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How to Build a Consistent Execution Checklist on TradingViewMost trading mistakes don’t come from bad strategy, they come from inconsistent execution. An execution checklist removes guesswork and replaces it with structure. When your actions follow a routine, your results stabilize. TradingView gives you everything you need to build a checklist that stays visible, actionable, and tied directly to your chart. 1. Define Your Core Conditions Before any trade, the bigger picture must be clear. Start your checklist by answering three questions: What is the higher-timeframe direction Where is price relative to key levels Is price approaching with strength or weakness Use TradingView’s drawing tools to mark support, resistance, value zones, and session highs and lows. Add a simple text note on the chart listing your core conditions so they are always visible. If the market context fails this first screen, the trade is already invalid. 2. Build Confirmation Criteria Once structure is confirmed, you move to evidence. Mark confirmation areas directly on your chart: Liquidity pools Fair value zones or imbalances Previous session highs and lows Asian range or New York open If your strategy uses indicators, document exact conditions: Moving average position and slope Volume behavior VWAP location Volatility expansion or contraction Define rules that don’t change based on emotion. Confirmation should prove your bias, not justify your urge to trade. 3. Validate Risk Before Execution Every setup must survive a risk checkpoint before it’s allowed to go live. Your checklist must answer: Where is my invalidation level How much capital am I risking Does this violate any daily limits Is the reward worth the risk Use TradingView’s long or short position tool to visualize risk directly on the chart. Save it as a template so your risk process stays uniform across all trades. No trade is valid if risk isn’t clean. 4. Create a Pre-Execution Routine A checklist only works if you actually follow it. Add a short pre-trade process directly to your chart notes using checkboxes or bullet points: Example execution checklist: Market phase confirmed Level identified Confirmation present Risk valid Entry condition active Walk through this list before clicking buy or sell. If one item fails, the trade fails. Over time, this routine removes emotional impulse completely. 5. Review and Refine Weekly Your checklist isn’t static, it evolves. Every week ask: Where did I break my rules What conditions led to losses Which confirmations work best What rules saved me from bad trades Use TradingView’s trade replay and journaling features to review execution quality, not just profit. Consistency improves when your system evolves with you. Final Thought A checklist doesn’t restrict your trading, it frees you from emotion. When your process is clear, your confidence increases. When your confidence increases, discipline follows. Good traders make decisions. Great traders execute procedures. Stay Green!
Education
by Green_Squad
6
Risk Management for Automated SystemsAutomation gives you speed, consistency, and emotionless execution, but it also has a dark side. A bot can follow rules perfectly, but if the rules are risky, it will amplify the danger with mechanical precision. That’s why risk management is the backbone of every successful automated strategy. It doesn’t matter how good your code is — without proper risk control, even the smartest system can fail fast. Below are five core pillars of risk management that every trader should build into their automation framework. 1. Know Your Maximum Drawdown Every trading system, even the best one, goes through losing streaks. What matters isn’t avoiding them, but controlling how deep they cut. Setting a maximum drawdown limit defines the exact point where your bot pauses or shuts down. Whether it’s 5%, 10%, or 20%, this boundary protects your capital and your mindset. Why it matters: Prevents “death spirals” during high volatility Stops the system if market conditions change Forces you to step back and evaluate logic Protects the account from black swan trends A bot that can’t stop itself, is a bot that will eventually blow up. A bot that knows when to stop, survives. 2. Position Sizing Is Everything You can have the best entry logic in the world, but if your position sizes are inconsistent or too large, the system becomes unstable. Smart position sizing adapts to: Account balance Market volatility Asset liquidity A fixed-percentage model, such as risking 1–2% per trade, keeps performance steady even during rough periods. It also allows your system to grow naturally without taking oversized risks. Think of sizing as the volume knob of your bot — turn it too high, and you distort everything. 3. Avoid Correlated Exposure Running several bots doesn’t automatically mean you are diversified. Many traders make the mistake of running multiple strategies that all rely on the same market behavior. For example: Three momentum bots on BTC, ETH, and SOL are still highly correlated Two trend systems may fail at the same time if the market suddenly ranges Several “dip-buying” strategies will all get hit hard during a crash True diversification means mixing: Uncorrelated assets Different signal types Varying timeframes Both trend and mean-reversion logic The goal is for your bots to perform differently, not identically. 4. Review Your System’s Risk Profile Markets change, and so should your risk model. Volatility increases and decreases, spreads widen, volume dries up, and certain assets become more unpredictable. Regular reviews ensure your system stays aligned with real conditions. What to check: Has drawdown increased over the last quarter? Are trades becoming larger than planned due to volatility shifts? Has your system entered a new market phase it wasn’t designed for? Are win rates or profit factor weakening? A quarterly or monthly audit reveals issues before they explode. Risk management isn’t a one-time setup — it’s a continuous process. A strategy tester can be very good tool to help you manage risk properly and evaluate risk. Here is an example from one of our strategies. 5. Let Risk Management Be Automated Too If your entries are automated but your risk controls aren’t, you’re only half-protected. Risk management logic you can automate: Stop-loss placement Progressive stop tightening Position scaling Reducing size after a losing streak Pausing after reaching a daily or weekly limit Complete shutdown at max drawdown This turns your bot into a self-regulating system that responds to both opportunity and danger. The more risk rules you automate, the less emotional interference you’ll face — and the more consistent your results become.
