Volatility Cone [Loxx]When it comes to forecasting volatility, it seems that the old axiom about weather is applicable: "Everyone talks about it, but no one can do much about it!" Volatility cones are a tool that may be useful in one’s attempt to do something about predicting the future volatility of an asset.
A "volatility cone" is a plot of the range of volatilities within a fixed probability band around the true parameter, as a function of sample length. Volatility cone is a visualization tool for the display of historical volatility term structure. It was introduced by Burghardt and Lane in early 1990 and is popular in the option trading community. This is mostly a static indicator due to processor load and is restricted to the daily time frame.
Why cones?
When we enter the options arena, in an effort to "trade volatility," we want to be able to compare current levels of implied volatility with recent historical volatility in an effort to assess the relative value of the option(s) under consideration Volatility cones can be an effective tool to help us with this assessment. A volatility cone is an analytical application designed to help determine if the current levels of historical or implied volatilities for a given underlying, its options, or any of the new volatility instruments, such as VolContractTM futures, VIX futures, or VXX and VXZ ETNs, are likely to persist in the future. As such, volatility cones are intended to help the user assess the likely volatility that an underlying will go on to display over a certain period. Those who employ volatility cones as a diagnostic tool are relying upon the principle of "reversion to the mean." This means that unusually high levels of volatility are expected to drift or move lower (revert) to their average (mean) levels, while relatively low volatility readings are expected to rise, eventually, to more "normal" values.
How to use
Suppose you want to analyze an options contract expiring in 3-months and this current option has an current implied volatility 25.5%. Suppose also that realized volatility (y-axis) at the 3-month mark (90 on the x-axis) is 45%, median in 35%, the 25th percentile is 30%, and the low is 25%. Comparing this range to the implied volatility you would maybe conclude that this is a relatively "cheap" option contract. To help you visualize implied volatility on the chart given an expiration date in bars, the indicator includes the ability to enter up to three expirations in bars and each expirations current implied volatility
By ascertaining the various historical levels of volatility corresponding to a given time horizon for the options futures under consideration, we’re better prepared to judge the relative "cheapness" or "expensiveness" of the instrument.
Volatility options
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility. One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility. That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Sampling periods used
5, 10, 20, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330, and 360
Historical Volatility plot
Purple outer lines: High and low volatility values corresponding to x-axis time
Blue inner lines: 25th and 75th percentiles of volatility corresponding to x-axis time
Green line: Median volatility values corresponding to x-axis time
White dashed line: Realized volatility corresponding to x-axis time
Additional things to know
Due to UI constraints on TradingView it will be easier to visualize this indicator by double-clicking the bottom pane where it appears and then expanded the y- and x-axis to view the entire chart.
You can click on each point on the graph to see what the volatility of that point is.
Option expiration dates will show up as large dots on the graph. You can input your own values in the settings.
Cerca negli script per "session"
Variety Distribution Probability Cone [Loxx]Variety Distribution Probability Cone forecasts price within a range of confidence using Geometric Brownian Motion (GBM) calculated using selected probability distribution, volatility, and drift. Below is detailed explanation of the inner workings of the indicator and the math involved. While normally this indicator would be used by options traders, this can also be used by regular directional traders who wish to observe a forecast of the confidence interval of possible prices over time.
What is a Random Walk
A random walk is a path which consists of a set of random steps. The starting point is zero and following movement may be one step to the left or to the right with equal probability. In the random walk process, there is no observable trend or pattern which are followed by the objects that is the movements are completely random. That is why the prices of a stock as it moves up and down can be modeled by random a walk process.
Stock Prices and Geometric Brownian Motion
Brownian motion, as first conceived by the botanist Robert Brown (1827), is a mathematical model used to describe random movements of small particles in a fluid or gas. These random movements are observed in the stock markets where the prices move up and down, randomly; hence, Brownian motion is considered as a mathematical model for stock prices.
P(exp(lnS0 + (mu + 1/2*sigma^2)t - z(0.05)*sigma*t^0.5) <= St <= exp(lnS0 + (mu + 1/2*sigma^2)t + z(0.05)*sigma*t^0.5)) = 0.95
Probability Distributions
Typically the normal distribution is used, but for our purposes here we extend this to Student t-distribution, Cauchy, Gaussian KDE, and Laplace
Student's t-Distribution
The probability density function of the Student’s t distribution is given by
g(x) = (L(v+1)/2) / L(v/2) * 1 / L(sqrt(v)) * (1 + x^2/v) ^ (-(v+1)/2)
with v degrees of freedom and v >= 0, denoted by X ~ t(v). The mean is 0 and the variance is v/(v-2). It is known that as v tends to infinity, the Student’s t-distribution tends to a standard normal probability density function, which has a variance of one. Blattberg and Gonedes were the first to propose that stock returns could be modeled by this distribution. (Blattberg and Gonedes, 1974) Platen and Sidorowicz later reaffirmed these findings.(Platen and Rendek, 2007) Finally, Cassidy, Hamp, and Ouyed used these findings to derive the Gosset formula, which is the Student t version of the Black-Scholes model.(Cassidy et al., 2010) They found that v = 2.65 provides the best fit when looking at the past 100 years of returns. They realized that as markets become more turbulent, the degrees of freedom should be adjusted to a smaller value.(Cassidy et al., 2010)
Cauchy Distribution
The probability density function of the Cauchy distribution is given by
f(x) = 1 / (theta*pi*(1 + ((x-n)/v)))
where n is the location parameter and theta is the scale parameter, for -infinity < x < infinity and is denoted by X ~ CAU(L,v). This model is similar to the normal distribution in that it is symmetric about zero, but the tails are fatter. This would mean that the probability of an extreme event occurring lies far out in the distributions tail. Using a crude example, if the normal distribution gave a probability of an extreme event occurring of 0.05% and the “best case” scenario of this event occurring 300 years, then using the Cauchy distribution one would find that the probability of occurring would be around 5% and now the “best case” scenario might have been reduced to only 63 years. Thus giving extreme events more of a likelihood of occurring. The mean, variance, and higher order moments are not defined (they are infinite); this implies that n and theta cannot be related to a mean and standard deviation. The Cauchy distribution is related to the Student’s t distribution T ~ CAU(1,0) when v = 1. In 1963, Benoit Mandelbrot was the first to suggest that stock returns follow a stable distribution, in particular, the Cauchy distribution.(Mandelbrot, 1963) His work was validated by Eugene Fama in 1965.(Fama, 1965) Recent research by Nassim Taleb came to the same conclusion as Mandelbrot, saying that stock returns follow a Cauchy distribution, as reported in his New York Times best-seller book “The Black Swan”.(Taleb, 2010)
Laplace Distribution
In probability theory and statistics, the Laplace distribution is a continuous probability distribution named after Pierre-Simon Laplace. It is also sometimes called the double exponential distribution, because it can be thought of as two exponential distributions (with an additional location parameter) spliced together along the abscissa, although the term is also sometimes used to refer to the Gumbel distribution. The difference between two independent identically distributed exponential random variables is governed by a Laplace distribution, as is a Brownian motion evaluated at an exponentially distributed random time. Increments of Laplace motion or a variance gamma process evaluated over the time scale also have a Laplace distribution.
The probability density function of the Cauchy distribution is given by
f(x) = 1/2b * exp(-|x-µ|/b)
Here, µ is a location parameter and b > 0, which is sometimes referred to as the "diversity", is a scale parameter. If µ = 0 and b=1, the positive half-line is exactly an exponential distribution scaled by 1/2.
The probability density function of the Laplace distribution is also reminiscent of the normal distribution; however, whereas the normal distribution is expressed in terms of the squared difference from the mean µ, the Laplace density is expressed in terms of the absolute difference from the mean. Consequently, the Laplace distribution has fatter tails than the normal distribution.
Gaussian Kernel Density Estimation
In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights. KDE is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. In some fields such as signal processing and econometrics it is also termed the Parzen–Rosenblatt window method, after Emanuel Parzen and Murray Rosenblatt, who are usually credited with independently creating it in its current form. One of the famous applications of kernel density estimation is in estimating the class-conditional marginal densities of data when using a naive Bayes classifier, which can improve its prediction accuracy.
Let (x1, x2, ..., xn) be independent and identically distributed samples drawn from some univariate distribution with an unknown density f at any given point x. We are interested in estimating the shape of this function f. Its kernel density estimator is:
f(x) = 1/nh * sum(k(x-xi)/h, n)
where K is the kernel—a non-negative function—and h > 0 is a smoothing parameter called the bandwidth. A kernel with subscript h is called the scaled kernel and defined as Kh(x) = 1/h K(x/h). Intuitively one wants to choose h as small as the data will allow; however, there is always a trade-off between the bias of the estimator and its variance.
The probability density function of Gaussian Kernel Density Estimation is given by
f(x) = 1 / (v * 2*pi)^0.5 * exp(-(x - m)^2 / (2 * v))
where v is the bandwidth component h squared
KDE Bandwidth Estimation
Bandwidth selection strongly influences the estimate obtained from the KDE (much more so than the actual shape of the kernel). Bandwidth selection can be done by a "rule of thumb", by cross-validation, by "plug-in methods" or by other means. The default is Scott's Rule.
Scott's Rule
n ^ (-1/(d+4))
with n the number of data points and d the number of dimensions.
In the case of unequally weighted points, this becomes
neff^(-1/(d+4))
with neff the effective number of datapoints.
Silverman's Rule
(n * (d + 2) / 4)^(-1 / (d + 4))
or in the case of unequally weighted points:
(neff * (d + 2) / 4)^(-1 / (d + 4))
With a set of weighted samples, the effective number of datapoints neff
is defined by:
neff = sum(weights)^2 / sum(weights^2)
Manual input
You can provide your own bandwidth input. This is useful for those who wish to run external to TradingView Grid Search Machine Learning algorithms to solve for the bandwidth per ticker.
Inverse CDF of KDE Calculation
1. Create an array of random normalized numbers, using an inverse CDF of a normal distribution of mean of zero
and standard deviation one
2. Create a line space range of values -3 to 3
3. Create a Gaussian Kernel Density Estimate CDF by iterating over the line space array created in step 2. For each line space item, find the mean difference between the line space and the random variable divided by the bandwidth.
4. Derive test statistics from the resulting KDE inverse CDF, we use cubic spline interpolation to solve for line space value for a given alpha computed using the user selected probability percent value in the settings.
