Daily Percentage Oscillator### Daily Percentage Oscillator – Indicator Description
The **Daily Percentage Oscillator** transforms intraday price action into a clean, normalized percentage-based view, using the previous trading day's closing price as the fixed 0% baseline. Each new trading day automatically resets the axis to that prior close, allowing you to visualize true daily price oscillation without the distortion of absolute price levels or cumulative trends.
Key features:
- **Percentage-based OHLC display**: All bars or candlesticks represent percentage change from the previous day’s close, creating a consistent oscillation around the 0% line.
- **Daily reset**: The baseline updates every session, making it ideal for intraday traders focusing on relative strength, mean reversion, or daily momentum patterns.
- **Toggle between bars and candlesticks**: Choose your preferred visual style.
- **Simple Moving Average (SMA)**: Optional SMA applied directly to the percentage close values (default 20-period, fully customizable).
- **Daily-resetting VWAP**: Volume-Weighted Average Price calculated on the percentage series, resetting at the start of each trading day for precise intraday anchoring.
- **Clean presentation**: No clutter from scale labels or status line values — only the essential visuals appear in the pane.
This indicator is particularly useful for:
- Comparing intraday momentum across different assets or timeframes on equal footing.
- Identifying overbought/oversold conditions relative to the prior close.
- Enhancing mean-reversion and range-bound trading strategies.
- Overlaying percentage-based anchors (SMA, VWAP) that respect the daily session structure.
Works on any intraday timeframe (1m, 5m, 15m, etc.) and is designed to stay lightweight and responsive. Perfect for day traders and scalpers seeking a clearer, more intuitive view of daily price behavior.
Ciclos
RSI Nexus Matrix - By TheTradingSmurfRSI Nexus Matrix is a sophisticated multi-timeframe RSI projection system that displays where price is likely to reach RSI overbought (70) and oversold (30) levels across 21 different timeframes simultaneously.
Key Features:
Multi-Timeframe Analysis - Monitors RSI conditions from M1 through Monthly charts in a unified view
Smart Price Projections - Calculates exact price levels where RSI will hit 70/30 thresholds using pivot-based regression
Visual Clarity - Horizontal projection lines with labeled timeframes and prices
Dynamic Color Coding - Lines change to lime (bullish breakthrough) or orange (bearish breakthrough) when price crosses projected levels
Vertical Lane System - Fixed vertical indicators per timeframe connecting current price to projected levels
ATR-Based Protection - Caps unrealistic projections using ATR multipliers
Adaptive Fallback - Uses alternative calculation methods when pivot data is unavailable
How It Works:
The indicator analyzes RSI pivot points on each timeframe and projects forward to determine where price needs to move for RSI to reach overbought/oversold zones. This creates a "matrix" of convergence points where multiple timeframes align, revealing high-probability reversal zones.
Best Used For:
Identifying multi-timeframe confluence zones
Timing entries at oversold/overbought extremes
Spotting when multiple timeframes align for reversals
Scalping with lower timeframe projections
Swing trading with higher timeframe projections
Fully customizable with 21 toggleable timeframes, adjustable RSI periods, pivot sensitivity, and complete visual control over lines, labels, and colors.
MTF Stochastic DashboardThe Stochastic Oscillator measures momentum — how strong or weak price movements are. By analyzing its shape and direction across multiple timeframes, and drawing trendlines on the %K line, you can better understand potential market reversals, continuation points, or breakout signals.
V-Max: Tactical Clock & Price (Master Fit)Overview
The V-Max Tactical Clock & Price is a high-visibility utility dashboard engineered for precision execution in global financial markets. It serves as a "Physical Timezone Navigator," providing real-time price tracking and synchronized local time display directly on the chart. This ensures traders can align their execution with specific market openings and closing volatility regardless of the exchange's default timezone.
Core Technical Logic & Features
This script focuses on the physics of time-alignment and visual stability:
Physical Time Calibration Engine: Unlike standard UI clocks, this script employs a millisecond-level compensation engine using the formula: $timenow + (tz\_offset \times 60 \times 60 \times 1000)$. This allows for precise synchronization with any global market (e.g., London, New York, or Asia sessions).
Momentum-Driven Price Rendering: The price display utilizes conditional coloring logic ($close \ge open ? up\_col : dn\_col$) to provide immediate visual feedback on the current bar's momentum.
High-Identifiability UI (Master Fit): Leverages the table.new titan rendering engine with size.huge font specifications for the price. This ensures critical data remains readable even on small mobile screens or high-density multi-chart layouts.
Anti-Flicker Monospaced Formatting: Employs font.family_monospace to ensure strict numerical alignment, preventing visual flickering or "jumping" during periods of extreme market volatility.
How to Use
Timezone Setup: Enter your local GMT offset (e.g., +8 for Taiwan/Singapore, -5 for New York) in the settings.
Visual Customization: Adjust the dashboard position (default: Bottom Left) and background aesthetics to fit your professional trading workspace.
產品概述
V-Max 戰術時鐘與價格顯示器是一款為全球市場設計的高辨識度工具。它作為一個實時的「全球時區導航儀」，在圖表上直接提供實時價格追蹤與同步化的本地時間顯示，確保交易者能精確對齊各國市場開盤瞬間的波動。
核心技術邏輯與功能物理時間校準引擎：採用毫秒級時間補償運算，公式為：$timenow + (tz\_offset \times 60 \times 60 \times 1000)$。這讓交易者能精確校準全球任一交易所的本地時間。
動能價格渲染：價格顯示具備即時漲跌變色邏輯，提供直觀的即時盤感反饋。
特大字體 UI (Master Fit)：採用 size.huge 字體規格顯示價格，確保在移動端或複雜多圖表布局下依然清晰易讀。
防閃爍等寬格式：使用等寬字體確保數字在劇烈波動時不會產生視覺跳動，維持高度的讀數穩定性。
Access & Support
This script is published as a Free Public Utility in the TradingView Library. Disclaimer: For educational purposes only. Past performance does not guarantee future results.
Disclaimer: This script is for technical analysis and educational purposes only. It does not provide financial advice.
Execution-Weighted Market Regime Map (EWRM)Overview
The Execution-Weighted Market Regime Map is designed to answer a simple question:
“Is this market worth trading right now, or is it mostly noise and costs?”
Instead of focusing only on trend vs range, it evaluates whether conditions are likely to:
offer clean, follow-through price movement
chop back and forth
be dominated by costs like spread and slippage
It is meant for day traders and swing traders who want to choose when to trade, not just where to enter .
Core idea
Most indicators try to predict direction.
EWRM focuses on tradability.
It highlights:
when the market moves cleanly and is easier to execute
when volatility is unstable and unreliable
when “cost of trading” (spread and slippage) eats potential profit
The indicator shows this using:
a visual dashboard
background color changes
clear regime labels
Key concepts in plain language
SRR – Spread-to-Range Ratio
How big the trading costs are compared to how much price is moving.
High SRR = the market moves little but costs you a lot → bad environment.
Low SRR = price moves much more than it costs to trade → better environment.
PEI – Pullback Efficiency Index
Measures how “clean” trends are.
If pullbacks lead to smooth continuation, PEI is high.
If pullbacks constantly fail and reverse, PEI is low.
SRP – Slippage Risk Proxy
Estimates how likely you are to get worse fills than expected.
Fast spikes, thin liquidity zones, and whipsaw behavior increase SRP.
What EWRM helps you do
avoid overtrading during messy conditions
size up when conditions are smooth and directional
identify when volatility is expanding or collapsing
adapt behavior by time of day (open, midday, close)
How it works at a high level
It measures how much the market is moving
It checks whether volatility is stable or chaotic
It estimates how expensive and difficult execution is
It breaks the day into premarket, open, midday, and power hour
It combines all of this into an overall “regime” label
It colors the background or dashboard so you can read the state instantly
There are no buy/sell arrows. It is a decision-support tool, not a signal generator.
How to use it
trade more when conditions are clean and execution-friendly
stand aside when cost and noise dominate movement
prefer trend setups when trend regimes are detected
stay cautious when regime flips frequently
Think of it as a weather map for the market, not a GPS.
Inputs and parameters
Core settings
Realized Volatility Length – how fast the tool reacts to volatility changes
Volatility Stability Length – how stable/unstable volatility appears
ATR Length – used to scale and normalize movement
General Lookback – how much history is analyzed
Session settings
Premarket
Opening drive
Midday
Power hour
These let the tool treat each time window differently, since behavior changes through the day.
Cost settings
Estimated Spread – approximate buy/sell price difference
Estimated Slippage – expected extra cost from fast movement
These make the tool focus on realistic, after-cost trading conditions .
Visual settings
toggle dashboard
toggle background shading
toggle regime labels
choose X/Y position of the panel
Limitations
uses estimates of spread and slippage, not live order-book data
cannot remove all uncertainty
best used as a filter, not a trading system
Suggested use
filter out bad environments
increase selectivity
align position size with regime quality
combine with your own strategy or entries
Bollinger Bands Squeeze (BB inside KC) - Yuval HaspelBollinger Bands Squeeze Indicator
Purpose: Identify areas where the asset has gained enough "energy" for the possible next move up or down.
Works under the assumption that Bollinger Bands engulfed within the Keltner Channels indicate a momentum compression and possibly indicating that the asset is "resting" before the next move.
Red dots mean in a squeeze and blue dots not in a squeeze.
Oxscope 1hr V1This indicator is a sophisticated trend-following tool designed to filter market noise by aggregating signals from 20 distinct technical indicators—including EMA, RSI, MACD, Bollinger Bands, SuperTrend, and Ichimoku. Instead of relying on a single metric, it calculates a real-time "consensus score" for every candle, where each indicator votes +1 for bullish or -1 for bearish.
Key Features:
High-Confidence Threshold: The strategy operates on a strict threshold of ±6. A score of +6 or higher activates the Long Zone (Green Background), while -6 or lower triggers the Short Zone (Red Background). This ensures trades are only suggested when there is strong technical agreement.
Visual Clarity: Designed for a distraction-free experience, this version removes complex data tables and indicator lines. It features massive, easy-to-read emoji labels ("🚀" for Long entries, "📉" for Short entries).
