Price Action Smart Money Concepts [BigBeluga]THE SMART MONEY CONCEPTS Toolkit
The Smart Money Concepts [ BigBeluga ] is a comprehensive toolkit built around the principles of "smart money" behavior, which refers to the actions and strategies of institutional investors.
The Smart Money Concepts Toolkit brings together a suite of advanced indicators that are all interconnected and built around a unified concept: understanding and trading like institutional investors, or "smart money." These indicators are not just randomly chosen tools; they are features of a single overarching framework, which is why having them all in one place creates such a powerful system.
This all-in-one toolkit provides the user with a unique experience by automating most of the basic and advanced concepts on the chart, saving them time and improving their trading ideas.
Real-time market structure analysis simplifies complex trends by pinpointing key support, resistance, and breakout levels.
Advanced order block analysis leverages detailed volume data to pinpoint high-demand zones, revealing internal market sentiment and predicting potential reversals. This analysis utilizes bid/ask zones to provide supply/demand insights, empowering informed trading decisions.
Imbalance Concepts (FVG and Breakers) allows traders to identify potential market weaknesses and areas where price might be attracted to fill the gap, creating opportunities for entry and exit.
Swing failure patterns help traders identify potential entry points and rejection zones based on price swings.
Liquidity Concepts, our advanced liquidity algorithm, pinpoints high-impact events, allowing you to predict market shifts, strong price reactions, and potential stop-loss hunting zones. This gives traders an edge to make informed trading decisions based on liquidity dynamics.
🔵 FEATURES
The indicator has quite a lot of features that are provided below:
Swing market structure
Internal market structure
Mapping structure
Adjustable market structure
Strong/Weak H&L
Sweep
Volumetric Order block / Breakers
Fair Value Gaps / Breakers (multi-timeframe)
Swing Failure Patterns (multi-timeframe)
Deviation area
Equal H&L
Liquidity Prints
Buyside & Sellside
Sweep Area
Highs and Lows (multi-timeframe)
🔵 BASIC DEMONSTRATION OF ALL FEATURES
1. MARKET STRUCTURE
The preceding image illustrates the market structure functionality within the Smart Money Concepts indicator.
➤ Solid lines: These represent the core indicator's internal structure, forming the foundation for most other components. They visually depict the overall market direction and identify major reversal points marked by significant price movements (denoted as 'x').
➤ Internal Structure: These represent an alternative internal structure with the potential to drive more rapid market shifts. This is particularly relevant when a significant gap exists in the established swing structure, specifically between the Break of Structure (BOS) and the most recent Change of High/Low (CHoCH). Identifying these formations can offer opportunities for quicker entries and potential short-term reversals.
➤ Sweeps (x): These signify potential turning points in the market where liquidity is removed from the structure. This suggests a possible trend reversal and presents crucial entry opportunities. Sweeps are identified within both swing and internal structures, providing valuable insights for informed trading decisions.
➤ Mapping structure: A tool that automatically identifies and connects significant price highs and lows, creating a zig-zag pattern. It visualizes market structure, highlights trends, support/resistance levels, and potential breakouts. Helps traders quickly grasp price action patterns and make informed decisions.
➤ Color-coded candles based on market structure: These colors visually represent the underlying market structure, making it easier for traders to quickly identify trends.
➤ Extreme H&L: It visualizes market structure with extreme high and lows, which gives perspective for macro Market Structure.
2. VOLUMETRIC ORDER BLOCKS
Order blocks are specific areas on a financial chart where significant buying or selling activity has occurred. These are not just simple zones; they contain valuable information about market dynamics. Within each of these order blocks, volume bars represent the actual buying and selling activity that took place. These volume bars offer deeper insights into the strength of the order block by showing how much buying or selling power is concentrated in that specific zone.
Additionally, these order blocks can be transformed into Breaker Blocks. When an order block fails—meaning the price breaks through this zone without reversing—it becomes a breaker block. Breaker blocks are particularly useful for trading breakouts, as they signal that the market has shifted beyond a previously established zone, offering opportunities for traders to enter in the direction of the breakout.
Here's a breakdown:
➤ Bear Order Blocks (Red): These are zones where a lot of selling happened. Traders see these areas as places where sellers were strong, pushing the price down. When the price returns to these zones, it might face resistance and drop again.
➤ Bull Order Blocks (Green): These are zones where a lot of buying happened. Traders see these areas as places where buyers were strong, pushing the price up. When the price returns to these zones, it might find support and rise again.
These Order Blocks help traders identify potential areas for entering or exiting trades based on past market activity. The volume bars inside blocks show the amount of trading activity that occurred in these blocks, giving an idea of the strength of buying or selling pressure.
➤ Breaker Block: When an order block fails, meaning the price breaks through this zone without reversing, it becomes a breaker block. This indicates a significant shift in market liquidity and structure.
➤ A bearish breaker block occurs after a bullish order block fails. This typically happens when there's an upward trend, and a certain level that was expected to support the market's rise instead gives way, leading to a sharp decline. This decline indicates that sellers have overcome the buyers, absorbing liquidity and shifting the sentiment from bullish to bearish.
Conversely, a bullish breaker block is formed from the failure of a bearish order block. In a downtrend, when a level that was expected to act as resistance is breached, and the price shoots up, it signifies that buyers have taken control, overpowering the sellers.
3. FAIR VALUE GAPS:
A fair value gap (FVG), also referred to as an imbalance, is an essential concept in Smart Money trading. It highlights the supply and demand dynamics. This gap arises when there's a notable difference between the volume of buy and sell orders. FVGs can be found across various asset classes, including forex, commodities, stocks, and cryptocurrencies.
FVGs in this toolkit have the ability to detect raids of FVG which helps to identify potential price reversals.
Mitigation option helps to change from what source FVGs will be identified: Close, Wicks or AVG.
4. SWING FAILURE PATTERN (SFP):
The Swing Failure Pattern is a liquidity engineering pattern, generally used to fill large orders. This means, the SFP generally occurs when larger players push the price into liquidity pockets with the sole objective of filling their own positions.
SFP is a technical analysis tool designed to identify potential market reversals. It works by detecting instances where the price briefly breaks a previous high or low but fails to maintain that breakout, quickly reversing direction.
How it works:
Pattern Detection: The indicator scans for price movements that breach recent highs or lows.
Reversal Confirmation: If the price quickly reverses after breaching these levels, it's identified as an SFP.
➤ SFP Display:
Bullish SFP: Marked with a green symbol when price drops below a recent low before reversing upwards.
Bearish SFP: Marked with a red symbol when price rises above a recent high before reversing downwards.
➤ Deviation Levels: After detecting an SFP, the indicator projects white lines showing potential price deviation:
For bullish SFPs, the deviation line appears above the current price.
For bearish SFPs, the deviation line appears below the current price.
These deviation levels can serve as a potential trading opportunity or areas where the reversal might lose momentum.
With Volume Threshold and Filtering of SFP traders can adjust their trading style:
Volume Threshold: This setting allows traders to filter SFPs based on the volume of the reversal candle. By setting a higher volume threshold, traders can focus on potentially more significant reversals that are backed by higher trading activity.
SFP Filtering: This feature enables traders to filter SFP detection. It includes parameters such as:
5. LIQUIDITY CONCEPTS:
➤ Equal Lows (EQL) and Equal Highs (EQH) are important concepts in liquidity-based trading.
EQL: A series of two or more swing lows that occur at approximately the same price level.
EQH: A series of two or more swing highs that occur at approximately the same price level.
EQLs and EQHs are seen as potential liquidity pools where a large number of stop loss orders or limit orders may be clustered. They can be used as potential reverse points for trades.
This multi-period feature allows traders to select less and more significant EQL and EQH:
➤ Liquidity wicks:
Liquidity wicks are a minor representation of a stop-loss hunt during the retracement of a pivot point:
➤ Buy and Sell side liquidity:
The buy side liquidity represents a concentration of potential buy orders below the current price level. When price moves into this area, it can lead to increased buying pressure due to the execution of these orders.
The sell side liquidity indicates a pool of potential sell orders below the current price level. Price movement into this area can result in increased selling pressure as these orders are executed.
➤ Sweep Liquidation Zones:
Sweep Liquidation Zones are crucial for understanding market structure and potential future price movements. They provide insights into areas where significant market participants have been forced out of their positions, potentially setting up new trading opportunities.
🔵 USAGE & EXAMPLES
The core principle behind the success of this toolkit lies in identifying "confluence." This refers to the convergence of multiple trading indicators all signaling the same information at a specific point or area. By seeking such alignment, traders can significantly enhance the likelihood of successful trades.
MS + OBs
The chart illustrates a highly bullish setup where the price is rejecting from a bullish order block (POC), while simultaneously forming a bullish Swing Failure Pattern (SFP). This occurs after an internal structure change, marked by a bullish Change of Character (CHoCH). The price broke through a bearish order block, transforming it into a breaker block, further confirming the bullish momentum.
The combination of these elements—bullish order blocks, SFP, and CHoCH—creates a powerful bullish signal, reinforcing the potential for upward movement in the market.
SFP + Bear OB
This chart above displays a bearish setup with a high probability of a price move lower. The price is currently rejecting from a bear order block, which represents a key resistance area where significant selling pressure has previously occurred. A Swing Failure Pattern (SFP) has also formed near this bear order block, indicating that the price briefly attempted to break above a recent high but failed to sustain that upward movement. This failure suggests that buyers are losing momentum, and the market could be preparing for a move to the downside.
Additionally, we can toggle on the Deviation Area in the SFP section to highlight potential levels where price deviation might occur. These deviation areas represent zones where the price is likely to react after the Swing Failure Pattern:
BUY – SELL sides + EQL
The chart showcases a bullish setup with a high probability of price breaking out of the current sell-side resistance level. The market structure indicates a formation of Equal Lows (EQL), which often suggests a build-up of liquidity that could drive the price higher.
The presence of strong buy-side pressure (69%), indicated by the green zone at the bottom, reinforces this bullish outlook. This area represents a key support zone where buyers are outpacing sellers, providing the foundation for a potential upward breakout.
EQL + Bull ChoCh
This chart illustrates a potential bullish setup, driven by the formation of Equal Lows (EQL) followed by a bullish Change of Character (CHoCH). The presence of Equal Lows often signals a liquidity build-up, which can lead to a reversal when combined with additional bullish signals.
Liquidity grab + Bull ChoCh + FVGs
This chart demonstrates a strong bullish scenario, where several important market dynamics are at play. The price begins its upward momentum from Liquidity grab following a bullish Change of Character (CHoCH), signaling the transition from a bearish phase to a bullish one.
As the price progresses, it performs liquidity grabs, which serve to gather the necessary fuel for further movement. These liquidity grabs often occur before significant price surges, as large market participants exploit these areas to accumulate positions before pushing the price higher.
The chart also highlights a market imbalance area, showing strong momentum as the price moves swiftly through this zone.
In this examples, we see how the combination of multiple “smart money” tools helps identify a potential trade opportunities. This is just one of the many scenarios that traders can spot using this toolkit. Other combinations—such as order blocks, liquidity grabs, fair value gaps, and Swing Failure Patterns (SFPs)—can also be layered on top of these concepts to further refine your trading strategy.