Volatility
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility. That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ)avg(var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as θ.
Manual
User input % value
Drift
Cost of Equity / Required Rate of Return (CAPM)
Standard Capital Asset Pricing Model used to solve for Cost of Equity of Required Rate of Return. Due to the processor overhead required to compute CAPM, the user must plug in values for beta, alpha, and expected market return using Loxx's CAPM indicator series. Used for stocks.
Mean of Log Returns
Average of the log returns for the underlying ticker over the user selected period of evaluation. General purpose use.
Risk-free Rate (r)
10, 20, or 30 year bond yields for the user selected currency. Under equilibrium the drift of the empirical GBM must be the risk-free rate. If the price process is a GBM under the empirical measure, then a consequence of viability is that it is also a GBM under an equivalent (risk-neutral) measure.
Risk-free Rate adjusted for Dividends (r-q)
This is the Risk-free Rate minus the Dividend Yield.
Forex (r-rf)
This is derived from the Garman and Kohlhagen (1983) modified Black-Scholes model can be used to price European currency options. This is simply the diffeence between Risk-free Rate of the Forex currency in question. This is used for Forex pricing.
Martingale (0)
When the drift parameter is 0, geometric Brownian motion is a martingale. In probability theory, a martingale is a sequence of random variables (i.e., a stochastic process) for which, at a particular time, the conditional expectation of the next value in the sequence is equal to the present value, regardless of all prior values. Typically used for futures or margined futures.
Manual
User input % value
Additional notes
Indicator can be used on any timeframe. The T (time) variable used to annualize volatility and inside the GBM formula is automatically calculated based on the timeframe of the chart.
Confidence interval of volatility is calculated using an inverse CDF of a Chi-Squared Distribution. You change the volatility input used to create the probability cones from from realized volatility to upper or lower confidence levels of volatility to better visualize extremes of range. Generally, you'd stick with realized volatility.
Days per year should be 252 for everything but Cryptocurrency. These are days trader per year. Maximum future forecast bars is 365. Forecast bars are limited to the maximum of selected days per year.
Includes the ability to overlay option expiration dates by bars to see the range of prices for that date at that bar
You can select confidence % you wish for both the cone in general and the volatility. There are three levels for the cones, this will show on the three different levels up and down on the chart.
The table on the right displays important calculated values so you don't have to remember what they are or what settings you selected
All values are annualized no matter the timeframe.
Additional distributions and measures of volatility and drift will be added in future releases.
KVKZKVKZ = KV'S KILLZONES
This Indicator, break the charts into session: ASIAN, LONDON, NEW YORK.
-The 1st two vertical lines (red) indicates the ASIAN RANGE
-The 2nd two vertical lines (red & green) indicates the LONDON session
-The 3rd two vertical lines (green & blue) indicates the NEW YORK session
-The will be no trading in between the two red vertical lines
-A fake move is expected to happen in between the 2nd red vertical line and green line, this fake move is known as the JUDAS SWING by ICT, you can YouTube Judas Swing and check out his concepts
-There are two automatically moving horizontal lines (orange), that plots the ASIAN high and lows, these levels are expected to be manipulated in the London session, and this is called the Judas Swing
-the purple lines are known as Institution Zones, basically just levels 30pips above and below the ASIAN range
-this indicator works well with GBPUSD, EURUSD, USDCHF
-this indicator doesn’t work well with USDJPY, AUDUSD, NZDUSD
INPUTS:
HOUR 1: 17
MIN 1 : 0
HOUR 2: 0
MIN 2 : 0
HOUR 3: 6
MIN 3 : 0
HOUR 4: 12
MIN 1 : 0
THIS INDICATOR IS NOT A HOLY GRAIL, BUT IF YOU CAN READ PRICE ACTION WELL, THESE SESSIONS BREAK DOWN COULD BE VERY USEFULL.
Extras:
dot = dotted lines
dsh = dashed lines
sol = solid lines
NOTE: time has to be set to NY time.
Anchored OBV SpaceManBTC Anchored OBV SpaceManBTC
The On Balance Volume indicator (OBV) is used in technical analysis to measure buying and selling pressure.
On Balance volume is primarily used to confirm or identify overall price trends or to anticipate price movements after divergences.
Anchored On Balance Volume unlike traditional OBV resets on your specified sessions: D, W, M, 3M, 4M, 6M, 1Y.
The actionable data is more useful HTF to see a potential long term trend change relative to the session reset chosen.
User can choose to disable highlightable session reset.
Recommended settings:
Daily tf with 3Month session pretty useful for the run so far. But please experiment away and share your results!
ToDo:
Non Reset Functionality,
Perhaps more timeframes
SMT - Smart Money Thursday Boxes
The Smart Money Trading Thursday - is a very specific trading system. You only trade it on a Thursday.
The script/indicator will color Thursdays as two boxes. If you just want one color, use same color for
both boxes. The boxes is there to indicate London/New York sessions.
SETTINGS
In the setting you find a numeric value as 1700-0400:5
The "5" indicate Thursday. You can change that if you prefer to color another specific day.
For example "4" would indicate Wednesday. And you can change the hours to fit your
sessions and trading style.
You can also use the 2 boxes on different days. If you for example would like to color up
London for Wednesday and Thursday. Then set hours to fit London session and adjust the
:5 to 4 on the 1st box and 5 on the 2nd.
HOW TO USE IT?
The Smart Money works in a way retail trading does not. Smart Money has an objective
to locate retail patterns, where there will be a lot of stop loss volume to be grabbed.
So when a retail trader see a setup like a "Double Top / Bottom". The Institutional
will see $$$ of dumb money, ready to be taken. The best moves happen on a Thursday
but if you are a skilled trader, you can see the move also occur on Wednesday or Friday.
The first thing that will happen, is that the Smart Money Breaks out of session. Meaning
they will leave the current weeks high/low range. To start collect negative contracts
of the retail volume.
When you see that happen. And you see a breakout that consist of 4 in a row 1 hour
chart candles. Then you have your first rule meet.
#1 Thursday breakout of current weeks high/low. And the move is a clean 4 hour move
as 4x H1 candles. The move can start within range. But must end clearly outside.
Visual Example:
#2 Next, we await an engulf at peak or near peak. That is where Institutional
may have problem to match any more contracts, and since they used their own
money to make this move. They must now mitigate orders, and return back to
the original retail pattern as most retail traders are now stopped out.
(Normally this is a long/clear candle out of range. they rarely go lower
then retail traders entry in the 1st push. This to not save any souls :)
#3 Price returns back to where the breakout from the retail happens.
You can now take your profit as a Smart Money Trader. Trading with less risk,
you can take profit of the return of that latest 4x H1 candle move. (Order
Block)
CONCLUSION
The best trade is when you can combine a retail pattern, followed by a
breakout which holds 4x 1 hour candles in the outbreak direction.
2nd best is when you have the 4x H1 breakout and really no clear retail
pattern. Still is the same game. Just not as clear as the one above.
Study the steps in this image and you see what to look after:
Good Luck with your trading!
Regards,
The Hunter Trading Group
GeeksDoByte 15m & 30m ORB + Prev Day High/LowCME_MINI:NQ1!
How It Works
Opening Ranges
At 9:30 ET, the script begins tracking the high & low.
It uses two fixed sessions:
15 min from 09:30 to 09:45
30 min from 09:30 to 10:00
On the very first bar of each session it initializes the range, then continuously updates the high/low on each new intraday bar.
Dashed lines are drawn when the session opens and extended horizontally across subsequent bars.
Previous Day’s Levels
Independently, it fetches yesterday’s high and low via a daily security call.
These historic levels are plotted as simple horizontal lines for daily context.
How to Use
Breakout Entries
A close above the 15 min ORB high can signal an early breakout; a further push above the 30 min ORB high confirms extended momentum.
Conversely, breaks below the respective lows can indicate short setups.
Support & Resistance
Yesterday’s high/low often act as magnet levels. If price is near the previous high when the opening ranges break, you get a confluence zone worth watching.
Trade Management
Combine the two opening-range levels to tier your stops or scale in.
For example, you might place an initial stop below the 15 min low and a wider stop below the 30 min low.
Rpaid Killzone Breakout v3.6Final Indicator Title: Rapid Killzone Break & HTF Levels
Overview
Welcome to the Rapid Killzone Break & HTF Levels, an all-in-one trading toolkit designed for precision and context. This indicator was built to solve a common problem for day traders: how to combine a precise, lower-timeframe (LTF) entry model with the essential context of higher-timeframe (HTF) levels.
This tool is founded on a session-based breakout strategy, leveraging the volatility and liquidity generated during specific market hours (the "Killzones"). It then layers critical HTF support and resistance levels onto your chart, allowing you to make more informed trading decisions without ever needing to switch timeframes.
Whether you trade Forex, Gold, or major Indices, this indicator provides a comprehensive framework for identifying high-probability breakout opportunities.
The Core Strategy
The methodology is a powerful three-step process based on session liquidity and qualified breakouts:
The Killzone Range: The indicator first identifies the high and low established during a specific, high-volatility trading session (e.g., the first hour of London or New York). This range acts as a pool of liquidity. The core idea is that the market will often seek to "sweep" or run the liquidity resting above the session high or below the session low.
The Qualified Breakout: This is not just any breakout strategy. A valid entry signal only appears when price closes decisively outside the Killzone range with significant momentum. To ensure the quality of the signal, the breakout must meet several user-defined criteria:
The Killzone must have a minimum pip range.
The breakout candle must have a strong body-to-wick ratio.
The breakout must be accompanied by a spike in volume.
Higher Timeframe Confluence: A breakout is more likely to succeed if it aligns with the HTF narrative. This indicator plots the previous higher-timeframe candle's high and low directly onto your chart. These levels act as powerful magnets for price or as formidable support/resistance zones. A breakout on the LTF that targets the HTF previous high is a much higher-probability setup than one trading directly into it.
Key Features
📊 DST-Aware Killzones: Automatically adjusting session boxes for London and New York. The timezones are fully configurable (e.g., Europe/London, America/New_York) and automatically handle Daylight Saving Time changes so you never have to manually adjust them.
📈 Killzone Pivots: Automatically draws the High, Low, and a dotted Midpoint from each Killzone session, acting as key intraday levels.
🏛️ Higher Timeframe (HTF) Levels: Plots the previous HTF candle's High and Low as dashed lines on your chart, providing critical context for support, resistance, and targets.
