Smart Signals [Vdubus]Smart Signals
Concept & Philosophy
Smart Signals is a "Regime-Filtered" oscillator designed to solve the biggest problem with standard indicators: Counter-trend noise.
Most oscillators (like Stochastic or RSI) are "dumb" to market context—they will signal "Sell" continuously during a strong uptrend simply because the price is high. Smart Signals fixes this by first determining the Market Regime (Bullish or Bearish) and then strictly filtering out any signal that contradicts that trend.
It creates a "Tiered" trading system that separates standard trend-following entries from high-probability "Sniper" entries (Hidden Divergence), all presented in a clean, color-blind-friendly visual interface.
Core Functions
1. The "Sheriff" (Trend Filter)
At the heart of the indicator is a heavy, modified Hull Moving Average (HMA 200) that acts as the trend baseline.
Bullish Regime: When the baseline is sloping UP, the indicator enters "Buy Only" mode. All Sell signals are mathematically deleted.
Bearish Regime: When the baseline is sloping DOWN, the indicator enters "Sell Only" mode. All Buy signals are mathematically deleted.
The Math: It uses a custom difference-weighted formula (wmaHalf = Length / 1) to create a stable, chop-resistant trend anchor.
2. Dual-Signal Engine
The indicator scans for two distinct types of entries simultaneously:
♦ Standard Signals (Blue/Red Diamonds):
Logic: A classic Stochastic pullback (Cross 20/80) aligned with the trend.
Use Case: These are frequent "Bread and Butter" trend entries. They are excellent for scaling into a position or adding to a winner as the trend continues.
Location: Plotted at the top (Sell) and bottom (Buy) edges of the panel.
+ Sniper Signals (Gold Crosses):
Logic: Hidden Divergence. The script detects when Price holds structure (Higher Low) while Momentum resets (Lower Low). This is a "Slingshot" setup.
Use Case: These are rare, high-conviction entries. They often mark the end of a complex correction and the resumption of the main trend.
Location: Plotted on the Zero Line to indicate structural strength.
3. Smart Momentum Histogram
The histogram visualizes the "Energy" of the move (MACD 21, 34, 7), but with a twist. It is color-coded to the signal priority:
Gold Bars: A Sniper (Divergence) setup is active.
Solid Blue/Red Bars: A Standard Signal is active.
Faded Blue/Red Bars: The trend is active, but momentum is resetting (waiting mode).
Gray Bars: Counter-trend noise (Ignore).
How to Trade It
Check the "Road": Look at the general color of the histogram columns.
Blue Columns: Look for Longs.
Red Columns: Look for Shorts.
The "Sniper" Entry: Wait for a Gold Cross (+) on the zero line. This is your primary signal to enter a trade with normal risk.
The "Pyramid" Entry: If the trend continues and you see Blue/Red Diamonds (♦) appear at the edges, these are safe places to add to your position.
The Exit: Since this is a trend-following tool, exit when the histogram color flips (e.g., from Blue to Red/Gray), or use your own support/resistance targets.
Alerts Configuration
The indicator comes with a full suite of alerts for automation:
Gold Buy / Gold Sell: Notifies you only for the high-probability Hidden Divergence setups.
Standard Buy / Standard Sell: Notifies you for every trend pullback.
ANY BUY / ANY SELL: A combo alert that triggers on either signal type (useful for simplifying your alert limits).
Accessibility
Color Blind Friendly: The default palette uses High-Contrast Blue (#2962FF) and Soft Red (#FF5252) instead of standard Green/Red, ensuring visibility for all users.
Zero Clutter: No text labels or confusing lines. Just clear, distinct shapes (Diamonds and Crosses) at fixed locations.
Stochasticoscillator
ChromaFlows Momentum Index - Consensus Engine V1.2ChromaFlows Momentum Index — Conceptual Description
Overview
ChromaFlows Momentum Index is a momentum-analysis tool designed to evaluate trend quality and directional agreement by combining multiple oscillators into a single consensus-based system.
Rather than displaying independent signals from separate indicators, this script produces output only when all internal engines align, filtering out conflicting or low-quality momentum conditions.
The goal is not to generate standalone trading signals, but to provide a clear visual representation of momentum consensus and regime strength.
Conceptual Architecture
The indicator is built around three momentum engines, each assigned a distinct functional role:
Slow Stochastic — acts as the primary momentum baseline, defining the broader overbought/oversold context.
Fast Stochastic — functions as a short-term acceleration filter, detecting rapid changes in momentum relative to the baseline.
RSI — serves as a regime validator, confirming whether momentum conditions are stable enough to be considered directional.
These components are not averaged or displayed independently.
Each engine is conditionally dependent on the others.
Interaction & Consensus Logic
ChromaFlows uses a strict consensus model:
A directional state is produced only when all momentum engines agree on direction.
If even one engine diverges, the system suppresses directional output and enters a neutral state.
This logic prevents partial or conflicting momentum signals from being displayed and reduces noise commonly produced by single-indicator oscillators.
The resulting output represents agreement quality, not raw oscillator values.
Visual Output & Interpretation
The main oscillator wave represents the current momentum state derived from the consensus logic:
Bullish Consensus — all engines aligned to the upside
Bearish Consensus — all engines aligned to the downside
Neutral State — disagreement or low-quality momentum
Additional visual elements (signal markers and trend filters) are derived from the same internal state, providing contextual confirmation rather than independent signals.
These visuals are intended to help users interpret momentum context, not to automate execution.
Originality & Purpose
This script is not a visual mashup of existing indicators.
Its output cannot be replicated by observing the individual components separately, as the system’s behavior depends on conditional interaction and suppression logic between engines.
By requiring full agreement before displaying momentum states, ChromaFlows emphasizes momentum clarity over signal frequency, making it suitable as a contextual analysis layer within broader trading frameworks.
Usage Notes
ChromaFlows Momentum Index is a visual analysis tool designed to assist with market interpretation.
It does not provide investment advice or guarantee outcomes and should be used in conjunction with other forms of analysis and risk management.
Version Notes (V1.2)
• Expanded divergence detection logic added for SMI line for improved momentum context
• Minor internal optimizations and code refinements
Stochastic MAs+ (K Logit Bands)Below is a ready-to-paste **English TradingView publish description** that is detailed enough to satisfy the “Originality & usefulness” and “Description” house-rule expectations. It explains **what is original**, **why the components are combined**, **how they work together**, and **how to use it**, including practical presets and cautions.
---
## Title
**Stochastic MAs+ (K Logit Bands) — Extreme-Zone Reversion with Adaptive Percentile Bands**
## Overview
This script is a **Stochastic-based extreme-zone tool** designed for traders who want signals that occur **near statistically-defined extremes**, while reducing noise and overtrading.
