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Volatility

HOW-TO: Cyato Bands █  Overview Welcome to the getting started page dedicated to my automated trading strategy Cyatophilum Bands, which is in continuous development. The strategy principle is to identify consolidation areas, catch breakouts and ride the trend as long as possible. █  Trade examples Breakout from Tight Consolidation Price consolidates within a narrow range and identifies the breakout point. False Breakout Avoidance Filter out noise from the market by incorporating volume, trend and range filters. Multi-Timeframe Analysis Set the Bands time frame higher than the current chart to perform MTF analysis. Reversal Confirmation In the strategy direction settings, you can choose to go long, short or both. Profitable Trend Continuation A cool feature the take profit has is that it gets disabled when the trend is strong and clear, allowing to play safe in a ranging market, while maximizing profits in strong trends. █  Indicator settings Bands Settings The band configuration settings allow you to create any kind of band, my favorite is the Donchian channels, but you can also create Bollinger and Kelter kinds of bands. Filter Settings The entry is triggered by a band breakout, but only that is not enough to create a solid strategy. Adjust the consolidation area, set a volume, range and trend filter to strengthen your entry. Stop Loss Settings Easily create a stop loss system using %, ATR, pips or AUTO calculation modes. Add a trailing stop using ATR or Classic modes. (more modes can be added upon request) Take Profit Settings Set a take profit system using also different modes and the amazing feature to disable take profit during strong trends. Backtest Settings Backtest quickly using the information panel. See if you beat buy and hold and ATH buy and hold, as well as other stats like daily return. █  Backtesting results & preconfigured charts BTC/USDT Snapshot: Chart : www.tradingview.com (Access Required) ETH/USDT Snapshot: Chart : www.tradingview.com (Access Required) BNB/USDT Snapshot: Chart: www.tradingview.com (Access Required) SOL/USDT Snapshot: Chart: www.tradingview.com (Access Required) ADA/USDT Snapshot: Chart: www.tradingview.com AVAX/USDT Snapshot: Chart: www.tradingview.com LINK/USDT Snapshot: Chart: www.tradingview.com MATIC/USDT Snapshot: Chart: www.tradingview.com IMX/USDT Chart: www.tradingview.com █ SCRIPT ACCESS Indicator and automation tools access can be purchased on my website. Links in my signature below.
Education
by cyatophilum
Understanding Volatility and How Traders Can Use It to Their BenWhat is Volatility? Volatility refers to the degree of variation in the price of a financial instrument over time. It is a statistical measure of the dispersion of returns for a given security or market index. In simpler terms, volatility represents the amount of uncertainty or risk related to the size of changes in an asset’s value. High volatility means the price of the asset can change dramatically over a short period in either direction, while low volatility implies more stable prices with fewer and smaller fluctuations. Measuring Volatility Historical Volatility: This measures past market prices and their fluctuations over a specific time period. It is calculated by taking the standard deviation of returns over that period. Implied Volatility: This is derived from the market price of a market-traded derivative (e.g., an option). It reflects the market's view of the likelihood of changes in a given security's price. Volatility Indexes: Tools like the CBOE Volatility Index (VIX) track market expectations of near-term volatility conveyed by S&P 500 stock index option prices. How Traders Can Use Volatility to Their Benefit Identifying Trading Opportunities: High Volatility: Traders often seek high volatility environments as they provide more opportunities to capture significant price movements. This is particularly beneficial for day traders and short-term traders who can capitalize on rapid price changes. Low Volatility: During periods of low volatility, traders might focus on strategies like mean reversion, where they anticipate that prices will return to their average. Risk Management: Understanding volatility helps traders manage risk better. By using tools such as stop-loss orders, traders can limit potential losses during volatile periods. Position sizing based on volatility can help in adjusting exposure. For instance, smaller positions might be taken during high volatility to mitigate risk, while larger positions could be considered during stable periods. Volatility-Based Strategies: Options Trading: Traders can use volatility to their advantage in options trading. Strategies like straddles and strangles profit from significant moves in either direction, which are more likely during high volatility periods. Market Timing: Hedging: Traders can hedge their portfolios against volatility by taking positions in assets or derivatives that are negatively correlated with their current holdings. Volatility can provide insights into market sentiment and potential turning points. For instance, a spike in volatility often precedes significant market corrections or rallies. Traders can use technical indicators like Bollinger Bands, which adjust for volatility, to identify overbought or oversold conditions in the market. Conclusion Volatility is a fundamental concept in trading that can both pose risks and offer opportunities. By understanding and measuring volatility, traders can enhance their risk management practices, identify profitable trading opportunities, and employ volatility-based strategies to improve their overall trading performance. Whether dealing with high or low volatility environments, a keen awareness of market fluctuations is essential for successful trading.
SP:SPXEducation
by moneymagnateash
4
Visualize $TSLA CALL pricing skew due to the upcoming earningsLet’s take a look at our new tradingview options screener indicator to see what we observe, as the options chain data has recently been updated. When we look at the screener, we can immediately see that NASDAQ:TSLA has an exceptional Implied Volatility Rank value of over 100, which is extremely high. This is clearly due to the upcoming earnings report on July 23rd. As we proceed, we notice that Tesla's Implied Volatility Index is also high, over 70. This means that not only the relative but also the absolute implied volatility of Tesla is high. Because the IVX value is above 30, Tesla’s IV Rank is displayed with a distinguishable black background. This favors credit strategies such as iron condors, broken wing butterflies, strangles, or simple short options. Next, let’s examine how this IV index value has changed over the past five days. We can see it has increased by more than 6%, indicating an upward trend as we approach the earnings report. In the next cell, we see a significant vertical price skew. Specifically, at 39 days to expiration, call options are 84% more expensive than put options at the same distance. This indicates that market participants are pricing in a significant upward movement in the options chain. The call skew is so pronounced that at 39 days to expiration, the 16 delta call value exits the expected range. This signifies a substantial delta skew twist, which I will show you visually. We see a horizontal IV index skew between the third and fourth weeks in the options chain. This means the front weekly IVX is lower than the IVX for the following week, which may favor calendar or diagonal strategies. Hovering over this with the mouse reveals it’s around the third and fourth week. In the last cell, we observe that there’s a horizontal IVX skew not just in weekly expirations but also between the second and third monthly expirations. Now, let’s see how these values appear visually on Tesla’s chart using our Options Overlay Indicator. On the right panel, the previously mentioned values are displayed in more detail when you hover over them with the mouse. The really exciting part is setting the 16 delta curve and seeing the extent of the upward shift in options pricing. This significant skew is also visible at closer delta values. When we enable the expected move and standard deviation curves, it immediately becomes clear what this severe vertical pricing skew in favor of call options means. Practically, market participants are significantly pricing in upward movement right after the earnings report. Hovering over the colored labels associated with the expirations displays all data precisely, showing the number of days until expiration and the high implied volatility index value for that expiration. Additionally, a green curve indicating overpricing due to extra interest is displayed. Weekly expiration horizontal IVX skew values appear in purple, and those affected by monthly skew are shown in turquoise blue. The 'Lite' version of our indicators is available for free to everyone, where you can also view Tesla as demonstrated. Pro indicators are available more than 150 US market symbols like SPY, S&P500, Nvidia, bonds, etfs and many others. Trade options like a pro with TanukiTrade Option Indicators for TradingView. Thank you for your attention.
NASDAQ:TSLAEducation
by TanukiTrade
Understanding Market Volatility and Its Impact on BitcoinIntroduction Market volatility is a crucial aspect that every Bitcoin investor and trader must understand. In this section, we'll explore what market volatility is, how it affects Bitcoin, and strategies to manage it. What is Market Volatility? Market volatility refers to the rate at which the price of an asset, such as Bitcoin, increases or decreases for a given set of returns. High volatility means that the price of Bitcoin can change dramatically over a short period, both positively and negatively. How Does Volatility Impact Bitcoin? Price Swings: Bitcoin is known for its significant price swings, which can be driven by various factors such as market sentiment, regulatory news, macroeconomic trends, and technological advancements. Investor Behavior: Volatility often influences investor behavior, leading to increased buying or selling pressure. This can result in rapid price movements, creating opportunities and risks. Market Sentiment: Positive news can lead to a surge in Bitcoin prices, while negative news can result in sharp declines. Understanding market sentiment is crucial for predicting these movements. Managing Volatility Diversification: Spread your investments across different assets to reduce risk. Diversification can help cushion the impact of volatility on your portfolio. Risk Management: Use stop-loss orders to limit potential losses. Setting predetermined exit points can protect your investments during periods of high volatility. Stay Informed: Keep up with the latest news and trends in the cryptocurrency market. Being informed allows you to make timely decisions and react appropriately to market changes. Long-term Perspective: Focus on the long-term potential of Bitcoin rather than short-term price fluctuations. A long-term perspective can help you stay calm during volatile periods. Conclusion Understanding market volatility is essential for navigating the Bitcoin market. By recognizing how volatility impacts prices and adopting strategies to manage it, you can better position yourself to take advantage of opportunities while minimizing risks. Stay informed, diversify your investments, and maintain a long-term perspective to thrive in the ever-changing world of Bitcoin.