🕯️ HTF Mini-Candles: Displays a visual summary of the last three HTF candles on the right side of your chart, so you can see the HTF trend at a glance.
⏰ Custom Vertical Timestamps: Up to three configurable vertical lines with labels to mark key events like other session opens (e.g., "Sydney Open").
🎛️ Advanced Breakout Filters: Fine-tune your signals with filters for minimum Killzone range, minimum candle body percentage, and volume spikes. (Important: The volume filter requires a data feed that provides real volume, such as OANDA, FXCM, or futures/stock data).
✅ Dynamic Entry Advice Table: After a signal, a table provides a suggested entry technique (e.g., "50% retrace to signal candle") based on how far price has moved from the breakout level.
📋 Killzone Range Stats Table: A clean table shows the current and average pip range for both the London and New York sessions, helping you gauge current volatility.
🛠️ Fully Customizable: Nearly every visual element can be toggled on/off or have its color and style changed to suit your personal chart theme.
How to Use This Indicator
This tool is designed to provide a clear, step-by-step workflow for your trading sessions.
Setup: In the settings, choose your desired Reference Timeframe (e.g., 240 for 4-Hour). Configure your Killzone session times and colors.
Context is King: Before the session begins, take note of where price is in relation to the dashed HTF High/Low lines. Is price consolidating below the previous HTF low? A breakout might target it. Is price approaching the HTF high? This could be a take-profit area or a point of resistance.
Wait for the Range: Allow the London or New York Killzone (the colored box) to form completely.
Anticipate the Breakout: Once the session box is closed, the indicator is now hunting for a valid breakout.
Validate the Signal: When a "Long" or "Short" label appears, this is your entry signal. Check the Info-Box data (RSI, volume, candle body %) to confirm the strength of the move.
Manage the Trade: Use the Killzone pivots and the HTF High/Low lines as potential areas to manage your trade, take partial profits, or identify a final target. Check the Entry Advice table for ideas on refined entries if you miss the initial move.
Applicable Markets
This strategy is most effective on instruments known for their session-based volatility. It has been tested and works exceptionally well on:
Forex Majors: EUR/USD, GBP/USD, etc.
Gold: XAU/USD
Indices: NASDAQ 100 (NQ100), S&P 500 (SPX500)
It is best used on lower timeframes (such as the 5-minute or 15-minute chart) for trade execution.
LilSpecCodes1. Killzone Background Highlighting:
It highlights 4 key market sessions:
Killzone Time (EST) Color
Silver Bullet 9:30 AM – 12:00 PM Light Blue
London Killzone 2:00 AM – 5:00 AM Light Green
NY PM Killzone 1:30 PM – 4:00 PM Light Purple
Asia Open 7:00 PM – 11:00 PM Light Red
These are meant to help you focus during high-probability trading times.
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2. Previous Day High/Low (PDH/PDL):
Plots green line = PDH
Plots red line = PDL
Tracks the current day’s session high/low and sets it as PDH/PDL on a new trading day
CHANGES WITH ETH/RTH
3. Inside Bar Marker:
Plots a small black triangle under bars where the high is lower than the previous bar’s high and the low is higher than the previous bar’s low (inside bars)
Useful for spotting potential breakout or continuation setups
4. Vertical Time Markers (White Dashed Lines)
Time (EST) Label
4:00 AM End of London Silver Bullet
9:30 AM NYSE Open
10:00 AM Start of NY Silver Bullet
11:00 AM End of NY Silver Bullet
11:30 AM (Customizable Input)
3:00 PM PM Killzone Ends
3:15 PM Futures Market Close
7:15 PM Asia Session Watch
Trend TraderDescription and Usage of the "Trend Trader" Indicator
The "Trend Trader" indicator, created by Gerardo Mercado as a legacy project, is a versatile trading tool designed to identify potential buy and sell signals across various instruments. While it provides predefined settings for popular instruments like US30, NDX100, GER40, and GOLD, it can be seamlessly adapted to any market, including forex pairs like EUR/USD. The indicator combines moving averages, time-based filters, and MACD confirmation to enhance decision-making for traders.
How It Works
Custom Moving Averages (MAs):
The indicator uses two moving averages:
Short MA: A faster-moving average (default: 10 periods).
Long MA: A slower-moving average (default: 100 periods).
Buy signals are generated when the Short MA crosses above the Long MA.
Sell signals are triggered when the Short MA crosses below the Long MA.
Time-Based Signals:
The user can define specific trading session times (start and end in UTC) to focus on high-activity periods for their chosen market.
Signals and background coloring are only active during the allowed session times.
MACD Confirmation:
A MACD (Moving Average Convergence Divergence) calculation on a 15-minute timeframe ensures stronger confirmation for signals.
Buy signals require the MACD line to be above the signal line.
Sell signals require the MACD line to be at or below the signal line.
Target Levels:
Predefined profit targets are dynamically set based on the selected trading instrument.
While it includes settings for US30, NDX100, GER40, and GOLD, the target levels can be adjusted to fit the volatility and structure of any asset, including forex pairs like EUR/USD.
Target 1 and Target 2 levels display when these thresholds are met after an entry signal.
Adaptability to Any Market:
Although predefined options are included for specific instruments, the indicator's moving averages, time settings, and MACD logic are applicable to any tradable asset, making it suitable for forex, commodities, indices, and more.
Visual Alerts:
Labels appear on the chart to highlight "BUY" and "SELL" signals at crossover points.
Additional labels indicate when price movements reach the predefined target levels.
Bar and background coloring visually represent active signals and MACD alignment.
Purpose
The indicator aims to simplify trend-following and momentum-based trading strategies. By integrating moving averages, MACD, customizable time sessions, and dynamic targets, it offers clear entry and exit points while being adaptable to the needs of individual traders across diverse markets.
How to Use
Setup:
Add the indicator to your TradingView chart.
Configure the moving average periods, trading session times, and target levels according to your preferences.
Select the instrument for predefined target settings or customize them to fit the asset you’re trading (e.g., EUR/USD or other forex pairs).
Interpreting Signals:
Buy Signal: The Short MA crosses above the Long MA, MACD confirms the upward trend, and the session is active.
Sell Signal: The Short MA crosses below the Long MA, MACD confirms the downward trend, and the session is active.
Adapt for Any Instrument:
Adjust the predefined target levels to match the volatility and trading style for your chosen asset.
For forex pairs like EUR/USD, consider typical pip movements to set appropriate profit targets.
Targets:
Use the provided target labels (e.g., 50 or 100 points) or customize them to reflect realistic profit goals based on the asset’s volatility.
Visual Aids:
Pay attention to the background color:
Greenish: Indicates a bullish trend during the allowed session.
Redish: Indicates a bearish trend during the allowed session.
Use the "BUY" and "SELL" labels for actionable insights.
This indicator is a flexible and powerful tool, suitable for traders across all markets. Its adaptability ensures that it can enhance your strategy, whether you’re trading forex, commodities, indices, or other assets. By offering actionable alerts and customizable settings, the "Trend Trader" serves as a valuable addition to any trader’s toolkit. FX:EURUSD
Enhanced Volume Trend Indicator with BB SqueezeEnhanced Volume Trend Indicator with BB Squeeze: Comprehensive Explanation
The visualization system allows traders to quickly scan multiple securities to identify high-probability setups without detailed analysis of each chart. The progression from squeeze to breakout, supported by volume trend confirmation, offers a systematic approach to identifying trading opportunities.
The script combines multiple technical analysis approaches into a comprehensive dashboard that helps traders make informed decisions by identifying high-probability setups while filtering out noise through its sophisticated confirmation requirements. It combines multiple technical analysis approaches into an integrated visual system that helps traders identify potential trading opportunities while filtering out false signals.
Core Features
1. Volume Analysis Dashboard
The indicator displays various volume-related metrics in customizable tables:
AVOL (After Hours + Pre-Market Volume): Shows extended hours volume as a percentage of the 21-day average volume with color coding for buying/selling pressure. Green indicates buying pressure and red indicates selling pressure.
Volume Metrics: Includes regular volume (VOL), dollar volume ($VOL), relative volume compared to 21-day average (RVOL), and relative volume compared to 90-day average (RVOL90D).
Pre-Market Data: Optional display of pre-market volume (PVOL), pre-market dollar volume (P$VOL), pre-market relative volume (PRVOL), and pre-market price change percentage (PCHG%).
2. Enhanced Volume Trend (VTR) Analysis
The Volume Trend indicator uses adaptive analysis to evaluate buying and selling pressure, combining multiple factors:
MACD (Moving Average Convergence Divergence) components
Volume-to-SMA (Simple Moving Average) ratio
Price direction and market conditions
Volume change rates and momentum
EMA (Exponential Moving Average) alignment and crossovers
Volatility filtering
VTR Visual Indicators
The VTR score ranges from 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions. This is visually represented by colored circles:
"●" (Filled Circle):
Green: Strong bullish trend (VTR ≥ 80)
Red: Strong bearish trend (VTR ≤ 20)
"◯" (Hollow Circle):
Green: Moderate bullish trend (VTR 65-79)
Red: Moderate bearish trend (VTR 21-35)
"·" (Small Dot):
Green: Weak bullish trend (VTR 55-64)
Red: Weak bearish trend (VTR 36-45)
"○" (Medium Hollow Circle): Neutral conditions (VTR 46-54), shown in gray
In "Both" display mode, the VTR shows both the numerical score (0-100) alongside the appropriate circle symbol.
