Twitter Model ICT [TradingFinder] MMXM ERL D + FVG + M15 MSS/SMT🔵 Introduction
The Twitter Model ICT is a trading approach based on ICT (Inner Circle Trader) models, focusing on price movement between external and internal liquidity in lower timeframes. This model integrates key concepts such as Market Structure Shift (MSS), Smart Money Technique (SMT) divergence, and CISD level break to identify precise entry points in the market.
The primary goal of this model is to determine key liquidity levels, such as the previous day’s high and low (PDH/PDL) and align them with the Fair Value Gap (FVG) in the 1-hour timeframe. The overall strategy involves framing trades around the 1H FVG and using the M15 Market Structure Shift (MSS) for entry confirmation.
The Twitter Model ICT is designed to utilize external liquidity levels, such as PDH/PDL, as key entry zones. The model identifies FVG in the 1-hour timeframe, which acts as a magnet for price movement. Additionally, traders confirm entries using M15 Market Structure Shift (MSS) and SMT divergence.
Bullish Twitter Model :
In a bullish setup, the price sweeps the previous day’s low (PDL), and after confirming reversal signals, buys are executed in internal liquidity zones. Conversely, in a bearish setup, the price sweeps the previous day’s high (PDH), and after confirming weakness signals, sells are executed.
Bearish Twitter Model :
In short setups, entries are only executed above the Midnight Open, while in long setups, entries are taken below the Midnight Open. Adhering to these principles allows traders to define precise entry and exit points and analyze price movement with greater accuracy based on liquidity and market structure.
🔵 How to Use
The Twitter Model ICT is a liquidity-based trading strategy that analyzes price movements relative to the previous day’s high and low (PDH/PDL) and Fair Value Gap (FVG). This model is applicable in both bullish and bearish directions and utilizes the 1-hour (1H) and 15-minute (M15) timeframes for entry confirmation.
The price first sweeps an external liquidity level (PDH or PDL) and then provides an entry opportunity based on Market Structure Shift (MSS) and SMT divergence. Additionally, the entry should be positioned relative to the Midnight Open, meaning long entries should occur below the Midnight Open and short entries above it.
🟣 Bullish Twitter Model
In a bullish setup, the price first sweeps the previous day’s low (PDL) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bullish Fair Value Gap (FVG) forms, which serves as the price target.
To confirm the entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should be observed, signaling a trend reversal to the upside. Additionally, SMT divergence with correlated assets can indicate weakness in selling pressure.
Under these conditions, a long position is taken below the Midnight Open, with a stop-loss placed at the lowest point of the recent bearish move. The price target for this trade is the FVG in the 1-hour timeframe.
🟣 Bearish Twitter Model
In a bearish setup, the price first sweeps the previous day’s high (PDH) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bearish Fair Value Gap (FVG) is identified, serving as the trade target.
To confirm entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should form, signaling a trend shift to the downside. If an SMT divergence is present, it can provide additional confirmation for the trade.
Once these conditions are met, a short position is taken above the Midnight Open, with a stop-loss placed at the highest level of the recent bullish move. The trade's price target is the FVG in the 1-hour timeframe.
🔵 Settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
Daily Position : Determines whether only the first signal of the day is considered or if signals are evaluated throughout the entire day.
Session : Specifies in which trading sessions the indicator will be active.
Second Symbol : This setting allows you to select another asset for comparison with the primary asset. By default, "XAUUSD" (Gold) is set as the second symbol, but you can change it to any currency pair, stock, or cryptocurrency. For example, you can choose currency pairs like EUR/USD or GBP/USD to identify divergences between these two assets.
Divergence Fractal Periods : This parameter defines the number of past candles to consider when identifying divergences. The default value is 2, but you can change it to suit your preferences. This setting allows you to detect divergences more accurately by selecting a greater number of candles.
The indicator allows displaying sessions based on various time zones. The user can select one of the following options :
UTC (Coordinated Universal Time)
Local Time of the Session
User’s Local Time
Show Open Price : Displays the New York market opening price.
Show PDH / PDL : Displays the previous day’s high and low to identify potential entry points.
Show SMT Divergence : Displays lines and labels for bullish ("+SMT") and bearish ("-SMT") divergences.
🔵 Conclusion
The Twitter Model ICT is an effective approach for analyzing and executing trades in financial markets, utilizing a combination of liquidity principles, market structure, and SMT confirmations to identify optimal entry and exit points.
By analyzing the previous day’s high and low (PDH/PDL), Fair Value Gaps (FVG), and Market Structure Shift (MSS) in the 1H and M15 timeframes, traders can pinpoint liquidity-driven trade opportunities. Additionally, considering the Midnight Open level helps traders avoid random entries and ensures better trade placement.
By applying this model, traders can interpret market movements based on liquidity flow and structural changes, allowing them to fine-tune their trading decisions with higher precision. Ultimately, the Twitter Model ICT provides a structured and logical approach for traders who seek to trade based on liquidity behavior and trend shifts in the market.
Search in scripts for "TAKE"
Uptrick Signal Density Cloud🟪 Introduction
The Uptrick Signal Density Cloud is designed to track market direction and highlight potential reversals or shifts in momentum. It plots two smoothed lines on the chart and fills the space between them (often called a “cloud”). The bars on the chart change color depending on bullish or bearish conditions, and small triangles appear when certain reversal criteria are met. A metrics table displays real-time values for easy reference.
🟩 Why These Features Have Been Linked Together
1) Dual-Line Structure
Two separate lines represent shorter- and longer-term market tendencies. Linking them in one tool allows traders to view both near-term changes and the broader directional bias in a single glance.
2) Smoothed Averages
The script offers multiple smoothing methods—exponential, simple, hull, and an optimized approach—to reduce noise. Using more than one type of moving average can help balance responsiveness with stability.
3) Density Cloud Concept
Shading the region between the two lines highlights the gap or “thickness.” A wider gap typically signals stronger momentum, while a narrower gap could indicate a weakening trend or potential market indecision. When the cloud is too wide and crosses a certain threshold defined by the user, it indicates a possible reversal. When the cloud is too narrow it may indicate a potential breakout.
🟪 Why Use This Indicator
• Trend Visibility: The color-coded lines and bars make it easier to distinguish bullish from bearish conditions.
• Momentum Tracking: Thicker cloud regions suggest stronger separation between the faster and slower lines, potentially indicating robust momentum.
• Possible Reversal Alerts: Small triangles appear within thick zones when the indicator detects a crossover, drawing attention to key moments of potential trend change.
• Quick Reference Table: A metrics table shows line values, bullish or bearish status, and cloud thickness without needing to hover over chart elements.
🟩 Inputs
1) First Smoothing Length (length1)
Default: 14
Defines the lookback period for the faster line. Lower values make the line respond more quickly to price changes.
2) Second Smoothing Length (length2)
Default: 28
Defines the lookback period for the slower line or one of the moving averages in optimized mode. It generally responds more slowly than the faster line.
3) Extra Smoothing Length (extraLength)
Default: 50
A medium-term period commonly seen in technical analysis. In optimized mode, it helps add broader perspective to the combined lines.
4) Source (source)
Default: close
Specifies the price data (for example, open, high, low, or a custom source) used in the calculations.
5) Cloud Type (cloudType)
Options: Optimized, EMA, SMA, HMA
Determines the smoothing method used for the lines. “Optimized” blends multiple exponential averages at different lengths.
6) Cloud Thickness Threshold (thicknessThreshold)
Default: 0.5
Sets the minimum separation between the two lines to qualify as a “thick” zone, indicating potentially stronger momentum.
🟪 Core Components
1) Faster and Slower Lines
Each line is smoothed according to user preferences or the optimized technique. The faster line typically reacts more quickly, while the slower line provides a broader overview.
2) Filled Density Cloud
The space between the two lines is filled to visualize in which direction the market is trending.
3) Color-Coded Bars
Price bars adopt bullish or bearish colors based on which line is on top, providing an immediate sense of trend direction.
4) Reversal Triangles
When the cloud is thick (exceeding the threshold) and the lines cross in the opposite direction, small triangles appear, signaling a possible market shift.
5) Metrics Table
A compact table shows the current values of both lines, their bullish/bearish statuses, the cloud thickness, and whether the cloud is in a “reversal zone.”
🟩 Calculation Process
1) Raw Averages
Depending on the mode, standard exponential, simple, hull, or “optimized” exponential blends are calculated.
2) Optimized Averages (if selected)
The faster line is the average of three exponential moving averages using length1, length2, and extraLength.
The slower line similarly uses those same lengths multiplied by 1.5, then averages them together for broader smoothing.
3) Difference and Threshold
The absolute gap between the two lines is measured. When it exceeds thicknessThreshold, the cloud is considered thick.
4) Bullish or Bearish Determination
If sma1 (the faster line) is above sma2 (the slower line), conditions are deemed bullish; otherwise, they are bearish. This distinction is reflected in both bar colors and cloud shading.
5) Reversal Markers
In thick zones, a crossover triggers a triangle at the point of potential reversal, alerting traders to a possible trend change.
🟪 Smoothing Methods
1) Exponential (EMA)
Prioritizes recent data for quicker responsiveness.
2) Simple (SMA)
Takes a straightforward average of the chosen period, smoothing price action but often lagging more in volatile markets.
3) Hull (HMA)
Employs a specialized formula to reduce lag while maintaining smoothness.
4) Optimized (Blended Exponential)
Combines multiple EMA calculations to strike a balance between responsiveness and noise reduction.
🟩 Cloud Logic and Reversal Zones
Cloud thickness above the defined threshold typically signals exceeding momentum and can lead to a quick reversal. During these thick periods, if the width exceeds the defined threshold, small triangles mark potential reversal points. In order for the reversal shape to show, the color of the cloud has to be the opposite. So, for example, if the cloud is bearish, and exceeds momentum, defined by the user, a bullish signal appears. The opposite conditions for a bullish signal. This approach can help traders focus on notable changes rather than minor oscillations.
🟪 Bar Coloring and Layered Lines
Bars take on bullish or bearish tints, matching the faster line’s position relative to the slower line. The lines themselves are plotted multiple times with varying opacities, creating a layered, glowing look that enhances visibility without affecting calculations.
🟩 The Metrics Table
Located in the top-right corner of the chart, this table displays:
• SMA1 and SMA2 current values.
• Bullish or bearish alignment for each line.
• Cloud thickness.
• Reversal zone status (in or out of zone).
This numeric readout allows for a quick data check without hovering over the chart.
🟪 Why These Specific Moving Average Lengths Are Used
Default lengths of 14, 28, and 50 are common in technical analysis. Fourteen captures near-term price movement without overreacting. Twenty-eight, roughly double 14, provides a moderate smoothing level. Fifty is widely regarded as a medium-term benchmark. Multiplying each length by 1.5 for the slower line enhances separation when combined with the faster line.
🟩 Originality and Usefulness
• Multi-Layered Smoothing. The user can select from several moving average modes, including a unique “optimized” blend, possibly reducing random fluctuations in the market data.
• Combined Visual and Numeric Clarity. Bars, clouds, and a real-time table merge into a single interface, enabling efficient trend analysis.
• Focus on Significant Shifts. Thick cloud zones and triangles draw attention to potentially stronger momentum changes and plausible reversals.
• Flexible Across Markets. The adjustable lengths and threshold can be tuned to different asset classes (stocks, forex, commodities, crypto) and timeframes.
By integrating multiple technical concepts—cloud-based trend detection, color coding, reversal markers, and an immediate reference table—the Uptrick Signal Density Cloud aims to streamline chart reading and decision-making.
🟪 Additional Considerations
• Timeframes. Intraday, daily, and weekly charts each yield different signals. Adjust the smoothing lengths and threshold to suit specific trading horizons.
• Market Types. Though applicable across asset classes, parameters might need tweaking to address the volatility of commodities, forex pairs, or cryptocurrencies.
• Confirmation Tools. Pairing this indicator with volume studies or support/resistance analysis can improve the reliability of signals.