BITSTAMP:BTCUSDEducation
by moneymagnateash
2
HOW-TO: Cyato Grid BotThe grid strategy is one of the most popular and interesting in the world of crypto and forex trading. Simply because it abuses volatility, market fluctuations, and those markets are well known for it. In this guide, I will explain the strategy and showcase a powerful grid trading indicator that can help traders to better understand and implement this strategy. █ The Key to the strategy It involves placing buy and sell orders at predetermined intervals or levels, called "Grid Steps". If a step is crossed to the downside, the strategy will buy. If price crosses a step to the upside, the strategy will sell. The last step to be crossed becomes inactive. When configuring the strategy, the process is pretty simple. The user can choose the number of steps with a higher and lower step price. With just these 3 settings, you can create a strategy. Now, the challenge with grid trading, is to optimize these 3 settings. █ Maximizing its effectiveness The first thing you want to do before even going into the settings is to find a suitable market for it. You want these 3 requirements:  • A ranging/going sideways market  • High volatility  • High liquidity For example, ETH/BTC is one of the most traded pair in grid trading. It has good volume for the strategy, behaves in a range since late 2021, and has decent volatility daily. █ Knowing the risks Very often, the lowest step is used as a stoploss. As with every trading strategy, there are risks and it is important to understand it. With grid trading, we take a bet that price will fluctuate in a range, and abuse that assumption to profit from price action. If price decides to leave the range, there is one scenario that will put us at risk. In the scenario where price breaks to the top, we are fine, this is take profit. However, if price breaks through the bottom (lowest step), we will find ourselves with a lot of buy orders above current price. That means we have unrealised loss. Now two difficult two choices are in our hands: sell at a loss, expecting price to go lower, and stop the strategy to start a new one at lower prices. Or wait until price climbs back up. In this example, we set a stop loss at 0.063 BTC below the lowest step, and price falls down to 0.048 BTC. If we decided to hold, the unrealised loss would grow bigger as price drops. Now that we know what are the risks, let's see how is profit calculated. █ Calculating Grid Profit We will have two types of profit when grid trading. One this called grid profit. Grid profit is generated every time a step is bought and sold at a higher price. The grid step "height" is the spacing between two steps, usually visualised in a % percentage of price. The sum of all the profits generated from the grid steps is the grid profit. The second type of profit is the open profit. This one is really important and should not be forgotten when calculating your strategy PNL. To put it simply, it is the profit or loss that would be realised if you would close all the open orders at current price. The open profit can vary a lot and it is crucial to know its value when you are looking to take profit or stop the strategy. In this example, I chose round numbers to make it easier. I used 2000 usd as initial capital for the strategy, which contains 20 steps. The strategy will therefore split this equally through the steps, so 100 usd per steps. I chose a grid step of 1.1% of price, which is makes around 1% after fees. It will consequently take 20 closed steps to generate 1% grid profit from the initial capital. After running the strategy for 74 days, we have 21 steps closed, which makes a tiny bit more than 1% grid profit in total. However, the open profit from the 12 orders still open is negative because price dropped. If we were to close all open orders and stop the strategy right now, the total profit would be 1.03 - 4.35 = -3.32 % We can see that it would not be a good time to stop the strategy, and shows that grid trading needs time to generate grid profit. That is why even though it is run on low timeframes, it remains a long term strategy. █ Cyato Grid Cyato Grid is a powerful indicator that can help to better understand and implement this strategy. I will now explain the key features and settings of the indicator, provide examples of how to use it in real-world trading scenarios, and offer tips and advice for maximizing its effectiveness. Backtesting As soon as you set the 3 settings - number of steps, lowest and highest price -, you will get results in the Strategy Tester and in the Backtest table in the top right of the chart. Those results will vary based on your strategy initial capital and order size. The order size being the amount to buy on each step, and is usually the same for each step. A good practice is to divide your inital capital by the number of steps to make sure you will never run out of funds to run the strategy. Order Type The strategy can be configured to use market or limit orders, as you prefer. With market order type, the strategy will place market orders at the current price every time a step is crossed. This allows to ensure that every order is filled, however you are subject to buy and sell a bit higher or lower than the exact grid step prices, and you will pay taker fees. With limit order type, the strategy will place limit orders. This allows to ensure that the strategy will buy and sell at the exact step prices and pay maker fees, which are usually less than taker fees. To make it work, the "Start Date" setting comes into place. Key Features  • Price percentage % step   Lets you set a price percentage between steps. The grid is then generated starting from lower or upper, configurable.  • Trailing Up    Automatically creates new steps when price climbs out of range.  • Trailing Stop    When trailing up is activated, the stop loss will dynamically follow the lowest price.  • Take Profit    Secure profits by stopping the strategy once total volume (grid profit and open profit) reaches a configurable percentage %. Automation You can fully automate the strategy through its alerts. Set the alert messages for buy, sell, take profit, stop losses directly in the indicator settings. Use the parameter "alert() function calls only" and you're good to go. It will use only 1 alert slot to run the whole strategy. Since it is not possible to place orders directly in TradingView, you will need a bot-software to do it. You can use any bot that work with TradingView alerts. Now, I offer a bot system for Binance along with the indicator. More info on my website, link below. Sample Use cases Crypto BNB/BTC BNB/ETH LTC/BTC Forex GBP/JPY EUR/JPY NZD/USD Tips and advice 1 — Set up the grid properly: Make sure you have a clear understanding of the asset you're trading and the market conditions that are affecting it. Set your grid levels based on your analysis of the asset's price movements and volatility. 2 — Adjust the grid as necessary: Keep an eye on market conditions and adjust your grid levels as needed. This will help you capture gains and limit losses as the market moves. 3 — Use proper risk management: Make sure you have a clear understanding of your risk tolerance and use appropriate risk management techniques, such as setting stop-loss orders, to limit your potential losses. 4 — Don't overtrade: Grid trading involves placing a large number of orders, so be mindful of transaction costs and don't overtrade. This will help you maximize your profits and reduce the potential for losses. 5 — Consider using automated software: Grid trading can be automated using software, which can save time and reduce the potential for human error. Consider using a reputable software provider and test your strategy thoroughly before using it in live trading. 6 — Keep a trading journal: Keeping a trading journal can help you evaluate your strategy and make improvements over time. Record your trades, including the grid levels and any adjustments you make, and evaluate your performance regularly. 7 — Stay disciplined: Stick to your strategy and avoid making emotional decisions based on short-term market movements. Stay disciplined and focus on the long-term profitability of your grid trading strategy. ═════════════════════════════════════════════════════════════════════════ █ SCRIPT ACCESS Indicator and automation tools access can be purchased on my website. The link is in my signature below.
Education
by cyatophilum
7
Beating the S&P500 (SPX) Buy&Hold strategy by 16 timesS&P500 (SPX) strategy using Stochastic RSI Min-Max, normalized Volatility and Trailing Stop signals, beats the Buy&Hold strategy by 16 times Embarking on the quest to time the market accurately, the 'Holy Grail' of strategies, led me to create a script to approach this goal. Unlike other strategies that I tested, this one not only surpasses the long-term S&P500 Buy&Hold approach but does so by a remarkable 16.38 times! Initially, I employed an A.I. program based on an LSTM Neural Network using TensorFlow. Despite achieving a 55% next-day prediction accuracy for short/long positions, I sought improvement using a heuristic pine-scripting approach, incorporating stochastic RSI oscillators, moving averages, and volatility signals. With default parameters, this strategy, freely available as "XPloRR S&P500 Stock Market Crash Detection Strategy v2" delivered a staggering 2,663,001% profit since February 1871. In the same period, the Buy&Hold strategy "only" generated 162,599% profit. Picture this: a $1,000 investment in 1871 would now be worth $26,630,014 by February 2024. Check it out for yourself loading this strategy. The script operates as a Stochastic RSI Min-Max script, automatically generating buy and sell alerts on the S&P500 SPX. What sets it apart? The strategy detects "corrections," minimizes losses using Trailing Stop and Moving Average parameters, and strategically re-enters the market after detecting bottoms using tuned Stochastic RSI signals and normalized Volatility thresholds. Tailor its parameters to your preference, use it for strategic exits and entries, or stick to the Buy&Hold strategy and start new buy trades at regular intervals using buy signals only. In the pursuit of minimizing losses, the script has learned the effectiveness of a 9% trailing stop on trades. As you can clearly see on the upper graph (revolving around 100), the average overall green surfaces (profits) of all trades are much bigger than the average red surfaces (losses). This follows Warren Buffets first rule of trading to "Never lose money" and thus minimizing losses. Update: Advanced S&P500 Stochastic RSI Min-Max Buy/Sell Alert Generator I have also created an Alerter script based on the same engine as this script, which auto-generates buy and sell alert signals (via e-mail, in-app push-notifications, pop-ups etc.). The script is currently fine-tuned for the S&P500 SPX tracker, but parameters can be fine-tuned upon request for other trackers or stocks. If you are interested in this alerter-version script or fine-tuning other trackers, please drop me a message or mail xplorr at live dot com. How to use this Strategy? Select the SPX (S&P500) graph and set the value to "Day" values (top) and set "Auto Fit Data To Screen" (bottom-right). Select in the Indicators the "XPloRR S&P500 Stock Market Crash Detection Strategy v2" script and set "Auto Fit Data To Screen" (bottom-right) Look in the strategy tester overview to optimize the values "Percent Profitable" and "Net Profit" (using the strategy settings icon, you can increase/decrease the parameters). How to interpret the graphical information? In the SPX graph, you will see the Buy(Blue) and Sell(Purple) labels created by the strategy. The green/red graph below shows the accumulated profit/loss in % of to the initial buy value of the trade (it revolves around 100%, 110 means 10% profit, 95 means 5% loss) The small purple blocks indicate out-of-trade periods The green graph below the zero line is the stochastic RSI buy signal. You can set a threshold (green horizontal line). The vertical green lines show minima below that threshold and indicate possible buy signals. The blue graph above the zero line is the normalized volatility signal. You can set a threshold (blue horizontal line) affecting buy signals. The red graph above the zero line is the slower stochastic RSI sell signal. You can set a threshold (red horizontal line). The red areas indicate values above that threshold. However real exits are triggered if close values are crossing below the trailing stop value or optionally when the fast moving average crosses under the slow one. The red areas above the threshold are rather indicative to show that the SPX is expensive and not ideal to enter. Please note that in bullish periods the red line and areas can stay at a permanent high value, so it is not ideal to use as a strict sell signal. However, when it drops below zero and the green vertical lines appear, these are strong buy signals together with a high volatility. These Parameters can be changed Buy Stochastic Lookback Buy Stochastic Smoother Buy Threshold Buy Only After Fall Minimum % Fall Sell Stochastic Lookback Sell Stochastic Smoother Sell Threshold Sell Only With Profit Minimum % Profit Use Sell MA Fast MA Sell Slow MA Sell MA Sell Threshold Use Buy Volatility Volatility Smoother Volatility Threshold Use Trailing Stop Use ATR (iso of a fixed percentage for the trailing stop) ATR Lookback Trailing Stop Factor(or fixed percentage if "use ATR" is false) Trailing Stop Smoother Important : optimizing and using these parameters is no guarantee for future winning trades!