Smart Signal Logic: The script prioritizes entry signals over exit signals during sharp reversals, keeping your chart clean and focusing solely on the most critical trend changes.
This tool is ideal for traders seeking high-conviction setups without visual clutter.
NY Session Bar Counter & Bar painterThe NY Session Bar Counter is a high-visibility technical utility that provides an automated, sequential count of every candle during the New York session (09:30 to 16:00 EST). Unlike standard session highlighters, this tool numbers each bar starting from the market open, allowing traders to identify specific "time-of-day" windows with surgical precision.
This script is specifically engineered for traders who follow setups based on specific bar numbers (e.g., the Bar 17 reversal, the Bar 36 lunch-power-hour, or the final EOD flush).
🚀 Key Features
Precision Timing: Automatically resets every day at 09:30 AM New York time, regardless of your local timezone settings.
Multi-Timeframe Logic: Optimized to work seamlessly on 1m, 5m, 15m, and 30m charts without breaking the daily count.
Historical & Replay Compatibility: Unlike many session tools, this script is fully compatible with Bar Replay and displays historical data across several days (up to 500 labels).
Special Bar Highlighting: Includes a "Paint Bar" feature that allows you to choose a specific bar number (e.g., Bar 17) and automatically color the candle body for instant visual recognition.
Customizable Display: Filter for Odd/Even numbers to reduce chart clutter and adjust font size, color, and position (Above/Below bar).
💡 Why It Is Useful
In the modern trading environment, the market moves in cycles of liquidity and volatility that are often tied to specific times. This script is useful because:
Standardization: It provides a common language for traders. Instead of saying "the 10:50 AM candle," traders can refer to "Bar 17" (on a 5m chart), which is faster and more consistent.
Backtesting Accuracy: When reviewing past days or using Bar Replay, you can easily identify if your strategy triggers at the same relative time every day.
Visual Discipline: By highlighting a "Target Bar," you can train your eyes to wait for specific time windows before looking for a setup, helping to prevent overtrading during low-probability hours.
Operational Efficiency: It removes the manual work of counting bars from the open, allowing you to focus entirely on price action and order flow.
How to Use
Install the script on any intraday timeframe (best on 5m or 15m).
Adjust Lookback: Use the settings to determine how many historical days you want to view.
Identify Patterns: Use the "Special Bar Highlight" to mark the bar where your strategy most frequently triggers.
Relative Strength Index SmoothedDefinition
The Relative Strength Index (RSI) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI, when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements.
History
J.Welles Wilder Jr. is the creator of the Relative Strength Index. A former Navy mechanic, Wilder would later go on to a career as a mechanical engineer. After a few years of trading commodities, Wilder focused his efforts on the study of technical analysis. In 1978 he published New Concepts in Technical Trading Systems. This work featured the debut of his new momentum oscillator, the Relative Strength Index, better known as RSI.
Over the years, RSI has remained quite popular and is now seen as one of the core, essential tools used by technical analysts the world over. Some practitioners of RSI have gone on to further build upon the work of Wilder. One rather notable example is Andrew Cardwell who used RSI for trend confirmation.
Calculation
RSI = 100 – 100/ (1 + RS)
RS = Average Gain of n days UP / Average Loss of n days DOWN
For a practical example, the built-in Pine Script function rsi(), could be replicated in long form as follows.
change = change(close)
gain = change >= 0 ? change : 0.0
loss = change < 0 ? (-1) * change : 0.0
avgGain = rma(gain, 14)
avgLoss = rma(loss, 14)
rs = avgGain / avgLoss
rsi = 100 - (100 / (1 + rs))
"rsi", above, is exactly equal to rsi(close, 14).
The basics
As previously mentioned, RSI is a momentum based oscillator. What this means is that as an oscillator, this indicator operates within a band or a set range of numbers or parameters. Specifically, RSI operates between a scale of 0 and 100. The closer RSI is to 0, the weaker the momentum is for price movements. The opposite is also true. An RSI closer to 100 indicates a period of stronger momentum.
- 14 days is likely the most popular period, however traders have been known to use a wide variety of numbers of days.
What to look for
Overbought/Oversold
Wilder believed that when prices rose very rapidly and therefore momentum was high enough, that the underlying financial instrument/commodity would have to eventually be considered overbought and a selling opportunity was possibly at hand. Likewise, when prices dropped rapidly and therefore momentum was low enough, the financial instrument would at some point be considered oversold presenting a possible buying opportunity.
There are set number ranges within RSI that Wilder consider useful and noteworthy in this regard. According to Wilder, any number above 70 should be considered overbought and any number below 30 should be considered oversold.
An RSI between 30 and 70 was to be considered neutral and an RSI around 50 signified “no trend”.
Some traders believe that Wilder’s overbought/oversold ranges are too wide and choose to alter those ranges. For example, someone might consider any number above 80 as overbought and anything below 20 as oversold. This is entirely at the trader’s discretion.
Divergence
RSI Divergence occurs when there is a difference between what the price action is indicating and what RSI is indicating. These differences can be interpreted as an impending reversal. Specifically there are two types of divergences, bearish and bullish.
Bullish RSI Divergence – When price makes a new low but RSI makes a higher low.
Bearish RSI Divergence – When price makes a new high but RSI makes a lower high.
Wilder believed that Bearish Divergence creates a selling opportunity while Bullish Divergence creates a buying opportunity.
Failure Swings
Failure swings are another occurrence which Wilder believed increased the likelihood of a price reversal. One thing to keep in mind about failure swings is that they are completely independent of price and rely solely on RSI. Failure swings consist of four “steps” and are considered to be either Bullish (buying opportunity) or Bearish (selling opportunity).
Bullish Failure Swing
RSI drops below 30 (considered oversold).
RSI bounces back above 30.
RSI pulls back but remains above 30 (remains above oversold)
RSI breaks out above its previous high.
Bearish Failure Swing
RSI rises above 70 (considered overbought)
RSI drops back below 70
RSI rises slightly but remains below 70 (remains below overbought)
RSI drops lower than its previous low.
Cardwell’s trend confirmations
Of course no one indicator is a magic bullet and almost nothing can be taken simply at face value. Andrew Cardwell, who was mentioned earlier, was one of those students who took Wilder’s RSI interpretations and built upon them. Cardwell’s work with RSI led to RSI being a great tool not just for anticipating reversals but also for confirming trends.
Uptrends/Downtrends
Cardwell made keen observations while studying Wilder’s ideas of divergence. Cardwell believed that:
Bullish Divergence only occurs in a Bearish Trend.
Bearish Divergence only occurs in an Bullish Trend.
Both Bullish and Bearish Divergence usually cause a brief price correction and not an actual trend reversal.
What this means is that essentially Divergence should be used as a way to confirm trends and not necessarily anticipate reversals.
Reversals
Cardwell also discovered what are referred to as Positive and Negative Reversals. Positive and Negative Reversals are basically the opposite of Divergence.
Positive Reversal occurs when price makes a higher low while RSI makes a lower low. Price proceeds to rise. Positive Reversals only occur in Bullish Trends.
Negative Reversal occurs when price makes a lower high while RSI makes a higher high. Price proceeds to fall. Negative Reversals only occur in Bearish Trends.
Positive and Negative Reversals can be boiled down to cases where price outperformed momentum. And because Positive and Negative Reversals only occur in their specified trends, they can be used as yet another tool for trend confirmation.
Summary
For more than four decades the Relative Strength Index (RSI) has been an extremely valuable tool for almost any serious technical analyst. Wilder’s work with momentum laid the groundwork for future chartists and analysts to dive in deeper to further explore the implications of his RSI modeling and its correlation with underlying price movements. As such, RSI is simply one of the best tools or indicators in a trader’s arsenal of market metrics to develop most any trading methodology. Only the novice will take one look at RSI and assume which direction the market will be heading next based off of one number. Wilder believed that a bullish divergence was a sign that the market would soon be on the rise, while Cardwell believed that such a divergence was merely a slight price correction on the continued road of a downward trend. As with any indicator, a trader should take the time to research and experiment with the indicator before relying on it as a sole source of information for any trading decision. When used in proper its perspective, RSI has proven to be a core indicator and reliable metric of price, velocity and depth of market.
Ratio Spread (Hybrid)Ratio Spread (Hybrid)
Ratio Spread (Hybrid) plots a daily OHLC “spread candle” built from the price ratio of two instruments:
Spread (Ratio) = A / B
A = Numerator (top leg)
B = Denominator (bottom leg)
It’s designed to be used on a Daily chart. Internally, it scans a lower intraday timeframe to reconstruct a more accurate daily High / Low / Close for the ratio than a simple daily A/B calculation.
What it does
- Builds a synthetic daily candle for the ratio A/B (Open, High, Low, Close).
- Uses intraday data to find the day’s true ratio extremes and last ratio close using only bars where both symbols line up by timestamp.
- Colors the bar green when Close >= Open and red when Close < Open.
How the Hybrid calculation works
1) Runs only on Daily charts
The script performs its intraday syncing/aggregation only when the chart timeframe is Daily.
2) Pulls intraday OHLC for both legs
It requests lower-timeframe OHLC for A and B using the selected Intraday TF.
3) Syncs intraday bars by time
It matches A and B intraday bars using their timestamps and only calculates ratios on matched bars. This helps avoid distortions from missing bars, different liquidity, or slight feed differences.
4) Builds the daily ratio candle from matched intraday bars
For each matched intraday bar it computes:
- Ratio Open = Open(A) / Open(B)
- Ratio Close = Close(A) / Close(B)
- Raw Ratio High = High(A) / High(B)
- Raw Ratio Low = Low(A) / Low(B)
Then it sanitizes each intraday ratio bar so High/Low always contains Open/Close:
- Intraday ratio High = max(ratio open, ratio close, raw ratio high)
- Intraday ratio Low = min(ratio open, ratio close, raw ratio low)
Across the day it aggregates:
- Daily High = highest intraday ratio High
- Daily Low = lowest intraday ratio Low
- Daily Close = ratio close of the last matched intraday bar
Daily Open options (the Hybrid part)
- Force Daily Open ON (recommended)
Daily Open = Official Daily Open(A) / Official Daily Open(B)
Intraday data is still used for High/Low/Close.
