TraderTürk M.Y Signal BoxThis Pine Script indicator (“TraderTürk M.Y Signal Box”) displays two information panels on the chart:
Signal Box (bottom left)
Volume: Shows the current bar’s volume alongside the average volume over a selected period (e.g. 20 bars), labeled as “High” or “Low.”
Popular Indicators: EMA 50, EMA 100, RSI(14), MACD(12,26,9), Stochastic(14,3), Bollinger Bands(20,2), and CCI(20), each reporting only “BUY”/“SELL”/“NEUTRAL.”
Buy/Sell Ratio Box (bottom right)
Tallies how many of those seven indicators are signaling “BUY” versus “SELL” and presents these counts as percentages.
Statistics
MG Universal model🚀 Summary🚀
The MG univerasal model is a composite of various items such as RSI, price Z-Score, Sharpe Ratio, Sortino Ratio, Omega Ratio, etc
Each component is normalized and then equally wheighted out to perform a global metric.
At the end, an Exponential Moving Average is added on the global metric.
You can easily find a description of each component on the internet, for the Crosby Ratio, it's a metric that comes from bitcoinmagazinepro.com.
✨ Key Features ✨
🗡 Smoothed Global Metric
Using a Moving average to smooth out the whole aggregated metric.
🗡 Bands Zone at extreme levels
Automatically displaying bands at top and bottom levels of the oscillator.
🗡 Normalizing components
Each component is normalized.
🗡 DataTable
Optional DataTable is available to check the score for each components and their related Z-Score.
📊 How I use it 📊
When catching up with 0 line (midline), crossing it :
if it goes above 0.2:
get out when it crosses 0.2 again
else:
get out when it crosses 0 again
That's the way I use it, may be there is a better way, FAFO :)
❓ Seeing a bug or an issue ❓
Feel free to DM me if you see a component that seems badly calculated.
I will be happy to fix it.
❗❗ Disclaimer ❗❗
This is a single indicator, even though it's aggregating many, do not use it as a standalone.
Past performance is not indicative of future results.
Always backtest, check, and align parameters before live trading.
Intraday Long Stoploss DistanceWhile working on intraday 1-minute charts i found it distracting to calculate the stoploss distance from the current price so i created an overlay indicator that plots the values of the last 15 minute and 30 minutes low for safe SL placement so you can get a rough idea of Risk management and lot size to use.
Still in early phases. Few more updates coming soon .stay updated.
*Not a financial advice.
BotBeans Optimizer - MA CrosserBotBeans Optimizer - MA Crosser
This script allows you to:
1. Select up to 12 types of Moving Averages (MA)
2. Backtest 7 combinations of MA crossover strategy at a time with key metrics such as Net Profit%, Profit Factor, Win Rate%, Total Trades and Maximum Drowdown (Max DD)
3. Easy to define slow MA length by using SlowMultiplier. Slow MA length is calculated by fast MA length multiplied by SlowMultipleir.
4. Ability to plot MA lines, trading signals, slop loss and take profit levels for clarification
5. Risk Management is implemented. By default, risk only 2% for each trade.
6. The script uses 14 Average True Range (ATR) multiplied by ATRMultiplier to determine stop loss level
7. Take profit level is calculated by stop loss level multiplied by RiskRewardRatio.
8. Implemented with trading fee for more accurate backtest result
Average Body RangeThe Average Body Range (ABR) indicator calculates the average size of a candle's real body over a specified period. Unlike the traditional Average Daily Range (ADR), which measures the full range from high to low, the ABR focuses solely on the absolute difference between the open and close of each bar. This provides insight into market momentum and trading activity by reflecting how much price is actually moving from open to close , not just in total.
This indicator is especially useful for identifying:
Periods of strong directional movement (larger body sizes)
Low-volatility or indecisive markets (smaller body sizes)
Changes in trend conviction or momentum
Customization:
Length: Number of bars used to compute the average (default: 14)
Use ABR to enhance your understanding of price behavior and better time entries or exits based on market strength.
MTFThis is a variation of the denosied MFI ma cross script that allows for reductionist trend following memeing, but taking it to the next level. This combines multiple ma's and finds local bottoms and tops to find the optimum trend to catch and ride along. PM for access.
Prop Firm Business SimulatorThe prop firm business simulator is exactly what it sounds like. It's a plug and play tool to test out any tradingview strategy and simulate hypothetical performance on CFD Prop Firms.
Now what is a modern day CFD Prop Firm?
These companies sell simulated trading challenges for a challenge fee. If you complete the challenge you get access to simulated capital and you get a portion of the profits you make on those accounts payed out.
I've included some popular firms in the code as presets so it's easy to simulate them. Take into account that this info will likely be out of date soon as these prices and challenge conditions change.
Also, this tool will never be able to 100% simulate prop firm conditions and all their rules. All I aim to do with this tool is provide estimations.
Now why is this tool helpful?
Most traders on here want to turn their passion into their full-time career, prop firms have lately been the buzz in the trading community and market themselves as a faster way to reach that goal.
While this all sounds great on paper, it is sometimes hard to estimate how much money you will have to burn on challenge fees and set realistic monthly payout expectations for yourself and your trading. This is where this tool comes in.
I've specifically developed this for traders that want to treat prop firms as a business. And as a business you want to know your monthly costs and income depending on the trading strategy and prop firm challenge you are using.
How to use this tool
It's quite simple you remove the top part of the script and replace it with your own strategy. Make sure it's written in same version of pinescript before you do that.
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
//--$$$$$--Strategy-- --$$$$$$--// ******************************************************************************************************************************
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
length = input.int(20, minval=1, group="Keltner Channel Breakout")
mult = input(2.0, "Multiplier", group="Keltner Channel Breakout")
src = input(close, title="Source", group="Keltner Channel Breakout")
exp = input(true, "Use Exponential MA", display = display.data_window, group="Keltner Channel Breakout")
BandsStyle = input.string("Average True Range", options = , title="Bands Style", display = display.data_window, group="Keltner Channel Breakout")
atrlength = input(10, "ATR Length", display = display.data_window, group="Keltner Channel Breakout")
esma(source, length)=>
s = ta.sma(source, length)
e = ta.ema(source, length)
exp ? e : s
ma = esma(src, length)
rangema = BandsStyle == "True Range" ? ta.tr(true) : BandsStyle == "Average True Range" ? ta.atr(atrlength) : ta.rma(high - low, length)
upper = ma + rangema * mult
lower = ma - rangema * mult
//--Graphical Display--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
u = plot(upper, color=#2962FF, title="Upper", force_overlay=true)
plot(ma, color=#2962FF, title="Basis", force_overlay=true)
l = plot(lower, color=#2962FF, title="Lower", force_overlay=true)
fill(u, l, color=color.rgb(33, 150, 243, 95), title="Background")
//--Risk Management--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
riskPerTradePerc = input.float(1, title="Risk per trade (%)", group="Keltner Channel Breakout")
le = high>upper ? false : true
se = lowlower
strategy.entry('PivRevLE', strategy.long, comment = 'PivRevLE', stop = upper, qty=riskToLots)
if se and upper>lower
strategy.entry('PivRevSE', strategy.short, comment = 'PivRevSE', stop = lower, qty=riskToLots)
The tool will then use the strategy equity of your own strategy and use this to simulat prop firms. Since these CFD prop firms work with different phases and payouts the indicator will simulate the gains until target or max drawdown / daily drawdown limit gets reached. If it reaches target it will go to the next phase and keep on doing that until it fails a challenge.
If in one of the phases there is a reward for completing, like a payout, refund, extra it will add this to the gains.
If you fail the challenge by reaching max drawdown or daily drawdown limit it will substract the challenge fee from the gains.
These gains are then visualised in the calendar so you can get an idea of yearly / monthly gains of the backtest. Remember, it is just a backtest so no guarantees of future income.
The bottom pane (non-overlay) is visualising the performance of the backtest during the phases. This way u can check if it is realistic. For instance if it only takes 1 bar on chart to reach target you are probably risking more than the firm wants you to risk. Also, it becomes much less clear if daily drawdown got hit in those high risk strategies, the results will be less accurate.
The daily drawdown limit get's reset every time there is a new dayofweek on chart.
If you set your prop firm preset setting to "'custom" the settings below that are applied as your prop firm settings. Otherwise it will use one of the template by default it's FTMO 100K.
The strategy I'm using as an example in this script is a simple Keltner Channel breakout strategy. I'm using a 0.05% commission per trade as that is what I found most common on crypto exchanges and it's close to the commissions+spread you get on a cfd prop firm. I'm targeting a 1% risk per trade in the backtest to try and stay within prop firm boundaries of max 1% risk per trade.
