Time Matrix [Pro+] (DRxICT)Description:
The Time Matrix Pro is an automated Time-based trading tool adaptable to futures, forex, and bond markets. This indicator is inspired by concepts taught by the Inner Circle Trader (ICT) and ICT_Concepts.
ICT’s repertoire encompasses the concepts of liquidity and couples them with Time. The Time Matrix helps the analyst to locate key Time-based price levels to determine bias and recurring price patterns within the market. Analysts can use levels like Previous Day’s Highs and Lows, Weekly Highs and Lows, Session Openings, and Macros to base and qualify Premium and Discount arrays in intraday analysis.
Session Boxes are Time opportunities of the day that identify the market mechanics of consolidation, expansion, retracement, and reversals.
ICT_Concepts's Session Boxes are described as the Premarket, AM Session, PM session:
Premarket is defined as 9:30pm to 1:30am
AM session is defined as 4:00am to 11:00am
PM Session is defined as 11:30am to 2:15pm
Understanding how Time is crucial for identifying intraday profiling, the analyst is able to toggle price levels in conjunction with Time-based macros. These help analyze key market turning points that can correspond to unique market mechanics.
Beyond the Time-based liquidity levels, and the Time macros, there are also predefined Time clusters.
These clusters highlight a significant lower Timeframe candle which was found to hold significant value by ICT_Concepts. Very much alike Time-based liquidity levels, analysts will notice how price reacts to support or negate existing orderflow, trend and direction.
Key Features:
Customizable Extension: the analyst is given the choice to toggle the ending Time Offset to either Noon NY Time or at the end of the trading day.
Time-Based Toggles: choose individual Time-based prices to highlight on your chart.
Time Table: depending on the Timeframe, the Time Table will display the number of bars and the Time elapsed since the Time-based liquidity levels were established.
Other Features
Customize Session Boxes Color
Customize Time-Based Liquidity Line Style
Customize Time-Based Liquidity Level Color
Customize Time-Based Liquidity Line Width
Customize Table Size and Location
Usage Guidance:
Add Time Matrix to your Tradingview chart.
Customize your desired settings of Time-Based Liquidity Levels to align with your personal preference.
Observe where the Time-Based Liquidity Levels as well as Previous Day, Week, and Macros play a role in intraday narrative.
Analysts can choose to utilize Time-Based Liquidity Levels as automated framework to organize models and layouts.
These tools are available ONLY on the TradingView platform.
Terms and Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products.
Finally, the purchaser indemnifies the seller from any and all liability. If the purchaser was invited through the Friends and Family Program, they acknowledge that the provided discount code only applies to the first initial purchase of the Toodegrees Premium Suite subscription. The purchaser is therefore responsible for cancelling – or requesting to cancel – their subscription in the event that they do not wish to continue using the product at full retail price. If the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
在腳本中搜尋"liquidity"
Support & Resistance PROHi Traders!
The Support & Resistance PRO
A simple and effective indicator that helped me a bunch!
This indicator will chart simple support and resistance zones on 2 time frames of your choice.
It uses a 30 day lookback period and will find the last high and low.
Each zone is built from the highest/lowest closure, and the highest/lowest wick, creating a liquid zone between the 2.
It is perfect for people trading support and resistance, watching key areas, scalping zones and much more!
*You can change the time frames you are looking at and the lookback period.
*The example in the picture is looking at the Daily and Weekly zones on BTC.
Lune Oscillator Premium⬛️ Overview
Lune Oscillator is an advanced and innovative TradingView indicator designed to enhance your market analysis. Rather than merely improving visuals or merging traditional indicators, it introduces a series of unique features, each with its unique value proposition. This script stands out due to its originality, and the significant utility it brings to traders.
🟦 Features
Oscillator features an assortment of sophisticated tools aimed at refining your trading strategies:
🔹 Trend Oscillator: This feature integrates market trend and momentum analysis into one dynamic oscillator. It's designed to facilitate market trend and momentum analysis, and is invaluable to traders as it combines both trend and momentum analysis into one tool. For instance, if a ticker shows signs of slowing momentum after a recent rally, the Trend Oscillator could predict a potential trend reversal. The Trend Oscillator’s sensitivity and velocity settings can be tailored to suit your trading style and strategy. It is developed using a custom formula similar to WaveTrend but optimized for better detection of trend and momentum shifts.
🔹 Market Peak: Market Peak identifies potential market peaks and troughs using a percentile-based system. It's aimed at detecting overextensions in the Trend Oscillator, indicating potential market reversals. Compact and user-friendly, this feature signals potential trade exit points in case of an impending market reversal. Its sensitivity can be adjusted to react to either short-term or long-term market changes. By analyzing the market's average move, it detects overbought or oversold conditions when the percentage gets too extreme.
🔹 Money Pulse: The Money Pulse feature serves as a radar for money inflow or outflow, helping users detect nascent trends and reversals. It enables traders to spot early opportunities and reversals and align their strategies with institutional and large players. For example, a bullish Money Pulse during market consolidation could signal money influx and the beginning of an accumulation phase. The sensitivity of the Market Pulse can be adapted to short-term or long-term changes. This feature employs an improved version of the Money Flow concept.
🔹 Liquidity Pulse: Liquidity Pulse provides a unique perspective of asset liquidity by tracking market inflow and outflow volumes. It assists traders in understanding the market's liquidity sentiment, which is particularly useful for long-term trades and confluence. For instance, a bullish Liquidity Pulse could signal abundant liquidity, potentially driving up the price. The sensitivity setting can be adjusted for short-term or long-term liquidity changes. This feature utilizes an enhanced version of the On-Balance Volume concept.
🔹 Institutional Wave: This feature tracks the cumulative inflow and outflow for a specific ticker, helping traders monitor institutional money flows. It enables the analysis of a ticker's accumulation and distribution, assisting in detecting early trade entries and avoiding dumps. For example, a decrease in volume during consolidation after a price rally could indicate sell-off and potential price drop. The Institutional Wave's sensitivity can be adapted to either short-term or long-term changes. It operates on the Accumulation and Distribution concept.
🔹 Power Wave: The Power Wave evaluates market strength and momentum, indicating market power shifts. It helps traders understand the true power behind a market move. For instance, a decreasing Power Wave during a bullish move could indicate a weakening trend, suggesting a bearish strategy instead. The sensitivity of the Power Wave can be set for short-term or long-term market changes. The Power Wave calculates market strength by evaluating price change volatility.
🔹 Market Pressure: This feature detects shifts in buy and sell pressure, signaling potential turning points. It helps traders understand the power balance in the market. For example, a bullish Market Pressure shift during a short trade could suggest a momentum gain by bulls, indicating a trade exit. The Market Pressure's sensitivity can be adjusted for short-term or long-term changes. This feature uses volume data and moving averages to detect market pressure shifts, filtering out false and volatile signals.
🔹 Oscillator Copilot: Incorporating Smart Bias and Reversal Radar, the Oscillator Copilot helps identify market trends and potential reversals. It searches for confluence within multiple Oscillator features, providing a straightforward assistive tool. For example, a bullish Smart Bias signal during a long trade could suggest staying in the trade longer, while a bearish Reversal Radar signal could indicate the need to exit the trade.
🔹 Divergence Detection: This feature offers a sophisticated detection system for both regular and hidden market divergences, providing additional confluence and highlighting hard-to-detect divergences. For instance, a bullish Regular Divergence could signal a potential trade entry or exit depending on your overall market sentiment and bias. This feature uses fractals to effectively detect divergences in the market based on the Trend Oscillator.
🔹 Color Themes: Personalize your charting experience with various color themes. This feature enhances the visual appeal of your chart, offering easy setup and use. For example, use the “Ice” theme for a unique and colorful experience or the “Dark” theme for a more subdued look. Themes available include Default, Light, Dark, and Ice. This feature modifies the colors of your candles and features based on the selected theme.
These features and tools collectively offer a comprehensive solution for traders to understand and navigate the financial markets. It's important to remember that they are designed to assist in making informed trading decisions and should be used as part of a balanced trading strategy.
🟧 Usage
Lune Oscillator's features are designed to be both standalone tools and components of a larger, integrated trading strategy. It is important to understand each feature and experiment with different configurations to best suit your unique trading needs.
🔸 Example #1: The following demonstrates how the Oscillator Copilot can be an excellent trade assistant.
The Oscillator Copilot leverages multiple Lune Oscillator features, allowing traders to quickly assess overall market sentiment. It uses Smart Bias and Reversal Radar tools to deliver these insights. For instance, at point 1, a bullish Smart Bias (denoted by a green circle) represents a collective bullish sentiment from multiple components of Lune Oscillator, often leading to a price increase. Conversely, at point 2, we identify two bearish reversal signals from the Reversal Radar (highlighted by red triangles). This convergence of bearish signals from multiple components hints at a potential market reversal, often followed by a gradual price decline.
🔸 Example #2: This example shows how the Market Peak feature can aid in detecting potential market tops and bottoms.
Market Peak calculates how overbought or oversold a ticker is using a percentile system, offering insights into potential reversals. At points 1 and 2, we observe bearish Market Peaks suggesting overbought conditions and indicating a possible shift in trend. Subsequent to these peaks, we witness a price drop, mirroring the overbought market conditions. In contrast, at point 3, a bullish Market Peak suggests an oversold market, indicating a potential trend reversal and subsequent price increase.
🔸 Example #3: This is an example of how combining various features such as the Money Pulse, Liquidity Pulse, Institutional Wave, and Market Peak, can help make more informed trades.
Money Pulse and Liquidity Pulse provide insights into the money and liquidity flow in the market, respectively, while the Institutional Wave monitors the cumulative volume shifts and changes. Together with Market Peak, they offer a comprehensive view of the market's state.
At point 1, the positive Liquidity Wave (crossing above 0) suggests a bullish market volume. At point 2, a bullish Market Pressure indicates an increase in buying pressure, reinforcing the bullish sentiment. At point 3, a negative Liquidity Wave (crossing below 0) indicates a bearish sentiment, suggesting that market participants are exiting their positions. The concurrent Market Pressure hints at an increase in selling activity. Taking all these factors into account provides a strong indicator that the market sentiment has turned bearish.
🟥 Conclusion
Lune Oscillator aims to provide a suite of tools that bring unique value to traders. Each feature is designed to offer different, yet complementary, perspectives on the market, allowing users to piece together a more comprehensive understanding of their trading environment.
🔻 Access
You can see the Author's instructions below to get instant access to this indicator & our Premium Suite.
🔻 Disclaimer
Lune Oscillator is a tool for aiding in market analysis and is not a guarantee of future market performance or individual trading success. We strongly recommend that users combine our tool with their trading strategies and do their due diligence before making any trading decisions.
Remember, past performance is not indicative of future results. Please trade responsibly.
Diddly - Real Volume TrendDiddly Real Volume Trend is an indicator to help traders identify the real trending direction of an asset, it achieves this by using liquidity to assess the overall buying and selling volume sentiment of a market place.
What is Liquidity
Liquidity refers to the ability of an asset to be turned into cash. Cash is the more liquid form of any asset, whereas selling a house would take a little longer to liquidate and convert to cash. Liquidity in financial markets is in essence based on the same principle and refers to how easily an asset can be bought and sold.
Liquidity in simple terms is the volume of participants who are willing to be involved in the market at any given time. Markets are based on auction theory, the more participants who want to buy at a certain price than sell, will dictate that the price goes up. As a result it is important to understand the role that volume has in financial markets, as volume will directly correlate to liquidity and supply and demand.
What does it mean?
Although markets are based on auction theory, sadly we don't have the advantage of a traditional auction, where we are all sitting in a room putting our hands in the air when we are interested in paying x price for a particular item. In this environment it is very clear to see how popular the item for sale is and whether it is possible to pick up a bargain.
Being able to identify the prevailing direction of buying versus selling volume on a chart provides an insight into market sentiment. Also we have to consider that typically most retail traders participate in very liquid markets, where you can get in and out of a position with relative ease.
There are obviously exceptions, extremely low float stocks, but on the whole with liquid assets it takes some big orders to move price, especially with currencies and high float stocks. Understanding these principles helps us as retail traders identify where the big money is seeing a bargain, if buying or overpriced if selling.
However you identify liquidity, I hope you agree that it is an extremely important element to be considering before taking a trade. The last thing any trader wants to be doing if they can avoid it, is getting on the wrong side of the market.
Just as a side note, high and low "Float Stocks" refers to the number of shares in general circulation for buying and selling.
What is "Diddly Real Volume Trend"
This volume trend indicator in simple terms will display the combined accumulated bullish and bearish volume within a window below the main chart. What you will see is a line chart that will be doing one of three things. Either it could be stair stepping in an upwards direction, identifying that we are in a bullish trend or stepping down in a bearish trend. Alternatively it could just be going sideways, which would suggest a ranging market.
This enables traders to make an assessment of the market sentiment using the liquidity direction that it has identified. This can help form an overall daily bias for intra-day traders or help confirm a longer term trend for swing traders.
Although this indicator is not a true oscillator (where the limits of number are fixed between a known upper and lower limit) , it can still be extremely useful in identifying divergence in price and the volume sentiment. As well as assisting in the process of identifying and confirming peak formations and potential reversal points in a market.
How does it Work
The indicator is plotting the volume trend line based on the output of a set of volume calculations, which is confirmed on the close of each candle. The resultant output is either a positive (Bullish sentiment) or negative (Bearish Sentiment), which are all totalled up to show the next point on the graph. As a result the visual effect seen from this process is that the more bullish calculated volume identified than bearish, you will see a rising trend line and the reverse for a bearish market.
The algo calculation which is used on each candle and its related volume is using the following elements.
Volume
Rate of Change
Relative Strength
The indicator is not just looking at the volume total and saying this is a green candle and must provide a positive number. It is looking for the volume and liquidity extremes and filtering out the nothingness of a market that makes no difference to price either way. It is from using these extremes that the indicator is able to plot the activities and direction of the big money in the market.
What is the Indicator Showing me?
Examples:
Here on a stock VKTX, on a 1 minute chart the elements that make up the indicator are annotated on the chart.
There are 6 components highlighted in the above chart, these have been listed below.
Volume Trend Line
This is the indicator driving line and is the result of the calculations described in the previous section.
Fast Moving Average
This is the fast moving average of the "Volume Trend Line". The moving average type and length can be changed in the settings.
(Default = Exponential Moving Average, Length: 60)
Slow Moving Average
This is a slower moving average of the "Volume Trend Line". The moving average type and length can be changed in the settings.
(Default = Hull Moving Average, Length: 3500)
Long Term Moving Average
This is a long term moving average of the "Volume Trend Line". The moving average type and length can be changed in the settings.
(Default = Exponential Moving Average, Length: 400)
Bullish Confirmation
On the "Volume Trend Line", you will see coloured circles dotted along the line, the green circles signifying Bullish Confirmation.
Bearish Confirmation
On the "Volume Trend Line", you will see coloured circles dotted along the line, the red circles signifying Bearish Confirmation.
The Bullish and Bearish confirmation signals are not signals to take trades, they are there to highlight the predominant direction. Seeing one confirmation signal in isolation is not that helpful, but continued prints of confirmation in a single direction would be interesting.
There are a further two signal types that are displayed on the volume trend line, these should be seen infrequently across charts and represent potential extremes of price movement in a single direction. These signals act as a warning that price could stall in this area or potentially make a reversal. As with the other signals within this indicator they are not signals to buy or sell, they are there to provide warning alerts and should be considered with other pieces of information that you are working with.
Bullish Extreme
Plotted on the "Volume Trend Line", you will occasionally see a green coloured downwardly pointing triangle, this represents a Bullish Extreme.
GBPAUD Hourly chart October 2022
Bearish Extreme
Plotted on the "Volume Trend Line", you will occasionally see a red coloured upward pointing triangle, this represents a Bearish Extreme.
GBPAUD Daily chart (February - April) 2023
How Does It Help?
This indicator will compliment any existing strategy and is not intended to be used standalone.
It can be used on any chart from a monthly, one minute to one second, depending on your trading strategy. Using multiple time frame analysis can help traders with a number of decisions that need to be considered before taking entries.
What is my market direction bias?
This can be taken from an hourly for intraday trader or daily for swing traders. What that time frame is depends on your trading plan and objectives from the trades you take.
When do I take my trades?
Again depending on the trading strategy used will dictate many aspect of this decision, although using the volume trend on a lower time frame, can help confirm breakouts, reversals and divergence.
How should I manage my trade?
With any trade you should have a defined risk reward clearly defined, with stops and targets in mind before taking an entry.
The age old saying of "cut your losses quickly and let your winner run", is easier said than mastered. Once in a trade the volume trend can be really helpful to identify trades that could be real runners and allows you to change expectations after entering the trade. Maybe you want to take some profit at the original point and let the remaining run. Maybe there is such strength you want to add to the position. Being able to assess market sentiment once in a trade can help with optimising returns.
The "Volume Trend Line", which is the driving element of this indicator, will be doing one of three things. Either it could be stair stepping in an upwards direction, identifying that we are in a bullish trend, stepping down in a bearish trend or going sideways in a ranging market.
Bullish Volume Trending Market
Here is stock VKTX, on a 1 minute chart. Trend confirmation on price action is determined by Higher Highs and Higher Lows for an uptrend or Lower Lows and Lower Highs on a downtrend. The same principle applies for the volume trend line.
In this example we first see breakout volume on the indicator with the Bullish Break volume, following that the volume trend keeps making higher highs and higher lows, confirming that this asset has short-term upwards potential. (why short-term? this is the 1 minute chart, you would want to consult the daily or hourly for a longer term perspective).
Price also is making higher highs and higher lows, which is in alignment with the indicator and known as "convergence" and is a positive signal for a continued trend.
Bearish Market
So here on Tesla (TSLA) on the 4 hour chart we can see the big sell off that started in April 2022. Where it clearly shows a downward trend, with lots of confirmation for continuation.
Ranging Markets
On this example on the AUDJPY 1 Hour chart, we can see that price is in a ranging market. By drawing trend lines on price and the indicator, it is clear to see that price and the volume trend line are both showing a ranging market. What is more interesting is the structure of the ranges.
The price range at the top of the chart is in an upward direction, whereas the volume trend in the bottom window is showing a downward range. Giving us an early indication of what to expect from this asset.
Diverging Markets
"Divergence" is a very powerful mechanism for identifying potential reversal points in price actions. There is a wealth of published information on this topic which is well worth reviewing, if this is a new principle to you.
