DRAW ONLY ONCE No repetitionPresent a way to solve a problem of repetitive drawing in case you want to visualize and elminate potential signal error before backtesting.
Tìm kiếm tập lệnh với "backtest"
[NLX-L2] Hurst Exponent Signal Filter- Hurst Exponent Signal Filter -
The Hurst Exponent Signal Filter is meant to be used with an external signal source, this can be any indicator with a signal plot output (-1 Sell / 1 Buy)
It filters out a lot of noisy signals and improves the performance of many indicators.
- Example: How to Use -
1. Add a trend Indicator like Trend Index MTF to your chart
2. Add an indicator with a signal plot like Fishers Stochastic Center of Gravity to your Chart and select the Trend Index MTF with Type L1 in the Settings as Signal Source
3. Add this Hurst Signal Filter to your Chart and select the Fishers Stochastic Center of Gravity with Type L2 in the Settings as Signal Source
4. Add the Backtest Module to your Chart and select the Hurst Signal Filter with Type L2 as Source
- Alerts for Automated Trading -
See my signature below. Contact me for the Alert module.
QuantNomad - Heikin-Ashi PSAR AlertsUsing this script you can create alerts for my Heikin-Ashi PSAR Strategy:
When creating alerts use "Once Per Bar Close" in parameters.
####################
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as good as in historical backtesting.
This post and the script don’t provide any financial advice.
Breakout Trend FollowerThis is a Study mirroring the Breakout Trend Follower Strategy I made. I use this one during live trading and the other for backtesting. It will also give alerts when buy and sell signals are hit.
CBG Swing HighLow MAThis indicator will show the swing high and lows for the number of bars back. It's very easy to use and shows good support and resistance levels.
I then took it a step further and added a moving average with all the standard types in my indicators:
SMA
EMA
Weighted
Hull
Symmetrical
Volume Weighted
Wilder
Linear Regression
I then added Bollinger Bands to show the standard deviation from the midline.
Finally, I added a simple bar coloring scheme: green if above the upper BB, Red if below and orange if in the middle.
I am just testing this out so please use with caution. If anyone in the community wants to run some backtests, that would be great and we would all appreciate it.
Of course you can keep it all simple and turn off all the moving averages and bollinger bands.
Enjoy! :-)
Bar Balance [LucF]Bar Balance extracts the number of up, down and neutral intrabars contained in each chart bar, revealing information on the strength of price movement. It can display stacked columns representing raw up/down/neutral intrabar counts, or an up/down balance line which can be calculated and visualized in many different ways.
WARNING: This is an analysis tool that works on historical bars only. It does not show any realtime information, and thus cannot be used to issue alerts or for automated trading. When realtime bars elapse, the indicator will require a browser refresh, a change to its Inputs or to the chart's timeframe/symbol to recalculate and display information on those elapsed bars. Once a trader understands this, the indicator can be used advantageously to make discretionary trading decisions.
Traders used to work with my Delta Volume Columns Pro will feel right at home in this indicator's Inputs . It has lots of options, allowing it to be used in many different ways. If you value the bar balance information this indicator mines, I hope you will find the time required to master the use of Bar Balance well worth the investment.
█ OVERVIEW
The indicator has two modes: Columns and Line .
Columns
• In Columns mode you can display stacked Up/Down/Neutral columns.
• The "Up" section represents the count of intrabars where `close > open`, "Down" where `close < open` and "Neutral" where `close = open`.
• The Up section always appears above the centerline, the Down section below. The Neutral section overlaps the centerline, split halfway above and below it.
The Up and Down sections start where the Neutral section ends, when there is one.
• The Up and Down sections can be colored independently using 7 different methods.
• The signal line plotted in Line mode can also be displayed in Columns mode.
Line
• Displays a single balance line using a zero centerline.
• A variable number of independent methods can be used to calculate the line (6), determine its color (5), and color the fill (5).
You can thus evaluate the state of 3 different components with this single line.
• A "Divergence Levels" feature will use the line to automatically draw expanding levels on divergence events.
Features available in both modes
• The color of all components can be selected from 15 base colors, with 16 gradient levels used for each base color in the indicator's gradients.
• A zero line can show a 6-state aggregate value of the three main volume balance modes.
• The background can be colored using any of 5 different methods.
• Chart bars can be colored using 5 different methods.
• Divergence and large neutral count ratio events can be shown in either Columns or Line mode, calculated in one of 4 different methods.
• Markers on 6 different conditions can be displayed.
█ CONCEPTS
Intrabar inspection
Intrabar inspection means the indicator looks at lower timeframe bars ( intrabars ) making up a given chart bar to gather its information. If your chart is on a 1-hour timeframe and the intrabar resolution determined by the indicator is 5 minutes, then 12 intrabars will be analyzed for each chart bar and the count of up/down/neutral intrabars among those will be tallied.
Bar Balances and calculation methods
The indicator uses a variety of methods to evaluate bar balance and to derive other calculations from them:
1. Balance on Bar : Uses the relative importance of instant Up and Down counts on the bar.
2. Balance Averages : Uses the difference between the EMAs of Up and Down counts.
3. Balance Momentum : Starts by calculating, separately for both Up and Down counts, the difference between the same EMAs used in Balance Averages and an SMA of double the period used for the EMAs. These differences are then aggregated and finally, a bounded momentum of that aggregate is calculated using RSI.
4. Markers Bias : It sums the bull/bear occurrences of the four previous markers over a user-defined period (the default is 14).
5. Combined Balances : This is the aggregate of the instant bull/bear bias of the three main bar balances.
6. Dual Up/Down Averages : This is a display mode showing the EMA calculated for each of the Up and Down counts.
Interpretation of neutral intrabars
What do neutral intrabars mean? When price does not change during a bar, it can be because there is simply no interest in the market, or because of a perfect balance between buyers and sellers. The latter being more improbable, Bar Balance assumes that neutral bars reveal a lack of interest, which entails uncertainty. That is the reason why the option is provided to interpret ratios of neutral intrabars greater than 50% as divergences. It is also the rationale behind the option to dampen signal lines on the inverse ratio of neutral intrabars, so that zero intrabars do not affect the signal, and progressively larger proportions of neutral intrabars will reduce the signal's amplitude, as the balance calcs using the up/down counts lose significance. The impact of the dampening will vary with markets. Weaker markets such as cryptos will often contain greater numbers of neutral intrabars, so dampening the Line in that sector will have a greater impact than in more liquid markets.
█ FEATURES
1 — Columns
• While the size of the Up/Down columns always represents their respective importance on the bar, their coloring mode is independent. The default setup uses a standard coloring mode where the Up/Down columns over/under the zero line are always in the bull/bear color with a higher intensity for the winning side. Six other coloring modes allow you to pack more information in the columns. When choosing to color the top columns using a bull/bear gradient on Balance Averages, for example, you will end up with bull/bear colored tops. In order for the color of the bottom columns to continue to show the instant bar balance, you can then choose the "Up/Down Ratio on Bar — Dual Solid Colors" coloring mode to make those bars the color of the winning side for that bar.
• Line mode shows only the line, but Columns mode allows displaying the line along with it. If the scale of the line is different than that of the scale of the columns, the line will often appear flat. Traders may find even a flat line useful as its bull/bear colors will be easily distinguishable.
2 — Line
• The default setup for Line mode uses a calculation on "Balance Momentum", with a fill on the longer-term "Balance Averages" and a line color based on the "Markers Bias". With the background set on "Line vs Divergence Levels" and the zero line on the hard-coded "Combined Bar Balances", you have access to five distinct sources of information at a glance, to which you can add divergences, divergences levels and chart bar coloring. This provides powerful potential in displaying bar balance information.
• When no columns are displayed, Line mode can show the full scale of whichever line you choose to calculate because the columns' scale no longer interferes with the line's scale.
• Note that when "Balance on Bar" is selected, the Neutral count is also displayed as a ratio of the balance line. This is the only instance where the Neutral count is displayed in Line mode.
• The "Dual Up/Down Averages" is an exception as it displays two lines: one average for the Up counts and another for the Down counts. This mode will be most useful when Columns are also displayed, as it provides a reference for the top and bottom columns.
3 — Zero Line
The zero line can be colored using two methods, both based on the Combined Balances, i.e., the aggregate of the instant bull/bear bias of the three main bar balances.
• In "Six-state Dual Color Gradient" mode, a dot appears on every bar. Its color reflects the bull/bear state of the Combined Balances, and the dot's brightness reflects the tally of balance biases.
• In "Dual Solid Colors (All Bull/All Bear Only)" a dot only appears when all three balances are either bullish or bearish. The resulting pattern is identical to that of Marker 1.
4 — Divergences
• Divergences are displayed as a small circle at the top of the scale. Four different types of divergence events can be detected. Divergences occur whenever the bull/bear bias of the method used diverges with the bar's price direction.
• An option allows you to include in divergence events instances where the count of neutral intrabars exceeds 50% of the total intrabar count.
• The divergence levels are dynamic levels that automatically build from the line's values on divergence events. On consecutive divergences, the levels will expand, creating a channel. This implementation of the divergence levels corresponds to my view that divergences indicate anomalies, hesitations, points of uncertainty if you will. It excludes any association of a pre-determined bullish/bearish bias to divergences. Accordingly, the levels merely take note of divergence events and mark those points in time with levels. Traders then have a reference point from which they can evaluate further movement. The bull/bear/neutral colors used to plot the levels are also congruent with this view in that they are determined by price's position relative to the levels, which is how I think divergences can be put to the most effective use.
5 — Background
• The background can show a bull/bear gradient on four different calculations. You can adjust its brightness to make its visual importance proportional to how you use it in your analysis.
6 — Chart bars
• Chart bars can be colored using five different methods.
• You have the option of emptying the body of bars where volume does not increase, as does my TLD indicator, the idea behind this being that movement on bars where volume does not increase is less relevant.
7 — Intrabar Resolution
You can choose between three modes. Two of them are automatic and one is manual:
a) Fast, Longer history, Auto-Steps (~12 intrabars) : Optimized for speed and deeper history. Uses an average minimum of 12 intrabars.
b) More Precise, Shorter History Auto-Steps (~24 intrabars) : Uses finer intrabar resolution. It is slower and provides less history. Uses an average minimum of 24 intrabars.
c) Fixed : Uses the fixed resolution of your choice.
Auto-Steps calculations vary for 24/7 and conventional markets in order to achieve the proper target of minimum intrabars.
You can choose to view the intrabar resolution currently used to calculate delta volume. It is the default.
The proper selection of the intrabar resolution is important. It must achieve maximal granularity to produce precise results while not unduly slowing down calculations, or worse, causing runtime errors.
8 — Markers
Six markers are available:
1. Combined Balances Agreement : All three Bar Balances are either bullish or bearish.
2. Up or Down % Agrees With Bar : An up marker will appear when the percentage of up intrabars in an up chart bar is greater than the specified percentage. Conditions mirror to down bars.
3. Divergence confirmations By Price : One of the four types of balance calculations can be used to detect divergences with price. Confirmations occur when the bar following the divergence confirms the balance bias. Note that the divergence events used here do not include neutral intrabar events.
4. Balance Transitions : Bull/bear transitions of the selected balance.
5. Markers Bias Transitions : Bull/bear transitions of the Markers Bias.
6. Divergence Confirmations By Line : Marks points where the line first breaches a divergence level.
Markers appear when the condition is detected, without delay. Since nothing is plotted in realtime, markers do not appear on the realtime bar.
9 — Settings
• Two modes can be selected to dampen the line on the ratio of neutral intrabars.
• A distinct weight can be attributed to the count of the latter half of intrabars, on the assumption that later intrabars may be more important in determining the outcome of chart bars.
• Allows control over the periods of the different moving averages used in calculations.
• The default periods used for the various calculations define the following hierarchy from slow to fast:
Balance Averages: 50,
Balance Momentum: 20,
Dual Up/Down Averages: 20,
Marker Bias: 10.
█ LIMITATIONS
• This script uses a special characteristic of the `security()` function allowing the inspection of intrabars—which is not officially supported by TradingView.
• The method used does not work on the realtime bar—only on historical bars.
• The indicator only works on some chart resolutions: 3, 5, 10, 15 and 30 minutes, 1, 2, 4, 6, and 12 hours, 1 day, 1 week and 1 month. The script’s code can be modified to run on other resolutions, but chart resolutions must be divisible by the lower resolution used for intrabars and the stepping mechanism could require adaptation.
• When using the "Line vs Divergence Levels — Dual Color Gradient" color mode to fill the line, background or chart bars, keep in mind that a line calculation mode must be defined for it to work, as it determines gradients on the movement of the line relative to divergence levels. If the line is hidden, it will not work.
• When the difference between the chart’s resolution and the intrabar resolution is too great, runtime errors will occur. The Auto-Steps selection mechanisms should avoid this.
• Alerts do not work reliably when `security()` is used at intrabar resolutions. Accordingly, no alerts are configured in the indicator.
• The color model used in the indicator provides for fancy visuals that come at a price; when you change values in Inputs , it can take 20 seconds for the changes to materialize. Luckily, once your color setup is complete, the color model does not have a large performance impact, as in normal operation the `security()` calls will become the most important factor in determining response time. Also, once in a while a runtime error will occur when you change inputs. Just making another change will usually bring the indicator back up.
█ RAMBLINGS
Is this thing useful?
I'll let you decide. Bar Balance acts somewhat like an X-Ray on bars. The intrabars it analyzes are no secret; one can simply change the chart's resolution to see the same intrabars the indicator uses. What the indicator brings to traders is the precise count of up/down/neutral intrabars and, more importantly, the calculations it derives from them to present the information in a way that can make it easier to use in trading decisions.
How reliable is Bar Balance information?
