[CP]Pivot Boss Multi Timeframe CPR Inception with MACD and EMAINTRODUCTION:
This indicator combines multi-timeframe CPR bands with MACD Momentum and EMA trend, all projected on the candlestick chart through a novel visualization.
If you have seen my other indicators on TradingView, you would know that I use floor pivots a lot and “Secrets of a Pivot Boss” is my favorite book. While using floor pivots, time and again I have noticed an interesting price behavior,
Trending moves in price typically start from around the Central Pivot Range (CPR). The CPR could be from ANY timeframe. These moves can easily be caught using simple momentum and trend indicators like MACD and EMA crossovers.
Yes, it is that simple. Follow along to understand how to use this indicator.
INDICATOR SETTINGS:
RANGEBOUND MACD AND EMA MARKINGS:
TradingView limits the max number of labels that can be shown on a chart to 500. Therefore, if you go far back enough, you won't see any markings for the MACD or EMA setups. If you are looking to test the efficacy of this indicator in the past, change the start and end dates to your desired timeframe and then select the ‘Mark MACD and EMA Setups in Range?’ option.
MULTI TIMEFRAME CENTRAL PIVOT RANGE:
Here you can select CPRs and their bands from which timeframes are shown on the chart. I will share my favorite settings later in this description.
CPR CONFIGURATION:
Show CPR Labels: CPRs markings can carry labels, so that you don’t confuse between which line is what. Use this setting to toggle them On/Off.
Show Next Time Period Pivots: Check this option if you want to see the CPR of the next time period. This is typically done to figure out the ’Two Day CPR Relationship’ . Read the book, “Secrets of a Pivot Boss”, to understand more.
EMA TREND:
Show EMA on the Chart: EMAs will be plotted on the chart. Standard stuff.
Mark EMA Crossovers on Chart: EMA crossovers will be marked on the chart in diamond shapes. If you are using EMA crossovers, I recommend setting this option to True.
Rest of the EMA settings are fairly obvious.
MACD MOMENTUM:
Projecting MACD parameters directly on the candlesticks is surely going to give you a new perspective about price action and MACD.
Also, in order to better understand the MACD projections on the chart, you can add a standard MACD indicator on the chart with default settings to figure out what my indicator is actually showing you.
Marking MACD Crossovers on Chart: Marks the MACD signal crossovers on the chart. This visualization was a game changer for me.
Show MACD Histogram on Chart: Projects the complete MACD Histogram in a novel fashion (Try it!). You will be able to visually see the ebbs and flow of momentum in the charts.
Mark MACD Histogram Peaks on Chart: Marks only the MACD peaks instead of the complete histogram. Peaks are a great way to enter an ongoing trend and to play an intraday rangebound market.
Rest of the settings are just the standard settings that you will find in a typical MACD indicator.
ALERTS:
Not shown in the settings panel, but I have added alerts for EMA and MACD Crossovers so that you don’t have to sit in front of the charts or constantly check the price all day long.
If you don’t know how to set alerts in TradingView, then please Google it.
INDICATOR USAGE EXAMPLES:
This indicator can be used in intraday as well as in higher timeframes.
There are quite a few variations possible, I personally prefer to use the EMA crossovers in intraday (5m) and MACD on Daily timeframes.
This is just a matter of personal preference, some people might prefer using EMAs only or MACD only in all timeframes.
Here are my personal settings for the intraday 5-minute timeframe:
Turn on all the CPR pivots starting from Yearly all the way to Daily. You can turn on 6 hourly and 4 hourly as well if you want.
Hourly CPR is mostly used when the price is in a strong trend and you missed the entry and don’t know when to enter. Price will typically experience pullbacks towards the Hourly CPR, before resuming in the direction of the trend. That is your chance to hop onto the bandwagon.
For Intraday, I keep the Bands off. Just a personal preference here.
You can turn ON the Show CPR Labels , if you want.
Turn ON both the options in the EMA TREND section. You would want to see the EMA crossovers marked on the chart as well as the EMAs themselves, as the distance between the two EMAs will give you an idea about the strength of the trend.
Keep rest of the settings in the EMA section as default (you can change the colors if you wish). I keep the same EMAs as the ones kept in the MACD indicator. I like to keep things simple.
In the MACD MOMENTUM section, turn ON Mark MACD Histogram Peaks on Chart and all the other options turned OFF. Leave the other settings as default. By the way, these are the default settings of the standard MACD Indicator.
You can set up EMA Bullcross and Bearcross alarms if you like.
Before checking out the examples, remember one super simple rule:
SOME OF THE BEST TRENDING MOVES IN THE MARKET, BE IT INTRADAY OR OTHERWISE, ORIGINATE IN THE VICINITY OF A LARGER TIMEFRAME PIVOT/CPR.
Look for price settling above/below a pivot, and then a move away from the pivot in any direction is typically a trending move.
You can use hourly pivots or MACD Histogram peaks marked on the chart to enter an existing trend, or add to your positions.
Let’s have a look at a few recent intraday examples from the Crypto, Indian, and US equity markets.
I have added my comments in the charts to make you easily understand what is going on.
Understand that both, moving average crossover and MACD, will give out a lot of signals (chop) every day. But almost 70% of them are going to be fake signals. It is the signals that you get when the price is near a Pivot, that tend to convert into gorgeous trending moves that last.
BTC 5m Charts
NIFTY Futures 5m Charts (good intraday trends are hard to find here, as the market is very efficient)
TSLA 5m Charts
Some important points for using this indicator in higher timeframes:
For higher timeframes, my personal preference is to go with the MACD indicator. I personally find MACD to be lethal on daily and weekly timeframes, if you know how to use it well.
The default settings of the indicator are the settings I use for both, Daily and Weekly, timeframes. Additionally, I turn off the CPR labels.
In theory large trending moves still have a big probability to start near an important pivot level, however, in larger timeframes, trending moves can start from anywhere. They need not start in the vicinity of any important pivot (but they often do!).
Weekly pivots can act as great pullback levels when the price is in strong momentum, when trading on the daily timeframe.
Quarterly Pivots act as great pullback levels when the price is in strong momentum, when trading on the weekly timeframe.
BTC Weekly Chart
BTC Daily Chart
Nifty Weekly Chart
Nifty Daily Chart
NASDAQ Weekly Chart
NASDAQ Daily Chart
FINAL WORDS:
Please understand that I have Cherry Picked the examples to showcase the capability of the indicator and its usage.
DO NOT conflate the accuracy of examples with the accuracy of this indicator.
Biggest catch is the fact that this indicator, like every other indicator out there, will have whipsaws. Some I have also marked in the example charts.
You need to come up with your own technique to avoid whipsaws, one technique I have shared here…… big moves typically start near pivots.
Work on avoiding whipsaws and finding you own edge in the markets.
If you really want to learn how to use Pivots, read the book ’Secrets of a Pivot Boss’ . This book can change your life.
Cerca negli script per "weekly"
My:HTF O/H/L/C█ MY Higher Time Frame Open / High / Low / Close
This indicator shows one line per Higher Time Frame Price of Interest.
We are interested to know whether we are currently seeing support or resistance at previous daily / weekly / monthly price of interest.
Each price of interest can be displayed or hidden in the configuration. Each line has a label attached to it with the (short) label on it to help identifying what is this line.
Price of interest with (short) label :
Current Daily Open (CDO)
Current Daily High (CDH)
Current Daily Low (CDL)
Previous Daily Open (PDO)
Previous Daily High (PDH)
Previous Daily Low (PDL)
Previous Daily Close (PDC)
Current Weekly Open (CWO)
Current Weekly High (CWH)
Current Weekly Low (CWL)
Previous Weekly Open (PWO)
Previous Weekly High (PWH)
Previous Weekly Low (PWL)
Previous Weekly Close (PWC)
Current Monthly Open (CMO)
Current Monthly High (CMH)
Current Monthly Low (CML)
Previous Monthly Open (PMO)
Previous Monthly High (PMH)
Previous Monthly Low (PML)
Previous Monthly Close (PMC)
RVC-Trade-With-Pivot-LevelsHow to Use PIVOT Levels for Trading
Always remember ->: *Trade with trend*
About script:
1. Daily and Weekly close above Pivot Level.
-- Sentiment is highly positive. Pivot Level acts as strong support.
2. Daily Close above Pivot and Weekly Close Below Pivot
-- Sentiment is positive.Weekly Pivot Level may act as strong resistance.
3. Daily close below Pivot and weekly close above Pivot
-- Sentiment is negative but weekly Pivot Level can acts as strong support.
