Bollinger Band Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of Bollinger Bands, candle wicks crossing the upper and lower Bollinger Bands and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional, B1 and S1 signals can be displayed that use the baseline as the pivot level.
Settings
SIGNALS
Show Bollinger Band Signals (Default: True): Allows signal labels to be shown.
Hide Baseline Signals (Default: False): Baseline signals are on by default. This will turn them off.
Show Wick Signals (Defau
lt: True): Displays signals when wicking occurs.
BOLLINGER BAND SETTINGS
Period length for Bollinger Band Basis (Default: 21): Length of the Bollinger Band (BB) moving average basis line.
Basis MA Type (Default: SMA): The moving average type for the BB Basis line.
Source (Default: “close”): The source of time series data.
Standard Deviation Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
WICK SETTINGS FOR BOLLINGER BANDS
Wick Ratio for Bands (Default: 0.3): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.3): The ratio of wick size to total candle size for use at baseline.
WICK SETTINGS FOR CANDLE SIGNALS
Upper Wick Threshold (Default: 50): The percent of upper wick compared to the full candle size or candle body size.
Lower Wick Threshold (Default: 50): The percent of lower wick compared to the full candle size or candle body size.
Use Candle Body (Default: false): Toggles the use of the full candle size versus the candle body size when calculating the wick signal.
VISUAL PREFERENCES
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
Show Signals (Default: true): Toggle the Bollinger Band upper band, lower band, and baseline signals.
Show Bollinger Bands (Default: true): Show the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Calculations
Bollinger Bands are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. Bollinger Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of standard deviations to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of standard deviations from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
在脚本中搜索"market structure"
BAERMThe Bitcoin Auto-correlation Exchange Rate Model: A Novel Two Step Approach
THIS IS NOT FINANCIAL ADVICE. THIS ARTICLE IS FOR EDUCATIONAL AND ENTERTAINMENT PURPOSES ONLY.
If you enjoy this software and information, please consider contributing to my lightning address
Prelude
It has been previously established that the Bitcoin daily USD exchange rate series is extremely auto-correlated
In this article, we will utilise this fact to build a model for Bitcoin/USD exchange rate. But not a model for predicting the exchange rate, but rather a model to understand the fundamental reasons for the Bitcoin to have this exchange rate to begin with.
This is a model of sound money, scarcity and subjective value.
Introduction
Bitcoin, a decentralised peer to peer digital value exchange network, has experienced significant exchange rate fluctuations since its inception in 2009. In this article, we explore a two-step model that reasonably accurately captures both the fundamental drivers of Bitcoin’s value and the cyclical patterns of bull and bear markets. This model, whilst it can produce forecasts, is meant more of a way of understanding past exchange rate changes and understanding the fundamental values driving the ever increasing exchange rate. The forecasts from the model are to be considered inconclusive and speculative only.
Data preparation
To develop the BAERM, we used historical Bitcoin data from Coin Metrics, a leading provider of Bitcoin market data. The dataset includes daily USD exchange rates, block counts, and other relevant information. We pre-processed the data by performing the following steps:
Fixing date formats and setting the dataset’s time index
Generating cumulative sums for blocks and halving periods
Calculating daily rewards and total supply
Computing the log-transformed price
Step 1: Building the Base Model
To build the base model, we analysed data from the first two epochs (time periods between Bitcoin mining reward halvings) and regressed the logarithm of Bitcoin’s exchange rate on the mining reward and epoch. This base model captures the fundamental relationship between Bitcoin’s exchange rate, mining reward, and halving epoch.
where Yt represents the exchange rate at day t, Epochk is the kth epoch (for that t), and epsilont is the error term. The coefficients beta0, beta1, and beta2 are estimated using ordinary least squares regression.
Base Model Regression
We use ordinary least squares regression to estimate the coefficients for the betas in figure 2. In order to reduce the possibility of over-fitting and ensure there is sufficient out of sample for testing accuracy, the base model is only trained on the first two epochs. You will notice in the code we calculate the beta2 variable prior and call it “phaseplus”.
The code below shows the regression for the base model coefficients:
\# Run the regression
mask = df\ < 2 # we only want to use Epoch's 0 and 1 to estimate the coefficients for the base model
reg\_X = df.loc\ [mask, \ \].shift(1).iloc\
reg\_y = df.loc\ .iloc\
reg\_X = sm.add\_constant(reg\_X)
ols = sm.OLS(reg\_y, reg\_X).fit()
coefs = ols.params.values
print(coefs)
The result of this regression gives us the coefficients for the betas of the base model:
\
or in more human readable form: 0.029, 0.996869586, -0.00043. NB that for the auto-correlation/momentum beta, we did NOT round the significant figures at all. Since the momentum is so important in this model, we must use all available significant figures.
Fundamental Insights from the Base Model
Momentum effect: The term 0.997 Y suggests that the exchange rate of Bitcoin on a given day (Yi) is heavily influenced by the exchange rate on the previous day. This indicates a momentum effect, where the price of Bitcoin tends to follow its recent trend.
Momentum effect is a phenomenon observed in various financial markets, including stocks and other commodities. It implies that an asset’s price is more likely to continue moving in its current direction, either upwards or downwards, over the short term.
The momentum effect can be driven by several factors:
Behavioural biases: Investors may exhibit herding behaviour or be subject to cognitive biases such as confirmation bias, which could lead them to buy or sell assets based on recent trends, reinforcing the momentum.
Positive feedback loops: As more investors notice a trend and act on it, the trend may gain even more traction, leading to a self-reinforcing positive feedback loop. This can cause prices to continue moving in the same direction, further amplifying the momentum effect.
Technical analysis: Many traders use technical analysis to make investment decisions, which often involves studying historical exchange rate trends and chart patterns to predict future exchange rate movements. When a large number of traders follow similar strategies, their collective actions can create and reinforce exchange rate momentum.
Impact of halving events: In the Bitcoin network, new bitcoins are created as a reward to miners for validating transactions and adding new blocks to the blockchain. This reward is called the block reward, and it is halved approximately every four years, or every 210,000 blocks. This event is known as a halving.
The primary purpose of halving events is to control the supply of new bitcoins entering the market, ultimately leading to a capped supply of 21 million bitcoins. As the block reward decreases, the rate at which new bitcoins are created slows down, and this can have significant implications for the price of Bitcoin.
The term -0.0004*(50/(2^epochk) — (epochk+1)²) accounts for the impact of the halving events on the Bitcoin exchange rate. The model seems to suggest that the exchange rate of Bitcoin is influenced by a function of the number of halving events that have occurred.
Exponential decay and the decreasing impact of the halvings: The first part of this term, 50/(2^epochk), indicates that the impact of each subsequent halving event decays exponentially, implying that the influence of halving events on the Bitcoin exchange rate diminishes over time. This might be due to the decreasing marginal effect of each halving event on the overall Bitcoin supply as the block reward gets smaller and smaller.
This is antithetical to the wrong and popular stock to flow model, which suggests the opposite. Given the accuracy of the BAERM, this is yet another reason to question the S2F model, from a fundamental perspective.
The second part of the term, (epochk+1)², introduces a non-linear relationship between the halving events and the exchange rate. This non-linear aspect could reflect that the impact of halving events is not constant over time and may be influenced by various factors such as market dynamics, speculation, and changing market conditions.
The combination of these two terms is expressed by the graph of the model line (see figure 3), where it can be seen the step from each halving is decaying, and the step up from each halving event is given by a parabolic curve.
NB - The base model has been trained on the first two halving epochs and then seeded (i.e. the first lag point) with the oldest data available.
Constant term: The constant term 0.03 in the equation represents an inherent baseline level of growth in the Bitcoin exchange rate.
In any linear or linear-like model, the constant term, also known as the intercept or bias, represents the value of the dependent variable (in this case, the log-scaled Bitcoin USD exchange rate) when all the independent variables are set to zero.
The constant term indicates that even without considering the effects of the previous day’s exchange rate or halving events, there is a baseline growth in the exchange rate of Bitcoin. This baseline growth could be due to factors such as the network’s overall growth or increasing adoption, or changes in the market structure (more exchanges, changes to the regulatory environment, improved liquidity, more fiat on-ramps etc).
Base Model Regression Diagnostics
Below is a summary of the model generated by the OLS function
OLS Regression Results
\==============================================================================
Dep. Variable: logprice R-squared: 0.999
Model: OLS Adj. R-squared: 0.999
Method: Least Squares F-statistic: 2.041e+06
Date: Fri, 28 Apr 2023 Prob (F-statistic): 0.00
Time: 11:06:58 Log-Likelihood: 3001.6
No. Observations: 2182 AIC: -5997.
Df Residuals: 2179 BIC: -5980.
Df Model: 2
Covariance Type: nonrobust
\==============================================================================
coef std err t P>|t| \
\------------------------------------------------------------------------------
const 0.0292 0.009 3.081 0.002 0.011 0.048
logprice 0.9969 0.001 1012.724 0.000 0.995 0.999
phaseplus -0.0004 0.000 -2.239 0.025 -0.001 -5.3e-05
\==============================================================================
Omnibus: 674.771 Durbin-Watson: 1.901
Prob(Omnibus): 0.000 Jarque-Bera (JB): 24937.353
Skew: -0.765 Prob(JB): 0.00
Kurtosis: 19.491 Cond. No. 255.