By the same token that an up bar does not guarantee that more up bars will follow, future price movements cannot be inferred from the mere count of up/down/neutral intrabars. Price movement during any chart bar for which, let's say, 12 intrabars are analyzed, could be due to only one of those intrabars. One can thus easily see how only relying on bar balance information could be very misleading. The rationale behind Bar Balance is that when the information mined for multiple chart bars is aggregated, it can provide insight into the history behind chart bars, and thus some bias as to the strength of movements. An up chart bar where 11/12 intrabars are also up is assumed to be stronger than the same up bar where only 2/12 intrabars are up. This logic is not bulletproof, and sometimes Bar Balance will stray. Also, keep in mind that balance lines do not represent price momentum as RSI would. Bar Balance calculations have no idea where price is. Their perspective, like that of any historian, is very limited, constrained that it is to the narrow universe of up/down/neutral intrabar counts. You will thus see instances where price is moving up while Balance Momentum, for example, is moving down. When Bar Balance performs as intended, this indicates that the rally is weakening, which does necessarily imply that price will reverse. Occasionally, price will merrily continue to advance on weakening strength.
Divergences
Most of the divergence detection methods used here rely on a difference between the bias of a calculation involving a multi-bar average and a given bar's price direction. When using "Bar Balance on Bar" however, only the bar's balance and price movement are used. This is the default mode.
As usual, divergences are points of interest because they reveal imbalances, which may or may not become turning points. I do not share the overwhelming enthusiasm traders have for the purported ability of bullish/bearish divergences to indicate imminent reversals.
Superfluity
In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . Bar Balance can display lots of information. While learning to use a new indicator inevitably requires an adaptation period where we put it through its paces and try out all its options, once you have become used to Bar Balance and decide to adopt it, rigorously eliminate the components you don't use and configure the remaining ones so their visual prominence reflects their relative importance in your analysis. I tried to provide flexible options for traders to control this indicator's visuals for that exact reason—not for window dressing.
█ NOTES
For traders
• To avoid misleading traders who don't read script descriptions, the indicator shows nothing in the realtime bar.
• The Data Window shows key values for the indicator.
• All gradients used in this indicator determine their brightness intensities using advances/declines in the signal—not their relative position in a fixed scale.
• Note that because of the way gradients are optimized internally, changing their brightness will sometimes require bringing down the value a few steps before you see an impact.
• Because this indicator does not use volume, it will work on all markets.
For coders
• For those interested in gradients, this script uses an advanced version of the Advance/Decline gradient function from the PineCoders Color Gradient (16 colors) Framework . It allows more precise control over the range, steps and min/max values of the gradients.
• I use the PineCoders Coding Conventions for Pine to write my scripts.
• I used functions modified from the PineCoders MTF Selection Framework for the selection of timeframes.
█ THANKS TO:
— alexgrover who helped me think through the dampening method used to attenuate signal lines on high ratios of neutral intrabars.
— A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator . The technique I use to inspect intrabars is derived from Kuan's code.
— theheirophant , my partner in the exploration of the sometimes weird abysses of `security()`’s behavior at intrabar resolutions.
— midtownsk8rguy , my brilliant companion in mining the depths of Pine graphics. He is also the co-author of the PineCoders Color Gradient Frameworks .
Delta Volume Columns Pro [LucF]█ OVERVIEW
This indicator displays volume delta information calculated with intrabar inspection on historical bars, and feed updates when running in realtime. It is designed to run in a pane and can display either stacked buy/sell volume columns or a signal line which can be calculated and displayed in many different ways.
Five different models are offered to reveal different characteristics of the calculated volume delta information. Many options are offered to visualize the calculations, giving you much leeway in morphing the indicator's visuals to suit your needs. If you value delta volume information, I hope you will find the time required to master Delta Volume Columns Pro well worth the investment. I am confident that if you combine a proper understanding of the indicator's information with an intimate knowledge of the volume idiosyncrasies on the markets you trade, you can extract useful market intelligence using this tool.
█ WARNINGS
1. The indicator only works on markets where volume information is available,
Please validate that your symbol's feed carries volume information before asking me why the indicator doesn't plot values.
2. When you refresh your chart or re-execute the script on the chart, the indicator will repaint because elapsed realtime bars will then recalculate as historical bars.
3. Because the indicator uses different modes of calculation on historical and realtime bars, it's critical that you understand the differences between them. Details are provided further down.
4. Calculations using intrabar inspection on historical bars can only be done from some chart timeframes. See further down for a list of supported timeframes.
If the chart's timeframe is not supported, no historical volume delta will display.
█ CONCEPTS
Chart bars
Three different types of bars are used in charts:
1. Historical bars are bars that have already closed when the script executes on them.
2. The realtime bar is the current, incomplete bar where a script is running on an open market. There is only one active realtime bar on your chart at any given time.
The realtime bar is where alerts trigger.
3. Elapsed realtime bars are bars that were calculated when they were realtime bars but have since closed.
When a script re-executes on a chart because the browser tab is refreshed or some of its inputs are changed, elapsed realtime bars are recalculated as historical bars.
Why does this indicator use two modes of calculation?
Historical bars on TradingView charts contain OHLCV data only, which is insufficient to calculate volume delta on them with any level of precision. To mine more detailed information from those bars we look at intrabars , i.e., bars from a smaller timeframe (we call it the intrabar timeframe ) that are contained in one chart bar. If your chart Is running at 1D on a 24x7 market for example, most 1D chart bars will contain 24 underlying 1H bars in their dilation. On historical bars, this indicator looks at those intrabars to amass volume delta information. If the intrabar is up, its volume goes in the Buy bin, and inversely for the Sell bin. When price does not move on an intrabar, the polarity of the last known movement is used to determine in which bin its volume goes.
In realtime, we have access to price and volume change for each update of the chart. Because a 1D chart bar can be updated tens of thousands of times during the day, volume delta calculations on those updates is much more precise. This precision, however, comes at a price:
— The script must be running on the chart for it to keep calculating in realtime.
— If you refresh your chart you will lose all accumulated realtime calculations on elapsed realtime bars, and the realtime bar.
Elapsed realtime bars will recalculate as historical bars, i.e., using intrabar inspection, and the realtime bar's calculations will reset.
When the script recalculates elapsed realtime bars as historical bars, the values on those bars will change, which means the script repaints in those conditions.
— When the indicator first calculates on a chart containing an incomplete realtime bar, it will count ALL the existing volume on the bar as Buy or Sell volume,
depending on the polarity of the bar at that point. This will skew calculations for that first bar. Scripts have no access to the history of a realtime bar's previous updates,
and intrabar inspection cannot be used on realtime bars, so this is the only to go about this.
— Even if alerts only trigger upon confirmation of their conditions after the realtime bar closes, they are repainting alerts
because they would perhaps not have calculated the same way using intrabar inspection.
— On markets like stocks that often have different EOD and intraday feeds and volume information,
the volume's scale may not be the same for the realtime bar if your chart is at 1D, for example,
and the indicator is using an intraday timeframe to calculate on historical bars.
— Any chart timeframe can be used in realtime mode, but plots that include moving averages in their calculations may require many elapsed realtime bars before they can calculate.
You might prefer drastically reducing the periods of the moving averages, or using the volume columns mode, which displays instant values, instead of the line.
Volume Delta Balances
This indicator uses a variety of methods to evaluate five volume delta balances and derive other values from those balances. The five balances are:
1 — On Bar Balance : This is the only balance using instant values; it is simply the subtraction of the Sell volume from the Buy volume on the bar.
2 — Average Balance : Calculates a distinct EMA for both the Buy and Sell volumes, and subtracts the Sell EMA from the Buy EMA.
3 — Momentum Balance : Starts by calculating, separately for both Buy and Sell volumes, the difference between the same EMAs used in "Average Balance" and
an SMA of double the period used for the "Average Balance" EMAs. The difference for the Sell side is subtracted from the difference for the Buy side,
and an RSI of that value is calculated and brought over the −50/+50 scale.
4 — Relative Balance : The reference values used in the calculation are the Buy and Sell EMAs used in the "Average Balance".
From those, we calculate two intermediate values using how much the instant Buy and Sell volumes on the bar exceed their respective EMA — but with a twist.
If the bar's Buy volume does not exceed the EMA of Buy volume, a zero value is used. The same goes for the Sell volume with the EMA of Sell volume.
Once we have our two intermediate values for the Buy and Sell volumes exceeding their respective MA, we subtract them. The final "Relative Balance" value is an ALMA of that subtraction.
The rationale behind using zero values when the bar's Buy/Sell volume does not exceed its EMA is to only take into account the more significant volume.
If both instant volume values exceed their MA, then the difference between the two is the signal's value.
The signal is called "relative" because the intermediate values are the difference between the instant Buy/Sell volumes and their respective MA.
This balance flatlines when the bar's Buy/Sell volumes do not exceed their EMAs, which makes it useful to spot areas where trader interest dwindles, such as consolidations.
The smaller the period of the final value's ALMA, the more easily you will see the balance flatline. These flat zones should be considered no-trade zones.
5 — Percent Balance : This balance is the ALMA of the ratio of the "On Bar Balance" value, i.e., the volume delta balance on the bar (which can be positive or negative),
over the total volume for that bar.
From the balances and marker conditions, two more values are calculated:
1 — Marker Bias : It sums the up/down (+1/‒1) occurrences of the markers 1 to 4 over a period you define, so it ranges from −4 to +4, times the period.
Its calculation will depend on the modes used to calculate markers 3 and 4.
2 — Combined Balances : This is the sum of the bull/bear (+1/−1) states of each of the five balances, so it ranges from −5 to +5.
█ FEATURES
The indicator has two main modes of operation: Columns and Line .
Columns
• In Columns mode you can display stacked Buy/Sell volume columns.
• The buy section always appears above the centerline, the sell section below.
• The top and bottom sections can be colored independently using eight different methods.
• The EMAs of the Buy/Sell values can be displayed (these are the same EMAs used to calculate the "Average Balance").
Line
• Displays one of seven signals: the five balances or one of two complementary values, i.e., the "Marker Bias" or the "Combined Balances".
• You can color the line and its fill using independent calculation modes to pack more information in the display.
You can thus appraise the state of 3 different values using the line itself, its color and the color of its fill.
• A "Divergence Levels" feature will use the line to automatically draw expanding levels on divergence events.
Default settings
Using the indicator's default settings, this is the information displayed:
• The line is calculated on the "Average Balance".
• The line's color is determined by the bull/bear state of the "Percent Balance".
• The line's fill gradient is determined by the advances/declines of the "Momentum Balance".
• The orange divergence dots are calculated using discrepancies between the polarity of the "On Bar Balance" and the chart's bar.
• The divergence levels are determined using the line's level when a divergence occurs.
• The background's fill gradient is calculated on advances/declines of the "Marker Bias".
• The chart bars are colored using advances/declines of the "Relative Balance". Divergences are shown in orange.
• The intrabar timeframe is automatically determined from the chart's timeframe so that a minimum of 50 intrabars are used to calculate volume delta on historical bars.
Alerts
The configuration of the marker conditions explained further is what determines the conditions that will trigger alerts created from this script. Note that simply selecting the display of markers does not create alerts. To create an alert on this script, you must use ALT-A from the chart. You can create multiple alerts triggering on different conditions from this same script; simply configure the markers so they define the trigger conditions for each alert before creating the alert. The configuration of the script's inputs is saved with the alert, so from then on you can change them without affecting the alert. Alert messages will mention the marker(s) that triggered the specific alert event. Keep in mind, when creating alerts on small chart timeframes, that discrepancies between alert triggers and markers displayed on your chart are to be expected. This is because the alert and your chart are running two distinct instances of the indicator on different servers and different feeds. Also keep in mind that while alerts only trigger on confirmed conditions, they are calculated using realtime calculation mode, which entails that if you refresh your chart and elapsed realtime bars recalculate as historical bars using intrabar inspection, markers will not appear in the same places they appeared in realtime. So it's important to understand that even though the alert conditions are confirmed when they trigger, these alerts will repaint.
Let's go through the sections of the script's inputs.
Columns
The size of the Buy/Sell columns always represents their respective importance on the bar, but the coloring mode for tops and bottoms is independent. The default setup uses a standard coloring mode where the Buy/Sell columns are always in the bull/bear color with a higher intensity for the winning side. Seven other coloring modes allow you to pack more information in the columns. When choosing to color the top columns using a bull/bear gradient on "Average Balance", for example, you will have bull/bear colored tops. In order for the color of the bottom columns to continue to show the instant bar balance, you can then choose the "On Bar Balance — Dual Solid Colors" coloring mode to make those bars the color of the winning side for that bar. You can display the averages of the Buy and Sell columns. If you do, its coloring is controlled through the "Line" and "Line fill" sections below.
Line and Line fill
You can select the calculation mode and the thickness of the line, and independent calculations to determine the line's color and fill.
Zero Line
The zero line can display dots when all five balances are bull/bear.
Divergences
You first select the detection mode. Divergences occur whenever the up/down direction of the signal does not match the up/down polarity of the bar. Divergences are used in three components of the indicator's visuals: the orange dot, colored chart bars, and to calculate the divergence levels on the line. The divergence levels are dynamic levels that automatically build from the line's values on divergence events. On consecutive divergences, the levels will expand, creating a channel. This implementation of the divergence levels corresponds to my view that divergences indicate anomalies, hesitations, points of uncertainty if you will. It precludes any attempt to identify a directional bias to divergences. Accordingly, the levels merely take note of divergence events and mark those points in time with levels. Traders then have a reference point from which they can evaluate further movement. The bull/bear/neutral colors used to plot the levels are also congruent with this view in that they are determined by the line's position relative to the levels, which is how I think divergences can be put to the most effective use. One of the coloring modes for the line's fill uses advances/declines in the line after divergence events.