Lastly, the original yearly and monthly performance table was developed by Quantnomad and I've build ontop of that code. Here's a link to the original publication:
That's everything for now, hope this indicator helps people visualise the potential of prop firms better or to understand that they are not a good fit for their current financial situation.
Bar Painting [iFarsheed]
Bar Painting
Overview:
The "Bar Painting " indicator is designed for traders who follow price action strategies inspired by Al Brooks.
This tool colors candles on your chart, making it easy to identify different candle types like trend bars, dojis, and pin bars without complex calculations. By simply observing the colors, you can quickly understand market dynamics.
Features:
Candle Coloring:
Bullish (up) and bearish (down) trend bars are highlighted in distinct colors for easy recognition.
Candles that do not fit these patterns appear in the default chart color, indicating they do not represent significant moves.
Visual Clarity:
The color coding provides a quick visual reference, allowing you to grasp market conditions at a glance.
No Calculations Required:
You don’t need to perform any calculations; just look at the colors to understand the strength of the market.
How to Use:
Customize Settings:
Adjust the colors of trend bars to ensure they contrast well with your chart background for improved visibility.
Use the settings to choose which candle types you want to highlight based on your trading preferences.
Analyze Candle Patterns:
Look at the colored candles to quickly identify trend bars, dojis, and pin bars that may signal potential market movements.
Informed Decision Making:
Use the highlighted candle patterns to assist in making trading decisions, such as identifying possible entry and exit points.
Important Note:
This coloring scheme is optimized for light mode charts. In dark mode, the colors may not display correctly.
To ensure proper color display, please set the visual order of the indicator to "Bring to Front."
Future Updates:
This indicator is an initial version, and more features will be added in the future.
If you have any suggestions or feedback, please feel free to share your thoughts in the comments section of the indicator.
Good luck with your trading!
-iFarsheed-
CVD (Cumulative Volume Delta)
Cumulative Volume Delta
Use a moving average with three different
I thought about determining the volatility and direction of the price of the stock price and finding a place to break through.
I made some Mistake coz I'm new corder
I'm reposting this simple script due to house rule violation. (Whatever can haha) 😁
I'm erasing all the comments in my native language that I had in my script... I thought it would make the User uncomfortable, so I locked the code, and I thought maybe that's the problem
Anyway, I'm sorry 😅
[Kpt-Ahab] PnL-calculatorThe PnL-Cal shows how much you’re up or down in your own currency, based on the current exchange rate.
Let’s say your home currency is EUR.
On October 10, 2022, you bought 10 Tesla stocks at $219 apiece.
Back then, with an exchange rate of 0.9701, you spent €2,257.40.
If you sold the 10 Tesla shares on April 17, 2025 for $241.37 each, that’s around a 10% gain in USD.
But if you converted the USD back to EUR on the same day at an exchange rate of 1.1398, you’d actually end up with an overall loss of about 6.2%.
Right now, only a single entry point is supported.
If you bought shares on different days with different exchange rates, you’ll unfortunately have to enter an average for now.
For viewing on a phone, the table can be simplified.
Institutional MACD (Z-Score Edition) [VolumeVigilante]📈 Institutional MACD (Z-Score Edition) — Professional-Grade Momentum Signal
This is not your average MACD .
The Institutional MACD (Z-Score Edition) is a statistically enhanced momentum tool, purpose-built for serious traders and breakout hunters . By applying Z-Score normalization to the classic MACD structure, this indicator uncovers statistically significant momentum shifts , enabling cleaner reads on price extremes, trend continuation, and potential reversals.
💡 Why It Matters
The classic MACD is powerful — but raw momentum values can be noisy and relative , especially on volatile assets like BTC/USD . By transforming the MACD line, signal line, and histogram into Z-scores , we anchor these signals in statistical context . This makes the Institutional MACD:
✔️ Timeframe-agnostic and asset-normalized
✔️ Ideal for spotting true breakouts , not false flags
✔️ A reliable tool for detecting momentum divergence and exhaustion
🧪 Key Features
✅ Full Z-Score normalization (MACD, Signal, Histogram)
✅ Highlighted ±Z threshold bands for overbought/oversold zones
✅ Customizable histogram coloring for visual momentum shifts
✅ Built-in alerts for zero-crosses and Z-threshold breaks
✅ Clean overlay with optional display toggles
🔁 Strategy Tip: Mean Reversion Signals with Statistical Confidence
This indicator isn't just for spotting breakouts — it also shines as a mean reversion tool , thanks to its Z-Score normalization .
When the Z-Score histogram crosses beyond ±2, it marks a statistically significant deviation from the mean — often signaling that momentum is overstretched and the asset may be due for a pullback or reversal .
📌 How to use it:
Z > +2 → Price action is in overbought territory. Watch for exhaustion or short setups.
Z < -2 → Momentum is deeply oversold. Look for reversal confirmation or long opportunities.
These zones often precede snap-back moves , especially in range-bound or corrective markets .
🎯 Combine Z-Score extremes with:
Candlestick confirmation
Support/resistance zones
Volume or price divergence
Other mean reversion tools (e.g., RSI, Bollinger Bands)
Unlike the raw MACD, this version delivers statistical thresholds , not guesswork — helping traders make decisions rooted in probability, not emotion.
📢 Trade Smart. Trade Vigilantly.
Published by VolumeVigilante
Correlation MatrixThis indicator displays a real-time correlation matrix of any five assets selected by the user. It helps traders and investors identify relationships between different instruments—whether they move together (positive correlation), in opposite directions (negative correlation), or not at all (neutral).
Vietnamese Stocks: Multi-Ticker Fibonacci AlertThis Pine Script™ indicator is designed specifically for traders monitoring the Vietnamese stock market (HOSE, HNX). Its primary goal is to automate the tracking of Fibonacci retracement levels across a large list of stocks, alerting you when prices breach key support zones.
Core Functionality:
The script calculates Fibonacci retracement levels (23.6%, 38.2%, 50%, 61.8%, 78.6%) for up to 40 tickers simultaneously. The calculation is based on the highest high and lowest low identified since a user-defined Start Time. This allows you to anchor the Fibonacci analysis to a specific market event, trend start, or time period relevant to your strategy.
What it Does For You:
Automated Watchlist Scanning: Instead of drawing Fib levels on dozens of charts, select one of the two pre-configured watchlists (up to 40 symbols each, customizable in settings) populated with popular Vietnamese stocks.
Time-Based Fibonacci: Define a Start Time in the settings. The script uses this date to find the subsequent highest high and lowest low for each symbol in your chosen watchlist, forming the basis for the Fib calculation.
Intelligent Alerts: Get notified via TradingView's alerts when the candle closing price of any stock in your active watchlist falls below the critical 38.2%, 50%, 61.8%, or 78.6% levels relative to its own high/low range since the start time. Alerts are consolidated for efficiency.
Visual Aids:
- Plots the same time-based Fibonacci levels directly on your current chart symbol for quick reference.
- Includes an optional on-chart table showing which monitored stocks are currently below key Fib levels (enable "Show Debug Info").
- Features experimental background coloring to highlight potential bullish signals on the current chart.
Configuration:
Start Time: Crucial input – sets the anchor point for Fib calculations.
WatchList Selection: Choose between WatchList #1 (Bluechip/Midcap focus) or WatchList #2 (Defensive/Other focus) using the boolean toggles.
Symbol Customization: Easily replace the default symbols with your preferred Vietnamese stocks directly in the indicator settings.
Notification Prefix: Add custom text to the beginning of your alert messages.
Alert Setup: Remember to create an alert in TradingView, selecting this indicator and the alert() condition, usually with "Once Per Bar Close" frequency.
This tool is open-source under the MPL 2.0 license. Feel free to use, modify, and learn from it.
tafirstlibGeneral Purpose: Starts by stating it's a collection of utility functions for technical analysis.
Core Functionality Areas: Mentions key categories like:
Extrema detection (isMin, isMax, etc.)
Condition checking over time (isMachedInRange, isContinuous, etc.)
Rate of change analysis (isSlowDown)
Moving average calculation (getMA)
Advanced Features: Highlights the more complex functions:
Visualization helpers (getColorNew)
Moving Regression (mr) for smoothing/trend
Cycle analysis (bpDom)
Overall Goal: Concludes by stating the library's aim – simplifying development and enabling complex analysis.