Education
by Green_Squad
10
Backtesting 101: How to Turn an Idea Into a Tested StrategyEvery trader has thought it: “If I’d just followed that setup every time, I’d be up big.” That’s where backtesting steps in, it separates luck from logic. It’s how you find out whether your strategy has a real edge, or just worked in hindsight. Most traders skip it, not because it’s useless, but because it forces them to face the truth. But if you can handle that truth, backtesting will make you a far more confident trader. What Backtesting Really Is Backtesting means applying your trading rules to historical data to see how your system would have performed. It’s not about predicting the future, it’s about proving whether your idea works in different market conditions. When done properly, it gives you three key insights: Profitability: does your edge actually exist? Risk: how deep are the drawdowns, and can you handle them? Consistency: does it work across bull, bear, and sideways markets? A solid backtest gives you confidence, not because it guarantees profit, but because it exposes weakness before the market does. The Most Common Mistakes Curve-fitting: tweaking rules until the past looks perfect. Ignoring fees and slippage: small costs that quietly erase profits. Testing too little data: short periods create false confidence. Focusing on one market: edges must survive different conditions. If your backtest looks too clean, it’s probably lying to you. Why It Matters Backtesting builds trust in your system and discipline in yourself. When you know your data, you stop second-guessing every trade. Losing trades stop feeling like failure, because you understand they’re part of a proven edge. Even bots rely on backtesting. Without it, automation is just random execution. With it, every trade follows structure, not emotion. All of these points make a difference between a winning or losing strategy. From Idea to System Every strategy starts as a hypothesis. Backtesting turns that hypothesis into data. Data turns into structure. Structure turns into consistency. That’s the real path to professional trading - logic first, emotion second.
FOREXCOM:SPX500Education
by Green_Squad
21
Trading Bots: The Future of the Markets?Let’s be real, the idea of a trading bot sounds like the holy grail. Set it up, go to bed, and wake up to profit. If only it were that simple. Most bots don’t fail because of bad code, they fail because of bad logic. A bot is only as good as the rules you give it. What a Trading Bot Actually Does A bot doesn’t predict the market, it reacts to it. It follows a defined strategy: Buy when X happens, sell when Y is confirmed, cut losses if price breaks Z. That’s all. No fear. No greed. No “maybe I’ll wait for one more candle.” The power of bots isn’t in magic,it’s in consistency. They do what most traders can’t: follow the plan exactly as written, every single time. Why Most Bots Fail The truth? Most traders plug in random bots they find online without understanding what’s inside. They win a few trades, feel invincible… and then lose it all when volatility spikes. The reason isn’t the bot, it’s the lack of testing and understanding. If you don’t know your system’s weak spots, you’ll eventually find them the hard way. That’s why backtesting matters. Backtesting: Your First Line of Defense Backtesting shows how your logic performs over hundreds of trades — across bull, bear, and sideways markets. It reveals your system’s strengths, weaknesses, and drawdowns before you risk a dollar. A good backtest should tell you: Your average win rate and risk/reward ratio. How your system handles volatility. How often it hits consecutive losses. Whether your edge actually holds over time. If your bot looks good in backtests and performs similarly in live conditions — you’re onto something real. *Example of one of our indicator How Bots Can Enhance Your Trading You don’t have to hand everything over to automation. In fact, many great traders use bots to handle the mechanical side, while keeping the decision-making human. Here are a few examples: Trade Execution: Let the bot enter trades instantly after your setup triggers. Risk Management: Bots can move stop-losses, take partial profits, or scale positions automatically. Signal Filtering: Use automation to scan hundreds of pairs and alert you only when conditions align. Backtesting Sandbox: Test new ideas safely with data before deploying them live. Bots don’t replace traders, they multiply efficiency. They free your mind from execution so you can focus on refinement. The Real Lesson A trading bot isn’t a shortcut. It’s a mirror, it reflects your discipline, your rules, and your logic. If your plan is solid, a bot will make it unstoppable. If your plan is weak, it’ll just lose money faster. Automation doesn’t fix bad habits, it exposes them. So learn the logic, test it hard, then let the system do what humans struggle with most: follow the plan.
