Elliott Wave Auto + Fib Targets + Scalper Strategy (Fixed)// Elliott Wave Auto + Fib Targets + Scalper Strategy
//
// Fixed by expert trader:
// - Replaced table with label-based visualization to avoid 'Column 2 is out of table bounds' error.
// - Uses label.new to display buy/sell signal counts in top-right corner, mimicking table layout.
// - Fixed array.sum() error: Replaced invalid range-based array.sum() with custom sum_array_range() function.
// - Removed barstate usage to fix 'Undeclared identifier barstate' error.
// - Replaced barstate.isconfirmed with true (process every bar).
// - Replaced barstate.isfirstconfirmed with bar_index == 0 (first bar).
// - Replaced strategy.alert with label.new for long/short entry signals (buy/sell markers).
// - Fixed array index out-of-bounds: Protected array.get() calls with size checks.
// - Fixed pyramiding: Set constant pyramiding=4 (max 5 entries); use allow_pyramiding to limit entries.
// - Fixed default_qty_value: Set constant default_qty_value=100.0; use entry_size_pct to scale qty.
// - Replaced alertcondition with labels for Elliott Wave patterns.
// - Fixed partial exits: 50% at TP1 with fixed SL, 50% at TP2 with fixed SL or trailing.
// - Fixed Elliott Wave pivot indexing for alternating H/L check.
// - Ensured proper position sizing and exit logic.
스크립트에서 "香港交易所+科技板+ETF+代码"에 대해 찾기
Macro & Earnings Dashboard — NY Fed CalendarMacro & Earnings Dashboard — NY Fed Calendar
This is an overlay indicator designed to provide a quick, real-time overview of the most critical upcoming US economic data releases and corporate earnings reports directly on your TradingView chart. It functions as a dynamic dashboard, removing the need to constantly check external calendars.
Key Features
1. Real-Time Economic Calendar (Bottom-Right Table)
The dashboard tracks the time remaining until the next release of five major, high-impact economic indicators. The data for these dates is pre-loaded directly from the New York Fed Economic Indicators Calendar (currently loaded for October through December 2025).
The tracked events include:
CPI (Consumer Price Index)
PPI (Producer Price Index)
Employment Situation (Non-Farm Payrolls / Unemployment Rate)
Interest Rate Decision (FOMC Meetings)
Consumer Sentiment (University of Michigan Survey)
2. Corporate Earnings Tracker (Top-Right Table)
This table uses TradingView's built-in data to calculate the estimated days remaining until the next Earnings Per Share (EPS) report for a curated list of high-profile NASDAQ tickers:
AAPL, NVDA, GOOG, TSLA, MSFT, AMZN, META
3. Color-Coded Urgency
The "Days" column for both macro and earnings tables uses a traffic light system to instantly communicate how soon the event is:
Red: The event is scheduled for Today or Tomorrow (0–1 day away).
Orange: The event is scheduled for the current week (within 6 days).
Teal: The event is more than a week away.
Gray: The date is currently unavailable or outside the loaded calendar range.
Iron Condor Pro v6 – Full EngineIronCondor Engine v6.6 is a multi-mode options strategy tool for planning and managing iron condors, straddles, strangles, and butterflies. It supports both setup planning and live trade tracking with modeled delta, risk-based strike selection, IV rank estimation, and visual breach alerts.
Use Setup Mode to preview strike structures based on IV proxy, ATR, delta targeting, and risk tier (High/Mid/Low/Delta). Use Live Mode to track real trades, enter strike/premium data, and monitor live P&L, delta drift, and range status.
This script does not connect to live option chains. Volatility and delta are modeled using price history. All strikes and premiums must be confirmed using your broker before placing trades. Best used with strong support/resistance levels and high IV rank (30%+).
For educational purposes only.
Workflow Guide
Use this flow whether you're setting up on Sunday night or any day before placing a trade.
Step 0: Pre-Script Preparation
Before using the script:
Identify major support and resistance zones on your chart. Define the expected range or consolidation area. Use this context to help evaluate strike placement
1. Setup Phase (Pre-Trade Planning)
Step 1 – Load the Script
Add: IronCondor Engine v6.6 – Full Risk/Decay Edition to your chart
Step 2 – Set Mode = Setup
This enables planning mode, where the engine calculates strike combinations based on:
Your selected risk profile (High, Mid, Low, or Delta)
Historical volatility (20-day log return)
ATR (Average True Range)
Target short delta (adjustable)
Step 3 – Review Setup Table
Enable Show Setup Table to view calculated strikes and width by risk tier.
