolution in time and across scales. It must be stressed that both time and frequency are important for Bitcoin price dynamics because the currency has undergone a wild evolution in recent years, and it would thus be naive to believe that the driving forces of the prices have remained unchanged during its existence.
In addition, the frequency domain viewpoint provides an opportunity to distinguish between short- and long-term correlations. We show that the time and frequency characteristics of the dynamics are indeed both worth investigating, and various interesting relationships are uncovered.
MethodsBefore turning to the results of our analysis, we provide a detailed description of the utilized wavelets methodology. In this section, we also provide a descriptive list of the data sources, which are crucial for the whole analysis, as he data availability of Bitcoin is unique in comparison with other financial assets.
Given the admissibility condition , any time series can be reconstructed back from its wavelet transform. The original series can be reconstructed from the continuous wavelet transforms for given frequencies so that there is no information loss [13, 14]. From a wide range of complex-valued wavelets that allow for a multivariate analysis, we opt for the Morlet wavelet, which provides a good balance between time and frequency localization [14, 15].
The continuous wavelet framework can be generalized for a bivariate case to study the relationship between two series in time and across scales. A continuous wavelet transform is then generalized into a cross wavelet transform as 3 where Wx u, s and Wy u, s are continuous wavelet transforms of series x t and y t , respectively .
The cross wavelet power uncovers regions in the time-frequency space where the series have common high power, and it can be thus understood as a covariance localized in the time-frequency space. To address this weakness, the wavelet coherence is introduced as 4 where S is a smoothing operator [14, 17]. The squared wavelet coherence ranges between 0 and 1, and it can be interpreted as a squared correlation localized in time and frequency.
Due to the above mentioned complexity of the used wavelets and in turn the use of the squared coherence rather than coherence itself, information about the direction of the relationship is lost. Graphically, the phase difference is represented by an arrow. If the arrow points to the right left , the series are positively negatively correlated, i. The relationship is usually a combination of the two, i. Note that the interpretation of phase relationships is partially dependent on specific expectations about the relationship because a leading relationship in the in-phase can easily be a lagging relationship in the anti-phase.
Please refer to Ref. Recently, the partial wavelet coherence has been proposed to control for the common effects of two variables on the third [18, 19], and it is defined as 6 The partial wavelet coherence ranges between 0 and 1, and it can be understood as the squared partial correlation between series y t and x1 t after controlling for the effect of x2 t localized in time and frequency.
For a more detailed treatment of the partial wavelet coherence, we refer interested readers to Refs. Data Here, we provide a detailed description of all analyzed series together with their source links. The characteristics of variables are described as of the time of the analysis, i. Bitcoin price index. There are various criteria for specific exchanges to be included in BPI, which are currently when the analysis was undertaken met by three exchanges:Bitfinex, Bitstamp and BTC-e.
Gox exchange was part of the index as well, but following its closure, the criteria ceased to be fulfilled. BPI is available on a 1-min basis, and it is formed as a simple average of the covered exchanges. Due to data availability, we analyze the relationships starting from 14 September On a daily basis, the following time series used in our analysis are reported: Total bitcoins in circulation Number of transactions excluding exchange transactions Estimated output volume Trade volume vs.
The creation of new bitcoins is driven and regulated by difficulty that mirrors the computational power of bitcoin miners hash rate. Bitcoin miners certify ongoing transactions and the uniqueness of the bitcoins by solving computationally demanding tasks, and they obtain new newly mined bitcoins as a reward.
Rewards and difficulties are given by a known formula. The Bitcoin is used primarily for two purposes:purchases and exchange rate trading. Blockchain provides the total number of transactions and their volume excluding the exchange rate trading exchange transactions. In addition, the ratio between volume of trade primarily purchases and exchange transactions is provided. Understandably, the over-the-counter OTC transactions are not covered.
Gox is already in insolvency, we include it in the total exchange volume because it was the biggest exchange until and its exclusion would thus strongly bias the actual volumes. After its bankruptcy, the volumes converged to zero. Google Trends standardly provides weekly data, whereas the Wikipedia series are daily. To obtain daily series for Google searches, one needs to download Google Trends data in three months blocks. The series are then chained and rescaled using the last overlapping month.