\==============================================================================
Below we see some regression diagnostics along with the regression itself.
Diagnostics: We can see that the residuals are looking a little skewed and there is some heteroskedasticity within the residuals. The coefficient of determination, or r2 is very high, but that is to be expected given the momentum term. A better r2 is manually calculated by the sum square of the difference of the model to the untrained data. This can be achieved by the following code:
\# Calculate the out-of-sample R-squared
oos\_mask = df\ >= 2
oos\_actual = df.loc\
oos\_predicted = df.loc\
residuals\_oos = oos\_actual - oos\_predicted
SSR = np.sum(residuals\_oos \*\* 2)
SST = np.sum((oos\_actual - oos\_actual.mean()) \*\* 2)
R2\_oos = 1 - SSR/SST
print("Out-of-sample R-squared:", R2\_oos)
The result is: 0.84, which indicates a very close fit to the out of sample data for the base model, which goes some way to proving our fundamental assumption around subjective value and sound money to be accurate.
Step 2: Adding the Damping Function
Next, we incorporated a damping function to capture the cyclical nature of bull and bear markets. The optimal parameters for the damping function were determined by regressing on the residuals from the base model. The damping function enhances the model’s ability to identify and predict bull and bear cycles in the Bitcoin market. The addition of the damping function to the base model is expressed as the full model equation.
This brings me to the question — why? Why add the damping function to the base model, which is arguably already performing extremely well out of sample and providing valuable insights into the exchange rate movements of Bitcoin.
Fundamental reasoning behind the addition of a damping function:
Subjective Theory of Value: The cyclical component of the damping function, represented by the cosine function, can be thought of as capturing the periodic fluctuations in market sentiment. These fluctuations may arise from various factors, such as changes in investor risk appetite, macroeconomic conditions, or technological advancements. Mathematically, the cyclical component represents the frequency of these fluctuations, while the phase shift (α and β) allows for adjustments in the alignment of these cycles with historical data. This flexibility enables the damping function to account for the heterogeneity in market participants’ preferences and expectations, which is a key aspect of the subjective theory of value.
Time Preference and Market Cycles: The exponential decay component of the damping function, represented by the term e^(-0.0004t), can be linked to the concept of time preference and its impact on market dynamics. In financial markets, the discounting of future cash flows is a common practice, reflecting the time value of money and the inherent uncertainty of future events. The exponential decay in the damping function serves a similar purpose, diminishing the influence of past market cycles as time progresses. This decay term introduces a time-dependent weight to the cyclical component, capturing the dynamic nature of the Bitcoin market and the changing relevance of past events.
Interactions between Cyclical and Exponential Decay Components: The interplay between the cyclical and exponential decay components in the damping function captures the complex dynamics of the Bitcoin market. The damping function effectively models the attenuation of past cycles while also accounting for their periodic nature. This allows the model to adapt to changing market conditions and to provide accurate predictions even in the face of significant volatility or structural shifts.
Now we have the fundamental reasoning for the addition of the function, we can explore the actual implementation and look to other analogies for guidance —
Financial and physical analogies to the damping function:
Mathematical Aspects: The exponential decay component, e^(-0.0004t), attenuates the amplitude of the cyclical component over time. This attenuation factor is crucial in modelling the diminishing influence of past market cycles. The cyclical component, represented by the cosine function, accounts for the periodic nature of market cycles, with α determining the frequency of these cycles and β representing the phase shift. The constant term (+3) ensures that the function remains positive, which is important for practical applications, as the damping function is added to the rest of the model to obtain the final predictions.
Analogies to Existing Damping Functions: The damping function in the BAERM is similar to damped harmonic oscillators found in physics. In a damped harmonic oscillator, an object in motion experiences a restoring force proportional to its displacement from equilibrium and a damping force proportional to its velocity. The equation of motion for a damped harmonic oscillator is:
x’’(t) + 2γx’(t) + ω₀²x(t) = 0
where x(t) is the displacement, ω₀ is the natural frequency, and γ is the damping coefficient. The damping function in the BAERM shares similarities with the solution to this equation, which is typically a product of an exponential decay term and a sinusoidal term. The exponential decay term in the BAERM captures the attenuation of past market cycles, while the cosine term represents the periodic nature of these cycles.
Comparisons with Financial Models: In finance, damped oscillatory models have been applied to model interest rates, stock prices, and exchange rates. The famous Black-Scholes option pricing model, for instance, assumes that stock prices follow a geometric Brownian motion, which can exhibit oscillatory behavior under certain conditions. In fixed income markets, the Cox-Ingersoll-Ross (CIR) model for interest rates also incorporates mean reversion and stochastic volatility, leading to damped oscillatory dynamics.
By drawing on these analogies, we can better understand the technical aspects of the damping function in the BAERM and appreciate its effectiveness in modelling the complex dynamics of the Bitcoin market. The damping function captures both the periodic nature of market cycles and the attenuation of past events’ influence.
Conclusion
In this article, we explored the Bitcoin Auto-correlation Exchange Rate Model (BAERM), a novel 2-step linear regression model for understanding the Bitcoin USD exchange rate. We discussed the model’s components, their interpretations, and the fundamental insights they provide about Bitcoin exchange rate dynamics.
The BAERM’s ability to capture the fundamental properties of Bitcoin is particularly interesting. The framework underlying the model emphasises the importance of individuals’ subjective valuations and preferences in determining prices. The momentum term, which accounts for auto-correlation, is a testament to this idea, as it shows that historical price trends influence market participants’ expectations and valuations. This observation is consistent with the notion that the price of Bitcoin is determined by individuals’ preferences based on past information.
Furthermore, the BAERM incorporates the impact of Bitcoin’s supply dynamics on its price through the halving epoch terms. By acknowledging the significance of supply-side factors, the model reflects the principles of sound money. A limited supply of money, such as that of Bitcoin, maintains its value and purchasing power over time. The halving events, which reduce the block reward, play a crucial role in making Bitcoin increasingly scarce, thus reinforcing its attractiveness as a store of value and a medium of exchange.
The constant term in the model serves as the baseline for the model’s predictions and can be interpreted as an inherent value attributed to Bitcoin. This value emphasizes the significance of the underlying technology, network effects, and Bitcoin’s role as a medium of exchange, store of value, and unit of account. These aspects are all essential for a sound form of money, and the model’s ability to account for them further showcases its strength in capturing the fundamental properties of Bitcoin.
The BAERM offers a potential robust and well-founded methodology for understanding the Bitcoin USD exchange rate, taking into account the key factors that drive it from both supply and demand perspectives.
In conclusion, the Bitcoin Auto-correlation Exchange Rate Model provides a comprehensive fundamentally grounded and hopefully useful framework for understanding the Bitcoin USD exchange rate.
Multi VWAP from Gaps [MW]Multi VWAP from Gaps
Introduction
The Multi VWAP from Gaps tool extends the concept of using the Anchored Volume Weighted Average Price, popularized by its founder, Brian Shannon, founder of AlphaTrends. It creates automatic AVWAPS for anchor points originating at the biggest gaps of the week, month, quarter and year. Currently, most standard VWAP tools allow users to place custom anchored VWAPs, but the routine of doing this for every equity being watched can become cumbersome. This tool makes that process multi-times easier. Considering that large gaps can represent a shift in market structure, this tool provides unique and immediate insight into how past daily price gaps can and have affected price action.
Settings
LABEL SETTINGS
Show Biggest Gap of Week | Month | Quarter : Toggle labels that identify the location of the biggest gaps for the selected time period.
Show Big Labels : Toggle labels from showing the date and gap size to just showing a single letter (W/M/Q/Y) designating the time period that the gap is from.
Hide All Labels : Turn labels off and on.
MAX VWAP LINES
Max Weekly | Monthly | Quarterly | Yearly Lines : How many VWAP lines, starting from today, should be shown for the specified time period. Max: 5
SHOW VWAP LINES
Show Weekly | Monthly | Quarterly | Yearly Lines : This feature allows you to remove lines for the specified time period.
Calculations
This indicator does not provide buy or sell signals. It is simply the VWAP calculated starting from an “anchor point”, or start time. It is calculated by the summation of Price x Volume / Volume for the period starting at the anchor point.
How to Interpret
According to Brian Shannon, VWAP is an objective measure of what the average trader has paid for a particular equity over a given period, and is the value that large institutional investors frequently use as a trade signal. Therefore, by definition, when the price is above an AVWAP, buyers are in control for that period of time. Likewise, if the price is below the AVWAP, sellers are in control for that period of time.
VWAPs that coincide with important events, such as FOMC meetings, CPI reports, earnings reports, have added significance. In many cases, these events can cause gaps to happen in day-to-day price movement, and can affect market structure going forward.
Practically speaking, price action can tend to change direction when a significant VWAP is hit, voiding buy and sell signals. Like moving averages, this indicator can show, in real-time, how a buy or sell signal should be interpreted. A significant AVWAP line is a point of interest, and can serve as strong support or resistance, because large institutions may be using those values for entries or exits. For a great analysis of how to use AVWAP, visit the AlphaTrends channel on Youtube here or you can buy Brian Shannon’s “Anchored VWAP” book on Amazon.