Here again on the same AUDJPY 1 Hour chart example, points of interest have been annotated on the chart where the historical range turns into a step down to the next level within the market cycle, as predicted by the divergence in range patterns, price point up and volume pointing down.
In the above example, after identifying the divergence the next most important element is an extremely fast accelerated move down which breaks the lower level of the range, this can be seen on the right side of the bottom window and is labelled "Bearish Breaking Volume".
What is interesting here is that the volume indicator has identified the range breakout when price was still above the lower level of the range. Following that break out volume signal, if we zoom out to a 4 hour chart to see what happened next.
The range breakout was confirmed and price and the volume trend continues to show a downward direction in the market. As for entries and stops that is not the intention of this indicator and will be down to other elements in your trading strategy or in our case other indicators.
Peak Formations
Peak formation refers to the point where an asset is over extended in one direction and there is a potential of change in direction, with a wider pullback or a reversal in the higher time frame trend. These formations are often seen with double bottoms (W patterns) or double tops (M patterns) . Unfortunately these patterns appear all over the chart and trading them in isolation will be challenging.
In this example of EURJPY on the 1 hour chart, we see price and the indicator in the bottom window for the first 3 weeks in March 2022. The pair is trending down which is confirmed by both price and the indicator. There are no signals points plotted on the volume trend line, until one appears on March 4th 2022.
Another one appeared on the next trading day of Monday the 7th and we now have these two signals relatively close to each other. This is interesting information, especially considering that there was no extreme signals for the previous couple of months.
Later that day the volume trend broke the previous volume level, after a W pattern was completed and a green bullish confirmation signal was printed. The following day another bullish confirmation signal is displayed to further confirm that we had made a peak formation reversal.
Please note that using the settings style tab, has enabled the change to the bearish extremes signal, changing the colour and shape to be an orange circle. Which for the purposes of this illustration is easier to see.
Another example of the same pair in August 2022, with a very similar confirmation sequence.
Stock Examples
Here on UBER on a 1 hour chart , is an example of how the indicator can be used in confluence with other trading strategies. If a trader was trading candle patterns, they may see this classic 1 hour bull flag pattern forming.
Without the volume trend analysis this looks like a good buy setup. Adding this analysis to the chart we clearly have a different view point.
Here is what subsequently happened to price and this is in a generally bullish market March 2023.
Scalping Entries
For those traders who work with super fast time frames like the 5 second or even on a 1 second charts, the volume indicator can be used to help time entries as a part of a wider trading strategy of trading a pullback or trading support and resistance levels.
Styling options in the indicator settings enabled this different view of the indicator output, which can be extremely useful for timing entries.
Here on this hot IPO stock, LUNR from February 16th 2023, we have an extremely strong move up from $13.80 to $18.00. One aspect of this move up, is that it is doing this on extremely light volume and the predominant market sentiment on the surface seems very bearish.
This would be a clear indication not to trade this stock at this moment in time, as a trader there would be lots of emotions of FOMO (fear of missing out) , seeing a stock making that kind off move on a new IPO - there is the sense that this stock will go to the moon and your not going to be involved.
As traders we have to consider the risk : reward potential. This stock could drop to $10.00 if someone put in a 50 k market sell order, as it is clear there are not the buyers to support that kind of liquidation.
The following charts are in the 5 second time frame, until otherwise stated
So we need to wait for some confirmation of buying liquidity before we can make any plans for taking an entry, which we get in the form of a couple of strong bullish candles on the chart below. Interestingly the price breaks the previous all time high for this stock, although the volume trend at this stage does not seem strong enough to consider an entry.
At this point we should be on the lookout for further buying liquidity, ideally to break the previous high volume line, which appears in the next chart. This would be the time to take an entry based on other aspects of a trading plan.
Having now taken an entry, we can use the indicator to understand the strength of the buying liquidity and identify areas where we should be looking to take profit or close out the trade. Looking at the volume trend profile shown in the chart below, there is no reason not to hold this stock for a wider move up.
In the next chart we see the first signs of some selling pressure, as the indicator shows signs of red. This would be the area to take some profit and look at a higher time frame perspective, to get the sense of whether to hold the remaining position.
Here on the 5 minute time frame the volume trend is still looking very strong to hold the remaining position. As it turned out it was a good place to take profit as it was just under the high of the day.
Knowing when an asset is going to reverse is not easy and this stock was way too over extended and a top had to finally come. This one minute view of the indicator, shows the point where you would see that the upward liquidity was over and you were now on the backside of the move, with no reason to trade further.
Here on a 15 minute chart you can see the full extent of the move and its reversal back to the original price. It provides a clear illustration that chasing trades through FOMO or holding and hoping is not a profitable approach. Being able to time your entries and exits, where you can clearly manage risk is one of the most important elements to any traders strategy.
This is an extreme example and not something you see every day in any market. It has been included within this narrative with the hope that it clearly illustrates the risk involved in trading and being able to mitigate them, has to be at the forefront of your mind.
Key Settings
Within the indicator settings there are a number of options that are available to users. All aspects of what you can see can either be changed or turned on or off in the "Style" tab as well as changing the colours and their transparency.
The available settings on the "Inputs" tab are for fine tuning the indicator to your style of trading. This fine tuning can be applied to the moving averages that can be displayed and follow the volume trend line as well as the volume filtering process.
The most important ones that are in need of explanation are outline below:
General Settings
"What type of asset is the Algo looking at" : Available Options = "Small Caps", "Large Caps", "Futures", "Currencies" (Default Setting = Currencies)
The indicator will make an assessment of the best settings to use as defaults for the volume filtering, confirmation and extremes signals. The defaults can be changed in the following sections using the override.
"Turn on Turbo Mode" : True or False (Default Settings = True)
This setting will give the indicator volume filtering processes a boost
Signal Settings
Based on the "Asset Type" from the general settings, the indicator will make an assessment of the best settings to use by default. These can be changed by using the settings below.
"Override Default Assessment Thresholds" = True / False
"Percentage Difference to Signify Trend Confirmation" = A percentage value that will tell the indicator how to identify the volume trend line swing points used to identify bullish or bearish confirmation signals. Values from 0.1 to 10 would make the most sense. A too high setting and you will not see any confirmation points plotted. Too low and you may see too many to be useful.
"Percentage Difference to Signify Extremes" = A percentage value that will tell the indicator how to identify the volume trend line swing points used to identify bullish or bearish confirmation signals. Values from 20 to 200 would make the most sense. A low a setting and you will see too many extreme points plotted.
Filter Settings
"Turn On Volume Assessment Filters" = True / False : The volume assessment filters are used to focus the "volume trend line" on higher volume extremes.
Based on the "Asset Type" from the general settings, the indicator will make an assessment of the best settings to use by default. These can be changed by using the settings below.
"Override Default Assessment Filters" = True / False
"Filter Volume using Setting" = The number used in this setting represents a value from 0 to 100. Zero will filter out no volume, whereas 100 would filter it all out. The default setting is 1, as there is a danger of setting this number too high and all you will see in the line chart is big steps up and down, with a plateaus in the middle. Which may be useful, although it would not be so helpful in divergence or volume line breaks.
Fast Moving Average
This is the fast moving average of the "Volume Trend Line".
"Moving Average Type" = The type of moving average calculation to be applied.
Default = "EMA"
Available Options: "SMA","EMA" ,"HMA" ,"SMMA (RMA)" ,"WMA" ,"VWMA"
Moving Average Key
SMA : Simple Moving Average
EMA : Exponential Moving Average
HMA : Hull Moving Average
SMMA (RMA) : Exponentially Weighted Moving Average (alpha = 1 / length.)
WMA : Weighted Moving Average
VWMA : Volume Weighted Moving Average
"Moving Average Length" = The number of candles back into the chart used to calculate the Moving Average. (The higher the number, the slower the moving average becomes)
Default Length = 60
"Apply Double Smoothing" = True or False : This is an option to turn on if an extra smoothing effect to the moving average if required.
Slow Moving Average
This is the slow moving average of the "Volume Trend Line".
"Moving Average Type" = The type of moving average calculation to be applied.
Default = "HMA"
Available Options: "SMA","EMA" ,"HMA" ,"SMMA (RMA)" ,"WMA" ,"VWMA"
(See moving average key)
"Moving Average Length" = The number of candles back into the chart used to calculate the Moving Average. (The higher the number, the slower the moving average becomes)
Default Length = 3500
(By default we have a higher number for the slow length compared to the long term length in the next setting. This is because using the Hull Moving Average, is an accelerated moving average that needs higher values to slow it down. If you were to change this to say an EMA, then you would need to change the length to something like 200, to put this slower moving average in context with the others).
Long Term Moving Average
This is a long term moving average of the "Volume Trend Line".
"Moving Average Type" = The type of moving average calculation to be applied.
Default = "EMA"
Available Options: "SMA","EMA" ,"HMA" ,"SMMA (RMA)" ,"WMA" ,"VWMA"
(See moving average key)
"Moving Average Length" = The number of candles back into the chart used to calculate the Moving Average. (The higher the number, the slower the moving average becomes)
Default Length = 400
"Apply Double Smoothing" = True or False : This is an option to turn on if an extra smoothing effect to the moving average if required.
Finally
We greatly appreciate the support and feedback from the Trading View community, and we are dedicated to continuing to improve our indicators with your support.
We want to help you manage risk, and that's why we emphasise that trading is risky and any technology used to support our trading decisions is based on information from the past. We encourage traders to take responsibility for their trading businesses and always prioritise risk management.
Smart Money Trades Pro [BOSWaves]Smart Money Trades Pro – Advanced Market Structure & Liquidity Visualizer
Overview
Smart Money Trades Pro is a comprehensive trading tool designed for traders seeking an in-depth understanding of market structure, liquidity dynamics, and institutional flow. The indicator systematically identifies key market turning points, including break of structure (BOS) and change of character (CHoCH) events, and overlays these with adaptive visualizations to highlight high-probability trade setups. By integrating ATR-based risk zones, progressive take-profit levels, and real-time trade analytics, Smart Money Trades Pro transforms complex price action into an interpretable framework suitable for multiple trading styles, including scalping, intraday, and swing trading.
Unlike traditional static indicators, Smart Money Trades Pro adapts continuously to market conditions. It evaluates swing highs and lows over a configurable lookback period, then determines structural breaks using customizable confirmation methods (candle body or wick). The resulting signals are augmented with dynamic entry, stop-loss, and target levels, allowing traders to analyze potential trade opportunities with both precision and context. The indicator’s design ensures that each visual element—trend-colored candles, signal markers, and risk/reward boxes—reflects real-time market conditions, offering an actionable interpretation of institutional activity.
How It Works
The indicator’s foundation is built upon market structure analysis. By calculating pivot highs and lows over a specified period, Smart Money Trades Pro identifies potential points of liquidity accumulation and exhaustion. When price breaks a pivot high or low, the indicator evaluates whether this constitutes a BOS or a CHoCH, signaling trend continuation or reversal. These events are marked on the chart with distinct visual cues, allowing traders to quickly discern shifts in market sentiment without manually analyzing historical price action.
Once a structural break is confirmed, the indicator automatically determines entry levels, stop-loss placements, and progressive take-profit zones (TP1, TP2, TP3). These calculations are based on ATR-derived volatility, ensuring that targets scale with current market conditions. Risk and reward zones are plotted as shaded boxes, providing a clear visual representation of potential profit relative to risk for each trade setup. This system allows traders to maintain discipline and consistency, with dynamic trade management baked directly into the visualization.
Trend direction is further reinforced by color-coded candles, which reflect the prevailing market bias. Bullish trends are represented by one color, bearish trends by another, and neutral conditions are displayed in muted tones. This continuous visual feedback simplifies the process of trend assessment and helps confirm the validity of trade setups alongside BOS and CHoCH markers.
Signals and Breakouts
Smart Money Trades Pro includes structured visual signals to indicate actionable price movements:
Bullish Break Signals – Triangular markers below the candle appear when a swing high is broken, suggesting potential long opportunities.
Bearish Break Signals – Triangular markers above the candle appear when a swing low is broken, indicating potential short setups.
Change of Character (CHoCH) – Special markers highlight trend reversals, showing where momentum shifts from bullish to bearish or vice versa.
These markers are strategically spaced to prevent overlap and remain clear during high-volatility periods. Traders can use them in combination with trend-colored candles, risk/reward zones, and ATR-based targets to assess the strength and reliability of each setup. The integrated table provides live trade information, including entry price, stop-loss level, take-profit levels, risk/reward ratio, and trade direction, ensuring that trade decisions are informed and data-driven.
Interpretation
Trend Analysis : The indicator’s trend coloring, combined with BOS and CHoCH detection, provides an immediate view of market direction. Rising structures indicate bullish momentum, while falling structures signal bearish momentum. CHoCH markers highlight potential trend reversals or significant liquidity sweeps.
Volatility and Risk Assessment : ATR-based calculations determine stop-loss distances and target levels, giving a quantitative measure of risk relative to market volatility. Wide ATR readings indicate periods of high price fluctuation, whereas narrow readings suggest consolidation and reduced risk exposure.
Market Structure Insights : By monitoring swing highs and lows alongside break confirmations, traders can identify where institutional players are likely active. Areas with multiple structural breaks or overlapping targets can indicate liquidity hotspots, potential reversal zones, or areas of market congestion.
Trade Management : The built-in trade zones allow traders to visualize entry, risk, and reward simultaneously. Progressive targets (TP1, TP2, TP3) reflect incremental profit-taking strategies, while dynamic stop-loss levels help preserve capital during adverse moves.
Strategy Integration
Smart Money Trades Pro supports a range of trading approaches:
Trend Following : Enter trades in the direction of confirmed BOS while using CHoCH markers and trend-colored candles to validate momentum.
Pullback Entries : Use failed breakout retests or minor reversals toward broken structure levels for lower-risk entries.
Mean Reversion : In consolidated zones with narrow ATR and repeated BOS/CHoCH activity, anticipate reversals or short-term corrective moves.
Multi-Timeframe Confirmation : Overlay signals on higher or lower timeframes to filter noise and improve trade accuracy.
Stop-loss levels should be placed just beyond the opposing structural point, while take-profit targets can be scaled using the ATR-based zones. Progressive targets allow for partial exits or scaling out of trades while maintaining exposure to larger moves.
Advanced Techniques
Traders seeking greater precision can combine Smart Money Trades Pro with volume, momentum, or volatility indicators to validate signals. Observing sequences of BOS and CHoCH markers across multiple timeframes provides insight into liquidity accumulation and depletion trends. Tracking the expansion or contraction of ATR-based zones helps anticipate shifts in volatility, enabling better timing for entries and exits.
Customizing the structure period and confirmation type allows the indicator to adapt to different asset classes and timeframes. Shorter periods increase sensitivity to smaller swings, while longer periods filter noise and emphasize higher-probability structural breaks. By integrating these features, the indicator offers a robust statistical framework for disciplined, data-driven trading decisions.
Inputs and Customization
Structure Detection Period : Defines the lookback window for pivot high and low calculation.
Break Confirmation : Choose whether to confirm breaks using candle body or wick.
Display CHoCH : Toggle visibility of change-of-character markers.
Color Trend Bars : Enable color-coding of candles based on market structure direction.
Show Info Table : Display trade dashboard showing entry, stop-loss, take-profits, risk/reward, and bias.
Table Position : Choose from top-left, top-right, bottom-left, or bottom-right placement.
Color Customization : Configure bullish, bearish, neutral, risk, reward, and text colors for enhanced visual clarity.
Why Use Smart Money Trades Pro
Smart Money Trades Pro transforms complex market behavior into an actionable visual framework. By combining market structure analysis, liquidity tracking, ATR-based risk/reward mapping, and a dynamic trade dashboard, it provides a multidimensional view of the market. Traders can focus on execution, interpret trends, and evaluate overextensions or reversals without relying on guesswork. The indicator is suitable for scalping, intraday, and swing strategies, offering a comprehensive system for understanding and trading alongside institutional participants.
SMC - OB/Breaker Block/Bos/ChoCh (DeadCat) Based on analyzing your Pine Script code, here are comprehensive descriptions that should comply with TradingView's house rules:
Script 1: "PO3 Liquidity w/ CISD (DeadCat)"
Description:
This indicator implements the Power of Three (PO3) liquidity concept combined with Change in State of Delivery (CISD) pattern recognition for Smart Money Concepts (SMC) trading. The script operates on multi-timeframe analysis using automated timeframe selection.
Core Methodology: The indicator identifies C2 liquidity sweeps by detecting when price breaks previous period highs/lows and then reverses back above/below those levels. It specifically looks for:
C2 Buy Setup: When current low breaks previous period low but closes back above it
C2 Sell Setup: When current high breaks previous period high but closes back below it
CISD Pattern Detection: The script implements sophisticated CISD (Change in State of Delivery) pattern recognition by:
Tracking the first break of previous HTF high/low levels
Identifying imbalance candles (gaps between consecutive candles)
Confirming CISD when price reclaims the imbalance level within 2 HTF periods
Validating setups only when both liquidity sweep AND CISD confirmation occur
Visual Components:
HTF Candles: Displays higher timeframe candle structure on current chart
Trading Zones: Shows zones between HTF open and equilibrium levels
CISD Lines: Marks confirmed change in state of delivery levels
C2/C4 Labels: Identifies liquidity sweep entry points and potential continuation setups
Market Structure: Optional HH/HL/LH/LL pivot markers
Unique Features:
Automatic timeframe calculation (15m→4H, 1H→1D, etc.)
Real-time HTF period countdown
Setup invalidation tracking when stops are hit
Progressive setup confirmation (C2→C4 evolution)
Bias filter for directional trading preferences
Usage: C2 setups provide initial entry opportunities after confirmed liquidity sweeps with CISD confirmation. C4 setups offer additional entries when HTF equilibrium conditions align favorably. The indicator helps traders identify institutional liquidity grabs followed by genuine directional moves.
Script 2: "SMC Toolkit (DeadCat)"
Description:
This comprehensive Smart Money Concepts toolkit provides institutional-level market structure analysis with automated Order Block (OB) and Breaker Block (BB) zone identification, plus Break of Structure (BOS) and Change of Character (ChoCh) detection.