• Potential Limitations. No indicator is foolproof; sudden market shifts or choppy conditions may reduce accuracy. Cautious position sizing and risk management remain essential.
🟩 Disclaimers
The Uptrick Signal Density Cloud relies on historical price data and may lag sudden moves or provide false positives in ranging conditions. Always combine it with other analytical techniques and sound risk management. This script is offered for educational purposes only and should not be considered financial advice.
🟪 Conclusion
The Uptrick Signal Density Cloud blends trend identification, momentum assessment, and potential reversal alerts in a single, user-friendly tool. With customizable smoothing methods and a focus on cloud thickness, it visually highlights important market conditions. While it cannot guarantee predictive accuracy, it can serve as a comprehensive reference for traders seeking both a quick snapshot of the current trend and deeper insights into market dynamics.
Uptrick: Fisher Eclipse1. Name and Purpose
Uptrick: Fisher Eclipse is a Pine version 6 extension of the basic Fisher Transform indicator that focuses on highlighting potential turning points in price data. Its purpose is to allow traders to spot shifts in momentum, detect divergence, and adapt signals to different market environments. By combining a core Fisher Transform with additional signal processing, divergence detection, and customizable aggressiveness settings, this script aims to help users see when a price move might be losing momentum or gaining strength.
2. Overview
This script uses a Fisher Transform calculation on the average of each bar’s high and low (hl2). The Fisher Transform is designed to amplify price extremes by mapping data into a different scale, making potential reversals more visible than they might be with standard oscillators. Uptrick: Fisher Eclipse takes this concept further by integrating a signal line, divergence detection, bar coloring for momentum intensity, and optional thresholds to reduce unwanted noise.
3. Why Use the Fisher Transform
The Fisher Transform is known for converting relatively smoothed price data into a more pronounced scale. This transformation highlights where markets may be overextended. In many cases, standard oscillators move gently, and traders can miss subtle hints that a reversal might be approaching. The Fisher Transform’s mathematical approach tightens the range of values and sharpens the highs and lows. This behavior can allow traders to see clearer peaks and troughs in momentum. Because it is often quite responsive, it can help anticipate areas where price might change direction, especially when compared to simpler moving averages or traditional oscillators. The result is a more evident signal of possible overbought or oversold conditions.
4. How This Extension Improves on the Basic Fisher Transform
Uptrick: Fisher Eclipse adds multiple features to the classic Fisher framework in order to address different trading styles and market behaviors:
a) Divergence Detection
The script can detect bullish or bearish divergences between price and the oscillator over a chosen lookback period, helping traders anticipate shifts in market direction.
b) Bar Coloring
When momentum exceeds a certain threshold (default 3), bars can be colored to highlight surges of buying or selling pressure. This quick visual reference can assist in spotting periods of heightened activity. After a bar color like this, usually, there is a quick correction as seen in the image below.
c) Signal Aggressiveness Levels
Users can choose between conservative, moderate, or aggressive signal thresholds. This allows them to tune how quickly the indicator flags potential entries or exits. Aggressive settings might suit scalpers who need rapid signals, while conservative settings may benefit swing traders preferring fewer, more robust indications.
d) Minimum Movement Filter
A configurable filter can be set to ensure that the Fisher line and its signal have a sufficient gap before triggering a buy or sell signal. This step is useful for traders seeking to minimize signals during choppy or sideways markets. This can be used to eliminate noise as well.
By combining all these elements into one package, the indicator attempts to offer a comprehensive toolkit for those who appreciate the Fisher Transform’s clarity but also desire more versatility.
5. Core Components
a) Fisher Transform
The script calculates a Fisher value using normalized price over a configurable length, highlighting potential peaks and troughs.
b) Signal Line
The Fisher line is smoothed using a short Simple Moving Average. Crossovers and crossunders are one of the key ways this indicator attempts to confirm momentum shifts.
c) Divergence Logic
The script looks back over a set number of bars to compare current highs and lows of both price and the Fisher oscillator. When price and the oscillator move in opposing directions, a divergence may occur, suggesting a possible upcoming reversal or weakening trend.
d) Thresholds for Overbought and Oversold
Horizontal lines are drawn at user-chosen overbought and oversold levels. These lines help traders see when momentum readings reach particular extremes, which can be especially relevant when combined with crossovers in that region.
e) Intensity Filter and Bar Coloring
If the magnitude of the change in the Fisher Transform meets or exceeds a specified threshold, bars are recolored. This provides a visual cue for significant momentum changes.
6. User Inputs
a) length
Defines how many bars the script looks back to compute the highest high and lowest low for the Fisher Transform. A smaller length reacts more quickly but can be noisier, while a larger length smooths out the indicator at the cost of responsiveness.
b) signal aggressiveness
Adjusts the buy and sell thresholds for conservative, moderate, and aggressive trading styles. This can be key in matching the indicator to personal risk preferences or varying market conditions. Conservative will give you less signals and aggressive will give you more signals.
c) minimum movement filter
Specifies how far apart the Fisher line and its signal line must be before generating a valid crossover signal.
d) divergence lookback
Controls how many bars are examined when determining if price and the oscillator are diverging. A larger setting might generate fewer signals, while a smaller one can provide more frequent alerts.
e) intensity threshold
Determines how large a change in the Fisher value must be for the indicator to recolor bars. Strong momentum surges become more noticeable.
f) overbought level and oversold level
Lets users define where they consider market conditions to be stretched on the upside or downside.
7. Calculation Process
a) Price Input
The script uses the midpoint of each bar’s high and low, sometimes referred to as hl2.
hl2 = (high + low) / 2
b) Range Normalization
Determine the maximum (maxHigh) and minimum (minLow) values over a user-defined lookback period (length).
Scale the hl2 value so it roughly fits between -1 and +1:
value = 2 * ((hl2 - minLow) / (maxHigh - minLow) - 0.5)
This step highlights the bar’s current position relative to its recent highs and lows.
c) Fisher Calculation
Convert the normalized value into the Fisher Transform:
fisher = 0.5 * ln( (1 + value) / (1 - value) ) + 0.5 * fisher_previous
fisher_previous is simply the Fisher value from the previous bar. Averaging half of the new transform with half of the old value smooths the result slightly and can prevent erratic jumps.
ln is the natural logarithm function, which compresses or expands values so that market turns often become more obvious.
d) Signal Smoothing
Once the Fisher value is computed, a short Simple Moving Average (SMA) is applied to produce a signal line. In code form, this often looks like:
signal = sma(fisher, 3)
Crossovers of the fisher line versus the signal line can be used to hint at changes in momentum:
• A crossover occurs when fisher moves from below to above the signal.
• A crossunder occurs when fisher moves from above to below the signal.
e) Threshold Checking
Users typically define oversold and overbought levels (often -1 and +1).
Depending on aggressiveness settings (conservative, moderate, aggressive), these thresholds are slightly shifted to filter out or include more signals.
For example, an oversold threshold of -1 might be used in a moderate setting, whereas -1.5 could be used in a conservative setting to require a deeper dip before triggering.
f) Divergence Checks
The script looks back a specified number of bars (divergenceLookback). For both price and the fisher line, it identifies:
• priceHigh = the highest hl2 within the lookback
• priceLow = the lowest hl2 within the lookback
• fisherHigh = the highest fisher value within the lookback
• fisherLow = the lowest fisher value within the lookback
If price forms a lower low while fisher forms a higher low, it can signal a bullish divergence. Conversely, if price forms a higher high while fisher forms a lower high, a bearish divergence might be indicated.
g) Bar Coloring
The script monitors the absolute change in Fisher values from one bar to the next (sometimes called fisherChange):
fisherChange = abs(fisher - fisher )
If fisherChange exceeds a user-defined intensityThreshold, bars are recolored to highlight a surge of momentum. Aqua might indicate a strong bullish surge, while purple might indicate a strong bearish surge.
This color-coding provides a quick visual cue for traders looking to spot large momentum swings without constantly monitoring indicator values.
8. Signal Generation and Filtering
Buy and sell signals occur when the Fisher line crosses the signal line in regions defined as oversold or overbought. The optional minimum movement filter prevents triggering if Fisher and its signal line are too close, reducing the chance of small, inconsequential price fluctuations creating frequent signals. Divergences that appear in oversold or overbought regions can serve as additional evidence that momentum might soon shift.
9. Visualization on the Chart
Uptrick: Fisher Eclipse plots two lines: the Fisher line in one color and the signal line in a contrasting shade. The chart displays horizontal dashed lines where the overbought and oversold levels lie. When the Fisher Transform experiences a sharp jump or drop above the intensity threshold, the corresponding price bars may change color, signaling that momentum has undergone a noticeable shift. If the indicator detects bullish or bearish divergence, dotted lines are drawn on the oscillator portion to connect the relevant points.
10. Market Adaptability
Because of the different aggressiveness levels and the optional minimum movement filter, Uptrick: Fisher Eclipse can be tailored to multiple trading styles. For instance, a short-term scalper might select a smaller length and more aggressive thresholds, while a swing trader might choose a longer length for smoother readings, along with conservative thresholds to ensure fewer but potentially stronger signals. During strongly trending markets, users might rely more on divergences or large intensity changes, whereas in a range-bound market, oversold or overbought conditions may be more frequent.
11. Risk Management Considerations
Indicators alone do not ensure favorable outcomes, and relying solely on any one signal can be risky. Using a stop-loss or other protections is often suggested, especially in fast-moving or unpredictable markets. Divergence can appear before a market reversal actually starts. Similarly, a Fisher Transform can remain in an overbought or oversold region for extended periods, especially if the trend is strong. Cautious interpretation and confirmation with additional methods or chart analysis can help refine entry and exit decisions.
12. Combining with Other Tools
Traders can potentially strengthen signals from Uptrick: Fisher Eclipse by checking them against other methods. If a moving average cross or a price pattern aligns with a Fisher crossover, the combined evidence might provide more certainty. Volume analysis may confirm whether a shift in market direction has participation from a broad set of traders. Support and resistance zones could reinforce overbought or oversold signals, particularly if price reaches a historical boundary at the same time the oscillator indicates a possible reversal.
13. Parameter Customization and Examples
Some short-term traders run a 15-minute chart, with a shorter length setting, aggressively tight oversold and overbought thresholds, and a smaller divergence lookback. This approach produces more frequent signals, which may appeal to those who enjoy fast-paced trading. More conservative traders might apply the indicator to a daily chart, using a larger length, moderate threshold levels, and a bigger divergence lookback to focus on broader market swings. Results can differ, so it may be helpful to conduct thorough historical testing to see which combination of parameters aligns best with specific goals.
14. Realistic Expectations
While the Fisher Transform can reveal potential turning points, no mathematical tool can predict future price behavior with full certainty. Markets can behave erratically, and a period of strong trending may see the oscillator pinned in an extreme zone without a significant reversal. Divergence signals sometimes appear well before an actual trend change occurs. Recognizing these limitations helps traders manage risk and avoids overreliance on any one aspect of the script’s output.
15. Theoretical Background
The Fisher Transform uses a logarithmic formula to map a normalized input, typically ranging between -1 and +1, into a scale that can fluctuate around values like -3 to +3. Because the transformation exaggerates higher and lower readings, it becomes easier to spot when the market might have stretched too far, too fast. Uptrick: Fisher Eclipse builds on that foundation by adding a series of practical tools that help confirm or refine those signals.
16. Originality and Uniqueness
Uptrick: Fisher Eclipse is not simply a duplicate of the basic Fisher Transform. It enhances the original design in several ways, including built-in divergence detection, bar-color triggers for momentum surges, thresholds for overbought and oversold levels, and customizable signal aggressiveness. By unifying these concepts, the script seeks to reduce noise and highlight meaningful shifts in market direction. It also places greater emphasis on helping traders adapt the indicator to their specific style—whether that involves frequent intraday signals or fewer, more robust alerts over longer timeframes.