Education
by Green_Squad
12
Indicators and Trading Signals — How It WorksWhen you first start trading, indicators feel like the secret sauce. RSI, MACD, EMA, Volume every line promises to reveal what the market will do next. You start stacking them like LEGO blocks, thinking more confirmation = more accuracy. But here’s the hard truth: indicators don’t predict they react. The real skill isn’t using more of them, it’s knowing when to listen and when to ignore. The Role of Indicators Indicators are tools, not magic formulas. They exist to translate price action into structure. That’s it. RSI tells you about momentum. Volume shows commitment. Moving averages reveal trend direction. Volatility indicators show risk zones. The power isn’t in the tool itself, it’s in how consistently you interpret it. That’s why two traders can look at the same RSI line and do completely opposite things. The Trap: Signal Hunting Every trader falls into this phase: jumping from one setup to another, waiting for that “perfect signal.” The problem? There isn’t one. Even the best indicators will fail if your execution and mindset aren’t aligned. Signals don’t make money! Systems do. Systems combine momentum, volume, volatility, and trend logic, so signals confirm each other, not contradict. Signal vs Execution Let’s be real, getting a signal is the easy part. Following it correctly is where most traders fall apart. You get a buy signal… but wait for “one more candle.” You see a sell alert… but hold, just in case it bounces. You close early because “it already moved enough.” That’s why automation matters. It doesn’t second-guess, it executes. From Noise to System If your screen looks like a Christmas tree of indicators, you’re not trading, you’re guessing. Clean it up. Pick a few tools that complement each other, build rules around them, and stick to those rules. That’s how professionals think: less emotion, more structure.
Education
by Green_Squad
12
Automated vs Manual Trading — Which One Really Wins?Most traders start out manually, staring at charts for hours, hunting for that perfect setup, trying to outsmart the market. It feels alive. You’re in control. But after a while, you realize something brutal: the real opponent isn’t the market, it’s you. Fear, greed, hesitation, fatigue. The emotions that ruin good trades. That’s when automation steps in. Manual Trading Manual trading builds skill, but it also exposes every weakness you’ve got. If this sounds familiar, you’re not alone: Entering late because you hesitated. Moving your stop loss “just one more time.” Doubling down after a loss. Missing setups because you needed sleep. Manual trading gives flexibility, sure. But it also gives you the freedom to sabotage your own plan. Automated Trading Benefits Consistency: trades follow predefined rules, eliminating impulsive deviations from the plan. Scale: automation handles higher frequency and 24/7 market coverage beyond human capacity. Speed and precision: orders execute with lower latency and exact risk parameters. Backtest + deploy: strategies validated historically can be deployed reliably across multiple markets. Operational leverage: frees human time for strategy development, risk oversight, and portfolio decisions. Disadvantages and risks Model risk: historical backtests do not guarantee future performance; edge can decay. Overfitting and brittle rules: overly specific parameters may break under regime changes. Misaligned incentives: automated systems execute mechanically; they cannot judge rare macro events or qualitative news. Monitoring burden: automation reduces manual trading work but increases need for robust monitoring, alerts, and contingency plans beforehand. ⚔️ Two Traders, One Market Here’s the truth: two traders can run the same strategy and get completely different results. Trader A trades manually, emotional, inconsistent. Trader B runs automation, same logic, perfect execution. Same system. Different outcome. Guess which one ends up consistent?