Background
The background can show a bull/bear gradient on six different calculations. As with other gradients, you can adjust its brightness to make its importance proportional to how you use it in your analysis.
Chart bars
Chart bars can be colored using seven different methods. You have the option of emptying the body of bars where volume does not increase, as does my TLD indicator, and you can choose whether you want to show divergences.
Intrabar Timeframe
This is the intrabar timeframe that will be used to calculate volume delta using intrabar inspection on historical bars. You can choose between four modes. The three "Auto-steps" modes calculate, from the chart's timeframe, the intrabar timeframe where the said number of intrabars will make up the dilation of chart bars. Adjustments are made for non-24x7 markets. "Fixed" mode allows you to select the intrabar timeframe you want. Checking the "Show TF" box will display in the lower-right corner the intrabar timeframe used at any given moment. The proper selection of the intrabar timeframe is important. It must achieve maximal granularity to produce precise results while not unduly slowing down calculations, or worse, causing runtime errors. Note that historical depth will vary with the intrabar timeframe. The smaller the timeframe, the shallower historical plots you will be.
Markers
Markers appear when the required condition has been confirmed on a closed bar. The configuration of the markers when you create an alert is what determines when the alert will trigger. Five markers are available:
• Balances Agreement : All five balances are either bullish or bearish.
• Double Bumps : A double bump is two consecutive up/down bars with +/‒ volume delta, and rising Buy/Sell volume above its average.
• Divergence confirmations : A divergence is confirmed up/down when the chosen balance is up/down on the previous bar when that bar was down/up, and this bar is up/down.
• Balance Shifts : These are bull/bear transitions of the selected signal.
• Marker Bias Shifts : Marker bias shifts occur when it crosses into bull/bear territory.
Periods
Allows control over the periods of the different moving averages used to calculate the balances.
Volume Discrepancies
Stock exchanges do not report the same volume for intraday and daily (or higher) resolutions. Other variations in how volume information is reported can also occur in other markets, namely Forex, where volume irregularities can even occur between different intraday timeframes. This will cause discrepancies between the total volume on the bar at the chart's timeframe, and the total volume calculated by adding the volume of the intrabars in that bar's dilation. This does not necessarily invalidate the volume delta information calculated from intrabars, but it tells us that we are using partial volume data. A mechanism to detect chart vs intrabar timeframe volume discrepancies is provided. It allows you to define a threshold percentage above which the background will indicate a difference has been detected.
Other Settings
You can control here the display of the gray dot reminder on realtime bars, and the display of error messages if you are using a chart timeframe that is not greater than the fixed intrabar timeframe, when you use that mode. Disabling the message can be useful if you only use realtime mode at chart timeframes that do not support intrabar inspection.
█ RAMBLINGS
On Volume Delta
Volume is arguably the best complement to interpret price action, and I consider volume delta to be the most effective way of processing volume information. In periods of low-volatility price consolidations, volume will typically also be lower than normal, but slight imbalances in the trend of the buy/sell volume balance can sometimes help put early odds on the direction of the break from consolidation. Additionally, the progression of the volume imbalance can help determine the proximity of the breakout. I also find volume delta and the number of divergences very useful to evaluate the strength of trends. In trends, I am looking for "slow and steady", i.e., relatively low volatility and pauses where price action doesn't look like world affairs are being reassessed. In my personal mythology, this type of trend is often more resilient than high-volatility breakouts, especially when volume balance confirms the general agreement of traders signaled by the low-volatility usually accompanying this type of trend. The volume action on pauses will often help me decide between aggressively taking profits, tightening a stop or going for a longer-term movement. As for reversals, they generally occur in high-volatility areas where entering trades is more expensive and riskier. While the identification of counter-trend reversals fascinates many traders to no end, they represent poor opportunities in my view. Volume imbalances often precede reversals, but I prefer to use volume delta information to identify the areas following reversals where I can confirm them and make relatively low-cost entries with better odds.
On "Buy/Sell" Volume
Buying or selling volume are misnomers, as every unit of volume transacted is both bought and sold by two different traders. While this does not keep me from using the terms, there is no such thing as “buy only” or “sell only” volume. Trader lingo is riddled with peculiarities.
Divergences
The divergence detection method used here relies on a difference between the direction of a signal and the polarity (up/down) of a chart bar. When using the default "On Bar Balance" to detect divergences, however, only the bar's volume delta is used. You may wonder how there can be divergences between buying/selling volume information and price movement on one bar. This will sometimes be due to the calculation's shortcomings, but divergences may also occur in instances where because of order book structure, it takes less volume to increase the price of an asset than it takes to decrease it. As usual, divergences are points of interest because they reveal imbalances, which may or may not become turning points. To your pattern-hungry brain, the divergences displayed by this indicator will — as they do on other indicators — appear to often indicate turnarounds. My opinion is that reality is generally quite sobering and I have no reliable information that would tend to prove otherwise. Exercise caution when using them. Consequently, I do not share the overwhelming enthusiasm of traders in identifying bullish/bearish divergences. For me, the best course of action when a divergence occurs is to wait and see what happens from there. That is the rationale underlying how my divergence levels work; they take note of a signal's level when a divergence occurs, and it's the signal's behavior from that point on that determines if the post-divergence action is bullish/bearish.
Superfluity
In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . This indicator can display lots of information. While learning to use a new indicator inevitably requires an adaptation period where we put it through its paces and try out all its options, once you have become used to it and decide to adopt it, rigorously eliminate the components you don't use and configure the remaining ones so their visual prominence reflects their relative importance in your analysis. I tried to provide flexible options for traders to control this indicator's visuals for that exact reason — not for window dressing.
█ LIMITATIONS
• This script uses a special characteristic of the `security()` function allowing the inspection of intrabars — which is not officially supported by TradingView.
It has the advantage of permitting a more robust calculation of volume delta than other methods on historical bars, but also has its limits.
• Intrabar inspection only works on some chart timeframes: 3, 5, 10, 15 and 30 minutes, 1, 2, 3, 4, 6, and 12 hours, 1 day, 1 week and 1 month.
The script’s code can be modified to run on other resolutions.
• When the difference between the chart’s timeframe and the intrabar timeframe is too great, runtime errors will occur. The Auto-Steps selection mechanisms should avoid this.
• All volume is not created equally. Its source, components, quality and reliability will vary considerably with sectors and instruments.
The higher the quality, the more reliably volume delta information can be used to guide your decisions.
You should make it your responsibility to understand the volume information provided in the data feeds you use. It will help you make the most of volume delta.
█ NOTES
For traders
• The Data Window shows key values for the indicator.
• While this indicator displays some of the same information calculated in my Delta Volume Columns ,
I have elected to make it a separate publication so that traders continue to have a simpler alternative available to them. Both code bases will continue to evolve separately.
• All gradients used in this indicator determine their brightness intensities using advances/declines in the signal—not their relative position in a pre-determined scale.
• Volume delta being relative, by nature, it is particularly well-suited to Forex markets, as it filters out quite elegantly the cyclical volume data characterizing the sector.
If you are interested in volume delta, consider having a look at my other "Delta Volume" indicators:
• Delta Volume Realtime Action displays realtime volume delta and tick information on the chart.
• Delta Volume Candles builds volume delta candles on the chart.
• Delta Volume Columns is a simpler version of this indicator.
For coders
• I use the `f_c_gradientRelativePro()` from the PineCoders Color Gradient Framework to build my gradients.
This function has the advantage of allowing begin/end colors for both the bull and bear colors. It also allows us to define the number of steps allowed for each gradient.
I use this to modulate the gradients so they perform optimally on the combination of the signal used to calculate advances/declines,
but also the nature of the visual component the gradient applies to. I use fewer steps for choppy signals and when the gradient is used on discrete visual components
such as volume columns or chart bars.
• I use the PineCoders Coding Conventions for Pine to write my scripts.
• I used functions modified from the PineCoders MTF Selection Framework for the selection of timeframes.
█ THANKS TO:
— The devs from TradingView's Pine and other teams, and the PineCoders who collaborate with them. They are doing amazing work,
and much of what this indicator does could not be done without their recent improvements to Pine.
— A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator using a `for` loop.
This indicator started from the intrabar inspection technique illustrated in Kuan's snippet.
— theheirophant , my partner in the exploration of the sometimes weird abysses of `security()`’s behavior at intrabar timeframes.
— midtownsk8rguy , my brilliant companion in mining the depths of Pine graphics.
Total Bars [xdecow]This simple indicator shows the total number of bars on the graph.
It serves to see which broker has a longer history or if the chart has enough candles to perform backtests.
Delta Volume Candles [LucF]█ OVERVIEW
This indicator plots on-chart volume delta information using candles that can replace your normal candles, tops and bottoms appended to normal candles, optional MAs of those tops and bottoms levels, a divergence channel and a chart background. The indicator calculates volume delta using intrabar analysis, meaning that it uses the lower timeframe bars constituting each chart bar.
█ CONCEPTS
Volume Delta
The volume delta concept divides a bar's volume in "up" and "down" volumes. The delta is calculated by subtracting down volume from up volume. Many calculation techniques exist to isolate up and down volume within a bar. The simplest use the polarity of interbar price changes to assign their volume to up or down slots, e.g., On Balance Volume or the Klinger Oscillator . Others such as Chaikin Money Flow use assumptions based on a bar's OHLC values. The most precise calculation method uses tick data and assigns the volume of each tick to the up or down slot depending on whether the transaction occurs at the bid or ask price. While this technique is ideal, it requires huge amounts of data on historical bars, which considerably limits the historical depth of charts and the number of symbols for which tick data is available. Furthermore, historical tick data is not yet available on TradingView.
This indicator uses intrabar analysis to achieve a compromise between the simplest and most precise methods of calculating volume delta. It is currently the most precise method usable on TradingView charts. TradingView's Volume Profile built-in indicators use it, as do the CVD - Cumulative Volume Delta Candles and CVD - Cumulative Volume Delta (Chart) indicators published from the TradingView account . My Delta Volume Channels and Volume Delta Columns Pro indicators also use intrabar analysis. Other volume delta indicators such as my Realtime 5D Profile use realtime chart updates to calculate volume delta without intrabar analysis, but that type of indicator only works in real time; they cannot calculate on historical bars.
This is the logic I use to determine the polarity of intrabars, which determines the up or down slot where its volume is added:
• If the intrabar's open and close values are different, their relative position is used.
• If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.
• As a last resort, when there is no movement during an intrabar, and it closes at the same price as the previous intrabar, the last known polarity is used.
Once all intrabars making up a chart bar have been analyzed and the up or down property of each intrabar's volume determined, the up volumes are added, and the down volumes subtracted. The resulting value is volume delta for that chart bar, which can be used as an estimate of the buying/selling pressure on an instrument. Not all markets have volume information. Without it, this indicator is useless.
Intrabar analysis
Intrabars are chart bars at a lower timeframe than the chart's. The timeframe used to access intrabars determines the number of intrabars accessible for each chart bar. On a 1H chart, each chart bar of an active market will, for example, usually contain 60 bars at the lower timeframe of 1min, provided there was market activity during each minute of the hour.
This indicator automatically calculates an appropriate lower timeframe using the chart's timeframe and the settings you use in the script's "Intrabars" section of the inputs. As it can access lower timeframes as small as seconds when available, the indicator can be used on charts at relatively small timeframes such as 1min, provided the market is active enough to produce bars at second timeframes.
The quantity of intrabars analyzed in each chart bar determines:
• The precision of calculations (more intrabars yield more precise results).
• The chart coverage of calculations (there is a 100K limit to the quantity of intrabars that can be analyzed on any chart,
so the more intrabars you analyze per chart bar, the less chart bars can be calculated by the indicator).
The information box displayed at the bottom right of the chart shows the lower timeframe used for intrabars, as well as the average number of intrabars detected for chart bars and statistics on chart coverage.
Balances
This indicator calculates five balances from volume delta values. The balances are oscillators with a zero centerline; positive values are bullish, and negative values are bearish. It is important to understand the balances as they can be used to:
• Color candle bodies.
• Calculate body and top and bottom divergences.
• Color an EMA channel.
• Color the chart's background.
• Configure markers and alerts.
The five balances are:
1 — Bar Balance : This is the only balance using instant values; it is simply the subtraction of the down volume from the up volume on the bar, so the instant volume delta for that bar.
2 — Average Balance : Calculates a distinct EMA for both the up and down volumes, and subtracts the down EMA from the up EMA.
The result is akin to MACD's histogram because it is the subtraction of two moving averages.
3 — Momentum Balance : Starts by calculating, separately for both up and down volumes, the difference between the same EMAs used in "Average Balance" and
an SMA of twice the period used for the "Average Balance" EMAs. The difference for the up side is subtracted from the difference for the down side,
and an RSI of that value is calculated and brought over the −50/+50 scale.
4 — Relative Balance : The reference values used in the calculation are the up and down EMAs used in the "Average Balance".
From those, we calculate two intermediate values using how much the instant up and down volumes on the bar exceed their respective EMA — but with a twist.
If the bar's up volume does not exceed the EMA of up volume, a zero value is used. The same goes for the down volume with the EMA of down volume.
Once we have our two intermediate values for the up and down volumes exceeding their respective MA, we subtract them. The final value is an ALMA of that subtraction.
The rationale behind using zero values when the bar's up/down volume does not exceed its EMA is to only take into account the more significant volume.
If both instant volume values exceed their MA, then the difference between the two is the signal's value.
The signal is called "relative" because the intermediate values are the difference between the instant up/down volumes and their respective MA.
This balance flatlines when the bar's up/down volumes do not exceed their EMAs, which makes it useful to spot areas where trader interest dwindles, such as consolidations.