Library "tafirstlib"
TODO: add library description here
isSlowDown(data)
isSlowDown
Parameters:
data (float) : array of numbers
Returns: boolean
isMin(data, maeLength)
isMin
Parameters:
data (float) : array of numbers
maeLength (int) : number
Returns: boolean
isMax(data, maeLength)
isMax
Parameters:
data (float) : array of numbers
maeLength (int) : number
Returns: boolean
isMinStopped(data, maeLength)
isMinStopped
Parameters:
data (float) : array of numbers
maeLength (int) : number
Returns: boolean
isMaxStopped(data, maeLength)
isMaxStopped
Parameters:
data (float) : array of numbers
maeLength (int) : number
Returns: boolean
isLongMinStopped(data, maeLength, distance)
isLongMinStopped
Parameters:
data (float) : array of numbers
maeLength (int) : number
distance (int) : number
Returns: boolean
isLongMaxStopped(data, maeLength, distance)
isLongMaxStopped
Parameters:
data (float) : array of numbers
maeLength (int) : number
distance (int) : number
Returns: boolean
isMachedInRangeSkipCurrent(data, findRange, findValue)
isMachedInRangeSkipCurrent
Parameters:
data (bool) : array of numbers
findRange (int) : number
findValue (bool) : number
Returns: boolean
isMachedInRange(data, findRange, findValue)
isMachedInRange
Parameters:
data (bool) : array of numbers
findRange (int) : number
findValue (bool) : number
Returns: boolean
isMachedColorInRange(data, findRange, findValue)
isMachedColorInRange isMachedColorInRange(series color data, int findRange, color findValue)
Parameters:
data (color) : series of color
findRange (int) : int
findValue (color) : color
Returns: boolean
countMachedInRange(data, findRange, findValue)
countMachedInRange
Parameters:
data (bool) : array of numbers
findRange (int) : number
findValue (bool) : number
Returns: number
getColor(data)
getColor
Parameters:
data (float) : array of numbers
Returns: color
getColorNew(data)
getColorNew
Parameters:
data (float) : array of numbers
Returns: color
isColorBetter(color_data)
isColorBetter
Parameters:
color_data (color) : array of colors
Returns: boolean
isColorWorst(color_data)
isColorWorst
Parameters:
color_data (color) : array of colors
Returns: boolean
isColorBetter2(color_data)
isColorBetter2
Parameters:
color_data (color) : array of colors
Returns: boolean
isColorWorst2(color_data)
isColorWorst2
Parameters:
color_data (color) : array of colors
Returns: boolean
isDecreased2Bar(data)
isDecreased2Bar
Parameters:
data (float) : array of numbers
Returns: boolean
isContinuousAdvance(targetSeries, range2Find, howManyException)
isContinuousAdvance
Parameters:
targetSeries (bool) : array of booleans
range2Find (int) : number
howManyException (int) : number
Returns: boolean
isContinuous(targetSeries, range2Find, truefalse)
isContinuous
Parameters:
targetSeries (bool) : array of booleans
range2Find (int) : number
truefalse (bool) : boolean
Returns: boolean
isContinuousNotNow(targetSeries, range2Find, truefalse)
isContinuousNotNow
Parameters:
targetSeries (bool) : array of booleans
range2Find (int) : number
truefalse (bool) : boolean
Returns: boolean
isContinuousTwoFactors(targetSeries, range2Find, truefalse)
isContinuousTwoFactors
Parameters:
targetSeries (bool) : array of booleans
range2Find (int) : number
truefalse (bool) : boolean
Returns: boolean
findEventInRange(startDataBarIndex, neededDataBarIndex, currentBarIndex)
findEventInRange
Parameters:
startDataBarIndex (int) : number
neededDataBarIndex (int) : number
currentBarIndex (int) : number
Returns: boolean
findMin(firstdata, secondata, thirddata, forthdata)
findMin
Parameters:
firstdata (float) : number
secondata (float) : number
thirddata (float) : number
forthdata (float) : number
Returns: number
findMax(firstdata, secondata, thirddata, forthdata)
findMax
Parameters:
firstdata (float) : number
secondata (float) : number
thirddata (float) : number
forthdata (float) : number
Returns: number
getMA(src, length, mav)
getMA
Parameters:
src (float) : number
length (simple int) : number
mav (string) : string
Returns: number
mr(mrb_src, mrb_window, mrb_degree)
Parameters:
mrb_src (float)
mrb_window (int)
mrb_degree (int)
bpDom(maeLength, bpw, mult)
Parameters:
maeLength (int)
bpw (float)
mult (float)
FunctionSurvivalEstimationLibrary "FunctionSurvivalEstimation"
The Survival Estimation function, also known as Kaplan-Meier estimation or product-limit method, is a statistical technique used to estimate the survival probability of an individual over time. It's commonly used in medical research and epidemiology to analyze the survival rates of patients with different treatments, diseases, or risk factors.
What does it do?
The Survival Estimation function takes into account censored observations (i.e., individuals who are still alive at a certain point) and calculates the probability that an individual will survive beyond a specific time period. It's particularly useful when dealing with right-censoring, where some subjects are lost to follow-up or have not experienced the event of interest by the end of the study.
Interpretation
The Survival Estimation function provides a plot of the estimated survival probability over time, which can be used to:
1. Compare survival rates between different groups (e.g., treatment arms)
2. Identify patterns in the data that may indicate differences in mortality or disease progression
3. Make predictions about future outcomes based on historical data
4. In a trading context it may be used to ascertain the survival ratios of trading under specific conditions.
Reference:
www.global-developments.org
"Beyond GDP" ~ www.aeaweb.org
en.wikipedia.org
www.kdnuggets.com
survival_probability(alive_at_age, initial_alive)
Kaplan-Meier Survival Estimator.
Parameters:
alive_at_age (int) : The number of subjects still alive at a age.
initial_alive (int) : The Total number of initial subjects.
Returns: The probability that a subject lives longer than a certain age.
utility(c, l)
Captures the utility value from consumption and leisure.
Parameters:
c (float) : Consumption.
l (float) : Leisure.
Returns: Utility value from consumption and leisure.
welfare_utility(age, b, u, s)
Calculate the welfare utility value based age, basic needs and social interaction.
Parameters:
age (int) : Age of the subject.
b (float) : Value representing basic needs (food, shelter..).
u (float) : Value representing overall well-being and happiness.
s (float) : Value representing social interaction and connection with others.
Returns: Welfare utility value.
expected_lifetime_welfare(beta, consumption, leisure, alive_data, expectation)
Calculates the expected lifetime welfare of an individual based on their consumption, leisure, and survival probability over time.
Parameters:
beta (float) : Discount factor.
consumption (array) : List of consumption values at each step of the subjects life.
leisure (array) : List of leisure values at each step of the subjects life.
alive_data (array) : List of subjects alive at each age, the first element is the total or initial number of subjects.
expectation (float) : Optional, `defaut=1.0`. Expectation or weight given to this calculation.
Returns: Expected lifetime welfare value.
Dynamic HL VWAP+ | Current & Prev🔴 Dynamic HL VWAP+ | Current & Previous 🔴
A precision volume-weighted tool for traders who want more than just standard VWAP.
🧠 What It Does
The Dynamic HL VWAP+ is a powerful custom-built indicator that anchors Volume Weighted Average Price (VWAP) lines not from the session open, but from the highest and lowest points of dynamically detected price cycles.
Unlike traditional VWAPs, this tool recalculates its anchor points from:
🔺 The most recent swing high (Highest Price in Lookback Period)
Please note currently it's limited to the default value or lower, as any higher, and it will conflict with Pine's restriction on "memory allocation" system for this kind of effort. Will update if there is any change in that.
🔻 The most recent swing low (Lowest Price in Lookback Period)
Then it does the same for the previous cycle (before the current lookback window), allowing you to see how price is behaving relative to past and present price extremes.
⚙️ Key Features
✅ Dynamic Anchoring
Anchors VWAPs from the most recent High and Low over a user-defined lookback period (len).
✅ Multi-Cycle Context
Plots both Current and Previous high/low-anchored VWAPs for contextual analysis.
✅ VWAP from Highs and Lows Separately
You’ll see how price reacts around bullish (High VWAP) and bearish (Low VWAP) pressures—great for scalping, pullbacks, and reversion plays.
✅ Line Visibility Control
You decide which lines to show:
Current High VWAP
Current Low VWAP
Previous High VWAP
Previous Low VWAP
✅ Lightweight and Label-Free
Optimized for performance. No labels, no alerts, just clean and effective plotting.