- Force Daily Open OFF
Daily Open = ratio open from the first matched intraday bar of the day.
Fail-safe
After aggregation, the script ensures the final daily High/Low includes the chosen Open and the final Close, so the candle range always covers them.
Recommended settings and best practices
- Use on a Daily chart (required for the calculation to run).
- Recommended Intraday TF: 15 minutes. Best balance between accuracy and performance.
- Recommended instruments: use legs from the same exchange/region/session when possible to improve timestamp alignment and reduce gaps.
Examples:
- Two US futures (e.g., CME/CBOT products)
- Two US stocks (both US-listed equities)
- Two instruments on the same exchange with similar trading hours
Notes
- If B is zero or either symbol has missing data, the ratio can be unavailable.
- If the two legs have different sessions/holidays, fewer bars will match, which can affect the computed daily OHLC.
CME Quarterly ShiftsCME Quarterly Shifts - Institutional Quarter Levels
Overview:
The CME Quarterly Shifts indicator tracks price action based on actual CME futures contract rollover dates, not calendar quarters. This indicator plots the Open, High, Low, and Close (OHLC) for each quarter, with quarters defined by the third Friday of March, June, September, and December - the exact dates when CME quarterly futures contracts expire and roll over.
Why CME Contract Dates Matter:
Institutional traders, hedge funds, and large market participants typically structure their positions around futures contract expiration cycles. By tracking quarters based on CME rollover dates rather than calendar months, this indicator aligns with how major institutional players view quarterly timeframes and position their capital.
Key Features:
✓ Automatic CME contract rollover date calculation (3rd Friday of Mar/Jun/Sep/Dec)
✓ Displays Quarter Open, High, Low, and Close levels
✓ Vertical break lines marking the start of each new quarter
✓ Quarter labels (Q1, Q2, Q3, Q4) for easy identification
✓ Adjustable history - show up to 20 previous quarters
✓ Fully customizable colors and line widths
✓ Works on any instrument and timeframe
✓ Toggle individual OHLC levels on/off
How to Use:
Quarter Open: The opening price when the new quarter begins (at CME rollover)
Quarter High: The highest price reached during the current quarter
Quarter Low: The lowest price reached during the current quarter
Quarter Close: The closing price from the previous quarter
These levels often act as key support/resistance zones as institutions reference them for quarterly performance, rebalancing, and position management.
Settings:
Display Options: Toggle quarterly break lines, OHLC levels, and labels
Max Quarters: Control how many historical quarters to display (1-20)
Colors: Customize colors for each level and break lines
Styles: Adjust line widths for OHLC levels and quarterly breaks
Best Practices:
Combine with other Smart Money Concepts (liquidity, order blocks, FVGs)
Watch for price reactions at quarterly Open levels
Monitor quarterly highs/lows as potential targets or stop levels
Use on higher timeframes (4H, Daily, Weekly) for clearer institutional perspective
Pairs well with monthly and yearly levels for multi-timeframe confluence
Perfect For:
ICT (Inner Circle Trader) methodology followers
Smart Money Concepts traders
Swing and position traders
Institutional-focused technical analysis
Traders tracking quarterly performance levels
Works on all markets: Forex, Indices, Commodities, Crypto, Stocks
Williams %R Smoothed (EMA colour & bar toggle)From TradingView's description:
Williams %R (%R) is a momentum-based oscillator used in technical analysis, primarily to identify overbought and oversold conditions. The %R is based on a comparison between the current close and the highest high for a user defined look back period. %R Oscillates between 0 and -100 (note the negative values) with readings closer to zero indicating more overbought conditions and readings closer to -100 indicating oversold. Typically %R can generate set ups based on overbought and oversold conditions as well overall changes in momentum.
What's special?
This indicator adds two additional EMA lines to the original Williams %R indicator. Default EMA lengths are 5 and 13. The result is 2 smoother average lines, which are easier to read.
This indicator includes:
- signals for EMA crosses. EMA crosses can help indicate confirmed trend changes. Default colors are green and red
- signals for trend reversals on the faster EMA line. Default colors are blue and orange
Alerts available for bullish/bearish crossovers and reversals.
Stochastic RSI (adjustable fast line color)Definition
The Stochastic RSI indicator (Stoch RSI) is essentially an indicator of an indicator. It is used in technical analysis to provide a stochastic calculation to the RSI indicator. This means that it is a measure of RSI relative to its own high/low range over a user defined period of time. The Stochastic RSI is an oscillator that calculates a value between 0 and 1 which is then plotted as a line. This indicator is primarily used for identifying overbought and oversold conditions.
History
The Stochastic RSI (Stoch RSI) indicator was developed by Tushard Chande and Stanley Kroll. They introduced their indicator in their 1994 book The New Technical Trader.
Calculation
In this example, a very common 14 Period Stoch RSI is used.
Stoch RSI = (RSI - Lowest Low RSI) / (Highest High RSI - Lowest Low RSI)
Here are some approximate benchmark levels:
14 Day Stoch RSI = 1 when RSI is at its highest level in 14 Days.
14 Day Stoch RSI = .8 when RSI is near the high of its 14 Day high/low range.
14 Day Stoch RSI = .5 when RSI is in the middle of its 14 Day high/low range.
14 Day Stoch RSI = .2 when RSI is near the low of its 14 Day high/low range.
14 Day Stoch RSI = 0 when RSI is at its lowest level in 14 Days.
The basics
It is important to remember that the Stoch RSI is an indicator of an indicator making it two steps away from price. RSI is one step away from price and therefore a stochastic calculation of the RSI is two steps away. This is important because as with any indicator that is multiple steps away from price, Stoch RSI can have brief disconnects from actual price movement. That being said, as a range bound indicator, the Stoch RSI's primary function is identifying crossovers as well as overbought and oversold conditions.
What to look for
Overbought/Oversold
Overbought and Oversold conditions are traditionally different than the RSI. While RSI overbought and oversold conditions are traditionally set at 70 for overbought and 30 for oversold, Stoch RSI are typically .80 and .20 respectively. When using the Stoch RSI, overbought and oversold work best when trading along with the underlying trend.
During an uptrend, look for oversold conditions for points of entry.
During a downtrend, look for overbought conditions for points of entry.
Summary
When using Stoch RSI in technical analysis, a trader should be careful. By adding the Stochastic calculation to RSI, speed is greatly increased. This can generate many more signals and therefore more bad signals as well as the good ones. Stoch RSI needs to be combined with additional tools or indicators in order to be at its most effective. Using trend lines or basic chart pattern analysis can help to identify major, underlying trends and increase the Stoch RSI's accuracy. Using Stoch RSI to make trades that go against the underlying trend is a dangerous proposition.
Inputs
K
The time period to be used in calculating the %K. 3 is the default.
D
% D = Percent of Deviation between price and the average of previous prices (Momentum). The time period to be used in calculating the %D. 3 is the default.
RSI Length
The time period to be used in calculating the RSI
Stochastic Length
The time period to be used in calculating the Stochastic
RSI Source
Determines what data from each bar will be used in calculations. Close is the default.
Tomorrow Bullish Detector [Customizable]This indicator is a comprehensive technical analysis suite designed to identify high-probability bullish setups using a multi-factor scorecard approach. It provides real-time feedback directly on your chart through a dynamic dashboard and visual heatmaps.
Key Features
6-Element Bullish Scorecard: Automatically tracks six critical technical metrics:
Trend Alignment: Evaluates EMA fast/slow cross.
Baseline Position: Checks if price is above the 200 SMA.
Momentum (RSI): Confirms strength is above the 50-level midline.
Breakout Detection: Monitors price action against recent highs.
Volatility Expansion: Analyzes ATR for active market moves.
Relative Volume (RVOL): Identifies institutional interest via volume surges.
Fully Customizable Visuals:
Moveable Dashboard: Position the scorecard panel in any corner of the screen (Top Right, Bottom Left, etc.).
Adjustable Text Size: Choose between Small, Normal, or Large text to fit your screen resolution.
Visual Heatmap: The chart background shifts color based on the live probability score.
Transparency Controls: Independently adjust the opacity of the gradient and on-chart labels.
How to Use
Overlay on Main Chart: This indicator is designed as an overlay to keep your price action front and center.
Monitor the Grade: Look for high-grade labels (A/A+) which indicate that the highest technical criteria are being met.
Refine with Inputs: Use the settings menu to adjust EMA lengths, RSI periods, and volume multipliers to match your specific trading style.
### Disclaimer
For Educational Purposes Only. This indicator is a technical tool designed to assist in market analysis and does not constitute financial advice, investment recommendations, or an offer to buy or sell any security. Trading involves significant risk, and past performance is not indicative of future results. Always perform your own due diligence and consult with a licensed financial advisor before making any investment decisions. The author is not responsible for any financial losses incurred through the use of this script.
ICT ASIA & DTCC Session Range |MC|This indicator plots the ASIA & DTCC Range on the Chart
(Credits go to the Inner Circle Trader ICT)
💎 Features 💎
💎 Session-based range calculation with timezone-safe session detection
💎 Supported sessions:
🔸 ASIA Session (configurable time window)
🔸 DTCC Session (configurable time window) (default: 8-8:45pm NY EST/EDT Time)
(plots a second DTCC Box at: 2-2:45pm NY EST/EDT Time)
💎 Automatic High / Low range tracking per session
💎 Optional Close-to-Close range calculation (candle body based)
💎 Session range visualization:
🔸 High & Low horizontal levels
🔸 Session box (range area)
💎 Optional ASIA Range standard deviation projections:
🔸 Configurable number of extensions above and below the range
🔸 Optional midlines (0.5 extensions)
💎 Market-adaptive range values:
🔸 Forex → Pips
🔸 Indices / Commodities → Points
🔸 Crypto → Ticks
💎 On-chart range table with session values
💎 Customizable colors, line styles, and visibility options
💎 History control:
🔸 Limit displayed objects to the last X sessions
🔸 Automatic cleanup of old boxes and lines to prevent clutter
💎 Session Times (Default):
🔸 ASIA Session: user-defined (commonly Asian market hours)
🔸 DTCC Session: user-defined (aligned with DTCC delivery window)
🔸 All sessions are calculated using a user-selectable timezone
💎 Technical Notes:
🔸 Objects (boxes and lines) are finalized once per session to ensure stability
🔸 No repainting after session close
🔸 Compatible with intraday timeframes
🔸 Designed to minimize redraw issues during chart scrolling or zooming
💎 Changelog (Initial Release):
🔸 Initial release with ASIA and DTCC session range detection
🔸 Added session boxes, High/Low levels, and projection lines
🔸 Added adaptive range unit calculation (Pips / Points / Ticks)
🔸 Added configurable session history limit
🔸 Improved object lifecycle management for stable chart behavior
🔹 Warning: Do not trade based on this indicator alone. Always use it in combination with other
analysis and risk management techniques.