Enhanced VTR Settings
The Enhanced Volume Trend component offers several advanced customization options:
Adaptive Volume Analysis (volTrendAdaptive):
When enabled, dynamically adjusts volume thresholds based on recent market volatility
Higher volatility periods require proportionally higher volume to generate significant signals
Helps prevent false signals during highly volatile markets
Keep enabled for most trading conditions, especially in volatile markets
Speed of Change Weight (volTrendSpeedWeight, range 0-1):
Controls emphasis on volume acceleration/deceleration rather than absolute levels
Higher values (0.7-1.0): More responsive to new volume trends, better for momentum trading
Lower values (0.2-0.5): Less responsive, better for trend following
Helps identify early volume trends before they fully develop
Momentum Period (volTrendMomentumPeriod, range 2-10):
Defines lookback period for volume change rate calculations
Lower values (2-3): More responsive to recent changes, better for short timeframes
Higher values (7-10): Smoother, better for daily/weekly charts
Directly affects how quickly the indicator responds to new volume patterns
Volatility Filter (volTrendVolatilityFilter):
Adjusts significance of volume by factoring in current price volatility
High volume during high volatility receives less weight
High volume during low volatility receives more weight
Helps distinguish between genuine volume-driven moves and volatility-driven moves
EMA Alignment Weight (volTrendEmaWeight, range 0-1):
Controls importance of EMA alignments in final VTR calculation
Analyzes multiple EMA relationships (5, 10, 21 period)
Higher values (0.7-1.0): Greater emphasis on trend structure
Lower values (0.2-0.5): More focus on pure volume patterns
Display Mode (volTrendDisplayMode):
"Value": Shows only numerical score (0-100)
"Strength": Shows only symbolic representation
"Both": Shows numerical score and symbol together
3. Bollinger Band Squeeze Detection (SQZ)
The BB Squeeze indicator identifies periods of low volatility when Bollinger Bands contract inside Keltner Channels, often preceding significant price movements.
SQZ Visual Indicators
"●" (Filled Circle): Strong squeeze - high probability setup for an impending breakout
Green: Strong squeeze with bullish bias (likely upward breakout)
Red: Strong squeeze with bearish bias (likely downward breakout)
Orange: Strong squeeze with unclear direction
"◯" (Hollow Circle): Moderate squeeze - medium probability setup
Green: With bullish EMA alignment
Red: With bearish EMA alignment
Orange: Without clear directional bias
"-" (Dash): Gray dash indicates no squeeze condition (normal volatility)
The script identifies squeeze conditions through multiple methods:
Bollinger Bands contracting inside Keltner Channels
BB width falling to bottom 20% of recent range (BB width percentile)
Very narrow Keltner Channel (less than 5% of basis price)
Tracking squeeze duration in consecutive bars
Different squeeze strengths are detected:
Strong Squeeze: BB inside KC with tight BB width and narrow KC
Moderate Squeeze: BB inside KC with either tight BB width or narrow KC
No Squeeze: Normal market conditions
4. Breakout Detection System
The script includes two breakout indicators working in sequence:
4.1 Pre-Breakout (PBK) Indicator
Detects potential upcoming breakouts by analyzing multiple factors:
Squeeze conditions lasting 2-3 bars or more
Significant price ranges
Strong volume confirmation
EMA/MACD crossovers
Consistent price direction
PBK Visual Indicators
"●" (Filled Circle): Detected pre-breakout condition
Green: Likely upward breakout (bullish)
Red: Likely downward breakout (bearish)
Orange: Direction not yet clear, but breakout likely
"-" (Dash): Gray dash indicates no pre-breakout condition
The PBK uses sophisticated conditions to reduce false signals including minimum squeeze length, significant price movement, and technical confirmations.
4.2 Breakout (BK) Indicator
Confirms actual breakouts in progress by identifying:
End of squeeze or strong expansion of Bollinger Bands
Volume expansion
Price moving outside Bollinger Bands
EMA crossovers with volume confirmation
MACD crossovers with significant price range
BK Visual Indicators
"●" (Filled Circle): Confirmed breakout in progress
Green: Upward breakout (bullish)
Red: Downward breakout (bearish)
Orange: Unusual breakout pattern without clear direction
"◆" (Diamond): Special breakout conditions (meets some but not all criteria)
"-" (Dash): Gray dash indicates no breakout detected
The BK indicator uses advanced filters for confirmation:
Requires consecutive breakout signals to reduce false positives
Strong volume confirmation requirements (40% above average)
Significant price movement thresholds
Consistency checks between price action and indicators
5. Market Metrics and Analysis
Price Change Percentage (CHG%)
Displays the current percentage change relative to the previous day's close, color-coded green for positive changes and red for negative changes.
Average Daily Range (ADR%)
Calculates the average daily percentage range over a specified period (default 20 days), helping traders gauge volatility and set appropriate price targets.
Average True Range (ATR)
Shows the Average True Range value, a volatility indicator developed by J. Welles Wilder that measures market volatility by decomposing the entire range of an asset price for that period.
Relative Strength Index (RSI)
Displays the standard 14-period RSI, a momentum oscillator that measures the speed and change of price movements on a scale from 0 to 100.
6. External Market Indicators
QQQ Change
Shows the percentage change in the Invesco QQQ Trust (tracking the Nasdaq-100 Index), useful for understanding broader tech market trends.
UVIX Change
Displays the percentage change in UVIX, a volatility index, providing insight into market fear and potential hedging activity.
BTC-USD
Shows the current Bitcoin price from Coinbase, useful for traders monitoring crypto correlation with equities.
Market Breadth (BRD)
Calculates the percentage difference between ATHI.US and ATLO.US (high vs. low securities), indicating overall market direction and strength.
7. Session Analysis and Volume Direction
Session Detection
The script accurately identifies different market sessions:
Pre-market: 4:00 AM to 9:30 AM
Regular market: 9:30 AM to 4:00 PM
After-hours: 4:00 PM to 8:00 PM
Closed: Outside trading hours
This detection works on any timeframe through careful calculation of current time in seconds.
Buy/Sell Volume Direction
The script analyzes buying and selling pressure by:
Counting up volume when close > open
Counting down volume when close < open
Tracking accumulated volume within the day
Calculating intraday pressure (up volume minus down volume)
Enhanced AVOL Calculation
The improved AVOL calculation works in all timeframes by:
Estimating typical pre-market and after-hours volume percentages
Combining yesterday's after-hours with today's pre-market volume
Calculating this as a percentage of the 21-day average volume
Determining buying/selling pressure by analyzing after-hours and pre-market price changes
Color-coding results: green for buying pressure, red for selling pressure
This calculation is particularly valuable because it works consistently across any timeframe.
Customization Options
Display Settings
The dashboard has two customizable tables: Volume Table and Metrics Table, with positions selectable as bottom_left or bottom_right.
All metrics can be individually toggled on/off:
Pre-market data (PVOL, P$VOL, PRVOL, PCHG%)
Volume data (AVOL, RVOL Day, RVOL 90D, Volume, SEED_YASHALGO_NSE_BREADTH:VOLUME )
Price metrics (ADR%, ATR, RSI, Price Change%)
Market indicators (QQQ, UVIX, Breadth, BTC-USD)
Analysis indicators (Volume Trend, BB Squeeze, Pre-Breakout, Breakout)
These toggle options allow traders to customize the dashboard to show only the metrics they find most valuable for their trading style.
Table and Text Customization
The dashboard's appearance can be customized:
Table background color via tableBgColor
Text color (White or Black) via textColorOption
The indicator uses smart formatting for volume and price values, automatically adding appropriate suffixes (K, M, B) for readability.
MACD Configuration for VTR
The Volume Trend calculation incorporates MACD with customizable parameters:
Fast Length: Controls the period for the fast EMA (default 3)
Slow Length: Controls the period for the slow EMA (default 9)
Signal Length: Controls the period for the signal line EMA (default 5)
MACD Weight: Controls how much influence MACD has on the volume trend score (default 0.3)
These settings allow traders to fine-tune how momentum is factored into the volume trend analysis.
Bollinger Bands and Keltner Channel Settings
The Bollinger Bands and Keltner Channels used for squeeze detection have preset (hidden) parameters:
BB Length: 20 periods
BB Multiplier: 2.0 standard deviations
Keltner Length: 20 periods
Keltner Multiplier: 1.5 ATR
These settings follow standard practice for squeeze detection while maintaining simplicity in the user interface.
Practical Trading Applications
Complete Trading Strategies
1. Squeeze Breakout Strategy
This strategy combines multiple components of the indicator:
Wait for a strong squeeze (SQZ showing ●)
Look for pre-breakout confirmation (PBK showing ● in green or red)
Enter when breakout is confirmed (BK showing ● in same direction)
Use VTR to confirm volume supports the move (VTR ≥ 65 for bullish or ≤ 35 for bearish)
Set profit targets based on ADR (Average Daily Range)
Exit when VTR begins to weaken or changes direction
2. Volume Divergence Strategy
This strategy focuses on the volume trend relative to price:
Identify when price makes a new high but VTR fails to confirm (divergence)
Look for VTR to show weakening trend (● changing to ◯ or ·)
Prepare for potential reversal when SQZ begins to form
Enter counter-trend position when PBK confirms reversal direction
Use external indicators (QQQ, BTC, Breadth) to confirm broader market support
3. Pre-Market Edge Strategy
This strategy leverages pre-market data:
Monitor AVOL for unusual pre-market activity (significantly above 100%)
Check pre-market price change direction (PCHG%)
Enter position at market open if VTR confirms direction
Use SQZ to determine if volatility is likely to expand
Exit based on RVOL declining or price reaching +/- ADR for the day
Market Context Integration
The indicator provides valuable context for trading decisions:
QQQ change shows tech market direction
BTC price shows crypto market correlation
UVIX change indicates volatility expectations
Breadth measurement shows market internals
This context helps traders avoid fighting the broader market and align trades with overall market direction.
Timeframe Optimization
The indicator is designed to work across different timeframes:
For day trading: Focus on AVOL, VTR, PBK/BK, and use shorter momentum periods
For swing trading: Focus on SQZ duration, VTR strength, and broader market indicators
For position trading: Focus on larger VTR trends and use EMA alignment weight
Advanced Analytical Components
Enhanced Volume Trend Score Calculation
The VTR score calculation is sophisticated, with the base score starting at 50 and adjusting for:
Price direction (up/down)
Volume relative to average (high/normal/low)
Volume acceleration/deceleration
Market conditions (bull/bear)
Additional factors are then applied, including:
MACD influence weighted by strength and direction
Volume change rate influence (speed)
Price/volume divergence effects
EMA alignment scores
Volatility adjustments
Breakout strength factors
Price action confirmations
The final score is clamped between 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions.
Anti-False Signal Filters
The indicator employs multiple techniques to reduce false signals:
Requiring significant price range (minimum percentage movement)
Demanding strong volume confirmation (significantly above average)
Checking for consistent direction across multiple indicators
Requiring prior bar consistency (consecutive bars moving in same direction)
Counting consecutive signals to filter out noise
These filters help eliminate noise and focus on high-probability setups.