17. Summary
Uptrick: Fisher Eclipse is an expanded take on the original Fisher Transform oscillator, including divergence detection, bar coloring based on momentum strength, and flexible signal thresholds. By adjusting parameters like length, aggressiveness, and intensity thresholds, traders can configure the script for day-trading, swing trading, or position trading. The indicator endeavors to highlight where price might be shifting direction, but it should still be combined with robust risk management and other analytical methods. Doing so can lead to a more comprehensive view of market conditions.
18. Disclaimer
No indicator or script can guarantee profitable outcomes in trading. Past performance does not necessarily suggest future results. Uptrick: Fisher Eclipse is provided for educational and informational purposes. Users should apply their own judgment and may want to confirm signals with other tools and methods. Deciding to open or close a position remains a personal choice based on each individual’s circumstances and risk tolerance.
Adaptive Moving Averagewhat is the purpose of the indicator?
When short-length moving averages are used as trailing stops, they cause exiting the trade too early. Keeping the length value too high will result in exiting the transaction too late and losing most of the profits earned. I aimed to prevent this problem with this indicator.
what is "Adaptive Moving Average"?
it is a moving average that can change its length on each candle depending on the selected source.
what it does?
The indicator first finds the average lengths of the existing candles and defines different distances accordingly. When the moving average drawn by the indicator enters the area defined as "far" by the indicator, the indicator reduces the length of the moving average, preventing it from moving too far from the price, and continues to do so at different rates until the moving average gets close enough to the price. If the moving average gets close enough to the price, it starts to increase the length of the average and thus the adaptation continues.
how it does it?
Since the change of each trading pair is different in percentage terms, I chose to base the average height of the candles instead of using constant percentage values to define the concept of "far". While doing this, I used a weighted moving average so that the system could quickly adapt to the latest changes (you can see it on line 17). After calculating what percentage of the moving average this value is, I caused the length of the moving average to change in each bar depending on the multiples of this percentage value that the price moved away from the average (look at line 20, 21 and 22). Finally, I created a new moving average using this new length value I obtained.
how to use it?
Although the indicator chooses its own length, we have some inputs to customize it. First of all, we can choose which source we will use the moving average on. The "source" input allows us to use it with other indicators.
"max length" and "min length" determine the maximum and minimum value that the length of the moving average can take.
Apart from this, there are options for you to add a standard moving average to the chart so that you can compare the adaptive moving average, and bollinger band channels that you can use to create different strategies.
This indicator was developed due to the need for a more sophisticated trailing stop, but once you understand how it works, it is completely up to you to combine it with other indicators and create different strategies.
VPSA-VTDDear Sir/Madam,
I am pleased to present the next iteration of my indicator concept, which, in my opinion, serves as a highly useful tool for analyzing markets using the Volume Spread Analysis (VSA) method or the Wyckoff methodology.
The VPSA (Volume-Price Spread Analysis), the latest version in the family of scripts I’ve developed, appears to perform its task effectively. The combination of visualizing normalized data alongside their significance, achieved through the application of Z-Score standardization, proved to be a sound solution. Therefore, I decided to take it a step further and expand my project with a complementary approach to the existing one.
Theory
At the outset, I want to acknowledge that I’m aware of the existence of other probabilistic models used in financial markets, which may describe these phenomena more accurately. However, in line with Occam's Razor, I aimed to maintain simplicity in the analysis and interpretation of the concepts below. For this reason, I focused on describing the data using the Gaussian distribution.
The data I read from the chart — primarily the closing price, the high-low price difference (spread), and volume — exhibit cyclical patterns. These cycles are described by Wyckoff's methodology, while VSA complements and presents them from a different perspective. I will refrain from explaining these methods in depth due to their complexity and broad scope. What matters is that within these cycles, various events occur, described by candles or bars in distinct ways, characterized by different spreads and volumes. When observing the chart, I notice periods of lower volatility, often accompanied by lower volumes, as well as periods of high volatility and significant volumes. It’s important to find harmony within this apparent chaos. I think that chart interpretation cannot happen without considering the broader context, but the more variables I include in the analytical process, the more challenges arise. For instance, how can I determine if something is large (wide) or small (narrow)? For elements like volume or spread, my script provides a partial answer to this question. Now, let’s get to the point.
Technical Overview
The first technique I applied is Min-Max Normalization. With its help, the script adjusts volume and spread values to a range between 0 and 1. This allows for a comparable bar chart, where a wide bar represents volume, and a narrow one represents spread. Without normalization, visually comparing values that differ by several orders of magnitude would be inconvenient. If the indicator shows that one bar has a unit spread value while another has half that value, it means the first bar is twice as large. The ratio is preserved.
The second technique I used is Z-Score Standardization. This concept is based on the normal distribution, characterized by variables such as the mean and standard deviation, which measures data dispersion around the mean. The Z-Score indicates how many standard deviations a given value deviates from the population mean. The higher the Z-Score, the more the examined object deviates from the mean. If an object has a Z-Score of 3, it falls within 0.1% of the population, making it a rare occurrence or even an anomaly. In the context of chart analysis, such strong deviations are events like climaxes, which often signal the end of a trend, though not always. In my script, I assigned specific colors to frequently occurring Z-Score values:
Below 1 – Blue
Above 1 – Green
Above 2 – Red
Above 3 – Fuchsia
These colors are applied to both spread and volume, allowing for quick visual interpretation of data.
Volume Trend Detector (VTD)
The above forms the foundation of VPSA. However, I have extended the script with a Volume Trend Detector (VTD). The idea is that when I consider market structure - by market structure, I mean the overall chart, support and resistance levels, candles, and patterns typical of spread and volume analysis as well as Wyckoff patterns - I look for price ranges where there is a lack of supply, demand, or clues left behind by Smart Money or the market's enigmatic identity known as the Composite Man. This is essential because, as these clues and behaviors of market participants — expressed through the chart’s dynamics - reflect the actions, decisions, and emotions of all players. These behaviors can help interpret the bull-bear battle and estimate the probability of their next moves, which is one of the key factors for a trader relying on technical analysis to make a trade decision.
I enhanced the script with a Volume Trend Detector, which operates in two modes:
Step-by-Step Logic
The detector identifies expected volume dynamics. For instance, when looking for signs of a lack of bullish interest, I focus on setups with decreasing volatility and volume, particularly for bullish candles. These setups are referred to as No Demand patterns, according to Tom Williams' methodology.
Simple Moving Average (SMA)
The detector can also operate based on a simple moving average, helping to identify systematic trends in declining volume, indicating potential imbalances in market forces.
I’ve designed the program to allow the selection of candle types and volume characteristics to which the script will pay particular attention and notify me of specific market conditions.
Advantages and Disadvantages
Advantages:
Unified visualization of normalized spread and volume, saving time and improving efficiency.
The use of Z-Score as a consistent and repeatable relative mechanism for marking examined values.
The use of colors in visualization as a reference to Z-Score values.
The possibility to set up a continuous alert system that monitors the market in real time.
The use of EMA (Exponential Moving Average) as a moving average for Z-Score.
The goal of these features is to save my time, which is the only truly invaluable resource.
Disadvantages:
The assumption that the data follows a normal distribution, which may lead to inaccurate interpretations.
A fixed analysis period, which may not be perfectly suited to changing market conditions.
The use of EMA as a moving average for Z-Score, listed both as an advantage and a disadvantage depending on market context.
I have included comments within the code to explain the logic behind each part. For those who seek detailed mathematical formulas, I invite you to explore the code itself.
Defining Program Parameters:
Numerical Conditions:
VPSA Period for Analysis – The number of candles analyzed.
Normalized Spread Alert Threshold – The expected normalized spread value; defines how large or small the spread should be, with a range of 0-1.00.
Normalized Volume Alert Threshold – The expected normalized volume value; defines how large or small the volume should be, with a range of 0-1.00.
Spread Z-SCORE Alert Threshold – The Z-SCORE value for the spread; determines how much the spread deviates from the average, with a range of 0-4 (a higher value can be entered, but from a logical standpoint, exceeding 4 is unnecessary).
Volume Z-SCORE Alert Threshold – The Z-SCORE value for volume; determines how much the volume deviates from the average, with a range of 0-4 (the same logical note as above applies).
Logical Conditions:
Logical conditions describe whether the expected value should be less than or equal to or greater than or equal to the numerical condition.
All four parameters accept two possibilities and are analogous to the numerical conditions.
Volume Trend Detector:
Volume Trend Detector Period for Analysis – The analysis period, indicating the number of candles examined.
Method of Trend Determination – The method used to determine the trend. Possible values: Step by Step or SMA.
Trend Direction – The expected trend direction. Possible values: Upward or Downward.
Candle Type – The type of candle taken into account. Possible values: Bullish, Bearish, or Any.
The last available setting is the option to enable a joint alert for VPSA and VTD.
When enabled, VPSA will trigger on the last closed candle, regardless of the VTD analysis period.
Example Use Cases (Labels Visible in the Script Window Indicate Triggered Alerts):
The provided labels in the chart window mark where specific conditions were met and alerts were triggered.
Summary and Reflections
The program I present is a strong tool in the ongoing "game" with the Composite Man.
However, it requires familiarity and understanding of the underlying methodologies to fully utilize its potential.
Of course, like any technical analysis tool, it is not without flaws. There is no indicator that serves as a perfect Grail, accurately signaling Buy or Sell in every case.
I would like to thank those who have read through my thoughts to the end and are willing to take a closer look at my work by using this script.
If you encounter any errors or have suggestions for improvement, please feel free to contact me.
I wish you good health and accurately interpreted market structures, leading to successful trades!
CatTheTrader
PIP Algorithm
# **Script Overview (For Non-Coders)**
1. **Purpose**
- The script tries to capture the essential “shape” of price movement by selecting a limited number of “key points” (anchors) from the latest bars.
- After selecting these anchors, it draws straight lines between them, effectively simplifying the price chart into a smaller set of points without losing major swings.
2. **How It Works, Step by Step**
1. We look back a certain number of bars (e.g., 50).
2. We start by drawing a straight line from the **oldest** bar in that range to the **newest** bar—just two points.
3. Next, we find the bar whose price is *farthest away* from that straight line. That becomes a new anchor point.
4. We “snap” (pin) the line to go exactly through that new anchor. Then we re-draw (re-interpolate) the entire line from the first anchor to the last, in segments.
5. We repeat the process (adding more anchors) until we reach the desired number of points. Each time, we choose the biggest gap between our line and the actual price, then re-draw the entire shape.
6. Finally, we connect these anchors on the chart with red lines, visually simplifying the price curve.
3. **Why It’s Useful**
- It highlights the most *important* bends or swings in the price over the chosen window.
- Instead of plotting every single bar, it condenses the information down to the “key turning points.”
4. **Key Takeaway**
- You’ll see a small number of red line segments connecting the **most significant** points in the price data.
- This is especially helpful if you want a simplified view of recent price action without minor fluctuations.
## **Detailed Logic Explanation**
# **Script Breakdown (For Coders)**
//@version=5
indicator(title="PIP Algorithm", overlay=true)
// 1. Inputs
length = input.int(50, title="Lookback Length")
num_points = input.int(5, title="Number of PIP Points (≥ 3)")
// 2. Helper Functions
// ---------------------------------------------------------------------
// reInterpSubrange(...):
// Given two “anchor” indices in `linesArr`, linearly interpolate
// the array values in between so that the subrange forms a straight line
// from linesArr to linesArr .
reInterpSubrange(linesArr, segmentLeft, segmentRight) =>
float leftVal = array.get(linesArr, segmentLeft)
float rightVal = array.get(linesArr, segmentRight)
int segmentLen = segmentRight - segmentLeft
if segmentLen > 1
for i = segmentLeft + 1 to segmentRight - 1
float ratio = (i - segmentLeft) / segmentLen
float interpVal = leftVal + (rightVal - leftVal) * ratio
array.set(linesArr, i, interpVal)
// reInterpolateAllSegments(...):
// For the entire “linesArr,” re-interpolate each subrange between
// consecutive breakpoints in `lineBreaksArr`.