4. Daily and Weekly Close below Pivot Level
-- Sentiment is highly Negative. Pivot Level acts as strong resistance.
BUY/SELL -- ENTRY
BUY ABOVE 23.6% UPWARD
IF Trend is positive and price cross and sustains above 23.6%(R1) upside, then it will be entry from BUY perspective.
If R1 is entry, R2/R3/R4/R5 ... will be targets.
SELL Below 23.6% Downward
IF Trend is negative and price cross and sustains below 23.6%(S1) downside, then it will be entry from SELL perspective.
If S1 is Sell side entry, S2/S3/S4/S5 will be targets.
Before taking ENTRY on BUY or SELL Side, please know your risk levels, Stop Loss and trade EXECUTION process.
Finally:
My view is my view and remains with me only. Once you accept it and trade it, it becomes your view. So credit or blame all yours.:)
Double RSIThis is double RSI script which plots one time frame higher RSI along with the current time frame i.e
For Weekly chart it display Weekly and Monthly RSI
For Daily chart it display Daily and Weekly RSI
For Intraday chart it display Intraday and Daily RSI.
Usage:
If Daily RSI is above 60 and weekly above 40 and moving up then stock is in a good uptrend look for buying when Daily takes support at 60. Usually First test of Daily produces a good entry for subsequent entries probability decreases.
For Downtrend look for Daily RSI below 40 and weekly below 60.
Volumeweighted macd leader with bb squeezethis indicator is very useful for stocks or crytpto especialy 3d and weekly charts
daily shows good too but if u re a daily trader use it if not dont use it coz 4h and daily is noisy some when there is no trend
thats why weekly and 3d is good because it ll give u accurate signal and trend reversals
this is not my script just a combination of lazybear squeeze momentum, macdleader and volume weighted macd of kivanc
i merge them so it also shows bb squeeze on zero line and settings name is median
macd leader is 2 differen color above zero line and below zero line
above zero line if macd leader is green its buy signal and trend is up
if blue it meand no trend or trend reversal so sell or wait if u use 4h or daily but 3d and weekly it means sell
below zero line macd leader color is red and means that there is downtrend and do not buy
when 3d or weekly turns blue on macd leader it means trend reversal about the start
good with heiken ashi candles
DO NOT FORGET THIS IS NOT PERFECT INDICATOR FOR SHORT TERM, PREFER IT 3D AND WEEKLY FR BETTER RESULTS
True Seasonal Pattern [tradeviZion]True Seasonal Pattern: Uncover Hidden Market Cycles
Markets have rhythms and patterns that repeat with surprising regularity. The True Seasonal Pattern indicator reveals these hidden cycles across different timeframes, helping you anticipate potential market movements based on historical seasonal tendencies.
What This Indicator Does
The True Seasonal Pattern analyzes years of historical price data to identify recurring seasonal trends. It then plots these patterns on your chart, showing you both the historical pattern and future projection based on past seasonal behavior.
Automatic Timeframe Detection: Works with Monthly, Weekly, and Daily charts
Historical Pattern Analysis: Analyzes up to 100 years of data (customizable)
Future Projection: Projects the seasonal pattern ahead on your chart
Smart Smoothing: Applies appropriate smoothing based on your timeframe
How to Use This Indicator
Add the indicator to a Daily, Weekly, or Monthly chart (not designed for intraday timeframes)
The indicator automatically detects your chart's timeframe
The blue line shows the historical seasonal pattern
Watch for potential turning points in the pattern that align with other technical signals
Seasonal patterns work best as a supporting factor in your analysis, not as standalone trading signals. They are particularly effective in markets with well-established seasonal influences.
Best Applications
Futures Markets: Commodities and futures often show strong seasonal tendencies due to production cycles, weather patterns, and economic factors
Stock Indices: Many stock markets demonstrate regular seasonal patterns (like the "Sell in May" phenomenon)
Individual Stocks: Companies with seasonal business cycles often show predictable price patterns
Practical Applications
Identify potential turning points based on historical seasonal patterns
Plan entries and exits around seasonal tendencies
Add seasonal context to your existing technical analysis
Understand why certain months or periods might show consistent behavior
Pro Tip: For best results, use this tool on instruments with at least 5+ years of historical data. Longer timeframes often reveal more reliable seasonal patterns.
Important Notes
This indicator works best on Daily, Weekly, and Monthly timeframes - not intraday charts
Seasonal patterns are tendencies, not guarantees
Always combine seasonal analysis with other technical tools
Past patterns may not repeat exactly in the future
// Sample of the seasonal calculation approach
float yearHigh = array.max(currentYearHighs)
float yearLow = array.min(currentYearLows)
// Calculate seasonality for each period
for i = 0 to array.size(currentYearCloses) - 1
float periodClose = array.get(currentYearCloses, i)
if not na(periodClose) and yearHigh != yearLow
float seasonality = (periodClose - yearLow) / (yearHigh - yearLow) * 100
I developed this indicator to help traders incorporate seasonal analysis into their trading approach without the complexity of traditional seasonal tools. Whether you're analyzing agricultural commodities, energy futures, or stock indices, understanding the seasonal context can provide valuable insights for your trading decisions.
Remember: Markets don't always follow seasonal patterns, but when they do, being aware of these tendencies can give you a meaningful edge in your analysis.
Swing Oracle + Cycle M5 // (\_/)
// ( •.•)
// (")_(")
Follow the White Rabbitz
Swing Oracle + Cycle M5 is a custom TradingView indicator combining a normalized oscillator (NDOS) with a 7-day cycle counter, designed for 5-minute charts. It helps traders identify overbought/oversold swing zones while tracking the market’s position within a weekly cycle that resets every Tuesday at midnight.
1. Inputs
Horizontal Levels
High Level (line_up): above this, NDOS signals overbought (“buy zone”)
Low Level (line_dn): below this, NDOS signals oversold (“sell zone”)
Mid-High / Mid-Low (line_mid_high, line_mid_low): for nuanced thresholding
Extra Levels (line_extra1–line_extra4): four additional hidden levels for advanced tuning
Trendline Source
Choose between EMA 8 or SMA 231 via trendline_source
Display Options
Draw Background Color? (button1): toggles colored background based on NDOS zone
Draw Candlesticks? (button2): toggles bar-coloring according to NDOS
2. Trendline & NDOS Calculation
Trendline
If “EMA8” selected: calculates ema(close, 8)
If “SMA231”: calculates sma(close, 231)
NDOS (Normalized Difference Oscillator)
Computes distance of current trendline value from its local high and low over the past Length bars (length)
Rendered on a 0–100 scale with a color gradient between two user-defined colors (gradientbull/gradientbear).
3. Weekly Cycle Counter (M5)
Cycle Start Detection
Marks every Tuesday at 00:00 as cycle zero (isTuesdayZero), storing its timestamp.
Cycle Number
Computes the number of full 7-day intervals since the last stored Tuesday, then plots it as a semi-transparent histogram aligned with the NDOS panel.
4. Visualization & Styles
Oscillator Plot
Thick line for NDOS, colored blue above line_up, red below line_dn, neutral otherwise—overlaid with the same gradient as the histogram.
Horizontal Levels
Distinct plots for each user level (High, Low, Mid-High, Mid-Low).
Filled Zones
Buy Zone: area between NDOS and High Level
No-Trade Zone: between High and Low Levels
Sell Zone: area between NDOS and Low Level
Optional Coloring
Background and candlesticks can be tinted based on whether NDOS is in buy or sell territory.
5. Typical Use Case
*Scalping & Swing: Quickly spot overbought/oversold conditions on 5-minute bars.
*Cycle Awareness: Ensure entries/exits align with your preferred phase of the weekly cycle (e.g., early vs. late in a Tuesday→Tuesday loop).
*Customization: Adjust levels, gradient colors, and trendline source to match your strategy’s sensitivity and preferred look.
MACD Multi-Timeframe x4 (Custom Params)■About this indicator
・This indicator can display 4 MACD lines for different time frames. (Multi-time framework)
・The color of the MACD line changes when the MACD has a golden or dead cross.
All MACDs can be set individually for long time period, short time period, and signal smoothing.
All MACDs can show/hide MACD lines, signal lines, histograms, and select colors.
■Explanation of effective usage
By displaying MACDs in multiple time frames, you can time the push.
For example, let's say you have three MACDs: one weekly, one daily, and one hour.
With the weekly and daily MACDs continuing to golden cross, the timing for the hourly MACD to golden cross is considered a push opportunity.
An example chart is attached below for your reference.
The area circled vertically is a push-buying opportunity.