SP:SPXEducation
by XPl0RR
Bollinger Bands Part II: Reversal PatternsBollinger Bands Part II: Reversal Patterns Analzying Two Key Patterns Called M-Tops and W-Bottoms This post will go into greater depth than the basic introduction to Bollinger Bands published last week. In particular, it will discuss two key reversal patterns. Both the M-top reversal pattern and W-bottom reversal pattern are price patterns that form in conjunction with the Bollinger Bands. M-Top Pattern The classic M-top reversal pattern forms when two consecutive price highs form an M-shaped price pattern with the first high tagging the upper band and the second high exhausting before tagging the upper band. An example is shown on Supplemental Chart A involving a topping pattern in BTCUSD from early 2021. This weekly chart shows the M-top in red. The second high meets the traditional (strict) criteria of a second peak near—but not touching—the upper band. This is soon evident as a price failure. Supplemental Chart A But an M-top reversal pattern may arise even when two actual tags or pierces of the upper band occur, i.e., the second high may tag the band without invalidating the pattern. This is based on the email discussion this author had with the creator of the Bollinger Bands a while back in 2022, recounted at the end of this post. In short, the most important feature of the pattern is price exhaustion and reversal at the second high . In other words, look for failure of the price move at or near band resistance (e.g., a failed breakout). The following technical signals may provide additional confirmation: weakening momentum indicators, including negative divergences in momentum indicators or a lower high on %B indicator which may present as a %B line divergence. W-Bottom Pattern The classic W-bottom reversal pattern forms when two consecutive price lows form a W-shaped price pattern with the first low tagging the lower band and the second low exhausting before tagging the lower band. Supplemental Chart B But note that a W-bottom reversal pattern may arise even when two actual tags or pierces of the lower band occur, i.e., the second low may tag the band without invalidating the pattern. This is based on the email discussion this author had with the creator of the Bollinger Bands a while back in 2022, recounted at the end of this post. In short, the most important feature of the pattern is price exhaustion and reversal at the second low. In other words, look for failure of the price move at band support (e.g., a failed breakdown). The following technical signals may provide additional confirmation: Strengthening momentum indicators, including positive divergences in momentum indicators or a higher low on % B indicator which may present as a %B line divergence. Understanding the Nuances In June 2022, John Bollinger, the creator of the Bollinger Bands, posted a monthly chart of BTC/USD on Twitter. He described the chart as a “picture perfect double (M-type) top in BTCUSD on the monthly chart complete with confirmation” from %B and bandwidth indicators. He noted also that the signal led to a tag of the lower band. Supplemental Chart C is my own attempt to recreate the monthly chart Bollinger had shown to reflect the same two major monthly highs in BTCUSD in early 2021 and then again in late 2021. Please note that Supplemental Chart C shows a different M-top than the one shown on the weekly time frame above on Supplemental Chart A, which only focuses on one of the two peaks analyzed in this monthly chart. Supplemental Chart C This chart that Bollinger originally posted in 2022 showed two actual tags of the upper band. This was not quite technically within the definition of an M-top in much of the technical literature. My previous reading on M-tops and W-bottoms found that all the definitions and examples showed that the second high or low must not touch or tag the relevant band. But this is incorrect to assume that M-tops and W-bottoms are invalid when this technical definition has not been strictly met, i.e., when two (or more) tags of the bands occurred at both price extremes. Responding to Bollinger’s chart of a “perfect M-top pattern,” I messaged John Bollinger, the creator of the bands, directly, hoping for clarification about the strict definition of M-tops and W-bottoms. My question was whether they can be valid while having two actual tags of the bands at both price extremes—two tags at both highs of an M-top and two tags at both lows of a W-bottom. Or were the technical books correct to say that the second peak or low must approach the bands but fail to touch them. In response to my questions, Bollinger clarified that whether a tag occurs at the second peak / high of an M-top is not important as price failure at upper band resistance. This reasoning can be applied in the inverse to W-bottoms as well. In other words, completing the second half of each formation requires a price failure, rather than a band-tag failure, upper band resistance (M-top) or lower band support (W-bottom). So this broadens the scope of what constitutes a valid M-top or W-bottom pattern. But it does not exclude patterns that meet the conventional technical definition. This means that valid M-top and W-bottom patterns include cases where the secondary high / low fails to tag the upper / lower band. Stated differently, failures to tag the bands at a secondary price high / low can also form valid topping and bottoming patterns. Finally, beware of seeking reversals too soon when price is trending strongly, or walking the bands —pullbacks in that specific scenario are not at all "price failures," and it's important to recognize the difference. Conclusion In short, the key is to apply substance over form, to follow the core concept rather than strictly adhering to the technical rules / definitions. Broaden the scope of the technical requirements to include price failures—on the secondary test—at band resistance or support. This will help traders recognize the patterns arising from this technical indicator more effectively. Further, Bollinger himself recommended using other indicators for confirmation, such as RSI or another indicator that isn't overlapping in its operation too much. Lastly, it may be important to realize that the final failure at or near the bands may not be the second peak or low but the fourth, fifth or sixth. Just draw the M at the end where it fits if there has been strength followed by a failure at or near the bands. And remember trading time frame (M-tops and W-bottoms that are valid have much less significance on shorter time frames and much more and lasting significance on longer time frames. And keep risk management on as always. ________________________________________ Author's Comment: Thank you for reviewing this post and considering its charts and analysis. The author welcomes comments, discussion and debate (respectfully presented) in the comment section. Shared charts are especially helpful to support any opposing or alternative view. This article is intended to present an unbiased, technical view of the security or tradable risk asset discussed. Please note further that this technical-analysis viewpoint is short-term in nature. This is not a trade recommendation but a technical-analysis overview and commentary with levels to watch for the near term. This technical-analysis viewpoint could change at a moment's notice should price move beyond a level of invalidation. Further, proper risk-management techniques are vital to trading success. And countertrend or mean-reversion trading, e.g., trading a rally in a bear market, is lower probability and is tricky and challenging even for the most experienced traders. DISCLAIMER: This post contains commentary published solely for educational and informational purposes. This post's content (and any content available through links in this post) and its views do not constitute financial advice or an investment or trading recommendation, and they do not account for readers' personal financial circumstances, or their investing or trading objectives, time frame, and risk tolerance. Readers should perform their own due diligence, and consult a qualified financial adviser or other investment / financial professional before entering any trade, investment or other transaction.
AMEX:SPYEducation
by SquishTrade
4
Bollinger Bands—Part 1: The BasicsIntroduction Imagine that you are placed on an island with only a trading platform (TradingView of course) and the island gods only permitted three indicators. What three indicators would you carefully select? At the top of my list would be the Bollinger Bands. Some people seek out complex or cryptic indicators in search for a better edge. Of course, some indicators and modes of anlaysis can be very useful despite being complex. But some indicators like the Bollinger Bands, can be valuable because of their simplicity, and they can also have a wealth of analytical value that is more complicated than would appear at a glance. In 1983, John Bollinger invented the eponymous Bollinger Bands. This valuable indicator operates centrally on the concept of standard deviation. In other words, standard deviation is a basic statistical concept behind the indicator, i.e., this concept is basic for mathematics professors and experts, but perhaps intermediate to advanced level for others. Standard Deviation One can easily find the common standard-deviation formula on the internet from many reputable sources. But one doesn't have to master the formula to use the concept of standard deviation—standard deviation essentially measures the variation in the data points around a mean (or average). Khan Academy offers a very useful and insightful guide to those who want to learn the core concepts of standard deviation. Supplemental Chart A contains Khan Academy's standard-deviation illustration and its well-worded explanation, although no one alive today can take credit for discovering and establishing this formula. Supplemental Chart A (Credit to Khan Academy's website for illustration with explanation of standard deviation) Here is a short, somewhat summary explanation of standard deviation's formula (though it doesn't apply to standard deviation of samples, a slightly different formula). Calculate the mean of a data set (e.g., a price series). Calculate each data point's distance, or variance, from that mean. The distance between each data point and the mean is then squared. Sum all the squared distances between each data point and the mean. Divide the sum of the squared distances by the total number of data points, or values in the data set. Take the square root of the quotient from the previous step, which is the average of all data points' squared distances from the mean. Moving Calculations Having identified the statistical concept at the heart of the bands' operation, it helps to remember that the moving average at the center of the bands, sometimes called the middle band of the Bollinger Bands, mean that the entire indicator should be considered a "moving indicator." In other words, even the standard-deviation bands, plotted a given number of standard deviations above or below the moving average, are moving based on the price data that evolves as time passes. Just like the moving average at the center of the bands continues to calculate the mean based on a moving lookback window of 20 periods or some other fixed number of periods, the standard deviations above and below the mean also derive from a moving lookback window. Analysis / Interpretation Bollinger Bands, as John Bollinger described in the journal Technical Analysis of Stocks & Commodities, "answer the question whether prices are high or low on a relative basis." He further explained that the "bands do not give absolute buy and sell signals simply by having been touched; rather, they provide a framework within which price may be related to indicators." He essentially recommended comparing price in relation to the bands and then using the action at the edges of the bands and using such signals in combination with another well-selected indicator (e.g., one might consider RSI). As created by Bollinger, the bands are typically set at +2 and –2 standard deviations above the mean. This can be adjusted on TradingView's platform. A well known trader, Anthony Crudele, uses the Bollinger Bands set at +3 and –3 standard deviations from the mean. He also uses the bands extensively as part of his system, and he does so with some unique and interesting features that he added. This author recommends following his videos regardless of whether his strategy is ultimately followed or adopted or whether some other strategy is adopted as most suitable for a particular asset or time frame. The bands not only measure whether price is high or low on a relative basis. But importantly, they reveal realized-volatility conditions in the market. If price volatility (or variation from the mean without regard to direction) is expanding in a trend-like move on the specific time frame being examined, whether hourly, daily, weekly, monthly or longer, then the Bollinger Bands reveal this by opening and widening, much like jaws. The jaws of the bands contract when volatility is contracting. Volatility—implied and realized—tends toward cycles and mean reversion. So the bands helpfully show traders where volatility is within its cycle. Some traders, for example, use the bands to trade squeezes, and when the bands contract for a substantial period of consolidation and narrow significantly. The squeeze helps increase the probability of a volatility expansion, a potential a widening of the bands as price moves either in the direction of the prior trend or a reversal. As with other indicators, the significance of the signal should be interpreted in the context of the time frame being analyzed. Supplemental Chart B In Supplemental Chart B, notice how the Bollinger Bands contracted as price consolidated in the latter part of last year on the weekly chart of SPY. The Bollinger Bands have been expanding as price has pushed higher to new highs at the degree of trend shown, i.e., the uptrend from 2022 lows to present. Conclusion The Bollinger Bands provide more analytical tools and features than the ones described today. If readers are interested in a more in-depth post on Bollinger Bands (perhaps a Part 2 as contemplated by the title), please indicate this in the comments! Look forward to hearing from you. ________________________________________ Author's Comment: Thank you for reviewing this post and considering its charts and analysis. The author welcomes comments, discussion and debate (respectfully presented) in the comment section. Shared charts are especially helpful to support any opposing or alternative view. This article is intended to present an unbiased, technical view of the security or tradable risk asset discussed. Please note further that this technical-analysis viewpoint is short-term in nature. This is not a trade recommendation but a technical-analysis overview and commentary with levels to watch for the near term. This technical-analysis viewpoint could change at a moment's notice should price move beyond a level of invalidation. Further, proper risk-management techniques are vital to trading success. And countertrend or mean-reversion trading, e.g., trading a rally in a bear market, is lower probability and is tricky and challenging even for the most experienced traders. DISCLAIMER: This post contains commentary published solely for educational and informational purposes. This post's content (and any content available through links in this post) and its views do not constitute financial advice or an investment or trading recommendation, and they do not account for readers' personal financial circumstances, or their investing or trading objectives, time frame, and risk tolerance. Readers should perform their own due diligence, and consult a qualified financial adviser or other investment / financial professional before entering any trade, investment or other transaction.