📈 How to Use
1. Trend Confirmation
When price holds above the Low VWAP or breaks the High VWAP, it signals trend strength.
If price rejects at High VWAP or fails to hold Low VWAP, it's a potential reversal/retest zone.
2. Reversion-to-Mean Plays
Look for price moving far from the VWAP lines and then curling back.
Works great on volatile intraday moves or swing setups.
3. Compare Current vs. Previous Cycle
If current VWAPs are higher than the previous ones, it shows bullish progress.
Converging VWAPs from prior and current cycles often indicate a squeeze or decision point.
📊 Example Scenarios
Example 1 – Intraday Bounce Play:
Price drops into a prior cycle’s Low VWAP line and forms a base—an ideal area to look for long scalps.
Example 2 – Breakout Retest:
Price breaks above the Current High VWAP, then comes back to retest it. If it holds, the breakout is likely valid.
Example 3 – Reversal Setup:
Price is trending up but fails at Current High VWAP and breaks down below Current Low VWAP—watch for short signals.
🛠 Settings
Lookback Bars: Defines how far back to look for the current swing High/Low (default = 66).
VWAP Source: Use ohlc4 for a balanced average, or customize to your preference.
Visibility Toggles: Easily enable/disable each of the four VWAP lines.
🧪 Best Timeframes & Markets
Works across all timeframes
Great for futures, crypto, stocks
Especially useful on 15m–1H intraday charts and 4H–D for swings
💬 Final Thoughts
If you're tired of static VWAPs that only anchor from the open, the Dynamic HL VWAP+ gives you a more price-reactive, context-aware, and actionable VWAP structure.
Ideal for:
Day traders looking for mean-reversion plays
Swing traders targeting pullbacks
Anyone who wants smarter VWAP lines built on recent price structure
This is an educational idea and publication, past performance or what you may see on chart might not be replicable for you. Use at your own risk.
Regards
MissedPrice[KiomarsRakei]█ Overview:
The MissedPrice script identifies price zones based on significant Open Interest shifts (including gaps) aligned with price movements. When sudden market positioning changes occur, the script pinpoints target zones where price is believed to return. Each signal directs you toward these opportunity zones with supporting metrics like Notional Value, Volume Ratio, and Funding Rate timing to help qualify the signals.
█ Core Concept:
Markets frequently "miss" critical price levels during rapid movements. These missed zones occur when:
Orders are revoked during sudden price shifts
Exchanges fail to execute at intended prices
TP/SL orders miss exact execution points
Institutional orders create supply/demand imbalances
Market structure shifts bypass key levels
Liquidity voids form from positioning changes
These missed price zones create natural targets that price tends to revisit. The MissedPrice indicator identifies these zones by analyzing the relationship between Open Interest, Price, and Volume.
█ Closer look at target zones:
Target zones are calculated using the open price where significant OI shifts occur, with zone width adjusted based on the High-Low ratio and ATR to adapt to current volatility. If a zone is touched once after a signal is generated, it is no longer valid. This can be understood as the missing positions and volume having now entered the market.
Each zone's Notional Value (NV) - calculated as OI change multiplied by price - measures the financial impact of the positioning shift. Higher NV indicates more significant market activity and greater liquidity, making price more likely to return to that area. Users can adjust NV ratio thresholds in the inputs to filter signal quality.
█ Features:
Statistical Dashboard: Real-time statistics table showing performance metrics for signals
Funding Rate Visualization: Vertical lines indicate funding rate times to help correlate signals with these significant market events
Alert Capability: Set up alerts for new signals to never miss a trading opportunity
Dynamic Entry Lines: Draws adjustable entry and target level lines to facilitate precise trade execution and measurement, customizable via inputs
█ Closer Look at Statistics Table:
Signal Count: Total numbers of signals generated and total candles included (limited by TradingView's OI historical data)
Win Rate: can be interpreted as the hit rate of target zones. Whenever price reaches the zone, it is calculated as a win, regardless of how far price may have moved in the opposite direction beforehand. This metric measures the script's accuracy in identifying price zones that eventually get revisited.
Total Profit: Calculates possible profit from first entry to target of hit signals - an estimate since humans can't take all signals and might have better entries or average down. By default is turned off can be turned on in the input menu.
Bad Signals: Signals taking too long to complete or moving much further from target
Bad but Hit: Bad signals that eventually hit the target despite early challenges
As you can see in the chart, there are zones that price does not return to touch. There is no guarantee that every identified zone will be reached, which is why the script provides additional qualification metrics to help assess signal probability.
Due to limitations of Open Interest data, you can only use this script on crypto pairs that have Open Interest data available on TradingView. While the script works on any timeframe, it performs best on timeframes less than daily.
█ Best Practices:
Use it in bar replay mode to master the strategy
Try different risk management systems based on how far price goes from the target and your creativity
Use the volume ratio and funding time data to further qualify signals
Notional Value plays a key role
Statistical Trailing Stop [LuxAlgo]The Statistical Trailing Stop tool offers traders a way to lock in profits in trending markets with four statistical levels based on the log-normal distribution of volatility.
The indicator also features a dashboard with statistics of all detected signals.
🔶 USAGE
The tool works out of the box, traders can adjust the data used with two parameters: data & distribution length.
By default, the tool takes volatility measures of groups of 10 candles, and statistical measures of the last 100 of these groups then traders can adjust the base level to use as trailing, the larger the level, the more resistant the tool will be to moves against the trend.
🔹 Base Levels
Traders can choose up to 4 different levels of trailing, all based on the statistical distribution of volatility.
As we can see in the chart above, each higher level is more resistant to market movements, so level 0 is the most reactive and level 3 the least.
It is up to the trader to determine the best level for each underlying, time frame and market conditions.
🔹 Dashboard
The tool provides a dashboard with the statistics of all trades, making it very easy to assess the performance of the parameters used for any given market.
As we can see on the chart, all Daily BTC signals with default parameters but different base levels, level 2 is the best performing of all four, giving a positive expectation of $2435 per trade, taking into account all long and short trades.
Of note are the long trades with a win rate of 76.47% and a risk-to-reward of 3.34, giving a positive expectation of $4839 per trade, with winners having an average duration of 210 days and losers 32 days.
This, compared to short trades with negative expectation, speaks to the uptrend bias of this particular market.
🔶 SETTINGS
Data Length: Select how many bars to use per data point
Distribution Length: Select how many data points the distribution will have
Base Level: Choose between 4 different trailing levels
🔹 Dashboard
Show Statistics: Enable/disable dashboard
Position: Select dashboard position
Size: Select dashboard size
DTT Yearly Volatility Grid [Pro+] (NINE/ANARR)Introduction :
This tool is designed to automate the Digital Time Theory (DTT) framework created by Ivan and Anarr and applies the DTT Yearly Volatility Grid to uncover swing trading opportunities by analyzing Time-based statistical market behavior across the 4H to Daily chart.
Description:
Built upon the proprietary Digital Time Theory (DTT) , this advanced version is tailored for traders seeking multi-day to multi-week moves . It equips swing traders with an edge by analyzing macro Time intervals and volatility behavior across higher Timeframes. Applicable to all major asset classes, including stocks, crypto, forex, and futures , this script breaks down the entire yearly range into Higher-Time Frame Time Models and statistical zones .
This version uses daily intervals to track broader volatility waves, highlight the DTT framework, and pinpoint premium/discount areas across swing cycles. Powered by Time-driven data insights, this tool assists traders in anticipating expansions, understanding long-range Time distortions, and positioning around statistically significant zones in the higher-Time frame narrative.
Key Features:
Time-Based Models and Macro Volatility Awareness:
Automatically populates the chart with DTT Yearly Time Models (4H, Daily), engineered to spotlight macro volatility events across broader market sessions. Helps swing traders identify potential inflection points, reversals, or trend continuation zones.
Average Model Range Probability (AMRP):
Measure the average volatility expected over higher Time-based models. Use AMRP Levels and Projections to assess the range potential of each Yearly Model Time window—vital for monitoring reversals, breakouts, or continuation plays across several sessions or weeks.
Digital Root Candles and HTF Liquidity Draws:
For DTT Yearly Models, the Digital Root Candles are calculated as a specific Daily candle, and can be viewed on the Daily or 4H Timeframe. Analysts can frame premium and discount zones, based on where price is trading in relation to the current or previous model's Digital Roots. These areas also act as anchors for institutional price movement, often serving as bases for accumulation/distribution periods or large impulse moves.