Other Usage Notes and Limitations
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Additionally, in order to build the VWAP calculations, past data is needed that may not be available on shorter timeframes. The workaround is that for some longer-term VWAP lines on shorter timeframes, you may see less than the total of lines that you selected in settings. This is particularly the case with quarterly VWAP lines on the 5 minute timeframe for some equities.
Acknowledgements
This script uses the MarketHolidays library by @Protervus. Also, for debugging, the JavaScript-style Debug Console by @algotraderdev was invaluable. Special thanks to @antsmuzic for helping review and debug the script. And, of course, without Brian Shannon's books, videos, and interviews, this indicator would would not have happened.
Order Blocks Finder [TradingFinder] Major OB | Supply and Demand🔵 Introduction
Drawing all order blocks on the path, especially in range-bound or channeling markets, fills the chart with lines, making it confusing rather than providing the trader with the best entry and exit points.
🔵 Reason for Indicator Creation
For traders familiar with market structure and only need to know the main accumulation points (best entry or exit points), and primary order blocks that act as strong sources of power.
🟣 Important Note
All order blocks, both ascending and descending, are identified and displayed on the chart when the structure of "BOS" or "CHOCH" is broken, which can also be identified with "MSS."
🔵 How to Use
When the indicator is installed, it plots all order blocks (active order blocks) and continues until the price reaches them. This continuation happens in boxes to have a better view in the TradingView chart.
Green Range : Ascending order blocks where we expect a price increase in these areas.
Red Range : Descending order blocks where we expect a price decrease in these areas.
🔵 Settings
Order block refine setting : When Order block refine is off, the supply and demand zones are the entire length of the order block (Low to High) in their standard state and cannot be improved. If you turn on Order block refine, supply and demand zones will improve using the error correction algorithm.
Refine type setting : Improving order blocks using the error correction algorithm can be done in two ways: Defensive and Aggressive. In the Aggressive method, the largest possible range is considered for order blocks.
🟣 Important
The main advantage of the Aggressive method is minimizing the loss of stops, but due to the widening of the supply or demand zone, the reward-to-risk ratio decreases significantly. The Aggressive method is suitable for individuals who take high-risk trades.
In the Defensive method, the range of order blocks is minimized to their standard state. In this case, fewer stops are triggered, and the reward-to-risk ratio is maximized in its optimal state. It is recommended for individuals who trade with low risk.
Show high level setting : If you want to display major high levels, set show high level to Yes.
Show low level setting : If you want to display major low levels, set show low level to Yes.
🔵 How to Use
The general view of this indicator is as follows.
When the price approaches the range, wait for the price reaction to confirm it, such as a pin bar or divergence.
If the price passes with a strong candle (spike), especially after a long-range or at the beginning of sessions, a powerful event is happening, and it is outside the credibility level.
An Example of a Valid Zone
An Example of Breakout and Invalid Zone. (My suggestion is not to use pending orders, especially when the market is highly volatile or before and after news.)
After reaching this zone, expect the price to move by at least the minimum candle that confirmed it or a price ceiling or floor.
🟣 Important : These factors can be more accurately measured with other trend finder indicators provided.
🔵 Auxiliary Tools
There is much talk about not using trend lines, candlesticks, Fibonacci, etc., in the web space. However, our suggestion is to create and use tools that can help you profit from this market.
• Fibonacci Retracement
• Trading Sessions
• Candlesticks
🔵 Advantages
• Plotting main OBs without additional lines;
• Suitable for timeframes M1, M5, M15, H1, and H4;
• Effective in Tokyo, Sydney, and London sessions;
• Plotting the main ceiling and floor to help identify the trend.
Implied Orderblock Breaker (Zeiierman)█ Overview
The Implied Order Block Breaker (Zeiierman) is a tool designed to identify enhanced order blocks with imbalances. These enhanced order blocks represent areas where there is a rapid price movement. Essentially, this indicator uses order blocks and suggests that a swift price movement away from these levels, breaking the current market structure, could indicate an area that the market has not correctly valued. This technique offers traders a unique method to identify potential market inefficiencies and imbalances, serving as a guide for potential price revisits.
The indicator doesn't scan for imbalances in the traditional sense — where there's an absence of trades between two price levels — but instead, it identifies quick movements away from key levels that suggest where an imbalance might exist. Relying on crossovers and cross-unders in conjunction with pivot points and examining the high/low within the same period provides an innovative method for traders to spot these potentially undervalued or overvalued areas in the market. These inferred imbalances can be crucial for traders looking for price levels where the market might make significant moves.
█ How It Works
Bullish
Crossover: The closing price of a bar crosses above a pivot high, which is an indication that buyers are in control and pushing the price upwards.
New Low Within Period: There is a lower low within the same period as the pivot high. This suggests that after setting a high, the market pulled back to set a new low, potentially leaving a price gap on the way up as the price quickly recovers.
Bearish
Crossunder: The closing price of a bar crosses under a pivot low, indicating that sellers are taking control and driving the price down.
New High Within Period: There is a higher high within the same period as the pivot low. This condition suggests that the market rallied to a new high before falling back below the pivot low, potentially leaving a gap on the way down.
█ How to Use
The enhanced order blocks are often revisited, and the price may aim to 'fill' the potential imbalance created by the rapid price movement, thereby presenting traders with potential entry or exit points. This approach aligns with the idea that imbalances are frequently revisited by the market, and when combined with the context of Order Blocks, it provides even more confluence.
Example
Here, if the price drops rapidly after setting a new high—crossing under the pivot low—it may skip over certain price levels, creating a 'gap' that signifies an area where the price might have been overvalued (imbalance), which the market may revisit for a potential price correction or revaluation.
█ Settings
Period: Determines the number of bars used for identifying pivot highs and lows. A higher value gives more significant but less frequent signals, while a lower value increases sensitivity but might give more false positives.
Pivot Surrounding: Specifies the number of candles to analyze around a pivot point. Increasing this value broadens the analysis range, potentially capturing more setups but possibly including less significant ones.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Candlestick Patterns [NAS Algo]Candlestick Patterns plots most commonly used chart patterns to help and understand the market structure.
Bullish Reversal Patterns:
Hammer:
Appearance: Small body near the high, long lower shadow.
Interpretation: Indicates potential bullish reversal after a downtrend.
Inverted Hammer:
Appearance: Small body near the low, long upper shadow.
Interpretation: Signals potential bullish reversal, especially when the preceding trend is bearish.
Three White Soldiers:
Appearance: Three consecutive long bullish candles with higher closes.
Interpretation: Suggests a strong reversal of a downtrend.
Bullish Harami:
Appearance: Small candle (body) within the range of the previous large bearish candle.
Interpretation: Implies potential bullish reversal.
Bearish Reversal Patterns:
Hanging Man:
Appearance: Small body near the high, long lower shadow.
Interpretation: Suggests potential bearish reversal after an uptrend.
Shooting Star:
Appearance: Small body near the low, long upper shadow.
Interpretation: Indicates potential bearish reversal, especially after an uptrend.
Three Black Crows:
Appearance: Three consecutive long bearish candles with lower closes.
Interpretation: Signals a strong reversal of an uptrend.
Bearish Harami:
Appearance: Small candle (body) within the range of the previous large bullish candle.
Interpretation: Implies potential bearish reversal.
Dark Cloud Cover:
Appearance: Bearish reversal pattern where a bullish candle is followed by a bearish candle that opens above the high of the previous candle and closes below its midpoint.
Continuation Patterns:
Rising Three Methods:
Appearance: Consists of a long bullish candle followed by three small bearish candles and another bullish candle.
Interpretation: Indicates the continuation of an uptrend.
Falling Three Methods:
Appearance: Consists of a long bearish candle followed by three small bullish candles and another bearish candle.
Interpretation: Suggests the continuation of a downtrend.
Gravestone Doji:
Appearance: Doji candle with a long upper shadow, little or no lower shadow, and an opening/closing price near the low.
Interpretation: Signals potential reversal, particularly in an uptrend.
Long-Legged Doji:
Appearance: Doji with long upper and lower shadows and a small real body.
Interpretation: Indicates indecision in the market and potential reversal.
Dragonfly Doji:
Appearance: Doji with a long lower shadow and little or no upper shadow.
Interpretation: Suggests potential reversal, especially in a downtrend.
Opening Range Gap + Std Dev [starclique]The ICT Opening Range Gap is a concept taught by Inner Circle Trader and is discussed in the videos: 'One Trading Setup For Life' and 2023 ICT Mentorship - Opening Range Gap Repricing Macro
ORGs, or Opening Range Gaps, are gaps that form only on the Regular Trading Hours chart.
The Regular Trading Hours gap occurs between 16:15 PM - 9:29 AM EST (UTC-4)
These times are considered overnight trading, so it is useful to filter the PA (price action) formed there.
The RTH option is only available for futures contracts and continuous futures from CME Group.
To change your chart to RTH, first things first, make sure you’re looking at a futures contract for an asset class, then on the bottom right of your chart, you’ll see ETH (by default) - Click on that, and change it to RTH.
Now your charts are filtering the price action that happened overnight.