NASDAQ:NDXEducation
by SquishTrade
2
Mastering Stop-Loss with ATR IndicatorMastering Stop-Loss and Take-Profit with ATR Indicator What is the ATR Indicator? The Average True Range (ATR) indicator is a nifty tool that helps traders gauge the market's volatility. Simply, it tells you how much an asset typically moves in a given timeframe. Placing Stop Loss to Avoid Getting Stopped Out Step 1: Identify ATR Value Look at the ATR indicator on your chart; it's usually at the bottom or top of your screen. Note the ATR value; the higher it is, the more volatile the market. Step 2: Setting Stop Loss Set your stop loss beyond the ATR value to avoid getting prematurely stopped due to regular market fluctuations. For instance, if the ATR is 50, consider placing your stop loss at least 60 points away to give your trade room to breathe. Understand ATR's Role ATR not only helps with stopping losses but also guides in setting realistic take-profit levels. It gives you an idea of how much the asset can move in a given time, assisting you in capturing profits before a potential reversal. Final Tips for Beginners Adapt to Market Changes: ATR values change as market conditions shift. Stay adaptable and reassess your stop-loss and take-profit levels accordingly. Practice on Demo Accounts: Before diving into live trading, practice using the ATR indicator on demo accounts. Gain confidence and refine your strategy without risking real money. In essence, the ATR indicator is your ally in navigating market volatility. By using it wisely, you can enhance your risk management, safeguarding your trades from unnecessary stop-outs while optimizing your profit potential. Happy trading! 📈✨
VANTAGE:SP500Education
by Elite_Forex
A Guide to Effective Trading with the Keltner Channel The Keltner Channel is a technical indicator that helps traders analyze price volatility and identify possible entry and exit points. It was developed by Charles Keltner in the 1960s and remains popular among technical traders today. The main components of the Keltner Channel include: Moving Average (SMA): This is the average of the price over a certain period of time. The moving average is used as the center line of the Keltner Channel and serves as a reference level for analysis. Keltner Channel Upper Band: This band sits above the moving average and is usually calculated as the sum of the moving average and the average true range (ATR) multiplied by a factor. It provides information about potential resistance levels. Lower Keltner Channel Band: This band is below the moving average and is calculated in a similar manner as the upper band, but subtracting the ATR multiplied by a factor. It indicates possible support levels. The basic idea behind using the Keltner channel is as follows: Trend Analysis: If the price is above the upper band of the Keltner Channel, it may indicate an uptrend. If the price is below the lower band, it may indicate a downtrend. Volatility: A widening Keltner Channel indicates an increase in volatility, while a contraction indicates a decrease. Entry and Exit Points: Traders use Keltner Channels to determine when to enter and exit the market. For example, crossing the upper band may signal a possible price decline and be considered a sell signal, while crossing the lower band may be a buy signal. However, in the original methodology it is considered that the crossing of the upper line by the price is a signal to open a long position, and the lower one - to open a short position Signal Filtering: Some traders use other indicators, such as Average Directional Index (ADX), to filter Keltner Channel signals and confirm trend strength. Let's consider this strategy. Entry into a long position will occur when the candle closes above the upper boundary of the Keltner channel and the DMI is above the threshold and shows a green band. Stop loss can be placed on the opposite side of the counter channel and make the risk reward ratio 2:1, for example. For a short position, it will be the opposite when the candle closes below the Keltner channel and the DMI bar will be red and above fresh hope with the same risk reward ratio and the position will reach the target. This strategy is quite simple and can be traded quite effectively if taking into account risk and money management. You can see one of our realized trading bots using Keltner channel breakdowns here. Wunder Keltner bot: Wunder Keltner bot is based on the breakout of the Keltner channel. Therefore we will need two indicators for a complete strategy: DMI and Keltner Channel. What is DMI? DMI stands for Directional Movement Index, and it is a technical indicator used in financial markets, particularly in the field of technical analysis. DMI is designed to assess the strength and direction of a trend, helping traders identify potential trend breakouts and the overall market momentum. It is a straightforward yet powerful tool that can be applied to various trading strategies. The Directional Movement Index consists of two components: the Positive Directional Indicator (+DI) and the Negative Directional Indicator (-DI), which are both calculated using price movement data. Here's how these components work: Positive Directional Indicator (+DI): This component measures the strength of the upward price movement or the bullish trend. It is calculated by comparing the difference between today's high price and yesterday's high price to the difference between yesterday's high and yesterday's low. The result is then smoothed to provide a more accurate reading. Negative Directional Indicator (-DI): On the other hand, the -DI measures the strength of the downward price movement or the bearish trend. It is calculated similarly to the +DI but focuses on the downside price movements. Once the +DI and -DI values are calculated, the DMI itself is often represented as a single line, along with a complementary line known as the Average Directional Index (ADX). The ADX helps traders assess the overall strength of the trend, regardless of whether it's bullish or bearish. Let's take a look at the key entry points. To enter Long, we need to see the deviation above the norm, and it is also important for us that the ADX value is above the specified level. You can see an example of a long position and also an example of a short position. For calculation, 2 channels are used, one for long trades, and the other for short trades. The division into 2 channels is used for more accurate entry calculations depending on trend directions. The ADX indicator is used to filter signals and determine the trend strength. ADX determines the strength of the trend and confirms the entry into the strategy if the value is greater than the level indicated in the settings. A function for calculating risk on the portfolio (your deposit) has been added to the script. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart. Conclusion: The Keltner Channel is a valuable technical indicator that can help traders assess price volatility and make informed decisions about entering and exiting positions in the financial markets. Developed by Charles Keltner in the 1960s, it remains a popular tool among technical analysts due to its simplicity and effectiveness. Remember that no trading strategy is foolproof, and success in the financial markets requires discipline, continuous learning, and adaptability. It's essential to backtest and practice any strategy in a risk-controlled environment before implementing it with real capital. Additionally, always stay informed about market news and events that can impact your trades. Ultimately, the Keltner Channel, when used in conjunction with other tools and a well-thought-out strategy, can be a valuable asset in your trading toolkit, helping you navigate the complexities of financial markets and work toward your trading goals.
Education
by Wunderbit
1
Short Dated Options to Deftly Manage Oil Market Shocks"Volatility gets you in the gut. When prices are jumping around, you feel different from when they are stable" quipped Peter L Bernstein, an American financial historian, investor, economist, and an educator. Crude oil prices are influenced by a variety of macro drivers. Oil market shocks are not rare events. They appear to recur at a tight frequency. From negative prices to sharp spikes in volatility, crude oil market participants "enjoy" daily free roller-coaster rides. Precisely for this reason, crude oil derivatives are among the most liquid and sophisticated markets globally. This paper delves specifically into weekly CME Crude Oil Weekly Options and is set out in three parts. First, what’s unique about short-dated options? Second, tools enabling investors to better navigate crude oil market dynamics. Third, a case study illustrating the usage of weekly crude oil options. PART 1: WHAT’S UNIQUE ABOUT CME CRUDE OIL WEEKLY OPTIONS? Macro announcements such as US CPI, China CPI, Fed rate decisions, Oil inventory changes and OPEC meetings drive oil price volatility. Sharp price movements can lead to premature stop-loss triggers. When prices gap up or gap down at open, stop orders perform poorly leading to substantial margin calls. Weekly options enable hedging against these risks with limited downside and substantial upside. Closer to expiration, options prices are sensitive to changes in the prices of the underlying. Small underlying price moves can have outsized value creation through short-dated options. Hedging with weekly options allows investors to enjoy large upside potential. Short duration vastly reduces the options premium burden. This high risk-reward ratio has made short-dated options popular among both buyers and sellers. The daily traded notional value of Zero-DTE options (Zero Days-To-Expiry, 0DTE) have grown to USD 1 Trillion. Among S&P 500 options, 0DTE options comprise 53% of the average daily volume (ADV), up from 19% a year ago. In 2020, CME launched Weekly WTI options with Friday expiry (LO1-5), offering robust, round-the-clock liquidity and enabling precise event exposure management at minimal cost. These weekly options are now the fastest growing energy products at CME with ADV growing 69% YoY with June 2023 ADV up 136% YoY. Building on rising demand, CME added weekly options expiring Monday and Wednesday. At any time, the four nearest weeks of each option are available for trading. Weekly options settle to the latest benchmark CL contract and like other CME WTI products, they are physically deliverable ensuring price integrity. Each weekly WTI options contract provides exposure to 1,000 barrels. Every USD 0.01 change per barrel change in WTI represents a P&L change of USD 10 in premium per contract. PART 2: EIGHT TOOLS TO BETTER NAVIGATE CRUDE OIL MARKET DYNAMICS Highlighted below are eight critical tools across TradingView and CME enabling investors to better navigate oil market dynamics. 1. OPEC+ Watch OPEC+ Watch charts the probability of different outcomes from OPEC+ meetings. Probabilities are derived from actual market data & represent a condensed consensus market view of forthcoming meetings. 2. News Flow TradingView’s News section collates the key market developments impacting crude oil. 3. Forward Curve TradingView maps crude oil prices across the forward curve exhibiting oil’s term structure. Augmenting the forward curve chart is a table CL contracts across various expiries with technical signals embedded in them enabling investors to spot calendar spread trading opportunities. 4. TradingView Scripts Supported by a vibrant community of script creators, TradingView has curated scripts catering to the specific needs of crude oil traders. OIL WTI/Brent Spread by MarcoValente: Shows the spread between WTI and Brent crude. This spread is growing in importance with growth in US oil exports. Seasonality Indicator by tradeforopp: Presents seasonal price trends along with key pivot points to guide traders. 5. Economic Calendars TradingView’s economic calendar highlights upcoming economic events segmented by dates and with countdown timers to help traders better manage their portfolios. Augmenting, TradingView’s calendar is CME’s Economic Events Analyzer which lists key events specifically impacting energy markets and highlights the relevant weekly options contract. 6. Options Expiration Calendar CME’s Options Expiration Calendar is a comprehensive yet condensed view of upcoming expiration dates of WTI options, even those that are not listed yet. 7. Daily/Weekly Options Report CME’s Daily/Weekly Options Report profiles volumes and OI by strike price for weekly options supplying key stats such as Put/Call ratio and key strike levels at a glance. 8. Strategy Simulator CME’s strategy simulator allows investors to simulate diverse options strategies. Selecting the relevant instruments and adding each component of the overall position automatically calculates the payoff while still allowing modification of key statistics such as volatility based on user inputs. The below shows the payoff of an ATM straddle position for the upcoming Monday weekly option. It also allows simulating various market conditions. Selecting price trends such as up fast, up slow, flat, down slow, down fast can simulate the changes in P&L. PART 3: ILLUSTRATING USAGE OF WEEKLY CRUDE OIL OPTIONS Why does CME list weekly options expiring on Monday, Wednesday, and Friday? Each of these address specific macro events. OPEC meeting outcomes are typically announced over the weekend leading to gaps in prices on Monday. EIA weekly crude oil inventory data are released on Wednesdays. Key US economic data such as CPI and Non-farm payrolls are released on Fridays. Use Case for Options expiring on Monday These can be used to hedge against downside risk associated with weekend events. For instance, in April, OPEC+ announced major supply cuts at their meeting on Sunday. This led to WTI price spiking 4% at market open. This can lead to “gap risk.” Gap risk refers to the risk that markets may open sharply above or below their previous close. Since, price never passes the levels in between, stop loss orders fail to trigger at set levels resulting in more-than-anticipated realised losses. Such gap risks from weekend news can be managed through Monday weekly options which provides a predictable and resilient payoff with limited downside risk. Use Case for Options expiring on Wednesday Oil inventory reports by EIA (U.S. Energy Information Administration) and API (American Petroleum Institute) are released every week on Tuesday and Wednesday respectively. Major misses/beats against expectations for these releases can result in large price moves. Wednesday options come in handy to better manage volatility stemming from these shocks or surprises. Weekly options provide superior ROI on small moves when compared to futures. Favourable price moves deliver larger payoffs from position in weekly options than futures and shorter expiries allow for much lower premium than monthly options. Illustrating with Back tested Results On June 14th, Crude price fell by 1.7% (USD 1.2) to USD 68.7/barrel upon release of inventory data that showed a larger than expected inventory build-up. In the lead up to this data release, a crude oil participant could either (a) Short Crude Oil Futures, or (b) Long Weekly Crude Oil Put Option. Summary outcomes from these two strategies are tabulated and charted below. The results speak for themselves. Short dated long put option is capital efficient, prudent, and credible as a risk management tool. That said, participants must evaluate the risk return profile taking into consideration market liquidity and volatility levels, among others, when choosing between instruments. KEY TAKEAWAYS In summary, 1) Weekly Options can be cleverly deployed to hedge against shocks in oil markets. 2) TradingView & CME provide a rich suite of tools to deftly navigate the oil market dynamics. 3) Weekly options expiring on (a) Monday helps manoeuvre developments over the weekend, (b) Wednesday helps to manage inventory data linked shocks, and (c) Friday enables investors to trade and hedge around key US economic data. MARKET DATA CME Real-time Market Data helps identify trading set-ups and express market views better. If you have futures in your trading portfolio, you can check out on CME Group data plans available that suit your trading needs www.tradingview.com DISCLAIMER This case study is for educational purposes only and does not constitute investment recommendations or advice. Nor are they used to promote any specific products, or services. Trading or investment ideas cited here are for illustration only, as an integral part of a case study to demonstrate the fundamental concepts in risk management or trading under the market scenarios being discussed. Please read the FULL DISCLAIMER the link to which is provided in our profile description.
