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Want to spot a turning point in trend before it happens?Want to spot a turning point in trend before it happens? Use Elliott wave parallel channel This chart shows the GBP/JPY currency pair using monthly candlesticks. The advance from Sep 2011 to June 2015 can be labeled as an impulse wave (A). From that high, the pair declined in three waves labeled as wave (B) of a Zigzag A-B-C correction with an expanding diagonal characteristic in the C wave position. As a rule, in a Zigzag rally, wave B notably terminates above the origin of wave A. When wave (C) advance of a zigzag rally is in operation, we can forecast where wave (C) might end. We can use Elliott wave channel projection by connecting the origin of wave (A) with the end of wave (B) and then drawing a parallel line from the end of wave (A). As a guideline, the resulting channel gives us a potential target for the wave (C) endpoint. Moreover, we can also use ratio analysis to improve the odds. As a guideline, in Zigzag formations, wave (C) commonly ends after traveling the same length as wave (A). Observe this level corresponds with the Elliott wave channel projection. This cluster of evidence hints at wave (C) advance from Mar 2020 is in late stages and that prices are approaching a major top.

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by Aquanet_Market_Forecast

Bitcoin vs. Ethereum: Deciphering the Distinctions Cryptocurrencies have revolutionized the financial landscape, with Bitcoin and Ethereum emerging as two prominent players shaping the digital economy. Despite sharing the common ground of blockchain technology, each offers distinct features and functionalities, underscoring the need to understand their differences. Introduction to Bitcoin Bitcoin, introduced in 2009 by the mysterious Satoshi Nakamoto, heralded the dawn of decentralized digital currencies. Its primary objective was to provide an alternative to traditional fiat currencies through a peer-to-peer electronic cash system. Transactions on the Bitcoin network are verified and recorded on an immutable public ledger, known as the blockchain. Introduction to Ethereum In 2015, Vitalik Buterin introduced Ethereum, presenting a paradigm shift beyond mere digital currency. Ethereum serves as an open-source platform for executing smart contracts and decentralized applications (DApps) without intermediaries. At its core is Ether (ETH), the native cryptocurrency powering transactions and fueling the ecosystem. Core Differences Purpose: Bitcoin functions primarily as a digital currency, aiming to revolutionize financial transactions. Ethereum, on the other hand, is a versatile platform enabling the execution of smart contracts and DApps, with broader implications for decentralization beyond monetary exchange. Technology: Bitcoin operates on a Proof-of-Work (PoW) consensus mechanism, requiring significant computational power for transaction validation. Ethereum initially adopted PoW but is transitioning to Proof-of-Stake (PoS) with Ethereum 2.0, offering improved scalability and energy efficiency. Scalability: Bitcoin processes approximately 7 transactions per second, while Ethereum can handle up to 30. Both face scalability challenges, with Ethereum exploring solutions like sharding to enhance throughput and efficiency. Supply: Bitcoin has a fixed maximum supply of 21 million coins, creating scarcity akin to digital gold. In contrast, Ethereum does not have a predefined supply limit, potentially allowing for continuous production, albeit with economic implications. Use Cases: Bitcoin is synonymous with a store of value, often likened to digital gold due to its limited supply and scarcity. Ethereum's versatility enables the creation of innovative applications such as decentralized finance (DeFi), non-fungible tokens (NFTs), decentralized autonomous organizations (DAOs), and more, expanding its utility beyond monetary transactions. Price Dynamics Bitcoin's market movements often dictate the broader cryptocurrency landscape, impacting the prices of assets like Ethereum. Influencing factors include market sentiment, regulatory developments, and macroeconomic conditions. Ethereum's price dynamics are further influenced by platform upgrades, developer activity, and the burgeoning demand for decentralized applications. Monthly Bitcoin Chart Monthly Ethereum Chart Conclusion While Bitcoin and Ethereum share the foundation of blockchain technology, their purposes, technologies, and applications diverge significantly. Bitcoin seeks to redefine monetary exchange, while Ethereum aims to revolutionize contractual agreements and decentralized applications. Understanding these distinctions is paramount in navigating the evolving landscape of digital assets and harnessing their transformative potential in the global economy.

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Google search trend for BTC Worldwide, 90days, search trend in Google for bitcoin (red arrows). Orange arrows represent " bitcoin use case ", ie the educated investor? It shows you the mainstream peak euphoria, enthusiasm or fear , usually at market extremes? Highest search volume coincides with trade volume. Other indicator for "hype" would be bitcoin hashtag in twitter/X. According to theory - during enthusiasm people would ignore the bad news or events, and only see everything as positive. This is a contrarian style, which is often the opposite of T.A., ie strong trend can be longterm bad. Pessimistic or skeptical sentiment is usually good (opposite of mainstream view or mood), or usually it means more money is left at sidelines.

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Understanding the Differences Between Stock Market and Crypto P2 Thank you very much for your support, as I told when we will get 20+ likes on Part 1, than I will make Part 2. Here you get the summary of each, with the other points: 10. Market Infrastructure: The infrastructure supporting traditional stock markets, including trading platforms, clearing systems, and market data providers, is well-established and interconnected, whereas the infrastructure for the crypto market is still evolving and fragmented, with multiple competing platforms and protocols. 11. Market History: Traditional stock markets have a long history dating back centuries, with well-documented market cycles and economic trends, whereas the crypto market has a relatively short history, with significant price movements driven by technological developments and market speculation. 12. Regulation of Investment Products: Traditional stock markets offer a wide range of investment products, including stocks, bonds, mutual funds, and exchange-traded funds (ETFs), all subject to regulatory oversight, whereas the crypto market primarily offers cryptocurrencies and tokenized assets with varying degrees of regulatory clarity. 13. Market Correlation: Stocks and traditional financial assets often exhibit correlations with broader economic indicators such as GDP growth and interest rates, whereas the crypto market may demonstrate correlations with factors such as Bitcoin dominance, market sentiment, and technological developments. 14. Market Participants: Traditional stock markets attract a diverse range of participants, including retail investors, institutional investors, hedge funds, and pension funds, whereas the crypto market has a more diverse participant base, including retail traders, technology enthusiasts, speculators, and early adopters of blockchain technology. 15. Market Fragmentation: The stock market operates as a unified marketplace with standardized trading rules and regulations, whereas the crypto market is fragmented across multiple exchanges, each with its own trading protocols, liquidity pools, and pricing mechanisms. 16. Market Impact of News Events: News events such as corporate earnings releases, economic data reports, and geopolitical developments have a significant impact on stock market movements, whereas the crypto market may react more strongly to news related to regulatory developments, technological advancements, and adoption trends. 17. Market Efficiency: The efficiency of traditional stock markets is supported by established trading mechanisms, liquidity providers, and market makers, leading to relatively stable price discovery and reduced arbitrage opportunities, whereas the crypto market may experience inefficiencies due to lower liquidity, market manipulation, and regulatory uncertainties. Stock Market: Pros: Stability: Stock markets have a long history and are generally stable investment options. Regulation: They are heavily regulated, providing a level of security for investors. Diversification: Investors can choose from a wide range of stocks across various sectors and industries. Dividends: Many stocks offer dividends, providing a source of passive income. Access to Information: There is a wealth of financial information available for analysis and research. Cons: Limited Trading Hours: Stock markets operate during specific hours on weekdays, limiting trading opportunities. High Entry Barriers: Some stocks may require a significant investment, making it inaccessible for small investors. Market Volatility: While generally stable, stock markets can still experience significant volatility during economic downturns or market crises. Slow Settlement: Settlement times for stock transactions can take several days, delaying access to funds. Limited Accessibility: Access to certain stocks may be restricted based on geographical location or regulatory requirements. Crypto Market: Pros: 24/7 Trading: Cryptocurrency markets operate 24/7, allowing for round-the-clock trading. Accessibility: Anyone with internet access can participate in the crypto market, promoting inclusivity. Potential for High Returns: The crypto market has seen explosive growth, offering the potential for high returns on investment. Decentralization: Cryptocurrencies operate on decentralized networks, reducing dependency on centralized authorities. Technological Innovation: The crypto market is at the forefront of technological innovation, with developments in blockchain and decentralized finance (DeFi). Cons: Volatility: Cryptocurrencies are highly volatile and can experience rapid price fluctuations. Lack of Regulation: Regulatory uncertainty in the crypto market can lead to investment risks and market manipulation. Security Risks: Cryptocurrency exchanges and wallets are susceptible to hacking and cyberattacks. Limited Adoption: Despite growth, cryptocurrencies still face challenges in widespread adoption as a mainstream form of payment. Complexity: Understanding cryptocurrencies and blockchain technology can be challenging for newcomers, leading to potential investment mistakes. Summary: Both the stock market and the crypto market offer unique opportunities and challenges for investors. The stock market provides stability, regulation, and a wide range of investment options, while the crypto market offers accessibility, potential for high returns, and technological innovation. Deciding which market is better depends on individual preferences, risk tolerance, and investment goals. Diversification across both markets may provide a balanced approach to building an investment portfolio.