To draw out your gap, use the Close of the 4:14 PM candle and the open of the 9:30 AM candle.
How is this concept useful?
Well, It can be used in many ways.
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How To Use The ORG
One of the ways you can use the opening range gap is simply as support and resistance
If we extend out the ORG from the example above, we can see that there is a clean retest of the opening range gap high after breaking structure to the upside and showing acceptance outside of the gap after consolidating within it.
The ORG High (4:14 Candle Close in this case) was used as support.
We then see an expansion to the upside.
Another way to implement the ORG is by using it as a draw on liquidity (magnet for price)
In this example, if we looked to the left, there was a huge ORG to the downside, leaving a massive gap.
The market will want to rebalance that gap during the regular trading hours.
The market rallies higher, rejects, comes down to clear the current days ORG low, then closes.
That is one example of how you can combine liquidity & ICT market structure concepts with Opening Range Gaps to create a story in the charts.
Now let’s discuss standard deviations.
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Standard Deviations
Standard Deviations are essentially projection levels for ranges / POIs (Point of Interests)
By this I mean, if you have a range, and you would like to see where it could potentially expand to, you’d place your fibonacci retracement tool on and high and low of the range, then use extension levels to find specific price points where price might reject from.
Since 0 and 1 are your Range High and Low respectively, your projection levels would be something like 1.5, 2, 2.5, and 3, for the extension from your 1 Fib Level, and -0.5, -1, -1.5, and -2 for your 0 Fib level.
The -1 and 2 level produce a 1:1 projection of your range low and high, meaning, if you expect price to expand as much as it did from the range low to range high, then you can project a -1 and 2 on your Fib, and it would show you what ICT calls “symmetrical price”
Now, how are standard deviations relevant here?
Well, if you’ve been paying attention to ICT’s recent videos, you would’ve caught that he’s recently started using Standard Deviation levels on breakers.
So my brain got going while watching his video on ORGs, and I decided to place the fib on the ORG high and low and see what it’d produce.
The results were very interesting.
Using this same example, if we place our fib on the ORG High and Low, and add some projection levels, we can see that we rejected right at the -2 Standard Deviation Level.
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You can see that I also marked out the EQ (Equilibrium, 50%, 0.5 of Fib) of the ORG. This is because we can use this level as a take profit level if we’re using an old ORG as our draw.
In days like these, where the gap formed was within a consolidation, and it continued to consolidate within the ORG zone that we extended, we can use the EQ in the same way we’d use an EQ for a range.
If it’s showing acceptance above the EQ, we are bullish, and expect the high of the ORG to be tapped, and vice versa.
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Using The Indicator
Here’s where our indicator comes in play.
To avoid having to do all this work of zooming in and marking out the close and open of the respective ORG candles, we created the Opening Range Gap + Standard Deviations Indicator, with the help of our dedicated Star Clique coder, a1tmaniac.
With the ORG + STD DEV indicator, you will be able to view ORG’s and their projections on the ETH (Electronic Trading Hours) chart.
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Features
Range Box
- Change the color of your Opening Range Gap to your liking
- Enable or disable the box from appearing using the checkbox
Range Midline
- Change the color of your Opening Range Gap Equilibrium
- Enable or disable the midline from appearing using the checkbox
Std. Dev
- Add whichever standard deviation levels you’d like.
- By default, the indicator comes with 0.5, 1, 1.5, and 2 standard deviation levels.
- Ensure that you add a comma ( , ) in between each standard deviation level
- Enable or disable the standard deviations from appearing using the opacity of the color (change to 0%)
Labels / Offset
- Adjust the offset of the label for the Standard Deviations
- Enable or disable the Labels from appearing using the checkbox
Time
- Adjust the time used for the indicators range
- If you’d like to use this for a Session or ICT Killzone instead, adjust the time
- Adjust the timezone used for the time referenced
- Options are UTC, US (UTC-4, New York Local Time) or UK (UTC+1, London Time)
- By default, the indicator is set to US
Faytterro Market Structerethis indicator creates the market structure with a little delay but perfectly. each zigzag is always drawn from highest to lowest. It also signals when the market structure is broken. signals fade over time.
The table above shows the percentage distance of the price from the last high and the last low.
zigzags are painted green when making higher peaks, while lower peaks are considered downtrends and are painted red. In fact, the indicator is quite simple to understand and use.
"length" is used to change the frequency of the signal.
"go to past" is used to see historical data.
Please review the examples:
CANDLE FILTER Todays scripts is based on my Pullback And Rally Candles with other meaningful candles such as Hammers and Dojis.
You can choose which Candles to show on the cart and if you want to candles to appear above or below a moving average.
If you follow my work, you may recognise some of these candles which I'm about to show you however these candles are 1) more refined and 2) has moving average filters.
Ive included a D,6H,1H Candle in this script as on different timeframes - each swing low on average has a different amount of bars within the swing low / swing high so the DPB and RD will only work on the Daily
//Pullback candle
This candle is very powerful when used with simple Price Action such as Market Structure//Demand zones and support zones. (((((WORKS BEST IN UPTRENDS AND BOTTOM OF RANGES)))))
Ive included a D,6H,1H Pullback Candle in this script as on different timeframes - each swing low on average has a different amount of bars within the swing low so the DPB will only work on the Daily
//DAILY PULLBACK (Swing Traders)
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//4H PULLBACK (Swing Traders)
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- this signal will produce more signals due to the swing low filter on the 4H
//1H PULLBACK
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- this signal has been refined due to too many candle displaying in weak areas
!!!IF YOU DONT WANT TO USE PULLBACKS DURING DOWNTRENDS THEN USE THE EMA FILTER TO TURN OFF THE PULLBACKS WHEN PRICE IS BELOW THE MOVING AVERAGE!!!
//Rally candle (My personal Favourite) (((((WORKS BEST IN DOWNTRENDS AND TOP OF RANGES)))))
This candle is very powerful when used with simple Price Action such as Market Structure//Supply zones and Resistance zones.
//DAILY RALLY(Swing Traders)
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//4H RALLY(Swing Traders)
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- this signal will produce more signals due to the swing high filter on the 4H
!!!IF YOU DONT WANT TO USE RALLIES DURING UPTRENDSTHEN USE THE EMA FILTER TO TURN OFF THE RALLIES WHEN PRICE IS ABOVE THE MOVING AVERAGE!!!
//POWERFUL DOJIS (INDECISION)
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We look for indecision in key areas to see if momentum is shifting. When combined with Pullbacks or Rallys - this will enhance the odds of a probably area.
//HAMMERS
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//MOVING AVERAGES
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Short EMA = 50
Long EMA = 200
This filter can be used when the market is trending - look out for rejections off the moving averages
Also you can chance the Short And Long EMA to choose which MA cross you want to use
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ALSO ALL THE CANDLES HAVE A ALERT CONDITIONS WHICH YOU CAN ACCESS - THIS WILL ALERT ANY CANDLE YOU CHOOSE
Please leave a like/comment on this post as this is much appreciated....
Order BlocksThis is experimental Indicator is to help identifying Order Blocks.
It uses not confirmed higher order pivots as Higher Highs (HH) and Lower Lows (LL), finds high/lows that created most recent LL/HH and in case if this high/low are broken it notes candle that broke structure, market structure broke line (MSB) and demand box (candle that created liquidity for the move that broke structure).
Concepts and parts of code used in this study:
1) @rumpypumpydumpy - Higher Order Pivots
2) @MarkMiddleton2020 - Order Blocks
Higher Order PivotsFirst order pivot points are defined as 3 or 5 bar "V" shaped patterns. For example a high with a lower high either side of the peak and in the case of the 5 bar variant with lower highs adjacent to a high below the peak.
Second order pivot points are defined by three first order pivots in the same manner. For example a peak pivot high with a lower pivot high to either side.
Third order pivots follow the same pattern, a peak second order pivot high with two adjacent second order pivot highs.
As it can take a significant and variable amount of time before higher order pivots are confirmed, it is generally inadvisable to use higher order pivots for live trading!
However they can be used for historical analysis. For example to delineate market structure of major market inflections.
For example :
Delineating market structure using 2nd order pivots derived from 3 bar, 1st order pivots
Major market inflections from 3rd order pivots derived from 5 bar, 1st order pivots
+ BB %B: MA selection, bar coloring, multi-timeframe, and alerts+ %B is, at its simplest, the classic Bollinger Bands %B indicator with a few added bells and whistles.
However, the right combination of bells and whistles will often improve and make a more adaptable indicator.
Classically, Bollinger Bands %B is an indicator that measures volatility, and the momentum and strength of a trend, and/or price movements.
It shows "overbought" and "oversold" spots on a chart, and is also useful for identifying divergences between price and trend (similar to RSI).
With + %B I've added the options to select one or two moving averages, candle coloring, and a host of others.
Let's start with the moving averages:
There are options for two: one faster and one slower. Or combine them how you will, or omit one or both of them entirely.
Here you will find options for SMA, EMA (as well as double and triple), Hull MA, Jurik MA, Least Squares MA, Triangular MA, Volatility Adjusted MA, and Weighted MA.
A moving average essentially helps to define trend by smoothing the noise of movements of the underlying asset, or, in this case, the output of the indicator.