NYMEX:CL1!Education
by mintdotfinance
6
Trading Breakouts with Donchian ChannelsBreakout trading is a popular strategy among traders seeking to capitalize on significant price moves that occur when the price breaks out of a well-defined range. It involves identifying key levels of support and resistance and entering trades when the price breaks above resistance or below support. By catching these breakout movements early, traders aim to capture potential profits as the price continues to move in the breakout direction. Donchian Channels are constructed by plotting three lines on a price chart: the upper band, the lower band, and the middle line. The upper band represents the highest high over a specified period, while the lower band represents the lowest low. The middle line, also known as the median line, is the average of the upper and lower bands. The interpretation of Donchian Channels is relatively straightforward. When the price breaks above the upper band, it signals a potential bullish breakout, suggesting that the price may continue to rise. Conversely, when the price breaks below the lower band, it indicates a potential bearish breakout, suggesting that the price may continue to decline. The width between the upper and lower bands represents the volatility of the asset. Understanding Donchian Channels A. Explanation of Donchian Channels and their construction: Donchian Channels are constructed using historical price data and provide traders with a visual representation of market volatility and potential breakout opportunities. To calculate Donchian Channels, traders select a specific lookback period, which determines the number of bars or candles used in the calculation. This lookback period can be adjusted based on the desired trading timeframe and market conditions. The upper band of the Donchian Channels represents the highest high over the selected period, while the lower band represents the lowest low. The middle line, also known as the median line, is calculated as the average of the upper and lower bands. By plotting these lines on a price chart, traders can visualize the range within which the price has been oscillating over the selected period. It is important to note that the choice of the lookback period will impact the sensitivity of the Donchian Channels. A shorter lookback period will result in narrower channels, capturing more recent price movements, while a longer lookback period will yield wider channels, incorporating a broader range of historical price data. B. Components of Donchian Channels: – Upper band : The upper band of the Donchian Channels represents the highest high over the selected period. It serves as a potential resistance level and provides traders with a reference point for potential breakout opportunities above this level. – Lower band : The lower band represents the lowest low over the selected period and acts as a potential support level. Traders monitor the price's behavior in relation to the lower band to identify potential breakout opportunities below this level. – Middle line : The middle line, often referred to as the median line, is calculated as the average of the upper and lower bands. It serves as a midpoint between the two bands and provides traders with a reference point for the mean or average price within the selected period. The middle line can act as a potential dynamic support or resistance level, depending on the direction of the price movement. C. Interpretation of Donchian Channels: Donchian Channels provide valuable insights into market volatility and potential breakout opportunities. Traders can interpret Donchian Channels in the following ways: – Market volatility : The width of the Donchian Channels reflects the level of market volatility. Wider channels indicate higher volatility, suggesting larger price swings and potentially stronger breakout opportunities. Narrower channels, on the other hand, indicate lower volatility and may suggest a period of consolidation or low trading activity. – Breakout opportunities : Traders monitor the price's behavior in relation to the upper and lower bands of the Donchian Channels to identify potential breakout opportunities. A breakout occurs when the price breaks above the upper band or below the lower band. A breakout above the upper band suggests a potential bullish opportunity, while a breakout below the lower band indicates a potential bearish opportunity. Traders may consider entering a trade when a breakout occurs, anticipating further price movement in the breakout direction. – Squeezing Donchian Channels: When the width between the upper and lower bands narrows significantly, it is referred to as a "squeeze." A squeeze indicates low volatility and a potential upcoming breakout. Traders watch for a breakout in either direction when the Donchian Channels squeeze, as it suggests that the market is likely to enter a period of increased volatility and directional movement. Identifying Breakout Opportunities with Donchian Channels A. Breakout above the upper band: A breakout occurs when the price crosses above the upper band of the Donchian Channels, indicating a potential bullish opportunity. Traders can use different entry strategies to capitalize on breakouts above the upper band: – Buying on the close above the upper band : Traders may choose to enter a long position when the price closes above the upper band. This approach confirms the breakout and provides confirmation that the upward momentum is sustained. – Percentage deviation from the upper band : Another approach is to wait for a specific percentage deviation from the upper band before entering a trade. For example, a trader might enter a long position if the price moves a certain percentage, such as 1% or 2%, above the upper band. This method allows for a more flexible entry and can help filter out minor price fluctuations. It is important to consider other technical indicators, such as volume or momentum oscillators, to confirm the strength of the breakout and assess potential price targets or exit points. Traders may also incorporate stop-loss orders to manage risk and protect against potential false breakouts. B. Breakout below the lower band: A breakdown occurs when the price crosses below the lower band of the Donchian Channels, signaling a potential bearish opportunity. Traders can use various entry strategies to take advantage of breakouts below the lower band: Selling on the close below the lower band: Traders may choose to enter a short position when the price closes below the lower band, confirming the breakdown and indicating a potential downtrend. Percentage deviation from the lower band: Alternatively, traders can wait for a specific percentage deviation from the lower band before entering a trade. For instance, they might enter a short position if the price moves a certain percentage below the lower band. This approach adds a level of confirmation and helps filter out minor price fluctuations. Similar to breakouts above the upper band, traders should consider additional technical indicators to confirm the breakdown and identify suitable price targets or exit points. Stop-loss orders are essential to manage risk and limit potential losses if the breakout turns out to be a false signal. It is worth noting that not all breakouts or breakdowns lead to sustained price movements. Traders should exercise caution and conduct thorough analysis, considering market conditions, overall trend, and other relevant factors. Using Donchian Channels as a tool for identifying breakout opportunities provides a structured approach to entering trades and enhances decision-making in breakout trading strategies. Confirmation Techniques with Volume Volume plays a crucial role in confirming breakouts and validating the strength of price movements. Higher volume during a breakout suggests greater market participation and increases the likelihood of a sustained move. Traders can use volume indicators in conjunction with Donchian Channels to confirm breakouts: – On-Balance Volume (OBV) : OBV is a popular volume indicator that measures buying and selling pressure. Traders can compare the OBV trend with the breakout in Donchian Channels to assess whether volume supports the breakout movement. If OBV shows a positive trend alongside a breakout above the upper band or below the lower band, it provides additional confirmation. – Volume Weighted Average Price (VWAP) : VWAP is another useful volume-based indicator that calculates the average price weighted by trading volume. Traders can compare the current price with the VWAP to determine if volume supports the breakout. If the price moves above the upper band accompanied by a surge in volume and a deviation from the VWAP, it strengthens the breakout signal. Managing Risk in Donchian Channel Breakout Trading A. Setting stop-loss orders: Stop-loss orders serve as a protective mechanism to limit potential losses if the breakout trade fails. By defining a predetermined level at which to exit the trade, traders can control and manage their risk effectively. Traders can use various techniques to determine the placement of stop-loss orders. One approach is to place the stop-loss below the breakout candle or below the lower band of Donchian Channels. This ensures that if the price reverses and breaks back into the channel, the trade is exited to minimize potential losses. B. Implementing position sizing: Position sizing is the process of determining the number of contracts or shares to trade based on individual risk tolerance. Traders should consider their risk appetite and financial objectives when determining position size. Common methods for position sizing include the fixed percentage method (risking a certain percentage of capital per trade) or the fixed dollar amount method (risking a specific dollar amount per trade). Volatility and the characteristics of the breakout can influence position sizing. Traders may opt for smaller position sizes in more volatile markets to manage risk effectively. Additionally, if the breakout signal exhibits higher confidence, such as a wide breakout range or strong confirmation signals, traders may consider increasing their position size to capitalize on potential larger moves. Fine-tuning Donchian Channel Breakout Strategies While Donchian Channels provide valuable insights into breakouts, combining them with trend-following indicators can enhance the effectiveness of the strategy. Trend indicators, such as moving averages or trendlines, can help traders identify the direction of the prevailing trend. By aligning the breakout trades with the trend direction, traders can increase the probability of successful trades. Momentum oscillators can be used alongside Donchian Channels to provide additional confirmation of breakout signals. Indicators like the Relative Strength Index (RSI) or the Stochastic Oscillator can help traders assess overbought or oversold conditions and gauge the strength of the breakout. Combining the signals from these oscillators with Donchian Channel breakouts can offer a more comprehensive view of market dynamics. Different timeframes can have varying impacts on the frequency and reliability of Donchian Channel breakouts. Shorter timeframes, such as intraday charts, may generate more frequent but potentially smaller breakouts. Conversely, longer timeframes, such as daily or weekly charts, may produce fewer but more significant breakouts. Traders should consider their trading style, available time, and risk tolerance when selecting the timeframe for breakout trading. Backtesting is a crucial step in fine-tuning Donchian Channel breakout strategies. By applying historical data to the strategy on various timeframes, traders can assess the performance and identify optimal parameters. Through backtesting, traders can refine their entry and exit rules, determine the most suitable lookback periods, and validate the strategy's effectiveness across different market conditions. Limitations and Considerations A. False breakouts and whipsaws: Despite the effectiveness of Donchian Channel breakout strategies, false breakouts can occur, leading to potential losses. False breakouts happen when the price briefly moves beyond the channel but quickly reverses back into the range. Traders must be aware of this possibility and implement risk management techniques to mitigate potential losses. To minimize the impact of false breakouts, traders can employ confirmation techniques, such as volume analysis or candlestick patterns. These tools can provide additional validation before entering a trade, reducing the risk of being caught in false breakout scenarios. By layering Donchian Channels of varying lengths over each other, range-bound or trending markets can become clearer and reduce the potential for trading a false breakout. Here we have channel lengths of 25, 50, 100, 150, and 200 overlaid to help determine the state of the market and identify take profit and stop loss levels: B. Market conditions affecting breakout trading: During periods of low volatility, price movements can become sluggish, resulting in fewer and less significant breakouts. Traders should be mindful of market conditions and adjust their expectations and strategies accordingly. It may be necessary to explore alternative trading approaches or consider other indicators that perform better in low volatility conditions. Donchian Channel breakout strategies work best in trending markets where price movements exhibit clear directional biases. In ranging markets, where prices oscillate within a defined range, breakouts may be less frequent and less reliable. Traders should exercise caution and consider alternative strategies when faced with prolonged ranging market conditions. C. Psychology and discipline in breakout trading: Breakout trading requires discipline and emotional control. Traders must be prepared for periods of drawdowns, missed opportunities, and potential losses. Maintaining a disciplined mindset, sticking to predetermined rules, and avoiding impulsive decisions are essential for long-term success in breakout trading. Successful breakout traders understand the importance of patience and following their predefined rules. It is crucial to wait for confirmed breakouts and not chase every potential trade. Adhering to risk management strategies, position sizing rules, and maintaining a consistent approach are key to managing emotions and maintaining discipline in breakout trading. Conclusion Donchian Channel breakout trading strategies hold immense potential for traders. By effectively utilizing Donchian Channels and incorporating appropriate risk management and confirmation techniques, traders can enhance their trading decisions and potentially realize substantial profits. The systematic approach offered by Donchian Channels enables traders to spot breakouts early and participate in significant price moves. To fully harness the power of Donchian Channels in breakout trading, it is essential for readers to engage in further exploration and practice. Backtesting historical data, paper trading, and implementing real-time trades based on Donchian Channel breakout strategies can provide valuable insights and hands-on experience. Continuous learning and refining of strategies will pave the way for improved trading outcomes. By understanding the construction and interpretation of Donchian Channels, incorporating confirmation techniques, managing risk effectively, and honing their skills through practice, traders can unlock the potential for consistent profits. Embrace the power of Donchian Channels, continue to explore, and adapt your strategies to evolving market conditions. May your journey with Donchian Channel breakout trading be filled with success and prosperity. Happy Trading, Tyler