Education
by Green_Squad
6
Automated Trading vs Manual TradingAutomated Trading vs Manual Trading In the modern world of trading, two distinct methodologies exist: manual trading vs algorithmic trading. Both these approaches aim at the same goal - to optimise profit and minimise losses in the financial markets. However, they vary significantly in their operation, the level of involvement required, and the nature of decision-making processes. In this FXOpen article, you will find the key differences between the approaches and their advantages and limitations that may help you to choose the right approach for you. Definition of Manual Trading Manual trading signifies the traditional approach to trading. In this method, a trader is actively involved in all aspects of the process. This includes conducting market research, analysing market trends, making buying or selling decisions, and placing trades. The manual approach relies heavily on the trader's skills, knowledge, and experience. The manual trader uses various tools and methods, including technical and fundamental analyses, to make informed decisions. These methods involve studying past market data, economic indicators, company financials, and market news to predict future market movements. Despite being time-consuming, many traders prefer this approach as it allows them to control their trading activities and make adjustments based on their instincts and experience. You can test manual trading at the free TickTrader platform. Definition of Automated Trading In contrast to human-based investing, automated trading, also known as algorithmic or robo trading, involves the use of computer programs or algorithms to analyse markets and place trades. These algorithms are designed to make trading decisions based on predefined rules and conditions. They can process large volumes of market data, identify market opportunities, and place trades quickly and precisely, something beyond human capability. Robots can be programmed to follow various strategies based on technical analysis, quantitative analysis, and other principles. These algorithms are typically developed using programming languages and require a high degree of technical expertise. However, many platforms now offer user-friendly tools for creating and testing algorithms, making auto-trading more accessible to the average trader. Also, some traders ask program developers to create a robot based on their requirements. Advantages and Disadvantages of Manual Trading Systems Despite being more traditional, manual investments hold their own advantages and disadvantages. Advantages: - The primary advantage of manual trading is the trader’s experience and ability to analyse markets. Unlike robotic systems, human traders can make intuitive decisions based on their experience and understanding of the market. In this case, the results of a duel between robot trading vs manual systems would end up beneficial to humans. - Another advantage of the manual approach is the flexibility it offers. Manual traders can adjust their strategies and risk tolerance levels based on the changing market conditions, economic news, and their personal comfort level. The manual approach also provides a deeper understanding of the markets, as traders are actively involved in trading. Disadvantages: - Self-trading is not without its challenges. It necessitates a substantial commitment of time and focus. Manual traders need to monitor the markets continuously, conduct thorough market analyses, and make decisions. Manual execution of trades may also be emotionally taxing; emotional decisions can often lead to poor trading outcomes. - In addition, human error can impact trading results. Unlike automated systems, manual traders cannot process large amounts of data quickly and accurately. This limitation can lead to missed trading opportunities or inaccurate decision-making. Advantages and Disadvantages of Automated Trading Over Manual Trading Advantages: - Automated trading offers several advantages over the manual variety. Some of the most significant benefits are speed and accuracy. Automated systems can analyse market data and place trades in milliseconds, which is impossible for humans. Also, algo trading allows for 24/7 activity, as human factors like fatigue or emotions do not constrain it. In this case, the algorithms win in a duel of algo trading vs manual trading. - Automated systems can handle multiple markets and securities simultaneously, allowing traders to diversify their portfolios more efficiently. By removing the emotional element from speculation, automated systems can help traders stick to their plans and avoid impulsive decisions. Disadvantages: - However, the automated approach also has its disadvantages. One of them is the need for a high level of technical expertise to set up and maintain the algorithms. Auto systems also have the risk of over-optimisation, where a system is fine-tuned to perform well based on past data but may not perform well in real market conditions. - Another challenge with automated trading is its inability to adapt to sudden market changes that a human trader could intuitively understand and respond