Yellow-green: Weekly Green: Daily Light blue: Hourly
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■このインジケーターについて
・このインジケーターは別の時間軸の4本のMACDを表示させることが出来ます。（マルチタイムフレームワーク）
・MACDがゴールデンクロス・デッドクロスした場合にMACDラインの色が変化します。
・全てのMACDについて個別に長期の期間・短期の期間・シグナルの平滑化を設定できます。
・全てのMACDはMACDライン・シグナルライン・ヒストグラムの表示/非表示、色の選択ができます。
■有効な使い方の説明
マルチタイムフレームでMACDを表示することで、押し目のタイミングを計ることが出来ます。
例えば、3本のMACDを1週間・1日・1時間とします。
週足と日足のMACDがゴールデンクロスを継続した状態で、1時間足のMACDがゴールデンクロスしてくるタイミングは押し目買いのチャンスと考えられます。
以下に例題のチャートを付けますので、参考にしてください。
縦に囲った辺りが押し目買いのチャンスになります。
黄緑：週足 緑：日足 水色：1時間足
Multi-Timeframe Closures with Signals month week dayMulti-Timeframe Price Anchoring Indicator (Monthly, Weekly, Daily)
This indicator provides a powerful visual framework for analyzing price action across three major timeframes: monthly, weekly, and daily. It plots the closing prices of each timeframe directly on the chart to help traders assess where current price stands in relation to significant historical levels.
🔍 Core Features:
Monthly, Weekly, and Daily Close Lines: Automatically updated at the start of each new period.
Color-coded Price Anchors: Each timeframe is visually distinct for fast interpretation.
Multi-timeframe Awareness: Helps you identify trend alignment or divergence across different time horizons.
Long & Short Bias Signals: The script can optionally display long or short suggestions based on where the current price stands relative to the anchored closing prices.
📈 How to Use:
Trend Confirmation: If price is consistently above all three levels, it signals a strong bullish trend (potential long bias). If it’s below, the opposite applies (short bias).
Reversal or Pullback Zones: When price becomes extended far above/below the monthly and weekly closes, it may suggest overbought/oversold conditions and the possibility of a reversal or retracement.
Intraday Alignment: Useful for traders who want to enter positions on lower timeframes while being aware of higher timeframe trends.
This indicator is ideal for swing traders, day traders, and position traders who want to anchor their decisions to meaningful multi-timeframe reference points.
Aurora Flow Oscillator [QuantAlgo]The Aurora Flow Oscillator is an advanced momentum-based technical indicator designed to identify market direction, momentum shifts, and potential reversal zones using adaptive filtering techniques. It visualizes price momentum through a dynamic oscillator that quantifies trend strength and direction, helping traders and investors recognize momentum shifts and trading opportunities across various timeframes and asset class.
🟢 Technical Foundation
The Aurora Flow Oscillator employs a sophisticated mathematical approach with adaptive momentum filtering to analyze market conditions, including:
Price-Based Momentum Calculation: Calculates logarithmic price changes to measure the rate and magnitude of market movement
Adaptive Momentum Filtering: Applies an advanced filtering algorithm to smooth momentum calculations while preserving important signals
Acceleration Analysis: Incorporates momentum acceleration to identify shifts in market direction before they become obvious
Signal Normalization: Automatically scales the oscillator output to a range between -100 and 100 for consistent interpretation across different market conditions
The indicator processes price data through multiple filtering stages, applying mathematical principles including exponential smoothing with adaptive coefficients. This creates an oscillator that dynamically adjusts to market volatility while maintaining responsiveness to genuine trend changes.
🟢 Key Features & Signals
1. Momentum Flow and Extreme Zone Identification
The oscillator presents market momentum through an intuitive visual display that clearly indicates both direction and strength:
Above Zero: Indicates positive momentum and potential bullish conditions
Below Zero: Indicates negative momentum and potential bearish conditions
Slope Direction: The angle and direction of the oscillator provide immediate insight into momentum strength
Zero Line Crossings: Signal potential trend changes and new directional momentum
The indicator also identifies potential overbought and oversold market conditions through extreme zone markings:
Upper Zone (>50): Indicates strong bullish momentum that may be approaching exhaustion
Lower Zone (<-50): Indicates strong bearish momentum that may be approaching exhaustion
Extreme Boundaries (±95): Mark potentially unsustainable momentum levels where reversals become increasingly likely
These zones are displayed with gradient intensity that increases as the oscillator moves toward extremes, helping traders and investors:
→ Identify potential reversal zones
→ Determine appropriate entry and exit points
→ Gauge overall market sentiment strength
2. Customizable Trading Style Presets
The Aurora Flow Oscillator offers pre-configured settings for different trading approaches:
Default (80,150): Balanced configuration suitable for most trading and investing situations.
Scalping (5,80): Highly responsive settings for ultra-short-term trades. Generates frequent signals and catches quick price movements. Best for 1-15min charts when making many trades per day.
Day Trading (8,120): Optimized for intraday movements with faster response than default settings while maintaining reasonable signal quality. Ideal for 5-60min or 4h-12h timeframes.
Swing Trading (10,200): Designed for multi-day positions with stronger noise filtering. Focuses on capturing larger price swings while avoiding minor fluctuations. Works best on 1-4h and daily charts.
Position Trading (14,250): For longer-term position traders/investors seeking significant market trends. Reduces false signals by heavily filtering market noise. Ideal for daily or even weekly charts.
Trend Following (16,300): Maximum smoothing that prioritizes established directional movements over short-term fluctuations. Best used on daily and weekly charts, but can also be used for lower timeframe trading.
Countertrend (7,100): Tuned to detect potential reversals and exhaustion points in trends. More sensitive to momentum shifts than other presets. Effective on 15min-4h charts, as well as daily and weekly charts.
Each preset automatically adjusts internal parameters for optimal performance in the selected trading context, providing flexibility across different market approaches without requiring complex manual configuration.
🟢 Practical Usage Tips
1/ Trend Analysis and Interpretation
→ Direction Assessment: Evaluate the oscillator's position relative to zero to determine underlying momentum bias
→ Momentum Strength: Measure the oscillator's distance from zero within the -100 to +100 range to quantify momentum magnitude
→ Trend Consistency: Monitor the oscillator's path for sustained directional movement without frequent zero-line crossings
→ Reversal Detection: Watch for oscillator divergence from price and deceleration of movement when approaching extreme zones
2/ Signal Generation Strategies
Depending on your trading approach, multiple signal strategies can be employed:
Trend Following Signals:
Enter long positions when the oscillator crosses above zero
Enter short positions when the oscillator crosses below zero
Add to positions on pullbacks while maintaining the overall trend direction
Countertrend Signals:
Look for potential reversals when the oscillator reaches extreme zones (±95)
Enter contrary positions when momentum shows signs of exhaustion
Use oscillator divergence with price as additional confirmation
Momentum Shift Signals:
Enter positions when oscillator changes direction after establishing a trend
Exit positions when oscillator direction reverses against your position
Scale position size based on oscillator strength percentage
3/ Timeframe Optimization
The indicator can be effectively applied across different timeframes with these considerations:
Lower Timeframes (1-15min):
Use Scalping or Day Trading presets
Focus on quick momentum shifts and zero-line crossings
Be cautious of noise in extreme market conditions
Medium Timeframes (30min-4h):
Use Default or Swing Trading presets
Look for established trends and potential reversal zones
Combine with support/resistance analysis for entry/exit precision
Higher Timeframes (Daily+):
Use Position Trading or Trend Following presets
Focus on major trend identification and long-term positioning
Use extreme zones for position management rather than immediate reversals
🟢 Pro Tips
Price Momentum Period:
→ Lower values (5-7) increase sensitivity to minor price fluctuations but capture more market noise
→ Higher values (10-16) emphasize sustained momentum shifts at the cost of delayed response
→ Adjust based on your timeframe (lower for shorter timeframes, higher for longer timeframes)
Oscillator Filter Period:
→ Lower values (80-120) produce more frequent directional changes and earlier response to momentum shifts
→ Higher values (200-300) filter out shorter-term fluctuations to highlight dominant market cycles
→ Match to your typical holding period (shorter holding time = lower filter values)
Multi-Timeframe Analysis:
→ Compare oscillator readings across different timeframes for confluence
→ Look for alignment between higher and lower timeframe signals
→ Use higher timeframe for trend direction, lower for earlier entries
Volatility-Adaptive Trading:
→ Use oscillator strength to adjust position sizing (stronger = larger)
→ Consider reducing exposure when oscillator reaches extreme zones
→ Implement tighter stops during periods of oscillator acceleration
Combination Strategies:
→ Pair with volume indicators for confirmation of momentum shifts
→ Use with support/resistance levels for strategic entry and exit points
→ Combine with volatility indicators for comprehensive market context
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal:
Yearly Quarters = 4 quarters of three months each.