🔵 SETTINGS
Window: limit calculation period
Swing: limit drawing function
Mapping structure: show structural points
Algorithmic Logic: (Extreme-Adjusted) Use max high/low or pivot point calculation
Algorithmic loopback: pivot point look back
Show Last: Amount of Order block to display
Hide Overlap: hide overlapping order blocks
Construction: Size of the order blocks
Fair value gaps: Choose between normal FVG or Breaker FVG
Mitigation: (close - wick - avg) point to mitigate the order block/imbalance
SFP lookback: find a higher / lower point to improve accuracy
Threshold: remove less relevant SFP
Equal H&L: (short-mid-long term) display longer term
Liquidity Prints: Shows wicks of candles where liquidity was grabbed
Sweep Area: Identify Sweep Liquidation areas
By combining these indicators in one toolkit, traders are equipped with a comprehensive suite of tools that address every angle of the Smart Money Concept. Instead of relying on disparate tools spread across various platforms, having them integrated into a single, cohesive system allows traders to easily see confluence and make more informed trading decisions.
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Momentum Alligator 4h Bitcoin StrategyOverview
The Momentum Alligator 4h Bitcoin Strategy is a trend-following trading system that operates on dual time frames. It utilizes the 1D Williams Alligator indicator to identify the prevailing major price trend and seeks trading opportunities on the 4-hour (4h) time frame when the momentum is turning up. The strategy is designed to close trades if the trend fails to develop or holding position if price continues increasing without any significant correction. Note that this strategy is specifically tailored for the 4-hour time frame.
Unique Features
2-layers market noise filtering system: Trades are only initiated in the direction of the 1D trend, determined by the Williams Alligator indicator. This higher time frame confirmation filters out minor trade signals, focusing on more substantial opportunities. At the same time, strategy has additional filter on 4h time frame with Awesome Oscillator which is showing the current price momentum.
Flexible Risk Management: The strategy exclusively opens long positions, resulting in fewer trades during bear markets. It incorporates a dynamic stop-loss mechanism, which can either follow the jaw line of the 4h Alligator or a user-defined fixed stop-loss. This flexibility helps manage risk and avoid non-trending markets.
Methodology
The strategy initiates a long position when the d-line of Stochastic RSI crosses up it's k-line. It means that there is a high probability that price momentum reversed from down to up. To avoid overtrading in potentially choppy markets, it skips the next two trades following a winning trade, anticipating sideways movement after a significant price surge.
This strategy has two layers trades filtering system: 4h and 1D time frames. The first one is awesome oscillator. It shall be increasing and value has to be higher than it's 5-period SMA. This is an additional confirmation that long trade is opened in the direction of the current momentum. As it was mentioned above, all entry signals are validated against the 1D Williams Alligator indicator. A trade is only opened if the price is above all three lines of the 1D Alligator, ensuring alignment with the major trend.
A trade is closed if the price hits the 4h jaw line of the Alligator or reaches the user-defined stop-loss level.
Risk Management
The strategy employs a combined approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined stop-loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 2% drop from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Stochastic RSI on 4h time frame to open long trade when momentum started reversing to the upside. On the one hand, Stochastic RSI is one of the most sensitive indicator, which allows to react fast on the potential trend reversal. On the other hand, this indicator can be too sensitive and provide a lot of false trend changing signals. To eliminate this weakness we use two-layers trades filtering system.
The first layer is the 4h Awesome oscillator. This is less sensitive momentum indicator. Usually it starts increasing when price has already passed significant distance from the actual reversal point. The strategy opens long trade only is Awesome oscillator is increasing and above it's 5-period SMA. This approach increases the probability to filter the false signals during the choppy market or if the reversal is false.
The second layer filter is the Williams Alligator indicator on 1D time frame. The 1D Alligator serves as a filter for identifying the primary trend and increases probability to avoid the trades with low potential because trading against major trend usually is more risky. It's much better to catch the trend continuation than local bounce.
Last but not least feature of this strategy is close trades condition. It uses the flexible approach. First of all, user can set up the fixed stop-loss according to his own risk-tolerance, by default this value is 2% of price movement. It restricts the potential loss at the moment when trade has just been opened. Moreover strategy utilizes the 4h Williams Alligator's jaw line to exit the trade. If price fell below it trade is closed. This approach helps to not keep open trade if trend is not developing and hold it if price continues going up.
Backtest Results:
Operating window: Date range of backtests is 2021.01.01 - 2024.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -3.04%
Maximum Single Profit: +29.67%
Net Profit: +6228.01 USDT (+62.28%)
Total Trades: 118 (24.58% win rate)
Profit Factor: 1.71
Maximum Accumulated Loss: 1527.69 USDT (-11.52%)
Average Profit per Trade: 52.78 USDT (+0.89%)
Average Trade Duration: 60 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use:
Add the script to favorites for easy access.
Apply to the 4h timeframe desired chart (optimal performance observed on the BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
AI Momentum [YinYang]Overview:
AI Momentum is a kernel function based momentum Indicator. It uses Rational Quadratics to help smooth out the Moving Averages, this may give them a more accurate result. This Indicator has 2 main uses, first it displays ‘Zones’ that help you visualize the potential movement areas and when the price is out of bounds (Overvalued or Undervalued). Secondly it creates signals that display the momentum of the current trend.
The Zones are composed of the Highest Highs and Lowest lows turned into a Rational Quadratic over varying lengths. These create our Rational High and Low zones. There is however a second zone. The second zone is composed of the avg of the Inner High and Inner Low zones (yellow line) and the Rational Quadratic of the current Close. This helps to create a second zone that is within the High and Low bounds that may represent momentum changes within these zones. When the Rationalized Close crosses above the High and Low Zone Average it may signify a bullish momentum change and vice versa when it crosses below.
There are 3 different signals created to display momentum:
Bullish and Bearish Momentum. These signals display when there is current bullish or bearish momentum happening within the trend. When the momentum changes there will likely be a lull where there are neither Bullish or Bearish momentum signals. These signals may be useful to help visualize when the momentum has started and stopped for both the bulls and the bears. Bullish Momentum is calculated by checking if the Rational Quadratic Close > Rational Quadratic of the Highest OHLC4 smoothed over a VWMA. The Bearish Momentum is calculated by checking the opposite.
Overly Bullish and Bearish Momentum. These signals occur when the bar has Bullish or Bearish Momentum and also has an Rationalized RSI greater or less than a certain level. Bullish is >= 57 and Bearish is <= 43. There is also the option to ‘Factor Volume’ into these signals. This means, the Overly Bullish and Bearish Signals will only occur when the Rationalized Volume > VWMA Rationalized Volume as well as the previously mentioned factors above. This can be useful for removing ‘clutter’ as volume may dictate when these momentum changes will occur, but it can also remove some of the useful signals and you may miss the swing too if the volume just was low. Overly Bullish and Bearish Momentum may dictate when a momentum change will occur. Remember, they are OVERLY Bullish and Bearish, meaning there is a chance a correction may occur around these signals.
Bull and Bear Crosses. These signals occur when the Rationalized Close crosses the Gaussian Close that is 2 bars back. These signals may show when there is a strong change in momentum, but be careful as more often than not they’re predicting that the momentum may change in the opposite direction.
Tutorial:
As we can see in the example above, generally what happens is we get the regular Bullish or Bearish momentum, followed by the Rationalized Close crossing the Zone average and finally the Overly Bullish or Bearish signals. This is normally the order of operations but isn’t always how it happens as sometimes momentum changes don’t make it that far; also the Rationalized Close and Zone Average don’t follow any of the same math as the Signals which can result in differing appearances. The Bull and Bear Crosses are also quite sporadic in appearance and don’t generally follow any sort of order of operations. However, they may occur as a Predictor between Bullish and Bearish momentum, signifying the beginning of the momentum change.
The Bull and Bear crosses may be a Predictor of momentum change. They generally happen when there is no Bullish or Bearish momentum happening; and this helps to add strength to their prediction. When they occur during momentum (orange circle) there is a less likely chance that it will happen, and may instead signify the exact opposite; it may help predict a large spike in momentum in the direction of the Bullish or Bearish momentum. In the case of the orange circle, there is currently Bearish Momentum and therefore the Bull Cross may help predict a large momentum movement is about to occur in favor of the Bears.
We have disabled signals here to properly display and talk about the zones. As you can see, Rationalizing the Highest Highs and Lowest Lows over 2 different lengths creates inner and outer bounds that help to predict where parabolic movement and momentum may move to. Our Inner and Outer zones are great for seeing potential Support and Resistance locations.
The secondary zone, which can cross over and change from Green to Red is also a very important zone. Let's zoom in and talk about it specifically.
The Middle Zone Crosses may help deduce where parabolic movement and strong momentum changes may occur. Generally what may happen is when the cross occurs, you will see parabolic movement to the High / Low zones. This may be the Inner zone but can sometimes be the outer zone too. The hard part is sometimes it can be a Fakeout, like displayed with the Blue Circle. The Cross doesn’t mean it may move to the opposing side, sometimes it may just be predicting Parabolic movement in a general sense.
When we turn the Momentum Signals back on, we can see where the Fakeout occurred that it not only almost hit the Inner Low Zone but it also exhibited 2 Overly Bearish Signals. Remember, Overly bearish signals mean a momentum change in favor of the Bulls may occur soon and overly Bullish signals mean a momentum change in favor of the Bears may occur soon.
You may be wondering, well what does “may occur soon” mean and how do we tell?
The purpose of the momentum signals is not only to let you know when Momentum has occurred and when it is still prevalent. It also matters A LOT when it has STOPPED!
In this example above, we look at when the Overly Bullish and Bearish Momentum has STOPPED. As you can see, when the Overly Bullish or Bearish Momentum stopped may be a strong predictor of potential momentum change in the opposing direction.
We will conclude our Tutorial here, hopefully this Indicator has been helpful for showing you where momentum is occurring and help predict how far it may move. We have been dabbling with and are planning on releasing a Strategy based on this Indicator shortly.
Settings:
1. Momentum:
Show Signals: Sometimes it can be difficult to visualize the zones with signals enabled.
Factor Volume: Factor Volume only applies to Overly Bullish and Bearish Signals. It's when the Volume is > VWMA Volume over the Smoothing Length.
Zone Inside Length: The Zone Inside is the Inner zone of the High and Low. This is the length used to create it.
Zone Outside Length: The Zone Outside is the Outer zone of the High and Low. This is the length used to create it.
Smoothing length: Smoothing length is the length used to smooth out our Bullish and Bearish signals, along with our Overly Bullish and Overly Bearish Signals.
2. Kernel Settings:
Lookback Window: The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars. Recommended range: 3-50.
Relative Weighting: Relative weighting of time frames. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel. Recommended range: 0.25-25.