to. For instance, traders may adjust their strategies accordingly in case of significant economic news or events, but an algorithm might not be capable of such adaptability. - Lastly, automated systems also carry the risk of technical glitches or system failures, which can lead to significant losses. It is, therefore, essential to regularly monitor and update automated systems. Does Algo Trading Beat Manual Trading? The question of "Does algo trading beat manual trading" is a matter of debate. The effectiveness of each trading method depends on various factors, such as the trader's skills and experience, the nature of the market, and the specific strategy used. Some traders may find success with robotics systems due to their speed and accuracy, while others might prefer the control and adaptability offered by manual solutions. In the world of manual trading vs automated trading in forex, it's essential to consider that FX markets are highly volatile and operate 24/7. This nature of forex markets makes them ideal for automated investing. However, the use of automated systems in FX also requires careful consideration of factors such as market volatility, liquidity, and technical glitches. Conclusion Ultimately, the choice between manual and automated investment boils down to personal preference, goals, risk tolerance, and technical expertise. Both methods have their own merits and challenges, and understanding these may help traders make informed decisions. Whether you are interested in manual or automated trading, platforms like FXOpen provide a robust and user-friendly environment for both. To get started on your investment journey, you can open an FXOpen account. Regardless of your trading method, remember that success requires a well-developed strategy, continuous learning, and effective risk management. So, keep learning, keep improving, and happy trading! This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
Education
by FXOpen
2
Bots vs Brains; The hidden edge of Human touch in tradingBots vs Brains; The hidden edge of Human touch in trading A random Google search on the internet about forex trading robots reveals thousands of forex robots exist. With all these trading robots promising handsome returns in the shortest time, the forex trading industry should be minting new millionaires daily. However, statistics from forex brokers paint a sad picture—a failure rate as high as 90%. In 2024, you can’t go a day without reading or watching a reel about Artificial Intelligence (AI). The high failure rate, especially in the world of finance, is baffling given all these technological advancements. This led me to take a deeper look into the world of automated forex trading, also known as bots or Expert Advisors (EA). Overview of Automated Trading A trading bot is software developed to analyze financial markets and execute trades on your behalf. Semi-automatic trading bots analyze the markets but do not execute trades. Large financial institutions, such as banks and hedge funds, use specialized algorithmic trading bots. These institutions bring together mathematicians, programmers, and economists to develop sophisticated algorithms. Needless to say, it requires significant financial resources and time to develop these bots. Development can take at least six months, followed by an additional six months of testing. The high cost makes these bots inaccessible to retail traders. Retail traders, however, are not left out. There are individuals and software platforms where you can develop your own trading bot. These bots are often marketed as being developed by experts with deep market knowledge—or so I thought. Trading bots follow specific rules based on the developer’s strategy, which ideally should mirror the success of an experienced trader. Therefore, if a trader is profitable, the bot should at least mimic their results, if not surpass them—more on this later. Before launching these bots, developers conduct extensive backtesting and refinement to optimize them for ideal market conditions. Advantages of Automated Trading Developers of trading bots often market them as superior to manual trading. They emphasize the need to eliminate human error and emotions, highlight faster execution speeds, and promote the ability to trade 24 hours a day as long as markets are open. Additionally, bots can save traders significant time that would otherwise be spent analyzing markets and executing trades. On the surface, purchasing trading robots seems like a smart decision. Limitations of Automated Trading Bots rely on historical data, assuming the future will mirror the past. However, global events are unpredictable. Take, for example, the 2008 financial crisis or the sudden shock of COVID-19—events like these can completely throw off a bot’s programming. Robots struggle to adjust to such volatility unless they’re frequently updated with new data, which many are not. This is a major limitation, especially when you consider how quickly the forex market moves with trillions of dollars in circulation. Earlier, I mentioned that robots are supposedly developed by profitable traders. But to my surprise, I found that with little trading