All of these MAs available track this in a different way, and it's up to the trader to figure out which makes most sense to him/her.
MA's, in my opinion, improve the basic %B by providing a clearer picture of what the indicator is actually "seeing", and may be useful for providing entries and exits.
Next up is candle coloring:
I've added the option for this indicator to color candles on the chart based on where the %B is in relation to its upper and lower bounds, and median line.
If the %B is above the median but below the upper bound, candles will be green (showing bullish market structure). If %B is below the median but above the lower bound, candles will be red (denoting bearish market structure).
Overbought and oversold candles will also be colored on the chart, so that a quick glance will tell you whether price action is bullish/bearish or "oversold"/"overbought".
I've also added functionality that enables candles to be colored based on if the %B has crossed up or crossed down the primary moving average.
One example as a way to potentially use these features is if the candles are showing oversold coloration followed by the %B crossing up your moving average coloration. You might consider a long there (or exit a short position if you are short).
And the last couple of tweaks:
You may set the timeframe to whatever you wish, so maybe you're trading on the hourly, but you want to know where the %B is on the 4h chart. You can do that.
The background fill for the indicator is split into bullish and bearish halves. Obviously you may turn the background off, or make it all one color as well.
I've also added alerts, so you may set alerts for "overbought" and "oversold" conditions.
You may also set alerts for %B crossing over or under the primary moving average, or for crossing the median line.
All of these things may be turned on and off. You can pretty much customize this to your heart's delight. I see no reason why anyone would use the standard %B after playing with this.
I am no coder. I had this idea in my head, though, and I made it happen through referencing another indicator I was familiar with, and watching tutorials on YouTube.
Credits:
Firstly, thanks to www.tradingview.com for his brilliant, free tutorials on YouTube.
Secondly, thanks to www.tradingview.com for his beautiful SSL Hybrid indicator (and his clean code) from which I obtained the MAs.
Please enjoy this indicator, and I hope that it serves you well. :)
MA, MATR, ChEx | All in One - 4CR CUPIn trade position setup, we always need to determine the market structure and manage the position sizing in a short period of decision time. Indicators such as moving average, initial stop loss and trailing stop loss are always helpful.
This indicator put all these handy tools into a single toolkit, which includes the following price action and risk management indicators:
MA - Moving Average
MATR - Moving Average less Average True Range
ChEx - Chandelier Exit
This script further enhances the setting so that you can easily customize the indicators.
For both the Moving Averages and the Moving Average less Average True Range , you can pick a type of moving average which suits your analysis style from a list of commonly used moving average formulations: namely, EMA , HMA , RMA, SMA and WMA , where EMA is selected as default.
The Moving Average less Average True Range , MATR, is usually applied as a reference to set the initial stop loss whenever opening a new position.
The abbreviation, MATR, is picked, so that this can serve as a handy reminder of a very good trading framework as elaborates as below:
M – Market Structure
A – Area of Value
T – Trigger
R – Risk Management (aka. Exit Strategy)
Ichimoku Kinko Hyo and moreI am publishing my updated Ichimoku ++ study with a more suitable title. Future updates will take place with this version.
Description:
The intention of this script is to build/provide a kind of work station / work bench for analysing markets and especially Bitcoin . Another goal is to get maximum market information while maintaining a good chart overview. A chart overloaded with indicators is useless because the structure of the chart is more difficult to see. The chart should be clear and market structure should be easy to see. The script allows you to add indicators and signals in different visualizations to better assess the quality of signals and the sentiment of the market.
A general advise:
Use the included indicators and signals in a confluent way to get stoploss, buy and sell entry points. SR clusters can be identified for use in conjunction with Fractals and other indicators as entry and exit pints. My other scripts can also help. Prefer 4 hours, daily and a longer time frame. There is no "Holy Grail" :).
Validated Order Blocks with Fib LevelsThis indicator automatically identifies and displays Smart Money Concepts (SMC) order blocks based on market structure breaks:
How it works:
Bearish Order Blocks (Red): Marks the last bullish candle before a swing high. The OB becomes valid when price breaks below the previous swing low, indicating institutional selling zones. Drawn from the candle's close (body top) to its low (bottom wick).
Bullish Order Blocks (Green): Marks the last bearish candle before a swing low. The OB becomes valid when price breaks above the previous swing high, indicating institutional buying zones. Drawn from the candle's high (top wick) to its close (body bottom).
Features:
Three Fibonacci retracement levels (50%, 75%, 100%) for each order block
Fib 100% faces downward on bearish OBs and upward on bullish OBs
Auto-validation: OBs are removed when price closes through them
Customizable: Adjustable swing detection, timeframe selection, and OB display limits
Optional Break of Structure (BOS) markers to show when OBs activate
Works on any timeframe with HTF analysis support
Perfect for identifying key institutional support/resistance zones and potential reversal areas.
BB + Keltner Squeeze (con SL)BB + Keltner Squeeze with Dynamic SL
This indicator combines Bollinger Bands (2σ and optional 3σ) with Keltner Channels to detect phases of volatility compression (squeeze) and their release (expansion).
Squeeze ON (orange dot): Bollinger Bands are inside the Keltner Channel → low volatility / market compression.
Release (green triangle): Bollinger Bands break outside the Keltner Channel → volatility expansion.
Orange background: visually highlights squeeze phases.
Dynamic Stop Loss options:
KC Mode: stop at the opposite Keltner band (wider, good for trend following).
ATRlike Mode: stop based on a multiple of the range (tighter, good for scalping or short swings).
Intended use:
Identify moments when the market is “building energy” and trade breakouts after a release.
Adjust stop losses dynamically according to volatility.
Note: This is not a standalone trading system. It works best when combined with trend confirmation tools (EMA, MACD, market structure, etc.).
Dynamic Volume Trace Profile [ChartPrime]⯁ OVERVIEW
Dynamic Volume Trace Profile is a reimagined take on volume profile analysis. Instead of plotting a static horizontal histogram on the side of your chart, this indicator projects dynamic volume trace lines directly onto the price action. Each bin is color-graded according to its relative strength, creating a living “volume skeleton” of the market. The orange trace highlights the current Point of Control (POC)—the price level with maximum historical traded volume within the lookback window. On the right side, the tool builds a mini profile, showing absolute volume per bin alongside its percentage share, where the POC always represents 100% strength .
⯁ KEY FEATURES
Dynamic On-Chart Bins:
The range between highest high and lowest low is split into 25 bins. Each bin is drawn as a horizontal trace line across the lookback chart period.
Gradient Color Encoding:
Trace lines fade from transparent to teal depending on relative volume size. The more intense the teal, the stronger the historical traded activity at that level.
Automatic POC Highlight:
The bin with the highest aggregated volume is flagged with an orange line . This POC adapts bar-by-bar as volume distribution shifts.
Right-Side Volume Profile:
At the chart’s right edge, the script prints a box-style profile. Each bin shows:
• Total volume (absolute units).
• Percentage of max volume, in parentheses (POC bin = 100%).
This gives both raw and normalized context at a glance.
Adjustable Lookback Window:
The lookback defines how many bars feed the profile. Increase for stable HTF zones or decrease for responsive intraday distributions.
POC Toggle & Styling:
Optionally toggle POC highlighting on/off, adjust colors, and set line thickness for better integration with your chart theme.
⯁ HOW IT WORKS (UNDER THE HOOD)
Step Sizing:
over last 100 bars is divided by to calculate bin height.
Volume Aggregation:
For each bar in the , the script checks which bin the close falls into, then adds that bar’s volume to the bin’s counter.
Gradient Mapping:
Bin volume is normalized against the max volume across all bins. That value is mapped onto a gradient from transparent → teal.
POC Logic:
The bin with highest volume is colored orange both on the dynamic trace and in the right-side profile.
Right-Hand Profile:
Boxes are drawn for each bin proportional to volume / maxVolume × 50 units, with text labels showing both absolute volume and normalized %.
⯁ USAGE
Use the orange trace as the dominant “magnet” level—price often gravitates to the POC.
Watch for clusters of strong teal traces as areas of high acceptance; thin or faint zones mark low-liquidity gaps prone to fast moves.
On intraday charts, tighten lookback to reveal session-based distributions . For swing or position trading, expand lookback to surface more durable volume shelves.
Compare the right-side profile % to judge how “top-heavy” or “bottom-heavy” the current distribution is.
Use bright, intense color traces as context for confluence with structure, OBs, or liquidity hunts.
⯁ CONCLUSION
Dynamic Volume Trace Profile takes the traditional volume profile and fuses it into the body of price itself. Instead of a fixed sidebar, you see gradient traces layered directly on the chart, giving real-time context of where volume concentrated and where price may be drawn. With built-in POC highlighting, normalized % readouts, and an adaptive right-side profile, it offers both precision levels and market structure awareness in a cleaner, more intuitive form.
Scalper - Pattern Recognition & Price Action with Divergence Scalper - Pattern Recognition & Price Action with Divergence
Overview
An educational indicator designed to demonstrate comprehensive technical analysis concepts through integrated pattern recognition, price action analysis, and divergence detection. This tool combines traditional candlestick patterns with modern institutional concepts and advanced divergence analysis for educational market study.