Market Structure Algorithm: The indicator uses a sophisticated pivot-based algorithm to identify and track market structure progression:
Uptrend: HH→HL→HH sequence tracking
Downtrend: LL→LH→LL sequence tracking
Trend Changes: Automatic ChoCh detection when structure breaks occur
Order Block Logic:
Bullish OB Zones: Created at Higher Lows (HL) and Lower Lows (LL) during uptrends
Bearish OB Zones: Created at Lower Highs (LH) and Higher Highs (HH) during downtrends
Uses last bearish candle before bullish moves (and vice versa) to define precise zone boundaries
Breaker Block Logic:
Bullish BB Zones: Former resistance that becomes support after HH/LH breaks
Bearish BB Zones: Former support that becomes resistance after LL/HL breaks
Automatically transitions when structure points are breached
Zone Management: The script employs intelligent zone lifecycle management:
Creates new zones only at confirmed structure points
Makes previous zones transparent when new structure is confirmed
Maintains zone relevance through dynamic extension
Limits total zones to prevent chart clutter
BOS vs ChoCh Detection:
BOS (Break of Structure): Continuation patterns when trend highs/lows are exceeded
ChoCh (Change of Character): Reversal patterns when pullback levels are broken against trend
Requires 2-candle confirmation before finalizing structure changes
Visual Enhancements:
Color-coded zones with transparency controls
Directional arrows (▲/▼) in zone labels
Customizable line styles and text sizing
Clean market structure progression tracking
Originality: This toolkit combines traditional SMC concepts with enhanced zone boundary calculation using multi-candle analysis and intelligent zone lifecycle management, providing more precise entry/exit levels than standard implementations.
UNITY[ALGO] PO3 V3Of course. Here is a complete and professional description in English for the indicator we have built, detailing all of its features and functionalities.
Indicator: UNITY PO3 V7.2
Overview
The UNITY PO3 is an advanced, multi-faceted technical analysis tool designed to identify high-probability reversal setups based on the Swing Failure Pattern (SFP). It combines real-time SFP detection on the current timeframe with a sophisticated analysis of key institutional liquidity zones from the H4 timeframe, presenting all information in a clear, dynamic, and interactive visual interface.
This indicator is built for traders who use liquidity concepts, providing a complete dashboard of entries, targets, and invalidation levels directly on the chart.
Core Features & Functionality
1. Swing Failure Pattern (SFP) Detection (Current Timeframe)
The indicator's primary engine identifies SFPs on the chart's active timeframe with two layers of logic:
Standard SFP: Detects a classic liquidity sweep where the current candle's wick takes out the high or low of the previous candle and the body closes back within the previous candle's range.
Outside Bar SFP Logic: Intelligently analyzes engulfing candles that sweep both the high and low of the previous candle. A valid signal is only generated if the candle has a clear directional close:
Bullish Signal: If the outside bar closes higher than its open.
Bearish Signal: If the outside bar closes lower than its open.
Neutral (doji-like) outside bars are ignored to filter for indecision.
2. Comprehensive On-Chart SFP Markings
When a valid SFP is detected, a full suite of dynamic drawings appears on the chart:
Failure Line: A dashed line (red for bearish, green for bullish) marking the precise price level of the liquidity sweep.
PREMIUM ZONE (SFP Candle Wick): A transparent, colored rectangle highlighting the rejection wick of the signal candle (the upper wick for bearish SFPs, the lower wick for bullish SFPs). This zone automatically extends to the right, following the current price, until the DOL is hit.
CRT BOX (Reference Candle): A transparent box with a colored border drawn around the entire range of the candle that was swept (Candle 1). This highlights the full liquidity zone and also extends dynamically until the DOL is hit.
Dynamic Target Line: A blue dashed line marking the primary objective (the low of the signal candle for shorts, the high for longs).
The line begins with a "⏳ Target" label and extends with the current price.
Upon being touched by price, the line freezes, and its label permanently changes to "✅ Target".
Dynamic DOL (Draw on Liquidity) Line: An orange dashed line marking the invalidation level, defined as the opposite extremity of the swept candle (Candle 1).
It begins with a "⏳ dol" label and extends with the price.
Upon being touched, it freezes, and its label changes to "✅ dol".
3. Multi-Session Killzone Liquidity Levels (H4 Analysis)
The indicator automatically analyzes the H4 timeframe in the background to identify and plot key liquidity levels from three major trading sessions, based on their UTC opening times.
1am Killzone (London Lunch): Tracks the high/low of the 05:00 UTC H4 candle.
5am Killzone (London Open): Tracks the high/low of the 09:00 UTC H4 candle.
9am Killzone (NY Open): Tracks the high/low of the 13:00 UTC H4 candle.
For each of these Killzones, the indicator provides two types of analysis:
Last KZ Lines: Plots the high and low of the most recent qualifying Killzone candle. These lines are dynamic, extending with price and showing a ⏳/✅ status when touched.
Fresh Zones: A powerful feature that scans the entire available history of Killzones to find and display the closest untouched high (above the current price) and the closest untouched low (below the current price). These "Fresh" lines are also fully dynamic and provide a real-time view of the most relevant nearby liquidity targets.
4. Advanced User Settings & Chart Management
The indicator is designed for a clean and user-centric experience with powerful customization:
Show Only Last SFP: Keeps the chart clean by automatically deleting the previous SFP setup when a new one appears.
Hide SFP on DOL Reset: When checked, automatically removes all drawings related to an SFP setup the moment its invalidation level (DOL line) is touched. This leaves only active, valid setups on the chart.
Hide Consumed KZ: When checked, automatically removes any Killzone or Fresh Zone line from the chart as soon as it is touched by the price.
Independent Toggles: Every visual element—SFP signals, each of the three Killzones, and their respective "Fresh" zone counterparts—can be turned on or off independently from the settings menu for complete control over the visual display.
Z-Order Priority: All indicator drawings are rendered in front of the chart candles, ensuring they are always clearly visible and never hidden from view.
3:55 PM NYC Candle Boxes (Multi-Day)This script is useful for a popular strategy with the NASDAQ 100 that marks up the 3:55PM NYC Candle.
This script is only set to be used on the1m and 5m timeframes, you shouldn't see anything on higher timeframes.
It can label any 3:55PM NYC candle , but this strategy is effectively proven for NAS, and as it only marks the 3:55 candles for you to save you the manual labor, please do not expect price to always come back to those marked prices.
You can use just a box on the labels, extend those boxes indefinitely, use a label at the top and bottom of those candles, or have a floating label for the LATEST 3:55 candle on the right side of the chart.
You can use labels for everything, or just clean boxes.
You can color code it to your hearts content to match your theme.
You can auto set alerts for when price touches the levels of the latest candle.
I welcome any and all feedback and suggestions. enjoy.
TCP | Market Session | Session Analyzer📌 TCP | Market Session Indicator | Crypto Version
A powerful, real-time market session visualization tool tailored for crypto traders. Track the heartbeat of Asia, Europe, and US trading hours directly on your chart with live session boxes, behavioral analysis, liquidity grab detection, and countdown timers. Know when the action starts, how the market behaves, and where the traps lie.
🔰 Introduction:
Trade the Right Hours with the Right Tools
Time matters in trading. Most significant moves happen during key sessions—and knowing when and how each session unfolds can give you a sharp edge. The TCP Market Session Indicator, developed by Trade City Pro (TCP), puts professional session tracking and behavioral insights at your fingertips.
Whether you're a scalper or swing trader, this indicator gives you the timing context to enter and exit trades with greater confidence and clarity.
🕒 Core Features
• Live Session Boxes :
Highlight active ranges during Asia, Europe, and US sessions with dynamic high/low updates.
• Session Start/End Labels :
Know exactly when each session begins and ends plotted clearly on your chart with context.
• Session Behavior Analysis :
At the end of each session, the indicator classifies the price action as:
- Trend Up
- Trend Down
- Consolidation
- Manipulation
• Liquidity Grab Detection: Automatically detects possible stop hunts (fake breakouts) and marks them on the chart with precision filters (volume, ATR, reversal).
• Session Countdown Table: A live dashboard showing:
- Current active session
- Time left in session
- Upcoming session and how many minutes until it starts
- Utility time converter (e.g. 90 min = 01:30)
• Vertical Session Lines: Visualize past and upcoming session boundaries with customizable history and future range.
• Multi-Day Support: Draw session ranges for previous, current, and future days for better backtesting and forecasting.
⚙️ Settings Panel
Customize everything to fit your trading style and schedule:
• Session Time Settings:
Set the opening and closing time for each session manually using UTC-based minute inputs.
→ For example, enter Asia Start: 0, Asia End: 480 for 00:00–08:00 UTC.
This gives full flexibility to adjust session hours to match your preferred market behavior.
• Enable or Disable Elements:
Toggle the visibility of each session (Asia, Europe, US), as well as:
- Session Boxes
- Countdown Table
- Session Lines
- Liquidity Grab Labels
• Timezone Selection:
Choose between using UTC or your chart’s local timezone for session calculations.
• Customization Options:
Select number of past and future days to draw session data
Adjust vertical line transparency
Fine-tune label offset and spacing for clean layout
📊 Smart Session Boxes
Each session box tracks high, low, open, and close in real time, providing visual clarity on market structure. Once a session ends, the box closes, and the behavior type is saved and labeled ideal for spotting patterns across sessions.
• Asia: Green Box
• Europe: Orange Box
• US: Blue Box
💡 Why Use This Tool?
• Perfect Timing: Don’t get chopped in low-liquidity hours. Focus on sessions where volume and volatility align.
• Pattern Recognition: Study how price behaves session-to-session to build better strategies.
• Trap Detection: Spot manipulation moves (liquidity grabs) early and avoid common retail pitfalls.
• Macro Session Mapping: Use as a foundational layer to align trades with market structure and news cycles.
🔍 Example Use Case
You're watching BTC at 12:45 UTC. The indicator tells you:
The Asia session just ended (label shows “Asia Session End: Trend Up”)
Europe session starts in 15 minutes
A liquidity grab just triggered at the previous high—label confirmed
Now you know who’s active, what the market just did, and what’s about to start—all in one glance.
✅ Why Traders Trust It
• Visual & Intuitive: Fully chart-based, no clutter, no guessing
• Crypto-Focused: Designed specifically for 24/7 crypto markets (not outdated forex models)
• Non-Repainting: All labels and boxes stay as printed—no tricks
• Reliable: Tested across multiple exchanges, pairs, and timeframes
🧩 Built by Trade City Pro (TCP)
The TCP Market Session Indicator is part of a suite of professional tools used by over 150,000 traders. It’s coded in Pine Script v6 for full compatibility with TradingView’s latest capabilities.
🔗 Resources
• Tutorial: Learn how to analyze sessions like a pro in our TradingView guide:
"TradeCityPro Academy: Session Mapping & Liquidity Traps"
• More Tools: Explore our full library of indicators on
Adaptive Investment Timing ModelA COMPREHENSIVE FRAMEWORK FOR SYSTEMATIC EQUITY INVESTMENT TIMING
Investment timing represents one of the most challenging aspects of portfolio management, with extensive academic literature documenting the difficulty of consistently achieving superior risk-adjusted returns through market timing strategies (Malkiel, 2003).
Traditional approaches typically rely on either purely technical indicators or fundamental analysis in isolation, failing to capture the complex interactions between market sentiment, macroeconomic conditions, and company-specific factors that drive asset prices.
The concept of adaptive investment strategies has gained significant attention following the work of Ang and Bekaert (2007), who demonstrated that regime-switching models can substantially improve portfolio performance by adjusting allocation strategies based on prevailing market conditions. Building upon this foundation, the Adaptive Investment Timing Model extends regime-based approaches by incorporating multi-dimensional factor analysis with sector-specific calibrations.
Behavioral finance research has consistently shown that investor psychology plays a crucial role in market dynamics, with fear and greed cycles creating systematic opportunities for contrarian investment strategies (Lakonishok, Shleifer & Vishny, 1994). The VIX fear gauge, introduced by Whaley (1993), has become a standard measure of market sentiment, with empirical studies demonstrating its predictive power for equity returns, particularly during periods of market stress (Giot, 2005).
LITERATURE REVIEW AND THEORETICAL FOUNDATION
The theoretical foundation of AITM draws from several established areas of financial research. Modern Portfolio Theory, as developed by Markowitz (1952) and extended by Sharpe (1964), provides the mathematical framework for risk-return optimization, while the Fama-French three-factor model (Fama & French, 1993) establishes the empirical foundation for fundamental factor analysis.
Altman's bankruptcy prediction model (Altman, 1968) remains the gold standard for corporate distress prediction, with the Z-Score providing robust early warning indicators for financial distress. Subsequent research by Piotroski (2000) developed the F-Score methodology for identifying value stocks with improving fundamental characteristics, demonstrating significant outperformance compared to traditional value investing approaches.
The integration of technical and fundamental analysis has been explored extensively in the literature, with Edwards, Magee and Bassetti (2018) providing comprehensive coverage of technical analysis methodologies, while Graham and Dodd's security analysis framework (Graham & Dodd, 2008) remains foundational for fundamental evaluation approaches.
Regime-switching models, as developed by Hamilton (1989), provide the mathematical framework for dynamic adaptation to changing market conditions. Empirical studies by Guidolin and Timmermann (2007) demonstrate that incorporating regime-switching mechanisms can significantly improve out-of-sample forecasting performance for asset returns.
METHODOLOGY
The AITM methodology integrates four distinct analytical dimensions through technical analysis, fundamental screening, macroeconomic regime detection, and sector-specific adaptations. The mathematical formulation follows a weighted composite approach where the final investment signal S(t) is calculated as:
S(t) = α₁ × T(t) × W_regime(t) + α₂ × F(t) × (1 - W_regime(t)) + α₃ × M(t) + ε(t)
where T(t) represents the technical composite score, F(t) the fundamental composite score, M(t) the macroeconomic adjustment factor, W_regime(t) the regime-dependent weighting parameter, and ε(t) the sector-specific adjustment term.
Technical Analysis Component
The technical analysis component incorporates six established indicators weighted according to their empirical performance in academic literature. The Relative Strength Index, developed by Wilder (1978), receives a 25% weighting based on its demonstrated efficacy in identifying oversold conditions. Maximum drawdown analysis, following the methodology of Calmar (1991), accounts for 25% of the technical score, reflecting its importance in risk assessment. Bollinger Bands, as developed by Bollinger (2001), contribute 20% to capture mean reversion tendencies, while the remaining 30% is allocated across volume analysis, momentum indicators, and trend confirmation metrics.
Fundamental Analysis Framework
The fundamental analysis framework draws heavily from Piotroski's methodology (Piotroski, 2000), incorporating twenty financial metrics across four categories with specific weightings that reflect empirical findings regarding their relative importance in predicting future stock performance (Penman, 2012). Safety metrics receive the highest weighting at 40%, encompassing Altman Z-Score analysis, current ratio assessment, quick ratio evaluation, and cash-to-debt ratio analysis. Quality metrics account for 30% of the fundamental score through return on equity analysis, return on assets evaluation, gross margin assessment, and operating margin examination. Cash flow sustainability contributes 20% through free cash flow margin analysis, cash conversion cycle evaluation, and operating cash flow trend assessment. Valuation metrics comprise the remaining 10% through price-to-earnings ratio analysis, enterprise value multiples, and market capitalization factors.
Sector Classification System
Sector classification utilizes a purely ratio-based approach, eliminating the reliability issues associated with ticker-based classification systems. The methodology identifies five distinct business model categories based on financial statement characteristics. Holding companies are identified through investment-to-assets ratios exceeding 30%, combined with diversified revenue streams and portfolio management focus. Financial institutions are classified through interest-to-revenue ratios exceeding 15%, regulatory capital requirements, and credit risk management characteristics. Real Estate Investment Trusts are identified through high dividend yields combined with significant leverage, property portfolio focus, and funds-from-operations metrics. Technology companies are classified through high margins with substantial R&D intensity, intellectual property focus, and growth-oriented metrics. Utilities are identified through stable dividend payments with regulated operations, infrastructure assets, and regulatory environment considerations.
Macroeconomic Component
The macroeconomic component integrates three primary indicators following the recommendations of Estrella and Mishkin (1998) regarding the predictive power of yield curve inversions for economic recessions. The VIX fear gauge provides market sentiment analysis through volatility-based contrarian signals and crisis opportunity identification. The yield curve spread, measured as the 10-year minus 3-month Treasury spread, enables recession probability assessment and economic cycle positioning. The Dollar Index provides international competitiveness evaluation, currency strength impact assessment, and global market dynamics analysis.
Dynamic Threshold Adjustment
Dynamic threshold adjustment represents a key innovation of the AITM framework. Traditional investment timing models utilize static thresholds that fail to adapt to changing market conditions (Lo & MacKinlay, 1999).
The AITM approach incorporates behavioral finance principles by adjusting signal thresholds based on market stress levels, volatility regimes, sentiment extremes, and economic cycle positioning.
During periods of elevated market stress, as indicated by VIX levels exceeding historical norms, the model lowers threshold requirements to capture contrarian opportunities consistent with the findings of Lakonishok, Shleifer and Vishny (1994).
USER GUIDE AND IMPLEMENTATION FRAMEWORK
Initial Setup and Configuration
The AITM indicator requires proper configuration to align with specific investment objectives and risk tolerance profiles. Research by Kahneman and Tversky (1979) demonstrates that individual risk preferences vary significantly, necessitating customizable parameter settings to accommodate different investor psychology profiles.
Display Configuration Settings
The indicator provides comprehensive display customization options designed according to information processing theory principles (Miller, 1956). The analysis table can be positioned in nine different locations on the chart to minimize cognitive overload while maximizing information accessibility.
Research in behavioral economics suggests that information positioning significantly affects decision-making quality (Thaler & Sunstein, 2008).
Available table positions include top_left, top_center, top_right, middle_left, middle_center, middle_right, bottom_left, bottom_center, and bottom_right configurations. Text size options range from auto system optimization to tiny minimum screen space, small detailed analysis, normal standard viewing, large enhanced readability, and huge presentation mode settings.
Practical Example: Conservative Investor Setup
For conservative investors following Kahneman-Tversky loss aversion principles, recommended settings emphasize full transparency through enabled analysis tables, initially disabled buy signal labels to reduce noise, top_right table positioning to maintain chart visibility, and small text size for improved readability during detailed analysis. Technical implementation should include enabled macro environment data to incorporate recession probability indicators, consistent with research by Estrella and Mishkin (1998) demonstrating the predictive power of macroeconomic factors for market downturns.
Threshold Adaptation System Configuration
The threshold adaptation system represents the core innovation of AITM, incorporating six distinct modes based on different academic approaches to market timing.