It combines three ideas into one coherent workflow:
1. **Stochastic %K/%D with selectable smoothing MAs** (EMA/ZEMA/SMA/KAMA)
2. **Adaptive Logit Percentile Bands** computed **on %K** (not price) to define “extreme” zones dynamically
3. A **two-step signal workflow** (Touch → Re-entry → First K/D Cross) with **cooldown + invalidation rules** to suppress repeated signals in choppy markets
This is not a “mashup for convenience.” The logit-percentile bands and the signal state-machine are explicitly built to **solve a common Stochastic problem**: fixed 20/80 levels are often too generic, and raw K/D crosses can fire repeatedly in ranges. The components here work together to make Stochastic extremes more **context-aware** and signals more **selective**.
---
## What makes it original / useful
### 1) Dynamic extremes based on the oscillator’s own distribution
Instead of using fixed 20/80, the script builds **percentile-based bands on transformed %K values**:
* **Logit transform** is used to expand sensitivity near 0 and 100 (where Stochastic tends to compress).
* A rolling buffer stores recent transformed values.
* **Percentiles** (e.g., 15% / 85%) define adaptive low/high bands that respond to changing volatility regimes.
Result: “Extreme” zones are **relative to recent market behavior**, which is often more practical than static thresholds.
### 2) A structured signal process to reduce overtrading
Classic Stochastic crossovers can spam signals. This script uses a **state-based trigger**:
**Long logic**
1. %K drops below the **adaptive low band** (touch/arm)
2. %K re-enters above the low band (re-entry)
3. The first bullish crossover occurs (K crosses above D) while K remains below the mid-band
**Short logic** is symmetrical.
Then it adds:
* **Cooldown**: prevents clustered entries during noisy periods
* **Max wait**: invalidates old setups if confirmation takes too long
* **Mid-band invalidation**: if K moves too far (crosses mid), the setup is considered late and discarded
This turns Stochastic into a **controlled mean-reversion trigger** rather than an always-on crossover machine.
---
## How it works (plain-language)
### A) Stochastic with selectable smoothing (MAK/MAD)
* `%K` is computed from the standard Stochastic formula, then smoothed with your chosen MA.
* `%D` is computed by smoothing `%K` with a chosen MA.
**MA options**
* **EMA**: baseline responsive smoothing
* **ZEMA**: reduced lag (faster reactions)
* **SMA**: heavier smoothing (less noise)
* **KAMA**: adaptive smoothing (reacts faster when price moves, slower in noise)
### B) K-based Logit Percentile Bands
The script builds bands from **%K**, not from price:
* Convert K into logit space → store in rolling buffer
* Compute low/high percentiles in logit space
* Convert back to 0–100 space with logistic function
* Produce: **kLo / kHi / kMid**
This keeps the bands stable and meaningful even when volatility changes.
### C) Signal state-machine
* **Touch**: K enters extreme zone
* **Re-entry**: K exits the extreme zone
* **Trigger**: first K/D cross after re-entry, while still in the “early” half of the band (before mid)
The idea is to catch reversals **early**, but not on the very first noisy bounce.
---
## How to use
### 1) Baseline setup (recommended starting point)
These defaults are already aligned with the script’s intent:
* Stoch: **21 / 3 / 7**
* Bands: **bandLen 200**, **low/high 0.15/0.85**, **logitGain 1.0**
* Signals: **cooldown 8**, **maxWait 24**, **Use D Direction Confirm ON**
This typically produces fewer, more selective signals than traditional 14/3/3 style settings.
### 2) Interpreting the plots
* **%K (purple)** and **%D (yellow)** are the smoothed oscillator lines.
* **kLo / kHi / kMid** are the adaptive bands.
* Labels:
* **“L”** appears near the low band when a long setup completes
* **“S”** appears near the high band when a short setup completes
### 3) Practical trading workflow
* Prefer using signals as **timing cues**, not as a complete strategy by themselves.
* Many traders combine this with:
* a trend filter (e.g., EMA200 direction)
* a volatility filter (avoid low-vol chop)
* or higher timeframe confirmation
The script is designed to give **high-quality entry timing near extremes**, but you still need a trade plan for exits and risk management.
---
## Tuning guide (fast)
### Want signals closer to extremes (more selective)?
* Decrease / increase percentiles:
* lowPct **0.12** and highPct **0.88**
* Increase logitGain slightly:
* logitGain **1.1–1.2**
* Increase cooldown:
* cooldown **10–14**
### Want earlier signals (faster confirmations)?
* Use faster MA for %D (or reduce periodD):
* maD = **ZEMA** (or EMA)
* Reduce cooldown a bit:
* cooldown **5–8**
### Getting too many signals in ranges?
* Increase periodK to reduce chop:
* periodK **34**
* Increase cooldown
* Keep D confirm enabled
---
## Strengths
* **Adaptive extreme zones**: bands adjust to changing regimes (better context than static 20/80)
* **Reduced noise**: the Touch→Re-entry→Cross structure avoids many “random” crosses
* **Configurable smoothing**: lets you tune response vs stability via MA type
* **Risk-friendly by design**: cooldown + invalidation reduce repeated entries during chop
## Limitations
* **Not a full strategy**: no position management, take-profit/stop rules, or trend filter included
* **Mean-reversion bias**: in strong trends, Stochastic can stay overbought/oversold for long periods
* **Band buffer needs history**: percentile bands are more reliable after enough bars have accumulated (bandLen)
---
## Notes on repainting / confirmations
* The percentile band buffer uses **confirmed bars** (optional) to avoid unstable band updates during an incomplete candle.
* Signal labels are plotted when the full signal conditions are met (you can enforce confirmed-bar signals via settings).
---
## Suggested disclaimer (TradingView-friendly)
This indicator is for research and educational purposes and does not constitute financial advice. Always test settings on your market/timeframe and use proper risk management.
4x Stochastic Combo - %K only4x Stochastic Combo in one indicator.
Default parameters: (9, 3, 3), (14, 3, 3), (40, 4, 4), (60, 10, 10)
Only %K is shown.
Possibility to set alerts "all above 80" or "all below 20".
How to use:
Look for divergence after getting an alert for good quality signals. Connect the stochastic signals with multi-timeframe analysis.
Stochastic BTC OptimizedEnhanced Stochastic for Bitcoin (BTC) – Optimized for Daily Timeframe
This enhanced Stochastic oscillator is specifically fine-tuned for BTC/USD on the 1D timeframe, leveraging historical data from Bitstamp (2011–2025) to minimize false signals and maximize reliability in Bitcoin's volatile swings.