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by smarttrader012

Understanding the Differences Between Stock Market and Crypto P1 Hey there, welcome to 'Stock Market VS Crypto Market'! Our goal? To break down the complexities and highlight the fascinating differences between traditional stocks and the exciting world of cryptocurrencies, making it easier for traders and investors to navigate both landscapes. This is Part 1: (In Part-2 I will tell where to invest and how much) 1. Market Maturity: Traditional stock markets have been established for centuries, with robust infrastructures and historical data available for analysis, whereas the crypto market is relatively young, experiencing rapid growth and evolving regulatory frameworks. 2. Market Size: The global stock market has a significantly larger market capitalization compared to the crypto market, reflecting the extensive presence of publicly traded companies and institutional investors. 3. Volatility: While both markets experience volatility, the crypto market tends to exhibit higher levels of volatility due to its speculative nature and rapid price fluctuations. 4. Transparency: Stock markets typically provide greater transparency in terms of financial reporting, corporate governance, and regulatory disclosures compared to the crypto market, where transparency can vary widely among different projects and exchanges. 5. Counterparty Risk: In the stock market, counterparty risk is mitigated through centralized clearinghouses and regulatory oversight, whereas the decentralized nature of the crypto market may expose investors to higher counterparty risk, such as hacking incidents or smart contract vulnerabilities. 6. Market Manipulation: Instances of market manipulation, such as pump and dump schemes, are regulated and monitored more closely in traditional stock markets compared to the crypto market, where regulatory enforcement may be less stringent. 7. Market Psychology: The psychology of investors in the stock market is influenced by traditional financial metrics and investor sentiment, whereas the crypto market often exhibits a unique blend of technological optimism, speculative frenzy, and fear of missing out (FOMO). 8. Custody Solutions: Custody of traditional stock assets is typically managed by regulated financial institutions, whereas custody solutions for cryptocurrencies range from self-custody through private wallets to third-party custodians and institutional-grade solutions. 9. Accessibility to Information: Stock market participants have access to a wealth of financial information through established platforms such as Bloomberg and Reuters, while information in the crypto market is often decentralized and distributed across various forums, social media platforms, and blockchain explorers. If we get 20+ likes, I´ll make Part-2 (including the summary, where to invest and which is better). So like (boost), follow, comment and share it for increasing the knowledge of your friends!

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by smarttrader012

Narratives in crypto Narratives its not a trend. The first investors who track and find the narrative and start buying tokens in this sector will make a good money, if theyll out in a right time. In the previous bull market, it was not difficult to see the DeFi narrative. Users wanted to see decentralization in everything: exchanges, stablecoins, wallets, landing pages, etc. Later, the narrative was born on exchanges with leverages such as DYDX, GMX, GNS and many others. Who paid attention to this narrative - made good money buying tokens or received a generous airdrops. On this Market you need always follow trends in order to better understand what is happening now around in this space. sometimes people can believe that Bitcoin halving will lead to price increases every four years - these and other narratives are used by many investors to predict price movements, but these are not some rules or laws in crypto! And often as we can see now old patterns and narratives stop working) The market is dynamic, you cannot perceive the market according to the old patterns of 2020, the world is changing. Defi in 2020, nft, layer1, The narratives are around Doge Coin and Elon Mask, shiba inu, Metaverse and Fb. Mana and sandbox grew in a few days, it is always important not the event itself and the sentiment around it, and it is important to enter and exit on time. Narrative AI, some tokens played back and showed new highs, and some were just speculation in this sector. Here's an important thing to note: ALWAYS have a fixation plan. Most narratives will eventually fail and the price of their tokens will bottom out. The best way to sense an emerging narrative is to practice critical thinking. Whenever you read any important news, even if it is not related to cryptocurrencies - think about whether it could potentially be related to cryptocurrencies. If so, with which coins or projects? Conventionally, a year ago no one was talking about RWA, now everyone has become like an expert in this sector. The same will happen with the DePin sector, I think SocialFI will be one of the key ones in the future, because we all use social networks. Why do narratives and catalysts matter in project evaluation? Just because a project is good doesn't mean it's the right time to invest. Fundamental analysis can help you determine which projects have the foundation for success, but narratives determine WHEN their prices will rise. Keeping track of narratives in a crypto can be a challenge because they can change very quickly. People are getting too obsessed with fundamental analysis. Asset prices only go up when other people buy them. Narratives + catalysts can drive people to buy. The project may be fundamentally good, but you may see downward or sideways price movement until there is a catalyst and narrative to drive growth. A great example of elastos, where fundamentally the project looks so cool, but has been in a downtrend for 5 years. And only now is some growth starting on the layer2 narrative for Bitcoin Find narratives and catalysts early by exploring social media platforms like Twitter and even niche media. Look at the key events coming up and then ask yourself, "What are the potential implications of these key events for the crypto market?". For example, at the moment, as I already said, it will be the RWA sector globally, that is, the tokenization of everything in the world. This is not a short-term narrative, but a long-term one. Short-term that will be tied to a sports event, Euro 2024 is a narrative of fan tokens, CHZ token and nft related around this topic, or even meme tokens. How to evaluate a narrative? - Can it be useful in the real world to suppress demand? - Can it affect a large number of people, or will it be a local group of people? - What is the current macro sentiment in the market, and the mood in social networks. After all, if the narrative takes place in a bear market, it will be very difficult to make a big profit from it. Then once you've identified potential narratives, you can look at the categories, and directly the tokens within those categories and their roadmaps. Take into account when forming your investment decisions - Analyze sentiment on Twitter, Reddit. This is where the main mood of the crowd is formed, follow the trends on Twitter, but remember that narratives can play both in a positive and negative way. - The main world media very often form a specially wrong opinion about the market, because essentially all the key media are controlled by big players, and since the coverage of users in them is large, they can set the vector for discussions. If all the mainstream media say that the RWA sector is just a bubble, a lot of people will actually believe it now) Narratives can emerge from portfolio analysis of public funds. But remember, funds can accumulate certain coins from a certain sector and anonymously a lot, but add some tokens to the portfolio on which they do not make a big bet, and you can go to all in. - Always analyze your media field with critical thinking. Analyze the information from the point of view of who and why start talk about this exactly now!? - Work with proper risks and invest according to your strategy - Do not invest in all sectors, choose a few of the most promising for you, and several tokens in each sector - Always filter who you read on social networks. millionaire influencers very often made capital not with trading) Hope you enjoyed the content I created, You can support with your likes and comments this idea so more people can watch! ✅Disclaimer: Please be aware of the risks involved in trading. This idea was made for educational purposes only not for financial Investment Purposes. --- • Look at my ideas about interesting altcoins in the related section down below ↓ • For more ideas please hit "Like" and "Follow"!

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by Crypto4light

Bubble theory 🫧 BTC miners There are two type of bubbles and they burst for different reasons? A bubble is when too many people hold something and what has driven prices up, now as a force works against them. There's a saying. Buy things when everyone is a skeptic. Sell when a taxi driver starts talking about investing. There are no more buyers left on top. First bubble is when volume dries up as the price hits extremes. Second is when peoples attitudes or sentiment, or opinions change to bearish. And that can happen over night, like a switch. It's interesting and finance is a social science. Some bubbles can burst due to external events, like start of wars or some financial crisis. There can be strong bull markets and most of times, these external events would just be noise? > Was btc miners in bubble? And what type of bubble? I think Yes and No? Whenever there's a risk free trade, supported by factors a bubble emerges? The price of Mara was rallying hard, trend was strong. You could argue people got over optimistic, knowing the ETF decision was a risk event. -> therefor (the burst) was sentiment driven. But also predictable? Bubble is when too many people hold asset and there re no buyers left. Similar how a taxi driver is hype about investing. Technical analysis gives you perspective and context. In 1st instance, impulse was too high and volume indicates crowding? It's tricky because it looks so bullish. In 2nd instance, impulse was too low. Price action looked bullish? bubbles happen when too many people hold the shares and expect them to rise. If 1st instance was sentiment switch driven, then 2nd time, the bubble must burst due to exhaustion (or no people left to buy... at these prices.. similar how taxi driver hops in the trade at the wrong time). Factors and thesis can be bullish - and bubble still bursts. Is NVDA and SMCI a bubble? I think there is difference between NVDA, SMCI investors and their time horizon? It could be. I think people believe their investment is supported by the tech drivers. Every dip should be bought out by smart investors and these are the best assets to own in next 5-10 years. It doesnt mean there cant be external events and risks. again- bubble is when too many people are in investment. So bubble can burst either by them changing their sentiment or beliefs (maybe fundamentals must change?). Or if price is just so ridiculously high or there is no money left at sidelines, that trend can't be sustainable. When markets rally - everyone only reads good news and ignores bad news. And vice versa. #HowardMarks #MarketCycle ---> The Risk-Reward buying at these tops just isn't great. That's why they burst. Accompanied by sentiment risks, that hide behind the hood.

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HOW TO $1k to $12.4mil in 83 trades on BTCUSD1D BITFINEX w/ NSV4 Through an analysis of 83 trades, NSV4 ('Ninja Signals V4' by BitcoinNinjas.org) has demonstrated its ability to turn a modest $1,000 investment into an impressive $12.4 million, showcasing remarkable potential. In this particular configuration, NSV4 massively outperformed almost any other strategy including the traditional 'buy and hold' in the backtesting of this example. This chart specifically provides insights and a deeper understanding of the effectiveness and potential of this indicator. It is one of the single best charts ever backtested for Ninja Signals. We have spent years receiving feedback from users and cultivating our script while backtesting different charts and timeframes to achieve this level of success. The reliability and continual profit over time for 10+ years is astounding in this particular case! This configuration is unique to this exchange, although is likely to achieve similar results on other exchanges (trading the same pair and the same time interval), perhaps needing only a few minor tweaks. Let us dissect NSV4's performance and discover the principles that have made it a game-changer. How is it possible to turn 1k into 12.4m in 83 trades? First of all, you can see that the first trade was in 2013, so these settings are backtested for over 10 years. This didn't happen over night. Also, this configuration adds the profit of the previous trade to the next trade. On a bot, this would equate to using the entire balance of the account with each trade, and continually increasing the trade amount as profit accrues. Here, we are 'compounding the interest' and using 100% of the trade balance for each trade. This is referred to as "Compounding". We always make sure that a configuration is highly profitable with compounding OFF before we turn it on. In this case, the results are magical. When we are backtesting for the best configurations, there are a few things to keep in mind, these principles are true for any Alerts generating indicator: 1) Has it traded recently, within the last few months? (Yes) 2) Has it been profitable each year if only traded for that year? (Yes) 3) Has it broke even or performed well in a bear market? (Yes) As you can see, this configuration has traded recently, It also meets all of the other criteria. Therefore, this would suffice as a tradeable config in our eyes. In short, why is this pack so successful? 1) Compounding. 2) Long trading history (10yr+). 3) Low SL (Stop Loss) of 6 prevents losing large amounts and keeps trades tight. 4) The results without compounding are stellar to begin with, good start, good finish. 5) Years of backtesting experience from our team culminates in epic configurations. The 1D chart equates to a longer period of time between trades than most people are used to, which results in approx 1 trade per 1-2 months. Most people are looking for quick scalping trades but as you can see here, NSV4 has steadily outperformed almost any strategy using complex combinations of basic trading principles and trading for a long period of time. The tortoise wins the race, in this case. We generally like to use NSV4 between 60m and 1D, anywhere in between. Sometime obscure timeframes such as 177m or 431min seem to do well. It takes time backtesting to find the best results, as with any script. Do you know of any other Alerts generating indicators on TradingView that have achieved this level of success? I haven't found any yet! I am anxious to try these settings and to keep testing! -spiftheninja PROFIT WHILE YOU SLEEP