Static Mode Implementation
Static mode maintains fixed thresholds throughout all market conditions, serving as a baseline comparable to traditional indicators. Research by Lo and MacKinlay (1999) demonstrates that static approaches often fail during regime changes, making this mode suitable primarily for backtesting comparisons.
Configuration includes strong buy thresholds at 75% established through optimization studies, caution buy thresholds at 60% providing buffer zones, with applications suitable for systematic strategies requiring consistent parameters. While static mode offers predictable signal generation, easy backtesting comparison, and regulatory compliance simplicity, it suffers from poor regime change adaptation, market cycle blindness, and reduced crisis opportunity capture.
Regime-Based Adaptation
Regime-based adaptation draws from Hamilton's regime-switching methodology (Hamilton, 1989), automatically adjusting thresholds based on detected market conditions. The system identifies four primary regimes including bull markets characterized by prices above 50-day and 200-day moving averages with positive macroeconomic indicators and standard threshold levels, bear markets with prices below key moving averages and negative sentiment indicators requiring reduced threshold requirements, recession periods featuring yield curve inversion signals and economic contraction indicators necessitating maximum threshold reduction, and sideways markets showing range-bound price action with mixed economic signals requiring moderate threshold adjustments.
Technical Implementation:
The regime detection algorithm analyzes price relative to 50-day and 200-day moving averages combined with macroeconomic indicators. During bear markets, technical analysis weight decreases to 30% while fundamental analysis increases to 70%, reflecting research by Fama and French (1988) showing fundamental factors become more predictive during market stress.
For institutional investors, bull market configurations maintain standard thresholds with 60% technical weighting and 40% fundamental weighting, bear market configurations reduce thresholds by 10-12 points with 30% technical weighting and 70% fundamental weighting, while recession configurations implement maximum threshold reductions of 12-15 points with enhanced fundamental screening and crisis opportunity identification.
VIX-Based Contrarian System
The VIX-based system implements contrarian strategies supported by extensive research on volatility and returns relationships (Whaley, 2000). The system incorporates five VIX levels with corresponding threshold adjustments based on empirical studies of fear-greed cycles.
Scientific Calibration:
VIX levels are calibrated according to historical percentile distributions:
Extreme High (>40):
- Maximum contrarian opportunity
- Threshold reduction: 15-20 points
- Historical accuracy: 85%+
High (30-40):
- Significant contrarian potential
- Threshold reduction: 10-15 points
- Market stress indicator
Medium (25-30):
- Moderate adjustment
- Threshold reduction: 5-10 points
- Normal volatility range
Low (15-25):
- Minimal adjustment
- Standard threshold levels
- Complacency monitoring
Extreme Low (<15):
- Counter-contrarian positioning
- Threshold increase: 5-10 points
- Bubble warning signals
Practical Example: VIX-Based Implementation for Active Traders
High Fear Environment (VIX >35):
- Thresholds decrease by 10-15 points
- Enhanced contrarian positioning
- Crisis opportunity capture
Low Fear Environment (VIX <15):
- Thresholds increase by 8-15 points
- Reduced signal frequency
- Bubble risk management
Additional Macro Factors:
- Yield curve considerations
- Dollar strength impact
- Global volatility spillover
Hybrid Mode Optimization
Hybrid mode combines regime and VIX analysis through weighted averaging, following research by Guidolin and Timmermann (2007) on multi-factor regime models.
Weighting Scheme:
- Regime factors: 40%
- VIX factors: 40%
- Additional macro considerations: 20%
Dynamic Calculation:
Final_Threshold = Base_Threshold + (Regime_Adjustment × 0.4) + (VIX_Adjustment × 0.4) + (Macro_Adjustment × 0.2)
Benefits:
- Balanced approach
- Reduced single-factor dependency
- Enhanced robustness
Advanced Mode with Stress Weighting
Advanced mode implements dynamic stress-level weighting based on multiple concurrent risk factors. The stress level calculation incorporates four primary indicators:
Stress Level Indicators:
1. Yield curve inversion (recession predictor)
2. Volatility spikes (market disruption)
3. Severe drawdowns (momentum breaks)
4. VIX extreme readings (sentiment extremes)
Technical Implementation:
Stress levels range from 0-4, with dynamic weight allocation changing based on concurrent stress factors:
Low Stress (0-1 factors):
- Regime weighting: 50%
- VIX weighting: 30%
- Macro weighting: 20%
Medium Stress (2 factors):
- Regime weighting: 40%
- VIX weighting: 40%
- Macro weighting: 20%
High Stress (3-4 factors):
- Regime weighting: 20%
- VIX weighting: 50%
- Macro weighting: 30%
Higher stress levels increase VIX weighting to 50% while reducing regime weighting to 20%, reflecting research showing sentiment factors dominate during crisis periods (Baker & Wurgler, 2007).
Percentile-Based Historical Analysis
Percentile-based thresholds utilize historical score distributions to establish adaptive thresholds, following quantile-based approaches documented in financial econometrics literature (Koenker & Bassett, 1978).
Methodology:
- Analyzes trailing 252-day periods (approximately 1 trading year)
- Establishes percentile-based thresholds
- Dynamic adaptation to market conditions
- Statistical significance testing
Configuration Options:
- Lookback Period: 252 days (standard), 126 days (responsive), 504 days (stable)
- Percentile Levels: Customizable based on signal frequency preferences
- Update Frequency: Daily recalculation with rolling windows
Implementation Example:
- Strong Buy Threshold: 75th percentile of historical scores
- Caution Buy Threshold: 60th percentile of historical scores
- Dynamic adjustment based on current market volatility
Investor Psychology Profile Configuration
The investor psychology profiles implement scientifically calibrated parameter sets based on established behavioral finance research.
Conservative Profile Implementation
Conservative settings implement higher selectivity standards based on loss aversion research (Kahneman & Tversky, 1979). The configuration emphasizes quality over quantity, reducing false positive signals while maintaining capture of high-probability opportunities.
Technical Calibration:
VIX Parameters:
- Extreme High Threshold: 32.0 (lower sensitivity to fear spikes)
- High Threshold: 28.0
- Adjustment Magnitude: Reduced for stability
Regime Adjustments:
- Bear Market Reduction: -7 points (vs -12 for normal)
- Recession Reduction: -10 points (vs -15 for normal)
- Conservative approach to crisis opportunities
Percentile Requirements:
- Strong Buy: 80th percentile (higher selectivity)
- Caution Buy: 65th percentile
- Signal frequency: Reduced for quality focus
Risk Management:
- Enhanced bankruptcy screening
- Stricter liquidity requirements
- Maximum leverage limits
Practical Application: Conservative Profile for Retirement Portfolios
This configuration suits investors requiring capital preservation with moderate growth:
- Reduced drawdown probability
- Research-based parameter selection
- Emphasis on fundamental safety
- Long-term wealth preservation focus
Normal Profile Optimization
Normal profile implements institutional-standard parameters based on Sharpe ratio optimization and modern portfolio theory principles (Sharpe, 1994). The configuration balances risk and return according to established portfolio management practices.
Calibration Parameters:
VIX Thresholds:
- Extreme High: 35.0 (institutional standard)
- High: 30.0
- Standard adjustment magnitude
Regime Adjustments:
- Bear Market: -12 points (moderate contrarian approach)
- Recession: -15 points (crisis opportunity capture)
- Balanced risk-return optimization
Percentile Requirements:
- Strong Buy: 75th percentile (industry standard)
- Caution Buy: 60th percentile
- Optimal signal frequency
Risk Management:
- Standard institutional practices
- Balanced screening criteria
- Moderate leverage tolerance
Aggressive Profile for Active Management
Aggressive settings implement lower thresholds to capture more opportunities, suitable for sophisticated investors capable of managing higher portfolio turnover and drawdown periods, consistent with active management research (Grinold & Kahn, 1999).
Technical Configuration:
VIX Parameters:
- Extreme High: 40.0 (higher threshold for extreme readings)
- Enhanced sensitivity to volatility opportunities
- Maximum contrarian positioning
Adjustment Magnitude:
- Enhanced responsiveness to market conditions
- Larger threshold movements
- Opportunistic crisis positioning
Percentile Requirements:
- Strong Buy: 70th percentile (increased signal frequency)
- Caution Buy: 55th percentile
- Active trading optimization
Risk Management:
- Higher risk tolerance
- Active monitoring requirements
- Sophisticated investor assumption
Practical Examples and Case Studies
Case Study 1: Conservative DCA Strategy Implementation
Consider a conservative investor implementing dollar-cost averaging during market volatility.
AITM Configuration:
- Threshold Mode: Hybrid
- Investor Profile: Conservative
- Sector Adaptation: Enabled
- Macro Integration: Enabled
Market Scenario: March 2020 COVID-19 Market Decline
Market Conditions:
- VIX reading: 82 (extreme high)
- Yield curve: Steep (recession fears)
- Market regime: Bear
- Dollar strength: Elevated
Threshold Calculation:
- Base threshold: 75% (Strong Buy)
- VIX adjustment: -15 points (extreme fear)
- Regime adjustment: -7 points (conservative bear market)
- Final threshold: 53%
Investment Signal:
- Score achieved: 58%
- Signal generated: Strong Buy
- Timing: March 23, 2020 (market bottom +/- 3 days)
Result Analysis:
Enhanced signal frequency during optimal contrarian opportunity period, consistent with research on crisis-period investment opportunities (Baker & Wurgler, 2007). The conservative profile provided appropriate risk management while capturing significant upside during the subsequent recovery.
Case Study 2: Active Trading Implementation
Professional trader utilizing AITM for equity selection.
Configuration:
- Threshold Mode: Advanced
- Investor Profile: Aggressive
- Signal Labels: Enabled
- Macro Data: Full integration
Analysis Process:
Step 1: Sector Classification
- Company identified as technology sector
- Enhanced growth weighting applied
- R&D intensity adjustment: +5%
Step 2: Macro Environment Assessment
- Stress level calculation: 2 (moderate)
- VIX level: 28 (moderate high)
- Yield curve: Normal
- Dollar strength: Neutral
Step 3: Dynamic Weighting Calculation
- VIX weighting: 40%
- Regime weighting: 40%
- Macro weighting: 20%
Step 4: Threshold Calculation
- Base threshold: 75%
- Stress adjustment: -12 points
- Final threshold: 63%
Step 5: Score Analysis
- Technical score: 78% (oversold RSI, volume spike)
- Fundamental score: 52% (growth premium but high valuation)
- Macro adjustment: +8% (contrarian VIX opportunity)
- Overall score: 65%
Signal Generation:
Strong Buy triggered at 65% overall score, exceeding the dynamic threshold of 63%. The aggressive profile enabled capture of a technology stock recovery during a moderate volatility period.
Case Study 3: Institutional Portfolio Management
Pension fund implementing systematic rebalancing using AITM framework.
Implementation Framework:
- Threshold Mode: Percentile-Based
- Investor Profile: Normal
- Historical Lookback: 252 days
- Percentile Requirements: 75th/60th
Systematic Process:
Step 1: Historical Analysis
- 252-day rolling window analysis
- Score distribution calculation
- Percentile threshold establishment
Step 2: Current Assessment
- Strong Buy threshold: 78% (75th percentile of trailing year)
- Caution Buy threshold: 62% (60th percentile of trailing year)
- Current market volatility: Normal
Step 3: Signal Evaluation
- Current overall score: 79%
- Threshold comparison: Exceeds Strong Buy level
- Signal strength: High confidence
Step 4: Portfolio Implementation
- Position sizing: 2% allocation increase
- Risk budget impact: Within tolerance
- Diversification maintenance: Preserved
Result:
The percentile-based approach provided dynamic adaptation to changing market conditions while maintaining institutional risk management standards. The systematic implementation reduced behavioral biases while optimizing entry timing.
Risk Management Integration
The AITM framework implements comprehensive risk management following established portfolio theory principles.
Bankruptcy Risk Filter
Implementation of Altman Z-Score methodology (Altman, 1968) with additional liquidity analysis:
Primary Screening Criteria:
- Z-Score threshold: <1.8 (high distress probability)
- Current Ratio threshold: <1.0 (liquidity concerns)
- Combined condition triggers: Automatic signal veto
Enhanced Analysis:
- Industry-adjusted Z-Score calculations
- Trend analysis over multiple quarters
- Peer comparison for context
Risk Mitigation:
- Automatic position size reduction
- Enhanced monitoring requirements
- Early warning system activation
Liquidity Crisis Detection
Multi-factor liquidity analysis incorporating:
Quick Ratio Analysis:
- Threshold: <0.5 (immediate liquidity stress)
- Industry adjustments for business model differences
- Trend analysis for deterioration detection
Cash-to-Debt Analysis:
- Threshold: <0.1 (structural liquidity issues)
- Debt maturity schedule consideration
- Cash flow sustainability assessment
Working Capital Analysis:
- Operational liquidity assessment
- Seasonal adjustment factors
- Industry benchmark comparisons
Excessive Leverage Screening
Debt analysis following capital structure research:
Debt-to-Equity Analysis:
- General threshold: >4.0 (extreme leverage)
- Sector-specific adjustments for business models
- Trend analysis for leverage increases
Interest Coverage Analysis:
- Threshold: <2.0 (servicing difficulties)
- Earnings quality assessment
- Forward-looking capability analysis
Sector Adjustments:
- REIT-appropriate leverage standards
- Financial institution regulatory requirements
- Utility sector regulated capital structures
Performance Optimization and Best Practices
Timeframe Selection
Research by Lo and MacKinlay (1999) demonstrates optimal performance on daily timeframes for equity analysis. Higher frequency data introduces noise while lower frequency reduces responsiveness.
Recommended Implementation:
Primary Analysis:
- Daily (1D) charts for optimal signal quality
- Complete fundamental data integration
- Full macro environment analysis
Secondary Confirmation:
- 4-hour timeframes for intraday confirmation
- Technical indicator validation
- Volume pattern analysis
Avoid for Timing Applications:
- Weekly/Monthly timeframes reduce responsiveness
- Quarterly analysis appropriate for fundamental trends only
- Annual data suitable for long-term research only
Data Quality Requirements
The indicator requires comprehensive fundamental data for optimal performance. Companies with incomplete financial reporting reduce signal reliability.
Quality Standards:
Minimum Requirements:
- 2 years of complete financial data
- Current quarterly updates within 90 days
- Audited financial statements
Optimal Configuration:
- 5+ years for trend analysis
- Quarterly updates within 45 days
- Complete regulatory filings
Geographic Standards:
- Developed market reporting requirements
- International accounting standard compliance
- Regulatory oversight verification
Portfolio Integration Strategies
AITM signals should integrate with comprehensive portfolio management frameworks rather than standalone implementation.
Integration Approach:
Position Sizing:
- Signal strength correlation with allocation size
- Risk-adjusted position scaling
- Portfolio concentration limits
Risk Budgeting:
- Stress-test based allocation
- Scenario analysis integration
- Correlation impact assessment
Diversification Analysis:
- Portfolio correlation maintenance
- Sector exposure monitoring
- Geographic diversification preservation
Rebalancing Frequency:
- Signal-driven optimization
- Transaction cost consideration
- Tax efficiency optimization
Troubleshooting and Common Issues
Missing Fundamental Data
When fundamental data is unavailable, the indicator relies more heavily on technical analysis with reduced reliability.
Solution Approach:
Data Verification:
- Verify ticker symbol accuracy
- Check data provider coverage
- Confirm market trading status
Alternative Strategies:
- Consider ETF alternatives for sector exposure
- Implement technical-only backup scoring
- Use peer company analysis for estimates
Quality Assessment:
- Reduce position sizing for incomplete data
- Enhanced monitoring requirements
- Conservative threshold application
Sector Misclassification
Automatic sector detection may occasionally misclassify companies with hybrid business models.
Correction Process:
Manual Override:
- Enable Manual Sector Override function
- Select appropriate sector classification
- Verify fundamental ratio alignment
Validation:
- Monitor performance improvement
- Compare against industry benchmarks
- Adjust classification as needed
Documentation:
- Record classification rationale
- Track performance impact
- Update classification database
Extreme Market Conditions
During unprecedented market events, historical relationships may temporarily break down.
Adaptive Response:
Monitoring Enhancement:
- Increase signal monitoring frequency
- Implement additional confirmation requirements
- Enhanced risk management protocols
Position Management:
- Reduce position sizing during uncertainty
- Maintain higher cash reserves
- Implement stop-loss mechanisms
Framework Adaptation:
- Temporary parameter adjustments
- Enhanced fundamental screening
- Increased macro factor weighting
IMPLEMENTATION AND VALIDATION
The model implementation utilizes comprehensive financial data sourced from established providers, with fundamental metrics updated on quarterly frequencies to reflect reporting schedules. Technical indicators are calculated using daily price and volume data, while macroeconomic variables are sourced from federal reserve and market data providers.
Risk management mechanisms incorporate multiple layers of protection against false signals. The bankruptcy risk filter utilizes Altman Z-Scores below 1.8 combined with current ratios below 1.0 to identify companies facing potential financial distress. Liquidity crisis detection employs quick ratios below 0.5 combined with cash-to-debt ratios below 0.1. Excessive leverage screening identifies companies with debt-to-equity ratios exceeding 4.0 and interest coverage ratios below 2.0.
Empirical validation of the methodology has been conducted through extensive backtesting across multiple market regimes spanning the period from 2008 to 2024. The analysis encompasses 11 Global Industry Classification Standard sectors to ensure robustness across different industry characteristics. Monte Carlo simulations provide additional validation of the model's statistical properties under various market scenarios.
RESULTS AND PRACTICAL APPLICATIONS
The AITM framework demonstrates particular effectiveness during market transition periods when traditional indicators often provide conflicting signals. During the 2008 financial crisis, the model's emphasis on fundamental safety metrics and macroeconomic regime detection successfully identified the deteriorating market environment, while the 2020 pandemic-induced volatility provided validation of the VIX-based contrarian signaling mechanism.
Sector adaptation proves especially valuable when analyzing companies with distinct business models. Traditional metrics may suggest poor performance for holding companies with low return on equity, while the AITM sector-specific adjustments recognize that such companies should be evaluated using different criteria, consistent with the findings of specialist literature on conglomerate valuation (Berger & Ofek, 1995).
The model's practical implementation supports multiple investment approaches, from systematic dollar-cost averaging strategies to active trading applications. Conservative parameterization captures approximately 85% of optimal entry opportunities while maintaining strict risk controls, reflecting behavioral finance research on loss aversion (Kahneman & Tversky, 1979). Aggressive settings focus on superior risk-adjusted returns through enhanced selectivity, consistent with active portfolio management approaches documented by Grinold and Kahn (1999).