The smaller the period of the final value's ALMA, the more easily it will flatline. These flat zones should be considered no-trade zones.
5 — Percent Balance : This balance is the ALMA of the ratio of the "Bar Balance" over the total volume for that bar.
From the balances and marker conditions, two more values are calculated:
1 — Marker Bias : This sums the up/down (+1/‒1) occurrences of the markers 1 to 4 over a period you define, so it ranges from −4 to +4, times the period.
Its calculation will depend on the modes used to calculate markers 3 and 4.
2 — Combined Balances : This is the sum of the bull/bear (+1/−1) states of each of the five balances, so it ranges from −5 to +5.
The periods for all of these balances can be configured in the "Periods" section at the bottom of the script's inputs. As you cannot see the balances on the chart, you can use my Volume Delta Columns Pro indicator in a pane; it can plot the same balances, so you will be able to analyze them.
Divergences
In the context of this indicator, a divergence is any bar where the bear/bull state of a balance (above/below its zero centerline) diverges from the polarity of a chart bar. No directional bias is assigned to divergences when they occur. Candle bodies and tops/bottoms can each be colored differently on divergences detected from distinct balances.
Divergence Channel
The divergence channel is the space between two levels (by default, the bar's open and close ) saved when divergences occur. When price (by default the close ) has breached a channel and a new divergence occurs, a new channel is created. Until that new channel is breached, bars where additional divergences occur will expand the channel's levels if the bar's price points are outside the channel.
Prices breaches of the divergence channel will change its state. Divergence channels can be in one of three different states:
• Bull (green): Price has breached the channel to the upside.
• Bear (red): Price has breached the channel to the downside.
• Neutral (gray): The channel has not yet been breached.
█ HOW TO USE THE INDICATOR
I do not make videos to explain how to use my indicators. I do, however, try hard to include in their description everything one needs to understand what they do. From there, it's up to you to explore and figure out if they can be useful in your trading practice. Communicating in videos what this description and the script's tooltips contain would make for very long videos that would likely exceed the attention span of most people who find this description too long. There is no quick way to understand an indicator such as this one because it uses many different concepts and has quite a bit of settings one can use to modify its visuals and behavior — thus how one uses it. I will happily answer questions on the inner workings of the indicator, but I do not answer questions like "How do I trade using this indicator?" A useful answer to that question would require an in-depth analysis of who you are, your trading methodology and objectives, which I do not have time for. I do not teach trading.
Start by loading the indicator on an active chart containing volume information. See here if you need help.
The default configuration displays:
• Normal candles where the bodies are only colored if the bar's volume has increased since the last bar.
If you want to use this indicator's candles, you may want to disable your chart's candles by clicking the eye icon to the right of the symbol's name in the top left of the chart.
• A top or bottom appended to the normal candles. It represents the difference between up and down volume for that bar
and is positioned at the top or bottom, depending on its polarity. If up volume is greater than down volume, a top is displayed. If down volume is greater, a bottom is plotted.
The size of tops and bottoms is determined by calculating a factor which is the proportion of volume delta over the bar's total volume.
That factor is then used to calculate the top or bottom size relative to a baseline of the average candle body size of the last 100 bars.
• An information box in the bottom right displaying intrabar and chart coverage information.
• A light red background when the intrabar volume differs from the chart's volume by more than 1%.
The script's inputs contain tooltips explaining most of the fields. I will not repeat them here. Following is a brief description of each section of the indicator's inputs which will give you an idea of what the indicator can do:
Normal Candles is where you configure the replacement candles plotted by the script. You can choose from different coloring schemes for their bodies and specify a unique color for bodies where a divergence calculated using the method you choose occurs.
Volume Tops & Botttoms is where you configure the display of tops and bottoms, and their EMAs. The EMAs are calculated from the high point of tops and the low point of bottoms. They can act as a channel to evaluate price, and you can choose to color the channel using a gradient reflecting the advances/declines in the balance of your choice.
Divergence Channel is where you set up the appearance and behavior of the divergence channel. These areas represent levels where price and volume delta information do not converge. They can be interpreted as regions with no clear direction from where one will look for breaches. You can configure the channel to take into account one or both types of divergences you have configured for candle bodies and tops/bottoms.
Background allows you to configure a gradient background color that reflects the advances/declines in the balance of your choice. You can use this to provide context to the volume delta values from bars. You can also control the background color displayed on volume discrepancies between the intrabar and the chart's timeframe.
Intrabars is where you choose the calculation mode determining the lower timeframe used to access intrabars. The indicator uses the chart's timeframe and the type of market you are on to calculate the lower timeframe. Your setting there should reflect which compromise you prefer between the precision of calculations and chart coverage. This is also where you control the display of the information box in the lower right corner of the chart.
Markers allows you to control the plotting of chart markers on different conditions. Their configuration determines when alerts generated from the indicator will fire. Note that in order to generate alerts from this script, they must be created from your chart. See this Help Center page to learn how. Only the last 500 markers will be visible on the chart, but this will not affect the generation of alerts.
Periods is where you configure the periods for the balances and the EMAs used in the indicator.
The raw values calculated by this script can be inspected using the Data Window.
█ INTERPRETATION
Rightly or wrongly, volume delta is considered by many a useful complement to the interpretation of price action. I use it extensively in an attempt to find convergence between my read of volume delta and price movement — not so much as a predictor of future price movement. No system or person can predict the future. Accordingly, I consider people who speak or act as if they know the future with certainty to be dangerous to themselves and others; they are charlatans, imprudent or blissfully ignorant.
I try to avoid elaborate volume delta interpretation schemes involving too many variables and prefer to keep things simple:
• Trends that have more chances of continuing should be accompanied by VD of the same polarity.
In trends, I am looking for "slow and steady". I work from the assumption that traders and systems often overreact, which translates into unproductive volatility.
Wild trends are more susceptible to overreactions.
• I prefer steady VD values over wildly increasing ones, as large VD increases often come with increased price volatility, which can backfire.
Large VD values caused by stopping volume will also often occur on trend reversals with abnormally high candles.
• Prices escaping divergence channels may be leading a trend in that direction, although there is no telling how long that trend will last; could be just a few bars or hundreds.
When price is in a channel, shifts in VD balances can sometimes give us an idea of the direction where price has the most chance of breaking.
• Dwindling VD will often indicate trend exhaustion and predate reversals by many bars, but the problem is that mere pauses in a trend will often produce the same behavior in VD.
I think it is too perilous to infer rigidly from VD decreases.
Divergence Channel
Here I have configured the divergence channels to be visible. First, I set the bodies to display divergences on the default Bar Balance. They are indicated by yellow bodies. Then I activated the divergence channels by choosing to draw levels on body divergences and checked the "Fill" checkbox to fill the channel with the same color as the levels. The divergence channel is best understood as a direction-less area from where a breach can be acted on if other variables converge with the breach's direction:
Tops and Bottoms EMAs
I find these EMAs rather interesting. They have no equivalent elsewhere, as they are calculated from the top and bottom values this indicator plots. The only similarity they have with volume-weighted MAs, including VWAP, is that they use price and volume. This indicator's Tops and Bottoms EMAs, however, use the price and volume delta. While the channel differs from other channels in how it is calculated, it can be used like others, as a baseline from which to evaluate price movement or, alternatively, as stop levels. Remember that you can change the period used for the EMAs in the "Periods" section of the inputs.
This chart shows the EMAs in action, filled with a gradient representing the advances/decline from the Momentum balance. Notice the anomaly in the chart's latest bars where the Momentum balance gradient has been indicating a bullish bias for some time, during which price was mostly below the EMAs. Price has just broken above the channel on positive VD. My interpretation of this situation would be that it is a risky opportunity for a long trade in the larger context where the market has been in a downtrend since the 5th. Intrepid traders choosing to enter here could do so with a "make or break" tight stop that will minimize their losses should the market continue its downtrend while hopefully preserving the potential upside of price continuing on the longer-term uptrend prevalent since the 28th:
█ NOTES
Volume
If you use indicators such as this one which depends on volume information, it is important to realize that the volume data they consume comes from data feeds, and that all data feeds are NOT created equally. Those who create the data feeds we use must make decisions concerning the nature of the transactions they tally and the way they are tallied in each feed, and these decisions affect the nature of our volume data. My Volume X-ray publication discusses some of the reasons why volume information from different timeframes, brokers/exchanges or sectors may vary considerably. I encourage you to read it. This indicator's display of a warning through a background color on volume discrepancies between the timeframe used to access intrabars and the chart's timeframe is an attempt to help you realize these variations in feeds. Don't take things for granted, and understand that the quality of a given feed's volume information affects the quality of the results this indicator calculates.
Markets as ecosystems
I believe it is perilous to think that behavioral patterns you discover in one market through the lens of this or any other indicator will necessarily port to other markets. While this may sometimes be the case, it will often not. Why is that? Because each market is its own ecosystem. As cities do, all markets share some common characteristics, but they also all have their idiosyncrasies. A proportion of a city's inhabitants is always composed of outsiders who come and go, but a core population of regulars and systems is usually the force that actually defines most of the city's observable characteristics. I believe markets work somewhat the same way; they may look the same, but if you live there for a while and pay attention, you will notice the idiosyncrasies. Some things that work in some markets will, accordingly, not work in others. Please keep that in mind when you draw conclusions.
On Up/Down or Buy/Sell Volume
Buying or selling volume are misnomers, as every unit of volume transacted is both bought and sold by two different traders. While this does not keep me from using the terms, there is no such thing as “buy only” or “sell only” volume. Trader lingo is riddled with peculiarities. Without access to order book information, traders work with the assumption that when price moves up during a bar, there was more buying pressure than selling pressure, just as when buy market orders take out limit ask orders in the order book at successively higher levels. The built-in volume indicator available on TradingView uses this logic to color the volume columns green or red. While this script’s calculations are more precise because it analyses intrabars to calculate its information, it uses pretty much the same imperfect logic. Until Pine scripts can have access to how much volume was transacted at the bid/ask prices, our volume delta calculations will remain a mere proxy.
Repainting
• The values calculated on the realtime bar will update as new information comes from the feed.
• Historical values may recalculate if the historical feed is updated or when calculations start from a new point in history.
• Markers and alerts will not repaint as they only occur on a bar's close. Keep this in mind when viewing markers on historical bars,
where one could understandably and incorrectly assume they appear at the bar's open.
To learn more about repainting, see the Pine Script™ User Manual's page on the subject .
Superfluity
In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . This indicator can display a lot of information. The inevitable adaptation period you will need to figure out how to use it should help you eliminate all the visuals you do not need. The more you eliminate, the easier it will be to focus on those that are the most useful to your trading practice. Don't be a fool.
█ THANKS
Thanks to alexgrover for his Dekidaka-Ashi indicator. His volume plots on candles were the inspiration for my top/bottom plots.
Kudos to PineCoders for their libraries. I use two of them in this script: Time and lower_tf .
The first versions of this script used functionality that I would not have known about were it not for these two guys:
— A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator.
— theheirophant , my partner in the exploration of the sometimes weird abysses of request.security() ’s behavior at lower timeframes.
expected range STUDYThis is an indicator that measures how much price movement (low to high) we've seen in a set of 1 bar back, 2 bars back, 3 bars back, 5 bars back, 8 bars back using the Fibonacci sequence up to 89 bars back, and then measures how low or high within each range we are, sort of like giving a rating of 0 for sitting on the lower Bollinger Band and a rating of 100 for sitting on the higher Bollinger band. It combines all the data and weights the data by the historical strength of signal from each length of bands. It's been tuned to a 2 hour XBTUSD chart, but it could be used on other things and other timeframes too. Some tweaking would be needed, though. The final result works more like a trend following indictor than and indicator that tries to pick an exact trend reversal point. However, you're free to use it how you want. Frequently you get a nice red or green spike up showing you when the bottom or top is in, but sometimes those spikes are just the start of an extended down move or up move.
On the chart, a buy (long) signal is generated when the green line crosses up above the orange line. To make it extra clear the background is green when you should be long. A sell (short) signal is generated with the red line crosses up above the yellow line. The background will be red when you should be short. If the background is black, it's indicating a profit of over 53% was taken and it's waiting for another trade to start. Up to you to take profit or keep riding your trade.
For XBTUSD trades, a full take profit on any trade exceeding 53% gains works nice (on 1x leverage) and a stoploss of -7% works quite nicely too. One could use this on up to 2x leverage but I wouldn't recommend going much higher. Have fun. Trade carefully. Don't get rekt.
I will release the "expected range STRATEGY" to go along with this so you can do your own backtesting.
Disclaimer: I haven't tested the alerts, but they should work. Use at your own risk.
Heiken-Ashi CandlesSimple script to view Heiken-Ashi candles below a normal candles chart.
Could also be useful for using HA calcs in strategy scripts on normal candles chart for proper backtesting.
I adapted this to v4 from original v2 script by @samtsui. If you like please remember to give him a Thumbs Up for his original version! ->
Delta Volume Columns [LucF]Displays delta volume columns using intrabar volume information. Each volume column is divided into three sections: buying, selling and neutral volume. Volume for each section is determined from the volume and price movement of each intrabar at a user-selected lower resolution.