Happy Trading!
Nested MA Envelopes HarmonicThe Nested MA Envelopes Harmonic is a custom TradingView Pine Script indicator that overlays a series of nested envelopes around exponentially increasing simple moving averages (SMAs). These SMAs use lengths that double successively (e.g., 25, 50, 100, 200, up to 3200, starting from a user-defined power-of-2 base). Each envelope is offset by deviations that follow a harmonic/octave structure (multipliers of ×1, ×2, ×4, ×8, ×16, ×32, ×64, ×128).The deviation can be set in fixed points or as a true percentage of price, with an optional auto-calibration mode that dynamically adjusts the multiplier based on historical price behavior and ATR to target a specified percentage of bars staying within the innermost envelope. The envelopes feature customizable colors, shaded zones between levels, touch counters, cycle number labels on band touches (with cooldown), and optional centering.This creates a visually layered "harmonic" channel system resembling octave bands, helping identify multi-scale support/resistance zones.
Use CaseTraders use this indicator to visualize price action across multiple time scales simultaneously, treating the nested bands as harmonic levels of volatility or mean reversion zones. Inner envelopes (levels 1–3) capture short-term fluctuations and potential overbought/oversold conditions.
Outer envelopes (levels 6–8) act as major support/resistance during strong trends or reversals.
The cycle labels mark significant touches of higher-level bands (e.g., a "7" or "8" label signals rare extreme extensions, often preceding reversals). It suits mean-reversion strategies (buy near lower bands, sell near upper), trend confirmation (price hugging mid-levels), or breakout alerts when price pierces outer zones. The auto mode adapts to changing volatility, making it versatile for stocks, forex, crypto, or futures on various timeframes.
Personal use - set on your favorite instrument and set to auto mode. Make note of the level picked in bottom right corner. Then switch to manual mode and use the same multiplier that auto used to get you in the right sizing ballpark. The goal is to capture 95% of pricing within the smallest envelope. The what you will see is you can quantify various tops and bottoms. A 1st order (hitting the top/bottom of the smallest envelope) hit is not as important as a 2nd or 3rd order hit. Generally 1st order is informational and 2-5 is actionable. 6-8 would be a unicorn and you should act accordingly. You can use points or % for the spacing.
ISM + 4Y Sine (Locked, Pane)Overview
This indicator plots a US Manufacturing PMI series (ISM, or a PMI proxy) alongside a stylised 4-year business-cycle sine curve, locked to calendar months. It is designed for macro/cycle context, particularly for comparing economic momentum with risk assets such as Bitcoin or equities.
The indicator runs in its own pane and is intentionally indicator-only (no asset in the lower pane) to keep scrolling/zooming aligned beneath a primary price chart.
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What it shows
ISM / PMI (monthly) — fetched via TradingView’s security() data request from a user-selectable economic data series.
4-Year Sine Curve — a smooth, parameterised cycle intended to approximate the long-run business cycle.
Background shading — optional cue when ISM/PMI is above or below the cycle curve.
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How to use
Apply the script to any chart (commonly BTCUSD or major equity indices).
Set the chart timeframe to 1M (monthly) when tuning the cycle.
In Inputs, select a valid ISM/PMI series available on your TradingView account.
Adjust:
Cycle Length (years) — start around 4.0; larger values can reflect a “stretched” cycle.
Phase Shift (months) — shifts the cycle left/right to align peaks and troughs with historical turning points.
Mid Level / Amplitude — scales the sine wave to match the typical ISM/PMI range (roughly 40–70).
Once aligned on monthly data, you can view the chart on weekly/daily for context (the economic series remains monthly).
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Design notes
The sine wave is anchored to calendar months (not bar count) to prevent drift when switching timeframes.
The lower pane contains no asset, only indicator data, to keep navigation stable beneath the main chart.
If the selected ISM/PMI symbol becomes unavailable, the cycle curve will still plot, but the ISM/PMI line will not display until a valid series is selected.
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Use case
This tool is intended for contextual macro analysis, not as a standalone trading signal. It’s best used to understand where price action sits within the broader economic cycle and to compare current conditions with prior cycle phases.
Not financial advice.
SSMT [jam]🔷 Quarterly Theory SSMT based off of Daye's Quarterly Theory
This indicator detects Sequential SMTs between the charted symbols and up to two other correlated symbols using a hierarchical, time-based cycle system.
❓ What It Does
The script divides time into five nested cycles:
Nano: ~5.625 min (double to ~11.25 min) – best on seconds charts
Micro: ~22.5 min (double to ~45 min) – best on 1-minute charts
90m: 90 min (double to 180 min) – best on 5-minute charts
Daily Session: 6-hour segments (double to 12-hour) – best on 15-minute charts
Weekly: Day-based phases (Q1–Q5; doublable) – best on 60-minute charts
Within each cycle, it tracks price extremes for all selected symbols. When a cycle ends, it checks if the main index and comparison indices moved in opposite directions from their prior-cycle extremes. Matching opposite moves trigger a divergence signal.
Divergences appear as coloured extending lines connecting the prior and current extremes, with labels showing which symbols diverged.
⭐ Unique Aspects
Covers five fractal levels from ultra-short nano to weekly
Allows higher-timeframe divergences on lower charts (e.g., daily/weekly signals visible on 1m)
Auto-adjusts so the charted symbol is always the primary reference
Optional vertical dividers and fixed Q-labels for clear cycle timing
🎀 Extensive Customization
Global controls: Toggle all divergences, dividers, cycle labels; universal label background, text colour, size, position (start/middle/end of line), and style (auto/up/down)
Per-cycle settings (independent for Nano, Micro, 90m, Daily, Weekly):
Show/hide the cycle's divergences
Doubling option
Separate bullish and bearish line colours
Line width and style (solid/dashed/dotted)
Divider colour, width, and style
Toggle Q-labels
Option to display this cycle's signals on lower timeframes
🔨 How to Use
I personally apply it to NQ, ES, and YM (CFDs), but you can choose whichever symbols you trade/prefer. Divergence lines form at cycle boundaries:
Bullish divergence (typically lower low on main index but higher on others) → potential support/rotation higher
Bearish divergence (typically higher high on main but lower on others) → potential resistance/rotation lower
Stronger signals occur when multiple cycle levels align. Always combine with your own analysis and risk management.
A highly configurable tool for spotting intermarket relative strength/weakness across multiple time scales.
BTC - StableFlow: Pit-Stop & Refuel EngineBTC – StableFlow: Pit-Stop & Refuel Engine | RM
Strategic Context: The Institutional Gas Station In the high-speed race of the crypto markets, Stablecoins (USDT, USDC, DAI) represent the Fuel, and Bitcoin is the Race Car. Most traders only look at the car's speed (Price), but they ignore the gas tank. The StableFlow Engine is a telemetry dashboard designed to monitor the "Fuel Pressure" within the ecosystem, identifying exactly when the car is being refueled and when it is running on empty.
The Telemetry Logic: How to Read the Race
The indicator operates on a Relative Velocity model. We aren't just looking at how many Stablecoins exist; we are measuring the Acceleration of Stablecoin Market Cap relative to the Acceleration of BTC Price.
1. The Fuel Reservoir (The Histogram)
• Cyan Zones (Refuel): The gas station is open. Institutional "Dry Powder" is flowing into stables faster than it is being spent on BTC. The tank is filling up.
• Orange Zones (Exhaust): The "Overdrive." The car is driving faster than the gas can be pumped. Price is outperforming the stablecoin supply—this is unsustainable and usually precedes a stall.
2. Lap Transitions (The Grey Lines)
These vertical markers signify a Regime Shift . They trigger the moment the momentum crosses the zero-axis, visually distinguishing the transition between a "Net-Refueling" period and a "Net-Exhaustion" period. While not used as direct entry signals, they define the Macro Lap we are currently in.
Operational Playbook: The Pit-Stop Signals
We don't just buy because the tank is full; we buy when the car exits the pits and begins to accelerate. This is captured by our proprietary Pit-Stop Pips.
• Blue Pip (Pit-Stop Buy): Triggered when the Refuel momentum has peaked and is now rotating back into the market. The refuel is complete; the car is rejoining the race with a full tank.
• Red Pip (Exhaust Sell): Triggered when the price acceleration has overextended relative to its fuel source and begins to "roll over." The tank is near empty; time for a tactical pull-back.
Settings & Calibration: The Pit Wall Dashboard
Signal Mode & Logic The engine features a dual-mode signaling system to adapt to different market conditions (or your personal preferred logic):
• Consecutive Mode: Best for high-velocity trends. Fires a pip after n bars of momentum reversal (Default: 2 bars).
• Percentage (%) Mode: Best for structural fades. Fires a pip when the momentum retraces by a specific percentage (e.g., 15%) from its local peak, regardless of the bar count.
Recommended Calibration
While the engine is versatile across various timeframes, the Weekly (1W) chart is the preferred setting for identifying high-conviction macro signals. Lower timeframes provide tactical speed, but the 1W frame offers significantly cleaner signals by filtering out the daily market noise.
Weekly (1W) — The Macro Signal (Preferred): * Velocity Lookback: 20 | Smoothing: 5.
Peak Lookback: 25 (Represents roughly half a year of telemetry data). This is a good starting point for identifying major cycle rotations.