Unlike the classic Stochastic (14, 3, 3), this version uses optimized parameters:
- K Period = 21 – smoother reaction, better suited for BTC’s macro cycles
- D Period = 3, Smooth K = 3 – reduces noise while preserving responsiveness
- Overbought = 85, Oversold = 15 – accounts for BTC’s tendency to trend strongly within extreme zones without immediate reversal
✅ Smart Signal Logic:
Buy/sell signals appear only when %K crosses %D inside the oversold (≤15) or overbought (≥85) zones, and only the first signal is shown to avoid whipsaws.
Visual Enhancements:
- Thick lines when %K/%D are in overbought/oversold zones
- Green/red background highlights on valid signals
- Optional up/down arrows for clear entry visualization
- Customizable colors, line widths, and transparency
🔒 No alerts included – clean, focused on price action and momentum.
💡 Pro Tip: For even higher accuracy, use this indicator in combination with a long-term trend filter (e.g., EMA 200). The oscillator excels in ranging or retracement phases but should not be used alone in strong parabolic moves.
Based on Mozilla Public License v2.0 – feel free to use, modify, and share. Perfect for swing traders and long-term Bitcoin analysts seeking high-probability reversal zones.
перевод на русский
Улучшенный Stochastic для Bitcoin (BTC) — оптимизирован для дневного таймфрейма
Этот улучшенный осциллятор Stochastic специально настроен под BTC/USD на дневном графике, с учётом исторических данных Bitstamp (2011–2025), чтобы минимизировать ложные сигналы и повысить надёжность в условиях высокой волатильности биткоина.
В отличие от классического Stochastic (14, 3, 3), эта версия использует оптимизированные параметры:
- Период K = 21 — более плавная реакция, лучше соответствует макроциклам BTC
- Период D = 3, Сглаживание K = 3 — снижает шум, сохраняя отзывчивость
- Уровень перекупленности = 85, перепроданности = 15 — учитывает склонность BTC к сильным трендам в экстремальных зонах без немедленного разворота
✅ Интеллектуальная логика сигналов:
Покупка/продажа отображается только при пересечении %K и %D внутри зоны перепроданности (≤15) или перекупленности (≥85), и только первый сигнал фиксируется, чтобы избежать «хлыстов».
Улучшенная визуализация:
- Жирные линии, когда %K/%D находятся в экстремальных зонах
- Зелёный/красный фон при появлении сигналов
- Опциональные стрелки для чёткого отображения точек входа
- Настройка цветов, толщины линий и прозрачности
🔒 Без алертов — чистый инструмент, сфокусированный на цене и импульсе.
💡 Совет профессионала: для ещё большей точности используйте этот индикатор вместе с трендовым фильтром (например, EMA 200). Осциллятор лучше всего работает в фазах консолидации или отката, но не стоит применять его в одиночку во время сильных параболических движений.
На основе Mozilla Public License v2.0 — свободно используйте, модифицируйте и делитесь. Идеален для свинг-трейдеров и аналитиков Bitcoin, ищущих зоны с высокой вероятностью разворота.
EQT Stochastic RibbonEQT Stochastic Ribbon is a modified Stochastic Oscillator with ribbon fill visualization.
Features:
- Dynamic color ribbon that changes based on trend direction (Blue for bullish, White for bearish)
- Crossover signals with triangle markers when %K crosses %D
- Customizable colors and signal offset
- Dashed lines at 80/20 levels for overbought/oversold zones
How to use:
- Blue ribbon = Bullish momentum (%K above %D)
- White ribbon = Bearish momentum (%K below %D)
- Triangle up = Buy signal (K crosses above D)
- Triangle down = Sell signal (K crosses below D)
Settings:
- K, D, Smooth - Standard Stochastic parameters
- Signal Offset - Distance of signal arrows from the line
- Bullish/Bearish Colors - Customize ribbon and signal colors
Stoch PRO + Dynamic EMA (EMA cross)Stoch PRO + Dynamic EMA Documentation
Overview:
- Pine Script v6 overlay indicator combining a trend-colored EMA with a Stochastic oscillator to highlight midline momentum shifts.
- Designed for TradingView charts (Indicators → Import) as a visual aid for timing entries within trend-following setups.
- Crafted and optimized around BTCUSDT on the 4h timeframe; adapt inputs before applying to other markets or intervals.
Inputs:
- EMA Length (default 50): smoothing window for the dynamic EMA; lower values respond faster but whipsaw more.
- Stochastic K Length (20): lookback for the raw %K calculation.
- Stochastic K Smoothing (3): SMA applied to %K to reduce noise.
- Stochastic D Smoothing (3): SMA over %K to produce the companion %D line.
Visual Elements:
- EMA plotted on price with linewidth 3; teal when close > EMA, fuchsia otherwise.
- Background tinted teal/fuchsia at high transparency (≈92) to reinforce the current trend bias without obscuring price bars.
Oscillator Logic:
- %K = ta.stoch(high, low, close, kLength); smoothed with ta.sma(kRaw, kSmooth).
- %D = ta.sma(k, dSmooth).
- Focus is on the midline (50) rather than traditional 20/80 extremes to emphasize rapid momentum flips.
Signals:
- Buy: %K crossing above 50 while close > EMA (teal state). Plots tiny teal circle below the bar.
- Sell: %K crossing below 50 while close < EMA (fuchsia state). Plots tiny purple circle above the bar.
Trading Workflow Tips:
- Use EMA/background color for directional bias, then confirm with %K 50-cross to refine entries.
- Consider higher-timeframe trend filters or price-action confirmation to avoid range chop.
- Stops often sit just beyond the EMA; adjust thresholds (e.g., 55/45) if too many false positives occur.
- Always plan risk/reward upfront—define TP/SL levels that fit your strategy and backtest them thoroughly before trading live.
Alerts & Extensions:
- Wrap crossUp/crossDown in alertcondition() if TradingView alerts are needed.
- For automation/backtesting, convert logic to a strategy() script or add position management rules.
Composite Stochastic Oscillator (CSO) [SharpStrat]Composite Stochastic Oscillator (CSO)
The Composite Stochastic Oscillator (CSO) is a refined momentum tool designed to improve on the limitations of the traditional stochastic indicator. Standard stochastics are often too sensitive, producing choppy signals and frequent false turns. CSO tackles this problem by combining multiple stochastic calculations, each with different lengths and smoothing settings, into a single, balanced output.
The goal of combining these stochastic variants is to create a more stable and reliable reading of market momentum. Each version of the stochastic captures different aspects of price behavior like shorter ones react faster, while longer ones filter noise. CSO brings them together mathematically to form a composite oscillator that reacts smoothly and consistently across varying market conditions. This makes it a useful improvement over the standard stochastic, providing traders with a more dependable signal while retaining the familiar interpretation framework.