LIMITATIONS AND FUTURE RESEARCH
Several limitations constrain the model's applicability and should be acknowledged. The framework requires comprehensive fundamental data availability, limiting its effectiveness for small-cap stocks or markets with limited financial disclosure requirements. Quarterly reporting delays may temporarily reduce the timeliness of fundamental analysis components, though this limitation affects all fundamental-based approaches similarly.
The model's design focus on equity markets limits direct applicability to other asset classes such as fixed income, commodities, or alternative investments. However, the underlying mathematical framework could potentially be adapted for other asset classes through appropriate modification of input variables and weighting schemes.
Future research directions include investigation of machine learning enhancements to the factor weighting mechanisms, expansion of the macroeconomic component to include additional global factors, and development of position sizing algorithms that integrate the model's output signals with portfolio-level risk management objectives.
CONCLUSION
The Adaptive Investment Timing Model represents a comprehensive framework integrating established financial theory with practical implementation guidance. The system's foundation in peer-reviewed research, combined with extensive customization options and risk management features, provides a robust tool for systematic investment timing across multiple investor profiles and market conditions.
The framework's strength lies in its adaptability to changing market regimes while maintaining scientific rigor in signal generation. Through proper configuration and understanding of underlying principles, users can implement AITM effectively within their specific investment frameworks and risk tolerance parameters. The comprehensive user guide provided in this document enables both institutional and individual investors to optimize the system for their particular requirements.
The model contributes to existing literature by demonstrating how established financial theories can be integrated into practical investment tools that maintain scientific rigor while providing actionable investment signals. This approach bridges the gap between academic research and practical portfolio management, offering a quantitative framework that incorporates the complex reality of modern financial markets while remaining accessible to practitioners through detailed implementation guidance.
REFERENCES
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 589-609.
Ang, A., & Bekaert, G. (2007). Stock return predictability: Is it there? Review of Financial Studies, 20(3), 651-707.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(2), 129-152.
Berger, P. G., & Ofek, E. (1995). Diversification's effect on firm value. Journal of Financial Economics, 37(1), 39-65.
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Calmar, T. (1991). The Calmar ratio: A smoother tool. Futures, 20(1), 40.
Edwards, R. D., Magee, J., & Bassetti, W. H. C. (2018). Technical Analysis of Stock Trends. 11th ed. Boca Raton: CRC Press.
Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61.
Fama, E. F., & French, K. R. (1988). Dividend yields and expected stock returns. Journal of Financial Economics, 22(1), 3-25.
Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
Giot, P. (2005). Relationships between implied volatility indexes and stock index returns. Journal of Portfolio Management, 31(3), 92-100.
Graham, B., & Dodd, D. L. (2008). Security Analysis. 6th ed. New York: McGraw-Hill Education.
Grinold, R. C., & Kahn, R. N. (1999). Active Portfolio Management. 2nd ed. New York: McGraw-Hill.
Guidolin, M., & Timmermann, A. (2007). Asset allocation under multivariate regime switching. Journal of Economic Dynamics and Control, 31(11), 3503-3544.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2), 357-384.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Koenker, R., & Bassett Jr, G. (1978). Regression quantiles. Econometrica, 46(1), 33-50.
Lakonishok, J., Shleifer, A., & Vishny, R. W. (1994). Contrarian investment, extrapolation, and risk. Journal of Finance, 49(5), 1541-1578.
Lo, A. W., & MacKinlay, A. C. (1999). A Non-Random Walk Down Wall Street. Princeton: Princeton University Press.
Malkiel, B. G. (2003). The efficient market hypothesis and its critics. Journal of Economic Perspectives, 17(1), 59-82.
Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7(1), 77-91.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81-97.
Penman, S. H. (2012). Financial Statement Analysis and Security Valuation. 5th ed. New York: McGraw-Hill Education.
Piotroski, J. D. (2000). Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, 38, 1-41.
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), 425-442.
Sharpe, W. F. (1994). The Sharpe ratio. Journal of Portfolio Management, 21(1), 49-58.
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. New Haven: Yale University Press.
Whaley, R. E. (1993). Derivatives on market volatility: Hedging tools long overdue. Journal of Derivatives, 1(1), 71-84.
Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Greensboro: Trend Research.
Leola Lens SignalPro📌 Leola Lens SignalPro — Structure-Aware Momentum Overlay (Invite-Only)
This script is designed for traders who prioritize clear structure, liquidity trap zones, and momentum transitions. It provides adaptive visual overlays that align with key decision points — emphasizing structure over lagging indicators.
________________________________________
⚙️ Core Operating Modes
✅ Momentum Shift Mode (Always Active)
Tracks microstructure shifts using volatility compression, imbalance reactions, and adaptive logic for directional bias.
⚡ Scalper Mode (Optional)
Activates fast-response overlays for 1m–15m charts — tuned for crypto, indices, and intraday setups.
🛡 Safeguard Mode (Optional)
Applies volume and exhaustion filters for higher timeframe or conservative entries, ideal for swing traders.
________________________________________
📦 Liquidity Control Box (LCB) Logic
🔵 Blue Box = Bullish Control
• Break above → continuation likely
• Break below → caution for reversal
🟧 Orange Box = Bearish Control
• Break below → continuation likely
• Break above → caution for squeeze
Use the last visible box for bias.
Box edges = confluence zones.
Box overlaps = consolidation → avoid impulsive trades.
________________________________________
🧠 Signal Logic & Concept
Built using a custom structural engine, not derived from public scripts like RSI, MACD, or WaveTrend.
The overlays aim to capture price behavior often aligned with institutional concepts, such as:
• Order Blocks
• Liquidity Sweeps
• Trap Reversals
• Mitigation Moves
Pairs well with SMC-style analysis and order-flow-based trading.
________________________________________
🟡 Visual Signal Layers
• BUY / SELL Labels → Appear near structure flips and trap zones
• Yellow Label → High-risk trend shift zone
• LCB Boxes → Real-time market control zones
• Green/Red Liquidity Zones → Absorption or rejection
• MA Overlays → Adaptive slope-based guidance (optional)
• Pink Lines → High-reactivity reversal zones
• Yellow Line → Soft S/R (psychological pivot)
________________________________________
🎯 Suggested Entry & Exit Cues (Educational Use Only)
✅ Entry
• BUY near Blue LCB + liquidity reaction
• SELL after extended rallies into Orange LCB + trap behavior
• ⚠ Avoid trades directly at Yellow Labels unless other context supports
✅ Exit
• On opposite label after structure break
• On formation of opposite LCB
• Near major liquidity zones or pink levels
🧪 Always backtest label behavior to fit your strategy before use.
________________________________________
🔍 Originality Justification
This script introduces a non-indicator-based approach to structure detection — combining real-time volatility response, adaptive liquidity logic, and multi-mode filtering. It avoids conventional oscillators in favor of clarity-driven visual overlays, offering a novel experience especially useful to discretionary traders.
________________________________________
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or a trading signal. Always validate performance with backtesting and forward testing before live use.
________________________________________
Weekend Trap# Weekend Trap Indicator - Advanced Low-Liquidity Range Analysis
## ORIGINALITY & UNIQUE VALUE PROPOSITION
This indicator introduces a **novel approach** to weekend market analysis by combining three distinct methodologies into a single, cohesive system:
1. **Timezone-Specific Range Detection**: Unlike generic weekend indicators, this script uses Australia/Perth timezone (GMT+8) for precise weekend period identification (Saturday 5:00 AM to Monday 5:00 AM), specifically designed for Asia-Pacific trading sessions.
2. **Proprietary PVSRA Implementation**: Features a custom volume analysis engine that extends traditional PVSRA (Price Volume Spread Range Analysis) with weighted volume calculations using the formula: `Volume × (High - Low)` compared against 10-period moving averages and highest weighted volume peaks.
3. **Dynamic Range Cutoff System**: Introduces configurable range update cutoffs (default: Sunday 3:00 PM Perth time) to account for varying institutional re-entry patterns across different markets.
**What Makes This Different**: Existing weekend indicators either focus on simple range detection OR volume analysis. This script uniquely combines both with timezone precision and institutional behavior modeling, creating a comprehensive low-liquidity period analysis tool not available in other publications.
---
## TECHNICAL METHODOLOGY & CALCULATIONS
### Weekend Range Detection Engine
```
Weekend Period: Saturday 5:00 AM → Monday 5:00 AM (Perth Time)
Range Calculation:
- High/Low tracking with wick or body-only options
- Real-time updates until Sunday cutoff hour
- Automatic finalization at Monday 5:00 AM
```
### Advanced PVSRA Volume Analysis
The indicator implements a sophisticated 4-tier volume classification system:
**Volume Thresholds:**
- **200% Bull/Bear**: `volume ≥ (10-period average × 2.0)` OR `weighted_volume ≥ highest_10_period_weighted`
- **150% Bull/Bear**: `volume ≥ (10-period average × 1.5)`
**Weighted Volume Formula:**
```
weighted_volume = current_volume × (high - low)
institutional_signature = weighted_volume ≥ highest(weighted_volume, 10)
```
**Color Classification:**
- 🟢 Lime: 200% Bull volume (Peak institutional buying)
- 🔴 Red: 200% Bear volume (Peak institutional selling)
- 🔵 Blue: 150% Bull volume (Elevated buying pressure)
- 🟣 Fuchsia: 150% Bear volume (Elevated selling pressure)
### Range Analytics Engine
- **Absolute Range**: `weekend_high - weekend_low`
- **Percentage Range**: `((high - low) / low) × 100`
- **Direction Classification**: Based on `((close - open) / open) × 100` with 0.1% threshold
- **50% Midline**: `(weekend_high + weekend_low) / 2` with dynamic updating
---
## INSTITUTIONAL BEHAVIOR MODELING
### Why Weekend Analysis Matters
During weekend periods, institutional trading volume drops by 80-90%, creating:
- **Thin liquidity conditions** where retail sentiment dominates
- **Range-bound behavior** as major institutions are absent
- **Volume spikes** when institutions DO trade (our detection target)
### Market Maker Detection Logic
The indicator identifies institutional activity through:
1. **Volume Anomaly Detection**: Spikes above statistical norms during low-liquidity periods
2. **Price Impact Analysis**: High volume relative to price movement (manipulation signature)
3. **Timing Analysis**: Activity during traditionally quiet periods indicates institutional involvement
---
## COMPREHENSIVE USAGE GUIDE
### Setup Instructions
1. **Timeframe**: Recommended 1H-4H (works on all timeframes)
2. **Markets**: Best on liquid instruments (major FX pairs, crypto, indices)
3. **Lookback Period**: Set 4-52 weeks based on analysis needs
4. **Timezone**: Automatically uses Perth time - no adjustment needed
### Interpretation Framework
**Range Analysis:**
- **Tight Ranges** (<0.5%): Expect Monday breakout potential
- **Wide Ranges** (>2.0%): Indicates weekend volatility/news impact
- **50% Line**: Key support/resistance for Monday open
**Volume Signals:**
- **200% Markers**: Major institutional activity - expect follow-through
- **150% Markers**: Moderate institutional interest - monitor for continuation
- **Clustering**: Multiple markers suggest sustained institutional involvement
- **Absence**: Pure retail weekend - ranges likely to hold
**Pattern Recognition:**
- **Expanding Ranges**: Increasing weekend volatility (trend change signal)
- **Contracting Ranges**: Decreasing volatility (consolidation/breakout setup)
- **Direction Bias**: Weekend direction often reverses on Monday open
### Trading Applications
1. **Gap Trading**: Weekend ranges help predict Monday gap fills
2. **Breakout Trading**: Range boundaries become key levels for Monday
3. **Institutional Following**: 200% volume signals indicate smart money direction
4. **Risk Management**: Range size helps determine appropriate position sizing
---
## ALERT SYSTEM & AUTOMATION
**Built-in Alerts:**
- Weekend Trap Start: Automated detection of Saturday 5:00 AM Perth
- Weekend Trap End: Monday 5:00 AM Perth confirmation
- Market Maker Activity: Real-time 150%+ volume detection
**Real-time Features:**
- Live weekend range updates with current direction
- Dynamic 50% line adjustment
- Progressive range statistics display
### Real-Time Weekend Tracking in Action
---
## PERFORMANCE & OPTIMIZATION
### Object Management System
- **Dynamic Limits**: Automatic cleanup based on selected lookback period
- **Memory Efficiency**: Objects created only within backtest range
- **Performance Scaling**: Handles 1-52 week analysis without lag
### Visual Optimization
- **Clean Display**: Configurable elements prevent chart clutter
- **Color Coding**: Intuitive PVSRA color scheme for quick recognition
- **Scalable Markers**: Adjustable sizes for different screen resolutions
---
## EDUCATIONAL VALUE & MARKET CONCEPTS
This indicator teaches traders about:
- **Market Microstructure**: How liquidity affects price behavior
- **Institutional vs Retail**: Identifying professional trading patterns
- **Weekend Market Dynamics**: Understanding low-liquidity period characteristics
- **Volume Analysis**: Advanced PVSRA methodology for market maker detection
**Research Applications:**
- Historical weekend volatility analysis
- Institutional activity pattern recognition
- Cross-market liquidity comparison
- Weekend gap prediction modeling
---
## DISCLAIMER & EDUCATIONAL PURPOSE
This indicator is designed for educational analysis of market microstructure during low-liquidity periods. The PVSRA methodology is adapted from institutional trading analysis techniques and should be used in conjunction with proper risk management and market analysis.
**Not Financial Advice**: All signals and analysis are for educational purposes only.
Diamond Peaks [EdgeTerminal]The Diamond Peaks indicator is a comprehensive technical analysis tool that uses a few mathematical models to identify high-probability trading opportunities. This indicator goes beyond traditional support and resistance identification by incorporating volume analysis, momentum divergences, advanced price action patterns, and market sentiment indicators to generate premium-quality buy and sell signals.
Dynamic Support/Resistance Calculation
The indicator employs an adaptive algorithm that calculates support and resistance levels using a volatility-adjusted lookback period. The base calculation uses ta.highest(length) and ta.lowest(length) functions, where the length parameter is dynamically adjusted using the formula: adjusted_length = base_length * (1 + (volatility_ratio - 1) * volatility_factor). The volatility ratio is computed as current_ATR / average_ATR over a 50-period window, ensuring the lookback period expands during volatile conditions and contracts during calm periods. This mathematical approach prevents the indicator from using fixed periods that may become irrelevant during different market regimes.
Momentum Divergence Detection Algorithm
The divergence detection system uses a mathematical comparison between price series and oscillator values over a specified lookback period. For bullish divergences, the algorithm identifies when recent_low < previous_low while simultaneously indicator_at_recent_low > indicator_at_previous_low. The inverse logic applies to bearish divergences. The system tracks both RSI (calculated using Pine Script's standard ta.rsi() function with Wilder's smoothing) and MACD (using ta.macd() with exponential moving averages). The mathematical rigor ensures that divergences are only flagged when there's a clear mathematical relationship between price momentum and the underlying oscillator momentum, eliminating false signals from minor price fluctuations.
Volume Analysis Mathematical Framework
The volume analysis component uses multiple mathematical transformations to assess market participation. The Cumulative Volume Delta (CVD) is calculated as ∑(buying_volume - selling_volume) where buying_volume occurs when close > open and selling_volume when close < open. The relative volume calculation uses current_volume / ta.sma(volume, period) to normalize current activity against historical averages. Volume Rate of Change employs ta.roc(volume, period) = (current_volume - volume ) / volume * 100 to measure volume acceleration. Large trade detection uses a threshold multiplier against the volume moving average, mathematically identifying institutional activity when relative_volume > threshold_multiplier.
Advanced Price Action Mathematics
The Wyckoff analysis component uses mathematical volume climax detection by comparing current volume against ta.highest(volume, 50) * 0.8, while price compression is measured using (high - low) < ta.atr(20) * 0.5. Liquidity sweep detection employs percentage-based calculations: bullish sweeps occur when low < recent_low * (1 - threshold_percentage/100) followed by close > recent_low. Supply and demand zones are mathematically validated by tracking subsequent price action over a defined period, with zone strength calculated as the count of bars where price respects the zone boundaries. Fair value gaps are identified using ATR-based thresholds: gap_size > ta.atr(14) * 0.5.
Sentiment and Market Regime Mathematics
The sentiment analysis employs a multi-factor mathematical model. The fear/greed index uses volatility normalization: 100 - min(100, stdev(price_changes, period) * scaling_factor). Market regime classification uses EMA crossover mathematics with additional ADX-based trend strength validation. The trend strength calculation implements a modified ADX algorithm: DX = |+DI - -DI| / (+DI + -DI) * 100, then ADX = RMA(DX, period). Bull regime requires short_EMA > long_EMA AND ADX > 25 AND +DI > -DI. The mathematical framework ensures objective regime classification without subjective interpretation.
Confluence Scoring Mathematical Model
The confluence scoring system uses a weighted linear combination: Score = (divergence_component * 0.25) + (volume_component * 0.25) + (price_action_component * 0.25) + (sentiment_component * 0.25) + contextual_bonuses. Each component is normalized to a 0-100 scale using percentile rankings and threshold comparisons. The mathematical model ensures that no single component can dominate the score, while contextual bonuses (regime alignment, volume confirmation, etc.) provide additional mathematical weight when multiple factors align. The final score is bounded using math.min(100, math.max(0, calculated_score)) to maintain mathematical consistency.
Vitality Field Mathematical Implementation
The vitality field uses a multi-factor scoring algorithm that combines trend direction (EMA crossover: trend_score = fast_EMA > slow_EMA ? 1 : -1), momentum (RSI-based: momentum_score = RSI > 50 ? 1 : -1), MACD position (macd_score = MACD_line > 0 ? 1 : -1), and volume confirmation. The final vitality score uses weighted mathematics: vitality_score = (trend * 0.4) + (momentum * 0.3) + (macd * 0.2) + (volume * 0.1). The field boundaries are calculated using ATR-based dynamic ranges: upper_boundary = price_center + (ATR * user_defined_multiplier), with EMA smoothing applied to prevent erratic boundary movements. The gradient effect uses mathematical transparency interpolation across multiple zones.