Start Regression at Bar: Bar index on which to start regression. The first bars of a chart are often highly volatile, and omission of these initial bars often leads to a better overall fit. Recommended range: 5-25.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Value At RiskThe Value at Risk Channel (VaR Channel) is a trading indicator designed to assist traders in managing their risk exposure effectively. By allowing users to select a specific time period and a probability value, this indicator generates upper and lower limits that the price might potentially attain within the chosen timeframe and probability range.
CONCEPTS
This indicator employs the concept of Value at Risk (VaR) calculation, a crucial metric in risk management. VaR quantifies the potential financial loss within a position, portfolio, or company over a defined time period. Financial institutions like banks and investment firms use VaR to estimate the extent and likelihood of potential losses in their portfolios.
The "historical method" is utilized to compute VaR within the indicator. This method analyzes the historical performance of returns and constructs a histogram representing the statistical distribution of past returns. Assuming returns adhere to a normal distribution, probabilities are assigned to different return values based on their position in the distribution percentile.
HOW TO USE
Suppose you wish to plot upper and lower price limits for a 4-hour period with a 5% probability. Access the indicator's Settings tab and set the Timeframe parameter to "4 hours" while configuring the Probability parameter to 5.0.
The indicator serves as a tool to determine appropriate Stop-Loss levels triggering with low probability. Additionally, it helps gauge the likelihood of triggering such levels.
Likewise, you can assess the probability of your desired Take-Profit level being reached within a specified time frame. For instance, if you anticipate your target to be achieved within a week, set the Timeframe parameter to "1 week" and adjust the Probability parameter to align the VaR channel's limits with your Take-Profit level. The resulting Probability parameter value reflects the likelihood of your target being met within the expected time frame.
This indicator proves valuable for evaluating and managing risk, as well as refining trading strategies. If you discover other applications for this indicator, feel free to share them in the comments!
SETTINGS
Timeframe: Designates the time period within which the price might touch the VaR channel's upper or lower boundary, considering the specified Probability parameter.
Probability: Defines the likelihood of the price reaching the VaR channel's upper or lower limit during the timeframe determined by the Timeframe parameter.
Window: Establishes the historical period (number of past bars) utilized for VaR calculation.
Fair value bands / quantifytools— Overview
Fair value bands, like other band tools, depict dynamic points in price where price behaviour is normal or abnormal, i.e. trading at/around mean (price at fair value) or deviating from mean (price outside fair value). Unlike constantly readjusting standard deviation based bands, fair value bands are designed to be smooth and constant, based on typical historical deviations. The script calculates pivots that take place above/below fair value basis and forms median deviation bands based on this information. These points are then multiplied up to 3, representing more extreme deviations.
By default, the script uses OHLC4 and SMA 20 as basis for the bands. Users can form their preferred fair value basis using following options:
Price source
- Standard OHLC values
- HL2 (High + low / 2)
- OHLC4 (Open + high + low + close / 4)
- HLC3 (High + low + close / 3)
- HLCC4 (High + low + close + close / 4)
Smoothing
- SMA
- EMA
- HMA
- RMA
- WMA
- VWMA
- Median
Once fair value basis is established, some additional customization options can be employed:
Trend mode
Direction based
Cross based
Trend modes affect fair value basis color that indicates trend direction. Direction based trend considers only the direction of the defined fair value basis, i.e. pointing up is considered an uptrend, vice versa for downtrend. Cross based trends activate when selected source (same options as price source) crosses fair value basis. These sources can be set individually for uptrend/downtrend cross conditions. By default, the script uses cross based trend mode with low and high as sources.
Cross based (downtrend not triggered) vs. direction based (downtrend triggered):
Threshold band
Threshold band is calculated using typical deviations when price is trading at fair value basis. In other words, a little bit of "wiggle room" is added around the mean based on expected deviation. This feature is useful for cross based trends, as it allows filtering insignificant crosses that are more likely just noise. By default, threshold band is calculated based on 1x median deviation from mean. Users can increase/decrease threshold band width via input menu for more/less noise filtering, e.g. 2x threshold band width would require price to cross wiggle room that is 2x wider than typical, 0x erases threshold band altogether.
Deviation bands
Width of deviation bands by default is based on 1x median deviations and can be increased/decreased in a similar manner to threshold bands.
Each combination of customization options produces varying behaviour in the bands. To measure the behaviour and finding fairest representation of fair and unfair value, some data is gathered.
— Fair value metrics
Space between each band is considered a lot, named +3, +2, +1, -1, -2, -3. For each lot, time spent and volume relative to volume moving average (SMA 20) is recorded each time price is trading in a given lot:
Depending on the asset, timeframe and chosen fair value basis, shape of the distributions vary. However, practically always time is distributed in a normal bell curve shape, being highest at lots +1 to -1, gradually decreasing the further price is from the mean. This is hardly surprising, but it allows accurately determining dynamic areas of normal and abnormal price behaviour (i.e. low risk area between +1 and -1, high risk area between +-2 to +-3). Volume on the other hand is typically distributed the other way around, being lowest at lots +1 to -1 and highest at +-2 to +-3. When time and volume are distributed like so, we can conclude that 1) price being outside fair value is a rare event and 2) the more price is outside fair value, the more anomaly behaviour in volume we tend to find.
Viewing metric calculations
Metric calculation highlights can be enabled from the input menu, resulting in a lot based coloring and visibility of each lot counter (time, cumulative relative volume and average relative volume) in data window:
— Alerts
Available alerts are the following:
Individual
- High crossing deviation band (bands +1 to +3 )
- Low crossing deviation band (bands -1 to -3 )
- Low at threshold band in an uptrend
- High at threshold band in a downtrend
- New uptrend
- New downtrend
Grouped
- New uptrend or downtrend
- Deviation band cross (+1 or -1)
- Deviation band cross (+2 or -2)
- Deviation band cross (+3 or -3)
— Practical guide
Example #1 : Risk on/risk off trend following
Ideal trend stays inside fair value and provides sufficient cool offs between the moves. When this is the case, fair value bands can be used for sensible entry/exit levels within the trend.
Example #2 : Mean reversions
When price shows exuberance into an extreme deviation, followed by a stall and signs of exhaustion (wicks), an opportunity for mean reversion emerges. The higher the deviation, the more volatility in the move, the more signalling of exhaustion, the better.
Example #3 : Tweaking bands for desired behaviour
The faster the length of fair value basis, the more momentum price needs to hit extreme deviation levels, as bands too are moving faster alongside price. Decreasing fair value basis length typically leads to more quick and aggressive deviations and less steady trends outside fair value.
pricing_tableThis script helps you evaluate the fair value of an option. It poses the question "if I bought or sold an option under these circumstances in the past, would it have expired in the money, or worthless? What would be its expected value, at expiration, if I opened a position at N standard deviations, given the volatility forecast, with M days to expiration at the close of every previous trading day?"
The default (and only) "hv" volatility forecast is based on the assumption that today's volatility will hold for the next M days.
To use this script, only one step is mandatory. You must first select days to expiration. The script will not do anything until this value is changed from the default (-1). These should be CALENDAR days. The script will convert to these to business days for forecasting and valuation, as trading in most contracts occurs over ~250 business days per year.
Adjust any other variables as desired:
model: the volatility forecasting model
window: the number of periods for a lagged model (e.g. hv)
filter: a filter to remove forecasts from the sample
filter type: "none" (do not use the filter), "less than" (keep forecasts when filter < volatility), "greater than" (keep forecasts when filter > volatility)
filter value: a whole number percentage. see example below
discount rate: to discount the expected value to present value
precision: number of decimals in output
trim outliers: omit upper N % of (generally itm) contracts
The theoretical values are based on history. For example, suppose days to expiration is 30. On every bar, the 30 days ago N deviation forecast value is compared to the present price. If the price is above the forecast value, the contract has expired in the money; otherwise, it has expired worthless. The theoretical value is the average of every such sample. The itm probabilities are calculated the same way.
The default (and only) volatility model is a 20 period EWMA derived historical (realized) volatility. Feel free to extend the script by adding your own.
The filter parameters can be used to remove some forecasts from the sample.
Example A:
filter:
filter type: none
filter value:
Default: the filter is not used; all forecasts are included in the the sample.
Example B:
filter: model
filter type: less than
filter value: 50
If the model is "hv", this will remove all forecasts when the historical volatility is greater than fifty.
Example C:
filter: rank
filter type: greater than
filter value: 75
If the model volatility is in the top 25% of the previous year's range, the forecast will be included in the sample apart from "model" there are some common volatility indexes to choose from, such as Nasdaq (VXN), crude oil (OVX), emerging markets (VXFXI), S&P; (VIX) etc.
Refer to the middle-right table to see the current forecast value, its rank among the last 252 days, and the number of business days until
expiration.
NOTE: This script is meant for the daily chart only.
RSI-VWAP Indicator %█ OVERALL
Simple and effective script that, as you already know, uses vwap as source of the rsi, and with good results as long as the market has no long-term downtrend.
RsiVwap = rsi (vwap (close), Length)
The default settings are for BTC in a 30 minute time frame. For other pairs and time frames you just have to play with the settings.
█ FEATURES
• The option to start trading from a certain date has been added.
• To make the profit more progressive, a percentage of your equity is used for entries and a percentage of your position is used for closings.
• The option to trade in Spot mode has been added, since, for the TradingView backtest, the money is infinite and if you do not limit it somehow,
it would offer you much better profits than the live trading.
QuantityOnLong = Spot ? (EquityPercent / 100) * ((strategy.equity / close) - strategy.position_size) : (EquityPercent / 100) * (strategy.equity / close)
• The option to stop the system when the drawdown exceeds the fixed limit has been added.
Drawdown, as you already know, is a very important measure of risk in trading systems.
The maximum drawdown will tell us what the maximum loss of a trading system has been during a period. This maximum loss is determined by:
strategy.risk.max_drawdown(Risk, strategy.percent_of_equity)
• Leverage plotted on labels added.
█ ALERTS
To enjoy the benefits of automatic trading, TradingView alerts can be used as direct buy-sell orders on spot, or long-close orders with leverage.
Currently there are Chrome extensions that act as a bridge between TradingView and your Exchange or Broker.
This is an example of syntax for this type of extensions. Copy and paste a message like this into the alert window:
{{strategy.order.action}} @ {{strategy.order.price}} | e = {{exchange}} a = account s = {{ticker}} b = {{strategy.order.action}} {{strategy.order.alert_message}}
█ NOTE
Certain Risks of Live Algorithmic Trading You Should Know:
• Backtesting cannot assure actual results.
• The relevant market might fail or behave unexpectedly.
• Your broker may experience failures in its infrastructure, fail to execute your orders in a correct or timely fashion or reject your orders.
• The system you use for generating trading orders, communicating those orders to your broker, and receiving queries and trading results from your broker may fail.
• Time lag at various point in live trading might cause unexpected behavior.
• The systems of third parties in addition to those of the provider from which we obtain various services, your broker, and the applicable securities market may fail or malfunction.
█ THANKS
Thanks to TradingView, its Pine code, its community and especially those Pine wizards who post their ideas that helps us to learn.
If the world is heading toward a equitable new world economic order, let's get rich first ...
Happy trading!