How It Works
Calculates five independent stochastic oscillators with customizable K, D, and slowing parameters.
Each stochastic contributes to the final composite value according to its assigned weight, allowing the user to emphasize faster or slower reactions.
The resulting composite K is then smoothed into a D line using a chosen moving average method (SMA, EMA, WMA, or RMA).
The oscillator is plotted along with optional overbought/oversold levels and a color fill to enhance visual interpretation.
A compact on-chart table displays the current K and D readings for quick reference.
Comparison with normal Stochastic
Compared to a standard stochastic, the CSO generally produces smoother lines and fewer false flips. As evident in the comparison chart, this improves upon the normal stochastic by reducing noise and making signals more reliable, although results depend on parameter settings too.
How To Use It
Use the CSO exactly like a normal stochastic: look for crossovers, overbought/oversold zones, and divergences.
In practice, CSO should provides smoother and more consistent signals than the regular stochastic, especially in sideways or volatile markets.
When plotted beside a standard stochastic, you’ll notice CSO avoids many of the false reversals that clutter traditional readings.
Customization Options
Choice of smoothing method (SMA, EMA, WMA, RMA).
Full control over each stochastic component’s parameters and weights.
Adjustable overbought/oversold levels and display preferences.
Option to enable or disable the on-chart table and zone fills.
Note
This indicator is shared purely for educational and research purposes. It is not financial advice and should not be treated as a ready-made trading system.
I encourage you to experiment with different parameter values (periods, weights, smoothing) to explore how the behavior changes and to learn from the results.
Stochastic Enhanced [DCAUT]█ Stochastic Enhanced
📊 ORIGINALITY & INNOVATION
The Stochastic Enhanced indicator builds upon George Lane's classic momentum oscillator (developed in the late 1950s) by providing comprehensive smoothing algorithm flexibility. While traditional implementations limit users to Simple Moving Average (SMA) smoothing, this enhanced version offers 21 advanced smoothing algorithms, allowing traders to optimize the indicator's characteristics for different market conditions and trading styles.
Key Improvements:
Extended from single SMA smoothing to 21 professional-grade algorithms including adaptive filters (KAMA, FRAMA), zero-lag methods (ZLEMA, T3), and advanced digital filters (Kalman, Laguerre)
Maintains backward compatibility with traditional Stochastic calculations through SMA default setting
Unified smoothing algorithm applies to both %K and %D lines for consistent signal processing characteristics
Enhanced visual feedback with clear color distinction and background fill highlighting for intuitive signal recognition
Comprehensive alert system covering crossovers and zone entries for systematic trade management
Differentiation from Traditional Stochastic:
Traditional Stochastic indicators use fixed SMA smoothing, which introduces consistent lag regardless of market volatility. This enhanced version addresses the limitation by offering adaptive algorithms that adjust to market conditions (KAMA, FRAMA), reduce lag without sacrificing smoothness (ZLEMA, T3, HMA), or provide superior noise filtering (Kalman Filter, Laguerre filters). The flexibility helps traders balance responsiveness and stability according to their specific needs.
📐 MATHEMATICAL FOUNDATION
Core Stochastic Calculation:
The Stochastic Oscillator measures the position of the current close relative to the high-low range over a specified period:
Step 1: Raw %K Calculation
%K_raw = 100 × (Close - Lowest Low) / (Highest High - Lowest Low)
Where:
Close = Current closing price
Lowest Low = Lowest low over the %K Length period
Highest High = Highest high over the %K Length period
Result ranges from 0 (close at period low) to 100 (close at period high)
Step 2: Smoothed %K Calculation
%K = MA(%K_raw, K Smoothing Period, MA Type)
Where:
MA = Selected moving average algorithm (SMA, EMA, etc.)
K Smoothing = 1 for Fast Stochastic, 3+ for Slow Stochastic
Traditional Fast Stochastic uses %K_raw directly without smoothing
Step 3: Signal Line %D Calculation
%D = MA(%K, D Smoothing Period, MA Type)
Where:
%D acts as a signal line and moving average of %K
D Smoothing typically set to 3 periods in traditional implementations
Both %K and %D use the same MA algorithm for consistent behavior
Available Smoothing Algorithms (21 Options):
Standard Moving Averages:
SMA (Simple): Equal-weighted average, traditional default, consistent lag characteristics
EMA (Exponential): Recent price emphasis, faster response to changes, exponential decay weighting
RMA (Rolling/Wilder's): Smoothed average used in RSI, less reactive than EMA
WMA (Weighted): Linear weighting favoring recent data, moderate responsiveness
VWMA (Volume-Weighted): Incorporates volume data, reflects market participation intensity
Advanced Moving Averages:
HMA (Hull): Reduced lag with smoothness, uses weighted moving averages and square root period
ALMA (Arnaud Legoux): Gaussian distribution weighting, minimal lag with good noise reduction
LSMA (Least Squares): Linear regression based, fits trend line to data points
DEMA (Double Exponential): Reduced lag compared to EMA, uses double smoothing technique
TEMA (Triple Exponential): Further lag reduction, triple smoothing with lag compensation
ZLEMA (Zero-Lag Exponential): Lag elimination attempt using error correction, very responsive
TMA (Triangular): Double-smoothed SMA, very smooth but slower response
Adaptive & Intelligent Filters:
T3 (Tilson T3): Six-pass exponential smoothing with volume factor adjustment, excellent smoothness
FRAMA (Fractal Adaptive): Adapts to market fractal dimension, faster in trends, slower in ranges
KAMA (Kaufman Adaptive): Efficiency ratio based adaptation, responds to volatility changes
McGinley Dynamic: Self-adjusting mechanism following price more accurately, reduced whipsaws
Kalman Filter: Optimal estimation algorithm from aerospace engineering, dynamic noise filtering
Advanced Digital Filters:
Ultimate Smoother: Advanced digital filter design, superior noise rejection with minimal lag
Laguerre Filter: Time-domain filter with N-order implementation, adjustable lag characteristics
Laguerre Binomial Filter: 6-pole Laguerre filter, extremely smooth output for long-term analysis
Super Smoother: Butterworth filter implementation, removes high-frequency noise effectively
📊 COMPREHENSIVE SIGNAL ANALYSIS
Absolute Level Interpretation (%K Line):
%K Above 80: Overbought condition, price near period high, potential reversal or pullback zone, caution for new long entries
%K in 70-80 Range: Strong upward momentum, bullish trend confirmation, uptrend likely continuing
%K in 50-70 Range: Moderate bullish momentum, neutral to positive outlook, consolidation or mild uptrend
%K in 30-50 Range: Moderate bearish momentum, neutral to negative outlook, consolidation or mild downtrend
%K in 20-30 Range: Strong downward momentum, bearish trend confirmation, downtrend likely continuing
%K Below 20: Oversold condition, price near period low, potential bounce or reversal zone, caution for new short entries
Crossover Signal Analysis:
%K Crosses Above %D (Bullish Cross): Momentum shifting bullish, faster line overtakes slower signal, consider long entry especially in oversold zone, strongest when occurring below 20 level