Adjust any of the following as needed:
Target Short Delta
Strike Interval ($)
Width multipliers (High/Mid/Low)
Risk tier under Auto-Feed Choice
Step 4 – Evaluate the Setup
Is the net credit at least 1.5–2.0x your max risk?
Are the short strikes clearly outside support/resistance zones?
Are the short deltas between 0.15 and 0.30?
Is the range wide enough to handle normal price movement?
Step 5 – Prep for Execution
Enable Auto-Feed Setup → Live to carry Setup strikes into Live mode
Or disable it if you prefer to manually enter strikes later
2. Trade Execution (Live Tracking Mode)
Step 1 – Place the Trade with Your Broker
Use your brokerage (TOS, Tasty, IBKR, etc.) to place the iron condor or other structure
Step 2 – Set Mode = Live
In Live mode:
If Auto-Feed is ON, the Setup strikes auto-populate
If Auto-Feed is OFF, manually enter:
Short and long strikes (Call and Put)
Premiums collected/paid per leg
Total net credit (Entry Credit)
Optional: Input current mid prices for each leg in the "Live Chain" section to track live mark-to-market P&L
Once all required fields are valid, the script activates:
Real-time profit/loss tracking
Max risk estimate
Delta monitoring on short legs
IV Rank estimate
Breach detection system
Chart visuals (if enabled)
3. Trade Management (During the Week)
While the trade is active, use the dashboard and visuals to monitor:
Key Metrics:
Unrealized P/L %
Mark-to-market value vs entry credit
Daily decay (theta)
Days until expiration
Breach status:
In Range
Near Breach
Breached
Alerts:
Price near short strike → suggests roll
Price breaches long strike → breach alert
50% or 75% profit → optional exit signal
Delta exceeds threshold → exposure may need adjustment
Management Tips:
At 50–75% profit: consider closing early
If price nears a short leg: roll, hedge, or manage
If nearing expiry: decide whether to hold or close
If IV collapses: may accelerate time decay or reduce exit value
4. End-of-Week or Expiration Management
If Profit Target Hit
Close early to reduce risk and lock gains
If Still Open Near Expiry
Close the position or
Hold through expiration only if you're fully prepared for pinning/gamma/assignment scenarios
Avoid holding open spreads over the weekend unless part of a defined strategy
Reference Notes
Strike Width
Defined as:
Width = Distance between Short and Long strike
Used for calculating max loss and breach visuals
Delta Guidelines
0.15–0.20 = safer, wider range, lower credit
0.25–0.30 = more aggressive, tighter range, higher credit
Use Target Short Delta input to adjust auto-selected strikes accordingly
Credit Example
Sell Call: $1.04
Sell Put: $0.23
Buy Call + Put wings: $0.14
Net Credit = $1.13 = $113 per contract (max profit)
This is the max profit if price stays between short strikes through expiration
IV Rank (Estimated)
This script does not use options chain IV data.
Instead, it calculates a volatility proxy:
ivRaw = ta.stdev(log returns, 20) * sqrt(252)
IV Rank is then calculated as the percentile of this value within the last 252 bars.
High IV Rank (30%–100%) → better premium-selling conditions
Low IV Rank (<30%) → lower edge for condors
Ideal to sell premium when IV Rank is above 30–50%
Disclosures and Limitations
This script is for educational use only
It does not connect to live option chains
All strikes, deltas, and premiums must be validated through your broker
Always confirm real-time IV, delta, and pricing before placing a trade
EMA KitEMA Kit delivers multiple 1D EMA's wrapped into a single indicator.
I was annoyed with having a bunch of EMA indicators on the left side of my chart for each individual EMA I rely on, so I created a single indicator with all of them.
This EMA kit allows you to select any combination of the following EMA's: 3D, 5D, 8D, 21D, 34D, 50D, 100D, 200D, and 200W. They are all based on the 1D timeframe regardless of the timeframe you're currently viewing on your chart - for example, if you toggle from a Daily chart to a 15 minute chart, the EMA's won't change to reflect the 15 minute timeframe. EMA Kit smoothes the lines to prevent staggering on lower timeframes. You can change the color scheme and line thickness and even toggle between different line types like area, histogram, etc. You also have the option to turn end-of-line price labels on/off. Current price level for each EMA is highlighted on the price scale.
