CryptoSignalScanner - DeFib v2 indicatorDESCRIPTION:
The DeFib indicator combines Moving Averages data points, Fibonacci sequence calculations and other methods to help traders make better decisions when it comes to entering and exiting trades at different time intervals. By analyzing these data points, the indicator provides valuable insights into the market trends and helps traders determine optimal moments to enter or exit a trade. Moving Averages helps smooth out price fluctuations over a specified period, providing a clearer picture of the overall market direction. The DeFib indicator uses a mix of these averages and Fibonacci methods to increase its chances of finding good trade opportunities. Whether analyzing short-term trends or longer-term patterns, this indicator assists traders in identifying favorable entry and exit points, thereby supporting more informed and strategic trading decisions.
By using Moving Averages data points based on the Fibonacci Sequence (+ some extra calculations we don't wish to share), we incorporate a unique perspective into the analysis. It helps to identify key levels of interest, potential trend reversals, and areas where price action may align with Fibonacci retracement levels. The Fibonacci Sequence is a mathematical sequence in which each number is the sum of the two preceding numbers (e.g., 0, 1, 1, 2, 3, 5, 8, 13, 21, and so on).
As a result of this information some L1, L2, S1 and S2 labels are printed on the chart. The labels are printed when a candle has been closed. Those labels are an indication when to enter or exit a trade. How to use those labels is described in the section "HOW TO USE" below.
This indicator is versatile and can be used on any timeframe, offering a wide range of features to support traders in their decision-making process. Here are some key aspects of this indicator:
User-Friendly:
Traders can easily customize all the settings according to their preferences, ensuring a personalized trading experience.
Long Signals:
The indicator provides both normal and strong long signals, which assist traders in identifying potential reversals in the market. These signals act as confirmation for traders to consider entering a long position.
Short Signals:
Similarly, the indicator offers normal and strong short signals, helping traders identify and confirm potential market reversals for short positions.
Fibonacci Sequence Calculation:
The calculation of the Long and Short labels is based on the Fibonacci Sequence, a mathematical pattern widely used in technical analysis. This adds a reliable and systematic approach to the indicator's signal generation.
Stop Loss:
When initiating a trade, it is our standard practice to implement a stop loss order based on the stop loss signal derived from the current or preceding candle. These stop loss signals are generated using the Average True Range (ATR) indicator.
Overlays:
The indicator includes overlays that visually represent market trends. These overlays identifying support and resistance levels, and providing valuable insights into the overall market behaviour.
Trend Table Box:
Traders can access a trend table box that displays the prevailing trend across different timeframes. This feature allows traders to assess the trend's strength and consistency. Additionally, users have the flexibility to adjust the timeframes based on their trading preferences.
Long/Short Alerts:
The indicator offers the functionality to add alerts for both long and short positions. Traders can set up notifications to be alerted when specific conditions are met, ensuring they stay informed even when they're not actively monitoring the charts.
Overall, this indicator provides traders with a comprehensive set of tools and features to enhance their trading decisions. Its user-friendly nature, combined with the inclusion of various signals, overlays, trend analysis, and alerts, enables traders to make informed choices and adapt to different market conditions effectively.
HOW TO USE:
This indicator incorporates specific signals that provide valuable insights into potential trend reversals in the market. Here's how each signal type is interpreted:
L1 (Long) Signal:
When an L1 signal appears, it suggests a potential uptrend reversal. Traders should pay attention to this signal as it indicates a possible shift from a downtrend to an uptrend. It serves as an early indication of a potential upward movement in prices. This is the fist point where we can take a long position. If we want to invest $100 into this trade we invest a maximum of $50 at this point. Don't forget to put a stop loss as described below in the "STOP LOSS" section.
L2 (Long) Signal:
An L2 signal acts as confirmation of the potential uptrend reversal identified by the L1 signal. When an L2 signal emerges, it strengthens the case for an upcoming uptrend. Traders may consider this signal as a stronger indication to support their decision to enter a long position. This is the point where we can invest another $50 if we already invested on the L1 signal. If we did not invested yet and we still see a clear reversal we enter the trade here with $100. Don't forget to put a stop loss as described below in the "STOP LOSS" section.
S1 (Short) Signal:
When an S1 signal is generated, it suggests a potential downtrend reversal. Traders should take note of this signal as it indicates a possible shift from an uptrend to a downtrend. It serves as an early indication of a potential downward movement in prices. This is the fist point where we can take a short position. If we want to invest $100 into this trade we invest a maximum of $50 at this point. Don't forget to put a stop loss as described below in the "STOP LOSS" section.
S2 (Short) Signal:
An S2 signal confirms the potential downtrend reversal identified by the S1 signal. When an S2 signal emerges, it reinforces the likelihood of an upcoming downtrend. Traders may consider this signal as a stronger indication to support their decision to enter a short position. This is the point where we can invest another $50 if we already invested on the S1 signal. If we did not invested yet and we still see a clear reversal we enter the trade here with $100. Don't forget to put a stop loss as described below in the "STOP LOSS" section.
These signals provide traders with a systematic framework to identify and evaluate potential reversals in market trends. By combining the information provided by both the L1 and L2 signals (for uptrends) or the S1 and S2 signals (for downtrends), traders can gain more confidence in their assessments of trend reversals. This indicator offers traders a valuable tool to capitalize on these reversal opportunities and make more informed trading decisions.
It is important to exercise caution and avoid blindly following the signals generated by the indicator. Instead, it is recommended to seek additional confirmations from other technical indicators such as the RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), or any other indicators that you are familiar with and trust.
While the signals provided by the indicator can be a useful starting point, relying solely on them may not always guarantee accurate predictions. By considering other technical indicators, traders can gain a more comprehensive view of the market conditions and validate the signals received from the indicator.
The RSI is a popular momentum oscillator that measures the speed and change of price movements. It helps traders identify overbought and oversold conditions, giving insights into potential trend reversals. The MACD, on the other hand, combines moving averages to provide signals for trend identification, as well as momentum and divergence analysis.
By utilizing these additional indicators or any others that you are familiar with, you can confirm the signals generated by the indicator under consideration. This approach enhances the reliability of your trading decisions by adding another layer of analysis and reducing the potential for false signals.
Each trader may have their preferred set of technical indicators based on their trading style and experience. It is important to select indicators that align with your trading strategy and complement the signals received from the indicator in question. This way, you can make more informed and well-rounded trading decisions, increasing the probability of successful trades and minimizing potential risks.
Stop Loss:
When initiating a trade, it is our standard practice to implement a stop loss order based on the stop loss signal derived from the current or preceding candle. These stop loss signals are generated using the Average True Range (ATR) indicator.
By employing a stop loss order, we aim to limit potential losses in case the trade moves against our anticipated direction. The stop loss signal, determined from the current or previous candle, provides a specific level at which the stop loss order is placed.
The Average True Range indicator is utilized to gauge the volatility of the market and determine an appropriate stop loss level. It takes into account the price range of the asset over a defined period, considering both high and low price points. By using the ATR, we can identify an optimal stop loss level that accounts for the asset's recent price fluctuations.
Implementing a stop loss based on the ATR-derived signal adds a layer of risk management to our trading strategy. It helps mitigate potential losses by automatically triggering the stop loss order if the price reaches or exceeds the predetermined level. This approach allows us to protect our capital and minimize the impact of adverse price movements.
It is important to note that the ATR-based stop loss signals should be used in conjunction with other analysis techniques and indicators. They serve as a dynamic reference point that considers market volatility, ensuring the stop loss level is adjusted accordingly.
By incorporating stop loss orders based on the stop loss signals derived from the current or previous candle using the ATR indicator, we aim to safeguard our trades and manage risk effectively. However, it is important to continually monitor and adjust the stop loss level as market conditions evolve, adhering to our risk management strategy throughout the duration of the trade.
Candlestick Sequence:
The Candlestick Sequence is a calculation used to identify potential trend reversal points in the financial markets. It consists of two main components, the Candlestick Sequence and the Candlestick Reversal. The Candlestick Sequence and Candlestick Reversal offer a structured way to identify potential reversals in the market.
WARNING:
• It is not advisable to engage in Leverage Trading unless you possess chart reading skills.
• It is not advisable to engage in Leverage Trading unless you are capable of interpreting technical indicators such as RSI, Moving Average, MACD, and others.
• It is crucial not to blindly follow trading signals without conducting your own analysis (DYOR - Do Your Own Research).
• Avoid succumbing to FOMO (Fear Of Missing Out) and impulsively entering trades. If you miss an entry point, it is important to let it go and patiently wait for the next potential entry point.
Leverage trading involves trading with borrowed funds, which amplifies both potential profits and losses. To participate in this form of trading, it is imperative to possess a certain level of expertise and knowledge. One key requirement is the ability to read and analyze charts effectively. Chart reading involves understanding various chart patterns, price movements, and support and resistance levels, among other factors. Without this skill, it can be challenging to make informed decisions and manage risk appropriately.
Additionally, leverage trading relies on technical indicators to identify potential trading opportunities and gauge market conditions. It is essential to have the ability to interpret indicators such as RSI, Moving Average, MACD, and others, as they provide valuable insights into market trends, momentum, and potential reversals. Ignoring or misunderstanding these indicators can lead to incorrect trading decisions and increased risk exposure.
Moreover, it is crucial not to blindly rely solely on trading signals, including those generated by indicators or other sources. While signals can be helpful, they should always be complemented by conducting one's own analysis. This entails conducting thorough research, considering multiple factors, and validating the signals with additional indicators or technical analysis techniques. This approach helps in making more informed and well-rounded trading decisions.
Finally, FOMO can be a detrimental emotion that drives impulsive and irrational trading behavior. It is important to avoid entering trades solely because of the fear of missing out on potential profits. If an entry point is missed, it is recommended to exercise patience and discipline by waiting for the next suitable opportunity. This approach helps to avoid unnecessary risks and maintain a more strategic and calculated trading approach.
By adhering to these warnings and taking the necessary precautions, traders can approach leverage trading more responsibly and increase their chances of success while mitigating potential losses.
REMARKS:
• It is important to emphasize that any information or content you encounter here is not intended as financial advice. We want to make it clear that we are not authorized or qualified to provide personalized investment advice. Our content, including ideas, opinions, views, predictions, forecasts, commentaries, suggestions, or stock picks, should be viewed strictly as informational, entertaining, or educational material.