%K Crosses Below %D (Bearish Cross): Momentum shifting bearish, faster line falls below slower signal, consider short entry especially in overbought zone, strongest when occurring above 80 level
Crossover in Midrange (40-60): Less reliable signals, often in choppy sideways markets, require additional confirmation from trend or volume analysis
Multiple Failed Crosses: Indicates ranging market or choppy conditions, reduce position sizes or avoid trading until clear directional move
Advanced Divergence Patterns (%K Line vs Price):
Bullish Divergence: Price makes lower low while %K makes higher low, indicates weakening bearish momentum, potential trend reversal upward, more reliable when %K in oversold zone
Bearish Divergence: Price makes higher high while %K makes lower high, indicates weakening bullish momentum, potential trend reversal downward, more reliable when %K in overbought zone
Hidden Bullish Divergence: Price makes higher low while %K makes lower low, indicates trend continuation in uptrend, bullish trend strength confirmation
Hidden Bearish Divergence: Price makes lower high while %K makes higher high, indicates trend continuation in downtrend, bearish trend strength confirmation
Momentum Strength Analysis (%K Line Slope):
Steep %K Slope: Rapid momentum change, strong directional conviction, potential for extended moves but also increased reversal risk
Gradual %K Slope: Steady momentum development, sustainable trends more likely, lower probability of sharp reversals
Flat or Horizontal %K: Momentum stalling, potential reversal or consolidation ahead, wait for directional break before committing
%K Oscillation Within Range: Indicates ranging market, sideways price action, better suited for range-trading strategies than trend following
🎯 STRATEGIC APPLICATIONS
Mean Reversion Strategy (Range-Bound Markets):
Identify ranging market conditions using price action or Bollinger Bands
Wait for Stochastic to reach extreme zones (above 80 for overbought, below 20 for oversold)
Enter counter-trend position when %K crosses %D in extreme zone (sell on bearish cross above 80, buy on bullish cross below 20)
Set profit targets near opposite extreme or midline (50 level)
Use tight stop-loss above recent swing high/low to protect against breakout scenarios
Exit when Stochastic reaches opposite extreme or %K crosses %D in opposite direction
Trend Following with Momentum Confirmation:
Identify primary trend direction using higher timeframe analysis or moving averages
Wait for Stochastic pullback to oversold zone (<20) in uptrend or overbought zone (>80) in downtrend
Enter in trend direction when %K crosses %D confirming momentum shift (bullish cross in uptrend, bearish cross in downtrend)
Use wider stops to accommodate normal trend volatility
Add to position on subsequent pullbacks showing similar Stochastic pattern
Exit when Stochastic shows opposite extreme with failed cross or bearish/bullish divergence
Divergence-Based Reversal Strategy:
Scan for divergence between price and Stochastic at swing highs/lows
Confirm divergence with at least two price pivots showing divergent Stochastic readings
Wait for %K to cross %D in direction of anticipated reversal as entry trigger
Enter position in divergence direction with stop beyond recent swing extreme
Target profit at key support/resistance levels or Fibonacci retracements
Scale out as Stochastic reaches opposite extreme zone
Multi-Timeframe Momentum Alignment:
Analyze Stochastic on higher timeframe (4H or Daily) for primary trend bias
Switch to lower timeframe (1H or 15M) for precise entry timing
Only take trades where lower timeframe Stochastic signal aligns with higher timeframe momentum direction
Higher timeframe Stochastic in bullish zone (>50) = only take long entries on lower timeframe
Higher timeframe Stochastic in bearish zone (<50) = only take short entries on lower timeframe
Exit when lower timeframe shows counter-signal or higher timeframe momentum reverses
Zone Transition Strategy:
Monitor Stochastic for transitions between zones (oversold to neutral, neutral to overbought, etc.)
Enter long when Stochastic crosses above 20 (exiting oversold), signaling momentum shift from bearish to neutral/bullish
Enter short when Stochastic crosses below 80 (exiting overbought), signaling momentum shift from bullish to neutral/bearish
Use zone midpoint (50) as dynamic support/resistance for position management
Trail stops as Stochastic advances through favorable zones
Exit when Stochastic fails to maintain momentum and reverses back into prior zone
📋 DETAILED PARAMETER CONFIGURATION
%K Length (Default: 14):
Lower Values (5-9): Highly sensitive to price changes, generates more frequent signals, increased false signals in choppy markets, suitable for very short-term trading and scalping
Standard Values (10-14): Balanced sensitivity and reliability, traditional default (14) widely used,适合 swing trading and intraday strategies
Higher Values (15-21): Reduced sensitivity, smoother oscillations, fewer but potentially more reliable signals, better for position trading and lower timeframe noise reduction
Very High Values (21+): Slow response, long-term momentum measurement, fewer trading signals, suitable for weekly or monthly analysis
%K Smoothing (Default: 3):
Value 1: Fast Stochastic, uses raw %K calculation without additional smoothing, most responsive to price changes, generates earliest signals with higher noise
Value 3: Slow Stochastic (default), traditional smoothing level, reduces false signals while maintaining good responsiveness, widely accepted standard
Values 5-7: Very slow response, extremely smooth oscillations, significantly reduced whipsaws but delayed entry/exit timing
Recommendation: Default value 3 suits most trading scenarios, active short-term traders may use 1, conservative long-term positions use 5+
%D Smoothing (Default: 3):
Lower Values (1-2): Signal line closely follows %K, frequent crossover signals, useful for active trading but requires strict filtering
Standard Value (3): Traditional setting providing balanced signal line behavior, optimal for most trading applications
Higher Values (4-7): Smoother signal line, fewer crossover signals, reduced whipsaws but slower confirmation, better for trend trading
Very High Values (8+): Signal line becomes slow-moving reference, crossovers rare and highly significant, suitable for long-term position changes only
Smoothing Type Algorithm Selection:
For Trending Markets:
ZLEMA, DEMA, TEMA: Reduced lag for faster trend entry, quick response to momentum shifts, suitable for strong directional moves
HMA, ALMA: Good balance of smoothness and responsiveness, effective for clean trend following without excessive noise
EMA: Classic choice for trending markets, faster than SMA while maintaining reasonable stability
For Ranging/Choppy Markets:
Kalman Filter, Super Smoother: Superior noise filtering, reduces false signals in sideways action, helps identify genuine reversal points
Laguerre Filters: Smooth oscillations with adjustable lag, excellent for mean reversion strategies in ranges
T3, TMA: Very smooth output, filters out market noise effectively, clearer extreme zone identification
For Adaptive Market Conditions:
KAMA: Automatically adjusts to market efficiency, fast in trends and slow in congestion, reduces whipsaws during transitions
FRAMA: Adapts to fractal market structure, responsive during directional moves, conservative during uncertainty
