Cryptocurrency graph analysis
A bullish indication is regarded a double bottom, while a bearish signal is considered a double top. Both the triple and double patterns are reversal settings, indicating that prices are poised to change direction. Although double tops and bottoms are significantly more prevalent crypto graph patterns, triple patterns frequently produce greater reversals.
Traders would have entered into a bearish position after the price broke down from the prior reaction low in early-July. Unlike the ascending and descending triangle, rising and falling wedges are reversal patterns.
A rising wedge is a bearish signal and a falling wedge is a bullish signal. Traders would have entered a short position following the breakdown from the lower trend line and realized a modest profit before the uptrend resumed over the following days. It develops when parallel support and resistance lines are crossed by an uptrend or decline. It implies either a potential trend reversal or a change in the present trend's slope. First, using emerging patterns, traders can start trading when the price swings inside the trendlines of their channel if they think the price is likely to stay there.
Initiate a trade when the price crosses the channel's trendlines, either on the upper or lower side, with complete patterns i. When this occurs, the price may surge in the breakout's direction. Bullish and Bearish Flag Crypto Graph Patterns These crypto patterns are expressed by small rectangular trading ranges within diagonal parallel lines for shorter periods of time.
It moves against the dominant price trend over a longer time period. It often develops after a rapid gain or collapse and frequently denotes a slight change in trend or areas of consolidation prior to the return of the prior trend. Bullish flags and bearish flags are both examples of flag patterns because it creates a backdrop for entering an established trend that is prepared to continue, the flag pattern is one of the most trustworthy continuity patterns used by traders.
Best Practices to Keep in Mind Cryptocurrency chart patterns are helpful for assessing market psychology, but they are more subjective than technical indicators. Blockchain technology and cryptocurrencies are related, but they are not the same thing. Here are the primary differences between the two. Always Seek Confirmation: Chart patterns provide hints into market sentiment, but they shouldn't be the only basis for a trade — you should look for confirmations elsewhere.
Look at the Volume: Volume plays an important role in analyzing chart patterns. If a breakout occurs on low volume, there's a risk that it could be a head fake or false breakout. Set a Stop Loss: Chart patterns can be helpful for setting stop loss levels. For instance, a good stop loss for an ascending triangle breakout is the lower trend line. Try It Out First: Consider paper trading to get comfortable with chart patterns before committing actual capital to trading ideas that incorporate them.
The Bottom Line Chart patterns provide traders with insights into market psychology, but they shouldn't be the only tool in a trader's tool belt. It's important to understand technical indicators and other market dynamics to achieve the best results. If you're an active crypto trader, it's equally important to ensure that your taxes are accurate. You can even pre-populate IRS forms or identify tax loss harvesting opportunities.
ZenLedger can help you easily calculate your crypto taxes, and also find opportunities for you to save money and trade smarter. Get started for free now or learn more about our tax professional prepared plans! Do chart patterns work for crypto? Shooting Star Candle Pattern A shooting star candle pattern is a bearish reversal pattern that occurs at the height of a rally before reversing down.
This pattern consists of a candle with a long upper wick and a small body, as can be seen in the image above. A shooting star candle pattern indicates drive-by buyers which are met by resistance. Popular patterns for technical analysis Head and Shoulders Head and shoulders patterns are reversal patterns that may show up at the peak or bottom of an ongoing trend.
If such a pattern shows up near the bottom of a trend, it's called an inverted head and shoulders pattern. These patterns show a tug of war between buyers and sellers, with one side finally coming on top, resulting in a greater pushback or pullback. Wedges The pattern that is formed in the above image is a wedge. They appear when a trend starts to settle down and finally results in a breakout.
Markets often move sideways to wedge back and forth until they move into a firm direction. Support and Resistance Understanding support and resistance are one of the most crucial parts of reading a crypto chart. Support levels in charts refer to a price level that the asset does not fall below for a fixed period. In contrast, resistance level refers to the price at which the asset is not expected to rise any higher. This is the level at which the sellers outnumber buyers in the market for a particular digital asset.
Experts are known to suggest support and resistance levels to assist traders while taking positions in crypto. Conclusion Understanding the patterns would help traders make an informed decision.
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However, for beginners, the basic free version offers all the necessary tools needed for charting. The charts are designed to be sleek, and highly customizable, with tons of known inbuild indicators, tools, alerts, trading scanners, news outlets and more. That being said, whether you are a beginner or professional in the industry. The only downside to this day is that through TradingView you cannot actually connect on too many trading brokers, especially when it comes to crypto-based exchanges.
However, this is not too big of an issue, because TradingView is designed for charting, and most exchanges also use their charts. Coinigy Coinigy is an all-in-one cryptocurrency trading platform that simplifies the process of tracking and trading multiple different cryptocurrencies on multiple different exchanges. And this feature alone is priceless for any rational investor. And because of the large number of exchanges, the platform also provides access to intence research material regarding the cryptocurrency industry.