• We emphasize that you should not construe the information provided here as personal investment advice or as a recommendation to take specific investment actions. It is crucial to conduct your own research, consider your individual financial circumstances, and consult with a qualified financial professional before making any investment decisions.
• While we aim to provide accurate and reliable information, we cannot guarantee the absence of errors or inaccuracies. Therefore, it is recommended to independently verify any information provided and exercise your own judgment when using it for decision-making purposes.
• Please be aware that any actions you take based on the information found here are done so at your own risk. We disclaim any liability for the consequences of your actions or decisions stemming from the information presented.
• Our intention is to provide helpful information that can contribute to your overall understanding and assist you in making better-informed decisions. However, it is essential to exercise caution, seek professional advice, and take responsibility for your investment choices.
Cheers & Good luck.
Moving Averages
Optimal Length BackTester [YinYangAlgorithms]This Indicator allows for a ‘Optimal Length’ to be inputted within the Settings as a Source. Unlike most Indicators and/or Strategies that rely on either Static Lengths or Internal calculations for the length, this Indicator relies on the Length being derived from an external Indicator in the form of a Source Input.
This may not sound like much, but this application may allows limitless implementations of such an idea. By allowing the input of a Length within a Source Setting you may have an ‘Optimal Length’ that adjusts automatically without the need for manual intervention. This may allow for Traditional and Non-Traditional Indicators and/or Strategies to allow modifications within their settings as well to accommodate the idea of this ‘Optimal Length’ model to create an Indicator and/or Strategy that adjusts its length based on the top performing Length within the current Market Conditions.
This specific Indicator aims to allow backtesting with an ‘Optimal Length’ inputted as a ‘Source’ within the Settings.
This ‘Optimal Length’ may be used to display and potentially optimize multiple different Traditional Indicators within this BackTester. The following Traditional Indicators are included and available to be backtested with an ‘Optimal Length’ inputted as a Source in the Settings:
Moving Average; expressed as either a: Simple Moving Average, Exponential Moving Average or Volume Weighted Moving Average
Bollinger Bands; expressed based on the Moving Average Type
Donchian Channels; expressed based on the Moving Average Type
Envelopes; expressed based on the Moving Average Type
Envelopes Adjusted; expressed based on the Moving Average Type
All of these Traditional Indicators likewise may be displayed with multiple ‘Optimal Lengths’. They have the ability for multiple different ‘Optimal Lengths’ to be inputted and displayed, such as:
Fast Optimal Length
Slow Optimal Length
Neutral Optimal Length
By allowing for the input of multiple different ‘Optimal Lengths’ we may express the ‘Optimal Movement’ of such an expressed Indicator based on different Time Frames and potentially also movement based on Fast, Slow and Neutral (Inclusive) Lengths.
This in general is a simple Indicator that simply allows for the input of multiple different varieties of ‘Optimal Lengths’ to be displayed in different ways using Tradition Indicators. However, the idea and model of accepting a Length as a Source is unique and may be adopted in many different forms and endless ideas.
Tutorial:
You may add an ‘Optimal Length’ within the Settings as a ‘Source’ as followed in the example above. This Indicator allows for the input of a:
Neutral ‘Optimal Length’
Fast ‘Optimal Length’
Slow ‘Optimal Length’
It is important to account for all three as they generally encompass different min/max length values and therefore result in varying ‘Optimal Length’s’.
For instance, say you’re calculating the ‘Optimal Length’ and you use:
Min: 1
Max: 400
This would therefore be scanning for 400 (inclusive) lengths.
As a general way of calculating you may assume the following for which lengths are being used within an ‘Optimal Length’ calculation:
Fast: 1 - 199
Slow: 200 - 400
Neutral: 1 - 400
This allows for the calculation of a Fast and Slow length within the predetermined lengths allotted. However, it likewise allows for a Neutral length which is inclusive to all lengths alloted and may be deemed the ‘Most Accurate’ for these reasons. However, just because the Neutral is inclusive to all lengths, doesn’t mean the Fast and Slow lengths are irrelevant. The Fast and Slow length inputs may be useful for seeing how specifically zoned lengths may fair, and likewise when they cross over and/or under the Neutral ‘Optimal Length’.
This Indicator features the ability to display multiple different types of Traditional Indicators within the ‘Display Type’.
We will go over all of the different ‘Display Types’ with examples on how using a Fast, Slow and Neutral length would impact it:
Simple Moving Average:
In this example above have the Fast, Slow and Neutral Optimal Length formatted as a Slow Moving Average. The first example is on the 15 minute Time Frame and the second is on the 1 Day Time Frame, demonstrating how the length changes based on the Time Frame and the effects it may have.
Here we can see that by inputting ‘Optimal Lengths’ as a Simple Moving Average we may see moving averages that change over time with their ‘Optimal Lengths’. These lengths may help identify Support and/or Resistance locations. By using an 'Optimal Length' rather than a static length, we may create a Moving Average which may be more accurate as it attempts to be adaptive to current Market Conditions.
Bollinger Bands:
Bollinger Bands are a way to see a Simple Moving Average (SMA) that then uses Standard Deviation to identify how much deviation has occurred. This Deviation is then Added and Subtracted from the SMA to create the Bollinger Bands which help Identify possible movement zones that are ‘within range’. This may mean that the price may face Support / Resistance when it reaches the Outer / Inner bounds of the Bollinger Bands. Likewise, it may mean the Price is ‘Overbought’ when outside and above or ‘Underbought’ when outside and below the Bollinger Bands.
By applying All 3 different types of Optimal Lengths towards a Traditional Bollinger Band calculation we may hope to see different ranges of Bollinger Bands and how different lookback lengths may imply possible movement ranges on both a Short Term, Long Term and Neutral perspective. By seeing these possible ranges you may have the ability to identify more levels of Support and Resistance over different lengths and Trading Styles.
Donchian Channels:
Above you’ll see two examples of Machine Learning: Optimal Length applied to Donchian Channels. These are displayed with both the 15 Minute Time Frame and the 1 Day Time Frame.
Donchian Channels are a way of seeing potential Support and Resistance within a given lookback length. They are a way of withholding the High’s and Low’s of a specific lookback length and looking for deviation within this length. By applying a Fast, Slow and Neutral Machine Learning: Optimal Length to these Donchian Channels way may hope to achieve a viable range of High’s and Low’s that one may use to Identify Support and Resistance locations for different ranges of Optimal Lengths and likewise potentially different Trading Strategies.
Envelopes / Envelopes Adjusted:
Envelopes are an interesting one in the sense that they both may be perceived as useful; however we deem that with the use of an ‘Optimal Length’ that the ‘Envelopes Adjusted’ may work best. We will start with examples of the Traditional Envelope then showcase the Adjusted version.
Envelopes:
As you may see, a Traditional form of Envelopes even produced with a Machine Learning: Optimal Length may not produce optimal results. Unfortunately this may occur with some Traditional Indicators and they may need some adjustments as you’ll notice with the ‘Envelopes Adjusted’ version. However, even without the adjustments, these Envelopes may be useful for seeing ‘Overbought’ and ‘Oversold’ locations within a Machine Learning: Optimal Length standpoint.
Envelopes Adjusted:
By adding an adjustment to these Envelopes, we may hope to better reflect our Optimal Length within it. This is caused by adding a ratio reflection towards the current length of the Optimal Length and the max Length used. This allows for the Fast and Neutral (and potentially Slow if Neutral is greater) to achieve a potentially more accurate result.
Envelopes, much like Bollinger Bands are a way of seeing potential movement zones along with potential Support and Resistance. However, unlike Bollinger Bands which are based on Standard Deviation, Envelopes are based on percentages +/- from the Simple Moving Average.
We will conclude our Tutorial here. Hopefully this has given you some insight into how useful adding a ‘Optimal Length’ within an external (secondary) Indicator as a Source within the Settings may be. Likewise, how useful it may be for automation sake in the sense that when the ‘Optimal Length’ changes, it doesn’t rely on an alert where you need to manually update it yourself; instead it will update Automatically and you may reap the benefits of such with little manual input needed (aside from the initial setup).
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
[KVA] Extremes ProfilerExtremes Profiler is a specialized indicator crafted for traders focusing on the relationship between price extremes and moving averages. This tool offers a comprehensive perspective on price dynamics by quantifying and visualizing significant distances of current prices from various moving averages. It effectively highlights the top extremes in market movements, providing key insights into price extremities relative to these averages. The indicator's ability to analyze and display these distances makes it a valuable tool for understanding market trends and potential turning points. Traders can leverage the Extremes Profiler to gain a deeper understanding of how prices behave in relation to commonly watched moving averages, thus aiding in making informed trading decisions
Key Features :
Extensive MA Analysis : Tracks the price distance from multiple moving averages including EMA, SMA, WMA, RMA, and HMA.
Top 50 (100) Distance Metrics : Highlights the 50 (100)greatest (highest or lowest) distances from each selected MA, pinpointing significant market deviations.
Customizable Periods : Offers flexibility with adjustable periods to align with diverse trading strategies.
Comprehensive View : Switch between timeframes for a well-rounded understanding of short-term fluctuations and long-term market trends.
Cross-Asset Comparison : Utilize the indicator to compare different assets, gaining insights into the relative dynamics and volatility of various markets. By analyzing multiple assets, traders can discern broader market trends and better understand asset-specific behaviors.
Customizable Display : Users can adjust the periods and number of results to suit their analytical needs.
Rainbow Fibonacci Momentum - SuperTrend🌈 "Rainbow Fibonacci Momentum - SuperTrend" Indicator 🌈
IMPORTANT: as this is a complex and elaborate TREND ANALYSIS on the graph, ALL INDICATORS REPAINT.
Experience the brilliance of "Rainbow Fibonacci Momentum - SuperTrend" for your technical analysis on TradingView! This versatile indicator allows you to visualize various types of Moving Averages, including Simple Moving Averages (SMA), Exponential Moving Averages (EMA), Weighted Moving Averages (WMA), Hull Moving Averages (HMA), and Volume Weighted Moving Averages (VWMA).
Each MA displayed in a unique color to create a stunning rainbow effect. This makes it easier for you to identify trends and potential trading opportunities.
Key Features:
📊 Multiple Moving Average Types - Choose from a range of moving average types to suit your analysis.