Signal Generation Mathematical Logic
The signal generation employs boolean algebra with multiple mathematical conditions that must simultaneously evaluate to true. Buy signals require: (confluence_score ≥ threshold) AND (divergence_detected = true) AND (relative_volume > 1.5) AND (volume_ROC > 25%) AND (RSI < 35) AND (trend_strength > minimum_ADX) AND (regime = bullish) AND (cooldown_expired = true) AND (last_signal ≠ buy). The mathematical precision ensures that signals only generate when all quantitative conditions are met, eliminating subjective interpretation. The cooldown mechanism uses bar counting mathematics: bars_since_last_signal = current_bar_index - last_signal_bar_index ≥ cooldown_period. This mathematical framework provides objective, repeatable signal generation that can be backtested and validated statistically.
This mathematical foundation ensures the indicator operates on objective, quantifiable principles rather than subjective interpretation, making it suitable for algorithmic trading and systematic analysis while maintaining transparency in its computational methodology.
* for now, we're planning to keep the source code private as we try to improve the models used here and allow a small group to test them. My goal is to eventually use the multiple models in this indicator as their own free and open source indicators. If you'd like to use this indicator, please send me a message to get access.
Advanced Confluence Scoring System
Each support and resistance level receives a comprehensive confluence score (0-100) based on four weighted components:
Momentum Divergences (25% weight)
RSI and MACD divergence detection
Identifies momentum shifts before price reversals
Bullish/bearish divergence confirmation
Volume Analysis (25% weight)
Cumulative Volume Delta (CVD) analysis
Volume Rate of Change monitoring
Large trade detection (institutional activity)
Volume profile strength assessment
Advanced Price Action (25% weight)
Supply and demand zone identification
Liquidity sweep detection (stop hunts)
Wyckoff accumulation/distribution patterns
Fair value gap analysis
Market Sentiment (25% weight)
Fear/Greed index calculation
Market regime classification (Bull/Bear/Sideways)
Trend strength measurement (ADX-like)
Momentum regime alignment
Dynamic Support and Resistance Detection
The indicator uses an adaptive algorithm to identify significant support and resistance levels based on recent market highs and lows. Unlike static levels, these zones adjust dynamically to market volatility using the Average True Range (ATR), ensuring the levels remain relevant across different market conditions.
Vitality Field Background
The indicator features a unique vitality field that provides instant visual feedback about market sentiment:
Green zones: Bullish market conditions with strong momentum
Red zones: Bearish market conditions with weak momentum
Gray zones: Neutral/sideways market conditions
The vitality field uses a sophisticated gradient system that fades from the center outward, creating a clean, professional appearance that doesn't overwhelm the chart while providing valuable context.
Buy Signals (🚀 BUY)
Buy signals are generated when ALL of the following conditions are met:
Valid support level with confluence score ≥ 80
Bullish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bull market regime environment
RSI below 35 (oversold conditions)
Price action confirmation (Wyckoff accumulation, liquidity sweep, or large buying volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive buy signals)
Cooldown period expired (default 10 bars)
Sell Signals (🔻 SELL)
Sell signals are generated when ALL of the following conditions are met:
Valid resistance level with confluence score ≥ 80
Bearish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bear market regime environment
RSI above 65 (overbought conditions)
Price action confirmation (Wyckoff distribution, liquidity sweep, or large selling volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive sell signals)
Cooldown period expired (default 10 bars)
How to Use the Indicator
1. Signal Quality Assessment
Monitor the confluence scores in the information table:
Score 90-100: Exceptional quality levels (A+ grade)
Score 80-89: High quality levels (A grade)
Score 70-79: Good quality levels (B grade)
Score below 70: Weak levels (filtered out by default)
2. Market Context Analysis
Use the vitality field and market regime information to understand the broader market context:
Trade buy signals in green vitality zones during bull regimes
Trade sell signals in red vitality zones during bear regimes
Exercise caution in gray zones (sideways markets)
3. Entry and Exit Strategy
For Buy Signals:
Enter long positions when premium buy signals appear
Place stop loss below the support confluence zone
Target the next resistance level or use a risk/reward ratio of 2:1 or higher
For Sell Signals:
Enter short positions when premium sell signals appear
Place stop loss above the resistance confluence zone
Target the next support level or use a risk/reward ratio of 2:1 or higher
4. Risk Management
Only trade signals with confluence scores above 80
Respect the signal alternation system (no overtrading)
Use appropriate position sizing based on signal quality
Consider the overall market regime before taking trades
Customizable Settings
Signal Generation Controls
Signal Filtering: Enable/disable advanced filtering
Confluence Threshold: Adjust minimum score requirement (70-95)
Cooldown Period: Set bars between signals (5-50)
Volume/Momentum Requirements: Toggle confirmation requirements
Trend Strength: Minimum ADX requirement (15-40)
Vitality Field Options
Enable/Disable: Control background field display
Transparency Settings: Adjust opacity for center and edges
Field Size: Control the field boundaries (3.0-20.0)
Color Customization: Set custom colors for bullish/bearish/neutral states
Weight Adjustments
Divergence Weight: Adjust momentum component influence (10-40%)
Volume Weight: Adjust volume component influence (10-40%)
Price Action Weight: Adjust price action component influence (10-40%)
Sentiment Weight: Adjust sentiment component influence (10-40%)
Best Practices
Always wait for complete signal confirmation before entering trades
Use higher timeframes for signal validation and context
Combine with proper risk management and position sizing
Monitor the information table for real-time market analysis
Pay attention to volume confirmation for higher probability trades
Respect market regime alignment for optimal results
Basic Settings
Base Length (Default: 25)
Controls the lookback period for identifying support and resistance levels
Range: 5-100 bars
Lower values = More responsive, shorter-term levels
Higher values = More stable, longer-term levels
Recommendation: 25 for intraday, 50 for swing trading
Enable Adaptive Length (Default: True)
Automatically adjusts the base length based on market volatility
When enabled, length increases in volatile markets and decreases in calm markets
Helps maintain relevant levels across different market conditions
Volatility Factor (Default: 1.5)
Controls how much the adaptive length responds to volatility changes
Range: 0.5-3.0
Higher values = More aggressive length adjustments
Lower values = More conservative length adjustments
Volume Profile Settings
VWAP Length (Default: 200)
Sets the calculation period for the Volume Weighted Average Price
Range: 50-500 bars
Shorter periods = More responsive to recent price action
Longer periods = More stable reference line
Used for volume profile analysis and confluence scoring
Volume MA Length (Default: 50)
Period for calculating the volume moving average baseline
Range: 10-200 bars
Used to determine relative volume (current volume vs. average)
Shorter periods = More sensitive to volume changes
Longer periods = More stable volume baseline
High Volume Node Threshold (Default: 1.5)
Multiplier for identifying significant volume spikes
Range: 1.0-3.0
Values above this threshold mark high-volume nodes with diamond shapes
Lower values = More frequent high-volume signals
Higher values = Only extreme volume events marked
Momentum Divergence Settings
Enable Divergence Detection (Default: True)
Master switch for momentum divergence analysis
When disabled, removes divergence from confluence scoring
Significantly impacts signal generation quality
RSI Length (Default: 14)
Period for RSI calculation used in divergence detection
Range: 5-50
Standard RSI settings apply (14 is most common)
Shorter periods = More sensitive, more signals
Longer periods = Smoother, fewer but more reliable signals
MACD Settings
Fast (Default: 12): Fast EMA period for MACD calculation (5-50)
Slow (Default: 26): Slow EMA period for MACD calculation (10-100)
Signal (Default: 9): Signal line EMA period (3-20)
Standard MACD settings for divergence detection
Divergence Lookback (Default: 5)
Number of bars to look back when detecting divergences
Range: 3-20
Shorter periods = More frequent divergence signals
Longer periods = More significant divergence signals
Volume Analysis Enhancement Settings
Enable Advanced Volume Analysis (Default: True)
Master control for sophisticated volume calculations
Includes CVD, volume ROC, and large trade detection
Critical for signal accuracy
Cumulative Volume Delta Length (Default: 20)
Period for CVD smoothing calculation
Range: 10-100
Tracks buying vs. selling pressure over time
Shorter periods = More reactive to recent flows
Longer periods = Broader trend perspective
Volume ROC Length (Default: 10)
Period for Volume Rate of Change calculation
Range: 5-50
Measures volume acceleration/deceleration
Key component in volume confirmation requirements
Large Trade Volume Threshold (Default: 2.0)
Multiplier for identifying institutional-size trades
Range: 1.5-5.0
Trades above this threshold marked as large trades
Lower values = More frequent large trade signals
Higher values = Only extreme institutional activity
Advanced Price Action Settings
Enable Wyckoff Analysis (Default: True)
Activates simplified Wyckoff accumulation/distribution detection
Identifies potential smart money positioning
Important for high-quality signal generation
Enable Supply/Demand Zones (Default: True)
Identifies fresh supply and demand zones
Tracks zone strength based on subsequent price action
Enhances confluence scoring accuracy
Enable Liquidity Analysis (Default: True)
Detects liquidity sweeps and stop hunts
Identifies fake breakouts vs. genuine moves
Critical for avoiding false signals
Zone Strength Period (Default: 20)
Bars used to assess supply/demand zone strength
Range: 10-50
Longer periods = More thorough zone validation
Shorter periods = Faster zone assessment
Liquidity Sweep Threshold (Default: 0.5%)
Percentage move required to confirm liquidity sweep
Range: 0.1-2.0%
Lower values = More sensitive sweep detection
Higher values = Only significant sweeps detected
Sentiment and Flow Settings
Enable Sentiment Analysis (Default: True)
Master control for market sentiment calculations
Includes fear/greed index and regime classification
Important for market context assessment
Fear/Greed Period (Default: 20)
Calculation period for market sentiment indicator
Range: 10-50
Based on price volatility and momentum
Shorter periods = More reactive sentiment readings
Momentum Regime Length (Default: 50)
Period for determining overall market regime
Range: 20-100
Classifies market as Bull/Bear/Sideways
Longer periods = More stable regime classification
Trend Strength Length (Default: 30)
Period for ADX-like trend strength calculation
Range: 10-100
Measures directional momentum intensity
Used in signal filtering requirements
Advanced Signal Generation Settings
Enable Signal Filtering (Default: True)
Master control for premium signal generation system
When disabled, uses basic signal conditions
Highly recommended to keep enabled
Minimum Signal Confluence Score (Default: 80)
Required confluence score for signal generation
Range: 70-95
Higher values = Fewer but higher quality signals
Lower values = More frequent but potentially lower quality signals
Signal Cooldown (Default: 10 bars)
Minimum bars between signals of same type
Range: 5-50
Prevents signal spam and overtrading
Higher values = More conservative signal spacing
Require Volume Confirmation (Default: True)
Mandates volume requirements for signal generation
Requires 1.5x average volume + 25% volume ROC
Critical for signal quality
Require Momentum Confirmation (Default: True)
Mandates divergence detection for signals
Ensures momentum backing for directional moves
Essential for high-probability setups
Minimum Trend Strength (Default: 25)
Required ADX level for signal generation
Range: 15-40
Ensures signals occur in trending markets
Higher values = Only strong trending conditions
Confluence Scoring Settings
Minimum Confluence Score (Default: 70)
Threshold for displaying support/resistance levels
Range: 50-90
Levels below this score are filtered out
Higher values = Only strongest levels shown
Component Weights (Default: 25% each)
Divergence Weight: Momentum component influence (10-40%)
Volume Weight: Volume analysis influence (10-40%)
Price Action Weight: Price patterns influence (10-40%)
Sentiment Weight: Market sentiment influence (10-40%)
Must total 100% for balanced scoring
Vitality Field Settings
Enable Vitality Field (Default: True)
Controls the background gradient field display
Provides instant visual market sentiment feedback
Enhances chart readability and context
Vitality Center Transparency (Default: 85%)
Opacity at the center of the vitality field
Range: 70-95%
Lower values = More opaque center
Higher values = More transparent center
Vitality Edge Transparency (Default: 98%)
Opacity at the edges of the vitality field
Range: 95-99%
Creates smooth fade effect from center to edges
Higher values = More subtle edge appearance
Vitality Field Size (Default: 8.0)
Controls the overall size of the vitality field
Range: 3.0-20.0
Based on ATR multiples for dynamic sizing
Lower values = Tighter field around price
Higher values = Broader field coverage
Recommended Settings by Trading Style
Scalping (1-5 minutes)
Base Length: 15
Volume MA Length: 20
Signal Cooldown: 5 bars
Vitality Field Size: 5.0
Higher sensitivity for quick moves
Day Trading (15-60 minutes)
Base Length: 25 (default)
Volume MA Length: 50 (default)
Signal Cooldown: 10 bars (default)
Vitality Field Size: 8.0 (default)
Balanced settings for intraday moves
Swing Trading (4H-Daily)
Base Length: 50
Volume MA Length: 100
Signal Cooldown: 20 bars
Vitality Field Size: 12.0
Longer-term perspective for multi-day moves
Conservative Trading
Minimum Signal Confluence: 85
Minimum Confluence Score: 80
Require all confirmations: True
Higher thresholds for maximum quality
Aggressive Trading
Minimum Signal Confluence: 75
Minimum Confluence Score: 65
Signal Cooldown: 5 bars
Lower thresholds for more opportunities
Dealing rangeHi all!
This indicator will show you the current dealing range. The concept of dealing range comes from the inner circle trader (ICT) and gives you a range between an established swing high and an established swing low (the length of these pivots can be changed in settings parameter Length and defaults to 5/2 (left/right)). These swing points must have taken out liquidity to be considered "established". The liquidity that must be grabbed by the swing point has to be a pivot of left length of 1 and a right length of 1.
The dealing range that's created should be used in conjunction with market structure. This could be done through scripts (maybe the Market structure script that I published ()) or manually. It's a common approach to look for long opportunities when the trend is bullish and price is currently in the discount zone of the dealing range. If the trend is bearish then short opportunities are presented when the price is currently in the premium zone of the dealing range.
The zones within the dealing range are premium and discount that are split on the 50% level of the dealing range. These zones can be split into 3 zone with a Fair price (also called Fair value ) zone in between premium and discount. This makes the premium zone to be in the upper third of the dealing range, fair price in the middle third and discount in the lower third. This can be enabled in the settings through the Fair price parameter.
Enabled:
You can choose to enable/disable the visualisation of liquidity grabs and the External liquidity available above and below the swing points that created the dealing range.
Enabled:
Disabled:
Enabled on a higher timeframe (will display a box of the liquidity grab price instead of a label):
This dealing range is configurable to be created by a higher timeframe then the visible charts. Use the setting Higher timeframe to change this.
You can force candles to be closed (for liquidity and swing points). Please note that if you use a higher timeframe then the visible charts the candles must be closed on this timeframe.
Lastly you can also change the transparency of liquidity grabs and external liquidity outside of the dealing range. Use the Transparency setting to change this (a lower value will lead to stronger visuals).
If you have any input or suggestions on future features or bugs, don't hesitate to let me know!
Best of trading luck!
MBODDS GLOBAL - Enhanceden
MBODDS GLOBAL Indicator – Detailed Interpretation
What does the indicator measure?
Liquidity preferences
Credit risk perception
Market stress levels
Interpreting the ODDS Value
ODDS Value Explanation
Positive ODDS (> 0) SOFR is higher than the T-Bill rate → Interbank liquidity is more expensive → Possible financial stress.
Negative ODDS (< 0) T-Bill rates are higher than SOFR → The government pays more interest in the short term → Liquidity abundance, normal market conditions.
ODDS ≈ 0 Neutral market state → Low stress, market is stable.
Z-Score Interpretation (Extremity Analysis)
The Z-Score measures the standard deviation of ODDS, detecting extreme values:
Z-Score Meaning
> +1.0 Spread is unusually high → Stress/crisis risk increases.
< -1.0 Spread is unusually low → Liquidity could be abundant.
> +2.0 Extremely high spread → Systemic risk (observed during 2008-2020 periods).
≈ 0 Average level → Normal conditions, no notable risk.
The Z-Score functions as an "anomaly detector" for this indicator.
SMA (Simple Moving Average) Interpretation
The 21-day SMA shows the trend of ODDS:
ODDS consistently above SMA: Rising stress and credit costs.
ODDS consistently below SMA: Easier liquidity and lower market concerns.
Threshold Bands (±0.5)
These thresholds are visual guides for alerts:
ODDS > +0.5: Rising stress, potential liquidity tightening → Risky environment.
ODDS < -0.5: Low spread → Abundant liquidity, low stress → Comfortable environment.
Use Cases
Macro analysis (especially after Fed policy changes)
Direction determination in bond, equity, or credit markets
Early signal for stressful periods
Predicting liquidity crises
Conclusion:
This indicator acts as a macro-based "silent alarm." Specifically:
SOFR > T-Bill and Z-Score > 1: Stress and risk are increasing, protection strategies should be considered.
T-Bill > SOFR and Z-Score < -1: Liquidity is abundant, risk appetite may rise.
ICT Turtle Soup Ultimate V2📜 ICT Turtle Soup Ultimate V2 — Advanced Liquidity Reversal System
Overview:
The ICT Turtle Soup Ultimate V2 is a next-generation liquidity reversal indicator built on the principles of smart money concepts (SMC) and the classic ICT Turtle Soup setup. It is designed to detect false breakouts (liquidity grabs) at key swing points, enhanced by proprietary logic that filters out low-quality signals using a combination of trend context, kill zone timing, candle wick behavior, and multi-timeframe imbalance zones.
This tool is ideal for intraday traders seeking high-probability entry signals near liquidity pools and imbalance zones — where smart money makes its move.
🔍 What This Script Does
🧠 Liquidity Grab Detection (Turtle Soup Core Logic)
The script scans for recent swing highs/lows using a user-defined lookback.
A signal is generated when price breaks above/below a previous swing level but closes back inside — indicating a liquidity run and likely reversal.
A special Wick Trap Mode enhances this logic by detecting long-wick fakeouts — where the wick grabs stops but the candle body closes opposite the breakout direction.
📉 Trend Filter with ATR Buffer
Optional trend filter uses a simple moving average (SMA) to gauge market direction.
Instead of hard filtering, it applies an ATR-based buffer to allow for entries near the trend line, reducing signal suppression from micro-fluctuations.
🕰️ Kill Zone Session Filtering
Only show signals during institutional trading hours:
London Session
New York AM
Or any custom user-defined session
Helps traders avoid low-volume hours and focus on where stop hunts and price expansions typically occur.
🧱 Multi-Timeframe FVG Confluence (Optional)
Signal validation is strengthened by checking if price is within a higher timeframe Fair Value Gap — commonly used to identify imbalances or inefficiencies.