// This ensures the line is globally correct after each new anchor insertion.
reInterpolateAllSegments(linesArr, lineBreaksArr) =>
array.sort(lineBreaksArr, order.asc)
for i = 0 to array.size(lineBreaksArr) - 2
int leftEdge = array.get(lineBreaksArr, i)
int rightEdge = array.get(lineBreaksArr, i + 1)
reInterpSubrange(linesArr, leftEdge, rightEdge)
// getMaxDistanceIndex(...):
// Return the index (bar) that is farthest from the current “linesArr.”
// We skip any indices already in `lineBreaksArr`.
getMaxDistanceIndex(linesArr, closeArr, lineBreaksArr) =>
float maxDist = -1.0
int maxIdx = -1
int sizeData = array.size(linesArr)
for i = 1 to sizeData - 2
bool isBreak = false
for b = 0 to array.size(lineBreaksArr) - 1
if i == array.get(lineBreaksArr, b)
isBreak := true
break
if not isBreak
float dist = math.abs(array.get(linesArr, i) - array.get(closeArr, i))
if dist > maxDist
maxDist := dist
maxIdx := i
maxIdx
// snapAndReinterpolate(...):
// "Snap" a chosen index to its actual close price, then re-interpolate the entire line again.
snapAndReinterpolate(linesArr, closeArr, lineBreaksArr, idxToSnap) =>
if idxToSnap >= 0
float snapVal = array.get(closeArr, idxToSnap)
array.set(linesArr, idxToSnap, snapVal)
reInterpolateAllSegments(linesArr, lineBreaksArr)
// 3. Global Arrays and Flags
// ---------------------------------------------------------------------
// We store final data globally, then use them outside the barstate.islast scope to draw lines.
var float finalCloseData = array.new_float()
var float finalLines = array.new_float()
var int finalLineBreaks = array.new_int()
var bool didCompute = false
var line pipLines = array.new_line()
// 4. Main Logic (Runs Once at the End of the Current Bar)
// ---------------------------------------------------------------------
if barstate.islast
// A) Prepare closeData in forward order (index 0 = oldest bar, index length-1 = newest)
float closeData = array.new_float()
for i = 0 to length - 1
array.push(closeData, close )
// B) Initialize linesArr with a simple linear interpolation from the first to the last point
float linesArr = array.new_float()
float firstClose = array.get(closeData, 0)
float lastClose = array.get(closeData, length - 1)
for i = 0 to length - 1
float ratio = (length > 1) ? (i / float(length - 1)) : 0.0
float val = firstClose + (lastClose - firstClose) * ratio
array.push(linesArr, val)
// C) Initialize lineBreaks with two anchors: 0 (oldest) and length-1 (newest)
int lineBreaks = array.new_int()
array.push(lineBreaks, 0)
array.push(lineBreaks, length - 1)
// D) Iteratively insert new breakpoints, always re-interpolating globally
int iterationsNeeded = math.max(num_points - 2, 0)
for _iteration = 1 to iterationsNeeded
// 1) Re-interpolate entire shape, so it's globally up to date
reInterpolateAllSegments(linesArr, lineBreaks)
// 2) Find the bar with the largest vertical distance to this line
int maxDistIdx = getMaxDistanceIndex(linesArr, closeData, lineBreaks)
if maxDistIdx == -1
break
// 3) Insert that bar index into lineBreaks and snap it
array.push(lineBreaks, maxDistIdx)
array.sort(lineBreaks, order.asc)
snapAndReinterpolate(linesArr, closeData, lineBreaks, maxDistIdx)
// E) Save results into global arrays for line drawing outside barstate.islast
array.clear(finalCloseData)
array.clear(finalLines)
array.clear(finalLineBreaks)
for i = 0 to array.size(closeData) - 1
array.push(finalCloseData, array.get(closeData, i))
array.push(finalLines, array.get(linesArr, i))
for b = 0 to array.size(lineBreaks) - 1
array.push(finalLineBreaks, array.get(lineBreaks, b))
didCompute := true
// 5. Drawing the Lines in Global Scope
// ---------------------------------------------------------------------
// We cannot create lines inside barstate.islast, so we do it outside.
array.clear(pipLines)
if didCompute
// Connect each pair of anchors with red lines
if array.size(finalLineBreaks) > 1
for i = 0 to array.size(finalLineBreaks) - 2
int idxLeft = array.get(finalLineBreaks, i)
int idxRight = array.get(finalLineBreaks, i + 1)
float x1 = bar_index - (length - 1) + idxLeft
float x2 = bar_index - (length - 1) + idxRight
float y1 = array.get(finalCloseData, idxLeft)
float y2 = array.get(finalCloseData, idxRight)
line ln = line.new(x1, y1, x2, y2, extend=extend.none)
line.set_color(ln, color.red)
line.set_width(ln, 2)
array.push(pipLines, ln)
1. **Data Collection**
- We collect the **most recent** `length` bars in `closeData`. Index 0 is the oldest bar in that window, index `length-1` is the newest bar.
2. **Initial Straight Line**
- We create an array called `linesArr` that starts as a simple linear interpolation from `closeData ` (the oldest bar’s close) to `closeData ` (the newest bar’s close).
3. **Line Breaks**
- We store “anchor points” in `lineBreaks`, initially ` `. These are the start and end of our segment.
4. **Global Re-Interpolation**
- Each time we want to add a new anchor, we **re-draw** (linear interpolation) for *every* subrange ` [lineBreaks , lineBreaks ]`, ensuring we have a globally consistent line.
- This avoids the “local subrange only” approach, which can cause clustering near existing anchors.
5. **Finding the Largest Distance**
- After re-drawing, we compute the vertical distance for each bar `i` that isn’t already a line break. The bar with the biggest distance from the line is chosen as the next anchor (`maxDistIdx`).
6. **Snapping and Re-Interpolate**
- We “snap” that bar’s line value to the actual close, i.e. `linesArr = closeData `. Then we globally re-draw all segments again.
7. **Repeat**
- We repeat these insertions until we have the desired number of points (`num_points`).
8. **Drawing**
- Finally, we connect each consecutive pair of anchor points (`lineBreaks`) with a `line.new(...)` call, coloring them red.
- We offset the line’s `x` coordinate so that the anchor at index 0 lines up with `bar_index - (length - 1)`, and the anchor at index `length-1` lines up with `bar_index` (the current bar).
**Result**:
You get a simplified representation of the price with a small set of line segments capturing the largest “jumps” or swings. By re-drawing the entire line after each insertion, the anchors tend to distribute more *evenly* across the data, mitigating the issue where anchors bunch up near each other.
Enjoy experimenting with different `length` and `num_points` to see how the simplified lines change!
TearRepresentative's Rule-Based Dip Buying Strategy Rule-Based Dip Buying Strategy Indicator
This TradingView indicator, inspired by TearRepresentative [ , is a refined tool designed to assist traders in implementing a rule-based dip buying strategy. The indicator automates the identification of optimal buy and sell points, helping traders stay disciplined and minimize emotional biases. It is tailored to index trading, specifically leveraged ETFs like SPXL, to capture opportunities in market pullbacks and recoveries.
Key Features
Dynamic Buy Levels:
Tracks the local high over a customizable lookback period and calculates three buy levels based on percentage drops from the high:
Buy Level 1: First entry point (e.g., 15% drop).
Buy Level 2: Second entry point (e.g., additional 10% drop).
Buy Level 3: Third entry point (e.g., additional 7% drop).
Average Price Tracking:
Dynamically calculates the average price for entered positions when multiple buy levels are triggered.
Sell Level:
Computes a take-profit level (e.g., 20% above the average price) to automate profit-taking when the market rebounds.
Signal Visualization:
Buy Signals: Displayed as green triangles at each buy level.
Sell Signals: Displayed as red triangles at the sell level.
Alerts:
Configurable alerts notify traders when buy or sell signals are triggered, ensuring no opportunity is missed.
Visual Aids:
Semi-transparent and dynamic lines represent buy and sell levels for clear visualization.
Labels provide additional clarity for active levels, helping traders quickly identify actionable signals.
How It Works
The indicator analyzes market movements to identify dips based on predefined thresholds.
Buy signals are triggered when the market price reaches specified levels below the local high.
Once a position is taken, the indicator dynamically adjusts the average entry price and calculates the corresponding sell level.
A sell signal is generated when the market price rises above the calculated take-profit level.
Why Use This Indicator?
Discipline: Automates decision-making, removing emotional factors from trading.
Clarity: Provides clear entry and exit points to simplify complex market dynamics.
Versatility: Suitable for all market conditions, especially during pullbacks and rebounds.
Customization: Allows traders to tailor parameters to their preferred trading style and risk tolerance.
Acknowledgment
This indicator is based on the strategy and insights provided by TearRepresentative, whose expertise in rule-based trading has inspired countless traders. TearRepresentative's approach emphasizes simplicity, reliability, and consistency, offering a robust framework for long-term success.
3 EMA + RSI with Trail Stop [Free990] (LOW TF)This trading strategy combines three Exponential Moving Averages (EMAs) to identify trend direction, uses RSI to signal exit conditions, and applies both a fixed percentage stop-loss and a trailing stop for risk management. It aims to capture momentum when the faster EMAs cross the slower EMA, then uses RSI thresholds, time-based exits, and stops to close trades.
Short Explanation of the Logic
Trend Detection: When the 10 EMA crosses above the 20 EMA and both are above the 100 EMA (and the current price bar closes higher), it triggers a long entry signal. The reverse happens for a short (the 10 EMA crosses below the 20 EMA and both are below the 100 EMA).
RSI Exit: RSI crossing above a set threshold closes long trades; crossing below another threshold closes short trades.
Time-Based Exit: If a trade is in profit after a set number of bars, the strategy closes it.
Stop-Loss & Trailing Stop: A fixed stop-loss based on a percentage from the entry price guards against large drawdowns. A trailing stop dynamically tightens as the trade moves in favor, locking in potential gains.
Detailed Explanation of the Strategy Logic
Exponential Moving Average (EMA) Setup
Short EMA (out_a, length=10)
Medium EMA (out_b, length=20)
Long EMA (out_c, length=100)
The code calculates three separate EMAs to gauge short-term, medium-term, and longer-term trend behavior. By comparing their relative positions, the strategy infers whether the market is bullish (EMAs stacked positively) or bearish (EMAs stacked negatively).
Entry Conditions
Long Entry (entryLong): Occurs when:
The short EMA (10) crosses above the medium EMA (20).
Both EMAs (short and medium) are above the long EMA (100).
The current bar closes higher than it opened (close > open).
This suggests that momentum is shifting to the upside (short-term EMAs crossing up and price action turning bullish). If there’s an existing short position, it’s closed first before opening a new long.
Short Entry (entryShort): Occurs when:
The short EMA (10) crosses below the medium EMA (20).
Both EMAs (short and medium) are below the long EMA (100).
The current bar closes lower than it opened (close < open).
This indicates a potential shift to the downside. If there’s an existing long position, that gets closed first before opening a new short.
Exit Signals
RSI-Based Exits:
For long trades: When RSI exceeds a specified threshold (e.g., 70 by default), it triggers a long exit. RSI > short_rsi generally means overbought conditions, so the strategy exits to lock in profits or avoid a pullback.
For short trades: When RSI dips below a specified threshold (e.g., 30 by default), it triggers a short exit. RSI < long_rsi indicates oversold conditions, so the strategy closes the short to avoid a bounce.
Time-Based Exit:
If the trade has been open for xBars bars (configurable, e.g., 24 bars) and the trade is in profit (current price above entry for a long, or current price below entry for a short), the strategy closes the position. This helps lock in gains if the move takes too long or momentum stalls.
Stop-Loss Management
Fixed Stop-Loss (% Based): Each trade has a fixed stop-loss calculated as a percentage from the average entry price.
For long positions, the stop-loss is set below the entry price by a user-defined percentage (fixStopLossPerc).
For short positions, the stop-loss is set above the entry price by the same percentage.