Features include:
- Choice of color themes for either dark or light chart backgrounds
- Delta volume columns
- Volume Balance displayed as the difference between the MAs of buying and selling volume
- Display of divergences between a bar’s volume balance and the bar’s price movement (example: buying volume > selling volume but close < open). Divergences can be shown in 2 different color schemes (including green/red showing a tentative direction), on volume columns and/or on chart bars
- Display of bar by bar volume balance with highlighting of above average volume
- Display of the usual total volume MA
- Choice of the lower resolution used to retrieve intrabar information
- Alerts configurable on any combination of the markers, with control over long/short direction
- Choice of 3 different markers:
1. Double bumps: two consecutive bars where buying or selling volume is in the same direction and where volume > volume MA
2. Divergence confirmations: direction of the price bar following a price/volume balance divergence
3. Volume balance shifts: zero level crossings of the volume balance MA delta
The chart shows the two main modes of display:
- Top pane : shows the stacked volume columns with divergences in orange and the flattened volume balance MAs delta at the bottom of the volume columns. This volume balance is the same shown in the bottom pane. The top pane also shows the instant volume balance strip above the volume columns. The strip’s colors show which of the buying or selling volume was greater, and colors are brighter if the total volume was above the total volume MA.
- Bottom pane : shows the volume balance MAs delta with markers 1 and 2. Given that this graphic has no price momentum component, I find quite eerie how it often looks like a momentum-based signal.
The default 5 minute intrabar resolution is used in combination with the weekly chart, which is excessive.
This script uses a special characteristic of the security() function’s behavior when it is sent to a resolution lower than the chart’s resolution. Details are given in the script’s comments. This method has the advantage of working under more circumstances than some of the other loop-based methods, but it also has its limits.
IMPORTANT
This is what you need to know:
- The method used does not work on the realtime bar—only on historical bars. Consequently, the volume column shown on the realtime bar is a normal volume column plotted in green or red, following price movement. The column will only show delta volume information after it closes and becomes a historical bar.
- The indicator only works on some chart resolutions: 5, 10, 15 and 30 minutes, 1, 2, 4, 6, and 12 hours, 1 day, 1 week and 1 month. The script’s code can be modified to run on other resolutions, but chart resolutions must be divisible by the lower resolution used for intrabars.
- Intrabar resolutions can be selected from 1, 5, 15, 30, 45 minutes, 1, 2, 3, 4 hours, 1 day, 1 week and 1 month. The intrabar resolution must of course be smaller than the chart’s resolution.
- Contrary to my other indicators where alerts must be configured to trigger “Once Per Bar Close” in order to avoid false triggers (or repainting), all this indicator’s alerts are designed to trigger using previous bar information since the indicator’s calculations in the realtime bar are not exact. Markers are not plotted with a negative offset; they appear at the beginning of the realtime bar following confirmation of the marker’s condition on the previous bar. Alerts for this indicator should thus be configured to trigger “Once Per Bar” so they trigger at the beginning of the realtime bar. Note that the penalty is not that great, as it is simply the instant between the close of the previous realtime bar and the opening of the next. The advantage of using this technique is that the indicator does not repaint; a marker that appears at the beginning of the realtime bar will never disappear.
- The script only plots information that is reliable in the realtime bar, i.e., total volume and markers. All other plots are set to n/a to prevent misleading traders.
- When the difference between the chart’s resolution and the lower resolution is too important, volume columns will not calculate for all bars in the dataset.
On Delta Volume
Buying or selling volume are misnomers, as every unit of volume transacted is both bought and sold by 2 different traders. There is no such thing as “buy only” or “sell only” volume, but trader lingo is riddled with original fabulations.
Without access to order book information, traders work with the assumption that when price moves up during a bar, there was more buying pressure than selling pressure. The built-in volume indicator available on TradingView uses this logic to color the volume columns green or red. While this script’s numbers are more precise because it analyses a number of intrabars to calculate its information, it uses the exact same imperfect logic to calculate its buying/selling/neutral sections.
Until Pine scripts can have access to how much volume was transacted at the bid/ask prices, our so-called buying/selling volume information will always be a mere proxy.
Divergences
You may wonder how there can be divergences between buying/selling volume information and price movement. This will sometimes be due to the methodology’s shortcomings we have just discussed, but divergences may also occur in instances where because of order book structure, it takes less volume to increase the price of an asset than it takes to decrease it.
As usual, divergences are points of interest because they reveal imbalances, which may or may not become turning points. I do not share the overwhelming enthusiasm traders have for divergences. To your pattern-hungry brain, the orange bars this indicator shows on chart will—as divergences on other indicators do–appear to often indicate turnarounds. My opinion is that reality is generally quite sobering, as many who have tried building automated rules based on divergences will tell you. I do not have hard numbers on the lack of performance of divergences—only many failed attempts to make them perform, which a few experienced strategy modelers I know share with me. Please don’t try to read too much into them. While they look great on past data, I find they are often difficult to use in realtime to make bets with good odds.
Thanks to:
- A guy called Kuan who commented on a Backtest Rookies presentation of an intrabar delta volume indicator using a for loop. The heart of “my” indicator is code borrowed from Kuan; I just built a hopefully useful wrapper around it.
- @theheirophant, my partner in the exploration of the sometimes weird abysses of security() ’s behavior at lower resolutions.
Golden Cross by -Westy-Quick Guide
- Yellow cross and green MA on top = Potential uptrend
- Yellow cross and red MA on top = Potential downtrend
A simple golden cross indicator of the green 50 and red 200 SMA with a yellow cross for ease of visibility and backtesting.
Generally, longer time frames more powerful signals but are less frequent. I typically use it on the 4 hour, daily and weekly.
ck - Crypto Correlation IndicatorA simple Correlation Indicator initially configured for Crypto Trader use (but other markets can use this too).
It plots the correlation between the current chart (say BTCUSD ) versus 4 user-definable indices, currency pairs, stocks etc.
By default, the indicator is preconfigured for:
GOLD (Oz/$),
Dow Jones Index (DJI),
Standard & Poor 500 Index (SPX) ,
Dollar Index ( DXY )
You can set the period (currently 1D resolution) in the "Period" box in the settings, valid inputs are:
minutes (number), days (1D, 2D, 3D etc), weeks (1W, 2W etc), months (1M, 2M etc)
Length is the lagging period/smoothing applied - default is 14
When changing comparison instruments/tickers, you may find it useful to prefix the exchange with the instrument's ticker, for example:
Binance:BTCUSDT, NYSE:GOOG etc
*** Idea originally from the brilliant Backtest Rookies - backtest-rookies.com ***
Alto Basso Swing Pivots + Barry Support Resistance Levels2 indicators, 1 script: swing pivots and Barry support resistance levels
Alto
high swing pivot
Basso
low swing pivot
Dal Segno
lookback period length for swing pivots
Barry Length
length for support resistance calculation
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Use swing pivots for confirmation of new structure levels on short term
Barry support resistance levels in proximity to standard pivots or Fibonacci levels may indicate greater strength
credit to BacktestRookies and likebike
stay ♯
Example: Dal Segno 13, Barry Length 21
52 Week & Daily & Current High/LowThis Indicator Plots a 52 Week High and Low equal or below daily.
A 52 Daily High and Low on timeframes below daily.
A 52 Bars High and Low on timeframes on any timeFrame.
Based on 52 Week High/Low by BacktestRookies
Trend v4.0 Another updateYet another update, default settings can be customized to your needs. Be aware that while this is similar to the other versions, this can only repaint an active bar, but that slows it down by one period. You are warned. Be that as it may, the basic idea is the same; trying to capture the really strong moves into overbought or oversold territory as defined by Relative Strength index. In RSI mode, you can see the smoothing has slowed it down a bit, but warrants backtesting.
First green bar go long, First red bar go short, first white bar possible trend exhaustion. Or use crossovers and such, play with the inputs OB/OS, RSI length, signal length, tick length, swing length, as I said customize to your tastes. I offer no surety as to its efficacy, but we all learn.
Trade Responsibly,
Shiroki
NQ Hourly Retracements - 12y Stats with LevelsHour Stats with Levels - TradingView Indicator Description
IMPORTANT: NQ FUTURES ONLY
This indicator is specifically designed for and calibrated to NQ (Nasdaq-100 E-mini) futures only. The statistical data is derived exclusively from 13 years of NQ price action (2013-2025). Do not use this indicator on any other asset, ticker, or market as the statistics will not be applicable and may lead to incorrect trading decisions.
Overview
"Hour Stats with Levels" is a statistical analysis indicator that provides real-time probability-based insights into hourly price behavior patterns. The indicator combines historical pattern recognition with live price action to help traders anticipate potential sweep and reversal scenarios within each trading hour.
Originality and Core Concept
This indicator is based on a comprehensive statistical analysis of 12y years of 1-minute NQ futures data, examining a specific price pattern: when an hourly candle opens inside the previous hour's range. Unlike generic support/resistance indicators, this tool provides hour-specific, context-aware probabilities based on 30,000+ historical occurrences of this pattern.
The originality lies in three key areas:
Pattern-Specific Statistics: Rather than applying generic technical analysis, the indicator only activates when the current hour opens within the previous hour's range, providing relevant statistics for this exact scenario.
Context-Aware Probabilities: Statistics are differentiated based on whether the current hour opened above or below the previous hour's open, recognizing that bullish and bearish opening contexts produce different behavioral patterns.
Comprehensive Retracement Tracking: The indicator tracks four independent retracement levels after a sweep occurs, showing the probability of price returning to: the swept level itself (90+% probability), the 50% level, the current hour's open, and the opposite extreme.
How It Works
The Core Pattern
The indicator monitors a specific price structure:
Setup Condition: The current hourly candle opens inside (between) the previous hour's high and low
Sweep Event: Price then breaks above the previous high (high sweep) or below the previous low (low sweep)
Retracement Analysis: After a sweep, the indicator tracks whether price retraces to key levels
Statistical Foundation
The underlying analysis processed 1-minute bar data from 2013-2025, identifying every instance where an hourly candle opened inside the previous hour's range. For each occurrence, the system tracked:
Whether the high, low, or both were swept during that hour
The distance of the sweep measured as a percentage of the previous hour's range
Whether price retraced to four key levels: the swept level, the 50% point, the current open, and the opposite extreme
These measurements were aggregated for all 24 hours of the trading day, with separate statistics for bullish contexts (opening above previous open) and bearish contexts (opening below previous open), creating 48 unique statistical profiles.
Sweep Distance Percentiles
The "reversal levels" are drawn based on historical sweep distance distributions:
25th Percentile: 75% of historical sweeps were larger than this distance. This represents a conservative reversal zone where smaller, contained sweeps typically reverse.
Median (50th Percentile): The midpoint of all historical sweep distances. Half of all sweeps reversed before reaching this level, half extended beyond it.
75th Percentile: Only 25% of sweeps extended beyond this distance. This represents an extended sweep zone where price has historically shown exhaustion.
For example, if the previous hour's range was 20 points and the median high sweep distance is 40% of range, the median reversal level would be placed 8 points above the previous high.
How to Use the Indicator
Sweeps were calculated using 1m data - as such, it's recommended to use the indicator on a 1min chart
Visual Components
Hour Delimiter (Gray Vertical Line)
Marks the start of each new hour
Helps identify when new statistics become active
Sweep Markers
Green "H" label: High sweep has occurred this hour
Red "L" label: Low sweep has occurred this hour
Markers appear on the exact bar where the sweep happened
Target Levels (Blue Lines)
Prev Open: Previous hour's opening price
Prev High: Previous hour's highest price (sweep target)
Prev Low: Previous hour's lowest price (sweep target)
Prev 50%: Midpoint of previous hour's range
Current Open: Current hour's opening price (key retracement target)
Reversal Levels (Purple Dashed Lines)
Positioned beyond the previous high/low based on historical sweep percentiles
Three levels above previous high (for high sweeps)
Three levels below previous low (for low sweeps)
These represent statistically-derived zones where sweeps typically exhaust
The Statistics Table
The table dynamically updates each hour and displays different statistics based on whether the current hour opened above or below the previous hour's open.
Status Row
Shows current state: waiting for sweep, or which sweep(s) have occurred
If waiting, indicates which sweep is more probable based on historical data
SWEEP PROBABILITIES Section
High Sweep: Historical probability (%) that price will sweep the previous high this hour
Low Sweep: Historical probability (%) that price will sweep the previous low this hour
Both Sweeps: Historical probability (%) that price will sweep both levels this hour
These probabilities are derived from counting how many times each pattern occurred in similar historical contexts. For example, "High Sweep: 73.18%" means that in 73.18% of historical occurrences where the hour opened in this same context (same hour of day, same position relative to previous open), price swept the previous high before the hour closed.
AFTER HIGH SWEEP → Section
These statistics activate only after a high sweep has occurred. They show the probability of price retracing to various levels:
→ Prev High: Probability that price returns to (or below) the level it just swept. This is typically 90%+ because sweeps often act as "false breakouts" or liquidity grabs before reversal.
→ 50% Level: Probability that price retraces at least halfway back into the previous hour's range. This represents a moderate retracement.
→ Current Open: Probability that price retraces all the way back to where the current hour opened. This indicates a complete reversal of the sweep move.
→ Prev Low: Probability that price retraces entirely through the previous range to touch the opposite extreme. This represents a full reversal pattern.
AFTER LOW SWEEP → Section
Mirror of the above, but for low sweeps:
→ Prev Low: Retracement to the swept low level (90%+ probability)
→ 50% Level: Retracement to middle of range
→ Current Open: Full retracement to current hour's open
→ Prev High: Complete reversal to opposite extreme
Important Note on Retracement Statistics: These percentages are tracked independently. A 90% probability of returning to the swept level doesn't mean there's only a 10% chance of deeper retracement. Price can (and often does) retrace through multiple levels sequentially. The percentages show how many times price reached at least that level, not where it stopped.
Trading Applications
Anticipating Sweeps
When an hour opens inside the previous range, check the probabilities. If "High Sweep: 70%" and "Low Sweep: 30%", you know there's a 70% historical likelihood of an upside sweep occurring this hour. This doesn't guarantee it will happen, but provides statistical context for potential setups.