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by Bitcoin_Ninjas

Crypto Regulations: How MiCA Will Affect EU Traders In the rapidly evolving world of cryptocurrency, the European Union has taken a significant and important step forward with the introduction of the Markets in Crypto-Assets Regulation (MiCA). This groundbreaking regulatory framework marks a pivotal moment for the crypto market within the EU, promising to bring much-needed clarity and stability to an industry that has long been likened to the Wild West due to its volatility and lack of standardization. The European Union is a leader in creating legislation for emerging technologies. This became clear with the introduction of GDPR, which protects internet users’ personal data, the AI Act that aims to protect citizens of the EU from malpractice, such as cognitive manipulation of people and social scoring, and now - MiCA. Paving the way forward for others, the EU is evolving its digital legislation frameworks faster than other unions or countries. This article delves into how MiCA will reshape the landscape for EU traders, impacting everything - from the way they interact with crypto assets to the broader market dynamics they navigate daily. Why do we need regulations like MiCA? If there are no regulations, markets can run wild and experience giant increases, however when the fun is over and people lose money to fraud and even large-scale bankruptcy of exchanges - investors, especially institutional ones, will not dare place their money in crypto projects and companies. And since for investors, money is trust - the cryptocurrency market is doomed without proper regulation. On the flip side, extremely stringent and disorganized legislation can lead to the same outcome. Countries struggle with the abstract nature of cryptocurrencies, and many have expressed an outright desire to ban them, seeing as it is the easier option. That is why MiCA is a well-devised framework for others to follow - It is focused and comprehensive. Some may argue that cryptocurrencies are meant to be decentralized, unregulated and follow a laissez-faire approach. While this is possible, more so for some cryptocurrencies than others, there can be no growth in these markets as new projects need to have banking and investors behind them to realize their blockchain-based ideas. It is also unrealistic to think that such a clandestine financial system will never cross paths with the regular banking system. What exactly is MiCA? The inception of the Markets in Crypto-Assets Regulation (MiCA) is rooted in the European Union's recognition of the growing significance of cryptocurrencies and the associated risks in an unregulated environment. The primary catalyst for MiCA's development was the need for regulatory clarity in the burgeoning crypto market, which had been expanding rapidly without a standardized regulatory framework since the birth of Bitcoin in 2009. This lack of regulation posed risks such as fraud, market manipulation and financial instability. These concerns were heightened by incidents like the surge in initial coin offerings (ICOs), the capitulation of multiple large exchanges and the ironic instability of stable-coins. MiCA was proposed to provide a harmonized regulatory framework for crypto-assets that are not covered under existing EU financial legislation. The objective was to safeguard investors, maintain financial stability, and promote innovation within a secure and transparent environment. By introducing clear rules, MiCA aims to legitimize the crypto market, making it safer and more attractive for investors and consumers while mitigating the potential for financial crime and market manipulation. This move towards regulation reflects a global trend of governments and financial authorities worldwide striving to balance the benefits of innovation in the digital asset space with the need for consumer protection and market integrity. As such, MiCA represents a significant step by the EU in establishing a comprehensive regulatory regime for crypto-assets, setting a precedent that could influence global standards in cryptocurrency regulation. Key Points of MiCA MiCA introduces several key provisions that are set to transform the crypto-asset landscape in the European Union. The areas that are discussed and regulated the most are the areas where incidents have happened and people have lost their funds. It is important not to make the same mistakes as before. Exchanges & Brokerages One of the primary aspects of MiCA is the establishment of stringent authorization requirements for crypto-asset service providers. Under MiCA, any entity aiming to offer services related to crypto-assets, including trading, custody, or advisory services, must obtain authorization from one of the EU's national financial regulators. This process is designed to ensure that providers adhere to high standards of operational conduct, governance, and consumer protection outlined in the legislation. Crypto exchanges have gone bankrupt, been hacked or shut down abruptly in crypto’s short history. The aim of legislatures is to prevent these collapses or stop them in their tracks. Initial Public / Coin Offerings Another fundamental component of MiCA is the regulation of public offerings of crypto-assets. Companies intending to offer crypto-assets to the public are required to publish a detailed white paper. This document must provide clear, fair, and comprehensive information about the risks involved, ensuring that potential buyers are well-informed. The regulations aim to prevent misleading practices and enhance transparency in the market. Until now, many ICOs do publish white papers, however they can be purely fictional, written to trick the untrained eye into thinking the project is professionally done. Furthermore, this official process of submitting a white paper will ensure that the people behind the project are known. This will prevent people from faking their identities in order to anonymously scam their clients. Stablecoins MiCA also specifically addresses the regulation of stablecoins, which are categorized as either e-money tokens (EMTs) or asset-referenced tokens (ARTs). EMTs are stablecoins pegged to the value of a fiat currency, such as USDT, USDC and BUSD. ARTs are linked to other assets, such as WETH, WBTC. MiCA mandates that stablecoins must maintain adequate reserves and adhere to governance standards. Furthermore, there are stringent rules for stablecoins not pegged to EU currencies, including a cap on the number of transactions per day, aimed at preventing these assets from undermining the Euro. This approach to stablecoins is a response to concerns about their potential impact on financial stability and monetary policy. These concerns are justified, following the collapse of a few large market cap stable-coins during 2022. Through these provisions, MiCA aims to establish a secure and transparent environment for the trading and use of crypto-assets, ensuring that the rights of investors are protected while fostering innovation in the sector. Conclusion The introduction of MiCA by the European Union represents a watershed moment for the crypto-asset market. By establishing a harmonized regulatory framework, MiCA seeks to provide clarity, enhance market integrity, and protect investors, all while fostering an environment conducive to innovation. For EU traders, these regulations offer a more secure and transparent trading landscape, albeit with increased compliance obligations. The provisions on stablecoins, in particular, demonstrate a nuanced approach to different types of crypto-assets. As MiCA comes into full effect, its influence is expected to extend beyond the EU, potentially setting a precedent for global crypto-asset regulation. For traders and investors, staying informed and adapting to these regulatory changes will be key to navigating the evolving crypto market landscape.

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Why the Bitcoin Halving Historically Increases Price The bitcoin halving, which occurs every four years, is encoded into Bitcoin itself. Its purpose is to cut in half the amount of Bitcoin that is rewarded for every block that is mined, meaning you must double the processing power every four years to mine the same amount of Bitcoin. (A block reward refers to the number of bitcoins you get if you successfully mine a block of the currency . Investopedia 2023 ) This means that it becomes twice as hard for bitcoin miners to mine the same amount of bitcoin they were mining four years earlier with the same hardware. This creates what is known as a drop in supply or supply shock, where market demand either stays the same or increases, and the price of bitcoin must increase to meet the demand. If the demand stays the same or increases, the price still has to increase because the supply of bitcoin being mined daily is half what it was in the previous four years. There are fewer coins to buy, so the market must compete by paying higher prices. Because this event is exponential, eventually hardware will not be able to keep up with the halving if miners want to be profitable. This may seem like an oversimplification of the most basic economic principles. However, that is what is fundamentally encoded into bitcoin, which guarantees an increase in price by cutting supply every four years (guaranteed only if demand stays the same or increases). That is why bitcoin halving is referred to as a market-moving event, because not only historically has it proven to increase prices and cut supply, but fundamentally it has too. Now let’s look at a real-life example for comparison. Gold does have real-world use in technology and jewelry. However, its main value and use are as a store of value. Most gold is bought and accumulated because it will retain its value, which is the same use case as bitcoin. What do you think would happen if the entire gold production market was slashed in half overnight and this process was repeated every four years? The price of gold would increase exponentially as the finite resource becomes more and more scarce because it is harder to mine. Now apply the same logic to bitcoin, and hopefully you will begin to see the picture. The next bitcoin has just under 60 days coming up in mid-April 2024, so mark your calendars.

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by altsandislands

Crypto Market Cap vs BTC ETH USDT This chart shows the market capitalization of all altcoins vs Ethereum, Bitcoin, and USDT. This will help you figure out where the money in crypto is going at any given time, so that you will have an informed decision on where to put your crypto in too.