🎨 Stunning Color Gradient - Each moving average type is displayed in a unique color, creating a beautiful rainbow effect.
📉 Overlay Compatible - Use it as an overlay on your price chart for clear trend insights.
With the "Rainbow Fibonacci Momentum - SuperTrend" indicator, you'll add a burst of color to your trading routine and gain a deeper understanding of market trends.
HOW IT WORKS
MA Lines:
MA - 5: purple lines
MA - 8: blue lines
MA - 13: green lines
MA - 21: yellow lines
MA - 34: orange lines
MA - 55: red line
Header Color Indicators:
Purple: MA-5 is in uptrend on the chart
Blue: MA-5 and MA-8 are in the uptrend on the chart
Green: MA-5, MA-8 and MA-13 are in the uptrend on the chart
Yellow: MA-5, MA-8, MA-13 and MA-21 are in the uptrend on the chart
Orange: MA-5, MA-8, MA-13, MA-21 and MA-34 are in the uptrend on the chart
Red: MA-5, MA-8, MA-13, MA-21, MA-34 and MA-55 are in the uptrend on the chart
Red + White Arrow: All MAs are correctly aligned in the uptrend on the chart
Footer Color Indicators:
Purple: MA-5 is in downtrend on the chart
Blue: MA-5 and MA-8 are in the downtrend on the chart
Green: MA-5, MA-8 and MA-13 are in the downtrend on the chart
Yellow: MA-5, MA-8, MA-13 and MA-21 are in the downtrend on the chart
Orange: MA-5, MA-8, MA-13, MA-21 and MA-34 are in the downtrend on the chart
Red: MA-5, MA-8, MA-13, MA-21, MA-34 and MA-55 are in the downtrend on the chart
Red + White Arrow: All MAs are correctly aligned in the downtrend on the chart
Background Colors:
Light Red: All MAs are on the rise!
Red: All MAs are align correctly on the rise!
Light Green: All MAs are in freefall!
Green: All MAs are align correctly in freefall!
Tiny Arrows Indicators/Alerts:
Down Arrow: All MAs are in freefall!
Up Arrow: All MAs are on the rise!
Big Arrows Indicators/Alerts:
Down Arrow: All MAs are align correctly in freefall!
Up Arrow: All MAs are align correctly on the rise!
Machine Learning: Optimal Length [YinYangAlgorithms]This Indicator aims to solve an issue that most others face; static lengths. This Indicator will scan lengths from the Min to Max setting (1 - 400 by default) to calculate which is the most Optimal Length in the current market condition. Almost every Indicator uses a length in some part of their calculation, and this length is usually adjustable via the Settings; however it is generally a static fixed length. Static non changing lengths may not always produce optimal results. As market conditions change generally the optimal length will too. For this reason we have created this indicator.
This Indicator will create a Neutral (Min - Max Length), Fast (Min - Mid Length ((Max - Min) / 2)) and Slow (Mid Length ((Max - Min) / 2) - Max Length). This allows you to understand which the Optimal Fast, Slow and Neutral lengths are within the given Mix and Max length settings.
This Indicator then plots these Optimal Lengths as an Oscillator which can then be used within ANOTHER Indicator as a Source within its Settings. Stand alone this Indicator may not prove all that useful, however when its Lengths are inputted into another Indicator it may prove very useful. This allows other Indicators to use the Optimal Length within its calculations from the Settings rather than relying on simply a fixed length. Unfortunately this results in users needing to manually plug the Optimal Length plots into the second Indicator; but it also allows for endless possibilities with applying Machine Learning Optimal Lengths within both Traditional and Non-Traditional Indicators and may give other Pine Coders an easy and effective way to add Machine Learning auto adjustable lengths within their already created Indicators.
The beautiful part about this Indicator is that aside from inputting the Optimal Length Plot into another Indicator, there is no manual updating needed. When the Optimal Length changes, the change will automatically reflect in the other Indicator without the need for you to manually adjust its length. This may be very useful with both time preservation, as well as if there is an automated strategy based upon said Indicator that now won’t need manual intervention.
Tutorial:
By default this is what the Machine Learning: Optimal Length Indicator looks like. It is simply a way of both Displaying and Plotting our current Optimal Length so that we may then use it as a source within ANOTHER Indicator. This will allow the automation of an Optimal Length to be updated, rather than needing any manual input from yourself (aside from set up).
For instance if you set the start length to 1 and the end length to 400 (default settings), it will scan to find the optimal Length setting between 1 and 400. This features 3 types of lengths:
Fast (Green Line): 1-199 (from start length to half way of total)
Slow (Red Line): 200 - 400 (mid way to end length)
Neutral (Blue Line): 1 - 400 (start to end length)
By breaking down the Optimal Length detection into these 3 different types, we can see how the Optimal Length compares and changes based on the lengths allotted to them and how performance changes.
For instance, you may notice that both the Fast and Slow Optimal Length didn’t change much in the example above; however the Neutral Optimal Length changed quite a bit. This is due to the fact that the Neutral is inclusive of all lengths available and may be considered the more accurate due to that. However, this doesn’t mean the Fast and Slow lengths aren’t important and should be used. They may be useful for seeing how something fairs in a Fast and Slow standpoint.
If you change your TimeFrame from 15 minute to 1 Day, you’ll notice that the Optimal Lengths gravitate towards their upper bounds:
199 is max for Fast, it’s at 195
400 is max for Slow, its at 393
400 is max for Neutral, its at 399
The Optimal Length may move up to its upper bounds on Higher Time Frames because there is a lot of price action and long term data being displayed. This may lead to higher lengths performing better in a profitability standpoint since its data is based on so far back and such drastic price movements.
Below we’re going to go through a few examples, including the code so you may reproduce the example and have an understanding of how versatile Inputting an Optimal Length as a source may be within Traditional Indicators.
Adding the Machine Learning: Optimal Length to another Indicator:
You may add the Optimal Length to another Indicator as shown in the example above. In the example we are adding the ‘Machine Learning: Optimal Length - Neutral’ to our Neutral Length within the Settings. The external Indicator needs to have the ability to input the Optimal Length as a Source, this way it can automatically change within the external Indicator when the Optimal Length Indicator changes its Optimal Length.
Please note you may get an error within an external Indicator that accepts the Length as a Source if you don’t select the Machine Learning: Optimal Length. For instance, if you use ‘Close’ within BTC/USDT the length used would be ~36,000. This length is too long and will throw an error.
For this reason, we will ensure the Max Length that may be used is 1000.
Please note, on lower Time Frames you may need to adjust the Max Length. For instance if 20k bar data is used, the Max Length ‘may’ fail to load when going by default Min: 1 and Max: 400. Generally with most pairs it will load if your TradingView subscription is Premium or greater; however if it is less there is a chance it may fail. If it fails for you too often please lower the Max Length Amount; or send us a message we can look into a fix for this.
*** If it fails to load, please try removing the external Indicator and re-adding it and adding the Lengths back as a Source within the Settings. Sometimes it fails, but re-adding may fix it. If it keeps failing afterwards, reduce the Max Length Amount as mentioned above. ***
Simple Moving Average:
In this example above have the Fast, Slow and Neutral Optimal Length formatted as a Slow Moving Average. The first example is on the 15 minute Time Frame and the second is on the 1 Day Time Frame, demonstrating how the length changes based on the Time Frame and the effects it may have.
Here is the code for the example Indicator shown above. This example shows how you may use the Optimal Length as a Source and then use that Optimal Length and plot it as a Simple Moving Average:
//@version=5
indicator("Optimal Length - Backtesting - MA", overlay=true, max_bars_back=5000)
outputType = input.string("All", "Output Type", options= )
lengthSource = input.source(close, "Neutral Length")
lengthSource_fast = input.source(close, "Fast Length")
lengthSource_slow = input.source(close, "Slow Length")
showNeutral = outputType == "Neutral" or outputType == "Fast + Neutral" or outputType == "Slow + Neutral" or outputType == "All"
showFast = outputType == "Fast" or outputType == "Fast + Neutral" or outputType == "Fast + Slow" or outputType == "All"
showSlow = outputType == "Slow" or outputType == "Slow + Neutral" or outputType == "Fast + Slow" or outputType == "All"
//Neutral
optimalLength = math.min(math.max(math.round(lengthSource), 1), 1000)
optimalMA = ta.sma(close, optimalLength)
//Fast
optimalLength_fast = math.min(math.max(math.round(lengthSource_fast), 1), 1000)
optimalMA_fast = ta.sma(close, optimalLength_fast)
//Slow
optimalLength_slow = math.min(math.max(math.round(lengthSource_slow), 1), 1000)
optimalMA_slow = ta.sma(close, optimalLength_slow)
plot(showNeutral ? optimalMA : na, color=color.blue)
plot(showFast ? optimalMA_fast : na, color=color.green)
plot(showSlow ? optimalMA_slow : na, color=color.red)
Bollinger Bands:
In the two examples above for Bollinger Bands we have first the 15 Minute Time Frame and then the 1 Day Time Frame. As described above in ‘Adding the Machine Learning: Optimal Length to another Indicator’ sometimes it may fail to load, for this reason in the 15 Minute it was reduced to a max of 300 Length.
Bollinger Bands are a way to see a Simple Moving Average (SMA) that then uses Standard Deviation to identify how much deviation has occurred. This Deviation is than Added and Subtracted from the SMA to create the Bollinger Bands which help Identify possible movement zones that are ‘within range’. This may mean that the price may face Support / Resistance when it reaches the Outer / Inner bounds of the Bollinger Bands. Likewise, it may mean the Price is ‘Overbought’ when outside and above or ‘Underbought’ when outside and below the Bollinger Bands.
By applying All 3 different types of Optimal Lengths towards a Traditional Bollinger Band calculation we may hope to see different ranges of Bollinger Bands and how different lookback lengths may imply possible movement ranges on both a Short Term, Long Term and Neutral perspective. By seeing these possible ranges you may have the ability to identify more levels of Support and Resistance over different lengths and Trading Styles.