Monthly Quarters = 4 quarters of one week each.
Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function.
Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day.
Sessions Quarters = 4 quarters of 90 minutes each.
90 Minute Quarters = 4 quarters of 22.5 minutes each.
Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each:
Q1 - January, February, March.
Q2 - April, May, June (True Open, April Open).
Q3 - July, August, September.
Q4 - October, November, December.
S&P 500 E-mini Futures (daily candles) — Monthly Cycle.
Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day):
Q1 - Week 1: first Monday of the month.
Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price).
Q3 - Week 3: third Monday of the month.
Q4 - Week 4: fourth Monday of the month.
S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle.
Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action:
Q1 - Monday.
Q2 - Tuesday (True Open, Daily Candle Open Price).
Q3 - Wednesday.
Q4 - Thursday.
S&P 500 E-mini Futures (1 hour candles) — Daily Cycle.
Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity:
Q1 - 18:00 - 00:00 Asia.
Q2 - 00:00 - 06:00 London (True Open).
Q3 - 06:00 - 12:00 NY AM.
Q4 - 12:00 - 18:00 NY PM.
S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle.
6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT):
Asian Session
Q1 - 18:00 - 19:30
Q2 - 19:30 - 21:00 (True Open)
Q3 - 21:00 - 22:30
Q4 - 22:30 - 00:00
London Session
Q1 - 00:00 - 01:30
Q2 - 01:30 - 03:00 (True Open)
Q3 - 03:00 - 04:30
Q4 - 04:30 - 06:00
NY AM Session
Q1 - 06:00 - 07:30
Q2 - 07:30 - 09:00 (True Open)
Q3 - 09:00 - 10:30
Q4 - 10:30 - 12:00
NY PM Session
Q1 - 12:00 - 13:30
Q2 - 13:30 - 15:00 (True Open)
Q3 - 15:00 - 16:30
Q4 - 16:30 - 18:00
S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle.
Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters:
Asian Session
Q1/1 18:00:00 - 18:22:30
Q2 18:22:30 - 18:45:00
Q3 18:45:00 - 19:07:30
Q4 19:07:30 - 19:30:00
Q2/1 19:30:00 - 19:52:30 (True Session Open)
Q2/2 19:52:30 - 20:15:00
Q2/3 20:15:00 - 20:37:30
Q2/4 20:37:30 - 21:00:00
Q3/1 21:00:00 - 21:23:30
etc. 21:23:30 - 21:45:00
London Session
00:00:00 - 00:22:30 (True Daily Open)
00:22:30 - 00:45:00
00:45:00 - 01:07:30
01:07:30 - 01:30:00
01:30:00 - 01:52:30 (True Session Open)
01:52:30 - 02:15:00
02:15:00 - 02:37:30
02:37:30 - 03:00:00
03:00:00 - 03:22:30
03:22:30 - 03:45:00
03:45:00 - 04:07:30
04:07:30 - 04:30:00
04:30:00 - 04:52:30
04:52:30 - 05:15:00
05:15:00 - 05:37:30
05:37:30 - 06:00:00
New York AM Session
06:00:00 - 06:22:30
06:22:30 - 06:45:00
06:45:00 - 07:07:30
07:07:30 - 07:30:00
07:30:00 - 07:52:30 (True Session Open)
07:52:30 - 08:15:00
08:15:00 - 08:37:30
08:37:30 - 09:00:00
09:00:00 - 09:22:30
09:22:30 - 09:45:00
09:45:00 - 10:07:30
10:07:30 - 10:30:00
10:30:00 - 10:52:30
10:52:30 - 11:15:00
11:15:00 - 11:37:30
11:37:30 - 12:00:00
New York PM Session
12:00:00 - 12:22:30
12:22:30 - 12:45:00
12:45:00 - 13:07:30
13:07:30 - 13:30:00
13:30:00 - 13:52:30 (True Session Open)
13:52:30 - 14:15:00
14:15:00 - 14:37:30
14:37:30 - 15:00:00
15:00:00 - 15:22:30
15:22:30 - 15:45:00
15:45:00 - 15:37:30
15:37:30 - 16:00:00
16:00:00 - 16:22:30
16:22:30 - 16:45:00
16:45:00 - 17:07:30
17:07:30 - 18:00:00
S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
Multi-Timeframe Anchored VWAP Valuation# Multi-Timeframe Anchored VWAP Valuation
## Overview
This indicator provides a unique perspective on potential price valuation by comparing the current price to the Volume Weighted Average Price (VWAP) anchored to the start of multiple timeframes: Weekly, Monthly, Quarterly, and Yearly. It synthesizes these comparisons into a single oscillator value, helping traders gauge if the current price is potentially extended relative to significant volume-weighted levels.
## Core Concept & Calculation
1. **Anchored VWAP:** The script calculates the VWAP separately for the current Week, Month, Quarter (3 Months), and Year (12 Months), starting the calculation from the first bar of each period.
2. **Price Deviation:** It measures how far the current `close` price is from each of these anchored VWAPs. This distance is measured in terms of standard deviations calculated *within* that specific anchor period (e.g., how many weekly standard deviations the price is away from the weekly VWAP).
3. **Deviation Score (Multiplier):** Based on this standard deviation distance, a score is assigned. The further the price is from the VWAP (in terms of standard deviations), the higher the absolute score. The indicator uses linear interpolation to determine scores between the standard deviation levels (defaulted at 1, 2, and 3 standard deviations corresponding to scores of +/-2, +/-3, +/-4, with a score of 1 at the VWAP).
4. **Timeframe Weighting:** Longer timeframes are considered more significant. The deviation scores are multiplied by fixed scalars: Weekly (x1), Monthly (x2), Quarterly (x3), Yearly (x4).
5. **Final Valuation Metric:** The weighted scores from all four timeframes are summed up to produce the final oscillator value plotted in the indicator pane.
## How to Interpret and Use
* **Histogram (Indicator Pane):**
* The main output is the histogram representing the `Final Valuation Metric`.
* **Positive Values:** Suggest the price is generally trading above its volume-weighted averages across the timeframes, potentially indicating strength or relative "overvaluation."
* **Negative Values:** Suggest the price is generally trading below its volume-weighted averages, potentially indicating weakness or relative "undervaluation."
* **Values Near Zero:** Indicate the price is relatively close to its volume-weighted averages.
* **Histogram Color:**
* The color of the histogram bars provides context based on the metric's *own recent history*.
* **Green (Positive Color):** The metric is currently *above* its recent average plus a standard deviation band (dynamic upper threshold). This highlights potentially significant "overvalued" readings relative to its normal range.
* **Red (Negative Color):** The metric is currently *below* its recent average minus a standard deviation band (dynamic lower threshold). This highlights potentially significant "undervalued" readings relative to its normal range.
* **Gray (Neutral Color):** The metric is within its typical recent range (between the dynamic upper and lower thresholds).
* **Orange Line:** Plots the moving average of the `Final Valuation Metric` itself (based on the "Threshold Lookback Period"), serving as the centerline for the dynamic thresholds.
* **On-Chart Table:**
* Provides a detailed breakdown for transparency.
* Shows the calculated VWAP, the raw deviation multiplier score, and the final weighted (adjusted) metric for each individual timeframe (W, M, Q, Y).
* Displays the current price, the final combined metric value, and a textual interpretation ("Overvalued", "Undervalued", "Neutral") based on the dynamic thresholds.
## Potential Use Cases
* Identifying potential exhaustion points when the indicator reaches statistically high (green) or low (red) levels relative to its recent history.
* Assessing whether price trends are supported by underlying volume-weighted average prices across multiple timeframes.
* Can be used alongside other technical analysis tools for confirmation.
## Settings
* **Calculation Settings:**
* `STDEV Level 1`: Adjusts the 1st standard deviation level (default 1.0).
* `STDEV Level 2`: Adjusts the 2nd standard deviation level (default 2.0).
* `STDEV Level 3`: Adjusts the 3rd standard deviation level (default 3.0).
* **Interpretation Settings:**
* `Threshold Lookback Period`: Defines the number of bars used to calculate the average and standard deviation of the final metric for dynamic thresholds (default 200).
* `Threshold StDev Multiplier`: Controls how many standard deviations above/below the metric's average are used to set the "Overvalued"/"Undervalued" thresholds (default 1.0).