Rolling midpointsThe script made for research purposes which plots these statistics of a given window: Mid-range (max + min)/2, Lower midpoint (mid-range + min)/2, and Higher midpoint (mid-range + max)/2.
This could be interesting when checking periods with sample size <= 0, or checking distros with srs kurtosis values.
Mean & median are also there.
Percentage Change Comparison [BVCC]This script allows you to input 2 different coins and plot % changes against each other.
Look Back is adjustable to account for different time frame windows. Default is 1, so each line will be graphed on a 1:1 ratio with the candle period selected on the chart. raising this number to 24 will plot the change across every 24 candles and so on. It's pretty interesting to move the input dialogue window out of the way and change this number, watching how the % gain comparisons change in real time.
Default coins to compare are set to BTCUSD and ETHUSD @ coinbase.
GMO (Gyroscopic Momentum Oscillator) GMO
Overview
This indicator fuses multiple advanced concepts to give traders a comprehensive view of market momentum, volatility, and potential turning points. It leverages the Gyroscopic Momentum Oscillator (GMO) foundation and layers on IQR-based bands, dynamic ATR-adjusted OB/OS levels, torque filtering, and divergence detection. The outcome is a versatile tool that can assist in identifying both short-term squeezes and long-term reversal zones while detecting subtle shifts in momentum acceleration.
Key Components:
Gyroscopic Momentum Oscillator (GMO) – A physics-inspired metric capturing trend stability and momentum by treating price dynamics as “angle,” “angular velocity,” and “inertia.”
IQR Bands – Highlight statistically typical oscillation ranges, providing insight into short-term squeezes and potential near-term trend shifts.
ATR-Adjusted OB/OS Levels – Dynamic thresholds for overbought/oversold conditions, adapting to volatility, aiding in identifying long-term potential reversal zones.
Torque Filtering & Scaling – Smooths and thresholds torque (the rate of change of momentum) and visually scales it for clarity, indicating sudden force changes that may precede volatility adjustments.
Divergence Detection – Highlights potential reversal cues by comparing oscillator swings against price swings, revealing regular and hidden bullish/bearish divergences.
Conceptual Insights
IQR Bands (Short-Term Squeeze & Trend Direction):
Short-Term Momentum and Squeeze: The IQR (Interquartile Range) bands show where the oscillator tends to “live” statistically. When the GMO line hovers within compressed IQR bands, it can signal a momentum squeeze phase. Exiting these tight ranges often correlates with short-term breakout opportunities.
Trend Reversals: If the oscillator pushes beyond these IQR ranges, it may indicate an emerging short-term trend change. Traders can watch for GMO escaping the IQR “comfort zone” to anticipate a new directional move.
Dynamic OB/OS Levels (Long-Term Reversal Zones):
ATR-Based Adaptive Thresholds: Instead of static overbought/oversold lines, this tool uses ATR to adjust OB/OS boundaries. In calm markets, these lines remain closer to ±90. As volatility rises, they approach ±100, reflecting greater permissible swings.
Long-Term Trend Reversal Potential: If GMO hits these dynamically adjusted OB/OS extremes, it suggests conditions ripe for possible long-term trend reversals. Traders seeking major inflection points may find these adaptive levels more reliable than fixed thresholds.
Torque (Sudden Force & Directional Shifts):
Momentum Acceleration Insight: Torque represents the second derivative of momentum, highlighting how quickly momentum is changing. High positive torque suggests a rapidly strengthening bullish force, while high negative torque warns of sudden bearish pressure.
Early Warning & Stability/Volatility Adjustments: By monitoring torque spikes, traders can anticipate momentum shifts before price fully confirms them. This can signal imminent changes in stability or increased volatility phases.
Indicator Parameters and Usage
GMO-Related Inputs:
lenPivot (Default 100): Length for calculating the pivot line (slow market axis).
lenSmoothAngle (Default 200): Smooths the angle measure, reducing noise.
lenATR (Default 14): ATR period for scaling factor, linking price changes to volatility.
useVolatility (Default true): If true, volatility (ATR) influences inertia, adjusting momentum calculations.
useVolume (Default false): If true, volume affects inertia, adding a liquidity dimension to momentum.
lenVolSmoothing (Default 50): Smooths volume calculations if useVolume is enabled.
lenMomentumSmooth (Default 20): EMA smoothing of GMO for a cleaner oscillator line.
normalizeRange (Default true): Normalizes GMO to a fixed range for consistent interpretation.
lenNorm (Default 100): Length for normalization window, ensuring GMO’s scale adapts to recent extremes.
IQR Bands Settings:
iqrLength (Default 14): Period to compute the oscillator’s statistical IQR.
iqrMult (Default 1.5): Multiplier to define the upper and lower IQR-based bands.
ATR-Adjusted OB/OS Settings:
baseOBLevel (Fixed at 90) and baseOSLevel (Fixed at 90): Base lines for OB/OS.
atrPeriodForOBOS (Default 50): ATR length for adjusting OB/OS thresholds dynamically.
atrScaling (Default 0.2): Controls how strongly volatility affects OB/OS lines.
Torque Filtering & Visualization:
torqueSmoothLength (Default 10): EMA length to smooth raw torque values.
atrPeriodForTorque (Default 14): ATR period to determine torque threshold.
atrTorqueScaling (Default 0.5): Scales ATR for determining torque’s “significant” threshold.
torqueScaleFactor (Default 10.0): Multiplies the torque values for better visual prominence on the chart.
Divergence Inputs:
showDivergences (Default true): Toggles divergence signals.
lbR, lbL (Defaults 5): Pivot lookback periods to identify swing highs and lows.
rangeUpper, rangeLower: Bar constraints to validate potential divergences.
plotBull, plotHiddenBull, plotBear, plotHiddenBear: Toggles for each divergence type.
Visual Elements on the Chart
GMO Line (Blue) & Zero Line (Gray):
GMO line oscillates around zero. Positive territory hints bullish momentum, negative suggests bearish.
IQR Bands (Teal Lines & Yellow Fill):
Upper/lower bands form a statistical “normal range” for GMO. The median line (purple) provides a central reference. Contraction near these bands indicates a short-term squeeze, expansions beyond them can signal emerging short-term trend changes.
Dynamic OB/OS (Red & Green Lines):
Red line near +90 to +100: Overbought zone (dynamic).
Green line near -90 to -100: Oversold zone (dynamic).
Movement into these zones may mark significant, longer-term reversal potential.
Torque Histogram (Colored Bars):
Plotted below GMO. Green bars = torque above positive threshold (bullish acceleration).
Red bars = torque below negative threshold (bearish acceleration).
Gray bars = neutral range.
This provides early warnings of momentum shifts before price responds fully.
Precession (Orange Line):
Scaled for visibility, adds context to long-term angular shifts in the oscillator.
Divergence Signals (Shapes):
Circles and offset lines highlight regular or hidden bullish/bearish divergences, offering potential reversal signals.
Practical Interpretation & Strategy
Short-Term Opportunities (IQR Focus):
If GMO compresses within IQR bands, the market might be “winding up.” A break above/below these bands can signal a short-term trade opportunity.
Long-Term Reversal Zones (Dynamic OB/OS):
When GMO approaches these dynamically adjusted extremes, conditions may be ripe for a major trend shift. This is particularly useful for swing or position traders looking for significant turnarounds.
Monitoring Torque for Acceleration Cues:
Torque spikes can precede price action, serving as an early catalyst signal. If torque turns strongly positive, anticipate bullish acceleration; strongly negative torque may warn of upcoming bearish pressure.
Confirm with Divergences:
Divergences between price and GMO reinforce potential reversal or continuation signals identified by IQR, OB/OS, or torque. Use them to increase confidence in setups.
Tips and Best Practices
Combine with Price & Volume Action:
While the indicator is powerful, always confirm signals with actual price structure, volume patterns, or other trend-following tools.
Adjust Lengths & Periods as Needed:
Shorter lengths = more responsiveness but more noise. Longer lengths = smoother signals but greater lag. Tune parameters to match your trading style and timeframe.
Use ATR and Volume Settings Wisely:
If markets are highly volatile, consider useVolatility to refine momentum readings. If liquidity is key, enable useVolume.
Scaling Torque:
If torque bars are hard to read, increase torqueScaleFactor further. The scaling doesn’t affect logic—only visibility.
Conclusion
The “GMO + IQR Bands + ATR-Adjusted OB/OS + Torque Filtering (Scaled)” indicator presents a holistic framework for understanding market momentum across multiple timescales and conditions. By interpreting short-term squeezes via IQR bands, long-term reversal zones via adaptive OB/OS, and subtle acceleration changes through torque, traders can gain advanced insights into when to anticipate breakouts, manage risk around potential reversals, and fine-tune timing for entries and exits.
This integrated approach helps navigate complex market dynamics, making it a valuable addition to any technical analysis toolkit.
base16Library "base16"
Base16 Syntax Theme Collection. dark/light Pairs placed into 2 matched groups.
included is tool for assembling your own themes, as well as all themes String names
to create your own Input menus / add to your own theme matrix, and theme selectors
addToMatrix(_mtx, _title, _choices, _theme)
To create a theme matrix with string index, use a color matrix global
add theme name to string array of theme titles
and last input a theme from above, or create your own theme arrays.