MACD Enhancement and Integration
The indicator enhances standard MACD analysis:
Calculating MACD relative strength compared to recent history
Normalizing MACD slope relative to volatility
Detecting MACD acceleration for stronger signals
Integrating MACD crossovers with other confirmation factors
EMA Analysis System
The indicator uses a comprehensive EMA analysis system:
Calculating multiple EMAs (5, 10, 21 periods)
Detecting golden cross (10 EMA crosses above 21 EMA)
Detecting death cross (10 EMA crosses below 21 EMA)
Assessing price position relative to EMAs
Measuring EMA separation percentage
Recent Enhancements and Evolution
Version 5.2 includes several improvements:
Enhanced AVOL to show buying/selling direction through color coding
Improved VTR with adaptive analysis based on market conditions
AVOL display now works in all timeframes through sophisticated estimation
Removed animal symbols and streamlined code with bright colors for better visibility
Improved anti-false signal filters throughout the system
Optimizing Indicator Settings
For Different Market Types
Range-Bound Markets:
Lower EMA Alignment Weight (0.2-0.4)
Higher Speed of Change Weight (0.8-1.0)
Focus on SQZ and PBK signals for breakout potential
Trending Markets:
Higher EMA Alignment Weight (0.7-1.0)
Moderate Speed of Change Weight (0.4-0.6)
Focus on VTR strength and BK confirmations
Volatile Markets:
Enable Volatility Filter
Enable Adaptive Volume Analysis
Lower Momentum Period (2-3)
Focus on strong volume confirmation (VTR ≥ 80 or ≤ 20)
For Different Asset Classes
Equities:
Standard settings work well
Pay attention to AVOL for gap potential
Monitor QQQ correlation
Futures:
Consider higher Volume/RVOL weight
Reduce MACD weight slightly
Pay close attention to SQZ duration
Crypto:
Higher volatility thresholds may be needed
Monitor BTC price for correlation
Focus on stronger confirmation signals
Integrated Visual System for Trading Decisions
The colored circle indicators create an intuitive visual system for quick market assessment:
Progression Sequence: SQZ (Squeeze) → PBK (Pre-Breakout) → BK (Breakout)
This sequence often occurs in order, with the squeeze leading to pre-breakout conditions, followed by an actual breakout.
VTR (Volume Trend): Provides context about the volume supporting these movements.
Color Coding: Green for bullish conditions, red for bearish conditions, and orange/gray for neutral or undefined conditions.
ZenAlgo - LevelsThis script combines multiple anchored Volume-Weighted Average Price (VWAP) calculations into a single tool, providing a continuous record of past VWAP levels and highlighting when price has tested them. Typically, VWAP indicators show only the current VWAP for a single anchor period, requiring you to either keep re-anchoring manually or juggle multiple instances of different VWAP tools for each timeframe. By contrast, this script automatically tracks both the ongoing VWAP and previously completed VWAP values, along with real-time detection of “tests” (when price crosses a particular VWAP level). It’s especially valuable for traders who want to see how price has interacted with VWAP over several sessions, weeks, or months—without switching between separate indicators or manually setting anchors.
Below is a comprehensive explanation of each component, why multiple VWAP lines working together can be more informative than a single line, and how to adjust the script for various markets and trading styles:
Primary VWAP vs. Historical VWAP Lines - Standard VWAP indicators typically focus on the current line only. This script also calculates a primary VWAP, but it “locks in” each completed VWAP value when a new time anchor is detected (e.g., new weekly bar, new monthly bar, new session). As a result, you retain an ongoing history of VWAP lines for every completed anchored period. This is more powerful than manually setting up multiple VWAP tools—one for each desired timeframe—because everything is handled in a single script. You avoid chart clutter and the risk of forgetting to reset your manual VWAP at the correct bar.
Why Combine Multiple Anchored VWAP Lines in One Script? - Viewing several anchored VWAP lines together offers synergy . You see not only the current VWAP but also previous ones from different sessions or months, all within the same chart pane. This synergy becomes apparent if multiple historical VWAP lines cluster near the same price level, indicating a potentially significant zone of volume-based support or resistance. Handling this manually would involve repeatedly setting separate VWAP indicators, each reset at specific points, which is time-consuming and prone to error. In this script, the process is automated: as soon as the anchor changes, a completed VWAP line is stored so you can observe how price eventually reacts to it, repeatedly or not at all.
Automated “Test” Detection - Once a historical VWAP line is set, the script tracks when price crosses it in subsequent bars. If the high and low of a bar span that line, the script marks it in red (both the line and its label). It also keeps a counter of how many times each line has been tested. This method goes beyond a simple visual approach by quantifying the retests. Because all these lines are created and managed in one place, you don’t have to manually label the lines or check them one by one.
Advantages Over Manually Setting Multiple VWAPs
You save screen space: Instead of layering several VWAP indicators, each with unique settings, this single script plots them all on one overlay.
Automation: When a new anchor period begins, the script “closes out” the old VWAP and starts a new one. You never need to remember to reset it manually.
Retest Visualization: The script not only draws each line but also changes color and updates the label automatically if a line gets tested. Doing this by hand would be labor-intensive.
Unified Parameters: All settings (e.g., array size, max distance, test count limit) apply uniformly. You can manage them from one place, instead of configuring multiple separate tools.
Extended Insight with Multiple VWAP Lines
Since VWAP reflects the volume-weighted average price for each chosen period, historical lines can show zones where the market had a fair-value consensus in previous intervals. When the script preserves these lines, you see potential support/resistance areas more distinctly. If, for instance, price continually pivots around an old VWAP line, that may reveal a strong volume-based level. With several older VWAP lines on the chart, you gain an immediate sense of where these volume-derived averages have appeared and how price reacted over time. This wider perspective often proves more revealing than a single “current” VWAP line that does not reflect previous anchor sessions.
Handling of Illiquid Markets and Volume Limitations
VWAP is inherently tied to volume data, so its reliability decreases if volume reporting is missing or if the asset trades with very low liquidity. In such cases, a single large trade might momentarily skew the VWAP, resulting in “false” test signals when the high/low range intersects an abnormal price swing. If you suspect the data is incomplete or the market is unusually thin, it’s wise to confirm the validity of these VWAP lines before using them for any decision-making. Additionally, unusual market conditions—like after-hours trading or sudden high-volatility events—may cause VWAP to shift quickly, setting up multiple lines in a short time.
Key User-Configurable Settings
Hide VWAP on Day timeframe and above : Lets you disable the primary VWAP plot on daily or higher timeframes for a cleaner view.
Anchor Period : Select from Session, Week, Month, Quarter, Year, Decade or Century. Controls how frequently the script resets and preserves the VWAP line.
Offset : Moves the current VWAP line by a specified number of bars if you need a shifted perspective.
Max Array Size : Caps how many past VWAP lines the script will remember. Prevents clutter if you’re charting very long histories.
Max Distance : Defines how far back (in bar index units) a line is kept. If a line’s start bar is older than this threshold, it’s removed, keeping the chart uncluttered.
Max Red Labels : Limits the number of tested (red) VWAP lines that appear. If price tests a large number of old lines, only the newest red labels remain once you hit the set limit.
Workflow Overview
As soon as a new anchor period begins (e.g., a new weekly candle if “Week” is chosen), the script ends the current VWAP and stores that final value in its internal arrays.
It creates a dotted line and label representing the completed VWAP, and keeps track of whether it has been tested or not.
Subsequent bars may then cross that line. If a bar’s high/low includes the line’s value, it’s flagged as tested, labeled red, and a test counter increases.
As new anchored periods come, old lines remain visible—unless they fall outside your maxDistance or you exceed the maximum stored line count.
Real-World Benefits
Combining multiple VWAP lines—ranging, for example, from session-based lines for intraday perspectives to monthly or quarterly lines for broader context—provides a layered view of the volume-based fair price. This can help you quickly spot zones where price repeatedly intersects old VWAPs, potentially highlighting where bulls or bears took action historically. Because this script automates the management of all these lines and flags their retests, it removes a great deal of repetitive manual work that would typically accompany multiple, separate VWAP indicators set to different anchors.
Limitations & Practical Use
As with any volume-related tool, the script depends on reliable volume data. Assets trading on smaller venues or during illiquid periods may produce spurious signals. The script does not signal buy or sell decisions; rather, it helps visually map out where volume-weighted averages from previous periods might still be relevant to market behavior. Always combine the insight from these historical VWAP lines with your existing analytical approach or other technical and fundamental tools you use.
Conclusion
This script unifies past and present VWAP lines into one overlay, automatically detecting new anchor resets, storing the final VWAP values, and indicating whenever old lines are retested by price. It offers synergy through the simultaneous display of multiple historical VWAP lines, making it quicker and easier to detect potential support/resistance zones and better reflect changing market volumes over time. You no longer need to manually create, configure, or reset multiple VWAP indicators. Instead, the script handles all aspects of line creation, retest detection, and clutter management, giving you a robust framework to observe how historical VWAP data aligns with current price action.
By understanding the significance of multiple anchored VWAP lines, you can assess market structure from multiple angles in a single view. As always, ensure you confirm the reliability of the volume data for your particular asset and use these lines in conjunction with other analyses to form a well-rounded perspective on current market behavior.
BTIC Range MidpointsThis code analyzes and displays price ranges from 15:15-15:44 ET, the Basis Trade at Index Close session.
It draws horizontal lines showing:
The high of each session
The low of each session
The midpoint (50%) of each session
Connections between different session ranges (50% points between highs and lows)
Key features include:
Works only on 15-minute timeframes or lower
Stores up to 20 days of historical sessions (configurable)
Filters out ranges too far from current price
Color-codes different session ranges
Provides customizable line styles and colors
Labels each range with identifiers
The indicator essentially helps traders identify important price levels from BTIC sessions, which could serve as potential support/resistance areas for future price action.
Timezone Highlight v1.0Features Explained:
Customizable Time Settings:
Easily adjust the opening and closing times for each session to fit your local time zone or trading preferences.
Color-Coded Sessions:
New York : Blue
London : Yellow
Tokyo : Red
Sydney : Green
You can modify the colors or transparency in the script.
Dynamic Highlighting:
Automatically highlights the active trading session based on the current time.
This Pine Script is user-friendly and designed to provide immediate visual insights into global market activity. Let me know if you need further enhancements!
Its my first script so please don't be too strict!