* **Table Settings:** Customize the position and colors of the data table displayed on the chart.
## Important Considerations
* This indicator measures price deviation relative to *anchored* VWAPs and its *own historical range*. It is not a standalone trading system.
* The interpretation of "Overvalued" and "Undervalued" is relative to the indicator's logic and calculations; it does not guarantee future price movement.
* Like all indicators, past performance is not indicative of future results. Use this tool as part of a comprehensive analysis and risk management strategy.
* The anchored VWAP and Standard Deviation values reset at the beginning of each respective period (Week, Month, Quarter, Year).
Correlation Heatmap█ OVERVIEW
This indicator creates a correlation matrix for a user-specified list of symbols based on their time-aligned weekly or monthly price returns. It calculates the Pearson correlation coefficient for each possible symbol pair, and it displays the results in a symmetric table with heatmap-colored cells. This format provides an intuitive view of the linear relationships between various symbols' price movements over a specific time range.
█ CONCEPTS
Correlation
Correlation typically refers to an observable statistical relationship between two datasets. In a financial time series context, it usually represents the extent to which sampled values from a pair of datasets, such as two series of price returns, vary jointly over time. More specifically, in this context, correlation describes the strength and direction of the relationship between the samples from both series.
If two separate time series tend to rise and fall together proportionally, they might be highly correlated. Likewise, if the series often vary in opposite directions, they might have a strong anticorrelation . If the two series do not exhibit a clear relationship, they might be uncorrelated .
Traders frequently analyze asset correlations to help optimize portfolios, assess market behaviors, identify potential risks, and support trading decisions. For instance, correlation often plays a key role in diversification . When two instruments exhibit a strong correlation in their returns, it might indicate that buying or selling both carries elevated unsystematic risk . Therefore, traders often aim to create balanced portfolios of relatively uncorrelated or anticorrelated assets to help promote investment diversity and potentially offset some of the risks.
When using correlation analysis to support investment decisions, it is crucial to understand the following caveats:
• Correlation does not imply causation . Two assets might vary jointly over an analyzed range, resulting in high correlation or anticorrelation in their returns, but that does not indicate that either instrument directly influences the other. Joint variability between assets might occur because of shared sensitivities to external factors, such as interest rates or global sentiment, or it might be entirely coincidental. In other words, correlation does not provide sufficient information to identify cause-and-effect relationships.
• Correlation does not predict the future relationship between two assets. It only reflects the estimated strength and direction of the relationship between the current analyzed samples. Financial time series are ever-changing. A strong trend between two assets can weaken or reverse in the future.
Correlation coefficient
A correlation coefficient is a numeric measure of correlation. Several coefficients exist, each quantifying different types of relationships between two datasets. The most common and widely known measure is the Pearson product-moment correlation coefficient , also known as the Pearson correlation coefficient or Pearson's r . Usually, when the term "correlation coefficient" is used without context, it refers to this correlation measure.
The Pearson correlation coefficient quantifies the strength and direction of the linear relationship between two variables. In other words, it indicates how consistently variables' values move together or in opposite directions in a proportional, linear manner. Its formula is as follows:
𝑟(𝑥, 𝑦) = cov(𝑥, 𝑦) / (𝜎𝑥 * 𝜎𝑦)
Where:
• 𝑥 is the first variable, and 𝑦 is the second variable.
• cov(𝑥, 𝑦) is the covariance between 𝑥 and 𝑦.
• 𝜎𝑥 is the standard deviation of 𝑥.
• 𝜎𝑦 is the standard deviation of 𝑦.
In essence, the correlation coefficient measures the covariance between two variables, normalized by the product of their standard deviations. The coefficient's value ranges from -1 to 1, allowing a more straightforward interpretation of the relationship between two datasets than what covariance alone provides:
• A value of 1 indicates a perfect positive correlation over the analyzed sample. As one variable's value changes, the other variable's value changes proportionally in the same direction .
• A value of -1 indicates a perfect negative correlation (anticorrelation). As one variable's value increases, the other variable's value decreases proportionally.
• A value of 0 indicates no linear relationship between the variables over the analyzed sample.
Aligning returns across instruments
In a financial time series, each data point (i.e., bar) in a sample represents information collected in periodic intervals. For instance, on a "1D" chart, bars form at specific times as successive days elapse.
However, the times of the data points for a symbol's standard dataset depend on its active sessions , and sessions vary across instrument types. For example, the daily session for NYSE stocks is 09:30 - 16:00 UTC-4/-5 on weekdays, Forex instruments have 24-hour sessions that span from 17:00 UTC-4/-5 on one weekday to 17:00 on the next, and new daily sessions for cryptocurrencies start at 00:00 UTC every day because crypto markets are consistently open.
Therefore, comparing the standard datasets for different asset types to identify correlations presents a challenge. If two symbols' datasets have bars that form at unaligned times, their correlation coefficient does not accurately describe their relationship. When calculating correlations between the returns for two assets, both datasets must maintain consistent time alignment in their values and cover identical ranges for meaningful results.
To address the issue of time alignment across instruments, this indicator requests confirmed weekly or monthly data from spread tickers constructed from the chart's ticker and another specified ticker. The datasets for spreads are derived from lower-timeframe data to ensure the values from all symbols come from aligned points in time, allowing a fair comparison between different instrument types. Additionally, each spread ticker ID includes necessary modifiers, such as extended hours and adjustments.
In this indicator, we use the following process to retrieve time-aligned returns for correlation calculations:
1. Request the current and previous prices from a spread representing the sum of the chart symbol and another symbol ( "chartSymbol + anotherSymbol" ).
2. Request the prices from another spread representing the difference between the two symbols ( "chartSymbol - anotherSymbol" ).
3. Calculate half of the difference between the values from both spreads ( 0.5 * (requestedSum - requestedDifference) ). The results represent the symbol's prices at times aligned with the sample points on the current chart.
4. Calculate the arithmetic return of the retrieved prices: (currentPrice - previousPrice) / previousPrice
5. Repeat steps 1-4 for each symbol requiring analysis.
It's crucial to note that because this process retrieves prices for a symbol at times consistent with periodic points on the current chart, the values can represent prices from before or after the closing time of the symbol's usual session.
Additionally, note that the maximum number of weeks or months in the correlation calculations depends on the chart's range and the largest time range common to all the requested symbols. To maximize the amount of data available for the calculations, we recommend setting the chart to use a daily or higher timeframe and specifying a chart symbol that covers a sufficient time range for your needs.
█ FEATURES
This indicator analyzes the correlations between several pairs of user-specified symbols to provide a structured, intuitive view of the relationships in their returns. Below are the indicator's key features:
Requesting a list of securities
The "Symbol list" text box in the indicator's "Settings/Inputs" tab accepts a comma-separated list of symbols or ticker identifiers with optional spaces (e.g., "XOM, MSFT, BITSTAMP:BTCUSD"). The indicator dynamically requests returns for each symbol in the list, then calculates the correlation between each pair of return series for its heatmap display.
Each item in the list must represent a valid symbol or ticker ID. If the list includes an invalid symbol, the script raises a runtime error.
To specify a broker/exchange for a symbol, include its name as a prefix with a colon in the "EXCHANGE:SYMBOL" format. If a symbol in the list does not specify an exchange prefix, the indicator selects the most commonly used exchange when requesting the data.
Note that the number of symbols allowed in the list depends on the user's plan. Users with non-professional plans can compare up to 20 symbols with this indicator, and users with professional plans can compare up to 32 symbols.
Timeframe and data length selection
The "Returns timeframe" input specifies whether the indicator uses weekly or monthly returns in its calculations. By default, its value is "1M", meaning the indicator analyzes monthly returns. Note that this script requires a chart timeframe lower than or equal to "1M". If the chart uses a higher timeframe, it causes a runtime error.
To customize the length of the data used in the correlation calculations, use the "Max periods" input. When enabled, the indicator limits the calculation window to the number of periods specified in the input field. Otherwise, it uses the chart's time range as the limit. The top-left corner of the table shows the number of confirmed weeks or months used in the calculations.
It's important to note that the number of confirmed periods in the correlation calculations is limited to the largest time range common to all the requested datasets, because a meaningful correlation matrix requires analyzing each symbol's returns under the same market conditions. Therefore, the correlation matrix can show different results for the same symbol pair if another listed symbol restricts the aligned data to a shorter time range.
Heatmap display
This indicator displays the correlations for each symbol pair in a heatmap-styled table representing a symmetric correlation matrix. Each row and column corresponds to a specific symbol, and the cells at their intersections correspond to symbol pairs . For example, the cell at the "AAPL" row and "MSFT" column shows the weekly or monthly correlation between those two symbols' returns. Likewise, the cell at the "MSFT" row and "AAPL" column shows the same value.