Extended Visualization:
Track and project prior model ranges (high, low, equilibrium) into the current swing window. This helps visualize macro support/resistance , range expansion, failure zones, and price gravitation levels for longer-term trade planning.
Lookback Periods and Model Count
Utilize adjustable lookback periods to control the number of past DTT Yearly Models displayed—ideal for swing traders and quarterly outlooks. Whether you’re reviewing one yearly model to focus on the present range or several months’ worth of data for backtesting and confluence, this feature keeps charts clean, structured, and aligned with your preferred historical perspective.
By tailoring how many previous Time-based models appear on the chart, traders can better visualize and backtest repeated behaviors, major volatility clusters, and how key levels evolve over Time.
Detailed Data Table:
View statistical AMRP data for multiple DTT Yearly Models in real-Time. The data table helps confirm whether current price movement exceeds, respects, or fails to reach historical volatility ranges—key for analyzing market compression or expansion phases.
Customization Options:
Toggle inner Time interval, calculate AMRP utilizing a custom model lookback, and display styles (solid/dotted lines), including color coordination per drawing. Easily customize your charts and settings to fit your swing trading system or macro analysis.
How Swing Traders Can Use DTT Yearly Volatility Grid Effectively
Identify Swing Premium and Discount Zones:
Use Root Candles and Yearly Time Model AMRP Zones to evaluate where price is positioned in the current Time Model. Using this tool, traders can plan trades with a longer term horizon for a minimum of 1 to 2-weeks or manage entries/exits around market structure shifts and liquidity pools
Expect Macro Volatility Shifts:
Use the HTF models to forecast when and which volatility models are historically known to create larger market impulses . These tools help spot periods of potential exhaustion or breakout, especially near key economic releases, quarterly closes , or macro liquidity zones .
Avoid Low Volatility Consolidations:
AMRP helps you detect when the market is compressing or coiling within a DTT Yearly Model. If price is trading between Digital Root Candles or the AMRP zones, analysts are likely to notice periods of consolidation, and the inability to reach their historical volatility averages.
Usage Guidance:
Add DTT Yearly Volatility Grid (NINE/ANARR) to your TradingView chart.
Make sure to be on the 4H, or Daily Timeframes depending on your asset class and analysis.
Use the DTT Model elements and the Data Table to track expansion zones, premium/discount extremes, and model range behavior.
Terms and Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products. Finally, the purchaser indemnifies the seller from any and all liability. If the purchaser was invited through the Friends and Family Program, they acknowledge that the provided discount code only applies to the first initial purchase of the Toodegrees Premium Suite subscription. The purchaser is therefore responsible for cancelling – or requesting to cancel – their subscription in the event that they do not wish to continue using the product at full retail price. If the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
Composite Scaled EMA LevelsComposite Scaled EMA Levels Indicator
This TradingView Pine Script indicator calculates a “composite EMA” that compares the closing price of the current asset with that of the XU100 index and scales the EMA values to the XU100 level. It then visualizes these computed levels as horizontal lines on the chart with corresponding labels.
Key Components:
Inputs and Data Retrieval:
Length Input: The user defines a parameter length (default is 10) which determines over how many bars the horizontal line is drawn.
Data Collection:
The daily closing price of the current symbol (current_close) is retrieved using request.security().
The daily closing price of the XU100 index (xu100) is also retrieved.
A ratio is computed as current_close / xu100. This ratio serves as the basis for calculating the composite EMAs.
EMA Calculations:
The indicator computes Exponential Moving Averages (EMAs) on the ratio for specific periods.
In the provided version, the script calculates EMAs for three periods (34, 55, and 233), though you can easily expand this to other periods if needed.
Each computed EMA (for instance, EMA34, EMA55, EMA233) is then scaled by multiplying it with the XU100 index’s close, converting it to a price level that is meaningful on the chart.
Drawing Horizontal Lines:
Instead of using the standard plot() function, the script uses line.new() to draw horizontal lines representing the scaled EMA values over the last “length” bars.
Before drawing new lines, any existing lines and labels are deleted to ensure that only the most current values are shown.
Adding Labels to Lines:
The script creates a label for each EMA using label.new(), placing the label at the current bar (i.e., the rightmost position on the chart) using label.style_label_left so that the text appears to the right of the line.
The label displays the name of the composite EMA (e.g., "Composite EMA 34") along with its current scaled value.
Visualization:
The horizontal lines and labels provide a visual reference for the composite EMA levels. These lines help traders see critical support/resistance levels derived from the relationship between the current asset and the XU100 index.
Colors are assigned for clarity (for example, the EMA lines in this version use green).
Summary:
The Composite Scaled EMA Levels indicator is designed to help traders analyze the relationship between an asset’s price and the broader market index (XU100) by calculating a ratio and then applying EMAs on that ratio. By scaling these EMAs back to price levels and displaying them as horizontal lines with clear labels on the chart, the indicator offers a visual tool to assess trend direction and potential support or resistance levels. This can assist in making informed trading decisions based on composite trend analysis.
CAM | Currency Strength PerformanceOverview 📊
The "CAM | Currency Strength Performance" indicator is a powerful forex trading tool that blends traditional composite analysis with dynamic performance tracking! 🚀 It compares the strength of a currency pair’s base and quote currencies against the pair’s price movement, offering traders a clear, colorful view of market dynamics through normalized lines and an upgraded strength-based histogram. 🎨
How It Works 🛠️
🔍 Automatic Currency Detection: Instantly identifies the base (e.g., XAU in XAUUSD) and quote (e.g., USD) currencies—no setup required!
📈 Composite Strength Calculation: Measures each currency’s power by averaging its exchange rate against a basket of 10 major currencies (GBP, EUR, CHF, USD, AUD, CAD, NZD, JPY, NOK, XAU). A classic strength snapshot! 💪
📏 Normalization: Scales composites and pair prices with a smart formula (price minus moving average, divided by standard deviation) for easy comparison. ⚖️
🎨 Dynamic Visualization:
Plots 3 normalized lines with unique colors:
Base Composite
Quote Composite
Actual Pair (⚪ white)
Benefits 🌈
🧠 Simplified Analysis: Normalized composites make static strength clear, while the new histogram reveals dynamic trends.
✅ Enhanced Decisions: Color-coded lines and a performance-driven histogram pinpoint trading opportunities fast—spot when base or quote takes the lead! 🚨
⏱️ Time-Saver: Auto-detection and dual metrics (static + dynamic) streamline your workflow.
🌍 Versatile: Works across all supported pairs, with colors adapting to currencies (e.g., orange AUD, yellow XAU).
👀 Eye-Catching: Vibrant visuals (purple GBP, green USD) and a purple histogram make it engaging and intuitive.
How It Helps Traders 💡
📈 Spot Trends: Normalized lines show steady strength; the histogram tracks recent outperformance—perfect for timing trades.
⚠️ Catch Divergences: See when strength shifts (e.g., base surging, quote lagging) don’t match price—hello, reversal signals! 🔍
🛡️ Manage Risk: Levels (1, -1) and histogram swings help gauge overbought/oversold conditions for smarter stops.
🔮 Big Picture: Combines static strength with dynamic momentum, giving a fuller market view for scalping or long-term strategies.
Conclusion ✨
"CAM | Currency Strength Performance" now fuses classic strength analysis with real-time performance tracking. With its upgraded histogram, traders get a dual lens—static composites plus dynamic strength—turning complex forex data into actionable insights! 📈💰
Mar 11
Release Notes
✨ New Feature: Strength Histogram:
Tracks the performance of base and quote currencies over a customizable lookback period (default: 10 bars). 📅
Calculates strength as the currency’s percentage change minus the basket’s average change, then plots the difference (base - quote) as a purple histogram. 📊
⚙️ Customizable Settings: Adjust Scaling Period (50), Histogram Scale Factor (0.5), Lookback Bars (10), and Levels (1, -1) to fit your trading style! 🎚️
How It Differs from the Previous Version 🔄
Old Histogram:
Showed the static difference between normalized base and quote composites—a snapshot of relative strength at a single point in time. 📷
Focused on current exchange rate levels, scaled by the pair’s normalized price movement.
New Histogram:
Displays the dynamic strength difference (base strength - quote strength) over a user-defined lookback period (e.g., 10 bars). 🌊
Measures past and current performance by calculating percentage changes relative to a basket, highlighting momentum and trends. 📈
Offers a more responsive, time-based view, showing how each currency has performed recently rather than just its absolute strength.