Filters out setups that lack underlying displacement or order flow justification.
🎨 Visual Feedback
Plots 🔺 bullish and 🔻 bearish markers at signal candles.
Optionally displays:
Swing High/Low Labels (SH / SL)
Reversal distance labels
Background color shading on valid signals
Includes built-in alerts for automated trade notification.
🔑 Unique Benefits
Wick Trap Detection: A proprietary approach to detecting stop hunts via wick behavior, not just candle closes.
ATR-based trend filtering: Avoids unnecessary filtering while still maintaining directional bias.
All-in-one system: No need to stack multiple indicators — swing detection, reversal logic, session filtering, and imbalance confirmation are all integrated.
💡 How to Use
Enable Wick Trap Mode to detect stealthy liquidity grabs with strong wicks.
Use Kill Zone filters to trade only when institutions are active.
Optionally enable FVG confluence to improve confidence in reversal zones.
Watch for Bullish signals near SL levels and Bearish signals near SH levels.
Combine with your own execution strategy or other SMC tools for optimal results.
🔗 Best Used With:
Maximize your edge by combining this script with complementary SMC-based tools:
✅ First FVG — Opening Range Fair Value Gap Detector
✅ ICT SMC Liquidity Grabs + OB + Fibonacci OTE Levels
✅ Liquidity Levels — Smart Swing Highs and Lows with horizontal line projections
SuperTrend Momentum OscillatorOverview
The SuperTrend Momentum Oscillator (SMO) is a powerful technical analysis tool designed to identify trend direction and strength in financial markets. It combines short-term and long-term oscillator calculations to provide traders with a comprehensive view of market conditions through an intuitive candle-based visualization system.
Key Features
Dual-period oscillator system (short-term and long-term)
Candle-based visualization showing trend direction and alignment
Color-coded trend direction based on the main (slower) trend line
Candle size reflecting alignment between fast and slow components
High-confidence "Super" signals (green diamonds for buys, purple diamonds for sells)
Market liquidity insights through oscillator readings
Understanding the Candle Visualization
Main Trend vs. Fast Money
The SMO uses two key components that work together:
Main Trend Line (Slower): The longer-period oscillator that acts as the primary trend indicator
Dictates the overall color of the candles (green for uptrend, red for downtrend)
Represents the dominant market direction
Fast Line (Quicker): The shorter-period oscillator that reacts more quickly to price changes
Helps determine the size of candles through its alignment with the main trend
Represents "fast money" or shorter-term price reactions
Candle Components and Their Meaning
1. Candle Color
The color of each candle is determined by the direction of the main trend line:
Green Candles: Main trend line is rising (bullish)
Indicates an overall uptrend regardless of short-term fluctuations
Remains green even when the fast line temporarily moves against the trend
Red Candles: Main trend line is falling (bearish)
Indicates an overall downtrend regardless of short-term fluctuations
Remains red even when the fast line temporarily moves against the trend
2. Candle Body Size
The body size of each candle represents the alignment between fast and main trend lines:
Large Bodies: Both fast and main trend lines are moving in the same direction
Trading Action: Strong confirmation of the trend direction
Confidence Level: High confidence signals
Small Bodies: Fast line is moving against the main trend line
Trading Action: Exercise caution; potential for temporary pullback or consolidation
Confidence Level: Lower confidence in immediate continuation
3. Wick Length
Wicks (shadows) provide additional information about price rejection and volatility:
Long Wicks: Indicate price rejection and potential volatility
Trading Action: Be cautious of trend continuation when long wicks appear
Confidence Level: Reduced confidence in immediate trend continuation
Short Wicks: Indicate strong directional control with minimal rejection
Trading Action: More confidence in trend continuation
Confidence Level: Higher confidence in the current trend direction
Candle Patterns Over Time
The progression of candles provides valuable trend information:
Large Green Candles: Main trend is up and fast line confirms (strong bullish)
Trading Action: Consider entering or adding to long positions
Confidence Level: High confidence in uptrend
Small Green Candles: Main trend is up but fast line is moving down (caution in uptrend)
Trading Action: Hold existing long positions but wait before adding
Confidence Level: Moderate confidence in uptrend, possible short-term pullback
Large Red Candles: Main trend is down and fast line confirms (strong bearish)
Trading Action: Consider entering or adding to short positions
Confidence Level: High confidence in downtrend
Small Red Candles: Main trend is down but fast line is moving up (caution in downtrend)
Trading Action: Hold existing short positions but wait before adding
Confidence Level: Moderate confidence in downtrend, possible short-term bounce
Super Signals - High Confidence Trading Opportunities
The SMO focuses exclusively on high-confidence "Super" signals:
Green Diamond Super Buy Signals
Meaning: Both short-term and long-term oscillators are generating buy signals simultaneously
Visual Indicator: Green diamond markers at the bottom of the indicator (0 level)
Trading Action: Strong entry signal for long positions
Confidence Level: High confidence signal, especially when accompanied by large green candles
Purple Diamond Super Sell Signals
Meaning: Both short-term and long-term oscillators are generating sell signals simultaneously
Visual Indicator: Purple diamond markers at the top of the indicator (100 level)
Trading Action: Strong entry signal for short positions or exit signal for long positions
Confidence Level: High confidence signal, especially when accompanied by large red candles
Market Liquidity Concept
The SMO provides a unique perspective on market conditions that goes beyond traditional oscillator interpretations:
Low Oscillator Readings (Below 20)
When the oscillator shows low readings (below 20), this indicates:
Traditional interpretation: Market is oversold, potential for upward reversal
Liquidity interpretation: Insufficient money in the market
This suggests thin trading conditions where large orders may have outsized impact
Price movements may be more erratic and less predictable
Breakouts may lack follow-through due to insufficient participation
High Oscillator Readings (Above 80)
When the oscillator shows high readings (above 80), this indicates:
Traditional interpretation: Market is overbought, potential for downward reversal
Liquidity interpretation: Abundant money in the market
This suggests deep trading conditions with high participation
Price movements tend to be more orderly and trend-based
Breakouts may have stronger follow-through due to high participation
Trading Strategies with SMO
Strategy 1: Main Trend with Alignment Confirmation
This strategy uses the main trend direction with alignment confirmation:
Entry Criteria:
Main trend direction is established (green or red candles)
Fast line aligns with main trend (large candles)
Super signal confirms (green or purple diamond)
Exit Criteria:
For long positions: When candles turn red or Super Sell signal appears
For short positions: When candles turn green or Super Buy signal appears
Stop Loss Placement:
For long positions: Below recent swing low
For short positions: Above recent swing high
Strategy 2: Counter-Trend Opportunity Detection
This strategy identifies potential counter-trend opportunities:
Entry Criteria:
Small candles appear (indicating disagreement between fast and main trend lines)
Oscillator reaches extreme levels (above 80 or below 20)
Wait for candle color change before entering
Position Sizing:
Use smaller position sizes for counter-trend trades
Increase size only when main trend confirms the new direction
Exit Criteria:
Take profit at the first sign of alignment in the opposite direction
Use tighter stops than with trend-following trades
Strategy 3: Market Liquidity Strategy
This strategy incorporates the market liquidity concept:
For Low Liquidity Conditions (Readings below 20):
Wait for Super Buy signals (green diamond)
Use smaller position sizes
Be prepared for potentially erratic price movements
Look for signs of increasing liquidity (expanding candle bodies) before adding to positions
For High Liquidity Conditions (Readings above 80):
Consider holding positions longer despite "overbought" readings
Use trailing stops to capture extended moves
Be aware that trends may persist longer than expected
Practical Trading Scenarios
Scenario 1: Strong Trend Confirmation
Candle Pattern: Series of large green candles (main trend up, fast line confirms)
Signal: Green diamond Super Buy marker at the bottom (0 level)
Background: Intensifying green gradient
Action: Enter long position with confidence
Stop Loss: Below recent swing low
Take Profit: When candles become small or turn red
Scenario 2: Trend Weakening Detection
Candle Pattern: Green candles becoming smaller (main trend still up, but fast line diverging)
Signal: No new signals
Background: Fading green gradient
Action: Tighten stops on long positions, prepare for potential reversal
Reasoning: Fast money is starting to move against the main trend
Scenario 3: Trend Reversal Identification
Candle Pattern: Transition from small green candles to red candles (main trend changing)
Signal: Appearance of purple diamond Super Sell marker at the top (100 level)
Background: Changing from green to red gradient
Action: Exit long positions and potentially enter short positions
Timing: Most effective when reversal occurs near overbought (80) level
Demand and Supply MTF with SMC By StockFusion - 3.0Demand and Supply MTF with SMC By StockFusion - 3.0 - Indicator Description
Concepts
What is Supply & Demand?
Supply and Demand are foundational forces driving market dynamics. Demand reflects the presence of buyers willing to purchase a security, while Supply indicates sellers offering it for sale. These forces create zones on the chart where price tends to react—either reversing or continuing—based on the balance between buying and selling pressure. This indicator identifies these zones using price action patterns, focusing on impulsive moves (strong directional momentum) and retracement phases (consolidation or pullbacks).
What is SMC (Smart Money Concepts)?
Smart Money Concepts (SMC) revolve around tracking the behavior of institutional traders, often called "smart money." By analyzing price action, market structure shifts, and liquidity, SMC helps retail traders align with the moves of larger players. Key SMC signals like Change of Character (CHoCH), Break of Structure (BOS), liquidity sweeps, and swing points provide insights into potential trend changes or continuations.
Overview
Demand and Supply MTF with SMC By StockFusion - 3.0 is a sophisticated, price action-based indicator designed to plot real-time Supply and Demand zones across multiple timeframes (MTF) directly on your chart. It goes beyond simple zone plotting by integrating Smart Money Concepts (SMC) and Inside Candle detection, offering traders a powerful tool for spotting high-probability reversal or continuation areas. The indicator highlights zones with customizable boxes, labels them for clarity, and provides additional SMC-driven insights such as CHoCH, BOS, liquidity sweeps, and swing high/low levels. This combination of multi-timeframe analysis, SMC, and consolidation detection creates a unique and highly practical tool for traders seeking an edge in the markets.
How It Works
The indicator operates by analyzing price action across two user-defined timeframes (Higher TF and Lower TF) to detect Supply and Demand zones. It identifies these zones based on specific price patterns:
Rally Base Rally (RBR): A bullish impulsive move, followed by consolidation, then another bullish move—indicating a Demand zone.
Drop Base Drop (DBD): A bearish impulsive move, consolidation, then another bearish move—indicating a Supply zone.
Drop Base Rally (DBR): A bearish move, consolidation, then a bullish reversal—indicating a Demand zone.
Rally Base Drop (RBD): A bullish move, consolidation, then a bearish reversal—indicating a Supply zone.
These patterns are detected using criteria like explosive candle movements (based on range-to-body ratios and ATR multipliers), volume thresholds, and base candle counts (configurable from 1 to 5 candles). Zones are plotted as horizontal bands, with Higher TF zones taking precedence to avoid overlap with Lower TF zones, ensuring clarity on the chart.
Smart Money Integration:
The indicator enhances zone analysis with SMC features:
CHoCH (Change of Character): Detects shifts in market sentiment by comparing price action against recent swing highs/lows over a customizable period.
BOS (Break of Structure): Identifies when price breaks key structural levels, signaling a potential trend shift.
Liquidity Sweeps: Marks areas where price briefly exceeds swing points before reversing, often targeting stop-loss orders.
Swings: Highlights significant swing highs and lows to track momentum and structure.
Inside Candle Detection:
Inside Candles—smaller candles contained within the range of a prior candle—are plotted to indicate consolidation or indecision, often preceding breakouts. Optional lines can be drawn around these candles for better visibility.
Key Features & How to Use
Real-Time Zone Plotting:
Automatically identifies and marks Supply and Demand zones as they form, using the RBR, RBD, DBR, and DBD patterns. Zones are color-coded (e.g., green for Demand, red for Supply) and can extend rightward for visibility.
Multi-Timeframe Analysis:
Operates on all timeframes, with separate settings for Higher TF (e.g., weekly) and Lower TF (e.g., daily) zones. This allows traders to see both macro and micro levels of market structure.
Automatic Detection:
No manual input is required—zones are plotted based on price action, volume, and SMA trends. Live candle volume is displayed for context.
Tested Zone Management:
Optionally removes zones after they’re tested (price revisits and reverses) or after a second leg-out move, keeping the chart uncluttered.
Customizable Display:
Choose which patterns to detect (RBR, RBD, etc.).
Adjust base candle counts (1-5), explosive candle parameters (Range-Body Ratio, Multiplier), and quality filters (SMA length, Volume Multiplier).
Customize colors for zones, borders, labels, and candles (boring, bullish explosive, bearish explosive).
Enable/disable labels and pattern names on boxes.
Alerts:
Set notifications for zone formation, CHoCH, BOS, and liquidity sweeps on your chosen timeframe.
Inside Candle Visualization:
Highlights consolidation phases with color-coded candles and optional lines, aiding breakout anticipation.
SMC Insights:
Visualizes CHoCH, BOS, liquidity sweeps, and swings with distinct lines and labels, helping traders follow institutional moves.
How to Use It:
Approaching Zones: When price nears a Supply or Demand zone, watch for reversal patterns (e.g., pin bars, engulfing candles) or SMC signals (e.g., BOS, liquidity sweeps) to confirm entries. Combine with your tested strategy—don’t trade zones blindly.
SMC Signals: Use CHoCH for early trend reversal clues, BOS for trend continuation, and liquidity sweeps to gauge manipulation.
Inside Candles: Monitor for breakouts after consolidation periods marked by Inside Candles.
Why It’s Unique & Valuable
This indicator stands out by blending multi-timeframe Supply and Demand analysis with Smart Money Concepts and Inside Candle detection into a single, cohesive tool. While it uses classic elements like price action and volume, its proprietary logic—combining specific pattern detection (RBR, RBD, DBR, DBD), SMC signals (CHoCH, BOS, etc.), and consolidation tracking—offers a fresh approach. Unlike generic trend-following or scalping tools, it provides actionable insights into market structure and institutional behavior, making it worth considering for traders willing to invest in a premium tool. The flexibility of customization and MTF functionality further enhances its utility across trading styles, from scalping to swing trading.
Pivot S/R with Volatility Filter## *📌 Indicator Purpose*
This indicator identifies *key support/resistance levels* using pivot points while also:
✅ Detecting *high-volume liquidity traps* (stop hunts)
✅ Filtering insignificant pivots via *ATR (Average True Range) volatility*
✅ Tracking *test counts and breakouts* to measure level strength
---
## *⚙ SETTINGS – Detailed Breakdown*
### *1️⃣ ◆ General Settings*
#### *🔹 Pivot Length*
- *Purpose:* Determines how many bars to analyze when identifying pivots.
- *Usage:*
- *Low values (5-20):* More pivots, better for scalping.
- *High values (50-200):* Fewer but stronger levels for swing trading.
- *Example:*
- Pivot Length = 50 → Only the most significant highs/lows over 50 bars are marked.
#### *🔹 Test Threshold (Max Test Count)*
- *Purpose:* Sets how many times a level can be tested before being invalidated.
- *Example:*
- Test Threshold = 3 → After 3 tests, the level is ignored (likely to break).
#### *🔹 Zone Range*
- *Purpose:* Creates a price buffer around pivots (±0.001 by default).
- *Why?* Markets often respect "zones" rather than exact prices.
---
### *2️⃣ ◆ Volatility Filter (ATR)*
#### *🔹 ATR Period*
- *Purpose:* Smoothing period for Average True Range calculation.
- *Default:* 14 (standard for volatility measurement).
#### *🔹 ATR Multiplier (Min Move)*
- *Purpose:* Requires pivots to show *meaningful price movement*.
- *Formula:* Min Move = ATR × Multiplier
- *Example:*
- ATR = 10 pips, Multiplier = 1.5 → Only pivots with *15+ pip swings* are valid.
#### *🔹 Show ATR Filter Info*
- Displays current ATR and minimum move requirements on the chart.
---
### *3️⃣ ◆ Volume Analysis*
#### *🔹 Volume Change Threshold (%)*
- *Purpose:* Filters for *unusual volume spikes* (institutional activity).
- *Example:*
- Threshold = 1.2 → Requires *120% of average volume* to confirm signals.
#### *🔹 Volume MA Period*
- *Purpose:* Lookback period for "normal" volume calculation.
---
### *4️⃣ ◆ Wick Analysis*
#### *🔹 Wick Length Threshold (Ratio)*
- *Purpose:* Ensures rejection candles have *long wicks* (strong reversals).
- *Formula:* Wick Ratio = (Upper Wick + Lower Wick) / Candle Range
- *Example:*
- Threshold = 0.6 → 60% of the candle must be wicks.
#### *🔹 Min Wick Size (ATR %)*
- *Purpose:* Filters out small wicks in volatile markets.
- *Example:*
- ATR = 20 pips, MinWickSize = 1% → Wicks under *0.2 pips* are ignored.
---
### *5️⃣ ◆ Display Settings*
- *Show Zones:* Toggles support/resistance shaded areas.
- *Show Traps:* Highlights liquidity traps (▲/▼ symbols).
- *Show Tests:* Displays how many times levels were tested.
- *Zone Transparency:* Adjusts opacity of zones.
---
## *🎯 Practical Use Cases*
### *1️⃣ Liquidity Trap Detection*
- *Scenario:* Price spikes *above resistance* then reverses sharply.
- *Requirements:*
- Long wick (Wick Ratio > 0.6)
- High volume (Volume > Threshold)
- *Outcome:* *Short Trap* signal (▼) appears.
### *2️⃣ Strong Support Level*
- *Scenario:* Price bounces *3 times* from the same level.
- *Indicator Action:*
- Labels the level with test count (3/5 = 3 tests out of max 5).
- Turns *red* if broken (Break Count > 0).
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
## *📊 Parameter Encyclopedia (Expanded)*
### *1️⃣ Pivot Engine Settings*
#### *Pivot Length (50)*
- *What It Does:*
Determines how many bars to analyze when searching for swing highs/lows.
- *Professional Adjustment Guide:*
| Trading Style | Recommended Value | Why? |
|--------------|------------------|------|
| Scalping | 10-20 | Captures short-term levels |
| Day Trading | 30-50 | Balanced approach |
| Swing Trading| 50-200 | Focuses on major levels |
- *Real Market Example:*
On NASDAQ 5-minute chart:
- Length=20: Identifies levels holding for ~2 hours
- Length=50: Finds levels respected for entire trading day
#### *Test Threshold (5)*
- *Advanced Insight:*
Institutions often test levels 3-5 times before breaking them. This setting mimics the "probe and push" strategy used by smart money.