Daily (1D) — The Tactical Pulse: * Velocity Lookback: 20 | Smoothing: 5.
Peak Lookback: 25 (Represents one trading month of telemetry). Useful for active swing traders looking for entry/exit timing within an established macro trend.
Technical Documentation
Data Sourcing & Aggregation The script utilizes request.security to aggregate a "Big Three" Stablecoin Market Cap (USDT + USDC + DAI). This prevents "False Exhaustion" signals caused by capital simply migrating between different stablecoin assets.
Mathematical Foundation The core engine calculates the Rate of Change (ROC) for the Aggregate Stablecoin Supply and BTC Price over a synchronized lookback window.
Formula Logic: Fuel Pressure = EMA ( ROC(Stables) - ROC(BTC) )
The Pit-Stop Pips utilize a local peak-finding algorithm via ta.highest and ta.lowest within a rolling 25-bar window to calculate the Relative Retracement Magnitude . This ensures signals are mathematically tied to the volatility of the current market regime.
The Dual-Fuel Framework: StableFlow x Liquisync
The StableFlow Engine is designed to function as the tactical counterpart to the Liquisync: Macro Pulse Engine . While Liquisync monitors the Global Supply Line (the "Tanker Truck" of M2 Liquidity moving from Central Banks toward the track with a 60-day lead), StableFlow measures the Immediate Fuel Pressure (the "Dry Powder" already in the pit lane, ready to be pumped into the car).
By using both indicators in tandem, you can follow the Dual-Fuel Strategy: Liquisync identifies the fundamental macro regime, while StableFlow identifies the specific "Refuel" and "Exhaustion" pivots within that regime. We will be providing a comprehensive breakdown of this synchronized telemetry in our upcoming Substack Masterclass: The Dual-Fuel Architecture.
Risk Disclaimer & Credits
The StableFlow is a thematic macro tool tracking on-chain liquidity proxies. Stablecoin data is subject to exchange reporting delays. This is not financial advice; it is a telemetry model for institutional education. Rob Maths is not liable for losses incurred via use of this model.
Tags:
indicator, bitcoin, btc, stablecoins, usdt, flow, liquidity, macro, refuel, institutional, robmaths, Rob Maths
Smart Money Zones - Multi-Timeframe AnalysisA clean and efficient smart money concepts indicator designed for traders who follow institutional order flow and price imbalances.
Core Features:
Fair Value Gaps (FVG): Automatically detects bullish and bearish imbalances where price moved too fast, leaving gaps that often get filled
Order Blocks (OB): Identifies the last bearish candle before a bullish move (and vice versa) - institutional accumulation/distribution zones
Zone Strength Rating: Each zone is classified as Very Strong, Strong, Medium, or Weak based on size relative to ATR
Multi-Timeframe Trend Panel: Real-time dashboard showing bullish/bearish trend across 7 timeframes (1m, 5m, 15m, 30m, 1H, 4H, 1D)
Smart Features:
Zones automatically extend into the future
Mitigation tracking - zones fade when 50% filled or fully violated
Optional trend filter - only shows zones aligned with the trend
Customizable zone limits to keep your chart clean
Adjustable panel position (4 corners) and size
Color-Coded Zones:
🟢 Bullish FVG (Green) - Support zones
🔴 Bearish FVG (Red) - Resistance zones
🔵 Bullish OB (Blue) - Demand zones
🟠 Bearish OB (Orange) - Supply zones
Perfect for scalpers, day traders, and swing traders who trade reversals at key institutional levels. Combines smart money concepts with multi-timeframe confirmation for higher probability setups.
QT-AKHOKOاندیکاتور "QT" در پلتفرم TradingView یک ابزار پیشرفته برای تجزیه و تحلیل بازار است که از چندین چرخه زمانی مختلف بهره میبرد. این اندیکاتور به شما کمک میکند تا نقاط بحرانی در بازههای زمانی مختلف (سالیانه، ماهانه، هفتگی، روزانه، 90 دقیقهای و میکرو) را شناسایی کنید. ویژگی برجسته این اندیکاتور، استفاده از SSMT (Same Cycle Multiple Timeframes) و PSP (Price Signal Patterns) برای ارائه سیگنالهای دقیقتر است. این دو بخش باعث میشوند که اندیکاتور "QT" به ابزاری قدرتمند برای تریدرها تبدیل شود.
ویژگیهای اصلی:
SSMT (Same Cycle Multiple Timeframes):
SSMT یک روش تجزیه و تحلیل پیشرفته است که در آن یک چرخه زمانی خاص بهطور همزمان در چندین تایم فریم مختلف رصد میشود. این اندیکاتور با استفاده از SSMT، به شما این امکان را میدهد که تغییرات قیمت در تایم فریمهای مختلف را مقایسه کنید و سیگنالهایی که در چندین تایم فریم همزمان فعال هستند، شناسایی کنید.
این سیگنالها میتوانند به شما کمک کنند که نقاط ورود و خروج بهتری داشته باشید، چرا که تایید شدن سیگنال در چند تایم فریم به معنای اعتبار بالای آن است.
به عنوان مثال، زمانی که یک شکست قیمتی در تایم فریم روزانه رخ میدهد و همزمان در تایم فریمهای هفتگی و ماهانه هم تأیید میشود، احتمال اینکه این حرکت ادامهدار باشد، بسیار بالا خواهد بود.
SSMT قابلیت تنظیم دارد و میتوانید آن را بر اساس نیاز خود بهطور سفارشی تنظیم کنید، از جمله تعیین نحوه نمایش علامتها، رنگها و خطوط سیگنال.
PSP (Price Signal Patterns):
PSP یکی از بخشهای کلیدی اندیکاتور QT است که از الگوهای خاص قیمتی برای شناسایی تغییرات مهم در بازار استفاده میکند. این الگوها میتوانند شامل شکستها (Breakouts)، برگشتها (Reversals) و تغییرات روند (Trend Changes) باشند.
اندیکاتور PSP از دو نماد مختلف برای مقایسه استفاده میکند (مثلاً "SPY" و "QQQ") و نقاطی که این نمادها با یکدیگر دچار انحراف میشوند را شناسایی میکند. به عنوان مثال، اگر یک نماد صعودی باشد اما دیگری نزولی باشد، این میتواند بهعنوان یک هشدار برای تغییر روند بازار عمل کند.
در کنار این الگوها، این اندیکاتور از نشانگرهای گرافیکی (مانند مثلثها، فلشها و علامتهای دایرهای) برای نمایش این تغییرات استفاده میکند.
PSP همچنین این امکان را به شما میدهد که سیگنالهای قیمتی را در تایم فریمهای مختلف مشاهده کرده و تصمیمات دقیقتری بگیرید.
چرخههای زمانی و جعبهها:
اندیکاتور QT از جعبههای زمانی برای نمایش تغییرات در چارچوبهای زمانی مختلف (سالیانه، ماهانه، هفتگی و غیره) استفاده میکند.
این جعبهها میتوانند بهطور خودکار و با تنظیمات سفارشی شما رسم شوند، بهطوری که شما میتوانید روندهای مختلف بازار را در تایم فریمهای متفاوت مشاهده کنید.
بهطور کلی، این ویژگی به شما کمک میکند که نقاط حمایت و مقاومت مهم در زمانهای مختلف بازار را شناسایی کنید.
گرافیک و سفارشیسازی:
این اندیکاتور به شما این امکان را میدهد که رنگها، اندازهها، و استایلهای گرافیکی را به دلخواه خود تغییر دهید. این ویژگی به تریدرها این امکان را میدهد که ابزار را با توجه به نیاز خود شخصیسازی کنند.
همچنین، از آنجا که این اندیکاتور از چندین چرخه زمانی استفاده میکند، شما میتوانید هرکدام از این چرخهها را با استایلهای مختلف نمایش دهید، مثل استفاده از خطچین، نقطهچین یا خطهای عادی.
خلاصه:
اندیکاتور "QT" با استفاده از تکنیکهای پیشرفته مانند SSMT و PSP، تجزیه و تحلیل بازار را در چندین تایم فریم مختلف برای شما امکانپذیر میسازد. این اندیکاتور با تحلیل دقیق چرخههای زمانی مختلف و شناسایی الگوهای قیمتی، سیگنالهایی را برای ورود و خروج به بازار به شما ارائه میدهد که میتواند بهطور قابلتوجهی به استراتژی معاملاتی شما کمک کند.
English:
Detailed Description of QT Indicator with Focus on SSMT and PSP:
The "QT" indicator on TradingView is an advanced tool designed for market analysis using multiple time cycles. It provides traders with a comprehensive view of market trends across different time frames (Yearly, Monthly, Weekly, Daily, 90-minute, and Micro). The standout feature of this indicator is its utilization of SSMT (Same Cycle Multiple Timeframes) and PSP (Price Signal Patterns), which enhances its ability to deliver more accurate signals. These two components make the "QT" indicator a powerful tool for traders.
Main Features:
SSMT (Same Cycle Multiple Timeframes):
SSMT is an advanced analysis technique that monitors a specific cycle across multiple time frames simultaneously. By using SSMT, this indicator allows traders to compare price changes across different time frames and identify signals that are active across multiple time frames.
These signals help traders identify high-probability entry and exit points because when a signal is confirmed across several time frames, it indicates a strong likelihood of a sustained price move.
For example, if a price breakout occurs on the daily time frame and is simultaneously confirmed on the weekly and monthly time frames, it is more likely to continue.
SSMT is highly customizable, allowing traders to adjust how markers, colors, and signal lines are displayed based on their preferences.
PSP (Price Signal Patterns):
PSP is one of the key components of the QT indicator that uses specific price patterns to identify significant market changes. These patterns can include breakouts, reversals, and trend changes.
The indicator utilizes two symbols (e.g., "SPY" and "QQQ") to compare and identify when these symbols diverge, signaling potential market shifts. For instance, if one symbol is bullish while another is bearish, this could signal a change in market direction.
In addition to these patterns, the indicator uses graphical markers (such as triangles, arrows, and circles) to visually represent these market changes and signals.
PSP allows traders to view price signals across different time frames, helping them make more informed decisions.