Note that the main diagonal cells in the display, where the row and column refer to the same symbol, all show a value of 1 because any series of non-na data is always perfectly correlated with itself.
The background of each correlation cell uses a gradient color based on the correlation value. By default, the gradient uses blue hues for positive correlation, orange hues for negative correlation, and white for no correlation. The intensity of each blue or orange hue corresponds to the strength of the measured correlation or anticorrelation. Users can customize the gradient's base colors using the inputs in the "Color gradient" section of the "Settings/Inputs" tab.
█ FOR Pine Script® CODERS
• This script uses the `getArrayFromString()` function from our ValueAtTime library to process the input list of symbols. The function splits the "string" value by its commas, then constructs an array of non-empty strings without leading or trailing whitespaces. Additionally, it uses the str.upper() function to convert each symbol's characters to uppercase.
• The script's `getAlignedReturns()` function requests time-aligned prices with two request.security() calls that use spread tickers based on the chart's symbol and another symbol. Then, it calculates the arithmetic return using the `changePercent()` function from the ta library. The `collectReturns()` function uses `getAlignedReturns()` within a loop and stores the data from each call within a matrix . The script calls the `arrayCorrelation()` function on pairs of rows from the returned matrix to calculate the correlation values.
• For consistency, the `getAlignedReturns()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences.
• A Pine script can execute up to 40 or 64 unique `request.*()` function calls, depending on the user's plan. The maximum number of symbols this script compares is half the plan's limit, because `getAlignedReturns()` uses two request.security() calls.
• This script can use the request.security() function within a loop because all scripts in Pine v6 enable dynamic requests by default. Refer to the Dynamic requests section of the Other timeframes and data page to learn more about this feature, and see our v6 migration guide to learn what's new in Pine v6.
• The script's table uses two distinct color.from_gradient() calls in a switch structure to determine the cell colors for positive and negative correlation values. One call calculates the color for values from -1 to 0 based on the first and second input colors, and the other calculates the colors for values from 0 to 1 based on the second and third input colors.
Look first. Then leap.
Relative Crypto Dominance Polar Chart [LuxAlgo]The Relative Crypto Dominance Polar Chart tool allows traders to compare the relative dominance of up to ten different tickers in the form of a polar area chart, we define relative dominance as a combination between traded dollar volume and volatility, making it very easy to compare them at a glance.
🔶 USAGE
The use is quite simple, traders just have to load the indicator on the chart, and the graph showing the relative dominance will appear.
The 10 tickers loaded by default are the major cryptocurrencies by market cap, but traders can select any ticker in the settings panel.
Each area represents dominance as volatility (radius) by dollar volume (arc length); a larger area means greater dominance on that ticker.
🔹 Choosing Period
The tool supports up to five different periods
Hourly
Daily
Weekly
Monthly
Yearly
By default, the tool period is set on auto mode, which means that the tool will choose the period depending on the chart timeframe
timeframes up to 2m: Hourly
timeframes up to 15m: Daily
timeframes up to 1H: Weekly
timeframes up to 4H: Monthly
larger timeframes: Yearly
🔹 Sorting & Sizing
Traders can sort the graph areas by volatility (radius of each area) in ascending or descending order; by default, the tickers are sorted as they are in the settings panel.
The tool also allows you to adjust the width of the chart on a percentage basis, i.e., at 100% size, all the available width is used; if the graph is too wide, just decrease the graph size parameter in the settings panel.
🔹 Set your own style
The tool allows great customization from the settings panel, traders can enable/disable most of the components, and add a very nice touch with curved lines enabled for displaying the areas with a petal-like effect.
🔶 SETTINGS
Period: Select up to 5 different time periods from Hourly, Daily, Weekly, Monthly and Yearly. Enable/disable Auto mode.
Tickers: Enable/disable and select tickers and colors
🔹 Style
Graph Order: Select sort order
Graph Size: Select percentage of width used
Labels Size: Select size for ticker labels
Show Percent: Show dominance in % under each ticker
Curved Lines: Enable/disable petal-like effect for each area
Show Title: Enable/disable graph title
Show Mean: Enable/disable volatility average and select color
Bitcoin Polynomial Regression ModelThis is the main version of the script. Click here for the Oscillator part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines. The Oscillator version can be found here.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Bitcoin Polynomial Regression OscillatorThis is the oscillator version of the script. Click here for the other part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Super Cycle Low FinderHow the Indicator Works
1. Inputs
Users can adjust the cycle lengths:
Daily Cycle: Default is 40 days (within 36-44 days).
Weekly Cycle: Default is 26 weeks (182 days, within 22-31 weeks).
Yearly Cycle: Default is 4 years (1460 days).
2. Cycle Low Detection
Function: detect_cycle_low finds the lowest low over the specified period and confirms it with a bullish candle (close > open).
Timeframes: Daily lows are calculated directly; weekly and yearly lows use request.security to fetch data from higher timeframes.
3. Half Cycle Lows
Detected over half the cycle length, plotted to show mid-cycle strength or weakness.
4. Cycle Translation
Logic: Compares the position of the highest high to the cycle’s midpoint.
Output: "R" for right translated (bullish), "L" for left translated (bearish), displayed above bars.
5. Cycle Failure
Flags when a new low falls below the previous cycle low, indicating a breakdown.
6. Visualization
Cycle Lows: Diamonds below bars (yellow for daily, green for weekly, blue for yearly).
Half Cycle Lows: Circles below bars (orange, lime, aqua).
Translations: "R" or "L" above bars in distinct colors.
Failures: Downward triangles below bars (red, orange, purple).
TimeMapTimeMap is a visual price-reference indicator designed to help traders rapidly visualize how current price levels relate to significant historical closing prices. It overlays your chart with reference lines representing past weekly, monthly, quarterly (3-month), semi-annual (6-month), and annual closing prices. By clearly plotting these historical price references, TimeMap helps traders quickly gauge price position relative to historical market structure, aiding in the identification of trends, support/resistance levels, and potential reversals.
How it Works:
The indicator calculates the precise number of historical bars corresponding to weekly, monthly, quarterly, semi-annual, and annual intervals, dynamically adjusting according to your chart’s timeframe (intraday, daily, weekly, monthly) and chosen market type (Stocks US, Crypto, Forex, or Futures). Historical closing prices from these periods are plotted directly on your chart as horizontal reference lines.
For intraday traders, the script accurately calculates historical offsets considering regular and extended trading sessions (e.g., pre-market and after-hours sessions for US stocks), ensuring correct positioning of historical lines.
User-Configurable Inputs Explained in Detail:
Market Type:
Allows you to specify your trading instrument type, automatically adjusting calculations for:
- Stocks US (default): 390 minutes per regular session (780 minutes if extended hours enabled), 5 trading days/week.
- Crypto: 1440 minutes/day, 7 trading days/week.
- Forex: 1440 minutes/day, 5 trading days/week.
- Futures: 1320 minutes/day, 5 trading days/week.
Show Weekly Close:
When enabled, plots a line at the exact closing price from one week ago. Provides short-term context and helps identify recent price momentum.
Show Monthly Close:
When enabled, plots a line at the exact closing price from one month ago. Helpful for evaluating medium-term price positioning and monthly trend strength.
Show 3-Month Close:
When enabled, plots a line at the exact closing price from three months ago. Useful for assessing quarterly market shifts, intermediate trend changes, and broader market sentiment.
Show 6-Month Close:
When enabled, plots a line at the exact closing price from six months ago. Useful for identifying semi-annual trends, significant price pivots, and longer-term support/resistance levels.
Show 1-Year Close:
When enabled, plots a line at the exact closing price from one year ago. Excellent for assessing long-term market direction and key annual price levels.
Enable Smoothing:
Activates a Simple Moving Average (SMA) smoothing of historical reference lines, reducing volatility and providing clearer visual references. Recommended for traders preferring less volatile reference levels.
Smoothing Length:
Determines the number of bars used in calculating the SMA smoothing of historical lines. Higher values result in smoother but slightly delayed reference lines; lower values offer more immediate yet more volatile levels.
Use Extended Hours (Intraday Only):
When enabled (only applicable for Stocks US), it accounts for pre-market and after-hours trading sessions, providing accurate intraday historical line calculations based on extended sessions (typically 780 minutes/day total).
Important Notes and Compliance:
- This indicator does not provide trading signals, recommendations, or predictions. It serves purely as a visual analytical tool to supplement traders’ existing methods.