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Imbalance Expert : Guide for mastering imabalance's Cryptocurrency trading is an intricate dance, where understanding and interpreting market imbalances can provide traders with a competitive edge. This comprehensive guide aims to demystify the art of trading imbalances, catering to both beginners and seasoned traders. Through a detailed exploration of strategies and considerations, we'll delve into the world of market dynamics, emphasizing the importance of a holistic approach to trading. First example has cool reason to go higher ( EQUAL HIGHS ) and big liquidity pool below Section 1: Understanding Imbalances 1.1 Defining Market Imbalances: Explore the concept of imbalances in the cryptocurrency market. Differentiate between bullish and bearish imbalances. 1.2 Reading the Signs: Learn to identify imbalances on various timeframes. Utilize technical indicators and chart patterns to confirm imbalances. Section 2: The Anatomy of Imbalance Trading 2.1 Spotting Imbalances in Price Action: Analyze real-world examples of imbalances using provided screenshots. Understand how imbalances manifest in different market conditions. 2.2 Tools of the Trade: Explore popular tools like volume analysis, order flow, and market profile to complement imbalance trading. Highlight the role of moving averages and trendlines in confirming imbalances. Section 3: Strategies for Imbalance Trading 3.1 Swing Trading with Imbalances: Discover how to swing trade using imbalances as entry and exit signals. Explore risk management techniques tailored for swing trading. 3.2 Scalping Opportunities: Uncover strategies for intraday trading based on short-term imbalances. Discuss the importance of quick decision-making and tight risk control. Section 4: Advanced Considerations 4.1 Macro and Micro Analysis: Emphasize the need to consider both macroeconomic trends and micro-level price action. Discuss how macroeconomic events can create imbalances with lasting effects. 4.2 Market Sentiment and News Analysis: Incorporate sentiment analysis and news events into the overall imbalance trading strategy. Understand how sudden shifts in sentiment can create imbalances. Section 5: Risk Management and Psychology 5.1 Risk Management Strategies: Explore risk management techniques specific to trading imbalances. Discuss the importance of position sizing and setting stop-loss orders. 5.2 Mastering Emotional Discipline: Address the psychological aspects of trading and how emotions can impact decision-making. Provide practical tips for maintaining discipline during trading. Conclusion: The Art and Science of Imbalance Trading In conclusion, mastering the art of trading imbalances requires a combination of technical expertise, strategic thinking, and emotional resilience. Whether you are a beginner looking to enter the world of cryptocurrency trading or a seasoned trader seeking new insights, this guide aims to equip you with the knowledge and tools necessary to navigate the dynamic landscape of imbalance trading. Remember, success in trading is an ongoing journey that requires continuous learning and adaptation to evolving market conditions. 💡 Imbalances Decoded | 📊 Tools of the Trade | 🚀 Strategies for Success | 🧠 Risk Management Mastery 💬 Share your insights: What are your experiences with trading imbalances, and what additional strategies have you found effective? 🌐✨

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by Yaroslav_Krasko

Never trade on news. Everything is hidden in the price action !Everyone was looking for ETF confirmation to get long. But the market turned red! US SEC grants approval for spot bitcoin ETFs - RTRS but the market moved against expectations. This is why we say never trade with fundamental news. Everything is hidden in the price action. Bitcoin had reached the ceiling of the channel and also our indicator had given a short signal. So, contrary to all positions, we opened the shorts and had fun!

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Altseason Indicator. Capitalization excluding BTC ETH USDT USDC Logarithm. Time Frame 1 week. Understanding the capitalization and growth potential of altcoins without BTC ETH and top steiblcoins USDT, USDC and DAI gives a brighter and more accurate picture of the timing of the start and development of that long-awaited altcoin season of more pronounced scale than now on 16 10 2023 - at the time of publication 8 12 2023. 1) The capitalization of these assets has long been in a squeeze - consolidation, this is a direct correlation with the accumulation zones. We are conventionally in the final phase of accumulation (almost). 2) Please note that there has been no real capitulation (perhaps there will not be, and if there is, it will be V figuratively, but that is not the point). Very much emphasize your attention to the timing of the length of this phase and past late 2018 and 2020. 3) Also note to your eye that at that time 2018-2020 there was not such a big capitalization outperformance from the rest of the BTC and ETH market. Compare that to the situation now, how much other altcoins are "undervalued" speculatively. You also need to realize that there is a correlation with stablecoins and their huge portion of the overall market compared to the time before. How to enter these parameters on tradingview? . In order to capitalize alts from TOTAL3 (initially without capitalization of BTC and ETH) and exclude all large-capitalization stablecoins from it, you need to do the following: In the ticker entry line in tradingview write: CRYPTOCAP:TOTAL3-CRYPTOCAP:USDT-CRYPTOCAP:USDC-CRYPTOCAP:DAI . Accordingly, a chart is created that subtracts the capitalization of the designated stablecoins (USDT, USDC, DAI) from TOTAL 3.