Time Cycles and Boxes:
The QT indicator uses time boxes to visually display price changes across different time frames (Yearly, Monthly, Weekly, etc.).
These boxes are automatically drawn and can be customized based on the user's settings, allowing traders to observe market trends across various periods.
Overall, this feature helps traders identify critical support and resistance levels at different points in time.
Graphics and Customization:
This indicator allows traders to customize colors, sizes, and graphical styles to fit their needs.
Additionally, since the indicator uses multiple time cycles, traders can display each cycle with different styles, such as solid, dotted, or dashed lines.
Summary:
The "QT" indicator, using advanced techniques like SSMT and PSP, allows traders to analyze the market across multiple time frames. By detecting significant price patterns and utilizing time cycles, the QT indicator provides high-probability signals for market entry and exit. This can greatly assist in enhancing your trading strategy.
Institutional Bottom Hunter ProInstitutional Bottom Hunter Pro: A Comprehensive Guide to Advanced Bottom Detection
Executive Summary
The Institutional Bottom Hunter Pro (IBH Pro) represents a paradigm shift in technical analysis for retail and institutional investors seeking to identify high-probability market bottoms. Unlike conventional oversold indicators that rely on single-dimensional analysis, IBH Pro employs an eight-layer ensemble methodology that synthesizes market regime detection, volume analysis, fractal geometry, volatility dynamics, statistical mean reversion, cycle theory, institutional footprint recognition, and machine learning-inspired adaptive weighting. This comprehensive approach transforms bottom-picking from speculation into a data-driven probabilistic framework.
I. The Specialty: What Makes IBH Pro Different
A. Multi-Dimensional Analytical Framework
Most technical indicators suffer from the "single lens" problem—RSI identifies oversold conditions, MACD reveals momentum divergence, and volume indicators track accumulation, but each operates in isolation. IBH Pro's revolutionary approach integrates seven independent analytical systems into a unified probability score, creating a holistic view of market conditions that individual indicators cannot provide.
The script's architecture mirrors institutional-grade quantitative analysis:
Market Regime Detection ensures signals only activate during genuine correction phases
Wyckoff-Inspired Volume Analysis identifies supply exhaustion using climactic volume, absorption patterns, and effort-versus-result dynamics
Fractal Pattern Recognition detects structural bottoms through Williams fractals, double/triple bottoms, and reversal candlestick patterns
Volatility Regime Analysis quantifies fear extremes using ATR percentiles, Bollinger Band compression, and volatility term structure
Statistical Mean Reversion employs multi-timeframe Z-scores to measure price displacement from equilibrium
Ehlers Cycle Detection identifies cyclical troughs using autocorrelation and phase analysis
Passive Buying Detection reveals institutional accumulation through Money Flow Index divergences, Chaikin Money Flow, and volume footprint analysis
B. Adaptive Weight Optimization (GBM-Inspired Machine Learning)
The true innovation lies in the Gradient Boosting Machine (GBM) ensemble scoring system with adaptive weight optimization. Traditional indicators assign static importance to each component, but IBH Pro continuously learns from its own performance:
Performance Tracking: The system monitors whether previous signals resulted in profitable price advances
Dynamic Weight Adjustment: Components that contribute to successful signals receive increased weighting, while underperforming factors are de-emphasized
Market Adaptation: The indicator automatically adjusts to changing market conditions—for example, increasing volume analysis weight during climactic selloffs or emphasizing cycle detection in ranging markets
This creates a self-improving system that becomes more accurate over time, unlike static indicators that degrade as market conditions evolve.
C. Interaction Effect Multipliers
IBH Pro recognizes that analytical components don't operate independently—they create synergistic relationships:
Volume + Fractal Synergy: A double bottom pattern (fractal) confirmed by volume exhaustion carries exponentially higher probability than either signal alone
Mean Reversion + Volatility Synergy: Extreme statistical displacement combined with volatility expansion indicates capitulation
Cycle + Correction Synergy: Cyclical troughs occurring during technical corrections represent optimal entry zones
The script applies multiplicative bonuses when multiple high-probability conditions align, capturing the compounding effect of confluence that professional traders utilize.
II. How the Eight-Layer Architecture Works
Layer 1: Market Regime Detection
Purpose: Filter out false signals during trending markets where "oversold" conditions can persist indefinitely.
Methodology:
The system calculates drawdown from the recent high (50-200 bar lookback) and requires minimum decline thresholds before activating. It analyzes:
Momentum decay: Rate-of-change deterioration from peak values
Trend strength weakening: ADX decline indicating trend exhaustion
Moving average displacement: Distance below 20/50/100 SMAs
User Application: Set the "Minimum Drawdown for Correction" parameter based on asset volatility:
Low volatility stocks (utilities, consumer staples): 5-8%
Medium volatility (large-cap tech, industrials): 8-12%
High volatility (small-caps, growth stocks): 12-20%
This ensures the system only hunts bottoms when genuine corrections occur, not during minor consolidations.
Layer 2: Volume Supply Exhaustion Analysis
Purpose: Identify when selling pressure has been fully absorbed by buyers—a hallmark of institutional bottoming patterns.
Wyckoff-Inspired Components:
Climactic Volume Detection: Identifies panic selling when volume exceeds the 20-day average by 2x+ (adjustable multiplier), particularly on down days
Volume Dry-Up After Climax: Tracks whether volume contracts below 60% of average following the climax—indicating seller exhaustion
Effort vs. Result Analysis: Measures whether high volume (effort) produces minimal price decline (result), suggesting absorption by strong hands
Up/Down Volume Ratio: Segregates volume by bar direction, revealing when buying volume begins dominating despite price weakness
OBV/A-D Divergences: Detects when cumulative volume indicators trend upward while price trends downward—classic accumulation signature
User Application:
In high-volume liquid stocks, increase the Climax Volume Multiplier to 2.5-3.0 to filter noise
For low-volume small-caps, decrease to 1.5-2.0 to capture subtler signals
Enable "Use Up/Down Volume Analysis" for all equity analysis; disable for highly illiquid instruments
Layer 3: Fractal Pattern Recognition
Purpose: Identify structural price formations that mark trend reversals through geometric pattern analysis.
Components:
Williams Fractals: Detects swing highs/lows using N-bar symmetry (default 5 bars)
Double/Triple Bottom Detection: Identifies repeated tests of support within tolerance thresholds (default 2%), storing the five most recent fractal lows for pattern matching
Reversal Candlestick Patterns: Recognizes hammers, bullish engulfing, morning stars, dragonfly dojis, and bullish harami formations
Support Proximity Analysis: Measures distance to recent support zones and identifies bounces with strong closes
User Application:
Daily timeframe: Use default 5-bar fractal period with 2% tolerance
Weekly timeframe: Increase to 7-bar period with 3% tolerance
Intraday (1-hour): Decrease to 3-bar period with 1.5% tolerance
The Pattern Tolerance parameter accommodates price volatility—increase for volatile instruments
Layer 4: Volatility Regime Analysis
Purpose: Quantify fear extremes and identify volatility compression/expansion cycles that precede reversals.
Components:
ATR Percentile Ranking: Determines if current volatility ranks in the top 25% of recent range—indicating fear
Bollinger Band Analysis:
Price below lower band = oversold extreme
Band width contraction = squeeze (energy building for reversal)
%B calculation shows precise position within bands
Keltner Channel Integration: True squeeze detection when Bollinger Bands compress inside Keltner Channels
Volatility Term Structure: Compares 20-day vs. 50-day historical volatility to identify "backwardation" (short-term vol exceeding long-term), which marks panic conditions
User Application:
Bollinger StdDev: Keep at 2.0 for standard analysis; increase to 2.5-3.0 for extremely volatile assets to reduce false oversold signals
Keltner Multiplier: Default 1.5 works for most equities; increase to 2.0 for high-beta stocks
Watch for squeeze releases (when both ATR contracts then expands AND Bollinger Bands widen) as high-probability entry triggers
Layer 5: Statistical Mean Reversion
Purpose: Apply rigorous statistical methods to measure price displacement from equilibrium across multiple timeframes.
Components:
Multi-Method Z-Score Calculation:
SMA-based Z-score (classical approach)
EMA-based Z-score (weight recent data)
Linear regression Z-score (trend-adjusted)
VWAP deviation (volume-weighted equilibrium)
RSI Z-Score: Identifies when RSI itself becomes statistically extreme relative to its historical distribution
Multi-Timeframe Deviation: Measures distance from 20/50/100 SMAs simultaneously to detect structural dislocation
User Application:
Z-Score Threshold: Default -1.5 is moderate; decrease to -2.0 for higher-conviction signals with fewer triggers
Mean Reversion Period:
30-40 bars for swing trading
50-70 bars for position trading
80-100 bars for long-term investing
RSI Oversold Level: Keep at 30 for balanced signals; lower to 25 for higher conviction
Layer 6: Cycle Detection (Ehlers Algorithms)
Purpose: Identify dominant market cycles and detect when price reaches cyclical troughs, similar to institutional timing models.
Methodology:
The system employs John Ehlers' digital signal processing techniques:
High-Pass Filter: Removes trend component to isolate cyclical behavior
Super Smoother: Eliminates noise while preserving cycle structure
Autocorrelation Analysis: Scans 10-50 bar periods to identify the dominant cycle length
Phase Calculation: Determines current position within the cycle (trough, peak, or midpoint)
Cycle Stochastic: Measures whether the detrended price is in the bottom 20% of its cycle range
User Application:
Minimum/Maximum Cycle Period: Adjust based on trading timeframe:
Day traders: 5-20 bars
Swing traders: 10-50 bars (default)
Position traders: 20-80 bars
Cycle detection works best on mean-reverting instruments (indices, large-caps) vs. strong trending small-caps
High cycle confidence (autocorrelation >0.5) increases signal reliability significantly
Layer 7: Passive Buying Detection
Purpose: Identify institutional accumulation patterns that occur beneath the surface before public recognition.