The FSI can be separated into various components. However, we use the overall index to control for all types of financial stress. However, the results remain largely the same regardless of the used currency. According to Grinsted et al. If the series are in fact multimodal, it is suggested that they be transformed to a uniform distribution and that quantiles of the original series, in turn, be analyzed. The inference based on the wavelet framework and the related Monte Carlo simulations based significance is then reliable.
For this matter, we transform all of the original series accordingly, as most of them and particularly the Bitcoin price, are multimodal, and we thus interpret the results based on the quantile analysis. This specific exchange rate pair is selected because trading volumes on the USD markets form a strong majority, followed by a profound lag by the Chinese renminbi CNY.
The analyzed period is restricted due to the availability of a Bitcoin price index covering the most important USD exchanges. Note that an analysis of a specific exchange is not feasible because the most important historical market, Mt. Gox, filed for bankruptcy after serious problems with bitcoin withdrawals in For this reason, we use the CoinDesk Bitcoin price index BPI , which is constructed as the average price of the most liquid exchanges.
Please refer to the Methods section for further details about BPI. Evolution of the price index is shown in Fig 1, in which we observe that the Bitcoin price is dominated by episodes of explosive bubbles followed by corrections, which never return to the starting value of the pre-bubble phase. It is completely unrealistic to know the total amount of US dollars in the worldwide economy on a daily basis. In a similar manner, it is also impossible to track the number of transactions that occur using the USD or other currencies.
However, the Bitcoin provides this type of information on daily basis, publicly and freely. Such data availability allows for more precise statistical analysis. We examine Bitcoin prices considering various aspects that might influence the price or that are often discussed as drivers of the Bitcoin exchange rate. We start with the economic drivers, or potential fundamental influences, followed by transaction and technical drivers, influences on the interest in the Bitcoin, its possible safe haven status; finally, we focus on the effects of the Chinese Bitcoin market.
Economic drivers In economic theory, the price of a currency is standardly driven by its use in transactions, its supply and the price level. Either the time series for all of these variables are available or we are able to reconstruct them from other series; see the Methods section for more details. As a measure of the transactions use, i.
The ratio thus shows what the ratio is between volumes on the currency exchange markets and in trade e. From the theory, the price of the currency should be positively correlated with its usage for real transactions because this increases the utility of holding the currency, and the usage should be leading the price. In Fig 2, we show the squared wavelet coherence between the Bitcoin price and the ratio.
We thus see the evolution of the local correlation in time and across frequencies. The hotter the color is, the higher the correlation. Statistically significant correlations are highlighted by a thick black curve around the significant regions; significance is based on Monte Carlo simulations against the null hypothesis of the red noise, i.
The cone of influence separates the reliable full colors and less reliable pale colors regions. A phase difference, i. Please refer to the Methods section for more detail. The variables are in the anti-phase, so they are negatively correlated in the long term.
However, there is no strong leader in the relationship. The slightly dominating frequency of the arrows pointing to the southwest hints that the ratio is a weak leader. On the shorter scales, most of the arrows point to the northeast, indicating that the variables are positively correlated and that the prices lead the Trade-Exchange ratio.
Note that this relationship is visible primarily for the periods with extreme price increases for the BTC. In other words, the Bitcoin appreciates in the long run if it is used more for trade, i. The former is thus consistent with the theoretical expectations, and the latter shows that increasing prices—potential bubbles—boost demand for the currency at the exchanges. Therefore, the Bitcoin behaves according to the standard economic theory, specifically the quantity theory of money, in the long run but it is prone to bubbles and busts in the short run.
The former finding might be seen as surprising given an unorthodox functioning of the Bitcoin, and the latter one is in hand with previous empirical studies [10, 11]. Download: PPT PowerPoint slide PNG larger image TIFF original image Wavelet coherence is represented by a colored contour:the hotter the color is, the higher the local correlation in the time-frequency space with time on the x-axis and scale on the y-axis.
The matching of colors and correlation levels is represented by the scale on the right hand side of the upper graph. Regions with significant correlations tested against the red noise are contrasted by a thick black curve. The cone of influence separating the regions with reliable and less reliable estimates is represented by bright and pale colors, respectively.
Phase lag-lead relationships are shown by the arrows—a positive correlation is represented by an arrow pointing to the right, a negative correlation by one to the left, leadership of the first variable is shown by a downwards pointing arrow and if it lags, the relationship is represented by an upward pointing arrow. The latter two relationships hold for the in-phase relationship positive correlation ; for the anti-phase negative correlation , it holds vice versa.