This mechanism prevents catastrophic losses if the market moves strongly against the position.
Trailing Stop:
The strategy also sets a trail stop using trail_points (the distance in price points) and trail_offset (how quickly the stop “catches up” to price).
As the market moves in favor of the trade, the trailing stop gradually tightens, allowing profits to run while still capping potential drawdowns if the price reverses.
Order Execution Flow
When the conditions for a new position (long or short) are triggered, the strategy first checks if there’s an opposite position open. If there is, it closes that position before opening the new one (prevents going “both long and short” simultaneously).
RSI-based and time-based exits are checked on each bar. If triggered, the position is closed.
If the position remains open, the fixed stop-loss and trailing stop remain in effect until the position is exited.
Why This Combination Works
Multiple EMA Cross: Combining 10, 20, and 100 EMAs balances short-term momentum detection with a longer-term trend filter. This reduces false signals that can occur if you only look at a single crossover without considering the broader trend.
RSI Exits: RSI provides a momentum oscillator view—helpful for detecting overbought/oversold conditions, acting as an extra confirmation to exit.
Time-Based Exit: Prevents “lingering trades.” If the position is in profit but failing to advance further, it takes profit rather than risking a trend reversal.
Fixed & Trailing Stop-Loss: The fixed stop-loss is your safety net to cap worst-case losses. The trailing stop allows the strategy to lock in gains by following the trade as it moves favorably, thus maximizing profit potential while keeping risk in check.
Overall, this approach tries to capture momentum from EMA crossovers, protect profits with trailing stops, and limit risk through both a fixed percentage stop-loss and exit signals from RSI/time-based logic.
Algorithmic Signal AnalyzerMeet Algorithmic Signal Analyzer (ASA) v1: A revolutionary tool that ushers in a new era of clarity and precision for both short-term and long-term market analysis, elevating your strategies to the next level.
ASA is an advanced TradingView indicator designed to filter out noise and enhance signal detection using mathematical models. By processing price movements within defined standard deviation ranges, ASA produces a smoothed analysis based on a Weighted Moving Average (WMA). The Volatility Filter ensures that only relevant price data is retained, removing outliers and improving analytical accuracy.
While ASA provides significant analytical advantages, it’s essential to understand its capabilities in both short-term and long-term use cases. For short-term trading, ASA excels at capturing swift opportunities by highlighting immediate trend changes. Conversely, in long-term trading, it reveals the overall direction of market trends, enabling traders to align their strategies with prevailing conditions.
Despite these benefits, traders must remember that ASA is not designed for precise trade execution systems where accuracy in timing and price levels is critical. Its focus is on analysis rather than order management. The distinction is crucial: ASA helps interpret price action effectively but may not account for real-time market factors such as slippage or execution delays.
Features and Functionality
ASA integrates multiple tools to enhance its analytical capabilities:
Customizable Moving Averages: SMA, EMA, and WMA options allow users to tailor the indicator to their trading style.
Signal Detection: Identifies bullish and bearish trends using the Relative Exponential Moving Average (REMA) and marks potential buy/sell opportunities.
Visual Aids: Color-coded trend lines (green for upward, red for downward) simplify interpretation.
Alert System: Notifications for trend swings and reversals enable timely decision-making.
Notes on Usage
ASA’s effectiveness depends on the context in which it is applied. Traders should carefully consider the trade-offs between analysis and execution.
Results may vary depending on market conditions and chart types. Backtesting with ASA on standard charts provides more reliable insights compared to non-standard chart types.
Short-term use focuses on rapid trend recognition, while long-term application emphasizes understanding broader market movements.
Takeaways
ASA is not a tool for precise trade execution but a powerful aid for interpreting price trends.
For short-term trading, ASA identifies quick opportunities, while for long-term strategies, it highlights trend directions.
Understanding ASA’s limitations and strengths is key to maximizing its utility.
ASA is a robust solution for traders seeking to filter noise, enhance analytical clarity, and align their strategies with market movements, whether for short bursts of activity or sustained trading goals.
supertrendLibrary "supertrend"
supertrend : Library dedicated to different variations of supertrend
supertrend_atr(length, multiplier, atrMaType, source, highSource, lowSource, waitForClose, delayed)
supertrend_atr: Simple supertrend based on atr but also takes into consideration of custom MA Type, sources
Parameters:
length (simple int) : : ATR Length
multiplier (simple float) : : ATR Multiplier
atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
delayed (simple bool) : : if set to true lags supertrend atr stop based on target levels.
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
supertrend_bands(bandType, maType, length, multiplier, source, highSource, lowSource, waitForClose, useTrueRange, useAlternateSource, alternateSource, sticky)
supertrend_bands: Simple supertrend based on atr but also takes into consideration of custom MA Type, sources
Parameters:
bandType (simple string) : : Type of band used - can be bb, kc or dc
maType (simple string) : : Moving Average type for Bands. This can be sma, ema, hma, rma, wma, vwma, swma
length (simple int) : : Band Length
multiplier (float) : : Std deviation or ATR multiplier for Bollinger Bands and Keltner Channel
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
useTrueRange (simple bool) : : Used for Keltner channel. If set to false, then high-low is used as range instead of true range
useAlternateSource (simple bool) : - Custom source is used for Donchian Chanbel only if useAlternateSource is set to true
alternateSource (float) : - Custom source for Donchian channel
sticky (simple bool) : : if set to true borders change only when price is beyond borders.
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
supertrend_zigzag(length, history, useAlternativeSource, alternativeSource, source, highSource, lowSource, waitForClose, atrlength, multiplier, atrMaType)
supertrend_zigzag: Zigzag pivot based supertrend
Parameters:
length (simple int) : : Zigzag Length
history (simple int) : : number of historical pivots to consider
useAlternativeSource (simple bool)
alternativeSource (float)
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
atrlength (simple int) : : ATR Length
multiplier (simple float) : : ATR Multiplier
atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
zupertrend(length, history, useAlternativeSource, alternativeSource, source, highSource, lowSource, waitForClose, atrlength, multiplier, atrMaType)
zupertrend: Zigzag pivot based supertrend
Parameters:
length (simple int) : : Zigzag Length
history (simple int) : : number of historical pivots to consider
useAlternativeSource (simple bool)
alternativeSource (float)
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
atrlength (simple int) : : ATR Length
multiplier (simple float) : : ATR Multiplier
atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
zsupertrend(zigzagpivots, history, source, highSource, lowSource, waitForClose, atrMaType, atrlength, multiplier)
zsupertrend: Same as zigzag supertrend. But, works on already calculated array rather than Calculating fresh zigzag
Parameters:
zigzagpivots (array) : : Precalculated zigzag pivots
history (simple int) : : number of historical pivots to consider
source (float) : : Default is close. Can Chose custom source
highSource (float) : : Default is high. Can also use close price for both high and low source
lowSource (float) : : Default is low. Can also use close price for both high and low source
waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
atrlength (simple int) : : ATR Length
multiplier (simple float) : : ATR Multiplier
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
M2 Money Shift for Bitcoin [SAKANE]M2 Money Shift for Bitcoin was developed to visualize the impact of M2 Money, a macroeconomic indicator, on the Bitcoin market and to support trade analysis.
Bitcoin price fluctuations have a certain correlation with cycles in M2 money supply.In particular, it has been noted that changes in M2 supply can affect the bitcoin price 70 days in advance.Very high correlations have been observed in recent years in particular, making it useful as a supplemental analytical tool for trading.
Support for M2 data from multiple countries
M2 supply data from the U.S., Europe, China, Japan, the U.K., Canada, Australia, and India are integrated and all are displayed in U.S. dollar equivalents.
Slide function
Using the "Slide Days Forward" setting, M2 data can be slid up to 500 days, allowing for flexible analysis that takes into account the time difference from the bitcoin price.
Plotting Total Liquidity
Plot total liquidity (in trillions of dollars) by summing the M2 supply of multiple countries.
How to use
After applying the indicator to the chart, activate the M2 data for the required country from the settings screen. 2.
2. adjust "Slide Days Forward" to analyze the relationship between changes in M2 supply and bitcoin price
3. refer to the Gross Liquidity plot to build a trading strategy that takes into account macroeconomic influences.
Notes.
This indicator is an auxiliary tool for trade analysis and does not guarantee future price trends.
The relationship between M2 supply and bitcoin price depends on many factors and should be used in conjunction with other analysis methods.
Market Session Times and Volume [Market Spotter]Market Session Times and Volume
Market Session Times
Inputs
The inputs tab consists of timezone adjustment which would be the chosen timezone for the plotting of the market sessions based on the market timings.
Further it contains settings for each box to show/hide and change box colour and timings for Asian, London and New York Sessions.
How it works
The indicator primarily works by marking the session highs and lows for the chosen time in the inputs, each of the sessions can be input a custom time value which would plot the box. It helps to identify the important price levels and the trading range for each individual session.
The midpoint of each session is marked with a dashed line. The indicator also marks a developing session while it being formed as well to identify potential secondary levels.
Usage
It can be used to trade session breakouts, false breaks and also divide the daily movement into parts and identify possible patterns while trading.
2. Volumes
Inputs
The volume part has 2 inputs - Smoothing and Normalisation. The smoothing period can simply be used to take in charge volumes of last X bars and normalisation can be used for calculating relative volumes based on last Y bars.
How it works
The indicator takes into account the buy and sell volumes of last X bars and then displays that as a relative smoothed volume which helps to identify longer term build or distribution of volume. It plots the positive volume from 0 to 100 and negative volume from 0 to -100 which has been normalised. The colors identify gradual increase or decrease in volumes
Usage
It can also be used to trade volume spikes well and can identify potential market shifts
VD Zig Zag with SMAIntroduction
The VD Zig Zag with SMA indicator is a powerful tool designed to streamline technical analysis by combining Zig Zag swing lines with a Simple Moving Average (SMA). It offers traders a clear and intuitive way to analyze price trends, market structure, and potential reversals, all within a customizable framework.
Definition
The Zig Zag indicator is a trend-following tool that highlights significant price movements by filtering out smaller fluctuations. It visually connects swing highs and lows to reveal the underlying market structure. When paired with an SMA, it provides an additional layer of trend confirmation, helping traders align their strategies with market momentum.
Calculations
Zig Zag Logic:
Swing highs and lows are determined using a user-defined length parameter.
The highest and lowest points within the specified range are identified using the ta.highest() and ta.lowest() functions.
Zig Zag lines dynamically connect these swing points to visually map price movements.
SMA Logic:
The SMA is calculated using the closing prices over a user-defined period.
It smooths out price action to provide a clearer view of the prevailing trend.
The indicator allows traders to adjust the Zig Zag length and SMA period to suit their preferred trading timeframe and strategy.
Takeaways
Enhanced Trend Analysis: The Zig Zag lines clearly define the market's structural highs and lows, helping traders identify trends and reversals.
Customizable Parameters: Both the swing length and SMA period can be tailored for short-term or long-term trading strategies.
Visual Clarity: By filtering out noise, the indicator simplifies chart analysis and enables better decision-making.
Multi-Timeframe Support: Adapts seamlessly to the chart's timeframe, ensuring usability across all trading horizons.
Limitations
Lagging Nature: As with any indicator, the Zig Zag and SMA components are reactive and may lag during sudden price movements.
Sensitivity to Parameters: Improper parameter settings can lead to overfitting, where the indicator reacts too sensitively or misses significant trends.
Does Not Predict: This indicator identifies trends and structure but does not provide forward-looking predictions.
Summary
The VD Zig Zag with SMA indicator is a versatile and easy-to-use tool that combines the strengths of Zig Zag swing analysis and moving average trends. It helps traders filter market noise, visualize structural patterns, and confirm trends with greater confidence. While it comes with limitations inherent to all technical tools, its customizable features and multi-timeframe adaptability make it an excellent addition to any trader’s toolkit.
Additional Features
Have an idea or a feature you'd like to see added?
Feel free to reach out or share your suggestions here—I’m always open to updates!