Educational Purpose & Originality
Core Educational Concepts
This indicator serves as a learning platform for understanding:
- **Pattern Recognition Methodology**: Systematic identification of candlestick formations
- **Price Action Theory**: Modern institutional footprint analysis
- **Divergence Analysis**: Momentum divergence detection across multiple oscillators
- **Confluence Systems**: Multi-signal integration and validation techniques
Original Implementation Features
1. Enhanced Pattern Detection Library
- **Volatility-Filtered Patterns**: ATR-based validation for pattern significance
- **Volume-Confirmed Formations**: Integration of volume analysis with pattern detection
- **Multi-Candle Pattern Recognition**: Three-candle formations and complex patterns
- **Context-Aware Detection**: Patterns validated against market structure
2. Advanced Divergence System
- **Multi-Oscillator Analysis**: RSI, CCI, and MACD divergence detection
- **Four Divergence Types**: Regular bullish/bearish and hidden bullish/bearish
- **Pivot-Based Detection**: Systematic swing high/low identification
- **Weighted Signal Integration**: Divergences integrated into confluence scoring
3. Modern Price Action Concepts
- **Fair Value Gaps (FVG)**: Identification of institutional inefficiencies
- **Order Block Detection**: Volume-validated accumulation/distribution zones
- **Dynamic Support/Resistance**: Touch-count validated levels with ATR tolerance
- **Breakout Analysis**: Volume-confirmed price breakouts
4. Intelligent Confluence System
- **Multi-Signal Aggregation**: Combines patterns, oscillators, divergences, and breakouts
- **Weighted Scoring Algorithm**: Different signal types receive appropriate weighting
- **Visual Confluence Display**: Clear indication of high-probability setups
- **Reason Tracking**: Shows which signals contribute to confluence
How to Use
Initial Configuration
1. **Enable Desired Components**: Toggle individual analysis modules based on learning focus
2. **Adjust Sensitivity Settings**: Configure pattern detection parameters for your market
3. **Select Divergence Options**: Choose oscillators and divergence types to monitor
4. **Set Confluence Requirements**: Define minimum signals needed for confirmation
Component Settings
Moving Average Configuration
- Four customizable MA lines for multi-timeframe trend analysis
- Selectable MA types (SMA, EMA, WMA, VWMA, HMA)
- Independent timeframe settings for each MA
Pattern Recognition Settings
- **Engulfing Patterns**: Strong engulfing with ATR validation
- **Doji Variations**: Standard, gravestone, and dragonfly detection
- **Hammer/Hanging Man**: Context-validated reversal patterns
- **Star Formations**: Morning and evening star patterns
- **Three Soldiers/Crows**: Momentum continuation patterns
Divergence Detection Parameters
- **Lookback Period**: Adjustable swing detection range
- **Minimum Pivot Strength**: Percentage threshold for valid pivots
- **Oscillator Selection**: RSI, CCI, MACD, or combination
- **Divergence Types**: Regular and hidden divergences
Signal Interpretation
Visual Indicators
- **Pattern Labels**: Clear marking of detected formations
- **Divergence Lines**: Visual connection between price and oscillator pivots
- **Support/Resistance Levels**: Dynamic horizontal levels with validation
- **Confluence Signals**: Large "BULL" or "BEAR" labels for high-probability setups
Dashboard Information
- Real-time oscillator values (RSI, CCI, MACD)
- Current signal count for bulls and bears
- Active divergence status
- Confluence confirmation status
Important Educational Considerations
Learning Focus
- **Pattern Study**: Understand how traditional patterns form and their limitations
- **Divergence Concepts**: Learn to identify momentum shifts before price reversals
- **Confluence Theory**: Practice combining multiple analysis techniques
- **Risk Awareness**: No pattern or signal guarantees future price movement
Limitations for Learning
- **Historical Analysis**: Patterns are identified after formation
- **No Predictive Guarantee**: Educational tool for understanding concepts, not predictions
- **Market Context Required**: Patterns should be considered within broader market context
- **Practice Required**: Effective use requires study and practice
Educational Best Practices
1. **Start Simple**: Enable one component at a time to understand each concept
2. **Paper Trade**: Practice identifying signals without real money risk
3. **Study Failed Signals**: Learn why patterns fail to improve understanding
4. **Combine with Other Analysis**: Use alongside fundamental and sentiment analysis
5. **Document Observations**: Keep a journal of pattern occurrences and outcomes
Technical Components
Indicator Architecture
- **Modular Design**: Independent modules for different analysis types
- **Performance Optimization**: Efficient calculation methods for smooth operation
- **Visual Management**: Controlled use of Pine Script drawing objects
- **Array-Based Storage**: Efficient data management for historical analysis
Calculation Methods
- **ATR-Based Validation**: Volatility-adjusted pattern filtering
- **Volume Analysis**: Comparative volume assessment for confirmation
- **Pivot Detection**: Mathematical identification of swing points
- **Statistical Validation**: Touch-count and tolerance-based S/R levels
Divergence Detection Methodology
Regular Divergences (Reversal Signals)
- **Bullish**: Price lower low + Oscillator higher low
- **Bearish**: Price higher high + Oscillator lower high
Hidden Divergences (Continuation Signals)
- **Hidden Bullish**: Price higher low + Oscillator lower low
- **Hidden Bearish**: Price lower high + Oscillator higher high
Validation Criteria
- Minimum pivot strength requirement (percentage-based)
- Lookback period for swing detection
- Multiple oscillator confirmation option
Confluence Scoring System
Signal Categories
1. **Pattern Signals** (Weight: 1): Candlestick formations
2. **Oscillator Signals** (Weight: 1): RSI/CCI extremes
3. **Breakout Signals** (Weight: 1): Volume-confirmed breaks
4. **Regular Divergences** (Weight: 2): Higher probability reversals
5. **Hidden Divergences** (Weight: 1): Trend continuation signals
Confluence Thresholds
- Adjustable minimum signal requirement (2-6 signals)
- Visual indication when threshold is met
- Detailed reason display for educational understanding
Educational Dashboard
Real-Time Metrics
- Oscillator readings (RSI, CCI, MACD)
- ATR volatility measurement
- Bull/Bear signal counts
- Divergence status
- Confluence confirmation
Customization Options
- Position selection (6 screen locations)
- Color customization for all elements
- Enable/disable individual components
Version Information
- **Version 1.1**: Added comprehensive divergence detection system
- **Educational Focus**: Designed for learning technical analysis concepts
- **Integration**: All components work together in confluence system
Disclaimer
This indicator is designed exclusively for educational purposes to demonstrate technical analysis concepts. It is not financial advice and should not be used as the sole basis for trading decisions. Past patterns and signals do not guarantee future results. Trading involves substantial risk of loss. Users should conduct their own research, practice with demo accounts, and consider seeking advice from qualified professionals before making investment decisions.
Learning Resources
The indicator includes extensive inline comments explaining each calculation and concept. Users are encouraged to study the source code to understand the methodology behind each component. This transparency aids in learning how technical indicators work and their limitations.
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**Note**: This is an educational tool meant to help traders learn pattern recognition and technical analysis concepts. Success requires practice, additional analysis, and proper risk management.
Breaout and followthroughThis indicator is designed to identify and highlight a single, powerful entry signal at the beginning of a new trend. It filters for high-volatility breakout bars that show strong directional conviction, helping traders catch the initial momentum of a potential move. It will only paint one bullish or bearish signal after a trend change is detected, preventing repeat signals during a sustained move.
Core Concept
The indicator combines four key concepts to generate high-probability signals:
Trend Direction: It first establishes the overall trend (bullish or bearish) using a configurable Exponential or Simple Moving Average (EMA/SMA).
Volatility Expansion: It looks for bars with a larger-than-average range by comparing the bar's size to the Average True Range (ATR). This helps identify moments of increased market interest.
Closing Strength (IBS): It uses the Internal Bar Strength (IBS) to measure directional conviction. A high IBS (closing near the top) suggests bullish strength, while a low IBS (closing near the bottom) suggests bearish pressure.
Breakout Confirmation: As an optional but powerful filter, it can confirm the signal by ensuring the bar is breaking above the high or below the low of a user-defined number of previous bars.
A signal is only generated on the first bar that meets all these criteria after the price crosses the trend-defining moving average, making it ideal for capturing the start of a new swing.
Features
Bullish Signals (Green): Highlights the first bar in an uptrend that is larger than the ATR, closes with a high IBS (>70), and optionally breaks out above the recent highs.
Bearish Signals (Red): Highlights the first bar in a downtrend that is larger than the ATR, closes with a low IBS (<30), and optionally breaks out below the recent lows.
"First Signal Only" Logic: The script is hard-coded to show only the initial signal in a new trend, filtering out noise and redundant signals.
Fully Customizable Trend Filter:
Choose between EMA or SMA for trend definition.
Set the MA length (default is a short-term 7-period MA).
Option to show or hide the moving average on the chart.
Optional Breakout Filter:
Enable or disable the requirement for the signal bar to break the high/low of previous bars.
Customize the lookback period for the breakout confirmation.
How to Use
This indicator can be used as a primary signal for a trend-following or momentum-based trading system.