VBSMI Strategy by QTX Algo SystemsVolatility Based SMI Strategy by QTX Algo Systems
Overview
The Volatility Based SMI Strategy transforms our popular VBSMI with Dynamic Bands indicator into a fully automated strategy that traders can backtest inside TradingView. It retains all core logic from the indicator—including adaptive volatility scaling and trend-based overbought/oversold thresholds—but adds two configurable entry methods, exit conditions, and a dual-mode trade execution engine.
This script is published separately from the VBSMI indicator because some traders use VBSMI as a confluence tool within their existing system, while others prefer a rules-based strategy that can be simulated, optimized, and tracked over time. This script serves the latter use case.
How It Works
Like the original indicator, this strategy uses:
Double-Smoothed SMI Calculation: Based on smoothed momentum using EMA of the relative and full range.
Adaptive Volatility Scaling: Uses a normalized BBWP-based factor to reflect current market volatility.
Dynamic Band Adjustment: Trend direction and strength shift overbought/oversold levels upward or downward.
Band Tilt & Compression Controls: Inputs allow users to define how aggressively the bands shift with trend conditions.
What’s different is the strategy layer—you now choose from two types of entry and exit logic, and two execution styles.
🛠️ Entry & Exit Modes
There are two logic modes for both entry and exit, allowing you to adapt the strategy to your own philosophy:
Cross Mode (SMI Crosses EMA):
Entry: Buy when SMI crosses above its EMA
Exit: Close when SMI crosses below its EMA
Exit OB/OS Mode (Band Exit Logic):
Entry: Buy when price exits dynamic oversold zone (crosses back above tilted oversold band)
Exit: Close when price exits dynamic overbought zone (crosses back below tilted overbought band)
You can mix and match the modes (e.g., enter on Cross, exit on Band Exit).
⚙️ Spot vs. Leverage Mode
Spot Mode
Designed for traders who prefer long-only setups
Enters a long position and holds until the exit condition is met
Prevents overlapping trades—ensures only one position at a time
Leverage Mode
Designed for those testing bi-directional systems (e.g., long/short switching)
Automatically flips between long and short entries depending on the signals
Useful for testing symmetrical strategies or inverse conditions
Both modes work across any asset class and timeframe.
Customization Options
Users can adjust:
Smoothing K/D: Controls how fast or slow the momentum reacts
SMI EMA Length: Determines the responsiveness of the signal line
Trend Lookback Period: Influences how stable the dynamic band tilt is
Band Tilt & Compression Strengths: Refines how far bands adjust based on trend
Entry/Exit Logic Type: Choose between “Cross” or “Exit OB/OS” logic
Trading Mode: Select either "Spot" or "Leverage" depending on your use case
Why It’s Published Separately
This script is not a cosmetic or minor variation of the original indicator. It introduces:
Entry/exit logic
Order execution
Strategy testing capabilities
Mode selection (Spot vs. Leverage)
Signal logic control (Cross vs. Band Exit)
Because the original VBSMI indicator is widely used as a charting and confirmation tool, converting it into a strategy changes how it functions. This version is intended for strategy evaluation and automation, while the original remains available for discretionary and visual use.
Use Cases
This strategy is best suited for:
Evaluating VBSMI-based signals in backtests
Comparing entry and exit logic over time
Testing setups on different assets and timeframes
Automating VBSMI-based logic in a structured and risk-aware framework
Disclaimer
This strategy is for educational purposes only. It does not guarantee future results or profitability. Always test in simulation before using any strategy live, and use proper risk management and trade discipline.
Uptrick: Stellar NexusOverview
Uptrick: Stellar Nexus is a multi-layered chart tool designed to help traders visualize market behavior with enhanced clarity and depth. It presents various overlays, signal triggers, and an asset-level behavioral table in one cohesive interface. Its core focus is to illustrate how different market states shift over time. By displaying directional structures, dynamic zones, momentum shifts, and a real-time probability assessment of multiple assets, it aims to deliver a comprehensive perspective for those looking to navigate complex market environments more confidently.
Purpose
The primary purpose of Stellar Nexus is to unify several market assessment methods into a single framework, sparing users the need to rely on multiple disjointed indicators. It is especially useful for traders who value having layered signals, interactive overlays, and a quick reference to asset-specific metrics within one tool. By consolidating multiple market insights, the script aspires to reduce guesswork, limit information overload, and present clear triggers for potential trade opportunities or risk management decisions.
Originality
Stellar Nexus stands out because it relies on a proprietary set of logic layers, each carefully designed to detect nuanced shifts in price movement. The script brings forward a streamlined depiction of underlying market changes through color-coded zones, shape markers, and short textual tags. Its architecture also accommodates multiple “modes” of viewing the market—be it through layered cloud structures, trend ribbons, or step-based overlays—so traders can adapt its outputs to match changing conditions. The presence of a specialized probability table and a real-time market state meter (HUD Meter) further underscores its uniqueness, providing at-a-glance scoring for various instruments and a gauge that visually displays ongoing transitions from trending to ranging phases.
Inputs
Stellar Nexus includes several user-configurable settings, organized into themed groups. Each input subtly modifies how information is derived or rendered on the chart:
General
Silken Veil (integer input) : Governs how smooth or responsive various underlying signals will appear.
Canvas (dropdown) : Chooses the primary visual overlay style among Nebula Trail, Velora, or Stellar Stepfilter.
Signals (dropdown) : Selects which built-in signal engine (Fluxor or Flowgen) is responsible for painting buy and sell markers.
Nova Tension (integer input) : Influences the internal motion sensitivity used by certain triggers.
Astral Ribbon (integer input) : Imparts a broader directional bias layer that can highlight whether the current environment is bullish or bearish.
Bands
Phase Delay (integer input) : Impacts baseline offsets for certain dynamic band calculations.
Band Softener (float input) : Creates a blended baseline, balancing two distinct smoothing techniques.
Spread Factor (float input) : Scales how wide or narrow the generated envelope bands become.
Layer Offset (float input) : Adjusts spacing between multiple layered boundaries in the band structure.
Smooth Mode (dropdown boolean) : Toggles an extra layer of smoothing on or off for the plotted envelopes.
Feed Matrix
Burst (integer input) : Adjusts how the Flowgen engine interprets momentum buildup. Higher values generally lead to more conservative signals.
Delta Curve Sync (integer input) : Alters the sensitivity of directional alignment within the Flowgen system, refining how quickly the script adapts to market slope changes.
Lambda Pulse Shift (integer input) : Controls timing offsets within the Flowgen structure, subtly influencing the trigger timing of transitions.
Sync Drift Limit (integer input) : Provides a stabilizing effect on the internal motion detection engine, helping reduce erratic behavior during choppy conditions.
WMA Open Filter Tunnel (integer input) : Filters signal validity by applying a dynamic range check on opening price structures, reducing false positives in unstable markets.
Probability Table
Show Predictability Table (boolean) : Enables or disables a table of asset metrics.
Show Numeric Values (boolean) : Switches between displaying numeric values and using simple directional markers in the table cells.
Stepfilter
Sensitivity (dropdown) : Offers a range of speed profiles (Very Fast to Very Slow and TURTLE option) that define how quickly or slowly the step-based overlay reacts to price changes.
HUD Meter
Show Stellar HUD Meter (boolean) : Turns on or off a specialized gauge for quick insight into trending vs. ranging conditions.
Take Profit Signals
Show TP Signals (boolean) : Determines whether exit or take-profit markers are displayed after certain conditions have been met.
Phase Length (integer input) : Influences the internal baseline used for the exit signal logic.
Sync Channel (integer input) : Sets a period within which different data points are compared or synced.
Filter (integer input) : Imposes an additional smoothing on exit-related cues.
Features
Signals (Fluxor and Flowgen)
Fluxor
Logic: Fluxor focuses on detecting specific price transitions, validating them against an internal directional and momentum layer, and then confirming the move based on the script’s overarching market bias.
Visual Representation: When Fluxor is activated, up and down label markers (“▲+” or “▼+”) appear at points the system regards as noteworthy transitions. These do not guarantee trades but are designed to guide users on when buying or selling pressure may have intensified or reversed.
How It Helps: Fluxor is streamlined for those who want simpler, clearer triggers that factor in both trend alignment and short-term motion shifts. This option is more for mean reversion traders.
Flowgen
Logic: Flowgen employs a slightly more sophisticated approach that evaluates multiple “environmental layers,” including structural alignment, directional slope checks, and distinct open-state filters.
Visual Representation: When Flowgen senses a valid transition, it prints discrete up and down markers, much like Fluxor, but triggered by different, multi-layer considerations.