Custom V2 KillZone US / FVG / EMAThis indicator is designed for traders looking to analyze liquidity levels, opportunity zones, and the underlying trend across different trading sessions. Inspired by the ICT methodology, this tool combines analysis of Exponential Moving Averages (EMA), session management, and Fair Value Gap (FVG) detection to provide a structured and disciplined approach to trading effectively.
Indicator Features
Identifying the Underlying Trend with Two EMAs
The indicator uses two EMAs on different, customizable timeframes to define the underlying trend:
EMA1 (default set to a daily timeframe): Represents the primary underlying trend.
EMA2 (default set to a 4-hour timeframe): Helps identify secondary corrections or impulses within the main trend.
These two EMAs allow traders to stay aligned with the market trend by prioritizing trades in the direction of the moving averages. For example, if prices are above both EMAs, the trend is bullish, and long trades are favored.
Analysis of Market Sessions
The indicator divides the day into key trading sessions:
Asian Session
London Session
US Pre-Open Session
Liquidity Kill Session
US Kill Zone Session
Each session is represented by high and low zones as well as mid-lines, allowing traders to visualize liquidity levels reached during these periods. Tracking the price levels in different sessions helps determine whether liquidity levels have been "swept" (taken) or not, which is essential for ICT methodology.
Liquidity Signal ("OK" or "STOP")
A specific signal appears at the end of the "Liquidity Kill" session (just before the "US Kill Zone" session):
"OK" Signal: Indicates that liquidity conditions are favorable for trading the "US Kill Zone" session. This means that liquidity levels have been swept in previous sessions (Asian, London, US Pre-Open), and the market is ready for an opportunity.
"STOP" Signal: Indicates that it is not favorable to trade the "US Kill Zone" session, as certain liquidity conditions have not been met.
The "OK" or "STOP" signal is based on an analysis of the high and low levels from previous sessions, allowing traders to ensure that significant liquidity zones have been reached before considering positions in the "Kill Zone".
Detection of Fair Value Gaps (FVG) in the US Kill Zone Session
When an "OK" signal is displayed, the indicator identifies Fair Value Gaps (FVG) during the "US Kill Zone" session. These FVGs are areas where price may return to fill an "imbalance" in the market, making them potential entry points.
Bullish FVG: Detected when there is a bullish imbalance, providing a buying opportunity if conditions align with the underlying trend.
Bearish FVG: Detected when there is a bearish imbalance, providing a selling opportunity in the trend direction.
FVG detection aligns with the ICT Silver Bullet methodology, where these imbalance zones serve as probable entry points during the "US Kill Zone".
How to Use This Indicator
Check the Underlying Trend
Before trading, observe the two EMAs (daily and 4-hour) to understand the general market trend. Trades will be prioritized in the direction indicated by these EMAs.
Monitor Liquidity Signals After the Asian, London, and US Pre-Open Sessions
The high and low levels of each session help determine if liquidity has already been swept in these areas. At the end of the "Liquidity Kill" session, an "OK" or "STOP" label will appear:
"OK" means you can look for trading opportunities in the "US Kill Zone" session.
"STOP" means it is preferable not to take trades in the "US Kill Zone" session.
Look for Opportunities in the US Kill Zone if the Signal is "OK"
When the "OK" label is present, focus on the "US Kill Zone" session. Use the Fair Value Gaps (FVG) as potential entry points for trades based on the ICT methodology. The identified FVGs will appear as colored boxes (bullish or bearish) during this session.
Use ICT Methodology to Manage Your Trades
Follow the FVGs as potential reversal zones in the direction of the trend, and manage your positions according to your personal strategy and the rules of the ICT Silver Bullet method.
Customizable Settings
The indicator includes several customization options to suit the trader's preferences:
EMA: Length, source (close, open, etc.), and timeframe.
Market Sessions: Ability to enable or disable each session, with color and line width settings.
Liquidity Signals: Customization of colors for the "OK" and "STOP" labels.
FVG: Option to display FVGs or not, with customizable colors for bullish and bearish FVGs, and the number of bars for FVG extension.
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Cet indicateur est conçu pour les traders souhaitant analyser les niveaux de liquidité, les zones d’opportunité, et la tendance de fond à travers différentes sessions de trading. Inspiré de la méthodologie ICT, cet outil combine l'analyse des moyennes mobiles exponentielles (EMA), la gestion des sessions de marché, et la détection des Fair Value Gaps (FVG), afin de fournir une approche structurée et disciplinée pour trader efficacement.
MERCURY by DrAbhiramSivprasad"MERCURY by DrAbhiramSivprasad"
Developed from over 10 years of personal trading experience, the Mercury Indicator is a strategic tool designed to enhance accuracy in trading decisions. Think of it as a guiding light—a supportive tool that helps traders refine and build more robust strategies by integrating multiple powerful elements into a single indicator. I’ll be sharing some examples to illustrate how I use this indicator in my own trading journey, highlighting its potential to improve strategy accuracy.
Reason behind the combination of emas , cpr and vwap is it provides very good support and resistance in my trading carrier so now i brought them together in one plate
How It Works:
Mercury combines three essential elements—EMA, VWAP, and CPR—each of which plays a vital role in detecting support and resistance:
Exponential Moving Averages (EMAs): Known for their strength in providing dynamic support and resistance levels, EMAs help in identifying trends and shifts in momentum. This indicator includes a dashboard with up to nine customizable EMAs, showing whether each is acting as support or resistance based on real-time price movement.
Volume Weighted Average Price (VWAP): VWAP also provides valuable support and resistance, often regarded as a fair price level by institutional traders. Paired with EMAs, it forms a dual-layered support/resistance system, adding an additional level of confirmation.
Central Pivot Range (CPR): By combining CPR with EMAs and VWAP, Mercury highlights “traffic blocks” in your target journey. This means it identifies zones where price is likely to stall or reverse, providing additional guidance for navigating entries and exits.
Why This Combination Matters:
Using these three tools together gives you a more complete view of the market. VWAP and EMAs offer dynamic trend direction and support/resistance, while CPR pinpoints critical price zones. This combination helps you find high-probability trades, adding clarity to complex market situations and enabling stronger confirmation on trend or reversal decisions.
How to Use:
Trend Confirmation: Check if all EMAs are aligned (green for uptrend, red for downtrend), which is visible in the EMA dashboard. An alignment across VWAP, CPR, and EMAs signifies high confidence in trend direction.
Breakouts & Breakdowns: Mercury has an alert system to signal when a price breakout or breakdown occurs across VWAP, EMA1, and EMA2. This can help in spotting strong directional moves.
Example Application: In my trading, I use Mercury to identify support/resistance zones, confirming trends with EMA/VWAP alignment and using CPR as a checkpoint. I find this especially useful for day trading and swing setups.
Recommended Timeframes:
Day Trading: 5 to 15-minute charts for swift, actionable insights.
Swing Trading: 1-hour or 4-hour charts for broader trend analysis.
Note:
The Mercury Indicator should be used as a supportive tool rather than a standalone strategy, guiding you toward informed decisions in line with your trading style and goals.
EXAMPLE OF TRADE
you can see the cart of XAUUSD on 11th nov 2024
1.SHORT POSITION - TIME FRAME 15 MIN
So here for a short position you need to wait for a breakdown candle which will print in orange post the candle you need to check ema dashboard is completly red that indicates no traffic blocks in your journey to destiny target from ema's and you can take the target from nearest cpr support line
TAKEN IN XAUUSD you can see in chart of XAUUSD on 7th nov
2.LONG POSITION - TIME FRAME 15 MIN -
So here for long position you need to wait for a breakout candle from indicator thats here is blue and check all ema boxes are green and candle body should close above all the 3 lines here it is the both ema 1 and 2 and the vwap line then you can take and entry and your target will be the nearest resistance from the daily cpr
3. STOP LOSS CRITERIA
After the entry any candle close below any of the last line from entry for example we have 3 lines vwap and ema 1 and 2 lines and u have made an entry and the last line before the entry is vwap then if any candle closes below vwap can be considered as stoploss like wise in any lines
The MERCURY indicator is a comprehensive trading tool designed to enhance traders' ability to identify trends, breakouts, and reversals effectively. Created by Dr. Abhiram Sivprasad, this indicator integrates several technical elements, including Central Pivot Range (CPR), EMA crossovers, VWAP levels, and a table-based EMA dashboard, to offer a holistic trading view.
Core Components and Functionality:
Central Pivot Range (CPR):
The CPR in MERCURY provides a central pivot level along with Below Central (BC) and Top Central (TC) pivots. These levels act as potential support and resistance, useful for identifying reversal points and zones where price may consolidate.
Exponential Moving Averages (EMAs):
MERCURY includes up to nine EMAs, with a customizable EMA crossover alert system. This feature enables traders to see shifts in trend direction, especially when shorter EMAs cross longer ones.
VWAP (Volume-Weighted Average Price):
VWAP is incorporated as a dynamic support/resistance level and, combined with EMA crossovers, helps refine entry and exit points for higher probability trades.
Breakout and Breakdown Alerts:
MERCURY monitors conditions for upside and downside breakouts. For an upside breakout, all EMAs turn green and a candle closes above VWAP, EMA1, and EMA2. Similarly, all EMAs turning red, combined with a close below VWAP and EMA1/EMA2, signals a downside breakdown. Continuous alerts are available until the trend shifts.
Real-Time EMA Dashboard:
A table displays each EMA’s relative position (Above or Below), helping traders quickly gauge trend direction. Colors in the table adjust to long/short conditions based on EMA alignment.
Usage Recommendations:
Trend Confirmation:
Use the CPR, EMA alignments, and VWAP to confirm uptrends and downtrends. The table highlights trends, making it easy to spot long or short setups at a glance.
Breakout and Breakdown Alerts:
The alert system is customizable for continuous notifications on critical price levels. When all EMAs align in one direction (green for long, red for short) and the close is above or below VWAP and key EMAs, the indicator confirms a breakout/breakdown.
Adaptable for Different Styles:
Day Trading: Traders can set shorter EMAs for quick insights.
Swing Trading: Longer EMAs combined with CPR offer insights into sustained trends.
Recommended Settings:
Timeframes: MERCURY is suitable for timeframes as low as 5 minutes for intraday traders, up to daily charts for trend analysis.
Symbols: Works across forex, stocks, and crypto. Adjust EMA lengths for asset volatility.
Example Strategy:
Long Entry: When the price crosses above CPR and closes above both EMA1 and EMA2.
Short Entry: When the price falls below CPR with a close below both EMA1 and EMA2.
Sharpe Ratio Z-ScoreThis indicator calculates the Sharpe Ratio and its Z-Score , which are used to evaluate the risk-adjusted return of an asset over a given period. The Sharpe Ratio is computed using the average return and the standard deviation of returns, while the Z-Score standardizes this ratio to assess how far the current Sharpe Ratio deviates from its historical average.
The Sharpe Ratio is a measure of how much return an investment has generated relative to the risk it has taken. In the context of this script, the risk-free rate is assumed to be 0, but in real applications, it would typically be the return on a safe investment, like a Treasury bond. A higher Sharpe Ratio indicates that the investment's returns are higher compared to its risk, making it a more favorable investment. Conversely, a lower Sharpe Ratio suggests that the investment may not be worth the risk.
Calculation:
Daily Returns Calculation: The script calculates the daily return of the asset. This measures the percentage change in the asset’s closing price from one period to the next.
Sharpe Ratio Calculation: The Sharpe Ratio is calculated by taking the average daily return and dividing it by the standard deviation of the returns, then multiplying by the square root of the period length.
Usage:
Traders and Investors can use the Sharpe Ratio to evaluate how well the asset is compensating for risk. A high Sharpe Ratio indicates a high return per unit of risk, whereas a low or negative Sharpe Ratio suggests poor risk-adjusted returns. In overbought times, an asset would have high/positive returns per unit of risk. In oversold times, an asset would have low/negative returns per unit of risk.