EMA/SMA Market Indicator V1 (Situational Awareness Uptrend)Red condition (highest priority in code)
Background = red if any of these are true:
Close < 10MA
OR Close < 20MA
OR (10MA and 20MA slopes ≤ threshold → “flat/down”)
Green condition (only if not red)
Background = green if:
(Close > 10MA or Close > 20MA)
AND Close > 50MA
Otherwise = nothing (transparent)
If neither red nor green is true → background is off.
So when is there no background?
Close is not below 10MA
Close is not below 20MA
MAs are not both flat/down
AND the price fails the “green test” (ex. under 50MA, or not above 10/20).
Best MA Finder: Sharpe/Sortino ScannerThis script, Best MA Finder: Sharpe/Sortino Scanner, is a tool designed to identify the moving average (SMA or EMA) that best acts as a dynamic trend threshold on a chart, based on risk-adjusted historical performance. It scans a wide range of MA lengths (SMA or EMA) and selects the one whose simple price vs MA crossover delivered the strongest results using either the Sharpe ratio or the Sortino ratio. Reading it is intuitive: when price spent time above the selected MA, conditions were on average more favorable in the backtest; below, less favorable. It is a trend and risk gauge, not an overbought or oversold signal.
What it does:
- Runs individual long-only crossover backtests for many MA lengths across short to very long horizons.
- For each length, measures the total number of trades, the annualized Sharpe ratio, and the annualized Sortino ratio.
- Uses the chosen metric value (Sharpe or Sortino) as the score to rank candidates.
- Applies a minimum trade filter to discard statistically weak results.
- Optionally applies a local stability filter to prefer a length that also outperforms its close neighbors by at least a small margin.
- Selects the optimal MA and displays it on the chart with a concise summary table.
How to use it:
- Choose MA type: SMA or EMA.
- Choose the metric: Sharpe or Sortino.
- Set the minimum trade count to filter out weak samples.
- Select the risk-free mode:
Auto: uses a short-term risk-free rate for USD-priced symbols when available.
Manual: you provide a risk-free ticker.
None: no risk-free rate.
- Optionally enable stability controls: neighbor radius and epsilon.
- Toggle the on-chart summary table as needed.
On-chart output:
- The selected optimal MA is plotted.
- The optional table shows MA length, number of trades, chosen metric value annualized, and the annual risk-free rate used.
Key features:
- Risk-adjusted optimization via Sharpe or Sortino for fair, comparable assessment.
- Broad MA scan with SMA and EMA support.
- Optional stability filter to avoid one-off spikes.
- Clear and auditable presentation directly on the chart.
Use cases:
- Traders who want a defensible, data-driven trend threshold without manual trial and error.
- Swing and trend-following workflows across timeframes and asset classes.
- Quick SMA vs EMA comparisons using risk-adjusted results.
Limitations:
- Not a full trading strategy with position sizing, costs, funding, slippage, or stops.
- Long-only, one position at a time.
- Discrete set of MA lengths, not a continuous optimizer.
- Requires sufficient price history and, if used, a reliable risk-free series.
This script is open-source and built from original logic. It does not replicate closed-source scripts or reuse significant external components.
Fetti Fields Header (Presets)This is for individuals that like to customize their charts and add some style and motivation
30m stratDefine a time range, and the indicator will highlight it with a shaded area
This indicator lets you visualize higher timeframe levels while viewing a lower timeframe chart.
SMC Volatility Liquidity Prothis one’s a confluence signaler. it fires “BUY CALL” / “BUY PUT” labels only when four things line up at once: trend, volatility squeeze, a liquidity sweep, and MACD momentum. quick breakdown:
what each block does
Trend filter (context)
ema50 > ema200 ⇒ trendUp
ema50 < ema200 ⇒ trendDn
Plots both EMAs for visual context.
Volatility compression (setup)
20-period Bollinger Bands (stdev 2).
bb_squeeze is true when current band width < its 20-SMA ⇒ price is compressed (potential energy building).
Liquidity sweep (trigger)
Tracks 20-bar swing high/low.
Long sweep: high > swingHigh ⇒ price just poked above the prior 20-bar high (took buy-side liquidity).
Short sweep: low < swingLow ⇒ price just poked below the prior 20-bar low (took sell-side liquidity).
MACD momentum (confirmation)
Standard MACD(12,26,9) histogram.