Below is the code for the Bollinger Bands example above:
//@version=5
indicator("Optimal Length - Backtesting - Bollinger Bands", overlay=true, max_bars_back=5000)
outputType = input.string("All", "Output Type", options= )
lengthSource = input.source(close, "Neutral Length")
lengthSource_fast = input.source(close, "Fast Length")
lengthSource_slow = input.source(close, "Slow Length")
showNeutral = outputType == "Neutral" or outputType == "Fast + Neutral" or outputType == "Slow + Neutral" or outputType == "All"
showFast = outputType == "Fast" or outputType == "Fast + Neutral" or outputType == "Fast + Slow" or outputType == "All"
showSlow = outputType == "Slow" or outputType == "Slow + Neutral" or outputType == "Fast + Slow" or outputType == "All"
mult = 2.0
src = close
neutralColor = color.blue
slowColor = color.red
fastColor = color.green
//Neutral
optimalLength = math.min(math.max(math.round(lengthSource), 1), 1000)
optimalMA = ta.sma(close, optimalLength)
//Fast
optimalLength_fast = math.min(math.max(math.round(lengthSource_fast), 1), 1000)
optimalMA_fast = ta.sma(close, optimalLength_fast)
//Slow
optimalLength_slow = math.min(math.max(math.round(lengthSource_slow), 1), 1000)
optimalMA_slow = ta.sma(close, optimalLength_slow)
//Neutral Bollinger Bands
dev = mult * ta.stdev(src, math.round(optimalLength))
upper = optimalMA + dev
lower = optimalMA - dev
plot(showNeutral ? optimalMA : na, "Neutral Basis", color=color.new(neutralColor, 0))
p1 = plot(showNeutral ? upper : na, "Neutral Upper", color=color.new(neutralColor, 50))
p2 = plot(showNeutral ? lower : na, "Neutral Lower", color=color.new(neutralColor, 50))
fill(p1, p2, title = "Neutral Background", color=color.new(neutralColor, 96))
//Slow Bollinger Bands
dev_slow = mult * ta.stdev(src, math.round(optimalLength_slow))
upper_slow = optimalMA_slow + dev_slow
lower_slow = optimalMA_slow - dev_slow
plot(showFast ? optimalMA_slow : na, "Slow Basis", color=color.new(slowColor, 0))
p1_slow = plot(showFast ? upper_slow : na, "Slow Upper", color=color.new(slowColor, 50))
p2_slow = plot(showFast ? lower_slow : na, "Slow Lower", color=color.new(slowColor, 50))
fill(p1_slow, p2_slow, title = "Slow Background", color=color.new(slowColor, 96))
//Fast Bollinger Bands
dev_fast = mult * ta.stdev(src, math.round(optimalLength_fast))
upper_fast = optimalMA_fast + dev_fast
lower_fast = optimalMA_fast - dev_fast
plot(showSlow ? optimalMA_fast : na, "Fast Basis", color=color.new(fastColor, 0))
p1_fast = plot(showSlow ? upper_fast : na, "Fast Upper", color=color.new(fastColor, 50))
p2_fast = plot(showSlow ? lower_fast : na, "Fast Lower", color=color.new(fastColor, 50))
fill(p1_fast, p2_fast, title = "Fast Background", color=color.new(fastColor, 96))
Donchian Channels:
Above you’ll see two examples of Machine Learning: Optimal Length applied to Donchian Channels. These are displayed with both the 15 Minute Time Frame and the 1 Day Time Frame.
Donchian Channels are a way of seeing potential Support and Resistance within a given lookback length. They are a way of withholding the High’s and Low’s of a specific lookback length and looking for deviation within this length. By applying our Fast, Slow and Neutral Machine Learning: Optimal Length to these Donchian Channels way may hope to achieve a viable range of High’s and Low’s that one may use to Identify Support and Resistance locations for different ranges of Optimal Lengths and likewise potentially different Trading Strategies.
The code to reproduce these Donchian Channels as displayed above is so:
//@version=5
indicator("Optimal Length - Backtesting - Donchian Channels", overlay=true, max_bars_back=5000)
outputType = input.string("All", "Output Type", options= )
lengthSource = input.source(close, "Neutral Length")
lengthSource_fast = input.source(close, "Fast Length")
lengthSource_slow = input.source(close, "Slow Length")
showNeutral = outputType == "Neutral" or outputType == "Fast + Neutral" or outputType == "Slow + Neutral" or outputType == "All"
showFast = outputType == "Fast" or outputType == "Fast + Neutral" or outputType == "Fast + Slow" or outputType == "All"
showSlow = outputType == "Slow" or outputType == "Slow + Neutral" or outputType == "Fast + Slow" or outputType == "All"
mult = 2.0
src = close
neutralColor = color.blue
slowColor = color.red
fastColor = color.green
//Neutral
optimalLength = math.min(math.max(math.round(lengthSource), 1), 1000)
optimalMA = ta.sma(close, optimalLength)
//Fast
optimalLength_fast = math.min(math.max(math.round(lengthSource_fast), 1), 1000)
optimalMA_fast = ta.sma(close, optimalLength_fast)
//Slow
optimalLength_slow = math.min(math.max(math.round(lengthSource_slow), 1), 1000)
optimalMA_slow = ta.sma(close, optimalLength_slow)
//Neutral Donchian Channels
lower_dc = ta.lowest(optimalLength)
upper_dc = ta.highest(optimalLength)
basis_dc = math.avg(upper_dc, lower_dc)
plot(showNeutral ? basis_dc : na, "Donchain Channel - Neutral Basis", color=color.new(neutralColor, 0))
u = plot(showNeutral ? upper_dc : na, "Donchain Channel - Neutral Upper", color=color.new(neutralColor, 50))
l = plot(showNeutral ? lower_dc : na, "Donchain Channel - Neutral Lower", color=color.new(neutralColor, 50))
fill(u, l, color=color.new(neutralColor, 96), title = "Donchain Channel - Neutral Background")
//Fast Donchian Channels
lower_dc_fast = ta.lowest(optimalLength_fast)
upper_dc_fast = ta.highest(optimalLength_fast)
basis_dc_fast = math.avg(upper_dc_fast, lower_dc_fast)
plot(showFast ? basis_dc_fast : na, "Donchain Channel - Fast Neutral Basis", color=color.new(fastColor, 0))
u_fast = plot(showFast ? upper_dc_fast : na, "Donchain Channel - Fast Upper", color=color.new(fastColor, 50))
l_fast = plot(showFast ? lower_dc_fast : na, "Donchain Channel - Fast Lower", color=color.new(fastColor, 50))
fill(u_fast, l_fast, color=color.new(fastColor, 96), title = "Donchain Channel - Fast Background")
//Slow Donchian Channels
lower_dc_slow = ta.lowest(optimalLength_slow)
upper_dc_slow = ta.highest(optimalLength_slow)
basis_dc_slow = math.avg(upper_dc_slow, lower_dc_slow)
plot(showSlow ? basis_dc_slow : na, "Donchain Channel - Slow Neutral Basis", color=color.new(slowColor, 0))
u_slow = plot(showSlow ? upper_dc_slow : na, "Donchain Channel - Slow Upper", color=color.new(slowColor, 50))
l_slow = plot(showSlow ? lower_dc_slow : na, "Donchain Channel - Slow Lower", color=color.new(slowColor, 50))
fill(u_slow, l_slow, color=color.new(slowColor, 96), title = "Donchain Channel - Slow Background")
Envelopes / Envelopes Adjusted:
Envelopes are an interesting one in the sense that they both may be perceived as useful; however we deem that with the use of an ‘Optimal Length’ that the ‘Envelopes Adjusted’ may work best. We will start with examples of the Traditional Envelope then showcase the Adjusted version.
Envelopes:
As you may see, a Traditional form of Envelopes even produced with our Machine Learning: Optimal Length may not produce optimal results. Unfortunately this may occur with some Traditional Indicators and they may need some adjustments as you’ll notice with the ‘Envelopes Adjusted’ version. However, even without the adjustments, these Envelopes may be useful for seeing ‘Overbought’ and ‘Oversold’ locations within a Machine Learning: Optimal Length standpoint.
Envelopes Adjusted:
By adding an adjustment to these Envelopes, we may hope to better reflect out Optimal Length within it. This is caused by adding a ratio reflection towards the current length of the Optimal Length and the max Length used. This allows for the Fast and Neutral (and potentially Slow if Neutral is greater) to achieve a potentially more accurate result.
Envelopes, much like Bollinger Bands are a way of seeing potential movement zones along with potential Support and Resistance. However, unlike Bollinger Bands which are based on Standard Deviation, Envelopes are based on percentages +/- from the Simple Moving Average.