McGinley Dynamic: Self-adjusting smoothing, follows price naturally, minimizes lag in trending markets while filtering noise in ranges
For Conservative Long-Term Analysis:
SMA: Traditional choice, predictable behavior, widely understood characteristics
RMA (Wilder's): Smooth oscillations, reduced sensitivity to outliers, consistent behavior across market conditions
Laguerre Binomial Filter: Extremely smooth output, ideal for weekly/monthly timeframe analysis, eliminates short-term noise completely
Source Selection:
Close (Default): Standard choice using closing prices, most common and widely tested
HLC3 or OHLC4: Incorporates more price information, reduces impact of sudden spikes or gaps, smoother oscillator behavior
HL2: Midpoint of high-low range, emphasizes intrabar volatility, useful for markets with wide intraday ranges
Custom Source: Can use other indicators as input (e.g., Heikin Ashi close, smoothed price), creates derivative momentum indicators
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
Traditional SMA-Based Stochastic:
Fixed lag regardless of market conditions, consistent delay of approximately (K Smoothing + D Smoothing) / 2 periods
Equal treatment of trending and ranging markets, no adaptation to volatility changes
Predictable behavior but suboptimal in varying market regimes
Enhanced Version with Adaptive Algorithms:
KAMA and FRAMA reduce lag by up to 40-60% in strong trends compared to SMA while maintaining similar smoothness in ranges
ZLEMA and T3 provide near-zero lag characteristics for early entry signals with acceptable noise levels
Kalman Filter and Super Smoother offer superior noise rejection, reducing false signals in choppy conditions by estimations of 30-50% compared to SMA
Performance improvements vary by algorithm selection and market conditions
Signal Quality Improvements:
Adaptive algorithms help reduce whipsaw trades in ranging markets by adjusting sensitivity dynamically
Advanced filters (Kalman, Laguerre, Super Smoother) provide clearer extreme zone readings for mean reversion strategies
Zero-lag methods (ZLEMA, DEMA, TEMA) generate earlier crossover signals in trending markets for improved entry timing
Smoother algorithms (T3, Laguerre Binomial) reduce false extreme zone touches for more reliable overbought/oversold signals
Comparison with Standard Implementations:
Versus Basic Stochastic: Enhanced version offers 21 smoothing options versus single SMA, allowing optimization for specific market characteristics and trading styles
Versus RSI: Stochastic provides range-bound measurement (0-100) with clear extreme zones, RSI measures momentum speed, Stochastic offers clearer visual overbought/oversold identification
Versus MACD: Stochastic bounded oscillator suitable for mean reversion, MACD unbounded indicator better for trend strength, Stochastic excels in range-bound and oscillating markets
Versus CCI: Stochastic has fixed bounds (0-100) for consistent interpretation, CCI unbounded with variable extremes, Stochastic provides more standardized extreme readings across different instruments
Flexibility Advantages:
Single indicator adaptable to multiple strategies through algorithm selection rather than requiring different indicator variants
Ability to optimize smoothing characteristics for specific instruments (e.g., smoother for crypto volatility, faster for forex trends)
Multi-timeframe analysis with consistent algorithm across timeframes for coherent momentum picture
Backtesting capability with algorithm as optimization parameter for strategy development
Limitations and Considerations:
Increased complexity from multiple algorithm choices may lead to over-optimization if parameters are curve-fitted to historical data
Adaptive algorithms (KAMA, FRAMA) have adjustment periods during market regime changes where signals may be less reliable
Zero-lag algorithms sacrifice some smoothness for responsiveness, potentially increasing noise sensitivity in very choppy conditions
Performance characteristics vary significantly across algorithms, requiring understanding and testing before live implementation
Like all oscillators, Stochastic can remain in extreme zones for extended periods during strong trends, generating premature reversal signals
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to provide traders with enhanced flexibility in momentum analysis. The Stochastic Oscillator has limitations and should not be used as the sole basis for trading decisions.
Important Considerations:
Algorithm performance varies with market conditions - no single smoothing method is optimal for all scenarios
Extreme zone signals (overbought/oversold) indicate potential reversal areas but not guaranteed turning points, especially in strong trends
Crossover signals may generate false entries during sideways choppy markets regardless of smoothing algorithm
Divergence patterns require confirmation from price action or additional indicators before trading
Past indicator characteristics and backtested results do not guarantee future performance
Always combine Stochastic analysis with proper risk management, position sizing, and multi-indicator confirmation
Test selected algorithm on historical data of specific instrument and timeframe before live trading
Market regime changes may require algorithm adjustment for optimal performance
The enhanced smoothing options are intended to provide tools for optimizing the indicator's behavior to match individual trading styles and market characteristics, not to create a perfect predictive tool. Responsible usage includes understanding the mathematical properties of selected algorithms and their appropriate application contexts.
Inakis-BB-Stoch-ATR-ADX StrategyStrategy Description
This advanced trading strategy combines multiple technical indicators to identify high-probability breakout opportunities in trending markets. The system uses a multi-layered filtering approach to ensure only the strongest signals trigger trades.
Key Components:
Primary Signals:
Bollinger Bands Breakout: Identifies price extremes when price breaks below the lower band (buy) or above the upper band (sell)
Stochastic Oscillator: Confirms oversold (<30) and overbought (>70) conditions
ADX Filter: Ensures sufficient trend strength is present (ADX > 20)
ATR Volatility Filter: Trades only during periods of adequate volatility
Advanced Features:
DMI Higher Timeframe Analysis: Incorporates directional movement from higher timeframes (default 1H) to align trades with the dominant trend
Volume Confirmation: Requires above-average volume for signal validation
Cooldown Period: Prevents overtrading by enforcing minimum bars between signals
Visual Feedback: Color-coded background based on higher timeframe trend direction
Risk Management:
Fixed position sizing with customizable contract size
Predefined Stop Loss (default 500 points) and Take Profit (default 1000 points) levels
Clear risk-reward ratio of 1:2
Trading Logic:
Long Entry: Price breaks below BB lower band + Stochastic < 30 + Higher TF bullish trend
Short Entry: Price breaks above BB upper band + Stochastic > 70 + Higher TF bearish trend
All entries require confirmation from ADX, ATR, and volume filters
Customization:
All parameters are fully adjustable through the input panel, allowing traders to optimize the strategy for different markets and timeframes. Each filter can be individually enabled/disabled for testing and optimization purposes.