Bullish: hist > 0 and rising versus previous bar.
Bearish: hist < 0 and falling.
the actual entry signals
LongEntry = trendUp AND bb_squeeze AND liquiditySweepLong AND macdBullish
→ prints a green “BUY CALL” label below the bar.
ShortEntry = trendDn AND bb_squeeze AND liquiditySweepShort AND macdBearish
→ prints a red “BUY PUT” label above the bar.
alerts & dashboard
Alerts: fires when those long/short conditions hit so you can set TradingView alerts on them.
On-chart dashboard (bottom-right):
Trend (Bullish/Bearish/Neutral)
Squeeze (Yes/No)
Liquidity (Long/Short/None)
Momentum (Bullish/Bearish/Neutral)
Current Signal (BUY CALL / BUY PUT / WAIT)
(btw the comment says “2 columns × 5 rows” but the table is actually 5 columns × 2 rows—values under each label across the row.)
what it’s trying to capture (in plain english)
Trade with the higher-timeframe bias (EMA 50 over 200).
Enter as volatility compresses (bands tight) and a sweep grabs stops beyond a 20-bar extreme.
Only pull the trigger when momentum agrees (MACD hist direction & side of zero).
caveats / tips
It’s an indicator, not a strategy—no entries/exits/backtests baked in.
Signals are strict (4 filters), so you’ll get fewer but “cleaner” prints; still not magical.
The liquidity-sweep check uses the prior bar’s 20-bar high/low ( ), so on bar close it won’t repaint; intrabar alerts may feel jumpy if you alert “on every tick.”
Consider adding:
Exit logic (e.g., ATR stop + take-profit, or opposite signal).
Minimum squeeze duration (e.g., bb_squeeze true for N bars) to avoid one-bar dips in width.
Cool-down after a signal to prevent clustering.
Session/time or volume filter if you only want liquid hours.
if you want, I can convert this into a backtestable strategy() version with ATR-based stops/targets and a few toggles, so you can see stats right away.
Whole number highlightsThis very simple indicator provides what should be a built-in TradingView feature: it highlights the whole number currency amounts (dollar, pound, euro, etc.) on your chart with a simple and unobtrusive dotted line. By default, a slightly thicker dotted line is used on whole number multiples of ten.
These are important to highlight because they often act as "psychological levels" in the marketplace, especially when they coincide with more significant levels of support or resistance. They can also help provide a sense of scale to the chart, which is useful when switching between various zoom levels.
It's open-source, so it can be easily combined into other indicators, which should especially be useful for those with limited plans who are allowed a limited number of indicators.
Disclaimer : Use at your own risk. This indicator and the strategy described herein are not in any way financial advice, nor does the author of this script make any claims about the effectiveness of this indicator or of any related strategy, which may depend highly on the discretion and skill of the trader executing it, among many other factors outside of the author's control. The author of this script accepts no liability, and is not responsible for any trading decisions that you may or may not make as a result of this indicator. You should expect to lose money if using this indicator.
TA█ TA Library
📊 OVERVIEW
TA is a Pine Script technical analysis library. This library provides 25+ moving averages and smoothing filters , from classic SMA/EMA to Kalman Filters and adaptive algorithms, implemented based on academic research.
🎯 Core Features
Academic Based - Algorithms follow original papers and formulas
Performance Optimized - Pre-calculated constants for faster response
Unified Interface - Consistent function design
Research Based - Integrates technical analysis research
🎯 CONCEPTS
Library Design Philosophy
This technical analysis library focuses on providing:
Academic Foundation
Algorithms based on published research papers and academic standards
Implementations that follow original mathematical formulations
Clear documentation with research references
Developer Experience
Unified interface design for consistent usage patterns
Pre-calculated constants for optimal performance
Comprehensive function collection to reduce development time
Single import statement for immediate access to all functions
Each indicator encapsulated as a simple function call - one line of code simplifies complexity
Technical Excellence
25+ carefully implemented moving averages and filters
Support for advanced algorithms like Kalman Filter and MAMA/FAMA
Optimized code structure for maintainability and reliability
Regular updates incorporating latest research developments
🚀 USING THIS LIBRARY
Import Library
//@version=6
import DCAUT/TA/1 as dta
indicator("Advanced Technical Analysis", overlay=true)
Basic Usage Example
// Classic moving average combination
ema20 = ta.ema(close, 20)
kama20 = dta.kama(close, 20)
plot(ema20, "EMA20", color.red, 2)
plot(kama20, "KAMA20", color.green, 2)
Advanced Trading System
// Adaptive moving average system
kama = dta.kama(close, 20, 2, 30)
= dta.mamaFama(close, 0.5, 0.05)
// Trend confirmation and entry signals
bullTrend = kama > kama and mamaValue > famaValue
bearTrend = kama < kama and mamaValue < famaValue
longSignal = ta.crossover(close, kama) and bullTrend
shortSignal = ta.crossunder(close, kama) and bearTrend
plot(kama, "KAMA", color.blue, 3)
plot(mamaValue, "MAMA", color.orange, 2)
plot(famaValue, "FAMA", color.purple, 2)
plotshape(longSignal, "Buy", shape.triangleup, location.belowbar, color.green)
plotshape(shortSignal, "Sell", shape.triangledown, location.abovebar, color.red)
📋 FUNCTIONS REFERENCE
ewma(source, alpha)
Calculates the Exponentially Weighted Moving Average with dynamic alpha parameter.