experience, anyone can create a robot on platforms like EA Trading Academy. All it takes is registering, selecting a few parameters, running a back test, and then selling it. It’s really that simple. The ease with which these bots can be built raises questions about their reliability, especially when they aren’t crafted by experts. I even plan to build one myself, and I’ll give you feedback in a year’s time. Why I Think Robots Don’t Work The main issue is that there’s a shortage of consistently profitable traders. A trader who dedicates the time and effort to developing a reliable robot is likely to charge a hefty fee. The likelihood that they would focus solely on developing robots instead of trading themselves is very slim. This makes me wonder—who is actually building all these robots? If most profitable traders are busy trading, it raises concerns about the experience level and expertise of those creating the majority of these products. Secondly, trading styles vary significantly from trader to trader. Purchasing a robot based solely on profitability or low cost is unwise. In addition to checking a developer’s track record, you should assess whether their risk tolerance and trading approach align with yours. For instance, buying a scalping robot when you prefer swing trading could be a costly mismatch. Finally, purchasing robots without a solid understanding of the markets is irresponsible, and the disasters that follow are often justified. Many experienced traders who have tested and reviewed bots on YouTube agree that 99% of them are either scams or simply don’t work. I encourage you to watch some of these reviews to see for yourself. The Future: Automation vs. Human Touch Mastery in trading comes from a combination of skill, time, and experience. While bots claim to save you the time spent on analysis, it's precisely that time—the deep learning and constant market study—that ultimately leads to true mastery. There are no shortcuts. Bots may be designed to minimize human error, and in theory, they do. But the reality is that even the most sophisticated bots are not infallible. They can and often do fail, sometimes catastrophically. When accounts are blown—whether by a human or a bot—it’s still the trader who bears the loss and the disappointment. So, while bots may reduce human error, they can never eliminate the human responsibility for those errors. Trading the financial markets is a craft like any other. Automation, AI, and machine learning can be valuable tools in your journey to becoming a skilled trader. They cannot replace the critical thinking and adaptability that come with human experience. AI can assist by analyzing large sets of data, flagging trends, or executing trades faster than a human could—but the nuanced understanding of market sentiment, global events, and individual risk tolerance is something only a human can develop through dedication and practice. Automation might help you refine your craft, but it's the time spent learning, making mistakes, and adapting that leads to true mastery. As promising as they are, AI and bots are tools—not substitutes—for the expertise that comes from being deeply engaged in the markets. Others before you have achieved mastery, and with enough commitment, you can too.
CAPITALCOM:DXYEducation
by morrisgitau
3
Alpha Ai Reversal: A High-Performance Strategy with 412% ReturnsKey Highlights: NASDAQ:NDAQ Net Profit: A solid $82,516.99 USD profit , reflecting a gain of 412.58%. This showcases the strategy's ability to multiply capital impressively over time. Total Closed Trades: 157 trades have been completed, indicating a good amount of market engagement, providing ample data to gauge the strategy's reliability. Percent Profitable: A high success rate, with 79.62% of trades closing in profit . This means nearly 8 out of 10 trades are winners, a confidence booster for any trader! Profit Factor: A profit factor of 3.296 indicates that for every dollar lost, the strategy earned over three dollars. This is a strong indicator of risk/reward management. Max Drawdown: The maximum observed drawdown was $13,564.86 USD, or 50.61%. While this is on the higher side, suggesting periods of significant losses, the overall profitability more than compensates for this. Average Trade: The average trade brought in $525.59 USD, representing a 1.14% gain per trade. This consistent performance adds up over time, as seen in the cumulative profits. Average Number of Bars in Trades: Each trade lasted an average of 17 bars. Given the 8-hour timeframe, this means trades were typically held for about 5-6 days, balancing between quick profits and sustained positions. The strategy seems well-calibrated for traders looking for high probability setups with significant profit potential. The strong profit factor and percentage profitability are particularly appealing, suggesting a strategy that can consistently outperform the market, even if the drawdowns require a strong stomach. For those willing to ride out the occasional rough patch, the Alpha Ai Reversal strategy offers a compelling balance of risk and reward, promising attractive returns in the long haul. This strategy could be a game-changer !