Look for a Green Bar (Bullish Signal): This suggests the start of a potential uptrend. Consider it a signal for a long entry. A logical stop-loss could be placed below the low of the highlighted signal bar.
Look for a Red Bar (Bearish Signal): This suggests the start of a potential downtrend. Consider it a signal for a short entry. A logical stop-loss could be placed above the high of the highlighted signal bar.
Adjust Settings: Use the settings menu to configure the indicator to your preferred market and timeframe. A longer Trend MA Length will result in fewer, more long-term signals, while a shorter length will be more responsive.
As with any tool, this indicator is best used in conjunction with other forms of analysis, such as market structure, support/resistance levels, and proper risk management.
Dominance Signal Apex [CHE]]Dominance Signal Apex — Triple-confirmed entry markers with stateful guardrails
Summary
This indicator focuses on entry timing by plotting markers only when three conditions align: a closed-bar Heikin-Ashi bias, a monotonic stack of super-smoother filters, and the current HMA slope. A compact state machine provides guardrails: it starts a directional state on closed-bar Heikin-Ashi bias, maintains it only while the smoother stack remains ordered, and renders a marker only if HMA slope agrees. This design aims for selective signals and reduces isolated prints during mixed conditions. Markers fade over time to visualize the age and persistence of the current state.
Motivation: Why this design?
Common triggers flip frequently in noise or react late when regimes shift. The core idea is to gate entry markers through a closed-bar state plus independent filter alignment. The state machine limits premature prints, removes markers when alignment breaks, and uses the HMA as a final directional gate. The result is fewer mixed-context entries and clearer clusters during sustained trends.
What’s different vs. standard approaches?
Reference baseline: Single moving-average slope or classic MA cross signals.
Architecture differences:
Multi-length two-pole super-smoother stack with strict ordering checks.
Closed-bar Heikin-Ashi bias to start a directional state.
HMA slope as a final gate for rendering markers.
Time-based alpha fade to surface state age.
Practical effect: Entry markers appear in clusters during aligned regimes and are suppressed when conditions diverge, improving selectivity.
How it works (technical)
Measurements: Four recursive super-smoother series on price at short to medium horizons. Up regime means each shorter smoother sits below the next longer one; down regime is the inverse.
State machine: On bar close, positive Heikin-Ashi bias starts a bull state and negative bias starts a bear state. The state terminates the moment the smoother ordering breaks relative to the prior bar.
Rendering gate: A marker prints only if the active state agrees with the current HMA slope. The HMA is plotted and colored by slope for context.
Normalization and clamping: Marker transparency transitions from a starting to an ending alpha across a fixed number of bars, clamped within the allowed range.
Initialization: Persistent variables track state and bar-count since state start; Heikin-Ashi open is seeded on the first valid bar.
HTF/security: None used. State updates are closed-bar, which reduces repaint paths.
Bands: Smoothed high, low, centerline, and offset bands are computed but not rendered.
Parameter Guide
Show Markers — Toggle rendering — Default: true — Hides markers without changing logic.
Bull Color / Bear Color — Visual colors — Defaults: bright green / red — Aesthetic only.
Start Alpha / End Alpha — Transparency range — Defaults: one hundred / fifty, within zero to one hundred — Controls initial visibility and fade endpoint.
Steps — Fade length in bars — Default: eight, minimum one — Longer values extend the visual memory of a state.
Smoother Length — Internal band smoothing — Default: twenty-one, minimum two — Affects computed bands only; not drawn.
Band Multiplier — Internal band offset — Default: one point zero — No impact on markers.
Source — Input for HMA — Default: close — Align with your workflow.
Length — HMA length — Default: fifty, minimum one — Larger values reduce flips; smaller values react faster.
Reading & Interpretation
Entry markers:
Bull marker (below bar): Closed-bar Heikin-Ashi bias is positive, smoother stack remains aligned for up regime, and HMA slope is rising.
Bear marker (above bar): Closed-bar Heikin-Ashi bias is negative, smoother stack remains aligned for down regime, and HMA slope is falling.
Fade: Transparency progresses over the configured steps, indicating how long the current state has persisted.
Practical Workflows & Combinations
Trend following: Focus on marker clusters aligned with HMA color. Add structure filters such as higher highs and higher lows or lower highs and lower lows to avoid counter-trend entries.
Exits/Stops: Consider exiting or reducing risk when smoother ordering breaks, when HMA color flips, or when marker cadence thins out.
Multi-asset/Multi-TF: Suitable for liquid crypto, FX, indices, and equities. On lower timeframes, shorten HMA length and fade steps for faster response.
Behavior, Constraints & Performance
Repaint/confirmation: State transitions and marker eligibility are decided on closed bars; live bars do not commit state changes until close.
security()/HTF: Not used.
Resources: Declared max bars back of one thousand five hundred; recursive filters and persistent states; no explicit loops.
Known limits: Some delay around sharp turns; brief states may start in noisy phases but are quickly revoked when alignment fails; HMA gating can miss very early reversals.
Sensible Defaults & Quick Tuning
Start here: Keep defaults.
Too many flips: Increase HMA length and raise fade steps.
Too sluggish: Decrease HMA length and reduce fade steps.
Markers too faint/bold: Adjust start and end alpha toward lower or higher opacity.
What this indicator is—and isn’t
A selective entry-marker layer that prints only under triple confirmation with stateful guardrails. It is not a full system, not predictive, and does not handle risk. Combine with market structure, risk controls, and position management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
ICT 369 Sniper MSS Indicator (HTF Bias) - H2LThis script is an ICT (Inner Circle Trader) concept-based trading indicator designed to identify high-probability reversal or continuation setups, primarily focusing on intraday trading using a Higher Timeframe (HTF) directional bias.
Here are the four core components of the indicator:
Higher Timeframe (HTF) Bias Filter (Market Structure Shift - MSS): It determines the overall trend by checking if the current price has broken the most recent high or low swing point of a larger timeframe (e.g., 4H). This establishes a Bullish or Bearish bias, ensuring trades align with the dominant trend.
Fair Value Gap (FVG) and OTE: It identifies price imbalances (FVGs) and calculates the Optimal Trade Entry (OTE) levels (50%, 62%, 70.5%, etc.) within those gaps, looking for price to retrace into these specific areas.
Kill Zones (Timing): It incorporates specific time windows (London and New York Kill Zones, based on NY Time) where institutional trading activity is high, only allowing entry signals during these defined periods.
Signal and Targets: It triggers a Long or Short signal when all criteria are met (HTF Bias, FVG, OTE retracement, and Kill Zone timing). It then calculates and plots suggested trade levels, including a Stop Loss (SL) and three Take Profit targets (TP1, TP2, and a dynamic Runner Target based on the weekly Average True Range or ATR).
In summary, it's a comprehensive tool for traders following ICT principles, automating the confluence check across trend, structure, liquidity, and timing.
Contrarian Period High & LowContrarian Period High & Low
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Overview
The "Contrarian Period High & Low" indicator is a powerful technical analysis tool designed for traders seeking to identify key support and resistance levels and capitalize on contrarian trading opportunities. By tracking the highest highs and lowest lows over user-defined periods (Daily, Weekly, or Monthly), this indicator plots historical levels and generates buy and sell signals when price breaks these levels in a contrarian manner. A unique blue dot counter and action table enhance decision-making, making it ideal for swing traders, trend followers, and those trading forex, stocks, or cryptocurrencies. Optimized for daily charts, it can be adapted to other timeframes with proper testing.
How It Works
The indicator identifies the highest high and lowest low within a specified period (e.g., daily, weekly, or monthly) and draws horizontal lines for the previous period’s extremes on the chart. These levels act as dynamic support and resistance zones. Contrarian signals are generated when the price crosses below the previous period’s low (buy signal) or above the previous period’s high (sell signal), indicating potential reversals. A blue dot counter tracks consecutive buy signals, and a table displays the count and recommended action, helping traders decide whether to hold or flip positions.
Key Components
Period High/Low Levels: Tracks the highest high and lowest low for each period, plotting red lines for highs and green lines for lows from the bar where they occurred, extending for a user-defined length (default: 200 bars).
Contrarian Signals: Generates buy signals (blue circles) when price crosses below the previous period’s low and sell signals (white circles) when price crosses above the previous period’s high, designed to capture potential reversals.
Blue Dot Tracker: Counts consecutive buy signals (“blue dots”). If three or more occur, it suggests a stronger trend, with the table recommending whether to “Hold Investment” or “Flip Investment.”
Action Table: A 2x2 table in the bottom-right corner displays the blue dot count and action (“Hold Investment” if count ≥ 4, else “Flip Investment”) for quick reference.
Mathematical Concepts
Period Detection: Uses an approximate bar count to define periods (1 bar for Daily, 5 bars for Weekly, 20 bars for Monthly on a daily chart). When a new period starts, the previous period’s high/low is finalized and plotted.
High/Low Tracking:
Highest high (periodHigh) and lowest low (periodLow) are updated within the period.
Lines are drawn at these levels when the period ends, starting from the bar where the extreme occurred (periodHighBar, periodLowBar).
Signal Logic:
Buy signal: ta.crossunder(close , prevPeriodLow) and not lowBroken and barstate.isconfirmed
Sell signal: ta.crossover(close , prevPeriodHigh) and not highBroken and barstate.isconfirmed
Flags (highBroken, lowBroken) prevent multiple signals for the same level within a period.