Parameters:
source (series float) : Series of values to process.
alpha (series float) : The smoothing parameter of the filter.
Returns: (float) The exponentially weighted moving average value.
dema(source, length)
Calculates the Double Exponential Moving Average (DEMA) of a given data series.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Double Exponential Moving Average value.
tema(source, length)
Calculates the Triple Exponential Moving Average (TEMA) of a given data series.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Triple Exponential Moving Average value.
zlema(source, length)
Calculates the Zero-Lag Exponential Moving Average (ZLEMA) of a given data series. This indicator attempts to eliminate the lag inherent in all moving averages.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Zero-Lag Exponential Moving Average value.
tma(source, length)
Calculates the Triangular Moving Average (TMA) of a given data series. TMA is a double-smoothed simple moving average that reduces noise.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Triangular Moving Average value.
frama(source, length)
Calculates the Fractal Adaptive Moving Average (FRAMA) of a given data series. FRAMA adapts its smoothing factor based on fractal geometry to reduce lag. Developed by John Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Fractal Adaptive Moving Average value.
kama(source, length, fastLength, slowLength)
Calculates Kaufman's Adaptive Moving Average (KAMA) of a given data series. KAMA adjusts its smoothing based on market efficiency ratio. Developed by Perry J. Kaufman.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the efficiency calculation.
fastLength (simple int) : Fast EMA length for smoothing calculation. Optional. Default is 2.
slowLength (simple int) : Slow EMA length for smoothing calculation. Optional. Default is 30.
Returns: (float) The calculated Kaufman's Adaptive Moving Average value.
t3(source, length, volumeFactor)
Calculates the Tilson Moving Average (T3) of a given data series. T3 is a triple-smoothed exponential moving average with improved lag characteristics. Developed by Tim Tillson.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
volumeFactor (simple float) : Volume factor affecting responsiveness. Optional. Default is 0.7.
Returns: (float) The calculated Tilson Moving Average value.
ultimateSmoother(source, length)
Calculates the Ultimate Smoother of a given data series. Uses advanced filtering techniques to reduce noise while maintaining responsiveness. Based on digital signal processing principles by John Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the smoothing calculation.
Returns: (float) The calculated Ultimate Smoother value.
kalmanFilter(source, processNoise, measurementNoise)
Calculates the Kalman Filter of a given data series. Optimal estimation algorithm that estimates true value from noisy observations. Based on the Kalman Filter algorithm developed by Rudolf Kalman (1960).
Parameters:
source (series float) : Series of values to process.
processNoise (simple float) : Process noise variance (Q). Controls adaptation speed. Optional. Default is 0.05.
measurementNoise (simple float) : Measurement noise variance (R). Controls smoothing. Optional. Default is 1.0.
Returns: (float) The calculated Kalman Filter value.
mcginleyDynamic(source, length)
Calculates the McGinley Dynamic of a given data series. McGinley Dynamic is an adaptive moving average that adjusts to market speed changes. Developed by John R. McGinley Jr.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the dynamic calculation.