The Z-Score provides a way to compare the current Sharpe Ratio to its historical distribution, offering a more standardized view of how extreme or typical the current ratio is.
Positive Z-score: Indicates that the asset's return is significantly lower than its risk, suggesting potential oversold conditions.
Negative Z-score: Indicates that the asset's return is significantly higher than its risk, suggesting potential overbought conditions.
Red Zone (-3 to -2): Strong overbought conditions.
Green Zone (2 to 3): Strong oversold conditions.
Sharpe Ratio Limitations:
While the Sharpe Ratio is widely used to evaluate risk-adjusted returns, it has its limitations.
Fat Tails: It assumes that returns are normally distributed and does not account for extreme events or "fat tails" in the return distribution. This can be problematic for assets like cryptocurrencies, which may experience large, sudden price swings that skew the return distribution.
Single Risk Factor: The Sharpe Ratio only considers standard deviation (total volatility) as a measure of risk, ignoring other types of risks like skewness or kurtosis, which may also impact an asset’s performance.
Time Frame Sensitivity: The accuracy of the Sharpe Ratio and its Z-Score is heavily influenced by the time frame chosen for the calculation. A longer period may smooth out short-term fluctuations, while a shorter period might be more sensitive to recent volatility.
Overbought and Oversold Zones: The script marks overbought and oversold conditions based on the Z-Score, but this is not a guarantee of market reversal. It’s important to combine this tool with other technical indicators and fundamental analysis for a more comprehensive market evaluation.
Volatility: The Sharpe Ratio and Z-Score depend on the volatility (standard deviation) of the asset’s returns. For highly volatile assets, such as cryptocurrencies, the Sharpe Ratio may not fully capture the true risk or may be misleading if the volatility is transient.
Doesn't Account for Downside Risk: The Sharpe Ratio treats upside and downside volatility equally, which may not reflect how investors perceive risk. Some investors may be more concerned with downside risk, which the Sharpe Ratio does not distinguish from upside fluctuations.
Important Considerations:
The Sharpe Ratio should not be used in isolation. While it provides valuable insights into risk-adjusted returns, it is important to combine it with other performance and risk indicators to form a more comprehensive market evaluation. Relying solely on the Sharpe Ratio may lead to misleading conclusions, particularly in volatile or non-normally distributed markets.
When integrated into a broader investment strategy, the Sharpe Ratio can help traders and investors better assess the risk-return profile of an asset, identifying periods of potential overperformance or underperformance. However, it should be used alongside other tools to ensure more informed decision-making, especially in highly fluctuating markets.
Enhanced London Session SMC SetupEnhanced London Session SMC Setup Indicator
This Pine Script-based indicator is designed for traders focusing on the London trading session, leveraging smart money concepts (SMC) to identify potential trading opportunities in the GBP/USD currency pair. The script uses multiple techniques such as Order Block Detection, Imbalance (Fair Value Gap) Analysis, Change of Character (CHoCH) detection, and Fibonacci retracement levels to aid in market structure analysis, providing a well-rounded approach to trade setups.
Features:
London Session Highlight:
The indicator visually marks the London trading session (from 08:00 AM to 04:00 PM UTC) on the chart using a blue background, signaling when the high-volume, high-impulse moves tend to occur, helping traders focus their analysis on this key session.
Order Block Detection:
Identifies significant impulse moves that may form order blocks (supply and demand zones). Order blocks are areas where institutions have executed large orders, often leading to price reversals or continuation. The indicator plots the high and low of these order blocks, providing key levels to monitor for potential entries.
Imbalance (Fair Value Gap) Detection:
Detects and highlights price imbalances or fair value gaps (FVG) where the market has moved too quickly, creating a gap in price action. These areas are often revisited by price, offering potential trade opportunities. The upper and lower bounds of the imbalance are visually marked for easy reference.
Change of Character (CHoCH) Detection:
This feature identifies potential trend reversals by detecting significant changes in market character. When the price action shifts from bullish to bearish or vice versa, a CHoCH signal is triggered, and the corresponding level is marked on the chart. This can help traders catch trend reversals at key levels.
Fibonacci Retracement Levels:
The script calculates and plots the key Fibonacci retracement levels (0.618 and 0.786 by default) based on the highest and lowest points over a user-defined swing lookback period. These levels are commonly used by traders to identify potential pullback zones where price may reverse or find support/resistance.
Directional Bias Based on Market Structure:
The indicator provides a market structure analysis by comparing the current highs and lows to the previous periods' highs and lows. This helps in identifying whether the market is in a bullish or bearish state, providing a clear directional bias for trade setups.
Alerts:
The indicator comes with built-in alert conditions to notify the trader when an order block, imbalance, CHoCH, or other significant price action event is detected, ensuring timely action can be taken.
Ideal Usage:
Timeframe: Suitable for intraday trading, particularly focusing on the London session (08:00 AM to 04:00 PM UTC).
Currency Pair: Specifically designed for GBP/USD but can be adapted to other pairs with similar market behavior.
Trading Strategy: Best used in conjunction with a price action strategy, focusing on the key levels identified (order blocks, FVG, CHoCH) and using Fibonacci retracement levels for precision entries.
Target Audience: Ideal for traders who follow smart money concepts (SMC) and are looking for a structured approach to identify high-probability setups during the London session.
Original Keltner with Support And ResistanceThis indicator is based on the original Keltner Channels using typical price and calculating the 10 period average of high - low
Typical price = (high + low + close)/3
In this case, I've taken Typical price as (open + high + low + close)/4 on the advice of John Bollinger from his book Bollinger on Bollinger Bands.
Buy Line = 10 Period Typical Price Average + 10 Period Average of (High - Low)
Sell Line = 10 Period Typical Price Average - 10 Period Average of (High - Low)
This is the basis for the indicator. I've added the highest of the Buy Line and lowest of the Sell Line for the same period which acts as Support and Resistance.
If price is trending below the Lowest of Sell Line, take only sell trades and the Lowest Line acts as resistance.
If price is trending above the Highest of Buy Line, take only buy trades and the Highest Line acts as support.
Target Trend [BigBeluga]The Target Trend indicator is a trend-following tool designed to assist traders in capturing directional moves while managing entry, stop loss, and profit targets visually on the chart. Using adaptive SMA bands as the core trend detection method, this indicator dynamically identifies shifts in trend direction and provides structured exit points through customizable target levels.
SP500:
🔵 IDEA
The Target Trend indicator’s concept is to simplify trade management by providing automated visual cues for entries, stops, and targets directly on the chart. When a trend change is detected, the indicator prints an up or down triangle to signal entry direction, plots three customizable target levels for potential exits, and calculates a stop-loss level below or above the entry point. The indicator continuously adapts as price moves, making it easier for traders to follow and manage trades in real time.
When price crosses a target level, the label changes to a check mark, confirming that the target has been achieved. Similarly, if the stop-loss level is hit, the label changes to an "X," and the line becomes dashed, indicating that the stop loss has been activated. This feature provides traders with a clear visual trail of whether their targets or stop loss have been hit, allowing for easier trade tracking and exit strategy management.
🔵 KEY FEATURES & USAGE
SMA Bands for Trend Detection: The indicator uses adaptive SMA bands to identify the trend direction. When price crosses above or below these bands, a new trend is detected, triggering entry signals. The entry point is marked on the chart with a triangle symbol, which updates with each new trend change.
Automated Targets and Stop Loss Management: Upon a new trend signal, the indicator automatically plots three price targets and a stop loss level. These levels provide traders with structured exit points for potential gains and a clear risk limit. The stop loss is placed below or above the entry point, depending on the trend direction, to manage downside risk effectively.
Visual Target and Stop Loss Validation: As price hits each target, the label beside the level updates to a check mark, indicating that the target has been reached. Similarly, if the stop loss is activated, the stop loss label changes to an "X," and the line becomes dashed. This feature visually confirms whether targets or stop losses are hit, simplifying trade management.
The indicator also marks the entry price at each trend change with a label on the chart, allowing traders to quickly see their initial entry point relative to current price and target levels.
🔵 CUSTOMIZATION
Trend Length: Set the lookback period for the trend-detection SMA bands to adjust the sensitivity to trend changes.
Targets Setting: Customize the number and spacing of the targets to fit your trading style and market conditions.
Visual Styles: Adjust the appearance of labels, lines, and symbols on the chart for a clearer view and personalized layout.
🔵 CONCLUSION
The Target Trend indicator offers a streamlined approach to trend trading by integrating entry, target, and stop loss management into a single visual tool. With automatic tracking of target levels and stop loss hits, it helps traders stay focused on the current trend while keeping track of risk and reward with minimal effort.
Range Detect SystemTechnical analysis indicator designed to identify potential significant price ranges and the distribution of volume within those ranges. The system helps traders calculate POC and show volume history. Also detecting breakouts or potential reversals. System identifies ranges with a high probability of price consolidation and helps screen out extreme price moves or ranges that do not meet certain volatility thresholds.
⭕️ Key Features
Range Detection — identifies price ranges where consolidation is occurring.
Volume Profile Calculation — indicator calculates the Point of Control (POC) based on volume distribution within the identified range, enhancing the analysis of market structure.
Volume History — shows where the largest volume was traded from the center of the range. If the volume is greater in the upper part of the range, the color will be green. If the volume is greater in the lower part, the color will be red.
Range Filtering — Includes multi-level filtering options to avoid ranges that are too volatile or outside normal ranges.
Visual Customization — Shows graphical indicators for potential bullish or bearish crossovers at the upper and lower range boundaries. Users can choose the style and color of the lines, making it easier to visualize ranges and important levels on the chart.
Alerts — system will notify you when a range has been created and also when the price leaves the range.
⭕️ How it works
Extremes (Pivot Points) are taken as a basis, after confirming the relevance of the extremes we take the upper and lower extremes and form a range. We check if it does not violate a number of rules and filters, perform volume calculations, and only then is the range displayed.
Pivot points is a built-in feature that shows an extremum if it has not been updated N bars to the left and N bars to the right. Therefore, there is a delay depending on the bars specified to check, which allows for a more accurate range. This approach allows not to make unnecessary recalculations, which completely eliminates the possibility of redrawing or range changes.
⭕️ Settings
Left Bars and Right Bars — Allows you to define the point that is the highest among the specified number of bars to the left and right of this point.
Range Logic — Select from which point to draw the range. Maximums only, Minimums only or both.
Use Wick — Option to consider the wick of the candles when identifying Range.
Breakout Confirmation — The number of bars required to confirm a breakout, after which the range will close.
Minimum Range Length — Sets the minimum number of candles needed for a range to be considered valid.
Row Size — Number of levels to calculate POC. *Larger values increase the script load.
% Range Filter — Dont Show Range is than more N% of Average Range.
Multi Filter — Allows use of Bollinger Bands, ATR, SMA, or Highest-Lowest range channels for filtering ranges based on volatility.
Range Hit — Shows graphical labels when price hits the upper or lower boundaries of the range, signaling potential reversal or breakout points.
Range Start — Show points where Range was created.
STANDARD DEVIATION INDICATOR BY WISE TRADERWISE TRADER STANDARD DEVIATION SETUP: The Ultimate Volatility and Trend Analysis Tool
Unlock the power of STANDARD DEVIATIONS like never before with the this indicator, a versatile and comprehensive tool designed for traders who seek deeper insights into market volatility, trend strength, and price action. This advanced indicator simultaneously plots three sets of customizable Deviations, each with unique settings for moving average types, standard deviations, and periods. Whether you’re a swing trader, day trader, or long-term investor, the STANDARD DEVIATION indicator provides a dynamic way to spot potential reversals, breakouts, and trend-following opportunities.
Key Features:
STANDARD DEVIATIONS Configuration : Monitor three different Bollinger Bands at the same time, allowing for multi-timeframe analysis within a single chart.
Customizable Moving Average Types: Choose from SMA, EMA, SMMA (RMA), WMA, and VWMA to calculate the basis of each band according to your preferred method.
Dynamic Standard Deviations: Set different standard deviation multipliers for each band to fine-tune sensitivity for various market conditions.