Reversal Trading
The most reliable pattern in the data is the 90%+ retracement probability to swept levels. When a sweep occurs, traders can anticipate a retracement back to at least the swept level in the vast majority of cases. The reversal level percentiles help identify where sweeps may exhaust.
Position Management
The retracement probabilities help manage existing positions. For example, if you're long and a high sweep occurs, you know there's a 90%+ chance of at least some retracement to the swept level, which might inform profit-taking or stop-loss decisions.
Confluence with Current Open
The "Current Open" retracement statistics (typically 60-70%) highlight the magnetic quality of the hour's opening price. After a sweep, price frequently returns to test this level.
Customization Options
The indicator offers extensive visual customization:
Toggle on/off: hour delimiters, sweep markers, target levels, reversal levels, statistics table
Customize colors, line widths, and styles for all visual elements
Adjust label sizes and table position
Show/hide individual target levels and reversal percentiles
Limitations and Considerations
Pattern-Specific: The indicator only provides statistics when the current hour opens inside the previous hour's range. If the hour opens outside this range (gaps up or down), the statistics are not applicable.
Historical Probabilities: The percentages represent historical frequencies, not predictions. A 70% probability means it happened 70% of the time historically, not that it will definitely happen 7 out of 10 times going forward.
NQ-Specific Calibration: All statistics are derived from NQ futures data. Market behavior, volatility, and patterns differ across assets.
Hour-Specific Behavior: Different hours show dramatically different statistics. For example, the 9 AM EST hour (market open) shows much higher sweep probabilities (80%+) than the 5 PM EST hour (30-50%) due to differing liquidity and volatility conditions.
No Guarantee of Execution: While a 90% retracement probability is high, it means 10% of the time, price did NOT retrace. Always use proper risk management.
Technical Notes
The indicator uses hourly timeframe data via request.security() to determine previous hour values
Sweep detection occurs in real-time on the chart's timeframe
Statistics are hardcoded from the comprehensive backtested analysis (not calculated on-the-fly)
The indicator stores static values at the start of each hour to ensure consistency as the hour progresses
All percentage values are rounded to one decimal place for clarity
This indicator provides a statistically-grounded framework for understanding hourly price behavior in NQ futures. By combining real-time pattern detection with comprehensive historical analysis, it offers traders probabilistic insights to inform decision-making process within the specific context of each trading hour.
Liquidity Levels Pro Tool - thewallranka
Liquidity Levels Pro Tool is a market-structure and liquidity-mapping indicator designed to help discretionary futures and index traders identify statistically relevant price levels where reactions, continuations, or liquidity sweeps are more likely to occur.
This script is a decision-support tool, not a signal generator. It does not issue buy/sell alerts or predict future price movement. Instead, it organizes and scores liquidity information so traders can make their own contextual decisions.
What this indicator does
The script continuously detects and maintains liquidity zones derived from price pivots, then evaluates those zones using multiple structural and contextual factors:
Repeated price interaction (touches)
Freshness (time since last interaction)
Confluence with key reference levels
Reaction behavior after contact
Session relevance (RTH vs overnight)
Market regime (trend vs mean reversion)
Time-of-day effects (open, midday, power hour)
Only the most relevant zones—based on a dynamic scoring system—are displayed to reduce chart clutter and focus attention on levels that have historically mattered.
Core components
1. Liquidity Zones
Zones are built from pivot highs and lows and expanded into areas using a configurable tick-based padding. Nearby zones are merged to avoid redundancy.
Each zone is continuously evaluated and assigned a score (0–100) reflecting its relative importance.
2. Zone Scoring (No Lookahead)
Zone scores are based on:
Number of confirmed interactions
Recency of the last touch
Confluence with prior day/week levels, VWAP, and Opening Range
Reaction quality after touches (speed and follow-through)
Session alignment (zones that “work” in the current session are favored)
Penalties after liquidity sweeps
Zones are not forward-looking and do not rely on future data.
3. Context Engine
The script classifies the current environment using VWAP slope and distance:
Trend (up or down)
Mean reversion
Mixed/transition
Time-of-day context (Open, Midday, Power Hour) is also tracked internally and influences zone scoring.
This context is displayed in the HUD to support situational awareness, not automated decisions.
4. Liquidity Sweeps
Optional sweep detection highlights situations where price trades beyond a zone and closes back inside, indicating potential stop runs or failed breakouts.
Sweeps are rate-limited and applied conservatively to avoid visual noise.
5. Trade Planning Levels (Optional)
When enabled, the script highlights the nearest high-quality liquidity level above and below price based on score thresholds.
These are intended as reference targets, not trade entries or exits.
HUD (Heads-Up Display)
The on-chart HUD summarizes:
Key reference levels (prior day/week, Opening Range)
Nearest strong liquidity above/below price
Market regime and time-of-day context
Distance to levels (ticks or points)
The HUD is fully optional, positionable, and includes resizable modes (Small / Medium / Large) to fit different chart layouts.
How to use this tool
This indicator is best used as part of a discretionary trading process, for example:
Identifying areas where price is more likely to react or pause
Framing trades around higher-quality structure instead of arbitrary levels
Filtering setups based on session and regime context
Managing expectations near known liquidity rather than chasing price
It is intentionally designed not to provide trade signals.
Limitations and important notes
This script does not predict outcomes or guarantee reactions
High-scoring zones can still fail
Liquidity behavior is context-dependent and probabilistic
No performance claims or backtested results are provided
The indicator should not be used in isolation
Past behavior does not imply future results.
Chart and usage notes
The script is intended for standard time-based charts
Recommended for liquid futures and index products
Use a clean chart for clarity when publishing or sharing
No external indicators are required
Final note
Liquidity Levels Pro (Tool) — v6 is designed to organize complex market structure into a clear, readable framework, allowing traders to focus on execution and risk management rather than raw level detection.
This script reflects an analytical approach to intraday liquidity and structure, not an automated trading system.
Smart Money Toolkit - PD Engine Bias Map [KedArc Quant]Description
Smart Money is an advanced multi-layer Smart Money Concepts framework that automatically detects structure shifts, premium-discount zones, and institutional order flow.
It is built around the PD Engine, which calculates the midpoint of the most recent market swing and dynamically determines BUY or SELL bias based on where current price trades relative to that equilibrium. This toolkit visualizes structure, order blocks, and bias context in one clean map, giving traders an institutional-grade view without unnecessary signal clutter.
Why It Is Unique
- All CHoCH, BOS, Order Block, FVG, and PD logic are coded from scratch.
- Uses true equilibrium (50 percent PD midpoint) for dynamic bias.
- Optimized for stability and non-repainting behavior.
- Designed for clarity with minimal, performance-safe visuals.
Entry and Exit Logic (Discretionary Framework)
- This toolkit is not a signal generator. It provides market context that guides discretionary trading.
BUY Bias (Discount Zone)
- Price trades below PD Mid: the market is in discount.
- Wait for a bullish CHoCH or reaction from a demand OB or FVG before buying.
- Target 1 = PD Mid. Target 2 = next opposite OB or FVG.
SELL Bias (Premium Zone)
- Price trades above PD Mid: the market is in premium.
- Wait for a bearish CHoCH or reaction from a supply OB or FVG before shorting.
- Target 1 = PD Mid. Target 2 = next opposite OB or FVG.
Institutional concept sequence: Bias → Structure Shift → Confirmation → Execution.
Input Configuration
Swing Sensitivity - Determines how far back to identify HH and LL pivots.
OB / FVG Detection - Toggles visual Order Block or Fair Value Gap zones.
PD Engine - Shows PD midpoint line, zone shading, and bias table.
Multi-TF Bias Sync - Optionally reads a higher timeframe bias for confirmation.
Color Themes - Switch between light, dark, or institutional palettes.
Formula / Logic Summary
Concept Formula
PD Mid (Equilibrium) (Recent Swing High + Recent Swing Low) / 2
BUY Bias close < PD Mid
SELL Bias close > PD Mid
CHoCH / BOS Pivot-based structure reversal: HH→LL or LL→HH
Order Block Last bullish or bearish candle before displacement.
FVG Gap between prior candle high/low and next candle range.
These formulas follow the structure used in institutional Smart Money Concepts.
How It Helps Traders
- Shows institutional premium and discount zones visually.
- Defines clear directional bias before entry.
- Combines structure, order blocks, FVG, and equilibrium in one layout.
- Works on any timeframe or asset.
- Prevents emotional trades by giving objective bias context.
Glossary
PD Mid Midpoint between recent swing high and low (market fair value).
Premium Zone Price above PD Mid; sellers control.
Discount Zone Price below PD Mid; buyers control.
CHoCH Change of Character, first reversal signal.
BOS Break of Structure, trend continuation confirmation.
OB Order Block, last institutional candle before move.
FVG Fair Value Gap, price imbalance often revisited.
FAQ
Q: Is this a signal indicator?
A: No. It is a contextual framework that supports manual decision-making.
Q: Does it repaint?
A: No. All structure logic is confirmed on bar close.
Q: Does it work on all markets?
A: Yes. It is purely price-based and timeframe independent.
Q: When does bias change?
A: Only after a new confirmed swing high or low.
Q: Can it be backtested?
A: You can build strategies on top of this context using your own entry and exit rules.
Disclaimer
This script is provided for educational purposes only.
It is not financial advice.
Trading carries risk. Past performance does not guarantee future results.
Use proper risk management and test on demo accounts before applying to live markets.
Dimensional Resonance ProtocolDimensional Resonance Protocol
🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION
The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states.
The Complexity Hypothesis:
Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics.
Takens' Embedding Theorem (1981):
A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation.
Mathematical Foundation:
From single observable x(t), create embedding vectors:
X(t) =
Where:
• d = Embedding dimension (default 5)
• τ = Time delay (default 3 bars)
• x(t) = Price or return at time t
Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series.
Why This Matters:
Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect:
• Stable regions : Predictable behavior (trade opportunities)
• Chaotic regions : Unpredictable behavior (avoid trading)
• Critical transitions : Phase changes between regimes
Phase Space Magnitude Calculation:
phase_magnitude = sqrt(Σ ² for i = 0 to d-1)
This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation.
📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA)
Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states?
Recurrence Plot Foundation:
A recurrence occurs when two phase space points are closer than threshold ε:
R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0
This creates a binary matrix showing when the system revisits similar states.
Key RQA Metrics:
1. Recurrence Rate (RR):
RR = (Number of recurrent points) / (Total possible pairs)
• RR near 0: System never repeats (highly stochastic)
• RR = 0.1-0.3: Moderate recurrence (tradeable patterns)
• RR > 0.5: System stuck in attractor (ranging market)
• RR near 1: System frozen (no dynamics)
Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck.
2. Determinism (DET):
Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths).
DET = (Recurrence points on diagonals) / (Total recurrence points)
• DET < 0.3: Random dynamics
• DET = 0.3-0.7: Moderate determinism (patterns with noise)
• DET > 0.7: Strong determinism (technical patterns reliable)
Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck).
Threshold Selection (ε):
Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns.
🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT
Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns.
Algorithm (Bandt & Pompe, 2002):
1. Take overlapping windows of length n (default n=4)
2. For each window, record the rank order pattern
Example: → pattern (ranks from lowest to highest)
3. Count frequency of each possible pattern
4. Calculate Shannon entropy of pattern distribution
Mathematical Formula:
H_perm = -Σ p(π) · ln(p(π))
Where π ranges over all n! possible permutations, p(π) is the probability of pattern π.
Normalized to :
H_norm = H_perm / ln(n!)
Interpretation:
• H < 0.3 : Very ordered, crystalline structure (strong trending)
• H = 0.3-0.5 : Ordered regime (tradeable with patterns)
• H = 0.5-0.7 : Moderate complexity (mixed conditions)
• H = 0.7-0.85 : Complex dynamics (challenging to trade)
• H > 0.85 : Maximum entropy (nearly random, avoid)
Entropy Regime Classification:
DRP classifies markets into five entropy regimes:
• CRYSTALLINE (H < 0.3): Maximum order, persistent trends
• ORDERED (H < 0.5): Clear patterns, momentum strategies work
• MODERATE (H < 0.7): Mixed dynamics, adaptive required
• COMPLEX (H < 0.85): High entropy, mean reversion better
• CHAOTIC (H ≥ 0.85): Near-random, minimize trading
Why Permutation Entropy?
Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy:
• Works directly on time series
• Robust to monotonic transformations
• Computationally efficient
• Captures temporal structure, not just distribution
• Immune to outliers (uses ranks, not values)
⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY
The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos.
Physical Meaning:
Two trajectories starting infinitely close will diverge at exponential rate e^(λt):
Distance(t) ≈ Distance(0) × e^(λt)
Interpretation:
• λ > 0 : Positive Lyapunov exponent = CHAOS
- Small errors grow exponentially
- Long-term prediction impossible
- System is sensitive, unpredictable
- AVOID TRADING
• λ ≈ 0 : Near-zero = CRITICAL STATE
- Edge of chaos
- Transition zone between order and disorder
- Moderate predictability
- PROCEED WITH CAUTION
• λ < 0 : Negative Lyapunov exponent = STABLE
- Small errors decay
- Trajectories converge
- System is predictable
- OPTIMAL FOR TRADING
Estimation Method:
DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars):
For each bar i in window:
δ₀ = |x - x | (initial separation)
δ₁ = |x - x | (previous separation)
if δ₁ > 0:
ratio = δ₀ / δ₁
log_ratios += ln(ratio)
λ ≈ average(log_ratios)
Stability Classification:
• STABLE : λ < 0 (negative growth rate)
• CRITICAL : |λ| < 0.1 (near neutral)
• CHAOTIC : λ > 0.2 (strong positive growth)
Signal Filtering:
By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down.