Returns: (float) The calculated McGinley Dynamic value.
mama(source, fastLimit, slowLimit)
Calculates the Mesa Adaptive Moving Average (MAMA) of a given data series. MAMA uses Hilbert Transform Discriminator to adapt to market cycles dynamically. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: (float) The calculated Mesa Adaptive Moving Average value.
fama(source, fastLimit, slowLimit)
Calculates the Following Adaptive Moving Average (FAMA) of a given data series. FAMA follows MAMA with reduced responsiveness for crossover signals. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: (float) The calculated Following Adaptive Moving Average value.
mamaFama(source, fastLimit, slowLimit)
Calculates Mesa Adaptive Moving Average (MAMA) and Following Adaptive Moving Average (FAMA).
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: ( ) Tuple containing values.
laguerreFilter(source, length, gamma, order)
Calculates the standard N-order Laguerre Filter of a given data series. Standard Laguerre Filter uses uniform weighting across all polynomial terms. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Length for UltimateSmoother preprocessing.
gamma (simple float) : Feedback coefficient (0-1). Lower values reduce lag. Optional. Default is 0.8.
order (simple int) : The order of the Laguerre filter (1-10). Higher order increases lag. Optional. Default is 8.
Returns: (float) The calculated standard Laguerre Filter value.
laguerreBinomialFilter(source, length, gamma)
Calculates the Laguerre Binomial Filter of a given data series. Uses 6-pole feedback with binomial weighting coefficients. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Length for UltimateSmoother preprocessing.
gamma (simple float) : Feedback coefficient (0-1). Lower values reduce lag. Optional. Default is 0.5.
Returns: (float) The calculated Laguerre Binomial Filter value.
superSmoother(source, length)
Calculates the Super Smoother of a given data series. SuperSmoother is a second-order Butterworth filter from aerospace technology. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Period for the filter calculation.
Returns: (float) The calculated Super Smoother value.
rangeFilter(source, length, multiplier)
Calculates the Range Filter of a given data series. Range Filter reduces noise by filtering price movements within a dynamic range.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the average range calculation.
multiplier (simple float) : Multiplier for the smooth range. Higher values increase filtering. Optional. Default is 2.618.
Returns: ( ) Tuple containing filtered value, trend direction, upper band, and lower band.
qqe(source, rsiLength, rsiSmooth, qqeFactor)
Calculates the Quantitative Qualitative Estimation (QQE) of a given data series. QQE is an improved RSI that reduces noise and provides smoother signals. Developed by Igor Livshin.
Parameters:
source (series float) : Series of values to process.
rsiLength (simple int) : Number of bars for the RSI calculation. Optional. Default is 14.
rsiSmooth (simple int) : Number of bars for smoothing the RSI. Optional. Default is 5.
qqeFactor (simple float) : QQE factor for volatility band width. Optional. Default is 4.236.
Returns: ( ) Tuple containing smoothed RSI and QQE trend line.
sslChannel(source, length)
Calculates the Semaphore Signal Level (SSL) Channel of a given data series. SSL Channel provides clear trend signals using moving averages of high and low prices.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: ( ) Tuple containing SSL Up and SSL Down lines.
ma(source, length, maType)
Calculates a Moving Average based on the specified type. Universal interface supporting all moving average algorithms.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
maType (simple MaType) : Type of moving average to calculate. Optional. Default is SMA.
Returns: (float) The calculated moving average value based on the specified type.
atr(length, maType)
Calculates the Average True Range (ATR) using the specified moving average type. Developed by J. Welles Wilder Jr.
Parameters:
length (simple int) : Number of bars for the ATR calculation.
maType (simple MaType) : Type of moving average to use for smoothing. Optional. Default is RMA.
Returns: (float) The calculated Average True Range value.
macd(source, fastLength, slowLength, signalLength, maType, signalMaType)
Calculates the Moving Average Convergence Divergence (MACD) with customizable MA types. Developed by Gerald Appel.
Parameters:
source (series float) : Series of values to process.
fastLength (simple int) : Period for the fast moving average.
slowLength (simple int) : Period for the slow moving average.
signalLength (simple int) : Period for the signal line moving average.
maType (simple MaType) : Type of moving average for main MACD calculation. Optional. Default is EMA.
signalMaType (simple MaType) : Type of moving average for signal line calculation. Optional. Default is EMA.
Returns: ( ) Tuple containing MACD line, signal line, and histogram values.
dmao(source, fastLength, slowLength, maType)
Calculates the Dual Moving Average Oscillator (DMAO) of a given data series. Uses the same algorithm as the Percentage Price Oscillator (PPO), but can be applied to any data series.