Education

Updated

Algorithmic vs. Manual Trading - Which Strategy Reigns Supreme Intro: In the dynamic world of financial markets, trading strategies have evolved significantly over the years. With advancements in technology and the rise of artificial intelligence (AI), algorithmic trading, also known as algo trading, has gained immense popularity. Algo trading utilizes complex algorithms and automated systems to execute trades swiftly and efficiently, offering numerous advantages over traditional manual trading approaches. In this article, we will explore the advantages and disadvantages of algo trading compared to manual trading, providing a comprehensive overview of both approaches. We will delve into the speed, efficiency, emotion-free decision making, consistency, scalability, accuracy, backtesting capabilities, risk management, and diversification offered by algo trading. Additionally, we will discuss the flexibility, adaptability, intuition, experience, emotional intelligence, and creative thinking that manual trading brings to the table. Advantages of Algo trading: Speed and Efficiency: One of the primary advantages of algo trading is its remarkable speed and efficiency. With algorithms executing trades in milliseconds, algo trading eliminates the delays associated with manual trading. This speed advantage enables traders to capitalize on fleeting market opportunities and capture price discrepancies that would otherwise be missed. By swiftly responding to market changes, algo trading ensures that traders can enter and exit positions at optimal prices. Emotion-Free Decision Making: Humans are prone to emotional biases, which can cloud judgment and lead to irrational investment decisions. Algo trading removes these emotional biases by relying on pre-programmed rules and algorithms. The algorithms make decisions based on logical parameters, objective analysis, and historical data, eliminating the influence of fear, greed, or other human emotions. As a result, algo trading enables more disciplined and objective decision-making, ultimately leading to better trading outcomes. Consistency: Consistency is a crucial factor in trading success. Algo trading provides the advantage of maintaining a consistent trading approach over time. The algorithms follow a set of predefined rules consistently, ensuring that trades are executed in a standardized manner. This consistency helps traders avoid impulsive decisions or deviations from the original trading strategy, leading to a more disciplined approach to investing. Enhanced Scalability: Traditional manual trading has limitations when it comes to scalability. As trade volumes increase, it becomes challenging for traders to execute orders efficiently. Algo trading overcomes this hurdle by automating the entire process. Algorithms can handle a high volume of trades across multiple markets simultaneously, ensuring scalability without compromising on execution speed or accuracy. This scalability empowers traders to take advantage of diverse market opportunities without any operational constraints. Increased Accuracy: Algo trading leverages the power of technology to enhance trading accuracy. The algorithms can analyze vast amounts of market data, identify patterns, and execute trades based on precise parameters. By eliminating human error and subjectivity, algo trading increases the accuracy of trade execution. This improved accuracy can lead to better trade outcomes, maximizing profits and minimizing losses. Backtesting Capabilities and Optimization: Another significant advantage of algo trading is its ability to backtest trading strategies. Algorithms can analyze historical market data to simulate trading scenarios and evaluate the performance of different strategies. This backtesting process helps traders optimize their strategies by identifying patterns or variables that generate the best results. By fine-tuning strategies before implementing them in live markets, algo traders can increase their chances of success. Automated Risk Management: Automated Risk Management: Managing risk is a critical aspect of trading. Algo trading offers automated risk management capabilities that can be built into the algorithms. Traders can program specific risk parameters, such as stop-loss orders or position sizing rules, to ensure that losses are limited and positions are appropriately managed. By automating risk management, algo trading reduces the reliance on manual monitoring and helps protect against potential market downturns. Diversification: Diversification: Algo trading enables traders to diversify their portfolios effectively. With algorithms capable of simultaneously executing trades across multiple markets, asset classes, or strategies, traders can spread their investments and reduce overall risk. Diversification helps mitigate the impact of individual market fluctuations and can potentially enhance long-term returns. Removal of Emotional Biases: Finally, algo trading eliminates the influence of emotional biases that often hinder trading decisions. Fear, greed, and other emotions can cloud judgment and lead to poor investment choices. Byrelying on algorithms, algo trading removes these emotional biases from the decision-making process. This objective approach helps traders make more rational and data-driven decisions, leading to better overall trading performance. Disadvantage of Algo Trading System Vulnerabilities and Risks: One of the primary concerns with algo trading is system vulnerabilities and risks. Since algo trading relies heavily on technology and computer systems, any technical malfunction or system failure can have severe consequences. Power outages, network disruptions, or software glitches can disrupt trading operations and potentially lead to financial losses. It is crucial for traders to have robust risk management measures in place to mitigate these risks effectively. Technical Challenges and Complexity: Technical Challenges and Complexity: Algo trading involves complex technological infrastructure and sophisticated algorithms. Implementing and maintaining such systems require a high level of technical expertise and resources. Traders must have a thorough understanding of programming languages and algorithms to develop and modify trading strategies. Additionally, monitoring and maintaining the infrastructure can be challenging and time-consuming, requiring continuous updates and adjustments to keep up with evolving market conditions. Over-Optimization: Another disadvantage of algo trading is the risk of over-optimization. Traders may be tempted to fine-tune their algorithms excessively based on historical data to achieve exceptional past performance. However, over-optimization can lead to a phenomenon called "curve fitting," where the algorithms become too specific to historical data and fail to perform well in real-time market conditions. It is essential to strike a balance between optimizing strategies and ensuring adaptability to changing market dynamic Over Reliance on Historical Data: Algo trading heavily relies on historical data to generate trading signals and make decisions. While historical data can provide valuable insights, it may not always accurately reflect future market conditions. Market dynamics, trends, and relationships can change over time, rendering historical data less relevant. Traders must be cautious about not relying solely on past performance and continuously monitor and adapt their strategies to current market conditions. Lack of Adaptability: Another drawback of algo trading is its potential lack of adaptability to unexpected market events or sudden changes in market conditions. Algo trading strategies are typically based on predefined rules and algorithms, which may not account for unforeseen events or extreme market volatility. Traders must be vigilant and ready to intervene or modify their strategies manually when market conditions deviate significantly from the programmed rules. Advantages of Manual Trading Flexibility and Adaptability: Manual trading offers the advantage of flexibility and adaptability. Traders can quickly adjust their strategies and react to changing market conditions in real-time. Unlike algorithms, human traders can adapt their decision-making process based on new information, unexpected events, or emerging market trends. This flexibility allows for agile decision-making and the ability to capitalize on evolving market opportunities. Intuition and Experience: Human traders possess intuition and experience, which can be valuable assets in the trading process. Through years of experience, traders develop a deep understanding of the market dynamics, patterns, and interrelationships between assets. Intuition allows them to make informed judgments based on their accumulated knowledge and instincts. This human element adds a qualitative aspect to trading decisions that algorithms may lack. Complex Decision-making: Manual trading involves complex decision-making that goes beyond predefined rules. Traders analyze various factors, such as fundamental and technical indicators, economic news, and geopolitical events, to make well-informed decisions. This ability to consider multiple variables and weigh their impact on the market enables traders to make nuanced decisions that algorithms may overlook. Emotional Intelligence and Market Sentiment: Humans possess emotional intelligence, which can be advantageous in trading. Emotions can provide valuable insights into market sentiment and investor psychology. Human traders can gauge market sentiment by interpreting price movements, news sentiment, and market chatter. Understanding and incorporating market sentiment into decision-making can help traders identify potential market shifts and take advantage of sentiment-driven opportunities. Contextual Understanding: Manual trading allows traders to have a deep contextual understanding of the markets they operate in. They can analyze broader economic factors, political developments, and industry-specific dynamics to assess the market environment accurately. This contextual understanding provides traders with a comprehensive view of the factors that can influence market movements, allowing for more informed decision-making. Creative and Opportunistic Thinking: Human traders bring creative and opportunistic thinking to the trading process. They can spot unique opportunities that algorithms may not consider. By employing analytical skills, critical thinking, and out-of-the-box approaches, traders can identify unconventional trading strategies or undervalued assets that algorithms may overlook. This creative thinking allows traders to capitalize on market inefficiencies and generate returns. Complex Market Conditions: Manual trading thrives in complex market conditions that algorithms may struggle to navigate. In situations where market dynamics are rapidly changing, volatile, or influenced by unpredictable events, human traders can adapt quickly and make decisions based on their judgment and expertise. The ability to think on their feet and adjust strategies accordingly enables traders to navigate challenging market conditions effectively. Disadvantage of Manual Trading Emotional Bias: Algo trading lacks human emotions, which can sometimes be a disadvantage. Human traders can analyze market conditions based on intuition and experience, while algorithms solely rely on historical data and predefined rules. Emotional biases, such as fear or greed, may play a role in decision-making, but algorithms cannot factor in these nuanced human aspects. Time and Effort: Implementing and maintaining algo trading systems require time and effort. Developing effective algorithms and strategies demands significant technical expertise and resources. Traders need to continuously monitor and update their algorithms to ensure they remain relevant in changing market conditions. This ongoing commitment can be time-consuming and may require additional personnel or technical support. Execution Speed: While algo trading is known for its speed, there can be challenges with execution. In fast-moving markets, delays in order execution can lead to missed opportunities or less favorable trade outcomes. Algo trading systems need to be equipped with high-performance infrastructure and reliable connectivity to execute trades swiftly and efficiently. Information Overload: In today's digital age, vast amounts of data are available to traders. Algo trading systems can quickly process large volumes of information, but there is a risk of information overload. Filtering through excessive data and identifying relevant signals can be challenging. Traders must carefully design algorithms to focus on essential information and avoid being overwhelmed by irrelevant or noisy data. The Power of AI in Enhancing Algorithmic Trading: Data Analysis and Pattern Recognition: AI algorithms excel at processing vast amounts of data and recognizing patterns that may be difficult for human traders to identify. By analyzing historical market data, news, social media sentiment, and other relevant information, AI-powered algorithms can uncover hidden correlations and trends. This enables traders to develop more robust trading strategies based on data-driven insights. Predictive Analytics and Forecasting: AI algorithms can leverage machine learning techniques to generate predictive models and forecasts. By training on historical market data, these algorithms can identify patterns and relationships that can help predict future price movements. This predictive capability empowers traders to anticipate market trends, identify potential opportunities, and adjust their strategies accordingly. Real-time Market Monitoring: AI-based systems can continuously monitor real-time market data, news feeds, and social media platforms. This enables traders to stay updated on market developments, breaking news, and sentiment shifts. By incorporating real-time data into their algorithms, traders can make faster and more accurate trading decisions, especially in volatile and rapidly changing market conditions. Adaptive and Self-Learning Systems: AI algorithms have the ability to adapt and self-learn from market data and trading outcomes. Through reinforcement learning techniques, these algorithms can continuously optimize trading strategies based on real-time performance feedback. This adaptability allows the algorithms to evolve and improve over time, enhancing their ability to generate consistent returns and adapt to changing market dynamics. Enhanced Decision Support: AI algorithms can provide decision support tools for traders, presenting them with data-driven insights, risk analysis, and recommended actions. By combining the power of AI with human expertise, traders can make more informed and well-rounded decisions. These decision support tools can assist in portfolio allocation, trade execution, and risk management, enhancing overall trading performance. How Algorithmic Trading Handles News and Events? In the fast-paced world of financial markets, news and events play a pivotal role in driving price movements and creating trading opportunities. Algorithmic trading has emerged as a powerful tool to capitalize on these dynamics. Automated News Monitoring: Algorithmic trading systems are equipped with the capability to automatically monitor news sources, including financial news websites, press releases, and social media platforms. By utilizing natural language processing (NLP) and sentiment analysis techniques, algorithms can filter through vast amounts of news data, identifying relevant information that may impact the market. Real-time Data Processing: Algorithms excel in processing real-time data and swiftly analyzing its potential impact on the market. By integrating news feeds and other event-based data into their models, algorithms can quickly evaluate the relevance and potential market significance of specific news or events. This enables traders to react promptly to emerging opportunities or risks. Event-driven Trading Strategies: Algorithmic trading systems can be programmed to execute event-driven trading strategies. These strategies are designed to capitalize on the market movements triggered by specific events, such as economic releases, corporate earnings announcements, or geopolitical developments. Algorithms can automatically scan for relevant events and execute trades based on predefined criteria, such as price thresholds or sentiment analysis outcomes. Sentiment Analysis: Sentiment analysis is a crucial component of news and event-based trading. Algorithms can analyze news articles, social media sentiment, and other textual data to assess market sentiment surrounding a specific event or news item. By gauging positive or negative sentiment, algorithms can make informed trading decisions and adjust strategies accordingly. Backtesting and Optimization: Algorithmic trading allows for backtesting and optimization of news and event-driven trading strategies. Historical data can be used to test the performance of trading models under various news scenarios. By analyzing the past market reactions to similar events, algorithms can be fine-tuned to improve their accuracy and profitability. Algorithmic News Trading: Algorithmic news trading involves the automatic execution of trades based on predefined news triggers. For example, algorithms can be programmed to automatically buy or sell certain assets when specific news is released or when certain conditions are met. This automated approach eliminates the need for manual monitoring and ensures swift execution in response to news events. Risk Management: Algorithmic trading systems incorporate risk management measures to mitigate the potential downside of news and event-driven trading. Stop-loss orders, position sizing algorithms, and risk management rules can be integrated to protect against adverse market movements or unexpected news outcomes. This helps to minimize losses and ensure controlled risk exposure. Flash Crash 2010: A Historic Market Event On May 6, 2010, the financial markets experienced an unprecedented event known as the "Flash Crash." Within a matter of minutes, stock prices plummeted dramatically, only to recover shortly thereafter. This sudden and extreme market turbulence sent shockwaves through the financial world and highlighted the vulnerabilities of an increasingly interconnected and technology-driven trading landscape. The Flash Crash Unfolds: On that fateful day, between 2:32 p.m. and 2:45 p.m. EDT, the U.S. stock market experienced an abrupt and severe decline in prices. Within minutes, the Dow Jones Industrial Average (DJIA) plunged nearly 1,000 points, erasing approximately $1 trillion in market value. Blue-chip stocks, such as Procter & Gamble and Accenture, saw their prices briefly crash to a mere fraction of their pre-crash values. This sudden and dramatic collapse was followed by a swift rebound, with prices largely recovering by the end of the trading session. The Contributing Factors: Several factors converged to create the perfect storm for the Flash Crash. One key element was the increasing prevalence of high-frequency trading (HFT), where computer algorithms execute trades at lightning-fast speeds. This automated trading, combined with the interconnectedness of markets, exacerbated the speed and intensity of the crash. Additionally, the widespread use of stop-loss orders, which are triggered when a stock reaches a specified price, amplified the selling pressure as prices rapidly declined. A lack of adequate market safeguards and regulatory mechanisms further exacerbated the situation. Role of Algorithmic Trading: Algorithmic trading played a significant role in the Flash Crash. As the markets rapidly declined, certain algorithmic trading strategies failed to function as intended, exacerbating the sell-off. These algorithms, designed to capture small price discrepancies, ended up engaging in a "feedback loop" of selling, pushing prices even lower. The speed and automation of algorithmic trading made it difficult for human intervention to effectively mitigate the situation in real-time. Market Reforms and Lessons Learned: The Flash Crash of 2010 prompted significant regulatory and technological reforms aimed at preventing similar events in the future. Measures included the implementation of circuit breakers, which temporarily halt trading during extreme price movements, and revisions to market-wide circuit breaker rules. Market surveillance and coordination between exchanges and regulators were also enhanced to better monitor and respond to unusual trading activity. Additionally, the incident highlighted the need for greater transparency and scrutiny of algorithmic trading practices. Implications for Market Stability: The Flash Crash served as a wake-up call to market participants and regulators, underscoring the potential risks associated with high-frequency and algorithmic trading. It highlighted the importance of ensuring that market infrastructure and regulations keep pace with technological advancements. The incident also emphasized the need for market participants to understand the intricacies of the trading systems they employ, and for regulators to continually evaluate and adapt regulatory frameworks to address emerging risks. The Flash Crash of 2010 stands as a pivotal moment in financial market history, exposing vulnerabilities in the increasingly complex and interconnected world of electronic trading. The event triggered significant reforms and led to a greater focus on market stability, transparency, and risk management. While strides have been made to enhance market safeguards and regulatory oversight, ongoing vigilance and continuous adaptation to technological advancements are necessary to maintain the integrity and stability of modern financial markets. How Algorithmic Trading Thrives in Changing Markets? Algorithmic trading (ALGO) can tackle changing market conditions through various techniques and strategies that allow algorithms to adapt and respond effectively. Here are some ways ALGO can address changing market conditions: Real-Time Data Analysis: Algo systems continuously monitor market data, including price movements, volume, news feeds, and economic indicators, in real-time. By analyzing this data promptly, algorithms can identify changing market conditions and adjust trading strategies accordingly. This enables Algo to capture opportunities and react to market shifts more rapidly than human traders. Dynamic Order Routing: Algo systems can dynamically route orders to different exchanges or liquidity pools based on prevailing market conditions. By assessing factors such as liquidity, order book depth, and execution costs, algorithms can adapt their order routing strategies to optimize trade execution. This flexibility ensures that algo takes advantage of the most favorable market conditions available at any given moment. Adaptive Trading Strategies: Algo can utilize adaptive trading strategies that are designed to adjust their parameters or rules based on changing market conditions. These strategies often incorporate machine learning algorithms to continuously learn from historical data and adapt to evolving market dynamics. By dynamically modifying their rules and parameters, algo systems can optimize trading decisions and capture opportunities across different market environments. Volatility Management: Changing market conditions often come with increased volatility. Algo systems can incorporate volatility management techniques to adjust risk exposure accordingly. For example, algorithms may dynamically adjust position sizes, set tighter stop-loss levels, or modify risk management parameters based on current market volatility. These measures help to control risk and protect capital during periods of heightened uncertainty. Pattern Recognition and Statistical Analysis: Algo systems can employ advanced pattern recognition and statistical analysis techniques to identify recurring market patterns or anomalies. By recognizing these patterns, algorithms can make informed trading decisions and adjust strategies accordingly. This ability to identify and adapt to patterns helps algocapitalize on recurring market conditions while also remaining adaptable to changes in market behavior. Backtesting and Simulation: Algo systems can be extensively backtested and simulated using historical market data. By subjecting algorithms to various market scenarios and historical data sets, traders can evaluate their performance and robustness under different market conditions. This process allows for fine-tuning and optimization of algo strategies to better handle changing market dynamics. In summary, algo tackles changing market conditions through real-time data analysis, dynamic order routing, adaptive trading strategies, volatility management, pattern recognition, statistical analysis, and rigorous backtesting. By leveraging these capabilities, algo can effectively adapt to evolving market conditions and capitalize on opportunities while managing risks more efficiently than traditional trading approaches The Rise of Algo Traders: Is Technical Analysis Losing Ground? Although algorithmic trading (algo trading) can automate and optimize certain elements of technical analysis, it is improbable that it will fully substitute it. Technical analysis is a financial discipline that encompasses the examination of historical price and volume data, chart patterns, indicators, and other market variables to inform trading strategies. There are several reasons why algo traders cannot entirely supplant technical analysis: Interpretation of Market Psychology: Technical analysis incorporates the understanding of market psychology, which is based on the belief that historical price patterns repeat themselves due to human behavior. It involves analyzing investor sentiment, trends, support and resistance levels, and other factors that can influence market movements. Algo traders may use technical indicators to identify these patterns, but they may not fully capture the nuances of market sentiment and psychological factors. Subjectivity in Analysis: Technical analysis often involves subjective interpretation by traders, as different individuals may analyze the same chart or indicator differently. Algo traders rely on predefined rules and algorithms that may not encompass all the subjective elements of technical analysis. Human traders can incorporate their experience, intuition, and judgment to make nuanced decisions that may not be easily captured by algorithms. Market Adaptability: Technical analysis requires the ability to adapt to changing market conditions and adjust strategies accordingly. While algorithms can be programmed to adjust certain parameters based on market data, they may not possess the same adaptability as human traders who can dynamically interpret and respond to evolving market conditions in real-time. Unpredictable Events: Technical analysis is often challenged by unexpected events, such as geopolitical developments, economic announcements, or corporate news, which can cause significant market disruptions. Human traders may have the ability to interpret and react to these events based on their knowledge and understanding, while algo traders may struggle to respond effectively to unforeseen circumstances. Fundamental Analysis: Technical analysis primarily focuses on price and volume data, while fundamental analysis considers broader factors such as company financials, macroeconomic indicators, industry trends, and news events. Algo traders may not have the capacity to analyze fundamental factors and incorporate them into their decision-making process, which can limit their ability to fully replace technical analysis. In conclusion, while algo trading can automate certain elements of technical analysis, it is unlikely to replace it entirely. Technical analysis incorporates subjective interpretation, market psychology, adaptability, and fundamental factors that may be challenging for algorithms to fully replicate. Human traders with expertise in technical analysis and the ability to interpret market dynamics will continue to play a significant role in making informed trading decisions. The Ultimate Winner - Algo Trading or Manual Trading? Determining whether algo trading or manual trading is best depends on various factors, including individual preferences, trading goals, and skill sets. Both approaches have their advantages and limitations, and what works best for one person may not be the same for another. Let's compare the two: Speed and Efficiency: Algo trading excels in speed and efficiency, as computer algorithms can analyze data and execute trades within milliseconds. Manual trading involves human decision-making, which may be subject to cognitive biases and emotional factors, potentially leading to slower execution or missed opportunities. Emotion and Discipline: Algo trading eliminates emotional biases from trading decisions, as algorithms follow predefined rules without being influenced by fear or greed. Manual trading requires discipline and emotional control to make objective decisions, which can be challenging for some traders. Adaptability: Algo trading can quickly adapt to changing market conditions and execute trades based on pre-programmed rules. Manual traders can adapt their strategies as well, but it may require more time and effort to monitor and adjust to rapidly evolving market dynamics. Complexity and Technical Knowledge: Algo trading requires programming skills or the use of algorithmic platforms, which can be challenging for traders without a technical background. Manual trading, on the other hand, relies on an understanding of fundamental and technical analysis, which requires continuous learning and analysis of market trends. Strategy Development: Algo trading allows for systematic and precise strategy development based on historical data analysis and backtesting. Manual traders can develop their strategies as well, but it may involve more subjective interpretations of charts, patterns, and indicators. Risk Management: Both algo trading and manual trading require effective risk management. Algo trading can incorporate predetermined risk management parameters into algorithms, whereas manual traders need to actively monitor and manage risk based on their judgment. Ultimately, the best approach depends on individual circumstances. Some traders may prefer algo trading for its speed, efficiency, and objective decision-making, while others may enjoy the flexibility and adaptability of manual trading. It is worth noting that many traders use a combination of both approaches, utilizing algo trading for certain strategies and manual trading for others. In conclusion, algorithmic trading offers benefits such as speed, efficiency, and risk management, while manual trading provides adaptability and human intuition. AI enhances algorithmic trading by processing data, recognizing patterns, and providing decision support. Algos excel in automated news monitoring and event-driven strategies. However, the Flash Crash of 2010 exposed vulnerabilities in the interconnected trading landscape, with algorithmic trading exacerbating the market decline. It serves as a reminder to implement appropriate safeguards and risk management measures. Overall, a balanced approach that combines the strengths of both algorithmic and manual trading can lead to more effective and resilient trading strategies.