- Historical lines plotted are strictly based on past available price data; the indicator never accesses future data or data outside the scope of Pine Script’s standard capabilities.
- The script incorporates built-in logic to avoid runtime errors if insufficient historical data exists for a selected timeframe, ensuring robustness even with limited historical bars.
- TimeMap is original work developed exclusively by Julien Eche (@Julien_Eche). It does not reuse or replicate third-party or existing open-source scripts.
Recommended Best Practices:
- Use TimeMap as a complementary analytical reference, not as a standalone strategy or trade decision-making tool.
- Adapt displayed historical periods and smoothing settings based on your trading style and market approach.
- Default plot colors are optimized for readability on dark-background charts; adjust as necessary according to your preference and chart color scheme.
This script is published open-source to benefit the entire TradingView community and fully complies with all TradingView script publishing rules and guidelines.
True Open CalculationsIndicator Description: True Open Calculations
This custom Pine Script indicator calculates and plots key "True Open" levels based on specific time intervals and trading sessions. The True Open levels represent significant price points on the chart, helping traders identify key reference points tied to various market opening times. These levels are important for understanding price action in relation to market sessions and trading cycles. The indicator is designed to plot lines corresponding to different "True Opens" on the chart and display labels with the associated information.
Key Features:
True Year Open:
This represents the opening price on the first Monday of April each year. It serves as a reference point for the yearly price level.
Plot Color: Green.
True Month Open:
This represents the opening price on the second Monday of each month. It helps in identifying monthly trends and provides a key reference for monthly price movements.
Plot Color: Blue.
True Week Open:
This represents the opening price every Monday at 6:00 PM. It gives traders a level to track weekly opening movements and can be useful for weekly trend analysis.
Plot Color: Orange.
True Day Open:
This represents the opening price at 12:00 AM (midnight) each day. It serves as a daily benchmark for price action at the start of the trading day.
Plot Color: Red.
True New York Session Open:
This represents the opening price at 7:30 AM (New York session start time). This level is crucial for traders focused on the New York trading session.
Plot Color: Purple.
Additional Features:
Labels: The indicator displays labels to the right of each plotted line to describe which "True Open" it represents (e.g., "True Year Open," "True Month Open," etc.).
Dynamic Plotting: The lines are only plotted on the current candle, and the lines are dynamically updated for each time period based on the corresponding "True Open."
Visual Cues: The colors of the plotted lines (green, blue, orange, red, purple) help quickly distinguish between different "True Open" levels, making it easy for traders to track price action and make informed decisions.
Use Cases:
Yearly, Monthly, Weekly, Daily, and Session Benchmarking: This indicator provides traders with important price levels to use as benchmarks for the current year, month, week, and day, helping to identify trends and potential reversals.
Session Awareness: It is particularly useful for traders who want to track key market sessions, such as the New York session, and their impact on price movement.
Long-term Analysis: By including the yearly open, this indicator helps traders gain a broader perspective on market trends and provides context for analyzing shorter-term price movements.
Benefits:
Helps identify important reference points for longer-term trends (yearly, monthly) as well as shorter-term moves (daily, weekly, and session).
Visually intuitive with color-coded lines and labels, allowing quick and easy identification of key market open levels.
Dynamic and real-time: The indicator plots and updates the True Open levels dynamically as the market progresses.
Highest High Line with Multi-Timeframe Supertrend and RSIOverview:
This powerful indicator combines three essential elements for traders:
Highest High Line – Tracks the highest price over a customizable lookback period across different timeframes.
Multi-Timeframe Supertrend – Displays Supertrend values and trend directions for multiple timeframes simultaneously.
Relative Strength Index (RSI) – Shows RSI values across different timeframes for momentum analysis.
Features:
✅ Customizable Highest High Line:
Selectable timeframes: Daily, Weekly, Monthly, Quarterly, Yearly
Adjustable lookback period
✅ Multi-Timeframe Supertrend:
Supports 1min, 5min, 10min, 15min, 30min, 1H, Daily, Weekly, Monthly, Quarterly, Yearly
ATR-based calculation with configurable ATR period and multiplier
Identifies bullish (green) & bearish (red) trends
✅ Multi-Timeframe RSI:
Calculates RSI for the same timeframes as Supertrend
Overbought (≥70) and Oversold (≤30) signals with color coding
✅ Comprehensive Table Display:
A clean, structured table in the bottom-right corner
Displays Supertrend direction, value, and RSI for all timeframes
Helps traders quickly assess trend and momentum alignment
How to Use:
Use the Highest High Line to identify key resistance zones.
Confirm trend direction with Multi-Timeframe Supertrend.
Check RSI values to avoid overbought/oversold conditions before entering trades.
Align multiple timeframes for stronger confirmation of trend shifts.
Ideal For:
✅ Scalpers (lower timeframes: 1m–30m)
✅ Swing Traders (higher timeframes: 1H–D)
✅ Position Traders (Weekly, Monthly, Quarterly)
💡 Tip: Look for Supertrend & RSI confluence across multiple timeframes for higher probability setups.
Trend Detection
#### *Description:*
This *Trend Detection* indicator is designed to help traders identify and confirm trends in the market using a combination of moving averages, volume analysis, and MACD filters. It provides clear visual signals for uptrends and downtrends, along with customizable settings to adapt to different trading styles and timeframes. The indicator is suitable for both beginners and advanced traders who want to improve their trend-following strategies.
---
#### *Key Features:*
1. *Trend Detection:*
- Uses *Moving Averages (MA)* to determine the overall trend direction.
- Supports multiple MA types: *SMA (Simple), **EMA (Exponential), **WMA (Weighted), and **HMA (Hull)*.
2. *Advanced Filters:*
- *MACD Filter:* Confirms trends using MACD crossovers.
- *Volume Filter:* Ensures trends are supported by above-average volume.
- *Multi-Timeframe Filter:* Validates trends using a higher timeframe (e.g., Daily or Weekly).
3. *Visual Signals:*
- Plots a *trend line* on the chart to indicate the current trend direction.
- Fills the background with *green* for uptrends and *red* for downtrends.
4. *Customizable Settings:*
- Adjust the *MA lengths, **MACD parameters, and **confirmation thresholds* to suit your trading strategy.
- Control the transparency of the background fill for better chart readability.
5. *Alerts:*
- Generates *buy/sell signals* when a trend is confirmed.
- Alerts can be set to trigger at the close of a candle for precise entry/exit points.
---
#### *How to Use:*
1. *Adding the Indicator:*
- Copy and paste the Pine Script code into the TradingView Pine Script editor.
- Add the indicator to your chart.
2. *Configuring the Settings:*
- *Trend Settings:*
- Choose the *MA type* (e.g., EMA for faster response, HMA for smoother trends).
- Set the *Trend MA Period* (e.g., 200 for long-term trends) and *Filter MA Period* (e.g., 100 for medium-term trends).
- *Advanced Filters:*
- Enable/disable the *MACD Filter* and adjust its parameters (Fast, Slow, Signal).
- Enable/disable the *Volume Filter* to ensure trends are supported by volume.
- *Multi-Timeframe Filter:*
- Enable this filter to validate trends using a higher timeframe (e.g., Daily or Weekly).
3. *Interpreting the Signals:*
- *Uptrend:* The trend line turns *green*, and the background is filled with a transparent green color.
- *Downtrend:* The trend line turns *red*, and the background is filled with a transparent red color.
- *Alerts:* Buy/sell signals are generated when the trend is confirmed.
4. *Using Alerts:*
- Set up alerts for *Buy Signal* (bullish reversal) and *Sell Signal* (bearish reversal).
- Alerts can be configured to trigger at the close of a candle for precise execution.
---
#### *Settings and Their Effects:*
1. *MA Type:*
- *SMA:* Smooth but lagging. Best for long-term trends.
- *EMA:* Faster response to price changes. Suitable for medium-term trends.
- *WMA:* Gives more weight to recent prices. Useful for short-term trends.
- *HMA:* Combines speed and smoothness. Ideal for all timeframes.
2. *Trend MA Period:*
- A longer period (e.g., 200) identifies long-term trends but may lag.
- A shorter period (e.g., 50) reacts faster but may produce false signals.
3. *Filter MA Period:*
- Acts as a secondary filter to confirm the trend.
- A shorter period (e.g., 50) provides tighter confirmation but may increase noise.
4. *MACD Filter:*
- Ensures trends are confirmed by MACD crossovers.
- Adjust the *Fast, **Slow, and **Signal* lengths to match your trading style.