The code used to reproduce the example above is as follows:
//@version=5
indicator("Optimal Length - Backtesting - Envelopes", overlay=true, max_bars_back=5000)
outputType = input.string("All", "Output Type", options= )
displayType = input.string("Envelope Adjusted", "Display Type", options= )
lengthSource = input.source(close, "Neutral Length")
lengthSource_fast = input.source(close, "Fast Length")
lengthSource_slow = input.source(close, "Slow Length")
showNeutral = outputType == "Neutral" or outputType == "Fast + Neutral" or outputType == "Slow + Neutral" or outputType == "All"
showFast = outputType == "Fast" or outputType == "Fast + Neutral" or outputType == "Fast + Slow" or outputType == "All"
showSlow = outputType == "Slow" or outputType == "Slow + Neutral" or outputType == "Fast + Slow" or outputType == "All"
mult = 2.0
src = close
neutralColor = color.blue
slowColor = color.red
fastColor = color.green
//Neutral
optimalLength = math.min(math.max(math.round(lengthSource), 1), 1000)
optimalMA = ta.sma(close, optimalLength)
//Fast
optimalLength_fast = math.min(math.max(math.round(lengthSource_fast), 1), 1000)
optimalMA_fast = ta.sma(close, optimalLength_fast)
//Slow
optimalLength_slow = math.min(math.max(math.round(lengthSource_slow), 1), 1000)
optimalMA_slow = ta.sma(close, optimalLength_slow)
percent = 10.0
maxAmount = math.max(optimalLength, optimalLength_fast, optimalLength_slow)
//Neutral
k = displayType == "Envelope" ? percent/100.0 : (percent/100.0) / (optimalLength / maxAmount)
upper_env = optimalMA * (1 + k)
lower_env = optimalMA * (1 - k)
plot(showNeutral ? optimalMA : na, "Envelope - Neutral Basis", color=color.new(neutralColor, 0))
u_env = plot(showNeutral ? upper_env : na, "Envelope - Neutral Upper", color=color.new(neutralColor, 50))
l_env = plot(showNeutral ? lower_env : na, "Envelope - Neutral Lower", color=color.new(neutralColor, 50))
fill(u_env, l_env, color=color.new(neutralColor, 96), title = "Envelope - Neutral Background")
//Fast
k_fast = displayType == "Envelope" ? percent/100.0 : (percent/100.0) / (optimalLength_fast / maxAmount)
upper_env_fast = optimalMA_fast * (1 + k_fast)
lower_env_fast = optimalMA_fast * (1 - k_fast)
plot(showFast ? optimalMA_fast : na, "Envelope - Fast Basis", color=color.new(fastColor, 0))
u_env_fast = plot(showFast ? upper_env_fast : na, "Envelope - Fast Upper", color=color.new(fastColor, 50))
l_env_fast = plot(showFast ? lower_env_fast : na, "Envelope - Fast Lower", color=color.new(fastColor, 50))
fill(u_env_fast, l_env_fast, color=color.new(fastColor, 96), title = "Envelope - Fast Background")
//Slow
k_slow = displayType == "Envelope" ? percent/100.0 : (percent/100.0) / (optimalLength_slow / maxAmount)
upper_env_slow = optimalMA_slow * (1 + k_slow)
lower_env_slow = optimalMA_slow * (1 - k_slow)
plot(showSlow ? optimalMA_slow : na, "Envelope - Slow Basis", color=color.new(slowColor, 0))
u_env_slow = plot(showSlow ? upper_env_slow : na, "Envelope - Slow Upper", color=color.new(slowColor, 50))
l_env_slow = plot(showSlow ? lower_env_slow : na, "Envelope - Slow Lower", color=color.new(slowColor, 50))
fill(u_env_slow, l_env_slow, color=color.new(slowColor, 96), title = "Envelope - Slow Background")
Hopefully these examples, including reproducing code, have given you some insight as to how useful this Machine Learning: Optimal Length may be and how another Indicator may easily modify their existing code to incorporate the usage of such Machine Learning: Optimal Length. We likewise will publish a Backtesting Indicator which incorporates all of the concepts we’ve gone over within here; in case you wish to take advantage of the Traditional Indicators mentioned above that allow the input of Machine Learning: Optimal Length and don’t wish to code them.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
RS for VPAThis is a supporting Indicator for the Volume Price Analysis Script VPA 5.0.
Purpose
To indicate the performance of the stock compared to an Index or any other selected stock. It also provides an idea about the strength of the Reference Index as well.
Description
The indicator is an unbound oscillator moving around a zero line. If the stock is strong then the values are positive and if it is weak the values are negative. If the stock is performing better (Stronger) than the Index the indicator is positive and colored green. If the stock is weaker than the Index it is negative and is colored Red.
The background indicates the strength of the Reference Index/Stock. Bullishness/up trend of the Index/Stock is indicated by yellow colour. Short term uptrend, Mid term uptrend and Long term trends are indicated by different shades of yellow varying from light to Dark. The bearishness / down trend is indicated by blue back ground.
How it Works
The relative strength is calculated by using the formula
RS = Gain of the stock / (Gain of the Ref. Index -1)
= (Stock Price today / Stock Price (N period ago)) /
(Index Price today / Index price (N period ago)) – 1
The Index strength is calculated as below
Short term trend up = 5 ema > 22 ema
Mid Term trend up = 22 ema > 60 ema
Long term trend up = 60 ema > 130 ema
Trend down = 5 ema < 22 ema
How to use
Use this indicator to assist your Price Action Analysis using VPA 5.0. When the Price action and volume indicates Bullishness, you can check if the relative strength is also supporting (Positive and in green Territory). This adds credibility to the Price action. Also check if the index is also positive (the Back ground is yellow). This makes the Price action even stronger. Ideally both the stock and index should be strong. Many time you would find the that the stock is in green territory but the index is in blue territory. This calls for some caution in evaluating the Price Action.
When the price action is positive but the relative strength is negative then one should be cautious and wait for the relative strength to turn positive before any entry decision.
Option for the Indicator
One can select the following from the setting for the indicator
1. Index or reference stock – Default is CNX 500
2. Relative Strength Calculation period – Default is 22
3. The EMA periods for the Index/Reference stock strength calculation
TTP Big Whale ExplorerThe Big Whale Explorer is an indicator that looks into the ratio of large wallets deposits vs withdrawals.
Whales tend to sale their holding when they transfer their holdings into exchanges and they tend to hold when they withdraw.
In this overlay indicator you'll be able to see in an oscillator format the moves of large wallets.
The moves above 1.5 turn into red symbolising that they are starting to distribute. This can eventually have an impact in the price by causing anything from a mild pullback to a considerable crash depending on how much is being actually sold into the market.
Moves below 0.5 mean that the large whales are heavily accumulating and withdrawing. During these periods price could still pullback or even crash but eventually the accumulation can take prices to new highs.
Instructions:
1) Load INDEX:BTCUSD or BNC:BLX to get the most historic data as possible
2) use the daily timeframe
3) load the indicator into the chart
Multiple Moving Averages with OffsetUser Description:
This indicator is designed to provide insights into market trends based on multiple moving averages with customizable offsets. It combines short-term and long-term moving averages to offer a comprehensive view of price movements. The user can adjust various parameters to tailor the indicator to their preferred settings.
How the Strategy Works:
Short-Term Fast Moving Average:
Length: 47 (Adjustable by the user)
Offset: Adjustable (User-defined)
Color: Green
Line Thickness: 2 (Thicker green line for better visibility)
Long-Term Fast Moving Average:
Length: 203 (Adjustable by the user)
Offset: Adjustable (User-defined)
Color: Red
Line Thickness: 2 (Thicker red line for better visibility)
Long-Term Slow Moving Average:
Length: 100 (Adjustable by the user)
Offset: 77 (Adjustable by the user)
Color: Custom Red (RGB: 161, 5, 5)
Line Thickness: 2 (Thicker red line for better visibility)
Interpretation:
When the Short-Term Fast Moving Average (green line) is above the Long-Term Fast Moving Average (red line), it may signal a potential uptrend.
Conversely, when the Short-Term Fast Moving Average is below the Long-Term Fast Moving Average, it may indicate a potential downtrend.
The Long-Term Slow Moving Average provides additional context, allowing users to assess the strength and stability of trends.
Customization:
Users can experiment with different lengths and offsets to fine-tune the indicator based on their trading preferences and market conditions.
TIPS:
- When price action reaches upper RED moving average is probable that the price action is close to a pull back or change of direction.
- When price action falls and closes below the bottom RED moving average it can be a possible change of direction to the downside.
- You can use the green moving average as a filter and confluence to identify if the price action is moving towards the upside or downside.
Note: This indicator is for informational purposes only and should be used in conjunction with other analysis tools for comprehensive decision-making.
Crypto Market Strategy (CMS)/Introduction
The Crypto Market Strategy (CMS) is a composite strategy for the cryptocurrency market. It integrates multiple strategies (called signals) to ensure you are exploiting multiple patterns/anomalies in the market.
/Signals
The three distinct strategies, each providing signals based on specific market conditions are explained below:
1. Limit Range: This signal targets stable market periods, triggering signals based on micro breakouts in price. The market during this period is described as stable because of the short lookback period required for breakout, four bars is the default.
2. Trend Breakout: This signal seeks to capitalize on significant market movements following consolidation periods, it triggers when large price breakouts occur. The market during this period is described as volatile because of the long lookback period required for breakout, forty bars is the default.
3. Momentum: After breakouts, price uptrends may persist for a long time, typically weeks to months. This signal captures long term trends.
An upward blue arrow signifies a long entry signal, a downward red arrow indicates a short entry signal, while an upward/downward pink arrow indicates an exit signal. All signals will have a label indicating the triggering strategy and number of units (this can be disabled in the style settings).
/Construction
The strategy is constructed using minimal indicators, it is basically price action and moving averages.
/Settings
The settings are organised according to the signals;
1. Limit range
Entry - This is the size of breakout
+Exit - Closes the trade in profit
-Exit - Closes the trade to minimise loss
2. Trend breakout
Entry - This is the size of the breakout
Exit - Closes the trade to minimise loss
3. Momentum
Entry - This determines how quickly a signal is triggered
Lookback - This is the duration considered for the entry
/Results
The backtest results are based on a starting capital of $13,700 (convenient amount for retail traders) with 5% of equity for the position size and pyramiding of 3 consecutive positions because there are three signals. Commissions vary from broker to broker with some charging zero commissions, so commissions is set to an exorbitant $3 per order to ensure profitability in backtests is reproducible in live trading. Slippage of 3 ticks is used to ensure the results are representative of real world, market order, end-of-day trading. The backtest results are available to view at the bottom of this page.
Note:
Past performance in backtesting does not guarantee future results. Cryptocurrency markets are particularly volatile, and individual execution and market changes can significantly affect strategy performance. Price data may also vary across exchanges.
/Tickers
CMS has been backtested primarily on BTCUSD. It also performs well on ETHUSD.
[KVA]nRSIThe nRSI stands as a groundbreaking enhancement of the traditional Relative Strength Index (RSI), specifically engineered for traders seeking a more refined and accurate tool in fast-moving markets.
Customizable Price Change Period (n): Unlike the traditional RSI which solely relies on a fixed period for average gains and losses, the nRSI introduces an additional parameter, n, to calculate price changes.
This adaptation focuses on minimizing market noise, sharpening the indicator's sensitivity to genuine trends and patterns.
Enhanced Signal Precision : By reducing the influence of short-term price spikes and fluctuations, the nRSI delivers a more precise signal. This precision is particularly crucial in volatile market conditions, where traditional indicators may be swayed by transient movements.
Ideal Usage
Strategic Trading Decisions : Ideal for traders who need to filter out insignificant price movements to make more strategic, informed trading decisions.
Reliable Divergence Spotting : Enhanced noise reduction aids in identifying more reliable divergences, key for predicting potential market reversals.
Trend Confirmation : The smoothed RSI, assisted by the moving average, becomes an invaluable tool for confirming the validity of market trends, minimizing false signals.
Anchored Relative StrengthThe Anchored Relative Strength (RS) Indicator is a tool designed for traders to compare the performance of a selected stock or security against a benchmark index or another security starting from a specific point in time.