Parameters:
_mtx : (color ) matrix for storage
_title : (string ) Name of theme being added
_choices : (string ) name index
_theme : (color ) colors being added
Returns: void
addToMatrix(_mtx, _theme)
Add theme to color matrix Non-indexed
Parameters:
_mtx : (color ) matrix for storage
_theme : (color ) colors being added
dark()
Dark Themne Selection (With light Equivalent in same location)
Returns: Color matrix of dark themes
light()
light Themne Selection (With dark Equivalent in same location)
Returns: Color matrix of light themes
selectTheme(_mtx, _themes, _theme)
Get a Theme By Name
Parameters:
_mtx : (Matrix color) Name of Theme
_themes : (Array string) Array with Names of Themes
_theme : (string ) Name of Theme to select
selectTheme(_mtx, _theme)
Get a Theme By Number
Parameters:
_mtx : (Matrix color) Name of Theme
_theme : (int ) Number of Theme to select
/// all themes included:
3024
apathy
apprentice
ashes
atelier_cave_light
atelier_cave
atelier_dune_light
atelier_dune
atelier_estuary_light
atelier_estuary
atelier_forest_light
atelier_forest
atelier_heath_light
atelier_heath
atelier_lakeside_light
atelier_lakeside
atelier_plateau_light
atelier_plateau
atelier_savanna_light
atelier_savanna
atelier_seaside_light
atelier_seaside
atelier_sulphurpool_light
atelier_sulphurpool
atlas
ayu_dark
ayu_light
ayu_mirage
bespin
black_metal_bathory
black_metal_burzum
black_metal_dark_funeral
black_metal_gorgoroth
black_metal_immortal
black_metal_khold
black_metal_marduk
black_metal_mayhem
black_metal_nile
black_metal_venom
black_metal
blue_forest
blueish
brewer
bright
brogrammer
brush_trees_dark
brush_trees
catppuccin
chalk
circus
classic_dark
classic_light
codeschool
clrs
cupcake
cupertino
da_one_black
da_one_gray
da_one_ocean
da_one_paper
da_one_sea
da_one_white
danqing_light
danqing
darcula
darkmoss
darktooth
dark_violet
decaf
default_dark
default_light
dirtysea
dracula
edge_dark
edge_light
eighties
embers
emil
equilibrium_dark
equilibrium_gray_dark
equilibrium_gray_light
equilibrium_light
espresso
eva_dim
eva
everforest
flat
framer
fruit_soda
gigavolt
github
google_dark
google_light
gotham
grayscale_dark
grayscale_light
green_screen
gruber
gruvbox_dark_hard
gruvbox_dark_medium
gruvbox_dark_pale
gruvbox_dark_soft
gruvbox_light_hard
gruvbox_light_medium
gruvbox_light_soft
gruvbox_material_dark_hard
gruvbox_material_dark_medium
gruvbox_material_dark_soft
gruvbox_material_light_hard
gruvbox_material_light_medium
gruvbox_material_light_soft
hardcore
harmonic16_dark
harmonic16_light
heetch_light
heetch_dark
helios
hopscotch
horizon_dark
horizon_light
horizon_terminal_dark
horizon_terminal_light
humanoid_dark
humanoid_light
ia_dark
ia_light
icy_dark
ir_black
isotope
kanagawa
katy
kimber
lime
macintosh
marrakesh
materia
material_darker
material_lighter
material_palenight
material_vivid
material
mellow_purple
mexico_light
mocha
monokai
Nebula
nord
nova
ocean
oceanicnext
one_light
onedark
outrun_dark
pandora
papercolor_dark
papercolor_light
paraiso
pasque
phd
pico
pinky
pop
porple
primer_dark_dimmed
primer_dark
primer_light
purpledream
qualia
railscasts
rebecca
rose_pine_dawn
rose_pine_moon
rose_pine
sagelight
sakura
sandcastle
seti_ui
shades_of_purple
shadesmear_dark
shadesmear_light
shapeshifter
silk_dark
silk_light
snazzy
solar_flare_light
solar_flare
solarized_dark
solarized_light
spaceduck
spacemacs
stella
still_alive
summercamp
summerfruit_dark
summerfruit_light
synth_midnight_terminal_dark
synth_midnight_terminal_light
tango
tender
tokyo_city_dark
tokyo_city_light
tokyo_city_terminal_dark
tokyo_city_terminal_light
tokyo_night_dark
tokyo_night_light
tokyo_night_storm
tokyo_night_terminal_dark
tokyo_night_terminal_light
tokyo_night_terminal_storm
tokyodark_terminal
tokyodark
tomorrow_night_eighties
tomorrow_night
tomorrow
london_tube
twilight
unikitty_dark
unikitty_light
unikitty_reversible
uwunicorn
vice
vulcan
windows_10_light
windows_10
windows_95_light
windows_95
windows_high_contrast_light
windows_high_contrast
windows_nt_light
windows_nt
woodland
xcode_dusk
zenburn
Alternate Hourly HighlightAlternate Hourly Highlight
This indicator automatically highlights every alternate one-hour window on your chart, making it easy to visually identify and separate each trading hour. The background alternates color every hour, helping traders spot hourly cycles, session changes, or develop time-based trading strategies.
Works on any timeframe.
No inputs required—just add to your chart and go!
Especially useful for intraday traders who analyze price action, volatility, or volume by the hour.
For custom colors or session windows, feel free to modify the script!
NY HIGH LOW BREAKNY HIGH LOW BREAK: A New York Session Breakout Strategy
The "NY HIGH LOW BREAK" indicator is a powerful TradingView script designed to identify and capitalize on breakout opportunities during the New York trading session. This strategy focuses on the initial price action of the New York market open, looking for clear breaches of the high or low established within the first 30 minutes. It's particularly suited for intraday traders who seek to capture momentum-driven moves.
Strategy Logic
The core of the "NY HIGH LOW BREAK" strategy revolves around these key components:
New York Session Opening Range Identification:
The script first identifies the opening range of the New York session. This is defined by the high and low prices established during the first 30 minutes of the New York trading session (from 7:01 AM GMT-4 to 7:31 AM GMT-4).
These crucial levels are then extended forward on the chart as horizontal lines, serving as potential support and resistance zones.
Breakout Signal Generation:
Long Signal: A buy signal is generated when the price breaks above the high of the New York opening range. Specifically, it looks for a candle whose open and close are both above the highLinePrice, and importantly, the previous candle's open was below and close was above the highLinePrice. This indicates a strong upward momentum confirming the breakout.
Short Signal: Conversely, a sell signal is generated when the price breaks below the low of the New York opening range. It looks for a candle whose open and close are both below the lowLinePrice, and the previous candle's open was above and close was below the lowLinePrice. This suggests strong downward momentum confirming the breakdown.
Supertrend Filter (Implicit/Future Enhancement):
While the supertrend and direction variables are present in the code, they are not actively used in the current signal generation logic. This suggests a potential future enhancement where the Supertrend indicator could be incorporated as a trend filter to confirm breakout directions, adding an extra layer of confluence to the signals. For example, only taking long breakouts when Supertrend indicates an uptrend, and short breakouts when Supertrend indicates a downtrend.
Second Candle Confirmation (Possible Future Enhancement):
The close_sec_candle function and openSEC, closeSEC variables indicate an attempt to capture the open and close of a "second candle" (30 minutes after the initial New York open). Currently, closeSEC is used in a specific condition for signal_way but not directly in the primary longSignal or shortSignal logic. This also suggests a potential future refinement where the price action of this second candle could be used for further confirmation or specific entry criteria.
Time-Based Filtering:
Signals are only considered valid within a specific trading window from 8:00 AM GMT-4 to 8:00 AM GMT-4 + 16 * 30 minutes (which is 480 minutes, or 8 hours) on 1-minute and 5-minute timeframes. This ensures that trades are taken during the most active and volatile periods of the New York session, avoiding late-session chop.
The script also highlights the New York session and lunch hours using background colors, providing visual context to the trading day.
Key Features
Automated New York Open Range Detection: The script automatically identifies and plots the high and low of the first 30 minutes of the New York trading session.
Clear Breakout Signals: Visually distinct "BUY" and "SELL" labels appear on the chart when a breakout occurs, making it easy to spot trading opportunities.
Timeframe Adaptability: While optimized for 1-minute and 5-minute timeframes for signal generation, the opening range lines can be displayed on various timeframes.
Customizable Risk-to-Reward (RR): The rr input allows users to define their preferred risk-to-reward ratio for potential trades, although it's not directly implemented in the current signal or trade management logic. This could be used by traders for manual trade management.
Visual Session and Lunch Highlights: The script colors the background to clearly delineate the New York trading session and the lunch break, helping traders understand the market context.
How to Use
Apply the Indicator: Add the "NY HIGH LOW BREAK" indicator to your chart on TradingView.
Select a Relevant Timeframe: For optimal signal generation, use 1-minute or 5-minute timeframes.
Observe the Opening Range: The green and red lines represent the high and low of the first 30 minutes of the New York session.
Look for Breakouts: Wait for price to decisively break above the green line (for a buy) or below the red line (for a sell).
Confirm Signals: The "BUY" or "SELL" labels will appear on the chart when the breakout conditions are met within the active trading window.
Implement Your Risk Management: Use your preferred risk management techniques, including stop-loss and take-profit levels, in conjunction with the signals generated. The rr input can guide your manual risk-to-reward calculations.
Potential Enhancements & Considerations
Supertrend Confirmation: Integrating the supertrend variable to filter signals would significantly enhance the strategy's robustness by aligning trades with the prevailing trend.
Stop-Loss and Take-Profit Automation: The rr input currently serves as a manual guide. Future versions could integrate automated stop-loss and take-profit placement based on this ratio, potentially using ATR for dynamic sizing.
Volume Confirmation: Adding a volume filter to confirm breakouts would ensure that only high-conviction moves are traded.
Backtesting and Optimization: Thorough backtesting across various assets and market conditions is crucial to determine the optimal settings and profitability of this strategy.
Session Times: The current session times are hardcoded. Making these user-definable inputs would allow for greater flexibility across different time zones and trading preferences.
The "NY HIGH LOW BREAK" is a straightforward yet effective strategy for capturing initial New York session momentum. By focusing on clear breakout levels, it aims to provide timely and actionable trading signals for intraday traders.
Marcin Bitcoin📊 Core Logic and Conditions
✅ Entry Condition (Long):
Buy signal occurs when all of the following are true:
🔼 Uptrend — The centerline of the Gaussian filter (filt) is going up.
💥 Breakout — The current price is above the upper band of the Gaussian channel (close > hband).
⚡ Momentum — The Stochastic RSI %K is greater than 80, meaning the price is in a strong overbought zone (indicating strong momentum).
📅 Within the Date Range — The current bar is within the selected backtest window.
➡️ If all are true, the strategy enters a long position.
❌ Exit Condition (Close Position):
Sell signal (close position) occurs when:
The price crosses below the upper band (crossunder(close, hband))
Within the selected time window
➡️ This acts as a trailing stop — the position is held as long as the price stays above the breakout band.
🧠 Why It Might Work
The strategy tries to catch strong upward breakouts with high momentum.
It avoids chop and sideways moves by requiring:
Trend confirmation (filter rising),
Momentum confirmation (Stoch > 80),
Breakout (price > upper band)
Rifle UnifiedThis script is designed for use on 30-second charts of Dow Jones-related symbols (YM, MYM, US30). It provides automated buy and sell signals using a combination of price action, RSI (Relative Strength Index), and volume analysis. The script is intended for both live trading signals and backtesting, with configurable risk management and debugging features.
Core Functionality
1. Signal Generation Logic
Trigger: The algorithm looks for a sharp price move (drop or rise) of a user-defined threshold (default: 80 points) within a specified lookback window (default: 20 minutes).
Levels: It monitors for price drops below specific numerical levels ending in 23, 43, or 73 (e.g., 42223, 42273).
RSI Condition: When price falls below one of these levels and the RSI is below 30, the setup is considered active.
Buy Signal: A buy is triggered if, after setup:
Price rises back above the level,
The RSI rate of change (ROC) indicates exhaustion of the drop,
The current bar shows positive momentum.
2. Trade Management
Stop Loss & Take Profit: Configurable fixed or trailing stop loss and take profit levels are plotted and managed automatically.
Exit Signals: The script signals exit based on price action relative to these risk management levels.
3. Filters & Enhancements
Parabolic Move Filter: Prevents entries during extreme price moves.
Dead Cat Bounce Filter: Avoids false signals after sharp reversals.
Volume Filter: Optionally requires volume conditions for trade entries (especially for shorts).
Multiple Confirmation Layers : Includes checks for 5-minute RSI, momentum, and price retracement.
User Inputs & Customization
Trade Direction: Toggle between LONG and SHORT signal generation.
Trigger Settings: Adjust thresholds for price moves, lookback windows, RSI ROC, and volume requirements.
Trade Settings: Set take profit, stop loss, and trailing stop behavior.