Momentum Divergence SignalDescription:
The Momentum Divergence Signal is a powerful tool that identifies potential trend reversals by analyzing the interaction between price movements and main oscillators. It highlights moments when price action diverges from the following, which can be a key signal of a trend shift. The most important aspect of this indicator is its ability to detect bullish and bearish divergences.
Coming to the critical part, it is highly recommended to pair this indicator with another trend confirmation tool for improved decision-making, as it works on catching both trend continuation and reversal signals, but it is always favored to match use it as a trend continuation entry provider.
Core Functionality:
Session-Based Signals:
The indicator limits signals to specific market sessions: the Asian, London, and US sessions, optimizing trade opportunities during active trading hours.
Cooldown Mechanism:
To prevent signal spamming, a cooldown period of at least 8 bars is required between each signal, ensuring that new signals are spaced out and not over-generating.
Divergence with Trend Confirmation:
While the RSI divergence alone can highlight potential trend shifts, this script is best paired with other trend-following indicators to filter out false signals. This ensures that the divergence signal is part of a broader, more reliable trend-following strategy.
Visual Components:
Buy and Sell Arrows: Visual arrows on the chart where the divergence occurs, accompanied by "Buy" and "Sell" labels in white to clearly indicate the signal points.
Advanced Concepts:
Divergence as a Reversal Signal: The key strength of this indicator lies in detecting divergences that can indicate a trend reversal. Divergences often precede significant changes in price direction, offering potential opportunities for traders to enter or exit positions before the trend fully shifts.
Pairing with Trend Confirmation Indicators: Since divergence signals can sometimes produce false positives, the most effective use of this tool comes when paired with a trend-following indicator (such as moving averages or price action analysis) to validate the reversal signals.
Applications:
Trend Reversal Detection: Monitor for divergences between price action and RSI to identify potential trend reversals. These signals are most useful when combined with trend confirmation tools to ensure the validity of the reversal.
Strategic Use in Trend-Following Systems: This indicator is best employed within a trend-following strategy where it serves as an additional confirmation signal for market shifts. While it can identify potential reversal points, its strength lies in its ability to identify shifts in momentum within an ongoing trend.
Real-Time Visual Feedback: The "Buy" and "Sell" signals, that are displayed directly on the chart, providing real-time context for traders.
Disclaimer: This indicator is designed for informational purposes only and should not be considered financial advice. Traders should combine it with other market analysis tools and perform their own research before making trading decisions.
ICT Opening Range GapOpening Range Gap
The Opening Range Gap, also known as the Regular Trading Hours (RTH) Gap, is the distance between the first opening tick of a session and the previous session's close, when looking at a chart's Regular Trading Hours (not to be confused with Electronic Trading Hours). This gap is an important element for Futures Market traders that follow the works of The Inner Circle Trader (ICT). To be more specific, the Opening Range Gap occurs between 4:15pm and 9:30am of the next day.
The Opening Range Gap can be viewed easily when switching the session type to "Regular trading hours".
The image above shows an example of an RTH Gap for Wednesday, June 12, 2024 in CME_MINI:ES1!
How To Use Opening Range Gap
The Opening Range Gap can be used like any other form of a gap by extending it into future price action and looking for it to be filled on the same day or the upcoming days.
Looking for 50% of the gap to be filled as an initial target is one of the methodologies taught by ICT. Additionally, the high and low of the gap (as well as the midpoint) can be used as points of dynamic support & resistance, even if the gap is already filled. Therefore, these gaps do not "expire", and they can be used as key price levels extended through to the end of the week.
Disclaimer
This indicator is mainly intended to work for Futures markets, and specifically the following Index Futures markets: E-mini S&P 500 Futures, E-mini NASDAQ-100 Futures, E-mini DOW Futures.
Given that, the indicator still supports various other markets/assets out-of-the-box, such as other types of Futures Markets, Stocks, Options, and more. The main difference will be that other markets may have RTH Gaps forming at different times, rather than the 4:15pm-9:30am gap that occurs in the Index Futures (Regular trading hours).
Indicator Purpose
While RTH Gaps can be labeled by hand, this indicator allows you to quickly plot multiple RTH Gaps and get a quick glimpse at potential gaps that you may have missed, which could end up being useful in your analysis.
This indicator is 100% custom-built, not using code from any other existing indicators that may plot Opening Range Gaps. The main purpose of this indicator was to overcome many shortcomings from other existing indicators, most notably the problem of displaying RTH Gaps while using ETH as the chart session.
Therefore, this indicator has many UNIQUE features, such as:
Ability to maintain accuracy of the closing/opening prices even when changing chart settings (e.g., toggling ETH/RTH sessions, toggling BACK-ADJUSTMENT on futures contracts, toggling SETTLEMENT prices, etc.).
Draw up to 25 previous Opening Range Gaps, even on ultra-low timeframes like the 1-minute or 1-second chart.
Automatically or manually choose which Opening Range Gaps to hide/show on the chart.
Highly customizable, including a different color scheme to easily distinguish between the Current and Previous RTH Gaps.
Modified price values to correctly display prices that use a format like 109'32 (e.g., Bond Futures or Wheat Futures).
Helpful tooltips to provide more detailed information about the RTH Gaps or about the current Input Settings.
Error Messages
There are some conditions which can cause the script to fail and display an error message (by clicking the red exclamation mark next to the indicator.)
Error messages:
Use a Standard Chart Type : this will occur when using a non-standard chart such as Heikin Ashi, Renko, Point & Figure, etc.
Use a Daily or Lower Timeframe : this error will appear when using a higher timeframe chart like weekly or monthly, because it can clutter the chart since RTH Gaps can form every day.
RTH Gap was not detected : this means that no RTH gap was found, which will occur on markets that don't have the option to toggle between ETH and RTH sessions (e.g., Forex or Crypto).
Exceeded the maximum lookback for Bar Replay mode : when using bar replay mode; this can depend on the amount of historical bars available in different account subscription types.
Unable to Activate Bar Replay mode : if the indicator could not be used in Bar Replay mode.
Restart Bar Replay : if the indicator works in Bar Replay but it detected an error that would cause RTH Gaps to be plotted incorrectly.
This is an example of what a script error would look like.
Indicator Settings
Most settings are self-explanatory or have a tooltip with information on what the setting does, but this section will only briefly cover the available settings.
Extend to End of Day : This setting is enabled by default. It will extend each RTH Gap only up to the end of its day (specifically, to the RTH close of the day). The option can be toggled OFF to automatically extend all RTH Gaps to the right-most candle on the chart.
Previous RTH Gaps : Between 1 and 25 previous RTH Gaps can be displayed. The checkbox can be toggled to quickly hide all previous RTH Gaps (but the same effect would be reached by setting the value to 0).
Hide Current RTH Gap : The Current RTH Gap (most recent one), can be optionally hidden from being plotted.
Beginning Anchor Point : Choose the beginning anchor point for all RTH Gaps. The default is "RTH Close", which means that each gap will be drawn on the chart starting from their previous session's RTH close @ 4:15pm. But it will be a more transparent version of the actual gap; this ghost-like image will extend from 4:15pm all the way up to 9:30am where the gap will then be drawn normally from 9:30am onwards. The other option for this setting is "RTH Open" which means that the gap will be drawn starting from the actual 9:30am opening.
Current RTH Gap Style
These settings are used to customize the visual style of the most recent RTH Gap (also known as the "Current" RTH Gap). Note: the exact same set of settings are available for the Previous RTH Gaps. The text label next to each gap can be optionally hidden to clean the chart a little.
Price Table
These are settings to customize the appearance of the Price Table on the right, including the ability to hide it completely. Note: to actually use the color configurations, you must select "Custom Style" in one of the dropdowns, otherwise it will use "Default Style" which means that the Price Table is automatically styled based on the colors chosen in the Current RTH Gap Style and Previous RTH Gap Style settings.
Overlap Handling
One of 7 available overlap handling options can be used to filter which RTH Gaps are plotted on the chart. By default, the "None" option will be selected, meaning that all valid RTH Gaps are plotted on the chart.
Formatting
Date Format : select the format of the date that is shown next to each RTH Gaps.
Timezone : choose the timezone for the RTH Gap closing/opening date-times that are displayed (only in tooltips when you hover over an RTH Gap label).
RTH Gap Label : choose the details to display next to each gap (e.g., date, or gap number, or both).
Price Format : only two options: Auto/Decimal. "Auto" uses custom processing to allow displaying values such as 109'32 for Bond futures.
Tooltips
The indicator provides additional details about an RTH Gap when you hover over a row in the Price Table.
Note: the same information can be found by hovering over the Text Label that is to the right of each RTH Gap (even when the Text Label is disabled via the Settings).
Overlap Handling
The tooltip next to "Select a Strategy" in the options will provide details on each overlap handling strategy. Additionally, when a strategy is selected, a new row in the Price Table will appear; hovering over that will show details about the currently selected strategy, as well as any suggestions in case the inputs were invalid. When a strategy hides an RTH Gap, the number in the Price Table will be replaced with an "Eye" icon, indicating that it is not currently plotted on the chart.
Available strategies are:
Option 1 (Gradients) : select the percentage opacity to shade RTH Gaps in. The more recent RTH Gaps will be closer to the maximum opacity defined, while the older RTH Gaps will appear more transparent, closer to the minimum opacity defined. Note: only affects previous RTH Gaps, not the current RTH Gap.
Option 2 (Day Extension) : select the number of days to extend each RTH Gap up to. Note: this will override the "Extend to End of Day" setting, regardless whether it is toggled ON or OFF.
Option 3 (Nested Gaps) : hides nested gaps, i.e., RTH Gaps that are enclosed within another RTH Gap. Note: this option is only available when the "Extend to End of Day" setting is disabled .
Option 4 (Intersecting Gaps) : hides intersecting/overlapping gaps, i.e., RTH Gaps that overlap one another (this may also include, but is not limited to, nested gaps). The drop-down next to this option allows choosing the priority of which RTH Gaps to hide first. Note: this option is only available when the "Extend to End of Day" setting is disabled .
Option 5 (Gap Width) : the chart will only show RTH Gaps that have a width/size between the defined parameters.
Option 6 (Close Proximity) : the chart will only show the RTH Gaps that are within a certain range from the market price. This can be useful when plotting multiple RTH Gaps while using auto-scaling on the chart. By only showing nearby RTH Gaps, it will prevent the auto-scaling from having to compress the candles to fit the far-away RTH Gaps onto the screen.