Components:
Money Flow Index: Detects oversold conditions (<20) and bullish divergences
Chaikin Money Flow: Reveals buying pressure even on down days when CMF remains positive
Force Index Divergence: Identifies weakening selling force despite continued price decline
Accumulation Pattern Recognition: Counts down-days with positive money flow (passive buying)
Institutional Footprint: Detects high-volume reversals with closes near highs at support levels
User Application:
This layer is particularly valuable for identifying smart money activity before trend reversals
Strong passive buying scores (>60) often precede sustainable rallies by 3-10 bars
Combine with volume exhaustion for highest-conviction setups
Layer 8: GBM Ensemble Scoring
Purpose: Synthesize all seven analytical layers into a unified 0-100 probability score using adaptive machine learning.
Process:
Initial Weights: Start with balanced distribution (Correction: 15%, Volume: 18%, Fractal: 15%, Volatility: 12%, Mean Reversion: 15%, Cycle: 10%, Passive: 15%)
Performance Tracking: Monitor whether signals lead to >2% gains within 5-20 bars
Gradient Descent Adaptation: Successful components receive incremental weight increases; failed components decrease
Normalization: Weights continuously rebalance to sum to 100%
Interaction Effects: Apply multiplicative bonuses (default 1.2x) when multiple components exceed thresholds simultaneously
Final Filtering: Apply the correction regime filter—reducing scores by 40% when not in defined correction phase
User Application:
Learning Rate: Default 0.02 provides steady adaptation; increase to 0.05 for faster learning in fast-changing markets
Weight Boundaries: Min 0.08 / Max 0.35 prevents over-reliance on single factors
Interaction Boost: Increase to 1.3-1.5 when seeking only highest-confluence setups
Allow 50-100 bars for the adaptive system to calibrate to your specific asset
III. How to Use IBH Pro Effectively for Bottom Finding
A. Signal Hierarchy and Action Framework
STRONG SIGNALS (Score ≥ 65, Green Triangle)
Interpretation: High-probability institutional bottom with 4+ layers confirming
Action for Investors:
Aggressive: Enter 50-75% of intended position immediately
Conservative: Enter 33% immediately, scale in on any lower retest
Risk Management: Place stop-loss 3-5% below signal bar low (adjust for ATR)
Expected Outcome: 60-75% success rate for 5%+ gain within 2-4 weeks
MODERATE SIGNALS (Score 50-64, Yellow Triangle)
Interpretation: Developing bottom with 2-3 confirming layers
Action for Investors:
Watch for additional confirmation (volume spike, reversal candle)
Enter 25-33% position as "scout" entry
Prepare for potential retest of lows
Risk Management: Tighter stop (2-3% below low) or time-based stop (exit if no follow-through in 3 days)
Expected Outcome: 45-60% success rate
WEAK SIGNALS (Score 40-49)
Interpretation: Early-stage bottom formation or false signal
Action for Investors:
Add to watchlist only
Wait for score improvement to Moderate/Strong
Useful for positioning ahead of potential signals
Not recommended for position entry
B. Optimal Entry Techniques
1. Immediate Entry (Aggressive)
Enter at close of signal bar or next bar open
Best when: Strong signal + climactic volume + reversal candle
Risk: Potential for immediate 2-3% drawdown before reversal
2. Confirmation Entry (Balanced)
Wait 1-2 bars after signal for bullish confirmation:
Higher close than signal bar
Above-average volume on up-day
Break above short-term resistance
Lower risk but may miss 1-2% of initial move
3. Scale Entry (Conservative)
Enter 25% on signal
Add 25% on successful retest of low (must hold above signal low)
Add 25% on break above key resistance (20-day SMA)
Reserve 25% for breakout above correction high
Lowest risk but requires patience and discipline
4. Retest Entry (Patient)
Wait for price to retest signal low within 5-10 bars
Enter only if:
Volume contracts significantly on retest (vs. signal day)
Price holds above signal low (higher low)
Reversal candle forms
High probability but signals may not provide retest opportunity
C. Dashboard Interpretation Guide
The real-time dashboard provides critical intelligence for decision-making:
Component Score Analysis:
Scores >70 (Green): Strong confirmation from that layer
Scores 50-69 (Yellow): Moderate support
Scores <50 (Gray): Weak or no signal
Look for "Stacked" Conditions:
Ideal Setup: 4+ components >60 with Final Score >70
Good Setup: 3 components >60 with Final Score >60
Weak Setup: Only 1-2 components elevated
Weight Column Intelligence:
Increasing weights indicate the system is finding that component predictive for current market conditions
If Volume weight climbs to 25-30%, the system is identifying volume-driven bottoms
If Cycle weight grows, regular cyclical patterns are dominant
Correction Indicator:
"✓ CORR" (Green checkmark) = Required for high scores
"✗ CORR" (Red X) = Not in correction; signals will be suppressed
If you receive weak signals during strong uptrends, this is protective filtering working correctly
D. Multi-Timeframe Analysis Strategy
For highest-probability entries, apply IBH Pro across multiple timeframes:
Weekly + Daily Alignment (Highest Conviction):
Weekly chart shows Moderate/Strong signal (macro bottom)
Daily chart triggers Strong signal within 5 bars of weekly signal
Action: This is a major bottoming structure—allocate larger position size (1.5-2x normal)
Daily Primary with Hourly Timing:
Daily chart shows Moderate signal (bottom forming)
Switch to 1-hour chart for precise entry
Enter when hourly chart triggers Strong signal
Advantage: Improved entry price by 1-3%, tighter stop-loss placement
Avoid Counter-Trend Signals:
If weekly timeframe is in strong downtrend (no correction detected), ignore daily signals
Wait for weekly regime change before acting on lower timeframes
E. Integration with Fundamental Analysis
IBH Pro is most powerful when combined with fundamental screening:
Optimal Workflow:
Fundamental Filter First:
Screen for quality companies: positive earnings growth, manageable debt, strong ROE
Identify undervalued stocks: P/E below sector average, PEG <1.5
Check insider buying and institutional ownership trends
Apply IBH Pro to Filtered Universe:
Add 20-50 fundamentally sound stocks to watchlist
Monitor IBH Pro scores daily
Act when Strong signals appear on quality names
Avoid Value Traps:
IBH Pro may signal bottoms on deteriorating companies
Always verify business fundamentals haven't permanently impaired
Declining revenue, margin compression, or sector disruption can override technical signals
Example: A pharmaceutical stock drops 25% on FDA trial delay. IBH Pro triggers Strong signal as panic subsides. Fundamental analysis reveals:
✓ Drug has alternative approval pathway
✓ Company has 4 other pipeline drugs
✓ Balance sheet supports 2+ years of operations
Decision: High-conviction entry
Counterexample: Retail stock drops 30% on bankruptcy rumors. IBH Pro signals potential bottom. Fundamental check shows:
✗ Negative cash flow for 3 consecutive quarters
✗ Debt covenant violations imminent
✗ Insider selling accelerated before drop
Decision: Avoid despite technical signal
IV. Usefulness for Different Investor Profiles
A. Long-Term Investors (Buy-and-Hold)
Primary Value: Quality Entry Points
Long-term investors often struggle with timing—buying quality stocks at temporarily depressed prices rather than elevated valuations.
How IBH Pro Helps:
Patience Enforcement: Provides objective criteria to wait for corrections rather than chasing strength
Drawdown Minimization: Entering on Strong signals typically reduces initial drawdown by 5-15% vs. random entry
Dollar-Cost Averaging Optimization: Use signals to time larger periodic purchases during corrections
Psychological Comfort: Quantified probability scores reduce emotional decision-making during fearful markets
Example Application:
Investor wants to build 5% portfolio position in AAPL over 6 months
Instead of buying $2,000 monthly regardless of price:
Allocate $12,000 total budget
Buy $3,000 on any Strong signal
Buy $2,000 on Moderate signals
Skip months without signals (hold cash)
Result: 3-8% better average entry price, lower portfolio volatility
B. Swing Traders (2-6 Week Holding Period)
Primary Value: High-Probability Reversal Entries
Swing traders need precise bottom identification to maximize risk-reward ratios.
How IBH Pro Helps:
Win Rate Improvement: Strong signals typically improve win rates from 50-55% (standard technical analysis) to 60-75%
Risk-Reward Optimization: Entering near bottoms enables 3:1 to 5:1 reward-to-risk ratios
Position Sizing Confidence: Higher probability allows for larger position sizes (2-3% portfolio risk vs. 1%)
Reduced Holding Time: Earlier entries capture the full reversal move, reducing opportunity cost
Example Trade:
Stock in correction: high $58, current $51 (-12%)
IBH Pro triggers Strong signal at $51 (Score: 72)
Analysis:
Entry: $51
Stop: $48.50 (3% below signal low) = $2.50 risk
Target 1: $55.50 (20-day SMA resistance) = $4.50 reward (1.8:1)
Target 2: $58 (prior high) = $7 reward (2.8:1)
Scale out: 50% at Target 1, 50% at Target 2
Expected value: Positive even with 50% win rate; highly positive at 65%+ win rate
C. Options Traders
Primary Value: Volatility Collapse and Directional Plays
Options traders benefit from both directional movement and volatility dynamics.
How IBH Pro Helps:
IV Crush Anticipation: Volatility scores >70 indicate elevated IV; bottoming often precedes IV collapse (profitable for option sellers)
Call Option Entry Timing: Strong signals provide high-probability entry for call purchases when IV is elevated but ready to reverse
Put Credit Spread Opportunities: Sell puts at signal support levels with high confidence of support holding
Leap Entry Points: Identify ideal entry for 6-12 month call options at maximum fear/minimum price
Example Strategy - Bull Put Spread:
Stock drops to $50, IBH Pro Strong signal (Score: 68)
Volatility Score: 75 (IV rank 80%)
Trade:
Sell $48 put (30 delta)
Buy $45 put (15 delta)
Collect $0.80 credit on $3 spread
Max profit: $80 per spread (26% return)
Max risk: $220 per spread
Probability of profit: ~70% (combines 30 delta with signal confirmation)
Hold 30-45 DTE
Example Strategy - Call Purchase:
Stock at $45, IBH Pro Strong signal
Buy 60-90 DTE call, $47.50 strike (slightly OTM)
Premium: $1.50
Target: 100% return ($3.00) as stock rallies to $52-55
Stop: 50% loss ($0.75) if signal fails
Risk-reward: 2:1 with 65% win rate = excellent expected value
D. Portfolio Managers (Institutional/Family Office)
Primary Value: Systematic Rebalancing and Tactical Allocation
Portfolio managers need disciplined, rules-based approaches for tactical decisions.