Debug & Visualization: Enable or disable various plots, labels, and debug tables for in-depth analysis.
Backtesting: Integrated backtester with summary and detailed statistics tables.
Technical Features
Uses External Libraries: Relies on RifleShooterLib for core logic and BackTestLib for backtesting and statistics.
Multi-timeframe Analysis: Incorporates both 30-second and 5-minute RSI calculations.
Chart Annotations: Plots entry/exit points, risk levels, and debug information directly on the chart.
Alert Conditions: Built-in alert triggers for key events (initial move, stall, entry).
Intended Use
Markets: Dow Jones symbols (YM, MYM, US30, or US30 CFD).
Timeframe: 30-second chart.
Purpose: Automated signal generation for discretionary or algorithmic trading, with robust risk management and backtesting support.
Notable Customization & Extension Points
Momentum Calculation: Plans to replace the current momentum measure with "sqz momentum".
Displacement Logic: Future update to use "FVG concept" for displacement.
High-Contrast RSI: Optional visual enhancements for RSI extremes.
Time-based Stop: Consideration for adding a time-based stop mechanism.
This script is highly modular, with extensive user controls, and is suitable for both live trading and historical analysis of Dow Jones index movements
BOR + 08:28BOR + TIME: Precision 1-Minute Opening Range Analysis
METHODOLOGY OVERVIEW
This indicator implements a proprietary time-based trading methodology that combines opening range analysis with precision timing algorithms designed exclusively for 1-minute charts during the New York trading session.
CORE ALGORITHM COMPONENTS
1. Bond Opening Range (BOR) Identification
- Captures the complete price range during 08:00-09:00 NY time
- Establishes the foundational trading range for the session
- Uses high-precision minute-level data to define exact boundaries
2. Critical Time Level Analysis (08:28 Candle)
- Identifies the 08:28-08:29 minute candle as a key reference point
- This specific timing represents a critical juncture before market open
- Captures the exact high/low range of this precise minute
3. Directional Bias Determination (09:00 Analysis)
- At exactly 09:00, compares current price position relative to 08:28 boundaries
- Above 08:28 High: Activates support-seeking mode (bullish bias)
- Below 08:28 Low: Activates resistance-seeking mode (bearish bias)
- Inside 08:28 Range: No directional bias established
4. Dynamic Standard Deviation Projections
- Uses the 08:28 candle range as the mathematical basis for standard deviation calculations
- Support Mode: Projects levels below 08:28 low using range multipliers (-1σ, -2σ, -3σ, -4σ)
- Resistance Mode: Projects levels above 08:28 high using range multipliers (+1σ, +2σ, +3σ, +4σ)
- Levels are active only during 09:00-10:30 trading window
UNIQUE FEATURES
Conditional Logic Engine
- Real-time directional switching based on 09:00 price position
- No static levels - everything adapts to intraday price action
- Eliminates noise by focusing on specific time windows
Precision Timing Requirements
- Requires exact 1-minute timeframe for accurate calculations
- Time-sensitive algorithm that relies on minute-by-minute analysis
- Optimized for high-frequency intraday trading decisions
Mathematical Framework
- Standard deviations calculated using actual candle range data
- Dynamic level spacing based on market volatility (08:28 range)
- Four-tier projection system for multiple target/stop levels
TRADING APPLICATION
Best Used For:
- ES, NQ, YM and other liquid index futures
- Active day trading during NY session (07:00-12:00)
- Scalping and short-term reversal strategies
- Intraday support/resistance identification
Signal Interpretation:
- Red lines represent potential reversal zones
- Direction determined by 09:00 vs 08:28 relationship
- Multiple standard deviation levels provide layered entry/exit points
- Time-restricted plotting ensures relevance during active trading hours
IMPORTANT REQUIREMENTS
- ONLY works on 1-minute charts - precision timing is essential
- Designed for New York trading session (futures markets)
- Most effective during high-volume trading periods
CUSTOMIZATION OPTIONS
- Toggle BOR box visibility and transparency
- Enable/disable 08:28 candle highlighting
- Adjust visual elements (colors, transparency)
- Show/hide range information labels
Momentum Regression [BackQuant]Momentum Regression
The Momentum Regression is an advanced statistical indicator built to empower quants, strategists, and technically inclined traders with a robust visual and quantitative framework for analyzing momentum effects in financial markets. Unlike traditional momentum indicators that rely on raw price movements or moving averages, this tool leverages a volatility-adjusted linear regression model (y ~ x) to uncover and validate momentum behavior over a user-defined lookback window.
Purpose & Design Philosophy
Momentum is a core anomaly in quantitative finance — an effect where assets that have performed well (or poorly) continue to do so over short to medium-term horizons. However, this effect can be noisy, regime-dependent, and sometimes spurious.
The Momentum Regression is designed as a pre-strategy analytical tool to help you filter and verify whether statistically meaningful and tradable momentum exists in a given asset. Its architecture includes:
Volatility normalization to account for differences in scale and distribution.
Regression analysis to model the relationship between past and present standardized returns.
Deviation bands to highlight overbought/oversold zones around the predicted trendline.
Statistical summary tables to assess the reliability of the detected momentum.
Core Concepts and Calculations
The model uses the following:
Independent variable (x): The volatility-adjusted return over the chosen momentum period.
Dependent variable (y): The 1-bar lagged log return, also adjusted for volatility.
A simple linear regression is performed over a large lookback window (default: 1000 bars), which reveals the slope and intercept of the momentum line. These values are then used to construct:
A predicted momentum trendline across time.
Upper and lower deviation bands , representing ±n standard deviations of the regression residuals (errors).
These visual elements help traders judge how far current returns deviate from the modeled momentum trend, similar to Bollinger Bands but derived from a regression model rather than a moving average.
Key Metrics Provided
On each update, the indicator dynamically displays:
Momentum Slope (β₁): Indicates trend direction and strength. A higher absolute value implies a stronger effect.
Intercept (β₀): The predicted return when x = 0.
Pearson’s R: Correlation coefficient between x and y.
R² (Coefficient of Determination): Indicates how well the regression line explains the variance in y.
Standard Error of Residuals: Measures dispersion around the trendline.
t-Statistic of β₁: Used to evaluate statistical significance of the momentum slope.
These statistics are presented in a top-right summary table for immediate interpretation. A bottom-right signal table also summarizes key takeaways with visual indicators.
Features and Inputs
✅ Volatility-Adjusted Momentum : Reduces distortions from noisy price spikes.
✅ Custom Lookback Control : Set the number of bars to analyze regression.
✅ Extendable Trendlines : For continuous visualization into the future.
✅ Deviation Bands : Optional ±σ multipliers to detect abnormal price action.
✅ Contextual Tables : Help determine strength, direction, and significance of momentum.
✅ Separate Pane Design : Cleanly isolates statistical momentum from price chart.
How It Helps Traders
📉 Quantitative Strategy Validation:
Use the regression results to confirm whether a momentum-based strategy is worth pursuing on a specific asset or timeframe.
🔍 Regime Detection:
Track when momentum breaks down or reverses. Slope changes, drops in R², or weak t-stats can signal regime shifts.
📊 Trade Filtering:
Avoid false positives by entering trades only when momentum is both statistically significant and directionally favorable.
📈 Backtest Preparation:
Before running costly simulations, use this tool to pre-screen assets for exploitable return structures.
When to Use It
Before building or deploying a momentum strategy : Test if momentum exists and is statistically reliable.
During market transitions : Detect early signs of fading strength or reversal.
As part of an edge-stacking framework : Combine with other filters such as volatility compression, volume surges, or macro filters.
Conclusion
The Momentum Regression indicator offers a powerful fusion of statistical analysis and visual interpretation. By combining volatility-adjusted returns with real-time linear regression modeling, it helps quantify and qualify one of the most studied and traded anomalies in finance: momentum.
Aetherium Institutional Market Resonance EngineAetherium Institutional Market Resonance Engine (AIMRE)
A Three-Pillar Framework for Decoding Institutional Activity
🎓 THEORETICAL FOUNDATION
The Aetherium Institutional Market Resonance Engine (AIMRE) is a multi-faceted analysis system designed to move beyond conventional indicators and decode the market's underlying structure as dictated by institutional capital flow. Its philosophy is built on a singular premise: significant market moves are preceded by a convergence of context , location , and timing . Aetherium quantifies these three dimensions through a revolutionary three-pillar architecture.
This system is not a simple combination of indicators; it is an integrated engine where each pillar's analysis feeds into a central logic core. A signal is only generated when all three pillars achieve a state of resonance, indicating a high-probability alignment between market organization, key liquidity levels, and cyclical momentum.
⚡ THE THREE-PILLAR ARCHITECTURE
1. 🌌 PILLAR I: THE COHERENCE ENGINE (THE 'CONTEXT')
Purpose: To measure the degree of organization within the market. This pillar answers the question: " Is the market acting with a unified purpose, or is it chaotic and random? "
Conceptual Framework: Institutional campaigns (accumulation or distribution) create a non-random, organized market environment. Retail-driven or directionless markets are characterized by "noise" and chaos. The Coherence Engine acts as a filter to ensure we only engage when institutional players are actively steering the market.
Formulaic Concept:
Coherence = f(Dominance, Synchronization)
Dominance Factor: Calculates the absolute difference between smoothed buying pressure (volume-weighted bullish candles) and smoothed selling pressure (volume-weighted bearish candles), normalized by total pressure. A high value signifies a clear winner between buyers and sellers.
Synchronization Factor: Measures the correlation between the streams of buying and selling pressure over the analysis window. A high positive correlation indicates synchronized, directional activity, while a negative correlation suggests choppy, conflicting action.
The final Coherence score (0-100) represents the percentage of market organization. A high score is a prerequisite for any signal, filtering out unpredictable market conditions.
2. 💎 PILLAR II: HARMONIC LIQUIDITY MATRIX (THE 'LOCATION')
Purpose: To identify and map high-impact institutional footprints. This pillar answers the question: " Where have institutions previously committed significant capital? "
Conceptual Framework: Large institutional orders leave indelible marks on the market in the form of anomalous volume spikes at specific price levels. These are not random occurrences but are areas of intense historical interest. The Harmonic Liquidity Matrix finds these footprints and consolidates them into actionable support and resistance zones called "Harmonic Nodes."
Algorithmic Process:
Footprint Identification: The engine scans the historical lookback period for candles where volume > average_volume * Institutional_Volume_Filter. This identifies statistically significant volume events.
Node Creation: A raw node is created at the mean price of the identified candle.
Dynamic Clustering: The engine uses an ATR-based proximity algorithm. If a new footprint is identified within Node_Clustering_Distance (ATR) of an existing Harmonic Node, it is merged. The node's price is volume-weighted, and its magnitude is increased. This prevents chart clutter and consolidates nearby institutional orders into a single, more significant level.
Node Decay: Nodes that are older than the Institutional_Liquidity_Scanback period are automatically removed from the chart, ensuring the analysis remains relevant to recent market dynamics.