5. *Volume Filter:*
- Ensures trends are supported by above-average volume.
- Reduces false signals during low-volume periods.
6. *Multi-Timeframe Filter:*
- Validates trends using a higher timeframe (e.g., Daily or Weekly).
- Increases reliability but may delay signals.
7. *Confirmation Value:*
- Sets the minimum percentage deviation from the trend MA required to confirm a trend.
- A higher value (e.g., 2.0%) reduces false signals but may delay trend detection.
8. *Confirmation Bars:*
- Sets the number of bars required to confirm a trend.
- A higher value (e.g., 5 bars) ensures sustained trends but may delay signals.
---
#### *Who Should Use This Indicator?*
1. *Trend Followers:*
- Traders who focus on identifying and riding long-term trends.
- Suitable for *swing traders* and *position traders*.
2. *Day Traders:*
- Can use shorter MA periods and faster filters (e.g., EMA, HMA) for intraday trends.
3. *Volume-Based Traders:*
- Traders who rely on volume confirmation to validate trends.
4. *Multi-Timeframe Traders:*
- Traders who use higher timeframes to confirm trends on lower timeframes.
5. *Beginners:*
- Easy-to-understand visual signals and alerts make it beginner-friendly.
6. *Advanced Traders:*
- Customizable settings allow for fine-tuning to match specific strategies.
---
#### *Example Use Cases:*
1. *Long-Term Investing:*
- Use a *200-period SMA* with a *Daily* higher timeframe filter to identify long-term trends.
- Enable the *Volume Filter* to ensure trends are supported by strong volume.
2. *Swing Trading:*
- Use a *50-period EMA* with a *4-hour* higher timeframe filter for medium-term trends.
- Enable the *MACD Filter* to confirm trend reversals.
3. *Day Trading:*
- Use a *20-period HMA* with a *1-hour* higher timeframe filter for short-term trends.
- Disable the *Volume Filter* for faster signals.
---
#### *Conclusion:*
The *Trend Detection* indicator is a versatile tool for traders of all levels. Its customizable settings and advanced filters make it suitable for various trading styles and timeframes. By combining moving averages, volume analysis, and MACD filters, it provides reliable trend signals with minimal lag. Whether you're a beginner or an advanced trader, this indicator can help you make better trading decisions by identifying and confirming trends in the market.
---
#### *Publishing on TradingView:*
- *Title:* Trend Detection with Advanced Filters
- *Description:* A powerful trend detection tool using moving averages, volume analysis, and MACD filters. Suitable for all trading styles and timeframes.
- *Tags:* Trend, Moving Averages, MACD, Volume, Multi-Timeframe
- *Category:* Trend-Following
- *Access:* Public or Private (depending on your preference).
---
Let me know if you need further assistance or additional features!
JL - DWM OHLCThis indicator plots the following price levels on your chart automatically AND will not show up if you are using a timeframe bigger than 60 minutes, 1 day, or 1 week.
Here are the price levels that are automatically plotted for you, and so you know the styling is different for Daily, Weekly, Monthly levels so you can easily distinguish between them:
- Prior Day: High / Low / Close
- Current Day: Open
- Prior Week: High / Low / Close
- Current Week: Open
- Prior Month: High / Low / Close
- Current Month: Open
These plots are timeframe dependent and will not plot on subsequently higher timeframes, here is how they work:
Daily Price Levels are only shown on timeframes that are smaller than 60 minutes.
Weekly Price Levels are only shown on timeframes smaller than 1 Day.
Monthly Price Levels are only shown on timeframes smaller than 1 Week.
This way, you can turn on the indicator and not have to think about turning off certain price levels if you switch to a larger / longer timeframe than what you typically use.
For example, Daily OHLC price levels will quickly clutter the 60 minute chart, and likely you don't need to know the HLC of the Prior Day if you are looking at the 60 minute chart. Therefor it may be helpful to automatically hide the Daily price level plots, and only show the Weekly and Monthly plots on the 60 minute timeframe.
I hope you find this indicator helpful, thanks for reading.
ReadyFor401ks Just Tell Me When!ReadyFor401ks Just Tell Me When!
LET ME START BY SAYING. NO INDICATOR WILL HELP YOU NAIL THE PERFECT ENTRY/EXIT ON A TRADE. YOU SHOULD ALWAYS EDUCATE YOURSELF AND HAVE A BASIC UNDERSTANDING OF INVESTING, TRADING, CHART ANALYSIS, AND THE RISKS INVOLVED WITH. THAT BEING SAID, WITH THE RIGHT ADJUSTMENTS, IT'S PRETTY D*$N CLOSE TO PERFECTION!
This indicator is designed to help traders identify t rend direction, continuation signals, and potential exits based on a dynamic blend of moving averages, ATR bands, and price action filters. Whether you’re an intraday trader scalping the 5-minute chart or a swing trader analyzing the weekly timeframe for LEAPS , this tool provides a clear, rule-based system to help guide your trading decisions.
⸻
Key Features & Benefits
🔹 Customizable Trend Power (Baseline) Calculation
• Choose from JMA, EMA, HMA, TEMA, DEMA, SMA, VAMA, and WMA for defining your baseline trend direction.
• The baseline helps confirm whether the market is in a bullish or bearish phase.
🔹 ATR-Based Trend Continuation & Volatility Measurement
• ATR bands dynamically adjust to market conditions, helping you spot breakouts and fakeouts.
• The indicator detects when price violates ATR range , which often signals impulse moves.
🔹 Clear Entry & Exit Signals
• Uses a Continuation MA (SSL2) to confirm trends.
• Includes a separate Exit MA (SSL3) that provides crossover signals to indicate when to exit trades or reverse positions .
• Plots trend continuation circles when ATR conditions align with trend signals.
🔹 Keltner Channel Baseline for Market Structure
• A modified Keltner Channel is integrated into the baseline to help filter out choppy conditions .
• If price remains inside the baseline, the market is in consolidation , while breakouts beyond the bands indicate strong trends .
🔹 Adaptive Color Coding for Market Conditions
• Bars change color based on momentum, making trend direction easy to read.
• Green = Bullish Trend, Red = Bearish Trend, Gray = Neutral/Chop.
🔹 Flexible Alerts for Trade Management
• Get real-time alerts when the Exit MA crosses price , helping you l ock in profits or switch directions .
⸻
How to Use This Indicator for Different Trading Styles
🟢 For Intraday Trading (5-Minute Chart Setup)
• Faster MA settings help react quickly to momentum shifts.
• Ideal for scalping breakouts, trend continuation setups, and intraday reversals.
• Watch for ATR violations and price interacting with the baseline/Keltner Channel for entries.
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My Settings for Intraday Trading on 5min Chart
ATR Period: 15
ATR Multi: 1
ATR Smoothing: WMA
Trend Power based off of: JMA
Trend Power Period: 30
Continuation Type: JMA
Continuation Length: 20
Calculate Exit of what MA?: HMA
Calculate Exit off what Period? 30
Source of Exit Calculation: close
JMA Phase *APPLIES TO JMA ONLY: 3
JMA Power *APPLIES TO JMA ONLY: 3
Volatility Lookback Period *APPLIES TO VAMA ONLY 30
Use True Range for Channel? Checked
Base Channel Multiplier: 0.4
ATR Continuation Criteria: 1.1
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🔵 For Swing Trading & LEAPS (Weekly Chart Setup - Default Settings)
• Slower MAs provide a broader view of trend structure.
• Helps capture multi-week trend shifts and confirm entry points for longer-term trades.
• Weekly ATR bands highlight when stocks are entering overextended conditions.
💡 Example:
Let’s say you’re looking at TSLA on a Weekly Chart using the default settings. You notice that price crosses above the continuation MA (SSL2) while remaining above the baseline (trend power MA). The bar turns green, and price breaks above ATR resistance, signaling a strong bullish continuation. This could be a great opportunity to enter a long-term swing trade or LEAPS options position.
On the flip side, if price reverses below the Exit MA (SSL3) and turns red while breaking the lower ATR band, it might signal a good time to exit longs or enter a short trade.
⸻
Final Thoughts
The ReadyFor401ks Just Tell Me When! indicator is an all-in-one trading system that simplifies trend-following, volatility measurement, and trade management. By integrating multiple moving average types, ATR filters, and clear visual cues, it allows traders to stay disciplined and remove emotions from their trading decisions.
✅ Perfect for scalpers, day traders, and swing traders alike!
🔔 Set up alerts for automated trade signals and never miss a key move!
💬 If you find this indicator useful, leave a comment and share how you use it in your trading! 🚀