Traditional Relative Strength
The traditional RS line is a popular tool used to compare the performance of a stock, typically calculated as the ratio of the stock's price to a benchmark index's price. It helps identify outperformers and underperformers relative to the market or a specific sector.
The Anchored Approach
The Anchored RS line enhances the traditional concept of the RS line by introducing an anchored approach, where calculations begin from a user-defined date. This feature provides the flexibility to start the comparison from a specific historical event, earnings, market peak, trough, or any date significant to the trader's analysis.
Calculating Relative Strength
The RS value is calculated by dividing the close price of the chosen stock by the close price of the comparative symbol (SPX by default). This calculation is performed for each bar since the Anchor Date.
Indicator Features
🔶Custom Start Date
🔶Custom Comparison Symbol
🔶RS Line Moving Average
🔶Comparison Symbol Line
🔶Customize Colors & Appearance
Users can change the anchor date simply by clicking on the indicator and dragging the anchor point.
Double Simple Moving AverageThe Double Simple moving average is an indicator developed to help traders identify dynamic levels of support and resistance as well as determine current trend direction.
This indicator shows both an SMA calculated on highs and one calculated on lows. In addition to that, it plots the deviation bands based on the space between the two main lines.
The gradient color between the two main lines can be used to determine the volumetric pressure and confirmation of the current trend.
PEMA SUITESPivot based EMA (PEMA) is giving ema based on pivot .
Pivot MA's indicator is a combination of the following:
Pivot SMA
Pivot EMA's
Pullback to EMA Band
Pivot EMA's Cross Over
Pivot Double-EMA's Cross Over
Modified Pivot EMA's Cross Over
All the pivot EMA’s calculations are based on "Profiting With Pivot-Based Moving Averages" book by Frank Ochoa.
How to use it :-
One should have to refer this book for in depth usage of this indicator.
You can use the option's provided in the indicator and the signals have been generated according to the concept in this book.
Don't turn on multiple option's, it becomes clumsy to look.
Description:-
1. Pullback to PEMA Band:-
Perhaps the most trader-friendly PEMA setup is the PEMA Pull-Back, because it forces you to trade in the direction of an established trend.
In this, u get the signal when the price retraces to 13 EMA and closes above the PEMA Band.
It is like Buy the Dips & Sell the Rips. The idea of the PEMA Pull-Back is to buy the market at a discount during an uptrend, and sell the market at a premium during a down trend.
2. PEMA Cross Over :-
The PEMA Crossover fires a signal when the fast EMA crosses the slow EMA.
If the fast EMA crosses above the slow EMA, a long signal is fired; whereas, if the fast EMA crosses below the slow EMA, a short signal is fired.
Depending on your trader personality, you will have to choose the periodicities of the two moving averages to suit your taste.
Some combination of EMA's are provided.
3. Double EMA Cross Over :-
A double exponential moving average (DEMA) is basically the EMA of an EMA, meaning the output is the second derivative of the original exponential moving average.
While an EMA is a faster moving average than the SMA, the DEMA is on another level in terms of speed.
4. Modified PEMA Cross Over :-
This system is an ultra-fast PEMA crossover signal that has built-in trend confirmation.
The Modified PEMA Crossover system fires signals in the direction of the prevailing trend, as measured by a larger moving average.
For Example, Take (1,3),21 combination. In this we use 1- and 3-period pivot EMA’s for crossovers, and use a 21-period pivot EMA for trend confirmation.
1 and 3 period EMA's are not shown in the chart, Only 21 EMA and signals are shown for clear view.
Therefore, this system will only allow bullish crossover signals to fire when price is above the 21-period pivot EMA, and will only allow bearish crossover signals to fire when price is below the 21-period average.
In essence, the results are usually highly qualified “buy the dip, and sell rip” type of opportunities.
This also helps you to avoid getting chopped up during price confluence.
Traders have to look for reversal when price is near the pivot based EMA Zone.
Micro Dots with VMA line [Crypto_Chili_]In the chart photo is a quick description of each part of the indicator is.
The Micro Dots were hours of testing different combinations of indicators and settings to find what looked and worked best. This is what I came up with, use it as a rough draft as it could probably be added to or changed around.
One simple way to use the indicator is if price is above VMA with green dots, look to long. If price is below VMA with red dots look to short.
Variable Moving Average - Also known as VMA or Track Line, is an Exponential Moving Average. VMA adjusts its smoothing constant on the basis of Market Volatility. This can help to measure the macro trend.
Micro Trend Dots - A Supertrend with extras filters. Supertrend is a trend-following indicator based on ATR (In this indicator TrueRange instead). The extra filters on top of the Supertrend help add confluence to them to give more confidence in the micro trend.
Credit to @LazyBear for the Variable Moving Average
Credit to @KivancOzbilgic for his Supertrend
Send me a message if you create something with the Micro Dots I'd love it see it!
Thank you friends I hope you enjoy!
No Signal is 100% correct at what it's trying to do. Use caution when trading!
Practice Risk Management.
Heiken Ashi Colored Moving AverageThis indicator is meant to plot a moving average but the color of the moving average will change based on Heikin Ashi. Its seems to be slightly off, I would love any suggestions on improving this indicator.
Thanks
User Defined Range Selector and Color Changing EMA LineThe "User Defined Range Selector and Color Changing EMA Line," stands out in the crowded field of trading indicators due to its unique blend of visual clarity and customizable functionality. Unlike traditional indicators, this tool not only tracks the Exponential Moving Average (EMA) but enhances it with a user-defined mirrored line to visually denote a range based on a percentage distance from the EMA.
Key Features:
- Dynamic Color-Changing EMA: The EMA line changes color based on its slope, providing instant visual cues about the market trend. Blue signifies an upward trend, red indicates a downward trend, and gray represents a sideways market.
- Customizable Range Selector: A mirrored EMA line is plotted, which can be set at a user-defined percentage away from the primary EMA. This feature allows traders to visualize a potential price range or channel, adding an extra layer of analysis for potential support and resistance zones.
- User-Driven Inputs: With inputs like EMA length, slope length, source, and the percentage distance for the mirrored line, the indicator offers a high level of customization, catering to various trading styles and strategies.
- Enhanced Trading Strategy Development: This combination of trend visualization and range identification aids in refining entry and exit points, making it an invaluable tool for developing more nuanced trading strategies.
Why It's Unique:
- Dual Functionality: The combination of trend indication (via color changes) and range visualization (through the mirrored line) sets this indicator apart from traditional EMA-based tools.
- Customization and Flexibility: The ability to tailor key parameters like EMA length and the percentage away for the mirrored line empowers traders to adapt the tool to fit their specific trading approach and market conditions.
- Visual Simplicity: Despite its multifaceted capabilities, the indicator maintains a clean and intuitive visual presentation, ensuring ease of use and interpretation.
License: This source code is subject to the terms of the Mozilla Public License 2.0. More details can be found at (mozilla.org). However, the code is public so use it as you see fit.
DCA Simulator---- EN ----
OBJECTIVE:
The aim of this indicator is to simulate the average acquisition price during a DCA from any date, any asset, any amount.
Useful for realizing that short-term volatility is not a problem when taking a long-term view, as only the fundamentals of the asset matter.
USAGE:
The indicator does not seek to reproduce tools to give you the size of your bag or what your absolute profit is. It should be used agnostically to the DCA amount, it allows you to identify whether starting from a date what your average purchase price and therefore whether you are currently in profit or not in relation to the current price.
You can also use it to compare assets against each other, which offers the best ROI via DCA.
NOTES:
The average price of the DCA will always be lower than the simple average price.
---- FR ----
OBJECTIF :
L'objectif de cette indicateur est de simuler le prix moyen d'acquisition lors d'un DCA à partir de n'importe quelle date, n'importe quel actif, peu importe le montant.
Utile pour se rendre compte que la volatilité court terme n'est pas un problème lors d'une vision long terme, seul compte le fondamental de l'actif.
USAGE :
L'indicateur ne cherche pas à reproduire des outils pour vous donner la taille de votre bag ou quel est votre profit absolu. Il doit être utilisé de manière agnostique au montant du DCA, il permet d'identifier si en commençant d'une date quel votre prix moyen d'achat et donc si vous êtes actuellement en profit ou pas par rapport au prix actuel.
Vous pouvez aussi vous en servir pour comparer des actifs entre eux, lequel offre le meilleur ROI via DCA.
NOTES :
L'on peut constater que le prix moyen du DCA sera systématiquement plus bas que la moyenne simple du prix
RSI & Backed-Weighted MA StrategyRSI & MA Strategy :
INTRODUCTION :
This strategy is based on two well-known indicators that work best together: the Relative Strength Index (RSI) and the Moving Average (MA). We're going to use the RSI as a trend-follower indicator, rather than a reversal indicator as most are used to. To the signals sent by the RSI, we'll add a condition on the chart's MA, filtering out irrelevant signals and considerably increasing our winning rate. This is a medium/long-term strategy. There's also a money management method enabling us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RSI :
The RSI is one of the best-known and most widely used indicators in trading. Its purpose is to warn traders when an asset is overbought or oversold. It was designed to send reversal signals, but we're going to use it as a trend indicator by increasing its length to 20. The RSI formula is as follows :
RSI (n) = 100 - (100 / (1 + (H (n)/L (n))))
With n the length of the RSI, H(n) the average of days closing above the open and L(n) the average of days closing below the open.
MA :
The Moving Average is also widely used in technical analysis, to smooth out variations in an asset. The SMA formula is as follows :
SMA (n) = (P1 + P2 + ... + Pn) / n
where n is the length of the MA.
However, an SMA does not weight any of its terms, which means that the price 10 days ago has the same importance as the price 2 days ago or today's price... That's why in this strategy we use a RWMA, i.e. a back-weighted moving average. It weights old prices more heavily than new ones. This will enable us to limit the impact of short-term variations and focus on the trend that was dominating. The RWMA used weights :
The 4 most recent terms by : 100 / (4+(n-4)*1.30)
The other oldest terms by : weight_4_first_term*1.30
So the older terms are weighted 1.30 more than the more recent ones. The moving average thus traces a trend that accentuates past values and limits the noise of short-term variations.
PARAMETERS :
RSI Length : Lenght of RSI. Default is 20.
MA Type : Choice between a SMA or a RWMA which permits to minimize the impact of short term reversal. Default is RWMA.