Education
by LeafAlgo
18
Educational: Grid Trading, What is it? How it works?Grid trading is often marketed as a way to win every trade. People usually get away with this type of marketing of the trading style due to the fact that grid trading does not care for market execution in the sense of market direction because you will close profitable trades if the market goes up or down. But it's not as simple as that. What is Grid trading? Grid trading is a type of trading strategy that makes use of market price variations by placing buy and sell orders at regular intervals around a base price. The foreign exchange market is where grid trading is most frequently employed, but it can also be used on other markets, like those for futures contracts. How to execute trades on a grid The image above explains exactly how positions that run in the upper direction are executed. Let's break down the process: (1) At the start of your grid trading system, you execute a buy and a sell position with the same lot size. (2) You will only set a take profit and a buy limit/sell limit, but no stop loss. (3) Assuming the price runs in the direction of the buy and you have a 10-pip stop loss, once the price hits your 10-pip stop loss, you will also execute a sell position via the sell limit. This sell position will have a 10-pip take profit in the opposite direction. See demonstration below: There is no restriction on the size of the grid. It does not have to be 10 pips apart. The distance of the grid is explained further in the publication. Here is a video using a trading simulator to show you how these positions would be executed : So, as you can see, with this style of trading, you can potentially make money whether the price goes up or down. However, it can be quite challenging to execute and maintain a large number of trades. Therefore, individuals typically employ automated systems or use trading software to manage and monitor these trades. Trending Market Grid trading can be used to profit from both trending and ranging markets. In a trending market, grid trading involves placing buy orders above the base price and sell orders below the base price. This way, the trader can capitalize on the price movement in a sustained direction. For example, if the base price of Bitcoin futures is $60,000, the trader can place buy orders every $1,000 above the base price. This is also sometimes wrong referred to as dollar cost averaging or compounding your trade which are very different investment strategies. Grid trading's key benefit is that it can be readily automated using trading bots and does not require a lot of forecasting of market direction. Grid trading's main disadvantage is that, if the market goes against the grid and the trader does not apply appropriate risk management strategies like stop-loss limits or position sizing, it may result in significant losses. Grid Size Choosing a grid spacing is one of the most important aspects of grid trading. This depends on a number of elements, including: - The volatility of the market: The more volatile the market is, the wider the grids should be to avoid frequent executions and commissions. - The personal preference of the trader: The trader should choose a grid size that suits their trading style and risk tolerance. Technical indicators like moving averages or Bollinger bands are sometimes used to calculate the spacing between the grids. These indicators can be used to determine the market's volatility and average price over a specific time frame. You can also use basic price action to determine what range the market is likely to tstay within and then calculate the grid in-between Ranging or Trending: Identifying whether the market is trending or range is another important aspect of grid trading. This can be used to determine whether to employ grids that move with the trend or against it. There are a number of approaches to determine if the market is trending or fluctuating, including: - Using trend lines or channels: A trend line or channel is a line that connects higher highs or lower lows in a trending market. A break of a trend line or channel can indicate a change in trend or a range-bound market. - Using trend indicators such as ADX or MACD: The average directional index (ADX) measures the strength of a trend on a scale from 0 to 100. A high ADX value (above 25) indicates a strong trend while a low ADX value (below 20) indicates a weak trend or a range-bound market. The moving average convergence divergence (MACD) measures the difference between two moving averages of different lengths. A positive MACD value indicates an uptrend while a negative MACD value indicates a downtrend. A crossover of MACD lines or zero line can indicate a change in trend or a range-bound market. Link to a publication on MACD : - Using range indicators such as RSI or Stochastic: The relative strength index (RSI) measures how overbought or oversold a market is on a scale from 0 to 100. A high RSI value (above 70) indicates an overbought market while a low RSI value (below 30) indicates an oversold market. A reversal of RSI from extreme levels can indicate a change in trend or a range-bound market. Link to related publication:
COINBASE:ETHUSDEducation
by ChristopherDownie
2
How to work with liquidity grab?Hello everyone👋 Today we will discuss how to effectively work with areas of increased liquidity. Actually, it would be appropriate to make this post after we have examined how order flow is formed in the market in order to understand the technical aspect of working with liquidity. Therefore, first, we will provide some introductory information using a long position as an example. When a trader buys an asset, they usually set a stop loss at a certain level or, if they don't use protective orders, their position will have a liquidation price depending on the chosen leverage. Based on this, when a specific price level is reached (stop loss or liquidation), their asset will be sold with a market order that will match the nearest limit order. Hence the conclusion: any exit from a losing position, as described above, is someone else's entry into a position with a limit order, often at a favorable price. This is how the positions of all major market participants are accumulated. So, we simply need to estimate where the maximum number of active stop losses is located and make a trading decision based on that. Most often, stop orders are located in the following zones: 1️⃣Obvious levels with equal highs/lows. 2️⃣Above/below any high/low in an obvious trend. After identifying such zones using our indicator or independently, you can take trades in the direction of liquidity grab (counter-trend trades with high potential but also high risk) or wait for actual liquidity grab and confirmation to enter a trend trade. In the next post, we will explore the technical aspect of liquidity grab for a deeper understanding of the topic. We look forward to your questions. Happy trading!
Education
by PhantomFlow
Ichimoku Cloud Demystified: A Comprehensive Deep DiveHello TradingView Community, it’s Ben with LeafAlgo! Today we will discuss one of my favorite indicators, the Ichimoku Cloud. The Ichimoku is a versatile trading tool that has captivated traders with its unique visual representation and powerful insights. We will dive deep into understanding the Ichimoku Cloud, explore its history, discuss its parts, highlight real-life examples, and address potential pitfalls. By the end of this article, we believe you will know how to leverage the Ichimoku Cloud effectively in your trading endeavors. Let’s dive in! Origin of The Ichimoku Cloud The Ichimoku Cloud, also known as Ichimoku Kinko Hyo, was developed by Goichi Hosoda in the late 1930s but was not published until later in the 1960s. Its name translates to "one glance equilibrium chart," reflecting its ability to provide a holistic view of market dynamics with a single glance. Over time the Ichimoku Cloud has become a popular trading tool among new and seasoned traders. Components of The Ichimoku Cloud Some traders believe the Ichimoku cloud is a complex jumble of lines with no rhyme or reason, but this is not necessarily true. The best way to understand the Ichimoku cloud is to break it down into its respective parts. Each element contributes to the overall interpretation of price action, trend direction, support and resistance levels, and potential entry and exit points. The Ichimoku Cloud has five components: Tenkan-sen, Kijun-sen, Senkou Span A and B, and Chikou Span. The Tenkan-sen and Kijun-sen, often called the Conversion Line and Base Line, respectively, are essential in identifying trend direction and momentum. Below we can see a bullish signal happens when the Tenkan-sen crosses above the Kijun-sen. Conversely, a bearish signal occurs when the Tenkan-sen crosses below the Kijun-sen. Typical length inputs for the Tenkan-sen and Kijun-sen are 9 and 26. The Senkou Span A and B form the cloud or "Kumo." These components serve as dynamic support and resistance levels, with Senkou Span A calculated as the average of the Conversion Line and Base Line and Senkou Span B representing the midpoint of the highest high and lowest low over a specified period, typically 52. The cloud's thickness and color provide visual cues for potential market strength and volatility. The Chikou Span, or the Lagging Span, is the current closing price plotted 26 periods back on the chart. It helps traders gauge the relationship between the current price and historical price action, providing insights into potential trend reversals or continuation. Putting the parts together gives us a complete picture of the Ichimoku Cloud. Each aspect contributes to the one-glance equilibrium theory, giving traders a more holistic view of price action. Applying the Ichimoku Cloud in Trading We now better understand all parts of the Ichimoku cloud, but that means little if we don’t understand how it can be utilized in trading. Let's explore examples that demonstrate the practical application of the Ichimoku Cloud: Example 1: Trend Following In an uptrend, we would look for the Tenkan-sen to cross above the Kijun-sen while the price remains above the cloud. When the price retraces to the cloud, a long position opportunity may arise, with the cloud acting as support. The Chikou Span should also be above the historical price action, confirming the bullish sentiment. Example 2: Trend Reversals and Breakout Opportunities A potential trend reversal or continuation can be identified when the Tenkan-sen crosses above the Kijun-sen and the price moves above the cloud. A breakout trade can initiate when the price breaks through the cloud's upper boundary, indicating a shift in momentum. For the Ichimoku cloud to give its strongest confirmation of a reversal, some traders will take a fairly conservative approach and wait for a few things to occur. Traders typically wait for a kumo twist, the Tenkan-sen/Kijun-sen cross, and the Chikou Span to break the cloud and be above the price. The reverse of these signals can be used in the same fashion for a short position. Example 3: The Kumo Twist In a trend, a Kumo Twist can signal a potential trend reversal. Look for the Senkou Span A to cross above or below the Senkou Span B within the cloud. This twist can confirm a shift in market sentiment. Traders can enter a position when the twist is confirmed, placing a stop loss above or below the cloud or the recent swing high/low. I think of the Kumo twists and subsequent clouds as a trend filter. Placing longs on the bullish side or shorts on the bearish side, however, some traders use the Ichimoku Cloud in a contrarian fashion. Contrarian trades can be profitable using this method as price tends to pull back to the clouds A or B span where support or resistance may lie. Pitfalls and Challenges: Avoiding Common Mistakes While the Ichimoku Cloud is a powerful tool, it is paramount to be aware of potential pitfalls. Here are a few challenges to navigate: False Signals and Choppy Market