Option 7 (CSV) : this option is used if none of the others suit you well; it allows specifically choosing which RTH Gaps to hide or show on the chart.
This is an example that chooses the Overlap Handling Strategy Option 6. Note that in this example, the tooltip in the price table shows a warning that the Input Number should be increased to plot some RTH Gaps on the chart.
Tips
Chart settings can be toggled to "Scale price chart only" to prevent the auto-scaling of TradingView from compressing the chart if there are RTH Gaps that are far away from the current market action.
If you change a lot of indicator settings such as RTH Gap color schemes, you can save the settings as the Default to prevent your settings from resetting the next time you use the indicator.
Musashi_BattleTimer-Musashi_Battle Timer-
Four financial sessions presented in a compact way that suits my trading style.
The indicator will do the following:
- Plot Background color separating sessions:
- Highlight Gray since Tokyo open to London open, then a gap.
- Highlight Red from London open to NY open, then a gap.
- Highlight Red from NY open to London Close, then a gap
- Highlight Gray from London close to Sidney open
- Sidney open to Tokio open NO highlight.
- Plot dotted limits for the highest and lowest price of the day.
- Plot a range for the Asian session (Sydney + Tokyo).
- Plot a few day's ADR (Average Daily Range) and extend the current one.
Have a good day.
AxiaAxia - Statistical Breakout Strategy Partner
Overview
Axia is a premium technical indicator designed to enhance breakout trading strategies by providing high-probability range breakout targets and comprehensive session analysis.
This indicator transforms historical price action into actionable statistical insights, helping traders identify optimal entry and exit points for range breakout scenarios.
Key Features
📊 Dual Session Analysis
Reference Session : Analyze key price levels from a defined reference period (default: 0200-0500 EST)
Trade Session : Monitor breakout opportunities during active trading hours (default: 0500-0900 EST)
Customizable session times with precision control (5-60 minute sensitivity)
🎯 High-Probability Breakout Targets
Dynamic Target Calculation : Automatically calculates breakout targets based on historical success rates
Confidence Levels : Configurable target confidence levels (default: 75%) based on statistical analysis
Visual Target Lines : Clear visual representation of high-probability target zones above and below reference ranges
📈 Comprehensive Statistical Analysis
Breakout Probability : Shows percentage chance of breaking above/below reference highs and lows
Reversion Statistics : Tracks probability of price returning to key levels (EQ, Open)
Success Rate Tracking : Monitors historical performance of breakout attempts
Sample Size Validation : Ensures statistical significance with minimum session requirements
🔍 Advanced Multi-Criteria Filtering System
Refine your analysis with powerful filtering options to isolate specific market conditions:
Day of Week Filter : Target specific trading days (Monday-Sunday) for pattern analysis
Reference Session Open Position : Filter by where the reference session opens within its own range (lower/middle/upper third)
Reference Session Direction : Filter by bullish or bearish reference session closes
Trade Session Entry Filter : Analyze based on where the trade session opens relative to the reference range
Combined Filters : Use multiple filters simultaneously for highly specific pattern isolation
Real-Time Filter Validation : Visual confirmation shows when current conditions match your filter criteria
📊 Real-Time Performance Tracking
Live Updates : Labels update in real-time as levels are hit during trade sessions
Success Indicators : Visual confirmation (✓) when targets are reached
Probability Adjustments : Dynamic probability updates based on intraday price action
🎨 Customizable Visual Design
Color Schemes : Fully customizable colors for ranges, lines, and labels
Line Styles : Adjustable line widths and styles
Label Positioning : Multiple table positions for statistics display
Clean Interface : Organized input panels for easy configuration
How It Works
Data Collection : The indicator analyzes historical price action across your defined reference and trade sessions
Pattern Recognition : Identifies recurring breakout patterns and their success rates
Statistical Analysis : Calculates probabilities based on historical performance with proper statistical validation
Target Generation : Creates high-probability target levels using percentile analysis of historical overshoots
Real-Time Updates : Provides live feedback as price action unfolds during trade sessions
Trading Applications
Breakout Strategy Enhancement
Identify high-probability breakout targets before they occur
Gauge the likelihood of successful range breaks
Set realistic profit targets based on historical data
Session-Based Trading
Capitalize on specific session behaviors and patterns
Focus on time periods with historically higher success rates
Align trading strategy with market session characteristics
Risk Management
Understand the probability of price returning to key levels after breakouts
Make informed decisions about stop-loss placement
Assess trade risk/reward ratios with statistical backing
Technical Specifications
Extensive Data Collection : Analyzes 800+ historical sessions even on lower timeframes for robust statistical analysis
Session Precision : 5-60 minute intervals for flexible time frame analysis
Statistical Validation : Minimum 30 sessions recommended for reliable statistics (indicator warns when below threshold)
Real-Time Updates : Live probability calculations and target tracking
Multi-Timeframe Support : Optimized for timeframes ≤60 minutes with enhanced session detection
Replay Mode : Special mode for backtesting with up to 450 sessions and 1-minute precision
Best Practices
Allow Sufficient Data : Ensure at least 30 historical sessions for statistical reliability
Customize Sessions : Adjust reference and trade sessions to match your market characteristics
Use Filters Wisely : Apply filters to focus on your preferred trading conditions
Monitor Sample Size : Pay attention to the total sessions count for statistical significance
Combine with Other Analysis : Use alongside your existing technical analysis for confirmation
Important Notes & Disclaimers
Educational Purpose : This indicator is designed for educational and analytical purposes only. It provides statistical analysis of historical price patterns but does not constitute investment advice.
Risk Warning :
Trading involves substantial risk of loss and is not suitable for all investors
Past performance does not guarantee future results
No trading system or methodology has ever been developed that can guarantee profits or ensure freedom from losses
Always use proper risk management and never risk more than you can afford to lose
Statistical Limitations :
Results are based on historical data and may not reflect future market conditions
Ensure sufficient sample size (30+ sessions minimum) for statistical reliability
Market conditions, volatility, and fundamental factors can affect indicator performance
The indicator works best with sufficient historical data for statistical accuracy
Usage Guidelines :
This tool should be used in conjunction with other forms of analysis
Consider current market conditions and fundamental factors alongside technical analysis
Always validate signals with additional technical indicators and market context
Recommended for experienced traders familiar with statistical analysis and risk management
No Guarantee : The indicator statistical probabilities are based on historical patterns and do not guarantee future price movements or trading success.
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Axia transforms complex statistical analysis into clear, actionable trading insights, making it an invaluable tool for traders seeking to improve their breakout strategy performance through data-driven decision making.
LANZ Strategy 2.0🔷 LANZ Strategy 2.0 — London Breakout Confirmation with Structural Swing Protection
LANZ Strategy 2.0 is a structured trading system that leverages the last confirmed market direction before the London session to define directional bias and manage trades based on key structural swing levels. It is tailored for intraday traders looking to capitalize on early London volatility with built-in risk management and visual clarity.
🧠 Core Components:
Directional Confirmation (Pre-London Bias): Validates the last breakout or structural move from the 15-minute timeframe before 02:15 a.m. New York time (start of the London session), establishing the expected market direction.
Time-Based Execution: Executes potential entries strictly at 02:15 a.m. NY time, using market structure to support Long or Short bias.
Dynamic Swing-Based SL System: Allows user to select between three SL protection models: First Swing (most recent structural point) Second Swing (prior level) Total Coverage (includes both swings + extra buffer) This supports flexibility based on trader profile or market conditions.
Visual Risk Mapping: All SL and TP levels are clearly plotted.
End-of-Session Management: Positions are automatically evaluated for closure at 11:45 a.m. NY time. SL, TP, or manual close outcomes are labeled accordingly.
📊 Visual Features:
Labels for 1st and 2nd swing levels upon entry.
Dynamic lines projecting SL/TP levels toward the end of the session.
Session background coloring for Pre-London, Execution, and NY sessions.
Real-time percentage outcome labels (+2.00%, -1.00%, or net % at session end).
Automatic deletion of previous visuals on new entries for clean charting.
⚙️ How It Works:
Detects last structural breakout on the 15m timeframe before 02:15 a.m. NY.
On the 02:15 a.m. candle, executes a Long or Short logic entry.
Plots corresponding SL and TP based on selected swing model.
Monitors price action: If TP or SL is hit, labels it accordingly. If no exit is hit, trade closes manually at 11:45 a.m. NY with net result shown.
Optional logic to reverse entries if market structure breaks before execution.
🔔 Alerts:
Daily execution alert at 02:15 a.m. NY (prompting manual review or action).
Optional alert logic can be extended for SL/TP hits or structure breaks.
📝 Notes:
Designed for semi-automated or discretionary intraday trading.
Best used on Forex pairs or indices with strong London session behavior.
Adjustable parameters include session hours, swing SL type, and buffer settings.
Credits:
Developed by LANZ, this script combines time-based execution with dynamic structure protection, offering a disciplined framework for participating in the London session breakout with clear visuals and risk logic.
Bull Bear Pivot by RawstocksThe "Bull Bear Pivot" indicator is a custom Pine Script (v5) tool designed for TradingView to assist traders in identifying key price levels and pivot points on intraday charts (up to 1-hour timeframes). It combines time-based open price markers, pivot high/low detection, and candlestick visualization to provide a comprehensive view of potential support, resistance, and trend reversal levels. Below is a detailed description of the indicator’s functionality, features, and intended use.
Indicator Overview:
The "Bull Bear Pivot" indicator is tailored for intraday trading, focusing on specific times of the day to mark significant price levels (open prices) and detect pivot points. It plots horizontal lines at the open prices of user-defined sessions, identifies pivot highs and lows on the current chart timeframe, and overlays custom candlesticks to highlight price action. The indicator is designed to work on timeframes of 1 hour or less (e.g., 1-minute, 3-minute, 5-minute, 15-minute, 30-minute, 60-minute) and includes a warning mechanism for invalid timeframes.
Key Features:
Time-Based Open Price Markers:
The indicator allows users to define up to five time-based sessions (e.g., 4:00 AM, 8:30 AM, 9:30 AM, 10:00 AM, and a custom time) to capture the open price at the start of each session.
For each session, it plots a horizontal line at the 1-minute open price, extending from the session start to the market close at 4:00 PM EST.
Each line is accompanied by a label positioned 5 bars to the right of the market close (4:00 PM EST), with the text right-aligned and vertically centered on the line.