3. 🌊 PILLAR III: CYCLICAL RESONANCE MATRIX (THE 'TIMING')
Purpose: To identify the market's dominant rhythm and its current phase. This pillar answers the question: " Is the market's immediate energy flowing up or down? "
Conceptual Framework: Markets move in waves and cycles of varying lengths. Trading in harmony with the current cyclical phase dramatically increases the probability of success. Aetherium employs a simplified wavelet analysis concept to decompose price action into short, medium, and long-term cycles.
Algorithmic Process:
Cycle Decomposition: The engine calculates three oscillators based on the difference between pairs of Exponential Moving Averages (e.g., EMA8-EMA13 for short cycle, EMA21-EMA34 for medium cycle).
Energy Measurement: The 'energy' of each cycle is determined by its recent volatility (standard deviation). The cycle with the highest energy is designated as the "Dominant Cycle."
Phase Analysis: The engine determines if the dominant cycles are in a bullish phase (rising from a trough) or a bearish phase (falling from a peak).
Cycle Sync: The highest conviction timing signals occur when multiple cycles (e.g., short and medium) are synchronized in the same direction, indicating broad-based momentum.
🔧 COMPREHENSIVE INPUT SYSTEM
Pillar I: Market Coherence Engine
Coherence Analysis Window (10-50, Default: 21): The lookback period for the Coherence Engine.
Lower Values (10-15): Highly responsive to rapid shifts in market control. Ideal for scalping but can be sensitive to noise.
Balanced (20-30): Excellent for day trading, capturing the ebb and flow of institutional sessions.
Higher Values (35-50): Smoother, more stable reading. Best for swing trading and identifying long-term institutional campaigns.
Coherence Activation Level (50-90%, Default: 70%): The minimum market organization required to enable signal generation.
Strict (80-90%): Only allows signals in extremely clear, powerful trends. Fewer, but potentially higher quality signals.
Standard (65-75%): A robust filter that effectively removes choppy conditions while capturing most valid institutional moves.
Lenient (50-60%): Allows signals in less-organized markets. Can be useful in ranging markets but may increase false signals.
Pillar II: Harmonic Liquidity Matrix
Institutional Liquidity Scanback (100-400, Default: 200): How far back the engine looks for institutional footprints.
Short (100-150): Focuses on recent institutional activity, providing highly relevant, immediate levels.
Long (300-400): Identifies major, long-term structural levels. These nodes are often extremely powerful but may be less frequent.
Institutional Volume Filter (1.3-3.0, Default: 1.8): The multiplier for detecting a volume spike.
High (2.5-3.0): Only registers climactic, undeniable institutional volume. Fewer, but more significant nodes.
Low (1.3-1.7): More sensitive, identifying smaller but still relevant institutional interest.
Node Clustering Distance (0.2-0.8 ATR, Default: 0.4): The ATR-based distance for merging nearby nodes.
High (0.6-0.8): Creates wider, more consolidated zones of liquidity.
Low (0.2-0.3): Creates more numerous, precise, and distinct levels.
Pillar III: Cyclical Resonance Matrix
Cycle Resonance Analysis (30-100, Default: 50): The lookback for determining cycle energy and dominance.
Short (30-40): Tunes the engine to faster, shorter-term market rhythms. Best for scalping.
Long (70-100): Aligns the timing component with the larger primary trend. Best for swing trading.
Institutional Signal Architecture
Signal Quality Mode (Professional, Elite, Supreme): Controls the strictness of the three-pillar confluence.
Professional: Loosest setting. May generate signals if two of the three pillars are in strong alignment. Increases signal frequency.
Elite: Balanced setting. Requires a clear, unambiguous resonance of all three pillars. The recommended default.
Supreme: Most stringent. Requires perfect alignment of all three pillars, with each pillar exhibiting exceptionally strong readings (e.g., coherence > 85%). The highest conviction signals.
Signal Spacing Control (5-25, Default: 10): The minimum bars between signals to prevent clutter and redundant alerts.
🎨 ADVANCED VISUAL SYSTEM
The visual architecture of Aetherium is designed not merely for aesthetics, but to provide an intuitive, at-a-glance understanding of the complex data being processed.
Harmonic Liquidity Nodes: The core visual element. Displayed as multi-layered, semi-transparent horizontal boxes.
Magnitude Visualization: The height and opacity of a node's "glow" are proportional to its volume magnitude. More significant nodes appear brighter and larger, instantly drawing the eye to key levels.
Color Coding: Standard nodes are blue/purple, while exceptionally high-magnitude nodes are highlighted in an accent color to denote critical importance.
🌌 Quantum Resonance Field: A dynamic background gradient that visualizes the overall market environment.
Color: Shifts from cool blues/purples (low coherence) to energetic greens/cyans (high coherence and organization), providing instant context.
Intensity: The brightness and opacity of the field are influenced by total market energy (a composite of coherence, momentum, and volume), making powerful market states visually apparent.
💎 Crystalline Lattice Matrix: A geometric web of lines projected from a central moving average.
Mathematical Basis: Levels are projected using multiples of the Golden Ratio (Phi ≈ 1.618) and the ATR. This visualizes the natural harmonic and fractal structure of the market. It is not arbitrary but is based on mathematical principles of market geometry.
🧠 Synaptic Flow Network: A dynamic particle system visualizing the engine's "thought process."
Node Density & Activation: The number of particles and their brightness/color are tied directly to the Market Coherence score. In high-coherence states, the network becomes a dense, bright, and organized web. In chaotic states, it becomes sparse and dim.
⚡ Institutional Energy Waves: Flowing sine waves that visualize market volatility and rhythm.
Amplitude & Speed: The height and speed of the waves are directly influenced by the ATR and volume, providing a feel for market energy.
📊 INSTITUTIONAL CONTROL MATRIX (DASHBOARD)
The dashboard is the central command console, providing a real-time, quantitative summary of each pillar's status.
Header: Displays the script title and version.
Coherence Engine Section:
State: Displays a qualitative assessment of market organization: ◉ PHASE LOCK (High Coherence), ◎ ORGANIZING (Moderate Coherence), or ○ CHAOTIC (Low Coherence). Color-coded for immediate recognition.
Power: Shows the precise Coherence percentage and a directional arrow (↗ or ↘) indicating if organization is increasing or decreasing.
Liquidity Matrix Section:
Nodes: Displays the total number of active Harmonic Liquidity Nodes currently being tracked.
Target: Shows the price level of the nearest significant Harmonic Node to the current price, representing the most immediate institutional level of interest.
Cycle Matrix Section:
Cycle: Identifies the currently dominant market cycle (e.g., "MID ") based on cycle energy.
Sync: Indicates the alignment of the cyclical forces: ▲ BULLISH , ▼ BEARISH , or ◆ DIVERGENT . This is the core timing confirmation.
Signal Status Section:
A unified status bar that provides the final verdict of the engine. It will display "QUANTUM SCAN" during neutral periods, or announce the tier and direction of an active signal (e.g., "◉ TIER 1 BUY ◉" ), highlighted with the appropriate color.
🎯 SIGNAL GENERATION LOGIC
Aetherium's signal logic is built on the principle of strict, non-negotiable confluence.
Condition 1: Context (Coherence Filter): The Market Coherence must be above the Coherence Activation Level. No signals can be generated in a chaotic market.
Condition 2: Location (Liquidity Node Interaction): Price must be actively interacting with a significant Harmonic Liquidity Node.
For a Buy Signal: Price must be rejecting the Node from below (testing it as support).
For a Sell Signal: Price must be rejecting the Node from above (testing it as resistance).
Condition 3: Timing (Cycle Alignment): The Cyclical Resonance Matrix must confirm that the dominant cycles are synchronized with the intended trade direction.
Signal Tiering: The Signal Quality Mode input determines how strictly these three conditions must be met. 'Supreme' mode, for example, might require not only that the conditions are met, but that the Market Coherence is exceptionally high and the interaction with the Node is accompanied by a significant volume spike.
Signal Spacing: A final filter ensures that signals are spaced by a minimum number of bars, preventing over-alerting in a single move.
🚀 ADVANCED TRADING STRATEGIES
The Primary Confluence Strategy: The intended use of the system. Wait for a Tier 1 (Elite/Supreme) or Tier 2 (Professional/Elite) signal to appear on the chart. This represents the alignment of all three pillars. Enter after the signal bar closes, with a stop-loss placed logically on the other side of the Harmonic Node that triggered the signal.
The Coherence Context Strategy: Use the Coherence Engine as a standalone market filter. When Coherence is high (>70%), favor trend-following strategies. When Coherence is low (<50%), avoid new directional trades or favor range-bound strategies. A sharp drop in Coherence during a trend can be an early warning of a trend's exhaustion.
Node-to-Node Trading: In a high-coherence environment, use the Harmonic Liquidity Nodes as both entry points and profit targets. For example, after a BUY signal is generated at one Node, the next Node above it becomes a logical first profit target.
⚖️ RESPONSIBLE USAGE AND LIMITATIONS
Decision Support, Not a Crystal Ball: Aetherium is an advanced decision-support tool. It is designed to identify high-probability conditions based on a model of institutional behavior. It does not predict the future.
Risk Management is Paramount: No indicator can replace a sound risk management plan. Always use appropriate position sizing and stop-losses. The signals provided are probabilistic, not certainties.
Past Performance Disclaimer: The market models used in this script are based on historical data. While robust, there is no guarantee that these patterns will persist in the future. Market conditions can and do change.
Not a "Set and Forget" System: The indicator performs best when its user understands the concepts behind the three pillars. Use the dashboard and visual cues to build a comprehensive view of the market before acting on a signal.
Backtesting is Essential: Before applying this tool to live trading, it is crucial to backtest and forward-test it on your preferred instruments and timeframes to understand its unique behavior and characteristics.
🔮 CONCLUSION
The Aetherium Institutional Market Resonance Engine represents a paradigm shift from single-variable analysis to a holistic, multi-pillar framework. By quantifying the abstract concepts of market context, location, and timing into a unified, logical system, it provides traders with an unprecedented lens into the mechanics of institutional market operations.
It is not merely an indicator, but a complete analytical engine designed to foster a deeper understanding of market dynamics. By focusing on the core principles of institutional order flow, Aetherium empowers traders to filter out market noise, identify key structural levels, and time their entries in harmony with the market's underlying rhythm.
"In all chaos there is a cosmos, in all disorder a secret order." - Carl Jung
— Dskyz, Trade with insight. Trade with confluence. Trade with Aetherium.
Red Report Filter x 'Bull_Trap_9'Hello Traders!
This one is my favorite.
This is indicator / filter: '2 of 2.'
'1 of 2' is the, 'Closed Market Filter,' I posted before this that you may like.
Again, I prefer 'Filter' over 'Indicator' because this Pine Script code does not interact with the actual price data.
It makes handling high impact reports effortless.
As you all know; if you're on a Prop and breach a 'Red,' you lose your account.
This will filter up to 5 reports. More than enough unless you're on EURUSD!
It offers both 'Red' and 'Orange' report control.
The default window times of 15 / 6 are programmed for red events. You can always alter the base code for your desired, 'Before / After.'
Click the tooltip for more info.