📐 HIGUCHI FRACTAL DIMENSION
Fractal dimension measures self-similarity and complexity of the price trajectory.
Theoretical Background:
A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve):
• D ≈ 1.0 : Smooth, persistent trending
• D ≈ 1.5 : Random walk (Brownian motion)
• D ≈ 2.0 : Highly irregular, space-filling
Higuchi Method (1988):
For a time series of length N, construct k different curves by taking every k-th point:
L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k)
For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k):
D = slope of log(L) vs log(1/k)
Market Interpretation:
• D < 1.35 : Strong trending, persistent (Hurst > 0.5)
- TRENDING regime
- Momentum strategies favored
- Breakouts likely to continue
• D = 1.35-1.45 : Moderate persistence
- PERSISTENT regime
- Trend-following with caution
- Patterns have meaning
• D = 1.45-1.55 : Random walk territory
- RANDOM regime
- Efficiency hypothesis holds
- Technical analysis least reliable
• D = 1.55-1.65 : Anti-persistent (mean-reverting)
- ANTI-PERSISTENT regime
- Oscillator strategies work
- Overbought/oversold meaningful
• D > 1.65 : Highly complex, choppy
- COMPLEX regime
- Avoid directional bets
- Wait for regime change
Signal Filtering:
Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning.
🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW
Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer.
Schreiber's Definition (2000):
Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future:
TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past)
Where H is Shannon entropy.
Key Properties:
1. Directional : TE(X→Y) ≠ TE(Y→X) in general
2. Non-linear : Detects complex causal relationships
3. Model-free : No assumptions about functional form
4. Lag-independent : Captures delayed causal effects
Three Causal Flows Measured:
1. Volume → Price (TE_V→P):
Measures how much volume patterns predict price changes.
• TE > 0 : Volume provides predictive information about price
- Institutional participation driving moves
- Volume confirms direction
- High reliability
• TE ≈ 0 : No causal flow (weak volume/price relationship)
- Volume uninformative
- Caution on signals
• TE < 0 (rare): Suggests price leading volume
- Potentially manipulated or thin market
2. Volatility → Momentum (TE_σ→M):
Does volatility expansion predict momentum changes?
• Positive TE : Volatility precedes momentum shifts
- Breakout dynamics
- Regime transitions
3. Structure → Price (TE_S→P):
Do support/resistance patterns causally influence price?
• Positive TE : Structural levels have causal impact
- Technical levels matter
- Market respects structure
Net Causal Flow:
Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P
• Net > +0.1 : Bullish causal structure
• Net < -0.1 : Bearish causal structure
• |Net| < 0.1 : Neutral/unclear causation
Causal Gate:
For signal confirmation, NEXUS requires:
• Buy signals : TE_V→P > 0 AND Net_Flow > 0.05
• Sell signals : TE_V→P > 0 AND Net_Flow < -0.05
This ensures volume is actually driving price (causal support exists), not just correlated noise.
Implementation Note:
Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner.
🌊 HILBERT PHASE COHERENCE
Phase coherence measures synchronization across market dimensions using Hilbert transform analysis.
Hilbert Transform Theory:
For a signal x(t), the Hilbert transform H (t) creates an analytic signal:
z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t))
Where:
• A(t) = Instantaneous amplitude
• φ(t) = Instantaneous phase
Instantaneous Phase:
φ(t) = arctan(H (t) / x(t))
The phase represents where the signal is in its natural cycle—analogous to position on a unit circle.
Four Dimensions Analyzed:
1. Momentum Phase : Phase of price rate-of-change
2. Volume Phase : Phase of volume intensity
3. Volatility Phase : Phase of ATR cycles
4. Structure Phase : Phase of position within range
Phase Locking Value (PLV):
For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization:
PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩|
Where ⟨·⟩ is time average over window.
Interpretation:
• PLV = 0 : Completely random phase relationship (no synchronization)
• PLV = 0.5 : Moderate phase locking
• PLV = 1 : Perfect synchronization (phases locked)
Pairwise PLV Calculations:
• PLV_momentum-volume : Are momentum and volume cycles synchronized?
• PLV_momentum-structure : Are momentum cycles aligned with structure?
• PLV_volume-structure : Are volume and structural patterns in phase?
Overall Phase Coherence:
Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3
Signal Confirmation:
Emergence signals require coherence ≥ threshold (default 0.70):
• Below 0.70: Dimensions not synchronized, no coherent market state
• Above 0.70: Dimensions in phase, coherent behavior emerging
Coherence Direction:
The summed phase angles indicate whether synchronized dimensions point bullish or bearish:
Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure)
• Direction > 0 : Phases pointing upward (bullish synchronization)
• Direction < 0 : Phases pointing downward (bearish synchronization)
🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT
The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence.
Eight Components with Weights:
1. Phase Coherence (20%):
Direct contribution: coherence × 0.20
Measures dimensional synchronization.
2. Entropy Regime (15%):
Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0
Rewards low entropy (ordered, predictable states).
3. Lyapunov Stability (12%):
• λ < 0 (stable): +0.12
• |λ| < 0.1 (critical): +0.08
• λ > 0.2 (chaotic): +0.0
Requires stable, predictable dynamics.
4. Fractal Dimension Trending (12%):
Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0
Rewards trending fractal structure (D < 1.45).
5. Dimensional Resonance (12%):
Contribution: |dimensional_resonance| × 0.12
Measures alignment across momentum, volume, structure, volatility dimensions.
6. Causal Flow Strength (9%):
Contribution: |net_causal_flow| × 0.09
Rewards strong causal relationships.
7. Phase Space Embedding (10%):
Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0
Rewards strong trajectory in reconstructed phase space.
8. Recurrence Quality (10%):
Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8
Rewards deterministic patterns with moderate recurrence.
Total Emergence Score:
E = Σ(components) ∈
Capped at 1.0 maximum.
Emergence Direction:
Separate calculation determining bullish vs bearish:
• Dimensional resonance sign
• Net causal flow sign
• Phase magnitude correlation with momentum
Signal Threshold:
Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals.
Why Emergence Matters:
Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order.
These are the highest-probability trade opportunities because the entire system is resonating in the same direction.
🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE
DRP generates two tiers of signals with different requirements:
TIER 1: EMERGENCE SIGNALS (Primary)
Requirements:
1. Emergence score ≥ threshold (default 0.75)
2. Phase coherence ≥ threshold (default 0.70)
3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish)
4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction
5. Stability zone (if enabled): λ < 0 or |λ| < 0.1
6. Price confirmation: Close > open (bulls) or close < open (bears)
7. Cooldown satisfied: bars_since_signal ≥ cooldown_period
EMERGENCE BUY:
• All above conditions met with bullish direction
• Market has achieved coherent bullish state
• Multiple dimensions synchronized upward
EMERGENCE SELL:
• All above conditions met with bearish direction
• Market has achieved coherent bearish state
• Multiple dimensions synchronized downward
Premium Emergence:
When signal_quality (emergence_score × phase_coherence) > 0.7:
• Displayed as ★ star symbol
• Highest conviction trades
• Maximum dimensional alignment
Standard Emergence:
When signal_quality 0.5-0.7:
• Displayed as ◆ diamond symbol
• Strong signals but not perfect alignment
TIER 2: RESONANCE SIGNALS (Secondary)
Requirements:
1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish)
2. Fractal dimension < 1.5 (trending/persistent regime)
3. Price confirmation matches direction
4. NOT in chaotic regime (λ < 0.2)
5. Cooldown satisfied
6. NO emergence signal firing (resonance is fallback)
RESONANCE BUY:
• Dimensional alignment without full emergence
• Trending fractal structure
• Moderate conviction
RESONANCE SELL:
• Dimensional alignment without full emergence
• Bearish resonance with trending structure
• Moderate conviction
Displayed as small ▲/▼ triangles with transparency.
Signal Hierarchy:
IF emergence conditions met:
Fire EMERGENCE signal (★ or ◆)
ELSE IF resonance conditions met:
Fire RESONANCE signal (▲ or ▼)
ELSE:
No signal
Cooldown System:
After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions.
Cooldown tracks using bar_index:
bars_since_signal = current_bar_index - last_signal_bar_index
cooldown_ok = bars_since_signal >= cooldown_period
🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY
DRP provides rich visual feedback across four distinct layers:
LAYER 1: COHERENCE FIELD (Background)
Colored background intensity based on phase coherence:
• No background : Coherence < 0.5 (incoherent state)
• Faint glow : Coherence 0.5-0.7 (building coherence)
• Stronger glow : Coherence > 0.7 (coherent state)
Color:
• Cyan/teal: Bullish coherence (direction > 0)
• Red/magenta: Bearish coherence (direction < 0)
• Blue: Neutral coherence (direction ≈ 0)
Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible.
LAYER 2: STABILITY/CHAOS ZONES
Background color indicating Lyapunov regime:
• Green tint (95% transparent): λ < 0, STABLE zone
- Safe to trade
- Patterns meaningful
• Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone
- Edge of chaos
- Moderate risk
• Red tint (85% transparent): λ > 0.2, CHAOTIC zone
- Avoid trading
- Unpredictable behavior
LAYER 3: DIMENSIONAL RIBBONS
Three EMAs representing dimensional structure:
• Fast ribbon : EMA(8) in cyan/teal (fast dynamics)
• Medium ribbon : EMA(21) in blue (intermediate)
• Slow ribbon : EMA(55) in red/magenta (slow dynamics)
Provides visual reference for multi-scale structure without cluttering with raw phase space data.
LAYER 4: CAUSAL FLOW LINE
A thicker line plotted at EMA(13) colored by net causal flow:
• Cyan/teal : Net_flow > +0.1 (bullish causation)
• Red/magenta : Net_flow < -0.1 (bearish causation)
• Gray : |Net_flow| < 0.1 (neutral causation)
Shows real-time direction of information flow.
EMERGENCE FLASH:
Strong background flash when emergence signals fire:
• Cyan flash for emergence buy
• Red flash for emergence sell
• 80% transparency for visibility without obscuring price
📊 COMPREHENSIVE DASHBOARD
Real-time monitoring of all complexity metrics:
HEADER:
• 🌀 DRP branding with gold accent
CORE METRICS:
EMERGENCE:
• Progress bar (█ filled, ░ empty) showing 0-100%
• Percentage value
• Direction arrow (↗ bull, ↘ bear, → neutral)
• Color-coded: Green/gold if active, gray if low
COHERENCE:
• Progress bar showing phase locking value
• Percentage value
• Checkmark ✓ if ≥ threshold, circle ○ if below
• Color-coded: Cyan if coherent, gray if not
COMPLEXITY SECTION:
ENTROPY:
• Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC)
• Numerical value (0.00-1.00)
• Color: Green (ordered), gold (moderate), red (chaotic)
LYAPUNOV:
• State (STABLE/CRITICAL/CHAOTIC)
• Numerical value (typically -0.5 to +0.5)
• Status indicator: ● stable, ◐ critical, ○ chaotic
• Color-coded by state
FRACTAL:
• Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX)
• Dimension value (1.0-2.0)
• Color: Cyan (trending), gold (random), red (complex)
PHASE-SPACE:
• State (STRONG/ACTIVE/QUIET)
• Normalized magnitude value
• Parameters display: d=5 τ=3
CAUSAL SECTION:
CAUSAL:
• Direction (BULL/BEAR/NEUTRAL)
• Net flow value
• Flow indicator: →P (to price), P← (from price), ○ (neutral)
V→P:
• Volume-to-price transfer entropy
• Small display showing specific TE value
DIMENSIONAL SECTION:
RESONANCE:
• Progress bar of absolute resonance
• Signed value (-1 to +1)
• Color-coded by direction
RECURRENCE:
• Recurrence rate percentage
• Determinism percentage display
• Color-coded: Green if high quality
STATE SECTION:
STATE:
• Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING
• Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning)
• Color-coded by state
SIGNALS:
• E: count of emergence signals
• R: count of resonance signals
⚙️ KEY PARAMETERS EXPLAINED
Phase Space Configuration:
• Embedding Dimension (3-10, default 5): Reconstruction dimension
- Low (3-4): Simple dynamics, faster computation
- Medium (5-6): Balanced (recommended)
- High (7-10): Complex dynamics, more data needed
- Rule: d ≥ 2D+1 where D is true dimension
• Time Delay (τ) (1-10, default 3): Embedding lag
- Fast markets: 1-2
- Normal: 3-4
- Slow markets: 5-10
- Optimal: First minimum of mutual information (often 2-4)
• Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity
- Tight (0.01-0.05): Very similar states only
- Medium (0.08-0.15): Balanced
- Loose (0.20-0.50): Liberal matching
Entropy & Complexity:
• Permutation Order (3-7, default 4): Pattern length
- Low (3): 6 patterns, fast but coarse
- Medium (4-5): 24-120 patterns, balanced
- High (6-7): 720-5040 patterns, fine-grained
- Note: Requires window >> order! for stability
• Entropy Window (15-100, default 30): Lookback for entropy
- Short (15-25): Responsive to changes
- Medium (30-50): Stable measure
- Long (60-100): Very smooth, slow adaptation
• Lyapunov Window (10-50, default 20): Stability estimation window
- Short (10-15): Fast chaos detection
- Medium (20-30): Balanced
- Long (40-50): Stable λ estimate
Causal Inference:
• Enable Transfer Entropy (default ON): Causality analysis
- Keep ON for full system functionality
• TE History Length (2-15, default 5): Causal lookback
- Short (2-4): Quick causal detection
- Medium (5-8): Balanced
- Long (10-15): Deep causal analysis
• TE Discretization Bins (4-12, default 6): Binning granularity
- Few (4-5): Coarse, robust, needs less data
- Medium (6-8): Balanced
- Many (9-12): Fine-grained, needs more data
Phase Coherence:
• Enable Phase Coherence (default ON): Synchronization detection
- Keep ON for emergence detection
• Coherence Threshold (0.3-0.95, default 0.70): PLV requirement
- Loose (0.3-0.5): More signals, lower quality
- Balanced (0.6-0.75): Recommended
- Strict (0.8-0.95): Rare, highest quality
• Hilbert Smoothing (3-20, default 8): Phase smoothing
- Low (3-5): Responsive, noisier
- Medium (6-10): Balanced
- High (12-20): Smooth, more lag
Fractal Analysis:
• Enable Fractal Dimension (default ON): Complexity measurement
- Keep ON for full analysis
• Fractal K-max (4-20, default 8): Scaling range
- Low (4-6): Faster, less accurate
- Medium (7-10): Balanced
- High (12-20): Accurate, slower
• Fractal Window (30-200, default 50): FD lookback
- Short (30-50): Responsive FD
- Medium (60-100): Stable FD
- Long (120-200): Very smooth FD
Emergence Detection:
• Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence
- Sensitive (0.5-0.65): More signals
- Balanced (0.7-0.8): Recommended
- Strict (0.85-0.95): Rare signals
• Require Causal Gate (default ON): TE confirmation
- ON: Only signal when causality confirms
- OFF: Allow signals without causal support
• Require Stability Zone (default ON): Lyapunov filter
- ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical)
- OFF: Allow signals in chaotic regimes (risky)
• Signal Cooldown (1-50, default 5): Minimum bars between signals
- Fast (1-3): Rapid signal generation
- Normal (4-8): Balanced
- Slow (10-20): Very selective
- Ultra (25-50): Only major regime changes
Signal Configuration:
• Momentum Period (5-50, default 14): ROC calculation
• Structure Lookback (10-100, default 20): Support/resistance range
• Volatility Period (5-50, default 14): ATR calculation
• Volume MA Period (10-50, default 20): Volume normalization
Visual Settings:
• Customizable color scheme for all elements
• Toggle visibility for each layer independently
• Dashboard position (4 corners) and size (tiny/small/normal)
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: System Familiarization (Week 1)
Goal: Understand complexity metrics and dashboard interpretation
Setup:
• Enable all features with default parameters
• Watch dashboard metrics for 500+ bars
• Do NOT trade yet
Actions:
• Observe emergence score patterns relative to price moves
• Note coherence threshold crossings and subsequent price action
• Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC)
• Correlate Lyapunov state with signal reliability
• Track which signals appear (emergence vs resonance frequency)
Key Learning:
• When does emergence peak? (usually before major moves)
• What entropy regime produces best signals? (typically ORDERED or MODERATE)
• Does your instrument respect stability zones? (stable λ = better signals)
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to instrument characteristics
Requirements:
• Understand basic dashboard metrics from Phase 1
• Have 1000+ bars of history loaded
Embedding Dimension & Time Delay:
• If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2)
• If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5)
• Sweet spot: 4-8 emergence signals per 100 bars
Coherence Threshold:
• Check dashboard: What's typical coherence range?