How It Helps: Flowgen caters to traders who desire more emphasis on layered agreement—where multiple aspects of the market must line up before a signal is shown. This option is more for trend following traders.
Overlays (Nebula Trail, Velora, Stellar Stepfilter)
Nebula Trail
Purpose: This indicator employs dynamic, color-coded bands around price action to illustrate prevailing market bias and track which side—bulls or bears—wields greater influence, aligning with a trend-following approach.
Usage: This indicator creates outer and inner “band” regions that can function as potential support or resistance in alignment with market momentum. In bullish phases, the cloud below price acts as a supportive barrier, whereas during bearish conditions, the cloud above price provides a point of resistance. When a bearish signal is detected, traders may enter short positions on a price bounce off this band and then exit when subsequent take-profit cues appear, effectively leveraging the band for both entry and exit strategies.
Velora
Purpose: Extends the concept of band visualization into layered “tiers,” giving a more fine-grained view of how price transitions from one band to another.
Representation: Zones are subdivided into multiple steps, each with distinct shading. As the script’s internal logic detects shifts between bullish or bearish conditions, these layered bands expand or contract to reflect changing momentum.
Usage: Velora subdivides zones into multiple steps, each featuring distinct shading. As the script's internal logic detects shifts between bullish or bearish conditions, these layered bands expand or contract, signaling changes in momentum. When price enters the upper band, especially if the HUD meter shows less definitive momentum, it may hint at a non-trending environment; conversely, in a bearish scenario, the lower band can act as potential support. Narrower bands often point to an impending breakout, while wider bands can suggest a possible reversion in price. Velora is well-suited for traders wanting to see more intermediate zones where the market may hesitate or show partial confirmation—ideal for refined entries or exits.
Smooth:
Choppy:
Stellar Stepfilter
Purpose: Focuses on a persistent directional line that only updates when the script’s logic deems a genuine shift is taking place.
Representation: A single line plots on the chart to represent the “locked” direction. During periods of noise or indecision, this line may remain static, reducing false signals. Optionally, bars can be recolored to reflect bullish or bearish states.
Usage: Traders who prefer a minimalistic, stand-back approach often select Stellar Stepfilter for its ability to filter out choppy conditions and highlight clearer momentum strides. When the line remains flat—particularly in the very slow or “turtle” mode—it signals a ranging market, offering valuable insight into periods of reduced volatility. In TURTLE mode, bars are recolored green or orange to reflect locked trend direction more visibly. TURTLE mode offers the most conservative setting within the Stepfilter engine, emphasizing stability and clarity by reacting only to the strongest directional conditions and visually reinforcing its state through bar coloring.
Very Fast
Very Slow
TURTLE Mode
Probability Table
Description: The Probability Table is displayed on the top-right corner (by default). It automatically fetches data for a handful of assets (in this case, five popular cryptocurrencies), then scores each asset on multiple behavioral metrics. By default, the Probability Table monitors SOL, BTC, ETH, BNB, and XRP from Binance.
Metrics Explained:
HV: Suggests how the asset’s price is fluctuating relative to a standard reference.
ATR/Vol: A ratio that provides insight into volatility compared to trading activity.
WBR: Compares candle wicks against their bodies to gauge the frequency of price swings outside an open-close range.
Liq Clust: Indicates if there are pockets of stable or unstable liquidity.
Momentum: Observes shifts in buying or selling pressure.
PRI: Shows a baseline measure of how far price has deviated from a certain average over time.
Final Verdict: Based on each metric’s reading, an overall classification emerges: Predictable, Moderate, or Chaotic.
How It Helps: Traders can quickly scan this table to see if an asset’s environment is “Predictable” (potentially more structured), “Moderate” (balanced or transitional), or “Chaotic” (unstable and riskier). Each cell can optionally show either numeric approximations or simple “up/down” arrows to reduce clutter.
Non Numeric Values
Numeric Values
Stellar HUD Meter
Description: Located at the top center of the chart, this horizontal gauge toggles between “Trending” and “Ranging,” representing how firmly price is locked in directional expansion versus sideways hesitation.
Mechanics (General): The gauge increments or decrements over time, smoothing out abrupt shifts. A pointer slides across the meter, indicating whether conditions are leaning more toward persistent momentum or uncertain, choppy movement.
How It Helps: This immediate visual feedback helps traders decide if momentum strategies or mean-reversion approaches are more suitable at a given moment, avoiding reliance on guesswork alone.
Take Profit Signals
Description: After any buy or sell trigger occurs (either through Fluxor or Flowgen), the script can flag up to three potential exit points.
Trigger Logic (General): These exits appear when certain internal checks sense that short-term upside or downside pressure may be waning.
Representation: Small markers (“X”) appear near the top or bottom of the candle.
How It Helps: Rather than passively holding a position, these optional signals remind traders of possible exhaustion points. If they choose to follow them, it can help secure partial or full profits during a trend.
Why more than one indicator?
Having more than one internal indicator engine allows Stellar Nexus to adapt to different market behaviors and personal trading styles. Sometimes traders require swift, high-frequency triggers (Fluxor). Other times, they prefer more layered agreement before taking a position (Flowgen). Similarly, each overlay—Nebula Trail, Velora, and Stellar Stepfilter—offers a distinct method for visualizing price action. Markets are dynamic, and no single representation is ideal for all conditions. By blending multiple approaches into one script, Stellar Nexus provides flexibility: a user can switch between sets of signals or overlays based on market phase, personal risk preference, or the timeframe being traded.
Additional Features
Alert System: Built-in alerts for every trigger or state change ensure that traders can receive real-time notifications, even when away from the chart. The alert system includes buy/sell triggers, trend shifts, overlay transitions, take-profit points, and predictability status changes across monitored assets.
Selective Visibility: Users can enable or disable various modules—Probability Table, HUD Meter, Take Profit Signals—to keep their chart interface uncluttered.
State Persistence: Certain modules “lock in” their reading until a strong reason emerges to change it, which can help minimize false flips in volatile conditions.
Tailored Aesthetics: Color choices and label styling are curated to be visually distinct, reducing confusion when multiple signals or overlays occur simultaneously.
Conclusion
Uptrick: Stellar Nexus is a comprehensive, multi-layer script that merges aesthetic clarity with functional depth. It combines diverse overlays, signal engines, probability analyses, and a heads-up market meter into one cohesive tool. By handling trending vs. ranging states, evaluating asset predictability, and offering selective take-profit cues, it serves as a versatile companion for traders who want organized, visually intuitive guidance. Its originality is found not only in how it disguises internal computations, but in the ease with which users can cycle through different overlays and signals to suit changing market conditions. As always, personal due diligence, market awareness, and risk management remain essential. Stellar Nexus simply provides a refined canvas on which to read and interpret price action more confidently.
Disclaimer
This indicator is provided solely for informational and educational purposes. It does not constitute investment advice or a recommendation to engage in any trading activities. Trading and investing in financial markets involve significant risk, and past performance is not indicative of future results. Always conduct your own research, utilize proper risk management, and consider consulting a qualified financial professional before making any investment decisions. Neither the creator nor any contributors to this script accept any liability for financial losses or damages arising from its use. Users of this indicator assume full responsibility for their trading activities.
Market OracleMarket Oracle Indicator: User Guide
Market Oracle is a powerful, all-in-one trading indicator for TradingView that combines multiple technical signals into a clear, actionable dashboard. Built for traders seeking a reliable edge, it analyzes trend, momentum, volatility, volume, and more to generate high-confidence buy and sell signals. With features like dynamic position sizing, market regime performance tracking, and customizable settings, it’s perfect for stocks, forex, crypto, or any market on any timeframe.
What It Does
Market Oracle evaluates market conditions using a blend of proven indicators (RSI, Stochastic RSI, EMAs, SuperTrend, MACD, Ichimoku Cloud, Bollinger Bands, ATR, ADX, and candlestick patterns) to produce a Composite Score (0-100) that reflects bullish or bearish strength. It generates:
Buy/Sell Signals: Triggered when the score crosses user-defined thresholds, filtered by volume, ADX, and trading hours.
Dynamic Position Sizing: Adjusts trade size based on volatility (ATR), reducing risk in choppy markets.
Market Regime Insights: Tracks performance in trending vs. ranging markets to highlight strategy strengths.
Comprehensive Dashboard: Displays real-time metrics like signal confidence, stop/take-profit levels, win rates, and more.
Whether you’re a day trader, swing trader, or long-term investor, Market Oracle simplifies decision-making with clear insights and robust backtesting.