This strategy is designed for trending markets and performs best on liquid instruments with clear directional moves.
MTF Oscillator Stack [BigBeluga]🔵 OVERVIEW
The MTF Oscillator Stack brings powerful multi-timeframe momentum analysis directly into your price chart. You can select one oscillator— RSI , MFI , or Stochastic RSI —and display it across up to 4 different timeframes. Each panel is neatly stacked horizontally above price , offering quick insight into cross-timeframe conditions like trend direction, exhaustion zones, and momentum shifts.
🔵 CONCEPTS
Single Oscillator Mode: Select one oscillator type (RSI, MFI, or Stoch RSI) to analyze across all selected timeframes.
Top-Chart Horizontal Panels: Oscillator plots are aligned horizontally at the top of the chart for seamless top-down reading.
Signal Comparison Arrows: Arrows (🢁 / 🢃) indicate oscillator position relative to its signal line.
Overbought/Oversold Zones: Transparent 30–70 fill zones highlight key reversal areas.
Dynamic Display Logic: Only enabled panels are shown; spacing adjusts based on active timeframes.
Timeframe Tagging: Each oscillator panel is labeled with its corresponding timeframe (e.g., 1H, 2H, 4H).
🔵 FEATURES
Choose one oscillator (RSI, MFI, or Stoch RSI) and apply it across up to 4 timeframes.
Each oscillator panel includes: price-synced plot, signal line, and zone shading.
Scale alignment allows users to place charts at the bottom or top.
Clear arrow signals show whether oscillator is bullish or bearish.
Individual length and signal settings per timeframe.
Toggle for alignment mode: evenly spaced or floating layout.
All panels use a consistent layout for faster decision-making.
🔵 HOW TO USE
Select your preferred oscillator and activate 2–4 key timeframes (e.g., 1H, 4H, D1, W1).
Use signal crossovers as a bullish (🢁) or bearish (🢃) trend cue.
Look for aligned extremes (e.g., all timeframes overbought) to spot momentum exhaustion.
Ideal for momentum confluence strategies and top-down confirmation.
Use horizontal layout to stay focused on price while assessing broader structure.
🔵 CONCLUSION
MTF Oscillator Stack simplifies complex multi-timeframe momentum analysis into one clean, actionable visual. Whether you're tracking RSI, MFI, or Stoch RSI, this tool helps you stay aligned with the broader trend—without ever leaving your main chart.
CryptoPulseStoch AICryptoPulseStoch AI Strategy
This strategy combines Bollinger Bands, multi-timeframe EMAs (200 and 50), and Stochastic Oscillator for crypto trading signals on the 1-minute timeframe. Long entries trigger on Stochastic %K/%D crossovers in oversold zones with price breaking the lower Bollinger Band and an upward EMA trend; shorts on crossunders in overbought zones with price breaking the upper Bollinger Band and a downward EMA trend. Includes ATR-based risk management, position sizing, and R:R targets. Overlay on any chart; supports leverage (100% margin). Visual lines/labels for TP/SL/entries; alerts for webhooks.
- **Account Balance (Default: 10000)**: Initial balance for calculating risk and position size; increase for larger accounts.
- **BB Length (Default: 20)**: Periods for Bollinger Bands basis and deviation; shorter for more signals, longer for smoothing.
- **BB Multiplier (Default: 2.0)**: Std dev factor for band width; higher widens bands, reducing false breakouts.
- **Stochastic %K Length (Default: 14)**: Periods for Stochastic Oscillator %K calculation; adjust for sensitivity.
- **Stochastic Smooth K (Default: 1)**: Smoothing period for %K; higher values reduce noise.
- **Stochastic Smooth D (Default: 3)**: Smoothing period for %D; higher values smooth the signal line.
- **Overbought Level (Default: 70)**: Stochastic threshold for bearish signals; lower for more frequent signals.
- **Oversold Level (Default: 30)**: Stochastic threshold for bullish signals; higher for more frequent signals.
- **Risk Per Trade (%) (Default: 2.0)**: Account percentage risked per trade; lower for conservative sizing.
- **Risk:Reward Ratio (Default: 6.0)**: Target profit multiple of risk; higher aims for bigger wins.
- **SL Multiplier (Default: 9.0)**: ATR factor for stop loss distance; adjust based on volatility.
- **TP Multiplier (Default: 6.0)**: ATR factor for take profit distance, scaled by R:R; adjust for target distance.
- **Line Length (bars) (Default: 25)**: Bars to extend TP/SL/entry lines; longer for better visibility.
- **Label Position (Default: left)**: Text placement relative to lines (left/right); choose for chart clarity.
- **ATR Period (Default: 14)**: Periods for ATR volatility measure; affects SL, TP, and position size.
- **EMA Timeframe (Default: 5 min)**: Resolution for EMA 200/50 calculation; use lower TFs for finer trend confirmation.
- **Visuals**: BB plots (blue basis, green upper, red lower); EMA200 (red), EMA50 (green); Stochastic %K (blue), %D (orange); red/green lines/labels for sell/buy entries, SL (red), TP (green).
- **Alerts**: Conditions for buy/sell signals with webhook messages for integration (e.g., Bitget).
Stochastic Money Flow IndexThe Stochastic Money Flow Index (or Stochastic MFI ), is a variation of the classic Stochastic RSI that uses the Money Flow Index (MFI) rather than the Relative Strength Index (RSI) in its calculation.
While the RSI focuses solely on price momentum, the MFI is a volume-weighted indicator, meaning it incorporates both price and volume data.
The Stochastic MFI is intended to provide a more precise and sensitive reading of the MFI by measuring the level of the MFI relative to its range over a specific period.
Settings
Stochastic Settings
%K Length : The number of periods used to calculate the Stochastic. (Default: 14)
%K Smoothing : The SMA length used to 'smooth' the %K line. (Default: 3)
%D Smoothing : The SMA length used to 'smooth' the %D line. (Default: 1)
Money Flow Index Settings
MFI Length : The number of periods used to calculate the Money Flow Index. (Default: 14)
MFI Source : The source used to calculate the Money Flow Index. (Default: close)
Additional Settings
Show Overbought/Oversold Gradients? : Toggle the display of overbought/oversold gradients. (Default: true)
StochFusion – Multi D-LineStochFusion – Multi D-Line
An advanced fusion of four Stochastic %D lines into one powerful oscillator.
What it does:
Combines four user-weighted Stochastic %D lines—from fastest (9,3) to slowest (60,10)—into a single “Fusion” line that captures both short-term and long-term momentum in one view.
How to use:
Adjust the four weights (0–10) to emphasize the speed of each %D component.