OANDA:NAS100USD
by Alpha-Capital
2
Create No Code Auto Trading Bot with Tradingview and OKXHello Everyone, In this tutorial, we learn about how to create simple auto trading bot using tradingview alerts and OKX exchange built in integration mechanism. Few exchanges have come up with this kind of direct integration from tradingview alerts to exchanges and as part of this tutorial, we are exploring the interface provided by OKX. In this session, we have discussed 🎲 Preparation Steps Preparing tradingview account Webhooks are only available for essential plans and plus. Enable 2FA in your tradingview account. Preparing your OKX account Create OKX account, and we prefer you do the initial tests under demo account before moving to active trading account. Bots created in demo account will not appear in the active trading account. Hence, when switching to active account, you need to create all the setup again. 🎲 OKX Tradingview Interface Features What is supported Auto trading based on strategy signal Custom signals - Enter Long, Exit Long, Enter Short, Exit Short What is not supported: Stop/Limit orders Bracket orders/ Complex execution templates 🎲 Weighing Pros and Cons of Using Direct Interface rather than Third party integration tools Pros Latency is minimal as per our observation Easy Integration with Tradingview and Pinescript Strategy Framework and no coding required You save cost on third parties and also avoid one hop. More secure as your data is shared between less number of parties. Cons No native support for Stop/Limit orders
Education
by Trendoscope
16
XLM Stellar Lumen - Potential for a bright future Remember to pay attention to Support Resistance Zones, Don't get greedy and follow a strategy. We are committed to safe and efficient investing, we have target zones for that reason! Thank you for reading along! XLM Potential price points Entry zone: $.1305-$.1310 Major support: $.122 Target 1: $.13745 Major resistance: $.176 Target 2: $.1955 Second major resistance zone: $.290-$.304 Precious top resistance level: $.545 Stellar (XLM) is a peer-to-peer (P2P) decentralized network created in 2014 by The Stellar Development Foundation or Stellar.org. The network officially launched in 2015 with the purpose of connecting the world's financial systems and ensuring a protocol for payment providers and financial institutions. The platform is designed to move financial resources swiftly and reliably at minimal cost. Stellar links people, banks, payment processors and allows users to create, send and trade multiple types of crypto. The basis of the network is its native digital currency - XLM or Lumens. XLM acts as an intermediate currency for operations and is also used to pay transaction fees. How it works: the protocol converts money in a few seconds, first into XLM, and then into the requested currency. The Stellar payment protocol is based on distributed ledger technology -- an open-source development, community-owned and distributed by community. The crypto asset of the Stellar platform helps with cross-border transactions, overcoming the problems of high fees and slow procedures. XLM is more focused on assisting individuals transfer money than they are with institutions. Thus, Stellar offers access to financial systems, and people can send money at low cost and promptly around the world.
COINBASE:XLMUSDLong
by Helios_Capital_Investment
How to automate Trading View indicator alerts with 3Commas In this guide we will explain how to connect and automate a Buy&Sell strategy with 3Commas using a Trading View indicator. This guide will enable you to create long strategies on all spot pairs available on 3Commas. In this example we will set up a Buy&Sell bot that will open the long position when the Tweezer Bottom - Bullish indicator signals the pattern. Then we will illustrate all the steps necessary to open the long position. The position will be closed using 3Commas take profit and stop loss. 1) Choice of the technical indicator to be used. Trading View offers an extensive library with technical indicators developed by the in-house team. To access all available indicators, open the indicators dashboard (A) and click on the Technicals section (B). In this example we will choose an indicator in the Patterns section (C) called Tweezer Bottom - Bullish (D). Remember that the choice of this indicator is purely random and is for educational purposes only, be sure to backtest and research before building any trading strategy. 2) Creating a bot on 3Commas. Now go to 3Commas and create a new DCA bot. This bot will allow you to connect the indicator signal. Set up the Main Settings section. Name your bot (A), select your exchange (B), and bot type (C). Select the ticker (A), set the type of strategy (B) and the capital to be used (C). In the Deal Start Condition section, open the drop-down menu and select 'Trading View custom signal'. Set the take profit. Set the stop loss. Configure the Safety Orders section for a Buy&Sell strategy. Set the value to zero within this section as shown in the screenshot. Set Max safety orders count and Max active safety orders count to zero. Now that you have properly created and configured your bot, go inside your new bot's 3Commas dashboard, scroll down, and copy the 'Initial Start Deal Condition' message. 3) Trading View Connection - 3Commas. Come back to Trading View and create a new alert (A), select the indicator from the drop-down menu (B), then choose Once Per Bar Close (C), and finally create a name for your alert and enter the message you copied previously within the Message field (D). As a last step, go into Notifications , enable the web-hook url and enter 3Commas' web-hook: 'https://3commas.io/trade_signal/trading_view'. Create your alert as a final step. You have now correctly created a new 3Commas Buy&Sell bot that will automatically open new orders when a new pattern is generated.