Education

by Money_Dictators

Updated

AI-Assisted Channel Patterns: Visuals for Precision Trading Types of Channel Pattern In this educational post, we won't take a trading position, but rather equip you with valuable insights. Today, we delve into the world of channel chart patterns. Channels come in two primary forms: bullish and bearish. Understanding these patterns is essential. A bullish channel appears as a descending pattern, resembling a falling rectangle, while a bearish channel manifests as an ascending pattern within rising rectangles. Technicals of Channel Patterns But why are these channels so important? Bullish channels often precede a shift from a bearish trend to a bullish one, signaling a shift from a pessimistic to an optimistic market outlook. Conversely, bearish channels frequently herald a move from a bullish trend to a bearish one, indicating a transition from an optimistic to a pessimistic market sentiment. Application of Channel Patterns Channels serve various purposes, from brokers illustrating their expectations to traders preparing for upcoming trends. They also offer an excellent opportunity for automation, as modern AI systems can detect channels with remarkable precision, often exceeding 70%. Our Notes to Channel Patterns However, it's worth noting that channel patterns are seldom used in isolation. To make the most of them, traders often combine AI-assisted channel detection systems with volume analysis. When analyzing BTC-USD markets across nine exchanges and over five years, we found that volume frequently aligns with precisely defined channel patterns. By incorporating volume as a technical indicator and leveraging AI-generated channels, you can enhance your trading strategies and increase your chances of success in the cryptocurrency markets. Best of luck in your trading endeavors! Best regards, ELI