Parameters:
source (series float) : Series of values to process.
fastLength (simple int) : Period for the fast moving average.
slowLength (simple int) : Period for the slow moving average.
maType (simple MaType) : Type of moving average to use for both calculations. Optional. Default is EMA.
Returns: (float) The calculated Dual Moving Average Oscillator value as a percentage.
continuationIndex(source, length, gamma, order)
Calculates the Continuation Index of a given data series. The index represents the Inverse Fisher Transform of the normalized difference between an UltimateSmoother and an N-order Laguerre filter. Developed by John F. Ehlers, published in TASC 2025.09.
Parameters:
source (series float) : Series of values to process.
length (simple int) : The calculation length.
gamma (simple float) : Controls the phase response of the Laguerre filter. Optional. Default is 0.8.
order (simple int) : The order of the Laguerre filter (1-10). Optional. Default is 8.
Returns: (float) The calculated Continuation Index value.
📚 RELEASE NOTES
v1.0 (2025.09.24)
✅ 25+ technical analysis functions
✅ Complete adaptive moving average series (KAMA, FRAMA, MAMA/FAMA)
✅ Advanced signal processing filters (Kalman, Laguerre, SuperSmoother, UltimateSmoother)
✅ Performance optimized with pre-calculated constants and efficient algorithms
✅ Unified function interface design following TradingView best practices
✅ Comprehensive moving average collection (DEMA, TEMA, ZLEMA, T3, etc.)
✅ Volatility and trend detection tools (QQE, SSL Channel, Range Filter)
✅ Continuation Index - Latest research from TASC 2025.09
✅ MACD and ATR calculations supporting multiple moving average types
✅ Dual Moving Average Oscillator (DMAO) for arbitrary data series analysis
Multi Momentum 10/21/42/63 — Histogram + 2xSMAMY MM INDICATOR INDIRED BY KARADI
It averages four rate-of-change snapshots of price, all anchored at today’s close.
If “Show as %” is on, the value is multiplied by 100.
Each term is a simple momentum/ROC over a different lookback.
Combining 10, 21, 42, 63 bars blends short, medium, and intermediate horizons into one number.
Positive MM → average upward pressure across those horizons; negative MM → average downward pressure.
Why those lengths?
They roughly stack into ~2× progression (10→21≈2×10, 21→42=2×21, 63≈1.5×42). That creates a “multi-scale” momentum that’s less noisy than a single fast ROC but more responsive than a long ROC alone.
How to read the panel
Gray histogram = raw Multi-Momentum value each bar.
SMA Fast/Slow lines (defaults 12 & 26 over the MM values) = smoothing of the histogram to show the trend of momentum itself.
Typical signals
Zero-line context:
Above 0 → bullish momentum regime on average.
Below 0 → bearish regime.
Crosses of SMA Fast & Slow: momentum trend shifts (fast above slow = improving momentum; fast below slow = deteriorating).
Histogram vs SMA lines: widening distance suggests strengthening momentum; narrowing suggests momentum is fading.
Divergences: price makes a new high/low but MM doesn’t → potential exhaustion.
Compared to a classic ROC
A single ROC(20) is very sensitive to that one window.
MM averages several windows, smoothing idiosyncrasies (e.g., a one-off spike 21 bars ago) and reducing “lookback luck.”
Settings & customization
Lookbacks (10/21/42/63): you can tweak for your asset/timeframe; the idea is to mix short→medium horizons.
Percent vs raw ratio: percent is easier to compare across symbols.
SMA lengths: shorter = more reactive but choppier; longer = smoother but slower.
Practical tips
Use regime + signal: trade longs primarily when MM>0 and fast SMA>slow SMA; consider shorts when MM<0 and fast
Golden Cross Master Filter by Carlos ChavezForget noisy Golden/Death Cross signals.
This is the **Golden Cross Master Filter** – built for traders who demand institutional-level confirmation.
✅ Exact EMA cross points with circle markers
✅ ATR / ADX / DI+ / DI- / Volume filters
✅ Gap% detection
✅ Visual OK/X dashboard
✅ Instant BUY/SELL labels & ready-to-use alerts
Cut the noise. Trade only the strongest crosses. 🚀
Golden Cross Master Filter is a professional tool to detect Golden and Death Crosses with institutional-grade filtering.