Blue Dot Counter: Increments on each buy signal, resets on a sell signal or if price exceeds the entry price after three or more buy signals.
Entry and Exit Rules
Buy Signal (Blue Circle): Triggered when the price crosses below the previous period’s low, suggesting a potential oversold condition and buying opportunity. The signal appears as a blue circle below the price bar.
Sell Signal (White Circle): Triggered when the price crosses above the previous period’s high, indicating a potential overbought condition and selling opportunity. The signal appears as a white circle above the price bar.
Blue Dot Tracker:
Increments blueDotCount on each buy signal and sets an entryPrice on the first buy.
Resets on a sell signal or if price exceeds entryPrice after three or more buy signals.
If blueDotCount >= 3, the table suggests holding; if >= 4, it reinforces “Hold Investment.”
Exit Rules: Exit a buy position on a sell signal or when price exceeds the entry price after three or more buy signals. Combine with other tools (e.g., trendlines, support/resistance) for additional confirmation. Always apply proper risk management.
Recommended Usage
The "Contrarian Period High & Low" indicator is optimized for daily charts but can be adapted to other timeframes (e.g., 1H, 4H) with adjustments to the period bar count. It excels in markets with clear support/resistance levels and potential reversal zones. Traders should:
Backtest the indicator on their chosen asset and timeframe to validate signal reliability.
Combine with other technical tools (e.g., moving averages, Fibonacci levels) for stronger trade confirmation.
Adjust barsPerPeriod (e.g., ~120 bars for Weekly on hourly charts) based on the chart timeframe and market volatility.
Monitor the action table to guide position management based on blue dot counts.
Customization Options
Period Type: Choose between Daily, Weekly, or Monthly periods (default: Monthly).
Line Length: Set the length of high/low lines in bars (default: 200).
Show Highs/Lows: Toggle visibility of period high (red) and low (green) lines.
Max Lines to Keep: Limit the number of historical lines displayed (default: 10).
Hide Signals: Toggle buy/sell signal visibility for a cleaner chart.
Table Display: A fixed table in the bottom-right corner shows the blue dot count and action, with yellow (Hold) or green (Flip) backgrounds based on the count.
Why Use This Indicator?
The "Contrarian Period High & Low" indicator offers a unique blend of support/resistance visualization and contrarian signal generation, making it a versatile tool for identifying potential reversals. Its clear visual cues (lines and signals), blue dot tracker, and actionable table provide traders with an intuitive way to monitor market structure and manage trades. Whether you’re a beginner or an experienced trader, this indicator enhances your ability to spot key levels and time entries/exits effectively.
Tips for Users
Test the indicator thoroughly on your chosen market and timeframe to optimize settings (e.g., adjust barsPerPeriod for non-daily charts).
Use in conjunction with price action or other indicators for stronger trade setups.
Monitor the action table to decide whether to hold or flip positions based on blue dot counts.
Ensure your chart timeframe aligns with the selected period type (e.g., daily chart for Monthly periods).
Apply strict risk management to protect against false breakouts.
Happy trading with the Contrarian Period High & Low indicator! Share your feedback and strategies in the TradingView community!
Momentum Volume Analyzer [CHE] Momentum Volume Analyzer — Adaptive momentum with volume-gated signals and expressive visual cues
Summary
This indicator combines a normalized momentum oscillator with a volume Z-score gate and adaptive gradient visuals. The oscillator centers around a midline and scales between a lower and an upper bound. Intensity is derived from the distance to the midline and is normalized inside a rolling window, which helps keep contrast consistent across regimes. Volume pressure is compressed to a discrete level between one and ten and is used to qualify momentum flips and extremes. Layered “burst” markers and optional background gradients provide immediate visual emphasis without adding new data sources. Pine version is v6. The script runs in a separate pane.
Motivation: Why this design?
Common oscillators flip rapidly during noisy conditions or flatten during calm periods, which obscures actionable shifts. A rolling normalization keeps the visual intensity stable across different regimes, and a volume gate reduces reactions when participation is weak. The goal is clearer momentum shifts that are supported by measurable activity rather than cosmetic smoothing alone.
What’s different vs. standard approaches?
Baseline reference: Classical RSI-style oscillators or simple filtered momentum without volume gating.
Architecture differences:
Local window normalization with gamma control for contrast.
Volume converted to a Z-score and compressed into a discrete level between one and ten with a configurable cap.
Directional color gradients that intensify with distance from the midline.
Layered glow markers with optional trail and an internal label budget to avoid UI overload.
Practical effect: Signals are visually stronger only when both momentum and volume align; background and line colors convey regime strength at a glance.
How it works (technical)
Momentum core: A high-pass path with automatic gain control produces a bounded oscillator centered around a midline. A simple moving average smooths the result over a short window.
Normalization and contrast: The absolute distance from the midline is scaled inside a rolling window and limited between zero and one. Two gamma parameters separately shape contrast for the line and for labels.
Coloring: When the oscillator is above the midline, a green gradient is used; below the midline, a red gradient is used. Intensity increases with normalized distance. Optional area fill to the midline and a background gradient reinforce strength.
Volume levels: Volume is standardized over a lookback window, clipped by a user cap, and mapped to a level between one and ten. Only positive excursions are considered; non-positive values map to zero.
Event markers: When the oscillator reaches extreme zones and the volume level is positive, the script spawns layered circular labels at fixed y-positions. A small trail can extend behind the event. An internal queue discards the oldest labels when a user-defined maximum is exceeded.
Alerts: Alerts fire on overbought and oversold spikes, midline shifts with minimum intensity and volume, and continuation patterns inside strong zones.
Parameter Guide
TFRSI length (default six): Core momentum lookback. Shorter values react faster but are less stable.
Signal SMA (default two): Light smoothing of the oscillator. Larger values reduce jitter.
Gradient window (default one hundred): Normalization window for intensity. Longer values produce steadier contrast but slower adaptation.
Line/marker transparency (default zero): Visual prominence of drawings. Higher values reduce dominance.
Background on and BG transparency (defaults true and eighty-five): Enables and tunes the pane background gradient.
Area fill to fifty and Fill transparency (defaults true and eighty): Fills between the oscillator and the midline.
Gamma bars/labels and Gamma plot (defaults zero point seven and zero point eight): Contrast shapers for markers and line. Higher values compress low intensities.
Bottom marker and Show last N (defaults true and three hundred thirty-three): Optional compact heat markers with a display cap.
Up/Down colors: Dark and neon pairs for positive and negative regimes.
Lookback (default two hundred) and Z cap (default five): Volume standardization window and clipping level before scaling to one through ten.
Enable bursts, Layers, Trail, Trail transparency, Max live labels, Size scale: Control the layered glow effect, trail length, opacity, label budget, and size multiplier. Reducing the size scale lowers visual dominance.
Spike min level, Shift min level, Min intensity, Rise/Fall length: Gates for alerts; adjust to balance sensitivity and false positives.
Reading & Interpretation
Line color and intensity: Green shades above the midline indicate bullish pressure; red shades below indicate bearish pressure. Stronger color corresponds to stronger normalized distance.
Background and fill: Reinforce regime strength; consider reducing transparency when the pane feels too busy.
Bursts and trails: Emphasize volume-backed extremes. Larger bursts reflect stronger volume levels or scaling choices.
Volume level: Internal level between one and ten. Levels near the upper bound signal exceptional activity.
Practical Workflows & Combinations
Trend following: Use midline cross upward with minimum shift level and intensity as a trigger. Confirm with structure such as higher highs and higher lows. For shorts, reverse the conditions.
Exits and risk: Fade exposure when intensity weakens toward the midline or when volume level drops below the shift threshold. Consider disabling bursts when monitoring many symbols.
Multi-asset and multi-timeframe: Defaults are designed to travel across liquid futures, large-cap equities, and major crypto pairs. For higher timeframes, increase the lookback window and consider reducing the Z cap.
Behavior, Constraints & Performance
Repaint and confirmation: Signals are evaluated on the live bar. They can appear and withdraw before bar close. For confirmed signals, require closed-bar alerts or manual confirmation.
Higher-timeframe sources: Not used. No `security` calls.
Resources: `max_bars_back` is two thousand. The script uses arrays and label objects, including loops for trails. The label budget mitigates clutter.
Known limits: Very illiquid symbols with unstable volume can reduce the usefulness of the Z-score. Sharp regime changes can still produce brief flips.
Sensible Defaults & Quick Tuning
Starting point: TFRSI length six, Signal two, Gradient window one hundred, Z cap five, Spike level six, Shift level four, Min intensity zero point four, Rise length three, Size scale zero point five.
Too many flips: Increase Signal, increase Gradient window, or raise Shift level.
Too sluggish: Decrease TFRSI length or reduce Gradient window.
Bursts too dominant: Lower Size scale or reduce Layers; increase Trail transparency or set Trail length to zero.
What this indicator is—and isn’t
This is a visualization and signal layer that couples momentum with a volume gate and adaptive visuals. It is not a complete trading system, optimizer, or predictor. Use it together with market structure, risk controls, and position management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