Education
by thequantscience
1
The S-Pattern - Where or Why Does This Happen?Hey folks - been a while since I made one of these (not too much interesting movements in the crypto markets lately, honestly), but after a long period of inactivity in XTZ, *something* seems to have triggered a move. There's a few people wondering where this spike in Tezos came from - unless the transaction was triggered by literally one wallet (unlikely since that would have been identified by now), we can only really speculate as to who or what "bought the dip". But generally speaking, the extreme verticality of the "pump" suggests that this was an automated trade or possibly someone with access to a button to make large hyper-coordinated trades. (If a bunch of people get together and buy-in together the price usually rises as a slope over time, not a spike.) Since we are in a bear market right now, the rules of the game for investors changes a bit. But it's important to remind yourself of the fundamentals of supply/demand and incentives in markets themselves doesn't change. So based on that, we can make a few educated guesses: 1. Bear markets don't necessarily mean that there is no money to invest - lots of people exited the market at the beginning of this bear market, converting their assets into cash. (These are the folks who quietly sold at the top and can be considered "smart money".) They are waiting for the market to bottom out as the hype fades away. So the money to invest itself is there (it is always there, really) - it's just unsure where or when to get back in right now. Someone or something made the guess that *this* is the bottom now, in other words. 2. The vertical part of the S-pattern suggests (automated or not) large-volume investors getting in, while the gradual slope downwards back to its original state is likely smaller investors exiting out of the ecosystem. (Many have expressed frustrations with the coin not having moved in a while and have been waiting for moments like these as an excuse to exit.) This is primarily the way markets "cleans" itself of short-term players and the reason why institutional investors often beat retail ones in the long - they have the means and patience to wait until the very bottom of the "valley". (Another reason why it's important to only invest what you can afford to lose.) 3. You have to be careful of getting your news from the media or social media because during down markets most talks and discussions will be about how bad the markets are - which is the obvious thing to complain about during those times. The negative sentiment eventually becomes a self-fulling prophecy and the price will continue to dip until the "losers" have left the scene. If you think about it, the only people who have a reason to complain are the ones that bought at the top and looking to recoup their losses. The ones that were in early, holding for long-term, or sold at the right time (lucky them!) don't really have much of a reason to engage with doom-spiral content. 4. And finally - smart-money investors look for primarily two things: A reason to get back in (will not happen with ponzi or vaporware projects, which is a good thing), and the right time to get back in. Even if they have done their research and believe in a project strongly, when half the people in the ecosystem are in a panicked state, it doesn't give them much confidence to get back in. At least not yet. So they wait until the price flatlines and things get quiet - are the folks threatening to exit gone yet? This is the reason why big rallies often happen unexpectedly after long periods of no movements, rather than a "rebound" after a massive dip. It is the waiting game smart investors play to get the best spread between buying low and selling high. -- A lot of this will feel weird and unfamiliar because I don't think crypto really has really gone through a "real" bear market - it was a product of the post-2008 0-interest rate era and a lot of the rallies were sustained by VC and hype money, which fueled a lot of irrational behavior during the last few cycles as a whole. (Including FTX.) But now that that era has come to an end, what comes next? A bit of spring cleaning in the markets is in order - I think. A lot of people have been waiting for this moment to come for a very long time, so it could possibly be one of the biggest rebounds in history...but only time will tell. Good luck, folks. 🤞
Long
by RyanTanaka
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FX:XAUUSD
by Alpha-Capital
PancakeSwap Bull Market Can Return if it Breaks This LogarithmicPancakeSwap (CAKE) may not see a new bull market until it clears its weekly logarithmic trendline. At the same time, cycle-wise, the cryptocurrency seems to have completed an Elliott Wave flat structure that suggests that we're about to bottom. CAKE Logarithmic Trendline The downward sloping logarithmic trendline connects all the major swing highs, starting with the 2021 all-time high of $44.27. The logarithmic trendline also aligns with the 200-day simple moving average, which gives it more weight. In this regard, a breakout can lead to a shift in the trend direction. CAKE Elliott Wave Cycle CAKE’s price is currently trading near its historically lowest level, but based on the Elliott Wave analysis, CAKE's long-term price structure mimics a flat pattern. Flats are corrective patterns in nature with an internal 3-3-5 wave structure. The first wave ended at the $44.27 all-time high, followed by another 3 wave price structure in wave B, which ended at the $9.44 low. The cryptocurrency then resumed lower in wave C, subdividing into another 5 wave price structure. In the short term, the current low of $2.48 remains intact; the correction can be called completed. Following this EW cycle, the cryptocurrency may be in the process of bottoming out. However, the next bull run will be confirmed once the CAKE price clears the logarithmic trendline. Another sign of a shift in the market can be signaled by a breakout above the 50 mid-level of the weekly RSI oscillator. Once the logarithmic trendline is cleared, there is not much resistance underway until the $10 psychological level.
by cryptohopper