Conditions In ranging or volatile markets, cloud signals may generate false indications. During such periods combine the Ichimoku Cloud with other technical indicators or wait until the market picks a direction. Moving out to higher time frames can help clear the murkiness of consolidation phases and provide a clearer picture of the trend, in turn, weeding out false signals. Overcomplicating Analysis The Ichimoku Cloud provides a wealth of information, but it's crucial to maintain simplicity and focus. Avoid overcrowding the chart with an abundance of indicators, especially other overlays. It is easy to get lost in the sauce or run into redundancies with too much on the chart. Testing and Adapting Each market has its characteristics or volatility, and it's essential to backtest the Ichimoku Cloud strategy, experiment with different parameters, and adapt to market conditions over time. Many traders rely on the standard settings, but in my time developing trading algorithms, I have learned that those settings do not hold from market to market or consistently over time. It is critical to regularly revisit your settings or overall trading strategy to make sure you are drawing on the best available information the Ichimoku Cloud can give. Enhancing the Ichimoku Cloud Strategy To enhance your understanding and utilization of the Ichimoku Cloud, consider the following: Incorporating Other Technical Indicators Combining the Ichimoku Cloud with other indicators, such as oscillators, to confirm signals can be beneficial. I know I said not to over-clutter your chart with other indicators, but that is a rule of thumb more set for overlays. Timeframe Considerations Adapt the Ichimoku Cloud to different timeframes based on your trading style. Higher time frames may provide more reliable signals, while lower timeframes may offer shorter-term opportunities. I don’t believe it ever hurts to back out a few time frames to get a clear picture of market dynamics and avoid tunnel vision. Conclusion The Ichimoku Cloud is a versatile indicator, and today we scratched the surface of how it can be appropriately used. Remember, practice, patience, and continuous learning are critical for refining your skills and adapting the Ichimoku Cloud strategy to ever-evolving market conditions. If there is anything unclear or you have any questions, please don’t hesitate to comment below. Trading education is our passion, and we are happy to help. Happy trading! :)
Education
by LeafAlgo
49
📊 Volume Profile: IndicatorsThere’s a reason why trading volume has been a standard indicator on every piece of charting software over the last 30 years… it provides a crucial edge. Volume provides you with logical insight into the activity of market participants at varying price levels. Volume analysis helps traders to become more reactionary to price movements rather than trying to predict where price will go next, as is the case with most technical indicators. 📍Key takeaways about volume Key takeaways about the normal volume indicator plotted on the X-axis in trading: 🔹Volume Indicator: The normal volume indicator measures the total number of shares or contracts traded during a given time period. It is commonly displayed as a histogram or line chart, with the X-axis representing time. 🔹Liquidity: Volume is a crucial metric as it provides insights into the liquidity of a security. Higher volume generally indicates greater market participation and liquidity, making it easier to buy or sell the asset without significantly impacting its price. 🔹Confirmation: Volume can confirm the validity of price movements. In an uptrend, increasing volume supports the bullish move, suggesting strength and conviction among buyers. Conversely, declining volume during an uptrend may signal weakness or lack of interest. The same principles apply to downtrends. 🔹 Breakouts and Reversals: Volume analysis is often used to identify breakouts and potential trend reversals. A significant increase in volume during a breakout suggests a higher probability of a sustained move, while decreasing volume near a support or resistance level might indicate a potential reversal. 🔹Divergence: Volume can reveal divergence between price and market sentiment. For example, if prices are rising but volume is decreasing, it could suggest that the rally is losing steam and a reversal may be imminent. Similarly, increasing volume during a price decline might indicate selling pressure and further downside potential. 🔹Confirmation of Patterns: Volume can provide confirmation or invalidation of chart patterns such as triangles, head and shoulders, or double tops/bottoms. Higher volume during pattern formations enhances their reliability, while low volume can cast doubt on the pattern's significance. 🔹Watch for Extreme Volume: Abnormal spikes in volume can indicate significant market events, such as earnings releases, news announcements, or institutional buying/selling. Unusual volume can lead to increased volatility and potentially offer trading opportunities. 🔹Relative Volume: Comparing current volume to historical average volume helps gauge the significance of the current trading activity. Higher volume relative to the average may imply increased interest, while lower volume might suggest a lack of conviction or reduced market participation. 👤 @AlgoBuddy 📅 Daily Ideas about market update, psychology & indicators ❤️ If you appreciate our work, please like, comment and follow ❤️
Education
by QuantVue
35
Introducing the Volatility Adjusted ADX (VADX)In this video, Stock Justice introduces you to the Volatility Adjusted ADX (VADX), a powerful tool that combines trend strength and market volatility. Learn how to customize your settings for optimal analysis and how this indicator, with its proprietary mathematical formulation, offers a nuanced perspective on market dynamics. Discover the benefits of normalized data and how to read and interpret the VADX line in conjunction with other indicators. All of this, delivered in Stock Justice's engaging style, will empower your technical analysis toolkit. Be ready to trade safe, trade smart!
NASDAQ:TSLAEducation
by StockJustice
Choosing Your Channel: Bollinger, Donchian, or Keltner?When it comes to trading financial instruments, traders have a plethora of technical indicators to choose from. Among these, Bollinger Bands, Donchian Channels, and Keltner Channels stand out as popular tools for analyzing price movements and identifying potential trading opportunities. Each of these channels has its advantages and unique methods of application. This blog will compare these three channels and provide examples of how each can be used, helping you decide which one is right for you. I. Bollinger Bands Understanding Bollinger Bands Bollinger Bands, developed by John Bollinger in the 1980s, is a volatility-based indicator that measures the standard deviation of price movements. It consists of three lines: a simple moving average (SMA) and two bands that are typically set at two standard deviations above and below the SMA. The distance between the bands adjusts as volatility increases or decreases. Using Bollinger Bands Bollinger Bands are useful for identifying price movements and potential reversals. When the bands contract, it indicates low volatility, and when they expand, it signals high volatility. A common strategy is to look for a breakout or breakdown when the bands contract. Example: If a stock's price has been trading within a narrow range, and the Bollinger Bands contract, a trader might anticipate a breakout or breakdown. If the price breaks above the upper band, it could signal a bullish trend, while a break below the lower band suggests a bearish trend. This breakout should be confirmed with other indicators such as the MACD or RSI. II. Donchian Channels Understanding Donchian Channels Donchian Channels, developed by Richard Donchian in the 1960s, is a trend-following indicator that measures the highest high and lowest low over a set number of periods, typically 20 periods. It consists of three lines: the upper channel line, the lower channel line, and the middle line, which is the average of the upper and lower lines. Using Donchian Channels Donchian Channels are primarily used to identify potential breakouts and breakdowns. Traders often use the channels to assess the strength of a trend and determine entry and exit points. The Donchian cloud can be a great tool for establishing lines of support and resistance as the price makes higher highs and lower lows and conversely lower highs or lower lows. Example: If a stock's price is consistently hitting highs, a trader might use the Donchian Channels to identify a possible breakout. If the price breaks above the upper channel line, it could signal a continuation of the bullish trend. Conversely, if the price breaks below the lower channel line, it may indicate a potential trend reversal. I typically look for a secondary lower high or higher lower to confirm a reversal and then confirm the breakout with an oscillator as seen in the example below. III. Keltner Channels Understanding Keltner Channels Keltner Channels, developed by Chester Keltner in the 1960s and later modified by Linda Raschke, is a volatility-based indicator that uses the average true range (ATR) to measure price movements. It consists of three lines: an exponential moving average (EMA) and two bands set at a multiple of the ATR above and below the EMA. Using Keltner Channels Keltner Channels are effective for identifying potential trading opportunities during trending markets and can be used in conjunction with other indicators to confirm price movements. The Keltner Channel is a great tool for identifying overbought/ oversold conditions in a trend. This can help traders find better points of entry for a trade. Example: A trader might use Keltner Channels to identify potential pullbacks in a trending market. If the price moves above the upper channel line during an uptrend, it could signal an overbought condition, and the trader might wait for the price to pull back toward the EMA before entering a long position. Similarly, if the price falls below the lower channel line during a downtrend, it might indicate an oversold condition, and the trader could wait for a bounce back toward the EMA before entering a short position. The trader should also verify the bounce with other indicators as shown below. IV. BONUS: Keltner/Bollinger Bands Squeeze Strategy Channels do not have to be exclusively used on their own. The Keltner/Bollinger Bands Squeeze Strategy is a powerful technique that combines the strengths of both Keltner Channels and Bollinger Bands to identify potential trading opportunities. By understanding the nuances of this strategy, traders can significantly enhance their trading arsenal and make more informed decisions in the market. The Squeeze: A Sign of Consolidation and Potential Breakout s The Keltner/Bollinger Bands Squeeze occurs when the Bollinger Bands contract within the Keltner Channels, indicating a period of low volatility or consolidation in the market. This "squeeze" can serve as a precursor to significant price breakouts, either on the upside or downside. By closely monitoring this pattern, traders can identify periods of market consolidation and prepare to capitalize on potential breakouts. How to Implement the Keltner/Bollinger Bands Squeeze Strategy To implement this strategy, traders should follow these steps: Overlay the Keltner Channels and Bollinger Bands on your chart: Start by adding both Keltner Channels and Bollinger Bands to your preferred trading platform's chart. Ensure that the settings of both indicators are adjusted to your desired values. Identify the Squeeze: Look for periods when the Bollinger Bands contract within the Keltner Channels. This signifies a "squeeze" and acts as a sign that the market is experiencing low volatility or consolidation. Monitor for Breakouts: Keep a close eye on the price action during the squeeze. When the Bollinger Bands expand outside of the Keltner Channels, this indicates a potential breakout from the consolidation period. The direction of the breakout (upwards or downwards) will depend on the overall market trend and price action. Enter the Trade: The Keltner/Bollinger Bands Squeeze Strategy can be further enhanced by combining it with other technical indicators, such as the Relative Strength Index, or Moving Average Convergence Divergence. These complementary indicators can provide additional confirmation of potential breakouts and help traders better gauge market conditions. Once a breakout is confirmed, traders can enter a trade in the direction of the breakout. It's essential to use stop-loss orders and manage risk appropriately since false breakouts can also occur. Exit the Trade: Traders should establish a price target and exit strategy based on their analysis and risk tolerance. This can include setting a specific profit target, using trailing stops, or leveraging other technical indicators to determine when to exit the trade. Conclusion Bollinger Bands, Donchian Channels, and Keltner Channels are all valuable technical indicators for analyzing price movements and identifying potential trading opportunities. When deciding which one is right for you, consider your trading style, preferred timeframes, and the specific characteristics of the markets you trade. It's essential to familiarize yourself with each indicator and practice using them in combination with other tools to enhance your trading strategy. We have even shown that these channels can complement each other to form a more comprehensive strategy. Remember, no single indicator is perfect, and incorporating multiple tools can help you gain a more comprehensive understanding of market dynamics. Good luck and happy trading! If you enjoyed our content don’t forget to give this post a boost, and follow our page for more trading education!