MA Length : Length of the selected MA. Default is 19.
RSI Long Signal : Minimum value of RSI to send a LONG signal. Default is 60.
RSI Short signal : Maximum value of RSI to send a SHORT signal. Default is 40.
ROC MA Long Signal : Maximum value of Rate of Change MA to send a LONG signal. Default is 0.
ROC MA Short signal : Minimum value of Rate of Change MA to send a SHORT signal. Default is 0.
TP activation in multiple of ATR : Threshold value to trigger trailing stop Take Profit. This threshold is calculated as multiple of the ATR (Average True Range). Default value is 5 meaning that to trigger the trailing TP the price need to move 5*ATR in the right direction.
Trailing TP in percentage : Percentage value of trailing Take Profit. This Trailing TP follows the profit if it increases, remaining selected percentage below it, but stops if the profit decreases. Default is 3%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. Default is 400, which means that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:ETHUSD with a timeframe set to 6h. Parameters are set as follows :
MA type: RWMA
MA Length: 19
RSI Long Signal: >60
RSI Short Signal : <40
ROC MA Long Signal : <0
ROC MA Short Signal : >0
TP Activation in multiple ATR : 5
Trailing TP in percentage : 3
ENTER RULES :
The principle is very simple:
If the asset is overbought after a bear market, we are LONG.
If the asset is oversold after a bull market, we are SHORT.
We have defined a bear market as follows : Rate of Change (20) RWMA < 0
We have defined a bull market as follows : Rate of Change (20) RWMA > 0
The Rate of Change is calculated using this formula : (RWMA/RWMA(20) - 1)*100
Overbought is defined as follows : RSI > 60
Oversold is defined as follows : RSI < 40
LONG CONDITION :
RSI > 60 and (RWMA/RWMA(20) - 1)*100 < -1
SHORT CONDITION :
RSI < 40 and (RWMA/RWMA(20) - 1)*100 > 1
EXIT RULES FOR WINNING TRADE :
We have a trailing TP allowing us to exit once the price has reached the "TP Activation in multiple ATR" parameter, i.e. 5*ATR by default in the profit direction. TP trailing is triggered at this point, not limiting our gains, and securing our profits at 3% below this trigger threshold.
Remember that the True Range is : maximum(H-L, H-C(1), C-L(1))
with C : Close, H : High, L : Low
The Average True Range is therefore the average of these TRs over a length defined by default in the strategy, i.e. 20.
RISK MANAGEMENT :
This strategy may incur losses. The method for limiting losses is to set a Stop Loss equal to 3*ATR. This means that if the price moves against our position and reaches three times the ATR, we exit with a loss.
Sometimes the ATR can result in a SL set below 10% of the trade value, which is not acceptable. In this case, we set the SL at 10%, limiting losses to a maximum of 10%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
Enjoy the strategy and don't forget to take the trade :)
hamster-bot MRS 2 (simplified version) MRS - Mean Reversion Strategy (Countertrend) (Envelope strategy)
This script does not claim to be unique and does not mislead anyone. Even the unattractive backtest result is attached. The source code is open. The idea has been described many times in various sources. But at the same time, their collection in one place provides unique opportunities.
Published by popular demand and for ease of use. so that users can track the development of the script and can offer their ideas in the comments. Otherwise, you have to communicate in several telegram chats.
Representative of the family of counter-trend strategies. The basis of the strategy is Mean reversion . You can also read about the Envelope strategy .
Mean reversion , or reversion to the mean, is a theory used in finance that suggests that asset price volatility and historical returns eventually will revert to the long-run mean or average level of the entire dataset.
The strategy is very simple. Has very few settings. Good for beginners to get acquainted with algorithmic trading. A simple adjustment will help avoid overfitting. There are many variations of this strategy, but for understanding it is better to start with this implementation.
Principle of operation.
1)
A conventional MA is being built. (fuchsia line). A limit order is placed on this line to close the position.
2)
(green line) A limit order is placed on this line to open a long position
3)
(red line) A limit order is placed on this line to open a short position
Attention!
Please note that a limit order is used. Conclude that the strategy has a limited capacity. And the results obtained on low-liquid instruments will be too high in the tester. On real auctions there will be a different result.
Note for testing the strategy in the spot market:
When testing in the spot market, do not include both long and short at the same time. It is recommended to test only the long mode on the spot. Short mode for more advanced users.
Settings:
Available types of moving averages:
SMA
EMA
TEMA - triple exponential moving average
DEMA - Double Exponential Moving Average
ZLEMA - Zero lag exponential moving average
WMA - weighted moving average
Hma - Hull Moving Average
Thma - Triple Exponential Hull Moving Average
Ehma - Exponential Hull Moving Average
H - MA built based on highs for n candles | ta.highest(len)
L - MA built based on lows for n candles | ta.lowest(len)
DMA - Donchian Moving Average
A Kalman filter can be applied to all MA
The peculiarity of the strategy is a large selection of MA and the possibility of shifting lines. You can set up a reverse trending strategy on the Donchian channel for example.
Use Long - enable/disable opening a Long position
Use Short - enable/disable opening a Short position
Lot Long, % - % allocated from the deposit for opening a Long position. In the spot market, do not use % greater than 100%
Lot Short, % - allocated % of the deposit for opening a Short position
Start date - the beginning of the testing period
End date - the end of the testing period (Example: only August 2020 can be tested)
Mul - multiplier. Used to offset lines. Example:
Mul = 0.99 is shift -1%
Mul = 1.01 is shift +1%
Non-strict recommendations:
1) Test the SPOT market on crypto exchanges. (The countertrend strategy has liquidation risk on futures)
2) Symbols altcoin/bitcoin or altcoin/altcoin. Example: ETH/BTC or DOGE/ETH
3) Timeframe is usually 1 hour
If the script passes moderation, I will supplement it by adding separate settings for closing long and short positions according to their MA
Volatility Exponential Moving AverageVEMA is a custom indicator that enhances the traditional moving average by incorporating market volatility. Unlike standard moving averages that rely solely on price, VEMA integrates both the Simple Moving Average (SMA) and the Exponential Moving Average (EMA) of the closing price, alongside a measure of market volatility.
The unique aspect of VEMA is its approach. It calculates the standard deviation of the closing price and also computes the simple moving average of this volatility. This dual approach to understanding market fluctuations allows for a more nuanced understanding of market dynamics.
Key to VEMA's functionality is the dynamic weighting factor, which adjusts the influence of SMA and EMA based on current market volatility. This factor increases the weight of the EMA, which is more responsive to recent price changes, during periods of high volatility. Conversely, during periods of lower volatility, the SMA, which offers a smoother view of price trends, becomes more prominent.
The resultant is a hybrid moving average that responds adaptively to changes in market volatility. This adaptability makes VEMA particularly useful in dynamic markets, potentially offering more insightful trend analysis and reversal signals compared to traditional moving averages.
Day Open,High,Low Fib LevelsDay Open,High,Low Fibonacci Levels indicator depicts Fibonacci levels from Highest to lowest price levels vis-à-vis Day Open Price. The indicator is structured based on default Intraday number of bars. Hence the indicator and Gray Zone concept is effective in lower time frames .The indicator has also “Regular” Check in Box option under “Input” with default 14 bars under “Regular Length” to switch over from default Intraday Length.
Green Zone represent area above Day Open Price when close is above Day Open Price.
Red Zone represent area below Day Open Price when close is below Day Open Price.
Gray Zone represent band within the Maximum and Minimum of Moving Averages of MA24,MA38,MA50,MA62,MA79 drawn with relevance to Fibonacci levels. The movement within this band is expected to be resistant prone on either direction.
Fibonacci levels between Highest and Lowest points during Green Zone and Red Zone are derived and reflected at 78.6,61.8,50.0,38.2 and 23.6 levels for users guidance.
Trades above Gray Zone are favored for Buy trades and below Gray Zone are favored for Sell trades. Trades within Gray Zone are resistant prone from either direction.
If number of bars in Gray Zone during Intraday are more than the combined number of bars above Green Zone and number of bras below Gray Zone then market may be assumed to be in Range bound state.
MA20 and MA200 are in default in display state. Position of MA 20 above and below Gray Zone and vis-à-vis MA Mid (Mid point in Gray Zone ) reflects the prevailing trend .MA 200 reflects the general Up trend or Down trend .
The Indicator reflects the Green Zone, Gray Zone ,Red Zone in the Table below the Chart depending on the position of Day Open Price below or above the Last Price .If the number of bars in the Gray Zone are more than the combined number of bars above and below Gray Zone the table reflect Range Bound Market.
Supplementing with other monitoring tools and Price Action dynamics the indicator assist the user to plan his entry and exit of trade based on the position of the market whether it is in Green Zone or Red Zone by taking into account the Fibonacci Levels.
DISCLAIMER : For educational and entertainment purpose only .Nothing in this content should be interpreted as financial advice or a recommendation to buy or sell any sort of security/ies or investment/s.
Demand and Supply Zones Lite [Afnan]Are you looking to level up your trading game and spot potential turning points in the stock market? Introducing the Smart Money Demand and Supply Zones indicator, a powerful tool designed to identify opportunities created by the Smart money.
The Smart Money Demand and Supply Zones indicator is built upon the principles of Rally Base Rally (RBR), Rally Base Drop (RBD), Drop Base Rally (DBR), Drop Base Drop (DBD).
🔍 Key Details 🔍
The "Smart Money" concept refers to large institutional investors and professional traders who possess significant financial resources and expertise. The importance of smart money lies in their influence on market trends and price movements. Their actions and positions often serve as signals for retail traders and investors to make informed decisions.
Formation of Smart Money: Smart money is attracted to areas in the market where they can find favourable risk-to-reward opportunities.
1. Rally Base Rally (RBR) Zones: These zones occur after a rally (upward price movement), followed by a period of consolidation (base formation), and then another rally. Smart money often forms positions here as it suggests a strong uptrend continuation.
2. Rally Base Drop (RBD) Zones: In this case, there is a rally, followed by a base formation, but instead of another rally, the price drops. Smart money may position themselves here in anticipation of a potential trend reversal.
3. Drop Base Rally (DBR) Zones: These zones form when there is a drop in price, followed by a base formation, and then a rally. Smart money may take positions here, expecting a trend reversal to the upside.