Education

by Elysian_Mind

Volatility Breakout Trading Explained "Welcome to a fascinating journey into the world of trading with the Volatility Breakout Strategy – a method that offers you a glimpse into the wisdom of legendary trader Larry Williams. In this comprehensive guide, we'll unravel the strategy's intricacies step by step, giving you the tools to incorporate it into your own trading style. Disclaimer: Before we dive in, a word of caution. This is not financial advice. It's designed for educational and entertainment purposes only. Your investment decisions should always be made with due diligence, and you bear the responsibility for any profits or losses incurred. Trade and invest wisely. The Volatility Breakout Strategy This time-tested strategy, crafted by the legendary Larry Williams, centers around the idea that trends tend to persist. In other words, what goes up often continues its ascent. The beauty of this strategy lies in its simplicity: Strategy Breakdown: Range Calculation: Begin by calculating the range, which is the difference between the daily high and low prices (Range = High - Low). Base Price: Determine the base price or entry price for the next day. It's calculated as the previous day's candle close plus a constant multiplier (K) times the range. Typically, K hovers around 0.6 to account for market noise. Entry Signal: If the current day's price surpasses the calculated base price, it's your signal to enter a position. Exit: The following day, sell all your positions at the market's open price. Let's Illustrate with an Example: Consider an asset with a daily range of $100. Calculating the base price gives us $1020. If the asset's price surpasses $1020 on the second day, you buy and ride the momentum. On the third day, you sell all positions at the market open. If the price reaches $1100 on the third day, that's a remarkable 7.84% return. Even if it retraces to $1000 at the opening, you still incur only a 1.96% loss. This showcases not just an attractive risk/reward ratio but also a statistical edge thanks to following the trend. Strengths of the Volatility Breakout Strategy: This strategy's strengths lie in its ability to sidestep the emotional rollercoaster of market psychology. By focusing on volatility and executing short-term trades with precise entry and exit points, it enables traders to tune out market noise. Trends, which reflect market psychology, become our allies rather than foes. Unlike reversal strategies, this approach provides a statistical edge and an appealing risk/reward ratio. Conclusion: While applying this strategy directly in today's markets may require some adjustments, understanding how legendary traders like Larry Williams approached the market is invaluable. The key takeaway is to remove emotion from your trading equation, maintain strict rules, and define clear invalidation points. These principles are fundamental to finding success in the dynamic world of trading. If you found this educational post insightful and engaging, don't forget to hit that like button and follow for more high-quality content. Feel free to share your thoughts and questions below—let's navigate the exciting world of trading together!"

Education

by CRYPTOMOJO_TA

Updated

Crypto Market's Time to Shine: ETFs and the Road Ahead Hello, traders! The past week brought some fascinating developments, and I've decided to share my insights and pose a question regarding the recent news. Let's start. In the world of futures ETFs, these financial instruments offer investors the chance to speculate on the price movements of assets like oil or Bitcoin, all without having to possess the underlying asset itself. I can't emphasize this enough – you're betting on the price action, not the asset. Now, let's talk about these future ETFs. They may seem like nothing more than paper contracts, with no direct influence on the spot price of the asset. But here's the kicker: they do wonders for Ethereum's visibility and reach in the market. Moving on to our next point: Ethereum's journey into the ETF realm puts it in fierce competition with Bitcoin for a coveted Spot ETF approval. The race is on, with a queue of filings already forming. Just a short while ago, Grayscale made a significant move by filing to convert their massive $5 billion Ethereum private trust ( OTC:ETHE ) into an ETF. That's a big deal, folks. But here's the thing to remember: while Ethereum ETFs are gaining momentum, the Bitcoin ETFs have been in line for quite some time. We all know that Spot ETFs are the ones that truly matter in this game. So, when can we expect a Bitcoin Spot ETF? Chances are, it's coming soon. Just last week, Congress sent a clear message to Gary Gensler, the SEC Chair, demanding an end to the discrimination against Bitcoin ETFs. They urged Gensler to approve a Spot Bitcoin ETF, arguing that it would protect investors. With BlackRock and Congress throwing their weight behind this, the SEC can't procrastinate indefinitely. That's why we believe that a Bitcoin Spot ETF might arrive sooner than later – possibly even within this year. Keep in mind that the SEC is set to make decisions on seven filings this month. And if they decide to delay, they'll still need to give a final verdict on nine more filings by March 2024. It's highly unlikely that they'll reject all of them. So, in all likelihood, we'll see a Bitcoin Spot ETF by March 2024 at the latest. And once that milestone is reached, an Ethereum Spot ETF might be the next big thing. Now, let's talk about why the crypto and web3 space is looking exceptionally bullish right now. We've got a Bitcoin Spot ETF approaching, backed by BlackRock and Congress. Ethereum is getting a boost from futures ETFs, pushing it further into the traditional finance realm. The macroeconomic environment is improving, and historically, October and November have been bullish months for crypto. Adding to the excitement is the upcoming Bitcoin halving scheduled for April 2024. It's a combination that makes this an incredibly enticing time to be in the markets. Oh, and did I mention that BlackRock is in the running for the Spot Bitcoin ETF? They wield control over a staggering $10 trillion in assets and have a track record of 575-1 for getting ETFs approved by the SEC. So, traders, what are your thoughts on this exciting future?

Education

How To Use Total Market Cap ✨We can use Total Market Cap to analyse when it's best to go bullish or bearish on the crypto market. A growing market cap can indicate investors' interest and their positive evaluation of the current market state = bullish whereas a stagnant market cap would indicate that investors are taking their money away from the crypto market = bearish. By analyzing the Total Crypto Market Cap weekly chart, we can see 5 clear waves to the downside, which means we are either in motive wave 1 or in wave A of a zigzag pattern. For both cases, we are expecting an ABC correction opposite to the recent 5 waves. we have already completed subwave A and finishing now subwave B, expecting subwave C higher. In a zigzag pattern ( 5-3-5) we have: Wave A= 5 waves Wave B = 3 waves Wave C = 5 waves Therefore, our mission for the long term is to catch the impulsive waves of wave C after wave B. But for now will be focusing on catching subwave C of wave B. We will be using this chart as a guide for the other cryptocurrencies charts. Stay tuned for more Crypto analysis!