🚀 Features:
- ✅ ATR / ADX / DI+/DI- / Volume conditions
- ✅ Gap% detection (daily gap between yesterday’s close and today’s open)
- ✅ Visual dashboard with OK/X status
- ✅ Exact circle markers at EMA cross points
- ✅ Ready-to-use BUY/SELL labels when filters are confirmed
- ✅ Built-in alerts for easy automation
This indicator is designed for intraday and swing traders who rely on EMA crosses but want to eliminate false signals.
It works across multiple timeframes (10m, 1h, 4h, Daily) and adapts to different trading styles.
Whether you trade CALLs/PUTs or just want stronger confirmation for Golden/Death Crosses, this filter helps you focus only on high-probability setups.
Alerta de toque de la 200-Week SMACuando el precio toca la MMS de 200 semanas es una posible compra.
QTrade Golden, Bronze & Death, Bubonic Cross AlertsThis indicator highlights key EMA regime shifts with simple, color-coded triangles:
- Golden / Death Cross — 50 EMA crossing above/below the 200 EMA.
- Bronze / Bubonic Cross — 50 EMA crossing above/below the 100 EMA.
- Early-Warning Proxy — tiny triangles for the 4 EMA vs. 200 EMA (4↑200 and 4↓200). These often fire before the 50/100 and 50/200 crosses.
No text clutter on the chart—just triangles. Colors: gold (50↑200), red (50↓200), darker-yellow bronze (50↑100), burgundy (50↓100), turquoise (4↑200), purple (4↓200).
What it tells you (in order of warning → confirmation)
- First warning: 4 EMA crosses the 200 EMA (proxy for price shifting around the 200 line).
- Second warning: 50 EMA crosses the 100 EMA (Bronze/Bubonic).
- Confirmation: 50 EMA crosses the 200 EMA (Golden/Death).
Alerts included
- Golden Cross (50↑200) and Death Cross (50↓200)
- Bronze Cross (50↑100) and Bubonic Cross (50↓100)
- 4 EMA vs. 200 EMA crosses (up & down) — early-warning proxy
- Price–100 EMA events (touch/cross, if enabled in settings)
Horrible Pine ScriptA script with a bug in setting the background color. Specifically written for the QQQ. Regardless of the parameter, the color is always red. Three test values are output.
NASDAQ VWAP Distance Histogram (Multi-Symbol)📊 VWAP Distance Histogram (Multi-Symbol)
This custom indicator plots a histogram of price strength relative to the VWAP (Volume-Weighted Average Price).
The zero line is VWAP.
Histogram bars above zero = price trading above VWAP (strength).
Histogram bars below zero = price trading below VWAP (weakness).
Unlike a standard VWAP overlay, this tool lets you monitor multiple symbols at once and aggregates them into a single, easy-to-read histogram.
🔑 Features
Multi-Symbol Support → Track up to 10 different tickers plus the chart symbol.
Aggregation Options → Choose between average or median deviation across enabled symbols.
Percent or Raw Values → Display distance from VWAP as % of price or raw price points.
Smoothing → Apply EMA smoothing to calm intraday noise.
Color-Coded Histogram → Green above VWAP, red below.
Alerts → Trigger when the aggregate crosses above/below VWAP.
Heads-Up Table → Shows number of symbols tracked and current aggregate reading.
⚡ Use Cases
Market Breadth via VWAP → Monitor whether your basket of stocks is trading above or below VWAP.
Index Substitution → Create your own “mini index” by tracking a hand-picked set of tickers.
Intraday Confirmation → Use aggregate VWAP strength/weakness to confirm entries and exits.
Relative Strength Spotting → Switch on/off specific tickers to see who’s holding above VWAP vs. breaking down.
🛠️ Settings
Include Chart Symbol → Toggle to include the current chart’s ticker.
Smoothing → EMA length (set to 0 to disable).
Percent Mode → Show results as % of price vs. raw difference.
Aggregate Mode → Average or median across all active symbols.
Symbol Slots (S1–S10) → Enter tickers to track alongside the chart.
⚠️ Notes
Works best on intraday charts since VWAP is session-based.
Designed for confirmation, not as a standalone entry/exit signal.
Ensure correct symbol format (e.g., NASDAQ:AAPL if needed).
✅ Tip: Combine this with your regular price action strategy. For example, if your setup triggers long and the histogram is well above zero, that’s added confirmation. If it’s below zero, caution — the basket shows weakness.
Moving Average SlopeA simple tool that allows you to choose from multiple types of moving averages (e.g. WMA, EMA, SMA, HMA) and define the MA period, and lookback period for slope calculation.