4. Drop Base Drop (DBD) Zones: In this scenario, the price drops, then forms a base, but subsequently continues to drop. Smart money might take bearish positions here, anticipating further downward movement.
🚀 Pending Orders from Smart Money Zones: 🚀
When the price approaches these smart money zones, institutional investors often place remaining pending orders to enter the market.
By identifying RBR/DBR zones as potential buying opportunities and RBD/DBD zones as potential selling opportunities on price charts, retail traders can align their trades with smart money activities. Implementing proper risk management and confirming signals enhances the likelihood of successful trades by following the footsteps of institutional investors.
💡 Key Features of the Indicator 💡
This indicator includes the following features:
Customizable Zone Length: Adjust the number of base candles in a zone to suit your preferences and strategy.
Candle Body Size Customization: Personalize the body size of candles for fine-tuning visual representation.
Base Candle Selection: Choose between the body of the candle or narrow range candles as the base candle for zone plotting.
Colour Customization For Candles: Customize Drop, Base, Rally, and Zone colours to match your visual preferences.
Number of Zones: This feature is flexible, allowing you to customize the quantity of zones displayed on the chart for improved visibility.
Zone Colours: You have the option to personalize the colours for both fresh and tested zones based on your preferences.
Zone Strength Customization: Adjust candle sensitivity for better control.
Swing High and Swing Low: Enable or disable support and demand lines based on Swing High and Swing Low.
Wick of Candle: Customize zone plotting using the body or wicks of candles for flexible analysis.
Previous Zones: You can choose to display or disable previous zones on the chart that have been deleted and utilized before. This option helps you maintain a clutter-free chart while retaining valuable historical information.
Moving Averages: Utilize four (4) customizable Moving Averages to enhance analysis from any time frame.
💎 Employing a Top-Down Approach and Multiple Time Frame Analysis: 💎
Let's delve into the concept of adopting a top-down approach combined with multiple time frame analysis in trading scenarios. It is consistently recommended to trade with the trend because, as the saying goes, "the trend is your friend." If you identify a demand zone on the chart but the overall trend is downward, it's crucial to confirm the stock's trend in higher timeframes. Avoid purchasing from the demand zone in such a scenario as you would be going against the trend. To consider buying from the demand zone, ensure that the overall trend is upward by checking the higher timeframe.
Similarly, if the higher timeframe trend is upward but the price is approaching a higher timeframe supply zone, refrain from buying in the lower timeframe. If the price reaches a higher timeframe supply zone, there is a likelihood that the price will face rejection from this zone.
If the price is significantly extended from the EMA 20 on a higher timeframe, for instance, if you plan to trade on a 30-minute timeframe and the price is considerably extended from the daily EMA 20, consider trading from zones that are closer to the daily EMA 20. When the price is extended from the higher timeframe EMA 20, it implies that the price is expensive, and there may be a tendency for it to return to the EMA 20. Therefore, it is advisable to trade from zones that are closer to the higher timeframe EMA 20 and avoid zones that are extended from the higher timeframe EMA 20.
For instance, imagine you're considering purchasing a stock that has reached a demand zone known as Rally Base Rally (RBR). If you identify a corresponding demand zone in a higher time frame located at the same position, and concurrently observe that the intermediate time frame indicates an upward trend, your potential for a successful trade is enhanced.
Conversely, if you spot a buying zone in a lower time frame, but notice a supply zone in the higher time frame at that exact position, the likelihood of a profitable trade decreases significantly. In such cases, it's prudent to steer clear of the lower time frame zone. This emphasizes the critical significance of employing a top-down approach or conducting a multiple time frame analysis.
Note: By Doing top down approach you can easily follow the footprints of smart money in the stock market or any other market by using this indicator and make well-informed trading decisions.
Remember, don't make decisions based only on one time frame. Check the overall trend of the stock and look at buying and selling points on bigger time scales. If you only use one time scale, your chances of making successful trades will be lower.
💎 To execute these comprehensive analyses and optimize your trading outcomes, you can make use of my indicator called "Demand & Supply Zone Scoring: Rally Base & Drop Concept."💎
This indicator is thoughtfully crafted to assess the strength of trade setups based on demand and supply zones through a scoring mechanism. It serves as your guide for correct top-down and multiple time frame analysis, eliminating the possibility of overlooking any strategic parameters. To gain deeper insights, you can learn more about how to use this indicator in its description.
Lastly, Thank you for your support, your likes & comments." Feel free to ask if you have questions.
Let's conquer the markets together! 🚀
Demand and Supply Zones Pro [Afnan]Are you looking to level up your trading game and spot potential turning points in the stock market? Introducing the Smart Money Demand and Supply Zones indicator, a powerful tool designed to identify opportunities created by the Smart money.
The Smart Money Demand and Supply Zones indicator is built upon the principles of Rally Base Rally (RBR), Rally Base Drop (RBD), Drop Base Rally (DBR), Drop Base Drop (DBD).
🔍 Key Details 🔍
The "Smart Money" concept refers to large institutional investors and professional traders who possess significant financial resources and expertise. The importance of smart money lies in their influence on market trends and price movements. Their actions and positions often serve as signals for retail traders and investors to make informed decisions.
Formation of Smart Money: Smart money is attracted to areas in the market where they can find favourable risk-to-reward opportunities.
1. Rally Base Rally (RBR) Zones: These zones occur after a rally (upward price movement), followed by a period of consolidation (base formation), and then another rally. Smart money often forms positions here as it suggests a strong uptrend continuation.
2. Rally Base Drop (RBD) Zones: In this case, there is a rally, followed by a base formation, but instead of another rally, the price drops. Smart money may position themselves here in anticipation of a potential trend reversal.
3. Drop Base Rally (DBR) Zones: These zones form when there is a drop in price, followed by a base formation, and then a rally. Smart money may take positions here, expecting a trend reversal to the upside.
4. Drop Base Drop (DBD) Zones: In this scenario, the price drops, then forms a base, but subsequently continues to drop. Smart money might take bearish positions here, anticipating further downward movement.
🚀 Pending Orders from Smart Money Zones: 🚀
When the price approaches these smart money zones, institutional investors often place remaining pending orders to enter the market.
By identifying RBR/DBR zones as potential buying opportunities and RBD/DBD zones as potential selling opportunities on price charts, retail traders can align their trades with smart money activities. Implementing proper risk management and confirming signals enhances the likelihood of successful trades by following the footsteps of institutional investors.
💡 Key Features of the Indicator 💡
This indicator includes the following features:
Customizable Zone Length: Adjust the number of base candles in a zone to suit your preferences and strategy.
Candle Body Size Customization: Personalize the body size of candles for fine-tuning visual representation.
Alert Feature: The alert feature can notify you when the price reaches a demand or supply zone, with the ability to customize the risk-to-reward parameters.
Base Candle Selection: Choose between the body of the candle or narrow range candles as the base candle for zone plotting.
Colour Customization For Candles: Customize Drop, Base, Rally, and Zone colours to match your visual preferences.
Number of Zones: This feature is flexible, allowing you to customize the quantity of zones displayed on the chart for improved visibility.
Zone Colours: You have the option to personalize the colours for both fresh and tested zones based on your preferences.
Zone Strength Customization: Adjust candle sensitivity for better control.
Swing High and Swing Low: Enable or disable support and demand lines based on Swing High and Swing Low.
Wick of Candle: Customize zone plotting using the body or wicks of candles for flexible analysis.
Previous Zones: You can choose to display or disable previous zones on the chart that have been deleted and utilized before. This option helps you maintain a clutter-free chart while retaining valuable historical information.
Moving Averages: Utilize four (4) customizable Moving Averages to enhance analysis from any time frame.
💎 Employing a Top-Down Approach and Multiple Time Frame Analysis: 💎
Let's delve into the concept of adopting a top-down approach combined with multiple time frame analysis in trading scenarios. It is consistently recommended to trade with the trend because, as the saying goes, "the trend is your friend." If you identify a demand zone on the chart but the overall trend is downward, it's crucial to confirm the stock's trend in higher timeframes. Avoid purchasing from the demand zone in such a scenario as you would be going against the trend. To consider buying from the demand zone, ensure that the overall trend is upward by checking the higher timeframe.
Similarly, if the higher timeframe trend is upward but the price is approaching a higher timeframe supply zone, refrain from buying in the lower timeframe. If the price reaches a higher timeframe supply zone, there is a likelihood that the price will face rejection from this zone.
If the price is significantly extended from the EMA 20 on a higher timeframe, for instance, if you plan to trade on a 30-minute timeframe and the price is considerably extended from the daily EMA 20, consider trading from zones that are closer to the daily EMA 20. When the price is extended from the higher timeframe EMA 20, it implies that the price is expensive, and there may be a tendency for it to return to the EMA 20. Therefore, it is advisable to trade from zones that are closer to the higher timeframe EMA 20 and avoid zones that are extended from the higher timeframe EMA 20.
For instance, imagine you're considering purchasing a stock that has reached a demand zone known as Rally Base Rally (RBR). If you identify a corresponding demand zone in a higher time frame located at the same position, and concurrently observe that the intermediate time frame indicates an upward trend, your potential for a successful trade is enhanced.
Conversely, if you spot a buying zone in a lower time frame, but notice a supply zone in the higher time frame at that exact position, the likelihood of a profitable trade decreases significantly. In such cases, it's prudent to steer clear of the lower time frame zone. This emphasizes the critical significance of employing a top-down approach or conducting a multiple time frame analysis.
Note: By Doing top down approach you can easily follow the footprints of smart money in the stock market or any other market by using this indicator and make well-informed trading decisions.
Remember, don't make decisions based only on one time frame. Check the overall trend of the stock and look at buying and selling points on bigger time scales. If you only use one time scale, your chances of making successful trades will be lower.
💎 To execute these comprehensive analyses and optimize your trading outcomes, you can make use of my indicator called "Demand & Supply Zone Scoring: Rally Base & Drop Concept."💎
This indicator is thoughtfully crafted to assess the strength of trade setups based on demand and supply zones through a scoring mechanism. It serves as your guide for correct top-down and multiple time frame analysis, eliminating the possibility of overlooking any strategic parameters. To gain deeper insights, you can learn more about how to use this indicator in its description.
Lastly, Thank you for your support, your likes & comments." Feel free to ask if you have questions.
Let's conquer the markets together! 🚀