Education

Investing in Crypto There are approximately 22,932 cryptocurrencies in existence. The image above shows the hundreds of cryptocurrencies on TradingView's crypto coins heat map. Click here to interact with the heat map With so many cryptocurrencies, how does one determine which, if any, are worth investing in? In this post, I'll explain how I sorted through thousands of cryptocurrencies to identify a small handful that met my investing criteria. This is post is meant to be educational, but is not meant to be financial advice. I began by using TradingView's crypto screener , shown below. I filtered out cryptocurrencies with a market cap of less than $100 million. In my opinion, cryptocurrencies with a market cap smaller than $100 million are too volatile and illiquid to safely invest or trade. Assets with a such small market cap can also be prone to price manipulation. The low volume and illiquid conditions also tend to result in poor-quality charting data. I analyzed the charts of over 200 cryptocurrencies with a market cap of over $100 million. To account for the possibility that a cryptocurrency under the $100 million market cap was growing fast enough to eventually become a candidate, I re-screened all the cryptocurrencies by market cap at a second point in time (6 months later). I also performed both screenings during the current crypto bear market when fewer new cryptocurrencies were coming into existence. I observed that most cryptocurrencies decayed in value relative to the U.S. dollar. When an asset decays in value relative to the U.S. dollar this generally means that the market believes the asset is becoming worthless. Since the majority of the most highly capitalized cryptocurrencies were decaying in price over time, I assumed that lesser capitalized cryptocurrencies were also decaying in price relative to the U.S. dollar. Therefore, I concluded that most cryptocurrencies are becoming worthless over time. To objectively determine whether or not an asset is decaying relative to the U.S. dollar one can apply a regression channel to the entire price history of the asset. If the channel is downsloping, then the asset is decaying in value as time passes. The chart above shows an example of a cryptocurrency that has decayed in value relative to the U.S. dollar. Most cryptocurrencies decay in value relative to the U.S. dollar. (Note: Although the denominator is Tether the chart has been adjusted to USD.) Although most cryptocurrencies decay in value over time, dozens of cryptocurrencies move up in value relative to the U.S. dollar over time (and have an upsloping regression channel). For these high-performing cryptocurrencies, I then used relative strength analysis to determine the best investing candidates. For each cryptocurrency that had a market cap of over $100 million and that had an upsloping regression channel relative to the U.S. dollar over its entire existence, I analyzed the cryptocurrency relative to Bitcoin to see if it outperformed. If the cryptocurrency decayed over time relative to Bitcoin (downsloping regression channel), I removed it from my list because I concluded that it would be better to just invest in Bitcoin. Although I excluded crypto that underperformed Bitcoin, I could not reach the conclusion that crypto that outperformed Bitcoin was worth investing in until I first validated the conclusion that Bitcoin itself was worth investing in. While a quick glance at the price history of Bitcoin, as shown below, may convince many people that Bitcoin is worth investing in, I needed an objective, evidence-based, and mathematical method to determine whether Bitcoin is a wealth-building asset or merely a speculative bubble. Fortunately, chart analysis can help us infer if an asset is a speculative bubble or actually wealth-building over the long term. In a prior post, I explained that from a conceptual standpoint, a wealth-building asset is one that expands the investor's purchasing power over time. In order to do this, a wealth-building asset generally must move up in price over time faster than the rate at which the money supply expands. In general, only assets that are perpetually scarce or that are increasingly productive can overcome this difficult hurdle to be classified as a wealth-building asset. To learn more about why an asset must outperform the growth rate of the money supply in order to be wealth-building, you can check out my post below. Therefore, in order to test whether or not Bitcoin is a wealth-building asset over the long term (years and decades), I compared Bitcoin against the money supply. What I found was surprising. The above chart compares the market cap of Bitcoin to the U.S. money supply (M1). I found that the market cap of Bitcoin was forming an apparent bull flag to the U.S. money supply (M1) on the yearly chart. Not only is a bull flag apparently forming, but the bull flag structure is apparently a perfect golden ratio. To learn more about golden ratio bull flag structures and why they can be quite significant, you can check out my post below about advanced bull flag concepts. I decided to delve deeper. This time I measured Bitcoin against the money supply on a lower timeframe and using a longer lookback period. I found that the total market cap of Bitcoin as a ratio to the money supply was moving in an apparent logistic growth curve . Although it is generally well-known that Bitcoin moves in a logistic growth curve to the U.S. dollar, it is not generally well-known that Bitcoin's market cap is also moving in the same logistic growth pattern relative to the money supply. The chart above shows the total market cap of Bitcoin moving in an apparent logistic growth curve relative to the money supply. The pink line at the top is the value 1, and it represents a horizontal asymptote (the highest possible value that can be reached). Bitcoin's market cap can only go as high as the total supply of money. As Bitcoin's market cap approaches the total supply of money, further growth becomes increasingly inhibited because there is a decreasing amount of money left that can be converted into Bitcoin so as to push its price up further. It is thus not possible for the total market cap of Bitcoin to exceed the total supply of money. In other words, when measured in U.S. dollars, the total value of 21 million Bitcoin can only ever be as high as the total global supply of U.S. dollars. Although the money supply tends to increase over time, the total market cap of Bitcoin as a ratio to the money supply can only ever reach 1. Since the inhibiting factor of the growth of Bitcoin's market cap is the money supply then what this means on a conceptual level is that Bitcoin's logistic growth is actually a mathematical indication that Bitcoin is replacing the money supply. In essence, by forming a logistic growth curve to the U.S. money supply, we can infer that Bitcoin is displacing, if not outright replacing, the U.S. dollar. If you would like more scientific evidence that Bitcoin conforms to a logistic growth function, you can check out this research article . It is not unusual that Bitcoin's price action appears as a logistic growth curve. Logistic growth curves characterize many types of replacement processes in nature. For example, each time a new variant of COVID-19 emerged, it replaced the previous variant through logistic growth, which can be shown in a chart of the relative prevalence of COVID-19 variants over time. The chart above shows the "S-curve" or sigmoid pattern that characterizes logistic growth. Variants of COVID-19 vying for hosts to infect is reflected as a logistic growth race among circulating and emerging variants. In many ways, this competition among virus variants is analogous to the competition of cryptocurrencies: Each cryptocurrency competes with existing and emerging cryptocurrencies to form a logistic growth curve relative to the U.S. dollar, thereby challenging its market dominance. A small subset of cryptocurrencies are so competitive that they also form a logistic growth curve relative to Bitcoin, which reflects their attempt to replace even Bitcoin's market dominance. The final step I took in analyzing cryptocurrency for investing potential was to detect which, if any, cryptocurrencies were moving in logistic growth not only to the U.S. dollar but also to Bitcoin. If one can detect an asset that will move in a logistic growth curve to Bitcoin early on, the extent of wealth that can be built is extraordinary. Below are a couple of examples of the relative strength analyses I performed. Bitcoin vs. Bitcoin Cash The above chart shows a downsloping regression channel, indicating that Bitcoin Cash decays in value relative to Bitcoin over time. Therefore, Bitcoin is a better long-term investment than Bitcoin Cash. Bitcoin vs. Ethereum In the chart above, one can see that when compared to Bitcoin, Ethereum produces an upsloping regression channel. Since the Pearson correlation coefficient is quite low and since Ethereum was unable to reach a higher high relative to Bitcoin in the current halving cycle, the relative strength of Ethereum and Bitcoin are indeterminate. In light of this, I decided that investing in both Bitcoin and Ethereum could allow me to diversify and lower the risk of investing in only one of the two. Aside from Bitcoin and Ethereum, in a follow-up post, I'll reveal which other 3 cryptocurrencies I currently invest in. One of them may be a surprise to many. Feel free to leave a comment below indicating which cryptocurrencies you think should be in the top 5 long-term investing candidates. In conclusion, the analysis above shows that, to a reasonably high degree of certainty, cryptocurrency (Bitcoin specifically) is challenging the current monetary system in ways that it has not been challenged before. It is my belief that cryptocurrency is the next step in the evolution of human financial markets. It builds the infrastructure for a monetary system that equips humans with more efficient transactions within digital spaces. While the Bitcoin blockchain is far from perfect and is heavily reliant on non-renewable energy consumption, it solves many of the inefficiencies that financial systems have been unable to solve for millennia. If you enjoyed this post, I would greatly appreciate it if you leave a boost! If you have any questions or would like to share your thoughts, feel free to leave them in the comments below. In a future post, I plan to explain why cryptocurrency's displacement of existing monetary systems is becoming increasingly inevitable due to the proliferation of DeFi protocols. Important Disclaimer Nothing in this post should be considered financial advice. Trading and investing always involve risks and one should carefully review all such risks before making a trade or investment decision. Do not buy or sell any security based on anything in this post. Past results do not guarantee future returns. Cryptocurrencies are highly volatile. Never borrow money or use margin to invest in cryptocurrency. Cryptocurrency is not backed or insured by any authority and is therefore a high-risk asset class. You can lose all or some of your money in cryptocurrency. Please consult with a financial advisor before making any financial decisions. This post is for educational purposes only.

Education

by SpyMasterTrades

Updated

#PATIENCE Hello traders, today we will talk about patience Patience is the key to the best trades. #Plan your trade. #Do your research. #Wait for the perfect entry And many more but only patience will allow this process to unfold. It's crucial to develop patience as a crypto trader. It's simple to fall for the hype surrounding quick earnings and instant delight. However, making snap judgments can result in losses. By exercising patience, traders can track market patterns, examine the market's behavior, and come to wise conclusions. The long-term advantages of this strategy may be substantial. Patience also enables traders to avoid emotional choices that could be harmful to the health of their portfolios, such as panic purchasing or selling. Additionally, the volatility of the cryptocurrency market is well-known. Prices can change quickly, and crypto assets can lose or gain more than 50% of their value in a matter of days or even hours. Having patience allows traders to weather the market's ups and downs without making snap decisions. Finally, traders can choose superior risk management strategies by exercising patience. Before making a choice, it enables them to conduct their due diligence and reduce their exposure to any damages. Conclusion: Having patience can help traders succeed when trading cryptocurrencies. They are able to make wise choices and steer clear of costly errors thanks to it. The saying "slow and steady wins the race" is true. It’s okay to wait… and wait… and wait for the exact moment to make your move. Play the long game. Never stop learning I would also love to know your charts and views in the comment section. Thank you

Education

by CRYPTOMOJO_TA

Updated

Supply and Demand Zones: Buying Low, Selling High 1. What Are Supply and Demand Zones? In the cryptocurrency trading, supply and demand zones are pivotal concepts that profoundly impact market behavior. These zones act as critical areas where traders engage in buying and selling actions, significantly influencing price movements. To gain a deeper understanding of how these zones work, let's delve into the specifics. 2. What Is A Supply Zone? A supply zone, within the context of cryptocurrency trading, represents a resistance area where traders are inclined to sell their assets. Supply zones are typically positioned above the current market spot price and often coincide with prominent psychological price thresholds, such as $50,000 or $60,000. This zone often becomes the focal point for take-profit orders, and when the price approaches it, resistance ensues. Unless there's a notable surge in buying pressure to counteract the selling momentum, prices are prone to decline. 3. What Is A Demand Zone? On the flip side, a demand zone serves as a support area where traders favor purchasing cryptocurrency assets. Demand zones are generally situated below the current market spot price and are frequently aligned with significant psychological price levels, such as $10,000 or $20,000. Traders are inclined to set limit buy orders within these zones, leading to upward price movements as the appeal of the support level draws in buyers. 4. How to Draw Supply and Demand Zones? Drawing supply and demand zones is a fundamental skill for cryptocurrency traders. To create these zones effectively, traders often employ the "Rectangle" tool available on @TradingView charts. By identifying historical peak levels and bottoms where price reversals have occurred, traders can accurately delineate supply and demand areas. 5. How to Find Supply and Demand Zones? While there isn't a specific indicator dedicated to supply and demand, we can utilize tools like "Pivot Points" to narrow down these key areas. Pivot Points are instrumental in highlighting support and resistance levels, making them valuable for identifying potential supply and demand zones. When Bitcoin or other cryptocurrencies reach these levels marked by Pivot Points, significant price reactions often follow, offering prime opportunities for profitable trades. 6. How to Trade Supply and Demand Zones? Trading based on supply and demand zones is a versatile strategy that suits both short-term and long-term trading approaches. The fundamental principle remains constant: buy within demand zones and sell within supply zones. For example, suppose Bitcoin is currently trading at $25,900, and demand zones are situated in the range of $25,300 to $25,600. In this case, we can place buy orders within this demand zone and sell orders in the supply zones. It's essential to adapt this strategy to your specific trading goals and preferences, utilizing support and resistance levels as a foundational framework for drawing trend lines and setting limit orders. Incorporating the power of supply and demand zones into your cryptocurrency trading strategy can provide invaluable insights and enhance your overall trading success. Whether you're a day trader or a long-term investor, comprehending and effectively utilizing these zones can enable you to make more informed decisions and potentially amplify your profitability in the cryptocurrency trading.

Education

Updated

Channel trading How to trade channels after sharp moves, where there is a valid money flow in the market. During this short video I just described one of very common and useful techniques that is applied for channel trading, which is for this video scalping, but it applies to all time frames. Here you need to get confirmation and be patient for pull back, it is important to put your stop loss precisely and of course be loyal to it (please do not move it) Put the stop loss under that shadow but with enough space for breathing

Education

01:25

Select market data provided by ICE Data services. Select reference data provided by FactSet. Copyright © 2025 FactSet Research Systems Inc.© 2025 TradingView, Inc.

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