Visual Clarity: Color-coded bands with adjustable thicknesses provide a clear view of upper and lower boundaries, along with fill backgrounds to highlight price ranges effectively.
Enhanced Trend Detection: Identify potential trend continuation, consolidation, or reversal zones based on the position and interaction of price with the three bands.
Offset Adjustment: Shift the bands forward or backward to analyze future or past price movements more effectively.
Why Use Triple STANDARD DEVIATIONS ?
STANDARD DEVIATIONS are a popular choice among traders for measuring volatility and anticipating potential price movements. This indicator takes STANDARD DEVIATIONS to the next level by allowing you to customize and analyze three distinct bands simultaneously, providing an unparalleled view of market dynamics. Use it to:
Spot Volatility Expansion and Contraction: Track periods of high and low volatility as prices move toward or away from the bands.
Identify Overbought or Oversold Conditions: Monitor when prices reach extreme levels compared to historical volatility to gauge potential reversal points.
Validate Breakouts: Confirm the strength of a breakout when prices move beyond the outer bands.
Optimize Risk Management: Enhance your strategy's risk-reward ratio by dynamically adjusting stop-loss and take-profit levels based on band positions.
Ideal For:
Forex, Stocks, Cryptocurrencies, and Commodities Traders looking to enhance their technical analysis.
Scalpers and Day Traders who need rapid insights into market conditions.
Swing Traders and Long-Term Investors seeking to confirm entry and exit points.
Trend Followers and Mean Reversion Traders interested in combining both strategies for maximum profitability.
Harness the full potential of STANDARD DEVIATIONS with this multi-dimensional approach. The "STANDARD DEVIATIONS " indicator by WISE TRADER will become an essential part of your trading arsenal, helping you make more informed decisions, reduce risks, and seize profitable opportunities.
Who is WISE TRADER ?
Wise Trader is a highly skilled trader who launched his channel in 2020 during the COVID-19 pandemic, quickly building a loyal following. With thousands of paid subscribed members and over 70,000 YouTube subscribers, Wise Trader has become a trusted authority in the trading world. He is known for his ability to navigate significant events, such as the Indian elections and stock market crashes, providing his audience with valuable insights into market movements and volatility. With a deep understanding of macroeconomics and its correlation to global stock markets, Wise Trader shares informed strategies that help traders make better decisions. His content covers technical analysis, trading setups, economic indicators, and market trends, offering a comprehensive approach to understanding financial markets. The channel serves as a go-to resource for traders who want to enhance their skills and stay informed about key market developments.
Liquidity VisualizerThe "Liquidity Visualizer" indicator is designed to help traders visualize potential areas of liquidity on a price chart. In trading, liquidity often accumulates around key levels where market participants have placed their stop orders or pending orders. These levels are commonly found at significant highs and lows, where traders tend to set their stop-losses or take-profit orders. The indicator aims to highlight these areas by drawing unbroken lines that extend indefinitely until breached by the price action.
Specifically, this indicator identifies and marks pivot highs and pivot lows, which are price levels where a trend changes direction. When a pivot high or pivot low is formed, it is represented on the chart with a horizontal line that continues to extend until the price touches or surpasses that level. The line remains in place as long as the level remains unbroken, which means there is potential liquidity still resting at that level.
The concept behind this indicator is that liquidity is likely to be resting at unbroken pivot points. These levels are areas where stop-loss orders or pending buy/sell orders may have accumulated, making them attractive zones for large market participants, such as institutions, to target. By visualizing these unbroken levels, traders can gain insight into where liquidity might be concentrated and where potential price reversals or significant movements could occur as liquidity is taken out.
The indicator helps traders make more informed decisions by showing them key price levels that may attract significant market activity. For instance, if a trader sees multiple unbroken pivot high lines above the current price, they might infer that there is a cluster of liquidity in that area, which could lead to a price spike as those levels are breached. Similarly, unbroken pivot lows may indicate areas where downside liquidity is concentrated.
In summary, this indicator acts as a "liquidity visualizer," providing traders with a clear, visual representation of potential liquidity resting at significant pivot points. This information can be valuable for understanding where price might be drawn to, and where large movements might occur as liquidity is targeted and removed by market participants.
Larry Williams Valuation Index [tradeviZion]Larry Williams Valuation Index
Welcome to the Larry Williams Valuation Index by tradeviZion! This script is an interpretation of Larry Williams' famous WillVal (Valuation) Index, originally developed in 1990 to help traders determine whether a market or asset is overvalued or undervalued. We've extended it to support multiple securities and offer alerts for different valuation levels, helping you make more informed trading decisions.
What is the Valuation Index?
The Valuation Index measures how a security's current price compares to its historical price action. It helps identify whether the security is overvalued (priced too high), undervalued (priced too low), or in a normal range.
This version supports multiple securities and uses valuation parameters to help you assess the relative valuation of three securities simultaneously. It can help you determine the best times to enter (buy) or exit (sell) the market.
Key Features
Multi-Security Analysis: Analyze up to three securities simultaneously to get a broader view of market conditions.
Valuation Levels: Automatically calculate overvaluation and undervaluation levels or set manual levels for consistent analysis.
Custom Alerts: Create custom alerts when securities move between overvalued, undervalued, or normal ranges.
Customizable Table Display: Display a table with valuation values and their status on the chart.
Getting Started
Step 1: Adding the Script to Your Chart
First, add the Larry Williams Valuation Index script to your chart on TradingView. The script is designed to work with any timeframe, but for best results, use weekly or daily timeframes for a longer-term perspective.
Step 2: Configuring Securities
The script allows you to analyze up to three different securities :
Security 1 (Default: DXY)
Security 2 (Default: GC1!)
Security 3 (Default: ZB1!)
You can enable or disable each security individually.
Custom Timeframe Option: You have the option to select a custom timeframe for analysis. This allows you to see whether the security is overvalued or undervalued in lower or higher timeframes. Note that this feature is experimental and has not been extensively tested. Larry Williams originally used the weekly timeframe to determine if a stock was overvalued or undervalued. By default, the indicator compares the current price with the security based on the selected timeframe, except if you choose to use a custom timeframe.
Pro Tip : New users can start with the default securities to understand the concept before using other assets.
Step 3: Valuation Index Settings
Short EMA Length : This is the short-term average used for calculations. A lower value makes it more responsive to recent price changes.
Long EMA Length : This is the long-term average, used to smooth the valuation over time.
Valuation Length (Default: 156) : Represents approximately three years of daily bars (as recommended by Larry Williams).
How is the Valuation Index Calculated?
The valuation calculation is done using a method called WVI (WillVal Index), which compares the current price of a security to the price of another correlated security. Here’s a step-by-step explanation:
1. Data Collection: The script takes the closing price of the security you are analyzing and the closing price of the correlated security.
2. Ratio Calculation : The ratio of the two prices is calculated:
Price Ratio = (Price of your security) / (Price of correlated security) * 100.
This ratio helps determine how expensive or cheap your security is compared to the correlated one.
3. Exponential Moving Averages (EMAs) : The price ratio is used to calculate short-term and long-term EMAs (Exponential Moving Averages). EMAs are used to create smooth lines that represent the average price of a security over a specific period of time, with more weight given to recent data. By calculating both short-term and long-term EMAs, we can identify the trend direction and how the security is performing compared to its historical averages.
4. Valuation Index Calculation:
The Valuation Index is calculated as the difference between the short-term EMA and the long-term EMA. This difference helps to determine if the security is currently overvalued or undervalued:
A positive value indicates that the price is above its longer-term trend, suggesting potential overvaluation.
A negative value indicates that the price is below its longer-term trend, suggesting potential undervaluation.
5. Normalization:
To make the valuation easier to interpret, the calculated valuation index is then normalized using the highest and lowest values over the selected valuation length (e.g., 156 bars).
This normalization process converts the index into a percentage between 0 and 100, where higher values indicate overvaluation and lower values indicate undervaluation.
Step 4: Understanding Valuation Levels
The valuation levels indicate whether a security is currently undervalued, overvalued, or in a normal range.
Manual Levels : You can manually set the overvaluation and undervaluation thresholds (default is 85 for overvalued and 15 for undervalued).
Auto Levels : The script can automatically calculate these levels based on recent price action, allowing you to adapt to changing market conditions.
Auto Levels Calculation Explained:
The Auto Levels are calculated by taking the average of the valuation indices for all three securities (e.g., index1, index2, and index3).
The script then looks at the highest and lowest values of this average over a selected number of recent bars (e.g., 50 bars).
The overvaluation level is determined by taking the highest value and multiplying it by a multiplier (e.g., 5). Similarly, the undervaluation level is calculated using the lowest value and the multiplier.
These dynamic levels adjust according to recent price action, providing an adaptive approach to identifying overvalued and undervalued conditions.
Step 5: How to Use the Script to Make Trading Decisions
For new users, here's a step-by-step trading strategy you can use with the Valuation Index:
1. Identify Undervalued Opportunities
When two or more securities are in the undervalued range (below 15 for manual or below automatically calculated undervalue levels), wait for at least two of these securities to turn from undervalued to normal .
This transition indicates a potential buy opportunity .
2. Buying Signal
When at least two securities transition from undervalued to normal, you can consider buying the asset.
This indicates that the market may be recovering from undervalued conditions and could be moving into a growth phase.
3. Selling Signal
Exit when the price high closes below the EMA 21 (21-day exponential moving average).
Alternatively, if the valuation index reaches overvalued levels (above 85 manually or auto-calculated), wait for it to drop back to normal . This can be another point to exit the trade .
You can also use any other sell condition based on your r isk management strategy .
Alerts for Valuation Levels
The script includes alerts to notify you of changing market conditions:
To activate these alerts, follow these steps, referring to the provided screenshot with detailed steps:
1. Enable Alerts : Click on the settings gear icon on the script title in your chart. In the settings menu, scroll to the section labeled Alerts Settings .
Enable Alerts by checking the Enable Alerts box.
Set the Required Securities for Alert (default is 2 securities).
Choose the Alert Frequency : Selecting Once Per Bar Close will trigger alerts only at the close of each bar, ensuring you receive confirmed signals rather than potentially noisy intermediate signals.
2. Select Alert Type : Choose the type of alert you want to activate, such as Alert on Overvalued, Alert on Undervalued, Alert on Over to Normal , or Alert on Under to Normal .
3. Save Settings : Click OK to save your alert settings.
4. Add Alert on Indicator : Click the "..." (More button) next to the indicator name on the chart and select " Add alert on tradeviZion - WillVal ".
5. Create Alert : In the Create Alert window:
Set Condition to tradeviZion - WillVal .
Ensure Any alert() function call is selected.
Set the Alert Name and select your Expiration preferences.
6. Set Notification Preferences : Go to the Notifications tab and select how you want to receive notifications, such as via app notification, toast notification, email , or sound alert . Adjust these preferences to best suit your needs.
7. Click Create : Finally, click Create to activate the alert.
These alerts will help you stay informed about key market conditions and take action accordingly, ensuring you do not miss critical trading opportunities.
Understanding the Table Display
The script includes an interactive table on the chart to show the valuation status of each security:
Security : The name of the security being analyzed.
Value : The current valuation index value.
Status : Indicates whether the security is overvalued, undervalued , or in a normal range.
Color: Displays a color code for easy identification of status:
Red for overvalued.
Green for undervalued.
Other colors represent normal valuation levels.
Empowering Messages : Motivational messages are displayed to encourage disciplined trading. These messages will change periodically, helping keep a positive trading mindset.
Acknowledgment
This tool builds upon the foundational work of Larry Williams, who developed the WillVal (Valuation) Index concept. It also incorporates enhancements to extend multi-security analysis, valuation normalization, and advanced alerting features, providing a more versatile and powerful indicator. The Larry Williams Valuation Index [ tradeviZion ] helps traders make informed decisions by assessing overvalued and undervalued conditions for multiple securities simultaneously.
Note : Always practice proper risk management and thoroughly test the indicator to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
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