Key Features
Composite Score:
Combines trend (EMAs, SuperTrend, MACD), momentum (RSI, Stochastic RSI), volatility (Bollinger Bands, ATR), volume (OBV, MA), Ichimoku Cloud, divergences, multi-timeframe trends, and candlestick patterns.
Score > 50 indicates bullishness; < 50 indicates bearishness. Extreme values (>90 or <10) flag overbought/oversold conditions.
Smart Signals:
Buy signals trigger when the score exceeds a threshold (default 70), with filters for volume, ADX strength, and Ichimoku/pattern confirmation.
Sell signals trigger below 100-threshold (default 30), with similar filters.
Signals include confidence levels (0-100%) based on indicator alignment.
Dynamic Position Sizing:
Scales trade size using ATR to limit risk in volatile markets (e.g., smaller positions when ATR is high).
Caps volatility adjustments (default 3x ATR) to maintain reasonable sizing.
Bases risk on a user-defined percentage (default 1% per trade).
Market Regime Performance:
Identifies trending (high ADX or wide Bollinger Bands) vs. ranging markets.
Tracks win rates separately for each regime, helping you optimize strategies for specific conditions.
Backtesting Metrics:
Shows buy/sell win rates, recent win rate, trending/ranging win rates, profit factor, max drawdown, and equity trend.
Helps evaluate strategy performance over time.
Customizable Dashboard:
Displays key metrics: Composite Score, Trend, Momentum, Volatility, Ichimoku, ADX, Divergences, Signal Status, Confidence, Stop/Take-Profit, Position Size, and more.
Toggles to show/hide backtest stats, Ichimoku Cloud, or multi-timeframe trends.
Clean layout with no clutter (e.g., no unnecessary “!” markers).
Alerts:
Set alerts for Buy/Sell Signals, Signal Exits, High Scores, or Overbought/Oversold conditions.
Messages include score and confidence (e.g., “Oracle+: Buy signal (Score: 75.2, Confidence: 80%)”).
Flexible Settings:
Adjust thresholds, indicator lengths, weights, risk parameters, and more.
Enable/disable features like trailing stops, market regime filters, or trading hour restrictions.
How to Use It
1. Add to TradingView
Copy the Market Oracle script into TradingView’s Pine Editor.
Click “Add to Chart” to apply it to your chosen market (e.g., BTC/USD, EUR/USD, SPY).
The dashboard appears in the bottom-right corner, showing real-time data.
2. Read the Dashboard
The dashboard is split into three sections:
Market State:
Composite Score: Current score and confidence (e.g., “75.2 (50.4%)”). “(OB)” or “(OS)” flags overbought/oversold.
Adjusted Threshold: Signal trigger level, adjusted for market regime.
Trend/MTF Trend: Bullish, Bearish, or Neutral (based on EMAs, SuperTrend, higher timeframe).
Momentum: Bullish, Bearish, or Neutral (RSI, Stochastic RSI).
Volatility: High or Low (Bollinger Bands, ATR).
Ichimoku Cloud: Bullish, Bearish, or Neutral (if enabled).
ADX Strength: Strong or Weak.
Divergence: Bullish, Bearish, or None (RSI, MACD).
Signals:
Signal Status: “Buy”, “Sell”, or “None”.
Signal Confidence: Percentage (e.g., “80%”) based on indicator agreement.
Stop Level/Take-Profit: Price levels for risk management.
Position Size: Units to trade, adjusted for volatility.
Avg Trade Duration: Average bars per trade.
Signal History: Recent signals/exits (e.g., “Buy | Buy Win”).
Backtest (optional):
Buy/Sell Win Rate: Percentage of winning trades.
Recent Win Rate: Win rate for recent trades.
Trending/Ranging Win Rate: Performance by market condition.
Profit Factor: Profit-to-loss ratio.
Max Drawdown: Largest equity drop.
Equity Trend: Up, Down, or Flat.
3. Customize Settings
Access the indicator’s settings by clicking the gear icon:
Signal Sensitivity:
Base Signal Threshold (default 70): Higher = stricter signals.
Min Confidence for Alerts (default 60%): Filters weaker alerts.
Risk Management:
Risk % per Trade (default 1%): Sets base risk.
Max ATR Multiplier (default 3.0): Caps position size reduction.
Take-Profit Ratio (default 2.0): Sets reward-to-risk ratio.
Use Trailing Stop (default false): Enable for dynamic stops.
Filters:
Use Volume Filter (default true): Requires above-average volume.
Use ADX Filter (default true): Requires strong trend (ADX > 25).
Use Market Regime Filter (default true): Adjusts thresholds for trending/ranging markets.
Avoid Specific Hours (default false): Skip signals during set hours (e.g., 0-6 UTC).
Indicators:
Adjust lengths for RSI (14), EMAs (20/50), MACD (12/26/9), etc.
Enable/disable Use Candlestick Patterns (default true) and choose type (Hammer, Engulfing, etc.).
Display:
Show Backtest Metrics (default true): Show win rates and stats.
Show Ichimoku Cloud (default true): Include cloud signals.
Show MTF Trend (default true): Include higher timeframe trend.
4. Set Alerts
In TradingView, click the alarm icon and select Market Oracle conditions:
Buy/Sell Signal: Triggers on new signals with sufficient confidence.
Signal Exit: Triggers when a trade closes (stop or take-profit hit).
High Score Alert: Triggers when score exceeds a threshold (default 80).
Overbought/Oversold: Warns of extreme conditions (if enabled).
Alerts include details for easy tracking (e.g., score, confidence).
5. Test and Trade
Test Markets: Try on forex (EUR/USD 1H), crypto (BTC/USD 4H), or stocks (AAPL daily).
Check Volatility: Monitor Position Size in volatile markets (e.g., XAU/USD); it shrinks to reduce risk.
Evaluate Regimes: Use “Trending Win Rate” and “Ranging Win Rate” to see where the strategy shines.
Backtest: Review Profit Factor and Max Drawdown to assess performance.
Start Small: Use a demo account to test signals before trading live.
Tips for Success
Match Your Style: Adjust scoreThreshold and timeframe to suit day trading (e.g., 15m, stricter threshold) or swing trading (e.g., 4H, looser threshold).
Monitor Regimes: If “Trending Win Rate” is higher, focus signals during strong trends (high ADX).
Manage Risk: Keep riskPerTrade low (e.g., 0.5-2%) and review Position Size for sanity.
Combine with Analysis: Use signals alongside support/resistance or news events for confirmation.
Tune Parameters: Experiment with atrVolatilityCap (e.g., 2.0 for tighter sizing) or adxThreshold (e.g., 30 for stronger trends).
Avoid Overtrading: Filter signals with minConfidenceForAlert (e.g., 70%) to focus on high-probability setups.
Example Scenarios
Crypto Breakout (BTC/USD 4H):
Composite Score jumps to 82, Signal Status shows “Buy” with 80% confidence.
Position Size is moderate due to high ATR during a rally.
“Trending Win Rate” is 65%, suggesting strength in directional moves.
Set an alert and enter with a 2:1 take-profit (e.g., stop at 60,000, target at 62,000).
Forex Range (EUR/USD 1H):
Score hovers near 45, no signal (Neutral).
“Ranging Win Rate” is 55%, indicating decent performance in consolidation.
Wait for a score above 70 or use a higher timeframe (e.g., Daily MTF Trend).
Stock Swing (AAPL daily):
Score hits 75, “Buy” signal with a small Position Size (low ATR).
Dashboard shows Bullish Ichimoku and MTF Trend.
Trade with a trailing stop to capture a multi-day move.
Why Choose Market Oracle?
All-in-One: Combines multiple indicators into one easy-to-read dashboard, saving you time.
Adaptive: Adjusts signals and sizing for market conditions (trending, ranging, volatile).
Transparent: Shows confidence, win rates, and risk levels to build trust in trades.
Customizable: Tailor to any market, timeframe, or trading style with dozens of settings.
No Clutter: Clean interface with no distracting visuals, just actionable data.
Getting Started
Add Market Oracle to your chart and explore the dashboard.
Test on a market you trade (e.g., ETH/USD 1H) with default settings.
Adjust scoreThreshold or riskPerTrade to match your risk tolerance.
Set alerts for Buy/Sell Signals and monitor performance via “Trending Win Rate” and “Profit Factor”.
Join TradingView communities to share setups and tips!
For questions or tweaks (e.g., adding VWAP, changing alert conditions), consult your indicator’s developer or TradingView’s Pine Script resources. Happy trading!