Education
by LeafAlgo
27
2nd Pine Script Lesson: Coding the Entry Logic - Bollinger BandWelcome back to our Trading View tutorial series! In this second lesson, be learning how to code the entry logic for a Bollinger Band indicator using Pine Script. If you're new here and missed the first lesson, we highly recommend starting there as it provides a solid foundation for understanding the concepts we'll be covering today: In this hands-on lesson, we'll guide you through every step of coding the entry logic for your own Bollinger Band indicator using Pine Script. By the end of this lesson, you'll have a functional indicator that you can use to inform your trading decisions. So, sit back, grab a cup of coffee, and let's get started! Code the entry logic a) This is where we are calling the Mikilap function with two arguments: - the coinpair and - the timeframe we want to use. // Calling the Mikilap function to start the calculation int indi_value = Function_Mikilap(symbol_full, time_frame) b) In the function initiation we convert the strings into simple strings. // Definition of a Pine Script individual function to handle the Request and avoid Repainting Errors Function_Mikilap(simple string coinpair, simple string tf_to_use) => c) As we are calling the function to get an integer value, we have to define an output variable as an integer and place this variable as the last line in the local scope of the function code to return the integer value. int function_result = 0 // placeholder for indicator calculations function_result Step 1: Using the lower bandwidth of the Bollinger Band based on SMA (close, 21) and a standard deviation of 2.0 and try to highlight bars, where close is next to the lower band a) Requesting the values for the coinpair with request.security() = request.security(coinpair, tf_to_use, ) We recommend using repainting functions like request or barstate only in a local scope (inside a function) and not to request complex calculated values. For saving calculation capacity it is useful to only request the classic four OHLCs and do any calculation with these four after the r equest.security() . b) Calculation of the lower Bollinger Bands values as we need the global info, which type of source, length, and deviation value to use for the calculation, let‘s cut & paste the input for the Bollinger Band in the general starting section of the code and as we want to look for close values „next“ to the lower bandwidth, we need to define what „next“ means; let‘s do it in another input variable, perhaps we want to play with the definition later. string symbol_full = input.symbol(defval = "BINANCE:BTCUSDT", title = "Select Pair:", group = "General") string time_frame = input.string(defval = "60", title = "Timeframe:", tooltip = "Value in minutes, so 1 hour = 60", group = "General") int length = input.int(defval = 21, title = "BB Length:", group = "Bollinger Band Setting") src = input(defval = close, title="BB Source", group = "Bollinger Band Setting") float mult = input.float(defval = 2.0, title="BB Standard-Deviation", group = "Bollinger Band Setting") float lower_dev = input.float(defval = 0.1, title="BB Lower Deviation in %", group = "Bollinger Band Setting")/100 First, let‘s make it visible on the chart by re-writing the Bollinger Bandplot, which is not needed anymore. // Calling the Mikilap function to start the calculation int indi_value = Function_Mikilap(symbol_full, time_frame) // Output on the chart // Part 2 - plotting a Band around the lower bandwidth of a Bollinger Band for the active CoinPair on the chart lower_bb = ta.sma(src, length) - (mult*ta.stdev(src, length)) lower_bb_devup = lower_bb + lower_bb * lower_dev lower_bb_devdown = lower_bb - lower_bb * lower_dev upper = plot(lower_bb_devup, "BB Dev UP", color=#faffaf) lower = plot(lower_bb_devdown, "BB Dev DOWN", color=#faffaf) fill(upper, lower, title = "BB Dev Background", color=color.rgb(245, 245, 80, 80)) c) Now we use the same calculation for the coinpair inside the function and start with the selection of the source (OHLC) to use, which is activein the respective input variable. // Defintion of a Pine Script individual function to handle the Request and avoid Repainting Errors Function_Mikilap(simple string coinpair, simple string tf_to_use) => int function_result = 0 bool barstate_info = barstate.isconfirmed = request.security(coinpair, tf_to_use, ) src_cp = switch src open => open_R high => high_R low => low_R => close_R lower_band_cp = ta.sma(src_cp,length) - (mult*ta.stdev(src_cp, length)) lower_band_cp_devup = lower_band_cp + lower_band_cp * lower_dev lower_band_cp_devdown = lower_band_cp - lower_band_cp * lower_dev // placeholder for indicator calculations d) As the bandwidth for the interesting close values is defined by our band, the only thing missing for the part of the Bollinger Band in our Mikilap indicator is to check if the close value of a bar is inside our band. As we are talking about closed bars, let‘s be sure that it is really closed by using barstate.isconfirmed (repainting built-in function!) and save it in a variable in the head of the function to avoid requesting this info too often. bool barstate_info = barstate.isconfirmed Now let‘s check if the close value of a bar is inside our band. bool bb_entry = close_R < lower_band_cp_devup and close_R > lower_band_cp_devdown and barstate_info And increase the output variable by 1 in case the close value is inside. if bb_entry function_result += 1 By using bb_entry , we are referring to the last bar next to the actual bar, because we want to enter on the opening of the bar after the criteria has been met. e) And to make these possible entries visible, we want to place a label below the bar and show the entry price (=open value of the bar) as mouseover (tooltip). This should only happen if the active coinpair on the chart is the same coinpair, which is in the calculation of the function. if function_result == 1 and ticker.standard(syminfo.tickerid) == coinpair label LE_arrow = label.new(x = bar_index, y = low_R, text = " ↑ LE", yloc = yloc.belowbar, color = color.rgb(255,255,255,25),style = label.style_none, textcolor = color.white, tooltip = str.tostring(open_R)) Note: You will love labels (!) and in case you are looking for text symbols that can be used as labels, look here: www.messletters.com If you need help use the Pine Script Reference Manual, which explains 99% of everything in Pine Script, here: www.tradingview.com f) As our function now returns different integer values (0 or 1), we can use this info to color the background on the actual chart in case it is 1. // Calling the Mikilap function to start the calculation int indi_value = Function_Mikilap(symbol_full, time_frame) color bg_color = indi_value ? color.rgb(180,180,180,75) : color.rgb(25,25,25,100) bgcolor(bg_color) g) To finish this little Pine Script lesson and to achieve our initial targets, we just need to integrate the second indicator (RSI) into the function. We want to use the RSI for 0,5 days (12 hours) and use it to ensure to not go into a long entry in an oversold (< 25) or overbought (> 70) market. We will use RSI (low, 12) within 25 to 45 as the range to go for. Your tasks: define new input variables for RSI: src_rsi and length_rsi define new input variables for the RSI range we want to use: rsi_minand rsi_max(please use the „inline“ format of an input type) calculate the RSI (src_rsi, length_rsi) inside our Mikilap-function define a boolean variable (rsi_entry) to check if the calculated RSI value is inside the range (please add as last check the barstate_info) add the RSI entry check to the Bollinger Band entry check to combine them Congratulations on finishing the second lesson on Trading View - we hope you found it informative and engaging! We're committed to providing you with valuable insights and practical knowledge throughout this tutorial series. So, we'd love to hear from you! Please leave a comment below with your suggestions on what you'd like us to focus on in the next lesson. Thanks for joining us on this learning journey, and we're excited to continue exploring Trading View with you!
Education
by Mizar_trading
8
Understanding the Parabolic Stop and Reverse (SAR) IndicatorThe Parabolic Stop and Reverse (PSAR) indicator is a technical analysis tool that helps traders identify potential reversals in price movements. It is represented by a series of dots that appear above or below the price chart. When the dots are below the price, it indicates a bullish trend potential, and when the dots are above the price, it signals a bearish trend potential. The indicator is calculated based on the price and time, and it adjusts its position as the price moves. When the price crosses the SAR, it signals a potential reversal. The indicator should be used in combination with other technical indicators to confirm trading signals. One strategy for entries using the PSAR indicator is using it with another technical indicator, such as the Relative Strength Index (RSI). When using this strategy, traders can look for oversold conditions on the RSI and then wait for a buy signal from the PSAR indicator. This can help identify potential entry points for long positions. On the other hand, traders can look for overbought conditions on the RSI and then wait for a sell signal from the PSAR to identify potential entry points for short positions. However, it's important to keep in mind that no trading strategy is foolproof, and risk management should always be a top priority. The PSAR indicator can also be used as a stop loss by traders. One way is to use it as a trailing stop loss, whereby the stop loss price is adjusted upwards as the price of the asset increases. Price crossing over the PSAR against the trade direction would signal the trader to close their position. This helps to lock in profits or limit potential losses. This can help to minimize losses and protect capital. Overall, the SAR indicator can be a useful tool for traders when used in combination with other technical indicators and risk management strategies.
Education
by LeafAlgo
Hunting Breakouts with Bollinger Bands and OBVThanks to zAngus for the idea, here is a simple trading strategy that uses two tools: Bollinger Bands and OBV to find moments when an asset's prices can increase or decrease. First and foremost, please note that this explanation is simplified and only covers the basics. Each individual can develop their own settings and adjustments according to their own preferences. Imagine that you are looking at a price chart of an asset. This chart shows how prices have changed over time. Sometimes prices go up and sometimes they go down. The trading strategy we are going to show you can help you find moments when prices are about to change direction. - Bollinger Bands are lines that show a zone where prices of an asset are likely to stay. These lines have two parts: a middle line that shows an average of prices and two other lines that show the zone where prices should be. The lines widen and narrow based on the volatility of prices. - OBV (On-Balance Volume) is another tool that measures whether more people are buying or selling an asset. If more people are buying an asset, OBV increases, and if more people are selling an asset, OBV decreases. Now, here is how we use these two tools to find moments when an asset's prices can increase or decrease: 1. First, we wait for prices to stabilize for a certain amount of time. This means that prices don't go up or down much during a given period. 2. Next, we look at the Bollinger Bands to see if prices have reached the upper or lower limit. If prices exceed the upper limit, it may mean that prices will increase. If prices fall below the lower limit, it may mean that prices will decrease. 3. To confirm what we have seen in the Bollinger Bands, we look at the OBV. If OBV increases or decreases at the same time as prices exceed the upper or lower limit of the Bollinger Bands, it means that more people are buying or selling the asset, and this reinforces our idea that prices will increase or decrease. 4. We enter the market by buying or selling the asset based on whether we think prices will increase or decrease. 5. We exit the market when prices reach the opposite upper or lower limit of the Bollinger Bands or an important resistance zone. This is a simple strategy, but it can help find moments when an asset's prices can increase or decrease. Remember that you must always use good risk management to avoid losing too much money if the market doesn't follow your forecast. Please note that this Bollinger Bands and OBV breakout trading strategy involves risk and is intended for educational purposes only. Any investments made using this strategy are done at your own risk, and you should always do your own research and seek professional advice before making any investment decisions.
Education
by Julien_Eche