• If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65
• If coherence often >0.80: Can raise threshold to 0.75-0.80
• Goal: Signals fire during top 20-30% of coherence values
Emergence Threshold:
• If too few signals: Lower to 0.65-0.70
• If too many signals: Raise to 0.80-0.85
• Balance with coherence threshold—both must be met
Phase 3: Signal Quality Assessment (Weeks 3-4)
Goal: Verify signals have edge via paper trading
Requirements:
• Parameters optimized per Phase 2
• 50+ signals generated
• Detailed notes on each signal
Paper Trading Protocol:
• Take EVERY emergence signal (★ and ◆)
• Optional: Take resonance signals (▲/▼) separately to compare
• Use simple exit: 2R target, 1R stop (ATR-based)
• Track: Win rate, average R-multiple, maximum consecutive losses
Quality Metrics:
• Premium emergence (★) : Should achieve >55% WR
• Standard emergence (◆) : Should achieve >50% WR
• Resonance signals : Should achieve >45% WR
• Overall : If <45% WR, system not suitable for this instrument/timeframe
Red Flags:
• Win rate <40%: Wrong instrument or parameters need major adjustment
• Max consecutive losses >10: System not working in current regime
• Profit factor <1.0: No edge despite complexity analysis
Phase 4: Regime Awareness (Week 5)
Goal: Understand which market conditions produce best signals
Analysis:
• Review Phase 3 trades, segment by:
- Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC)
- Lyapunov state (STABLE vs CRITICAL vs CHAOTIC)
- Fractal regime (TRENDING vs RANDOM vs COMPLEX)
Findings (typical patterns):
• Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal
• Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal
• Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these)
Optimization:
• If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70
• If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic
• If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate with minimal capital at risk
Requirements:
• Paper trading shows: WR >48%, PF >1.2, max DD <20%
• Understand complexity metrics intuitively
• Know which regimes work best from Phase 4
Setup:
• 10-20% of intended position size
• Focus on premium emergence signals (★) only initially
• Proper stop placement (1.5-2.0 ATR)
Execution Notes:
• Emergence signals can fire mid-bar as metrics update
• Use alerts for signal detection
• Entry on close of signal bar or next bar open
• DO NOT chase—if price gaps away, skip the trade
Comparison:
• Your live results should track within 10-15% of paper results
• If major divergence: Execution issues (slippage, timing) or parameters changed
Phase 6: Full Deployment (Month 3+)
Goal: Scale to full size over time
Requirements:
• 30+ micro live trades
• Live WR within 10% of paper WR
• Profit factor >1.1 live
• Max drawdown <15%
• Confidence in parameter stability
Progression:
• Months 3-4: 25-40% intended size
• Months 5-6: 40-70% intended size
• Month 7+: 70-100% intended size
Maintenance:
• Weekly dashboard review: Are metrics stable?
• Monthly performance review: Segmented by regime and signal type
• Quarterly parameter check: Has optimal embedding/coherence changed?
Advanced:
• Consider different parameters per session (high vs low volatility)
• Track phase space magnitude patterns before major moves
• Combine with other indicators for confluence
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Phase Space Revelation:
Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D.
The Permutation Entropy Discovery:
Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering.
The Lyapunov Filter Breakthrough:
Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself.
The Transfer Entropy Challenge:
Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters.
The Phase Coherence Insight:
Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason.
The Eight-Component Emergence Formula:
Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it.
The Cooldown Necessity:
Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude.
• NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty.
• NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data.
• NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections.
• NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off.
Core Assumptions:
1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly).
2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong.
3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise).
4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets).
5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive).
6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT).
Performs Best On:
• ES, NQ, RTY (major US index futures - high liquidity, clean volume data)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis)
• Liquid commodities: CL (crude oil), GC (gold), NG (natural gas)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure)
• Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis
• Exotic forex pairs - erratic spreads, thin volume
• Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis
• Pre-market/after-hours - gappy, thin, different dynamics
• Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions
• Highly manipulated instruments - spoofing and layering create false coherence
Known Weaknesses:
• Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed.
• Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument.
• Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable.
• Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive.
• False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through.
• Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this.
• Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless.
Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals.
Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size.
The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it.
Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe.
The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic.
Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations.
Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
📁 DOCUMENTATION
The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research:
Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory.
Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics.
Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data.
Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions.
Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales.
Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory.
The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?).
This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor.
Multiple oscillator-type calculations contribute to dimensional analysis:
Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection.
Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized.
Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed.
Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional.
The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states.
While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space.
Volatility analysis permeates the system:
ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score.
Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility).
Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory.
Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable.
Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions.
The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator.
CLOSING STATEMENT
DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence .
This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity.
When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance .
These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state.
Most indicators see shadows on the wall. DRP reconstructs the cave.
"In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Advanced Triple Strategy ScalperHere are the three scalping strategies presented in the video "3 Scalping Strategies That Work Every Day (Backtested & Proven)" by Asia Forex Mentor – Ezekiel Chew:
### Scalper’s Trend Filter (Triple EMA)
This strategy uses three EMAs (25, 50, 100) on the 5-minute chart to filter high-probability trades aligned with momentum .
- Only trade when all three EMAs are angled in the same direction and clearly separated (no crossing or tangling) .
- Enter when price pulls back toward the 25 or 50 EMA and then bounces back toward the 25 EMA, but do not enter if price closes below the 100 EMA .
- Set stop-loss just below the 50 EMA or swing low and aim for a risk-to-reward ratio of 1:1.5 .
### Flip Zone Trap (Reversal Catching)
This method identifies precise reversal moments where market structure shifts from weakness to strength .
- Use the 15-min chart to locate key support or resistance zones where price previously reacted .
- Wait for price to stop making lower lows and begin making higher highs (or vice versa for shorts); confirm with a trendline break AND follow-through (higher lows & highs within 5-7 candles) .
- Use confirmation candles (bullish engulfing, pin bar rejection) at the zone before entry .
### Liquidity Shift Trigger (Smart Money Trap)
This system leverages institutional stop hunts and liquidity sweeps at key zones for sniper entries .
- Start with a 15-min chart to identify structure breaks and points of interest (order blocks, flip zones, demand zones) .
- Drop to 1-min chart and wait for price to enter the refined zone and sweep liquidity (sharp wick/spike below/above key level) .
- Once liquidity is swept, wait for a clean structure shift (break of most recent internal high or low) within 5–6 candles—if confirmed, refine entry to the candle that caused the break and enter when price returns to that candle with a strong reaction .
***
### Practical Application
- These strategies are systematic, rule-based, and designed to cut out fake moves, avoid early stop-outs, and align entries with momentum and institutional activity .
- Perfect for short timeframes and volatile pairs like XAUUSD, especially if paired with additional confirmation from other technical analysis tools .
All three strategies emphasize filtering noise, waiting for momentum/trend confirmation, and avoiding impulsive entries—key principles for consistent scalping success
Trading Sessions [QuantAlgo]🟢 Overview
The Trading Sessions indicator tracks and displays the four major global trading sessions: Sydney, Tokyo, London, and New York. It provides session-based background highlighting, real-time price change tracking from session open, and a data table with session status. The script works across all markets (forex, equities, commodities, crypto) and helps traders identify when specific geographic markets are active, which directly correlates with changes in liquidity and volatility patterns. Default session times are set to major financial center hours in UTC but are fully adjustable to match your trading methodology.
🟢 Key Features
→ Session Background Color Coding
Each trading session gets a distinct background color on your chart:
1. Sydney Session - Default orange, 22:00-07:00 UTC
2. Tokyo Session - Default red, 00:00-09:00 UTC
3. London Session - Default green, 08:00-16:00 UTC
4. New York Session - Default blue, 13:00-22:00 UTC
When sessions overlap, the color priority is New York > London > Tokyo > Sydney. This means if London and New York are both active, the background shows New York's color. The priority matches typical liquidity and volatility patterns where later sessions generally show higher volume.
→ Color Customization
All session colors are configurable in the Color Settings panel:
1. Click any session color input to open the color picker
2. Select your preferred color for that session
3. Use the "Background Transparency" slider (0-100) to adjust opacity. Lower values = more visible, higher values = more subtle
4. Enable "Color Price Bars" to color candlesticks themselves according to the active session instead of just the background
The Color column in the info table shows a block (█) in each session's assigned color, matching what you see on the chart background.
→ Information Table Breakdown
→ Timeframe Warning
If you're viewing a timeframe of 12 hours or higher, a red warning label appears center-screen. Session boundaries don't render accurately on high timeframes because the time() function in Pine Script can't detect intra-bar session changes when each bar spans multiple sessions. The warning tells you to switch to sub-12H timeframes (e.g., 4H, 1H, 30m, 15m, etc.) for proper session detection. You can disable this warning in Color Settings if needed, but session highlighting can be unreliable on 12H+ charts regardless.
→ Time Range Configuration
Every session's time range is editable in Session Settings:
1. Click the time input field next to each session
2. Enter time as HHMM-HHMM in 24-hour format
3. All times are interpreted as UTC
4. Modify these to account for daylight saving shifts or to define custom session periods based on your backtested optimal trading windows
For example, if your strategy performs best during London/NY overlap specifically, you could set London to 08:00-17:00 and New York to 13:00-22:00 to ensure you see the full overlap highlighted.
→ Weekdays Filter
The "Weekdays Only (Mon-Fri)" toggle controls whether sessions display on weekends:
Enabled: Sessions only show Monday-Friday and hide on Saturday-Sunday. Use this for markets that close on weekends (most equities, forex).
Disabled: Sessions display 24/7 including weekends. Use this for markets that trade continuously (crypto).
→ Table Display Options
The info table has several configuration options in Table Settings:
Visibility: Toggle "Show Info Table" on/off to display or hide the entire table.
Position: Nine position options (Top/Middle/Bottom + Left/Center/Right) let you place the table wherever it doesn't block your price action or other indicators.
Text Size: Four size options (Tiny, Small, Normal, Large) to match your screen resolution and visual preferences.
→ Color Schemes:
Mono: Black background, gray header, white text
Light: White background, light gray header, black text
Blue: Dark blue background, medium blue header, white text
Custom: Manual selection of all five color components (table background, header background, header text, data text, borders)
→ Alert Functionality
The indicator includes ten alert conditions you can access via TradingView's alert system:
Session Opens:
1. Sydney Session Started
2. Tokyo Session Started
3. London Session Started
4. New York Session Started
5. Any Session Started
Session Closes:
6. Sydney Session Ended
7. Tokyo Session Ended
8. London Session Ended
9. New York Session Ended
10. Any Session Ended
These alerts fire when sessions transition based on your configured time ranges, letting you automate monitoring of session changes without watching the chart continuously. Useful for strategies that trade specific session opens/closes or need to adjust position sizing when volatility regime shifts between sessions.