How to use:
You do need to update the inputs daily with the current report times before each open.
I trade YM / US markets. Those reports are very repetitive on their delivery times, so I usually leave a 10:00 setting in slot 1. I then toggle it 'On' or 'Off' per demand.
Just open the dialogue box and it is pretty self explanatory.
I used task scheduler for a lot of years, but that wasn't very reliable, modest work to set up daily and a lot of times I may not hear it or it malfunctions because of a Windows update.
TradingView has the little icon that floats from the bottom right, but who really looks for that.
Any audio alert is subject to fail for a number of reasons.
This filter REDS the screen in your face. Leaves no doubt about what's coming.
I know there may be other apps and options out there, but this filter is integral to the TradingView chart itself embedded through Pine Script. It is right there, a click away, easy to input data, and as long as your chart is active and working, the filter will fire.
I did not build an alert condition into this, but I'm sure that could be an option if you want to program in audio as well.
Please Note: Only when the price candles push into the filter zone, will the filter start to display. Run a test a minute from the current price candle and you can see how it functions.
I appreciate your interest.
Intraday & Annual CAPM AlphaIntraday & Annual CAPM Alpha
This TradingView™ Pine v6 indicator computes and plots a stock’s CAPM α (alpha) on both intraday and daily/annualized timeframes, allowing you to monitor relative performance against a chosen benchmark (e.g. SPX, NDX).
⸻
Key Outputs
1. Intraday α per Bar (blue line)
• Calculates α from a rolling-window linear regression of the last N bars’ returns (default 60).
• Expressed as “extra return per bar” vs. the benchmark.
2. Intraday α Daily-Equivalent (stepped blue line)
• Scales the per-bar α to a full trading day (390 minutes), showing “if this pace held all day, outperformance (%)”.
3. Annualized α (yellow line)
• Performs the same CAPM regression on daily returns over a D-day lookback (default 252), then annualizes α by multiplying by 252.
• Indicates longer-term relative strength/weakness vs. the benchmark.
⸻
Inputs
• Benchmark Symbol: Choose any index or ETF (e.g. “SPX”, “NDX”).
• Intraday Lookback Bars: Number of bars for intraday α regression (default 60).
• Daily Lookback Days: Number of trading days for daily CAPM regression (default 252).
• Use Log Returns?: Toggle between arithmetic vs. log returns.
⸻
How to Use
• Short-Term Signals:
• Watch the blue α/bar line on 1–15 min charts. A cross from negative to positive suggests intraday outperformance; a reversal warns of weakening momentum.
• The blue daily-equivalent α gives a smoother view—e.g. > +1% signals strong intraday bias, < –1% signals underperformance.
• Long-Term Trends:
• On daily charts, focus on the yellow annualized α. A sustained positive α implies this stock has historically beaten the benchmark; sustained negative α implies the opposite.
• Combining Timeframes:
• Use intraday α for timing entries/exits within the session, and annualized α to confirm whether you want a bullish or bearish bias over days to weeks.
⸻
Install & Configure
1. Copy the Pine v6 script into the TradingView Pine Editor.
2. Set your favorite benchmark, lookback periods, and returns type.
3. Add to your chart to start visualizing real-time CAPM α signals!
Feel free to adjust the lookback windows and threshold levels to suit your trading style.
Adaptive Signal Oscillator (ASO)📘 Adaptive Signal Oscillator (ASO)
A fully dynamic, self-calibrating oscillator that adapts to any asset or timeframe by optimizing for real-time signal stability and volatility structure — without relying on static parameters or hardcoded thresholds.
🔍 Overview
The Adaptive Signal Oscillator (ASO) is a next-generation technical analysis tool designed to provide context-aware long/short signals across crypto, equities, or forex markets. Unlike traditional oscillators (RSI, Stochastics, MACD), ASO requires no manual tuning of lookback periods or overbought/oversold zones — it self-optimizes based on current market behavior.
🧠 How It Works
✅ 1. Dynamic Lookback Optimization
ASO evaluates a range of lookback lengths between user-defined minLen and maxLen. For each length, it calculates the standard deviation of returns and finds the one with the least volatility change (i.e., the most stable structure). This length is dynamically assigned as bestLen, recalculated on every bar.
✅ 2. Multi-Layer Signal Composition
Four independent signal layers are computed using bestLen:
RSI Layer: Measures relative price strength via a custom dynamic RSI.
Z-Score Layer: Standardized deviation of price from its mean.
Volatility Layer: Standard deviation of log or percent returns.
Price Position Layer: Current price percentile within the lookback window.
Each of these layers is transformed into a percentile score scaled to the range .
✅ 3. Volatility-Based Weighting
The standard deviation (volatility) of each signal layer is computed. Less volatile layers are weighted more heavily, ensuring the final composite signal prioritizes stable, consistent inputs.
Weights are normalized and combined to form a composite score, representing a dynamically blended, noise-weighted signal across the four layers.
✅ 4. Optional Adaptive Smoothing
A boolean toggle lets users apply smoothing to the final score. The smoothing window scales proportionally to bestLen, preserving adaptiveness even during trend transitions.
✅ 5. Percentile-Based Thresholding
Rather than using arbitrary fixed thresholds, ASO converts the composite score into a ranked percentile. Long/short signals are then generated based on user-defined percentile bands, adapting naturally to each asset’s behavior.
📈 Interpreting ASO
Score > Threshold → Strong long signal (highlighted in aqua).
Score < Threshold → Strong short signal (highlighted in fuchsia).
Crossing h_thresh (e.g., 0) → Neutral-to-bias change; useful for early trend cues.
The background and label update in real time to reflect the current regime and bestLen.
⚙️ Inputs
minLen, maxLen, step: Define the search range for optimal lookback length.
retMethod: Choose between log or percent return calculations.
threshHigh, threshLow: Define signal zones using percentiles.
smooth: Enable dynamic score smoothing.
h_thresh: Midline crossover zone for directional context.
⚠️ Disclaimer
This tool is designed for exploratory and educational purposes only. It does not offer financial advice or trading recommendations. Past performance is not indicative of future results.
Always consult a licensed financial advisor before making investment decisions.
Chebyshev-Gauss Moving AverageThis indicator applies the principles of Chebyshev-Gauss Quadrature to create a novel type of moving average. Inspired by reading rohangautam.github.io
What is Chebyshev-Gauss Quadrature?
It's a numerical method to approximate the integral of a function f(x) that is weighted by 1/sqrt(1-x^2) over the interval . The approximation is a simple sum: ∫ f(x)/sqrt(1-x^2) dx ≈ (π/n) * Σ f(xᵢ) where xᵢ are special points called Chebyshev nodes.
How is this applied to a Moving Average?
A moving average can be seen as the "mean value" of the price over a lookback window. The mean value of a function with the Chebyshev weight is calculated as:
Mean = /
The math simplifies beautifully, resulting in the mean being the simple arithmetic average of the function evaluated at the Chebyshev nodes:
Mean = (1/n) * Σ f(xᵢ)
What's unique about this MA?
The Chebyshev nodes xᵢ are not evenly spaced. They are clustered towards the ends of the interval . We map this interval to our lookback period. This means the moving average samples prices more intensely from the beginning and the end of the lookback window, and less intensely from the middle. This gives it a unique character, responding quickly to recent changes while also having a long "memory" of the start of the trend.
PCA Regime-Adjusted MomentumSummary
The PCA Regime-Adjusted Momentum (PCA-RAM) is an advanced market analysis tool designed to provide nuanced insights into market momentum and structural stability. It moves beyond traditional indicators by using Principal Component Analysis (PCA) to deconstruct market data into its most essential patterns.
The indicator provides two key pieces of information:
A smoothed momentum signal based on the market's dominant underlying trend.
A dynamic regime filter that gauges the stability and clarity of the market's structure, advising you when to trust or fade the momentum signals.
This allows traders to not only identify potential shifts in momentum but also to understand the context and confidence behind those signals.
Core Concepts & Methodology
The strength of this indicator lies in its sound, data-driven methodology.
1. Principal Component Analysis (PCA)
At its core, the indicator analyzes a rolling window (default 50 periods) of standardized market data (Open, High, Low, Close, and Volume). PCA is a powerful statistical technique that distills this complex, 5-dimensional data into its fundamental, uncorrelated components of variance. We focus on the First Principal Component (PC1), which represents the single most dominant pattern or "theme" driving the market's behavior in the lookback window.
2. The Momentum Signal
Instead of just looking at price, we project the current market data onto this dominant underlying pattern (PC1). This gives us a raw "projection score" that measures how strongly the current bar aligns with the historically dominant market structure. This raw score is then smoothed using two an exponential moving averages (a fast and a slow line) to create a clear, actionable momentum signal, similar in concept to a MACD.
3. The Dynamic Regime Filter
This is arguably the indicator's most powerful feature. It answers the question: "How clear is the current market picture?"
It calculates the Market Concentration Ratio, which is the percentage of total market variance explained by PC1 alone.
A high ratio indicates that the market is moving in a simple, one-dimensional way (e.g., a clear, strong trend).
A low ratio indicates the market is complex, multi-dimensional, and choppy, with no single dominant theme.
Crucially, this filter is dynamic. It compares the current concentration ratio to its own recent average, allowing it to adapt to any asset or timeframe. It automatically learns what "normal" and "choppy" look like for the specific chart you are viewing.
How to Interpret the Indicator
The indicator is displayed in a separate pane with two key visual elements:
The Momentum Lines (White & Gold)
White Line: The "Fast Line," representing the current momentum.
Gold Line: The "Slow Line," acting as the trend confirmation.
Bullish Signal: A crossover of the White Line above the Gold Line suggests a shift to positive momentum.
Bearish Signal: A crossover of the White Line below the Gold Line suggests a shift to negative momentum.
The Regime Filter (Purple & Dark Red Background)
This is your confidence gauge.
Navy Blue Background (High Concentration): The market structure is stable, simple, and trending. Momentum signals are more reliable and should be given higher priority.
Dark Red Background (Low Concentration): The market structure is complex, choppy, or directionless. Momentum signals are unreliable and prone to failure or "whipsaws." This is a signal to be cautious, tighten stops, or potentially stay out of the market.
Potential Trading Strategies
This tool is versatile and can be used in several ways:
1. Primary Signal Strategy
Condition: Wait for the background to turn Purple, confirming a stable, high-confidence regime.
Entry: Take the next crossover signal from the momentum lines (White over Gold for long, White under Gold for short).
Exit/Filter: Consider exiting positions or ignoring new signals when the background turns Navy.
2. As a Confirmation or Filter for Your Existing Strategy
Do you have a trend-following system? Only enable its long and short signals when the PCA-RAM background is Purple.
Do you have a range-trading or mean-reversion system? It might be most effective when the PCA-RAM background is Navy, indicating a lack of a clear trend.
3. Advanced Divergence Analysis
Look for classic divergences between price and the momentum lines. For example, if the price is making a new high, but the Gold Line is making a lower high, it may indicate underlying weakness in the trend, even on a Purple background. This divergence signal is more powerful because it shows that the new price high is not being confirmed by the market's dominant underlying pattern.