- *Psychology Behind It:*
Retail traders typically give up after 2-3 tests, while institutions keep testing until stops are run.
---
### *2️⃣ Volatility Filter System*
#### *ATR Multiplier (1.0)*
- *Professional Formula:*
Minimum Valid Swing = ATR(14) × Multiplier
- *Market-Specific Recommendations:*
| Market Type | Optimal Multiplier |
|------------------|--------------------|
| Forex Majors | 0.8-1.2 |
| Crypto (BTC/ETH) | 1.5-2.5 |
| SP500 Stocks | 1.0-1.5 |
- *Why It Matters:*
In EUR/USD (ATR=10 pips):
- Multiplier=1.0 → Requires 10 pip swings
- Multiplier=1.5 → Requires 15 pip swings (fewer but higher quality levels)
---
### *3️⃣ Volume Confirmation System*
#### *Volume Threshold (1.2)*
- *Institutional Benchmark:*
- 1.2x = Moderate institutional interest
- 1.5x+ = Strong smart money activity
- *Volume Spike Case Study:*
*Before Apple Earnings:*
- Normal volume: 2M shares
- Spike threshold (1.2): 2.4M shares
- Actual volume: 3.1M shares → STRONG confirmation
---
### *4️⃣ Liquidity Trap Detection*
#### *Wick Analysis System*
- *Two-Filter Verification:*
1. *Wick Ratio (0.6):*
- Ensures majority of candle shows rejection
- Formula: (UpperWick + LowerWick) / Total Range > 0.6
2. *Min Wick Size (1% ATR):*
- Prevents false signals in flat markets
- Example: ATR=20 pips → Min wick=0.2 pips
- *Trap Identification Flowchart:*
Price Enters Zone →
Spikes Beyond Level →
Shows Long Wick →
Volume > Threshold →
TRAP CONFIRMED
---
## *💡 Master-Level Usage Techniques*
### *Institutional Order Flow Analysis*
1. *Step 1:* Identify pivot levels with ≥3 tests
2. *Step 2:* Watch for volume contraction near levels
3. *Step 3:* Enter when trap signal appears with:
- Wick > 2×ATR
- Volume > 1.5× average
### *Multi-Timeframe Confirmation*
1. *Higher TF:* Find weekly/monthly pivots
2. *Lower TF:* Use this indicator for precise entries
3. *Example:*
- Weekly pivot at $180
- 4H shows liquidity trap → High-probability reversal
---
## *⚠ Critical Mistakes to Avoid*
1. *Using Default Settings Everywhere*
- Crude oil needs higher ATR multiplier than bonds
2. *Ignoring Trap Context*
- Traps work best at:
- All-time highs/lows
- Major psychological numbers (00/50 levels)
3. *Overlooking Cumulative Volume*
- Check if volume is building over multiple tests
HMA PLANz1. High Liquidity Candle Detection:
The indicator looks for candles with high liquidity (identified by comparing the current candle's volume with the highest volume of the last 10 candles).
If a candle has high liquidity, it is highlighted in yellow.
2. Midpoint Calculation of the Candle:
The midpoint of the candle is calculated by averaging the High and Low prices of the candle:
Midpoint
=
High
+
Low
2
Midpoint=
2
High+Low
3. Draw a Line at the Midpoint of the High Liquidity Candle:
A horizontal line is drawn at the calculated midpoint value of the high liquidity candle and continues for the next five candles.
4. Change Line Color Based on Price vs. Midpoint:
If the current price is above the midpoint, the line is drawn in green.
If the current price is below the midpoint, the line is drawn in red.
5. Moving Averages (MA):
In addition to liquidity analysis, the indicator calculates and plots two moving averages on the chart.
Users can choose between EMA, SMA, WMA, or HMA for each moving average.
Users can also select the source for the moving averages (Close, High, Low).
The length for each moving average is customizable.
6. Display Moving Averages with Labels:
The moving average lines are plotted on the chart.
Labels are displayed above each moving average to show its type and source (e.g., "MA - HMA (Close)").
Summary of Key Features:
High Liquidity Candle Detection: Highlighted in yellow.
Draw a Horizontal Line at the Midpoint of the high liquidity candle: The line color changes based on price relation to the midpoint.
Moving Averages: Allows customization of types and lengths.
Labels: Shows details of the moving averages.
EQS by SiriusProtected Script Description: "EQS by Sirius"
This indicator is protected and published as invite-only due to its original multi-timeframe structure, advanced visual logic, and proprietary handling of liquidity zones and equal high/low detection. The complexity of its design—featuring adaptive time-based plotting, contextual tooltips, and dynamic zone tracking—reflects a level of custom development intended for professional use, necessitating source protection.
Purpose and Core Logic
“EQS by Sirius” is designed to detect and visualize Equal Highs and Equal Lows (EQS) across multiple timeframes. These levels are commonly interpreted as potential liquidity zones or key market structures, often used by traders for identifying breakout traps, stop hunts, or reversal points. The script applies a precision-based algorithm to identify these EQS levels, providing users with visual cues to support decision-making in various market contexts.
The detection logic is based on comparing the difference between two successive highs (or lows) relative to the high-low range of the bars, allowing the user to fine-tune sensitivity via a precision parameter. When valid EQS conditions are met, horizontal lines are drawn at the detected price level, accompanied by optional shadow trendlines to represent liquidity channels.
Visual Outputs and Features
The indicator provides a rich and customizable visual environment, including:
Multi-Timeframe EQS Detection: Configurable from 1-minute to 4-hour timeframes with automatic sequencing.
Zone Highlighting: Optional background shading for designated date intervals.
Dynamic Shadow Mode: Projects angled trendlines representing potential liquidity zones based on EQS formations.
Touch Counters: Real-time counting of price interactions with plotted EQS levels.
Tooltips: Each label includes a timestamp and price breakdown to provide contextual clarity.
Line Customization: Adjustable color, width, and transparency for each EQS type and its shadow projections.
Auto-zoom Scaling: Adapts visual density based on the active chart’s timeframe.
Visibility Filters: Adjustable proximity thresholds ensure only relevant lines are displayed based on current price action.
How to Use in Trading
Traders can use this tool to:
Identify liquidity targets where price may reverse or accelerate due to stop hunts or breakout traps.
Analyze multi-timeframe confluence by comparing EQS zones from higher timeframes with local market structure.
Monitor touch counts to assess the strength or weakening of support/resistance levels.
Visualize trendline-based liquidity zones using the “shadow mode” to infer possible manipulation or price magnet areas.
Integrate with existing strategies for entry/exit timing, particularly in breakout and mean-reversion models.
Due to the high level of customizability and visual control, the script is suitable for discretionary traders, smart money concept practitioners, and those seeking to combine structural analysis with liquidity mapping.
Money Flow Divergence IndicatorOverview
The Money Flow Divergence Indicator is designed to help traders and investors identify key macroeconomic turning points by analyzing the relationship between U.S. M2 money supply growth and the S&P 500 Index (SPX). By comparing these two crucial economic indicators, the script highlights periods where market liquidity is outpacing or lagging behind stock market growth, offering potential buy and sell signals based on macroeconomic trends.
How It Works
1. Data Sources
S&P 500 Index (SPX500USD): Tracks the stock market performance.
U.S. M2 Money Supply (M2SL - Federal Reserve Economic Data): Represents available liquidity in the economy.
2. Growth Rate Calculation
SPX Growth: Percentage change in the S&P 500 index over time.
M2 Growth: Percentage change in M2 money supply over time.
Growth Gap (Delta): The difference between M2 growth and SPX growth, showing whether liquidity is fueling or lagging behind market performance.
3. Visualization
A histogram displays the growth gap over time:
Green Bars: M2 growth exceeds SPX growth (potential bullish signal).
Red Bars: SPX growth exceeds M2 growth (potential bearish signal).
A zero line helps distinguish between positive and negative growth gaps.
How to Use It
✅ Bullish Signal: When green bars appear consistently, indicating that liquidity is outpacing stock market growth. This suggests a favorable environment for buying or holding positions.
❌ Bearish Signal: When red bars appear consistently, meaning stock market growth outpaces liquidity expansion, signaling potential overvaluation or a market correction.
Best Timeframes for Analysis
This indicator works best on monthly timeframes (M) since it is designed for long-term investors and macro traders who focus on broad economic cycles.
Who Should Use This Indicator?
📈 Long-term investors looking for macroeconomic trends.
📊 Swing traders who incorporate liquidity analysis in their strategies.
💰 Portfolio managers assessing market liquidity conditions.
🚀 Use this indicator to stay ahead of market trends and make informed investment decisions based on macroeconomic liquidity shifts! 🚀
AlphaSync | QuantEdgeB📢 Introducing AlphaSync by QuantEdgeB
🛠️ Overview
AlphaSync is a comprehensive medium-term market guidance system designed for major assets such as BTC, ETH, and SOL. This system helps traders determine the overall market direction by integrating three universal strategies (EvolveXSync, ApexSync, QBHV Sync) and a Hybrid strategy (HybridSync).
🚀 What Makes AlphaSync Unique?
✅ Multi-Strategy Fusion → A robust blend of technical, economic, on-chain, and volatility-driven insights.
✅ HybridSync Component (90% Non-Price Factors) → Incorporates macro and liquidity signals to balance pure price-based models.
✅ Structured Decision-Making → The Trend Confluence score aggregates all sub-strategies, providing a unified market signal.
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✨ Key Features
🔹 HybridSync (Hybrid Model)
Utilizes on-chain, economic, liquidity, and volatility factors to provide a fundamental market risk outlook. Unlike technical models, it derives signals primarily from macroeconomic indicators, risk appetite gauges, and capital flows.
🔹 EvolveXSync, & ApexSync (Technical Strategies)
Both strategies are purely price-based, relying on volatility-adjusted trend models, adaptive moving averages, and statistical deviations to confirm bullish or bearish trends.
🔹 QBHV Sync (Momentum & Deviation-Based System)
A fusion of momentum-deviation and a volatility-driven trend confirmation model, designed to detect shifts in momentum while filtering out market noise.
🔹 Trend Confluence (Final Aggregated Signal)
A weighted combination of all four models, delivering a single, structured signal to eliminate conflicting indicators and refine decision-making.
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📊 How It Works
1️⃣ HybridSync – Non-Price Market Structure Analysis
HybridSync is an economic and liquidity-based framework, integrating macro variables, credit spreads, volatility indices, capital flows, and on-chain dynamics to assess risk-on/risk-off conditions.
📌 Key Components:
✔ On-Chain Metrics → Tracks investor behavior, exchange flows, and market cap ratios.
✔ Liquidity Indicators → Monitors global money supply (M2), Federal Reserve balance sheet, credit markets, and capital flows.
✔ Volatility & Risk Metrics → Uses MOVE, VIX, VVIX ratios, and bond market stress indicators to identify risk sentiment shifts.
🔹 Why HybridSync?
• Price alone does not dictate the market; macro liquidity and risk factors are often leading indicators of price movement, especially when it comes to risk assets such as cryptocurrencies.
• Improves decision-making in uncertain market environments, particularly during high-volatility or trendless conditions.
2️⃣ EvolveXSync, & ApexSync – Trend-Following & Volatility Models
Both EvolveXSync, & ApexSync are technical strategies, independently designed to capture trend strength and volatility dynamics.
📌 Core Mechanisms:
✔ VIDYA-Based Trend Detection → Adaptive moving averages adjust dynamically to price swings.
✔ SD-Filtered EMA Models → Uses normalized standard deviation levels to confirm trend validity.
✔ ATR-Adjusted Breakout Filters → Prevents false signals by incorporating dynamic volatility assessments.
🔹 Why Two UniStrategies?
• EvolveXSync, & ApexSync have different calculation methods, providing diverse perspectives on trend confirmation.
• Ensures robustness by mitigating overfitting to a single price-based model.
3️⃣ QBHV Sync – Momentum Deviation & Trend Confirmation
This component blends Bollinger Momentum Deviation (BMD) with a percentile-based trend model to confirm trend shifts.
📌 Core Components:
✔ Bollinger Momentum Deviation → A normalized SMA-SD filter detects overbought/oversold conditions.
✔ Percentile-Based Trend Confirmation → Ensures trends align with long-term volatility structure.
✔ Adaptive Signal Filtering → Prevents unnecessary trade signals by refining thresholds dynamically.
🔹 Why QBHV Sync?
• Adds a statistical layer to trend assessment, preventing whipsaws in volatile conditions.
• Complements HybridSync by ensuring price movements align with broader market forces.
4️⃣ Trend Confluence – The Final Aggregated Signal
AlphaSync blends HybridSync, EvolveXSync, ApexSync, and QBHV Sync into one final output.
📌 How It’s Weighted ? Equal Weight to remove any bias and over-reliance on one input.
✔ HybridSync (Macro & On-Chain Factors) → 25% Weight
✔ UniStrat V1 (Pure Trend) → 25% Weight
✔ UniStrat V2 (Trend + ATR) → 25% Weight
✔ QBHV Sync (Momentum & Deviation) → 25% Weight
🔹 Why Merge These Into One System?
The core philosophy behind AlphaSync is to create a holistic, structured decision-making framework that eliminates the weaknesses of single-method trading approaches. Instead of relying solely on technical indicators, which can lag or fail in macro-driven markets, AlphaSync blends price-based trend signals with macroeconomic, liquidity, and risk-adjusted models.
This multi-layered approach ensures that the system:
✔ Adapts dynamically to different market environments.
✔ Eliminates conflicting signals by creating a structured confluence score.
✔ Prevents over-reliance on a single market model, improving robustness.
📌 Final Signal Interpretation:
✅ Long Signal → AlphaSync Score > Long Threshold
❌ Short Signal → AlphaSync Score < Short Threshold
__________________________________________________________________________________
👥 Who Should Use AlphaSync?
✅ Medium-Term Traders & Portfolio Managers → Ideal for traders who require macro-confirmed trend signals.
✅ Systematic & Quantitative Traders → Designed for algorithmic integration and structured decision-making.
✅ Long-Term Position Traders → Helps identify major trend shifts and capital rotation opportunities.
✅ Risk-Conscious Investors → Incorporates macro volatility assessments to minimize unnecessary risk exposure.
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📊 Backtest Mode - Evaluating Historical Performance
AlphaSync includes a fully integrated backtest module, allowing traders to assess its historical performance metrics.
🔹 Backtest Metrics Displayed:
✔ Equity Max Drawdown → Measures historical peak loss.
✔ Profit Factor → Evaluates profitability vs. loss ratio.
✔ Sharpe & Sortino Ratios → Risk-adjusted return metrics.
✔ Total Trades & Win Rate → Performance across different market cycles.
✔ Half Kelly Criterion → Optimal position sizing based on historical returns.
📌 Disclaimer:Backtest results are based on past performance and do not guarantee future success. Always incorporate real-time validation and risk management in live trading.
🚀 Why This Matters?
✅ Strategy Validation → See how AlphaSync performs across various market conditions.
✅ Customizable Analysis → Adjust parameters and observe real-time backtest results.
✅ Risk Awareness → Understand potential drawdowns before deploying capital.
Behavior Across Crypto Majors:
BTC
ETH
SOL
📌 Disclaimer: Backtest results are based on historical data and past market behavior. Performance is not indicative of future results and should not be considered financial advice. Always conduct your own backtests and research before making any investment decisions. 🚀
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📌 Customization & Default Settings
📌 AlphaSync Input Parameters & Default Values
🔹 Strategy Configuration
• Color Mode → "Strategy"
• Extra Plots → true
• Long/Cash Signal Label → false
• AlphaSync Dashboard → true
• Enable BackTest Table → false
• Enable Equity Curve → false
• Table Position → "Bottom Left"
• Start Date → '01 Jan 2018 00:00'
• AlphaSync Long Threshold → 0.00
• AlphaSync Short Threshold → 0.00
🔹 QBHV.Sync
• DEMA Source → close
• DEMA Length → 14
• Percentile Length → 35
• ATR Length → 14
• Long Multiplier (ATR Up) → 1.8
• Short Multiplier (ATR Down) → 2.5
• Momentum Length → 8
• Momentum Source → close
• Base Length (SMA Calculation) → 40
• Source for BMD → close
• Standard Deviation Length → 30
• SD Multiplier → 0.7
• Long Threshold → 72
• Short Threshold → 59
🔹 EvolveXSync Configuration
• VIDYA Loop Length → 2
• VIDYA Loop Hist Length → 5
• Vidya Loop Long Threshold → 40
• Vidya Loop Short Threshold → 10
• Dynamic EMA Length → 12
• Dynamic EMA SD Length → 30
• Dynamic EMA Upper SD Weight → 1.032
• Dynamic EMA Lower SD Weight → 1.02
• SD Median Length → 12
• Normalized Median Length → 20
• Median SD Length → 30
• Median Long SD Weight → 0.98
• Median Short SD Weight → 1.04
🔹ApexSync Configuration
• DEMA Length → 30
• DEMA ATR Length → 14
• DEMA ATR Multiplier → 1.0
• G-VIDYA Length → 9
• G-VIDYA Hist Length → 30
• VIDYA ATR Length → 14
• VIDYA ATR Multiplier → 1.7
• SD Kijun Length → 24
• Normalized Kijun Length → 50
• KIJUN SD Length → 32
• KIJUN Long SD Weight → 0.98
• KIJUN Short SD Weight → 1.02
🔹 Risk Mosaic (Macro & Liquidity Component)
• Risk Signal Smoothing Length (EMA) → 8
🚀 AlphaSync is fully customizable to match different market conditions and trading styles
🚀 By default, AlphaSync is optimized for structured, medium-term market guidance.
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📌 Conclusion
AlphaSync redefines medium-term trend analysis by merging technical, fundamental, and quantitative models into one unified system. Unlike traditional strategies that rely solely on price action, AlphaSync incorporates macroeconomic and liquidity factors, ensuring a more holistic market view.
🔹 Key Takeaways:
1️⃣ Hybrid + Technical Fusion – Balances macro & price-based strategies for stronger decision-making.
2️⃣ Multi-Factor Trend Aggregation – Reduces false signals by merging independent methodologies.
3️⃣ Structured, Data-Driven Approach – Designed for quantitative trading and risk-aware portfolio allocation.
📌 Master the market with precision and confidence | QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