Henceforth, specifically for the fundamental drivers, Bitcoin price is negatively correlated to the Trade-Exchange ratio top over the long-term for the entire analyzed period, and there is no evident leader in the relationship. The Bitcoin price level is negatively correlated with the Bitcoin price in the long-term for the entire analyzed period as well bottom left , with no evident leader. The supply of bitcoins is positively correlated with the price in the long-term bottom right , with no evident leader.
This is referred to as the law of one price in the standard economic theory. When the price level associated with one currency decreases with respect to the price level of another currency, the first currency should be appreciating and its exchange rate should thus be increasing. An expected causality goes from the price level to the exchange rate price of the Bitcoin.
The price level in our case is constructed as the average price of a trade transaction for a given day. Fig 2 uncovers that the most stable interactions take place at high scales at approximately days. The relationship is negative as expected, but the leader is not clear. The relationship is again negative as expected, but the leadership of the price level is more evident here. Most of the other significant correlations are outside the reliable region. Again, the Bitcoin behavior does not contradict the standard monetary economics in the long run.
The money supply works as a standard supply, so that its increase leads to a price decrease. A negative relationship is thus expected. Moreover, due to a known algorithm for bitcoin creation, only long-term horizons are expected to play a role. In Fig 2, we observe that there is a relationship between the Bitcoin price and its supply. However, most of the significant regions are outside of the reliable region. Moreover, the orientation of the phase arrows is unstable, so it is not possible to detect either a sign or a leader in the relationship.
This difficulty might be due to the fact that both the current and the future money supply is known in advance, so that its dynamics can be easily included in the expectations of Bitcoin users and investors. The expectations of the future money supply is thus incorporated into present prices and relationship between the two is in turn negligible.
Transaction drivers The use of bitcoins in real transactions is tightly connected to fundamental aspects of its value. However, there are two possibly contradictory effects between the usage of bitcoins and their price, which might be caused by its speculative aspect. One effect stems from a standard expectation that the more frequently the coins are used, the higher their demand—and thus their price—will become.
However, if the price is driven by speculation, volatility and uncertainty regarding the price, as well as the increasing USD value of transaction fees, can lead to a negative relationship. Trade volume and trade transactions are used as measures of usage. In Fig 3, we observe that for both variables, the significant relationships take place primarily at higher scales and occur primarily in The effect diminishes in ; and at lower scales, the significant regions are only short-lived and can be due to statistical fluctuations and noise.
For the trade transactions, it is clear that the relationship is positive and that the transactions lead the price, i. However, the effect becomes weaker in time. For the trade volume, the relationship changes in time, and the phase arrows change their direction too often to offer us any strong conclusion.
The transaction aspect of the Bitcoin value seems to be losing its weight in time. The price leads both relationships as the phase arrow points to southeast in most cases, and the interconnection remains quite stable in time. The trade volume bottom left is again connected to the Bitcoin price primarily in the long-term. However, the relationship is not very stable over time. The relationship then becomes less significant and the leader position is no longer evident. Massive upper wick followed by bullish PA usually means wicked price will be revisited Acts as a sort of clue.
Leaving this here if the theory holds true. The best is to buy every dip of this coin The possible buy region is call out on the chart A long announced and hyped pump from the WSB team. They use people's money to pump their initial investment and then letting it die before you can say 'oops I fucked up'.
Don't go along with these people or you'll get burned. Finally broke the cloud and now it is free and can go up good Macd is stronge And if you are new buy in correction and hodl for short midterm Do your own research Set SL.
Get started. AlanSantana Premium. SpartaBTC Premium. PeacefulWarrior Premium. Mehdisouriiii Pro. Wall street bets keeps disrupting. PPT btc update. CryptoNicho Premium. Show more ideas. Breaking news. More news.
A peer-to-peer internet currency that allows decentralized transfers of value between individuals and businesses. Bitcoin vs. bitcoins. Bitcoin is the system. Total balances held in BTC 1B$ compared with 1,B$ circulating in USD. 30 Transactions per min. (Visa transaction , per minute.) BitCoin: Challenges. Find predesigned Bitcoin Powerpoint Presentation Slides PowerPoint templates slides, graphics, and image designs provided by SlideTeam.