Users can enable/disable each marker, customize the session time, label text, line color, and text color via the indicator’s settings.
Pivot Highs and Lows:
The indicator calculates pivot highs and lows on the current chart timeframe using the ta.pivothigh and ta.pivotlow functions.
Pivot highs are marked with green triangles above the bars, and pivot lows are marked with red triangles below the bars.
The pivot period (lookback/lookforward) is user-configurable, allowing flexibility in detecting short-term or longer-term reversals.
Custom Candlesticks:
The indicator overlays custom candlesticks on the chart, colored green for bullish candles (close > open) and red for bearish candles (close < open).
This feature helps visualize price action alongside the open price markers and pivot points.
Timeframe Restriction:
The indicator is designed to work on timeframes of 1 hour or less. If the chart timeframe exceeds 1 hour (e.g., 4-hour, daily), a warning label ("Timeframe > 1H\nIndicator Disabled") is displayed, and no elements are plotted.
Customizable Appearance:
Users can customize the appearance of the open price marker lines, including the line style (solid, dashed, dotted) and line width.
Labels for the open price markers have no background (transparent) and use customizable text colors.
Overnight vs Intra-day Performance█ STRATEGY OVERVIEW
The "Overnight vs Intra-day Performance" indicator quantifies price behaviour differences between trading hours and overnight periods. It calculates cumulative returns, compound growth rates, and visualizes performance components across user-defined time windows. Designed for analytical use, it helps identify whether returns are primarily generated during market hours or overnight sessions.
█ USAGE
Use this indicator on Stocks and ETFs to visualise and compare intra-day vs overnight performance
█ KEY FEATURES
Return Segmentation : Separates total returns into overnight (close-to-open) and intraday (open-to-close) components
Growth Tracking : Shows simple cumulative returns and compound annual growth rates (CAGR)
█ VISUALIZATION SYSTEM
1. Time-Series
Overnight Returns (Red)
Intraday Returns (Blue)
Total Returns (White)
2. Summary Table
Displays CAGR
3. Price Chart Labels
Floating annotations showing absolute returns and CAGR
Color-coded to match plot series
█ PURPOSE
Quantify market behaviour disparities between active trading sessions and overnight positioning
Provide institutional-grade attribution analysis for returns generation
Enable tactical adjustment of trading schedules based on historical performance patterns
Serve as foundational research for session-specific trading strategies
█ IDEAL USERS
1. Portfolio Managers
Analyse overnight risk exposure across holdings
Optimize execution timing based on return distributions
2. Quantitative Researchers
Study market microstructure through time-segmented returns
Develop alpha models leveraging session-specific anomalies
3. Market Microstructure Analysts
Identify liquidity patterns in overnight vs daytime sessions
Research ETF premium/discount mechanics
4. Day Traders
Align trading hours with highest probability return windows
Avoid overnight gaps through informed position sizing
Dynamic Customizable 50% Line & Daily High/Low + True Day OpenA Unique Indicator for Precise Market-Level Analysis
This indicator is a fully integrated solution that automates complex market-level calculations and visualizations, offering traders a tool that goes beyond the functionality of existing open-source alternatives. By seamlessly combining several trading concepts into a single script, it delivers efficiency, accuracy, and customization that cater to both novice and professional traders.
Key Features: A Breakdown of What Makes It Unique
1. Adaptive Daily Highs and Lows
Automatically detects and plots daily high and low levels based on the selected time frame, dynamically updating in real time.
Features session-based adjustments, allowing traders to focus on levels that matter for specific trading sessions (e.g., London, New York).
Fully customizable styling, visibility, and alerts tailored to each trader’s preferences.
How It Works:
The indicator calculates daily high and low levels directly from price data, integrating session-specific time offsets to account for global trading hours. These levels provide traders with clear visual markers for key liquidity zones.
2. Automated ICT 50% Range Line
A pioneering implementation of ICT’s mid-range concept, this feature dynamically calculates and displays the midpoint of the daily range.
Offers traders a visual guide to identify premium and discount zones, aiding in determining market bias and potential trade setups.
How It Works:
The script calculates the range between the day’s high and low, dividing it by two to generate the midline. This line updates in real-time, ensuring that traders always see the most current premium and discount levels as price action evolves.
3. Dynamic Market Open Levels
Plots session opens (e.g., Asia, London, New York) and the True Day Open to provide actionable reference points for intra-day trading strategies.
Enhances precision in identifying liquidity shifts and aligning trades with institutional price movements.
How It Works:
The indicator uses predefined session times to calculate and display the opening levels for key trading sessions. It dynamically adjusts for time zones, ensuring accuracy regardless of the trader’s location.
4. Custom Watermark for Enhanced Visualization
Includes an optional watermark feature that allows users to display custom text on their charts.
Ideal for personalization, branding, or highlighting session notes without disrupting the clarity of the chart.
Why This Indicator Stands Out
First-to-Market Automation:
While the ICT 50% range line is a widely recognized concept, this is the first script to automate its calculation, combining it with other pivotal trading levels in a single tool.
All-in-One Functionality:
Unlike open-source alternatives that focus on individual features, this script integrates daily highs/lows, mid-range levels, session opens, and customizable watermarks into one cohesive system. The consolidation reduces the need for multiple indicators and ensures a clean, efficient chart setup.
Dynamic Customization:
Every feature can be adjusted to align with a trader’s strategy, time zone, or aesthetic preferences. This level of adaptability is unmatched in existing tools.
Proprietary Logic:
The indicator’s underlying calculations are built from scratch, leveraging advanced programming techniques to ensure accuracy and reliability. These proprietary methods differentiate it from similar open-source scripts.
How to Use This Indicator
Apply the Indicator:
Add it to your TradingView chart from the library.
Configure Settings:
Use the intuitive settings panel to adjust plotted levels, colors, styles, and visibility. Tailor the indicator to your trading strategy.
Incorporate into Analysis:
Combine the plotted levels with your preferred trading approach to identify liquidity zones, establish market bias, and pinpoint potential reversals or entries.
Stay Focused:
With all key levels automated and updated in real time, traders can focus on execution rather than manual plotting.
Originality and Justification for Closed Source
This script is closed-source due to its unique combination of features and proprietary logic that automates complex trading concepts like the ICT 50% range line and session-specific levels. Open-source alternatives lack this level of integration and customization, making this indicator a valuable and original contribution to the TradingView ecosystem.
What Sets It Apart from Open-Source Scripts?
Unlike open-source tools, this indicator doesn’t just replicate individual features—it enhances and integrates them into a seamless, all-in-one solution that offers traders a more efficient and effective way to analyze the market.
Candle 1 2 3 on XAUUSD (by Veronica)Description
Discover the Candle 1 2 3 Strategy, a simple yet effective trading method tailored exclusively for XAUUSD on the 15-minute timeframe. Designed by Veronica, this strategy focuses on identifying key reversal and continuation patterns during the London and New York sessions, making it ideal for traders who prioritise high-probability entries during these active market hours.
Key Features:
1. Session-Specific Trading:
The strategy operates strictly during London (03:00–06:00 UTC) and New York (08:30–12:30 UTC) sessions, where XAUUSD tends to show higher volatility and clearer price movements.
Pattern Criteria:
- Works best if the first candle is NOT a pin bar or a doji.
- Third candle should either:
a. Be a marubozu (large body with minimal wicks).
a. Have a significant body with wicks, ensuring the close of the third candle is above Candle 2 (for Buy) or below Candle 2 (for Sell).
Callout Labels and Alerts:
Automatic Buy and Sell labels are displayed on the chart during qualifying sessions, ensuring clarity for decision-making.
Integrated alerts notify you of trading opportunities in real-time.
Risk Management:
Built-in Risk Calculator to estimate lot sizes based on your account size, risk percentage, and stop-loss levels.
Customizable Table:
Displays your calculated lot size for various stop-loss pip values, making risk management seamless and efficient.
How to Use:
1. Apply the indicator to XAUUSD (M15).
2. Focus on setups appearing within the London and New York sessions only.
3. Ensure the first candle is neither a pin bar nor a doji.
4. Validate the third candle's body placement:
For a Buy, the third candle’s close must be above the second candle.
For a Sell, the third candle’s close must be below the second candle.
5. Use the generated alerts to streamline your entry process.
Notes:
This strategy is meant to complement your existing knowledge of market structure and price action.
Always backtest thoroughly and adjust parameters to fit your personal trading style and risk tolerance.
Credit:
This strategy is the intellectual property of Veronica, developed specifically for XAUUSD (M15) traders seeking precision entries during high-volume sessions.
First 1-Minute Candle High/Low After Specific TimeDescription:
This indicator captures and marks the high and low of the first 1-minute candle after a specified time (default: 9:30 AM) and tracks the highs and lows of the first five candles. The levels marked by these initial candles are often critical in determining early session support and resistance, providing a visual guide for traders monitoring price action in the opening minutes of a trading session.
Key Features and Usage
1-Minute Candle High/Low: The indicator captures the high and low of the first 1-minute candle after the specified session start time. This level is marked with horizontal lines and labels, providing traders with an immediate reference for early-session price extremes.
5-Candle Range High/Low: After the first five candles, the indicator also highlights the highest and lowest levels within this range, offering additional support/resistance lines to aid in understanding early price movements.
Custom Labels and Dynamic Line Extension:
Labels update dynamically and display whether the 1-minute high/low coincides with the 5-minute range high/low, combining these labels if they match.
Horizontal lines extend to the current bar to remain visible throughout the session for consistent reference.
Customization Options
Colors and Label Text: Users can adjust colors for the 1-minute and 5-minute high/low lines and the label text for optimal readability.
Label Position Offset: Labels are placed slightly above or below their respective lines to avoid overlap with price action, maintaining clarity on the chart.
Intended Use
This indicator is especially useful for intraday traders focusing on opening range breakout strategies, scalping, or short-term trend analysis. It is intended for use on intraday charts (such as 1-minute or 5-minute intervals) and provides straightforward levels to assess early market structure.
Technical Details
Customization of Start Time: Users can change the default start time to any desired session opening time, adapting it to various markets or trading sessions.
Dynamic Line and Label Updates: Both lines and labels dynamically extend with the chart, while labels remain easy to read as they shift based on recent price action.
This script is designed to be simple yet powerful, offering key insights into session open levels without relying on predictive or lookahead features. It is useful for real-time analysis and adds value by helping traders identify critical levels in the market's early stages.