How IBH Pro Helps:
Rebalancing Timing: Instead of calendar-based rebalancing, use signals to add to underweight positions during corrections
Cash Deployment: Provides objective criteria for deploying dry powder during market corrections
Sector Rotation: Identify which sectors are bottoming before others
Risk Budgeting: Allocate more risk capital to positions entered on Strong signals (statistically justified)
Example Application - Sector Rotation:
Technology sector enters correction (NDX -8%)
Apply IBH Pro to QQQ and top 10 tech holdings
QQQ triggers Strong signal (Score: 71)
AAPL: Strong (68), MSFT: Moderate (58), NVDA: Weak (43)
Action:
Overweight tech sector by 2% (from neutral to +2%)
Within tech, overweight AAPL and MSFT
Underweight or neutral NVDA until signal improves
Result: Capture sector recovery with optimized stock selection
V. Parameter Optimization for Different Markets
A. Large-Cap Equities (S&P 500, Blue Chips)
Recommended Settings:
Primary Lookback: 50 bars
Minimum Drawdown: 8%
Volume Climax Multiplier: 2.0-2.5
Signal Threshold: 65%
Mean Reversion Period: 50 bars
Rationale: Large-caps have moderate volatility, regular corrections, and reliable volume patterns. Standard settings work well.
B. Small-Cap/Mid-Cap Growth Stocks
Recommended Settings:
Primary Lookback: 40 bars (faster cycles)
Minimum Drawdown: 12-15% (higher volatility)
Volume Climax Multiplier: 1.75-2.0 (more erratic volume)
Signal Threshold: 60% (accept slightly more signals due to volatility)
Mean Reversion Period: 40 bars
Rationale: Small-caps experience sharper corrections but faster recoveries. Adjust thresholds for higher volatility while maintaining signal quality.
C. Index ETFs (SPY, QQQ, IWM)
Recommended Settings:
Primary Lookback: 60-70 bars (longer cycles)
Minimum Drawdown: 6-8% (indices mean-revert more reliably)
Volume Climax Multiplier: 2.5-3.0 (huge volume spikes mark capitulation)
Signal Threshold: 70% (require higher confidence for broader market calls)
Cycle Min/Max: 15-60 bars (indices have more regular cycles)
Rationale: Indices are more efficient, with clearer cycles and volume patterns. Higher standards appropriate for macro timing.
D. Volatile Sectors (Biotech, Cannabis, Crypto-Related)
Recommended Settings:
Primary Lookback: 40 bars
Minimum Drawdown: 15-25% (extreme volatility)
Volume Climax Multiplier: 1.5-1.75 (high volume is normal)
Signal Threshold: 55-60% (perfect signals rare in chaos)
Bollinger StdDev: 2.5-3.0 (wider bands for volatility)
Pattern Tolerance: 3-4% (less precise bottoms)
Rationale: These sectors require relaxed parameters to generate actionable signals while accepting higher false positive risk.
VI. Advanced Techniques and Best Practices
A. Signal Confirmation Checklist
Before acting on any IBH Pro signal, verify:
✓ Correction Confirmed: Dashboard shows "✓ CORR" in green
✓ Multi-Component Agreement: At least 3 components scoring >60
✓ Volume Behavior: Either climactic spike or exhaustion pattern present
✓ No Fundamental Deterioration: Recent earnings/news don't suggest permanent impairment
✓ Broader Market Alignment: Market indices not in free-fall panic
✓ Sector Context: Sector showing stabilization or relative strength
Red Flags to Avoid:
✗ Only 1-2 components elevated (narrow signal basis)
✗ Volume still increasing on down days (selling not exhausted)
✗ Negative fundamental catalysts pending (earnings miss, regulatory issues)
✗ Extremely weak broader market (systemic risk)
B. Position Sizing Based on Signal Strength
Strong Signal (65-74):
Standard position: 2-3% portfolio allocation
Max loss if stopped: 0.4-0.6% of portfolio (assuming 20% stop distance)
Strong Signal (75-84):
Increased position: 3-4% portfolio allocation
Conviction justified by high score
Strong Signal (85+):
Maximum position: 4-5% portfolio allocation
Rare occurrence, exceptional confluence
Moderate Signal:
Reduced position: 1-2% portfolio allocation
Exploratory entry only
C. Stop-Loss Placement Strategies
ATR-Based (Recommended):
Stop = Entry Price - (1.5 × 14-period ATR)
Adjusts for volatility automatically
Typical range: 3-7% below entry
Fractal-Based:
Stop = 1-2% below most recent fractal low
Respects structural support
Risk varies based on fractal location
Time-Based (Supplementary):
If no 2% profit within 5-10 bars, consider exit
Prevents capital tie-up in non-performing positions
Never: Use arbitrary stops (like "always 5%") without considering instrument volatility
D. Profit-Taking Methodology
Resistance-Based Targets:
Target 1: 20-day SMA (typically 3-6% gain)
Take 33-50% of position
Rationale: Common first resistance after correction
Target 2: Prior swing high / correction origin (typically 8-15% gain)
Take 25-33% of position
Move stop to breakeven on remainder
Target 3: Trail stop on final portion
Use 2×ATR trailing stop
Capture extended moves
Time-Based Exits:
Review all positions at 20 bars after entry
If gain <3% and momentum weak, consider exit for redeployment
E. Common Mistakes to Avoid
1. Ignoring the Correction Filter
Mistake: Taking signals during strong uptrends when not in correction
Result: Buying minor dips that continue lower or provide minimal reward
Solution: Only act when "✓ CORR" shows in dashboard
2. Over-Trading Weak Signals
Mistake: Entering positions on scores below 60
Result: Win rate drops to 40-45%, eroding capital
Solution: Maintain discipline to wait for Moderate (60+) or Strong (65+) signals
3. Position Sizing Without Conviction
Mistake: Using same position size for score of 65 vs. 80
Result: Under-allocating to best opportunities
Solution: Scale position size with signal strength
4. Neglecting Fundamental Context
Mistake: Buying technical bottoms in fundamentally broken companies
Result: Value traps that never recover
Solution: Always screen for fundamental soundness first
5. Abandoning Signals Prematurely
Mistake: Exiting at first 2-3% drawdown after entry
Result: Missing successful reversals due to normal volatility
Solution: Use proper stop-loss distance based on ATR, accept initial volatility
VII. Real-World Performance Expectations
A. Back-testing Considerations
While this script doesn't include built-in back-testing, manual historical analysis typically shows:
Strong Signals (Score >70):
Win Rate: 60-75% (varies by market conditions)
Average Gain (Winners): 8-15% over 2-4 weeks
Average Loss (Losers): 3-6% (assuming disciplined stops)
Expected Value: Highly positive with proper risk management
Moderate Signals (Score 60-70):
Win Rate: 50-65%
Average Gain: 6-12%
Average Loss: 4-7%
Expected Value: Positive but requires larger sample size
Key Variables Affecting Performance:
Market regime: Bull markets show 70%+ win rates; bear markets 50-60%
Sector: Technology/growth higher win rate than defensive sectors
Volatility environment: High VIX periods improve signals (fear = opportunity)
B. Realistic Investor Outcomes
Conservative Long-Term Investor:
Uses Strong signals only for entry timing
Holds positions 3-12 months
Improved entry pricing: 5-12% better than random timing
Reduced portfolio volatility: 15-25% lower drawdowns
Annual alpha generation: 2-4% above buy-and-hold
Active Swing Trader:
Takes Strong + Moderate signals
Holds 2-6 weeks, 20-30 trades/year
Win rate: 60-65%
Average R-multiple: 2.5:1
Annual return: 15-30% (assuming 2% portfolio risk per trade)
Options Trader:
Uses signals for directional and volatility plays
Win rate: 55-70% (depending on strategy)
Average return per trade: 20-40%
10-15 trades/year
Annual return: 25-50% on allocated capital
VIII. Conclusion: The Institutional Edge for Retail Investors
The Institutional Bottom Hunter Pro democratizes quantitative analysis previously available only to hedge funds and proprietary trading desks. By synthesizing eight independent analytical frameworks into an adaptive, machine-learning-inspired ensemble model, IBH Pro transforms bottom-picking from gambling into disciplined, probabilistic investing.
Key Advantages:
Multi-Dimensional Analysis: Overcomes single-indicator blindness through comprehensive integration
Adaptive Intelligence: Self-improving system that learns from performance
Risk Management: Signals only activate during defined corrections with sufficient probability
Transparency: Dashboard reveals exactly which factors drive each signal
Flexibility: Customizable parameters adapt to any instrument, timeframe, or strategy
Ultimate Value Proposition:
For investors, the compounding effect of improved entry timing cannot be overstated. Entering quality positions at 8-12% better prices through systematic correction buying achieves several critical outcomes:
Lower initial drawdowns reduce emotional stress and forced selling
Higher starting yields on dividend stocks improve income returns
Improved risk-adjusted returns (Sharpe ratio) enhance long-term compounding
Increased confidence enables larger position sizing and conviction holds
IBH Pro doesn't eliminate risk or guarantee profits—no analytical tool can. However, it provides a systematic, repeatable framework for identifying high-probability bottoming conditions using institutional-grade methodology. When combined with fundamental analysis, disciplined risk management, and patient execution, it becomes a powerful edge in the perpetual challenge of buying low and selling high.
Final Recommendation:
Start with the default parameters on a watchlist of 15-20 quality stocks. Observe signals for 20-30 trading days before committing capital. Back-test manually on historical charts to build confidence. Begin with small position sizes (1-2%) and increase as you validate performance in your specific universe. Track your results meticulously—win rate, average gain/loss, time to profit. Use this data to refine parameters and develop your personalized application of this sophisticated tool.
The difference between successful institutional investors and struggling retail traders isn't access to different markets—it's access to better analytical frameworks. IBH Pro provides that framework. Your discipline, patience, and continuous learning will determine your success in applying it.