All in all, Coinigy has one of the best cryptocurrency charts for all crypt traders out there offering an experience unlike anything else in the cryptocurrency space. Cryptowatch uses sleek charts which gives users the ability to visualize price movements and market trends in real-time.
Users can also connect their portfolio to view the performance across multiple exchanges. Cryptowatch is absolutely free to use for charting, however, the premium plan includes a variety of benefits such as the ability to trade intuitively through the platform either by using your mobile phone or desktop computer by connecting up to 8 exchange simultaneously. From a perspective, this financial exchange network can be seen as a social network. In social networks, nodes are individuals, and the edges between them can be friendships or other social relationships.
In the transaction graph of a cryptocurrency, vertices are accounts or addresses in the currency network, and the edges between them are transactions between those accounts. Since these accounts have hidden identities, they do not represent the true identities of individuals. Note that a person can create multiple accounts, and it is almost impossible to link these accounts, and detect that they belong to the same individual.
There are graph analytics methods and heuristics to link some of the accounts Nick , but since these techniques are prone to errors and cannot detect all related accounts, we do not use any of these methods for linking accounts and merging their corresponding nodes in the transaction graph. Our contributions can be summarized as follows: 1 We compare the structural properties of the transaction graphs of five widely-used cryptocurrencies.
Related work Various studies have been conducted on cryptocurrency transaction networks from different perspectives. Among these studies, there is no comprehensive review, and most of them have focused on one or two specific coins, especially Bitcoin and Ethereum, and used outdated blockchain data which does not cover recent developments in the field. In most of these studies the transaction graph is investigated statically and its dynamics and evolution over time are not considered.
We have categorized related work by the cryptocurrencies they have reviewed: Bitcoin Ron and Shamir in , analyzed the bitcoin transaction graph statically. In another study on Bitcoin, Maesa et al. They analyzed the distances between nodes and studied graph metrics such as density and phenomena like the rich-get-richer phenomenon Di Francesco Maesa et al.
But these studies are only limited to Bitcoin, and with modern wallets and the advent of mixers Mixing service , the deanonymization heuristic has become ineffective. In another related work by Fleder et al. Their analysis and calculations on the transaction graph is limited, and their deanonymization heuristic is no longer valid due to the existence of mixers.
Kondor et al. Ethereum In a study by Chen et al. They did not examine the money flow graph dynamically and also their study is limited to a few metrics. In another study by Guo et al. However, this study only deals with a small part of the blockchain at two specific time spots and is not showing the dynamics of the graph over time Guo et al. Multiple coins Liang et al. Currently, Namecoin is no longer active and it is not in the list of top coins according to their market capitalization CoinMarketCap Furthermore, their study is not as comprehensive as ours and they focused on a few metrics and a limited number of cryptocurrencies.
Methodology Dataset The data used in this study were obtained directly from the blockchain of the cryptocurrencies. There are several ways to get these information, and we used two different methods for data collection. For Bitcoin, Ethereum, Litecoin, and Dash, we obtained blockchain data from their peer-to-peer network using their client software.
These data are stored in binary format and needed to be converted into human-readable formats such as comma-separated values CSV for further analysis. These binary data can be converted by parsers which output several large CSV files. These files contain each transaction details including the timestamp, the number of inputs and outputs of the transaction, the incoming and outgoing addresses, and other related information which is stored in the blockchain.
We also made a custom parser for parsing Dash blockchain. To build the transaction graph, we need database operations like Join and Select. Due to the high volume of data, we used Apache Spark, which is one of the most well-known big data processing tools, to perform these operations ApacheSpark Building transaction graph The blockchain structure for each of these cryptocurrencies is different, but some are very similar.
For example, the Bitcoin and Litecoin blockchains are very similar, but the Ethereum blockchain has a completely different structure because of its nature and sophistication. But in all of them, the transaction information is contained within the blocks. In each block, a certain number of transactions can be placed.
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Users can also connect their portfolio to view the performance across multiple exchanges. Cryptowatch is absolutely free to use for charting, however, the premium plan includes a variety of benefits such as the ability to trade intuitively through the platform either by using your mobile phone or desktop computer by connecting up to 8 exchange simultaneously.
Note that users can trade for free through the Cryptowatch interface by connecting it to the Kraken Pro Account. This is extremely useful in case you are living in the united states since Kraken is also US Customer Friendly exchange with margin features. BitcoinWisdom BitcoinWisdom is totally free cryptocurrency charting website, that includes all the key exchanges such as Bitmex , Deribit , Kraken , Binance and Coinbase Pro.
This platform filled an important purpose back in the day by providing one of the first useable Bitcoin charts for traders. Nowadays BitcoinWisdom is still used by many OG:s and often most beginners also find themselves looking into them, and no wonder since these charts are very userfriendly and easy to use.
Start using BitcoinWisdom for free! How to analyze the cryptocurrency charts? Learning to do technical analysis on cryptocurrency charts is no one night wonder, like everything in life, it takes some work and effort to understand all tools, features, and key elements on the cryptocurrency price charts. A good example of this is how newbies often try to learn all the different indicators, completely forgetting that indicators always follow price, which is what they should be focusing on.
As we can see above, there are of course multiple cryptocurrency charting solutions. Transactions in cryptocurrencies are publicly available, hence, statistical studies on different aspects of these currencies are possible. However, previous statistical analysis on cryptocurrencies transactions have been very limited and mostly devoted to Bitcoin, with no comprehensive comparison between these currencies.
In this study, we intend to compare the transaction graph of Bitcoin, Ethereum, Litecoin, Dash, and Z-Cash, with respect to the dynamics of their transaction graphs over time, and discuss their properties. In particular, we observed that the growth rate of the nodes and edges of the transaction graphs, and the density of these graphs, are closely related to the price of these currencies. We also found that the transaction graph of these currencies is non-assortative, i.
Introduction Cryptocurrencies have made it possible for a financial system to perform transactions without the need for a centralized authority while keeping the transaction details and money generation clear and publicly available. All transaction information of a cryptocurrency is usually stored in a distributed public ledger, named blockchain. The tasks of recording, updating, and maintaining the blockchain is the responsibility of network users for each coin, whose identities are unknown, and rewards have been created to provide them with sufficient incentives to do so, making the network up and running.
Although the system is running by anonymous people, due to computational infeasibility of forging digital signatures and security of cryptography algorithms, transaction alteration is almost impossible. This level of security is guaranteed by cryptographic algorithms, and as long as these algorithms are secure, cryptocurrencies integrity is protected. Bitcoin is the first cryptocurrency created by an anonymous person or group of people by the nickname Satoshi Nakamoto, which established a decentralized money transfer system using blockchain Nakamoto Subsequently, other cryptocurrencies, which are usually referred to as altcoins, were created by adding more capabilities and offering alternative design criteria.
Ethereum was introduced by Vitalik Buterin in and is the first blockchain-based distributed computing platform to consider the concept of exe- cutable smart contracts Buterin It is one of the most influential and widely-used cryptocurrencies introduced after Bitcoin.
Litecoin is also one of the earliest cryptocurrencies that is technically very similar to Bitcoin and has only slight differences with it Litecoin For example, Litecoin uses the Scrypt hash function instead of SHA for proof of work, and records transactions in the blockchain four times faster than Bitcoin. Litecoin is created as a hard fork of Bitcoin, and has a separate blockchain. Dash is another cryptocurrency which is quite similar to Bitcoin and uses the X11 hashing algorithm for proof of work Duffield and Diaz Similar to Litecoin, Dash has a separate blockchain, with transactions speed 4 times faster than Bitcoin.
Z-Cash is a highly secure cryptocurrency that uses zero-knowledge proofs, as a result of which privacy and anonymity of users is significantly enhanced Hopwood et al. In all of the mentioned cryptocurrencies, the ability to transfer money is the basic and common core capability.
Using the blockchain data of each of these currencies, the transactions in which they occur can be accessed. As a result, it is possible to analyze transactions in these currencies from different aspects and perform a variety of statistical analyses on them. In particular, it is possible to examine a real network of financial transactions for each cryptocurrency.
In this paper, the financial exchange network of the five aforementioned cryptocurrencies has been studied and several statistical metrics and network measures are calculated, and their meanings are discussed. From a perspective, this financial exchange network can be seen as a social network. In social networks, nodes are individuals, and the edges between them can be friendships or other social relationships.
In the transaction graph of a cryptocurrency, vertices are accounts or addresses in the currency network, and the edges between them are transactions between those accounts. Since these accounts have hidden identities, they do not represent the true identities of individuals.
Note that a person can create multiple accounts, and it is almost impossible to link these accounts, and detect that they belong to the same individual. There are graph analytics methods and heuristics to link some of the accounts Nick , but since these techniques are prone to errors and cannot detect all related accounts, we do not use any of these methods for linking accounts and merging their corresponding nodes in the transaction graph. Our contributions can be summarized as follows: 1 We compare the structural properties of the transaction graphs of five widely-used cryptocurrencies.
Related work Various studies have been conducted on cryptocurrency transaction networks from different perspectives. Among these studies, there is no comprehensive review, and most of them have focused on one or two specific coins, especially Bitcoin and Ethereum, and used outdated blockchain data which does not cover recent developments in the field.
In most of these studies the transaction graph is investigated statically and its dynamics and evolution over time are not considered. We have categorized related work by the cryptocurrencies they have reviewed: Bitcoin Ron and Shamir in , analyzed the bitcoin transaction graph statically.
In another study on Bitcoin, Maesa et al.
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