Watch the Fusion line crossing key zones:
– Above 80 → overbought condition, potential short entry.
– Below 20 → oversold condition, potential long entry.
– Around 50 → neutral/midline, watch for trend shifts.
Applications:
Entry/exit filter: Only take trades when the Fusion line confirms zone exits.
Trend confirmation: Analyze slope and cross of the midline for momentum strength.
Multi-timeframe alignment: Use on different chart resolutions to find confluence.
Tips & Tricks:
Default weights give more influence to slower %D—good for trend-focused strategies.
Equal weights provide a balanced oscillator that mimics an ensemble average.
Experiment: Increase the fastest weight to capture early reversal signals.
Developed by: TradeQUO — inspired by DayTraderRadio John
“The best momentum indicator is the one you adapt to your own trading rhythm.”
Uptrick: Mean ReversionOverview
Uptrick: Mean Reversion is a technical indicator designed to identify statistically significant reversal opportunities by monitoring market extremes. It presents a unified view of multiple analytical layers—momentum shifts, extreme zones, divergence patterns, and a multi-factor bias dashboard—within a single pane. By translating price momentum into a normalized framework, it highlights areas where prices are likely to revert to their average range.
Introduction
Uptrick: Mean Reversion relies on several core concepts:
Volatility normalization
The indicator rescales recent market momentum into a common scale so that extreme readings can be interpreted consistently across different assets and timeframes.
Mean reversion principle
Markets often oscillate around an average level. When values stray too far beyond typical ranges, a return toward the mean is likely. Uptrick: Mean Reversion detects when these extremes occur.
Momentum inflection
Sharp changes in momentum direction frequently presage turning points. The indicator watches for shifts from upward momentum to downward momentum (and vice versa) to help time entries and exits.
Divergence
When price trends and internal momentum readings move in opposite directions, it can signal weakening momentum and an impending reversal. Uptrick: Mean Reversion flags such divergence conditions directly on the indicator pane.
Multi-factor sentiment
No single metric tells the entire story. By combining several independent sentiment measures—price structure, momentum, oscillators, and external market context—Uptrick: Mean Reversion offers a more balanced view of overall market bias.
Purpose
Uptrick: Mean Reversion was created for traders who focus on countertrend opportunities rather than simply following established trends. Its main objectives are:
Spot extreme conditions
By normalizing momentum into a standardized scale, the indicator clearly marks when the market is in overbought or oversold territory. These conditions often align with points where a snapback toward average is more probable.
Provide reversal signals
Built-in logic detects when momentum shifts direction within extreme zones and displays clear buy or sell markers to guide countertrend entries and exits.
Highlight hidden divergences
Divergence between price and internal momentum can suggest underlying weakness or strength ahead of actual price moves. Uptrick: Mean Reversion plots these divergences directly, allowing traders to anticipate reversals earlier.
Offer contextual bias
A dynamic dashboard aggregates multiple independent indicators—based on recent price action, momentum readings, common oscillators, and broader market context—to produce a single sentiment label. This helps traders determine whether mean reversion signals align with or contradict overall market conditions.
Cater to lower timeframes
Mean reversion tends to occur more frequently and reliably on shorter timeframes (for example, 5-minute, 15-minute, or 1-hour charts). Uptrick: Mean Reversion is optimized for these nimble environments, where rapid reversals can be captured before a larger trend takes hold.
Originality and Uniqueness
Uptrick: Mean Reversion stands out for several reasons:
Proprietary normalization framework
Instead of relying on raw oscillator values, it transforms momentum into a standardized scale. This ensures that extreme readings carry consistent meaning across different assets and volatility regimes.
Inflection-based signals
The indicator waits for a clear shift in momentum direction within extreme zones before plotting reversal markers. This approach reduces false signals compared to methods that rely solely on fixed threshold crossings.
Embedded divergence logic
Divergence detection is handled entirely within the same pane. Rather than requiring a separate indicator window, Uptrick: Mean Reversion identifies instances where price and internal momentum readings do not align and signals those setups directly on the chart.
Adjustable sensitivity profiles
Traders can choose from predefined risk profiles—ranging from very conservative to very aggressive—to automatically adjust how extreme a reading must be before triggering a signal. This customization helps balance between capturing only the most significant reversals or generating more frequent, smaller opportunities.
Multi-factor bias dashboard
While many indicators focus on a single metric, Uptrick: Mean Reversion aggregates five distinct sentiment measures. By balancing price-based bias, momentum conditions, and broader market context, it offers a more nuanced view of when to take—or avoid—countertrend trades.
Why Indicators Were Merged
Proprietary momentum oscillator
A custom-built oscillator rescales recent price movement into a normalized range. This core component underpins all signal logic and divergence checks, allowing extreme readings to be identified consistently.
Inflection detection
By comparing recent momentum values over a configurable lookback interval, the indicator identifies clear shifts from rising to falling momentum (and vice versa). These inflection points serve as a prerequisite for reversal signals when combined with extreme conditions.
Divergence framework
Local peaks and troughs are identified within the normalized oscillator and compared to corresponding price highs and lows. When momentum peaks fail to follow price to new extremes (or vice versa), a divergence alert appears, suggesting weakening momentum ahead of a price turn.
Classic price bias
Recent bar structures are examined to infer whether the immediate past price action was predominantly bullish, bearish, or neutral. This provides one piece of the overall sentiment picture.
Smoothed oscillator bias
A secondary oscillator reading is smoothed and compared to a central midpoint to generate a simple bullish or bearish reading.
Range-based oscillator bias
A familiar range-bound oscillator is used to detect oversold or overbought readings, contributing to the sentiment score.
Classic momentum crossover bias
A traditional momentum check confirms whether momentum currently leans bullish or bearish.
External market trend bias
The indicator monitors a major currency’s short-term trend to gauge broader market risk appetite. A falling currency—often associated with higher risk tolerance—contributes a bullish bias point, while a rising currency adds a bearish point.
All these elements run concurrently. Each piece provides a “vote” toward an overall sentiment reading. At the same time, the proprietary momentum oscillator drives both extreme-zone detection and divergence identification. By merging these inputs, the final result is a single pane showing both precise reversal signals and a unified market bias.
How It Works
At runtime, the indicator proceeds through the following conceptual steps:
Read user inputs (risk profile, lookback index, visual mode, color scheme, background highlighting, bias table display, divergence toggles).
Fetch the latest price data.
Process recent price movement through a proprietary normalization engine to produce a single, standardized momentum reading for each bar.
Track momentum over a configurable lookback interval to detect shifts in direction.
Compare the current momentum reading to dynamically determined extreme thresholds (based on the chosen risk profile).
If momentum has flipped from down to up within an oversold area, display a discrete buy marker. If momentum flips from up to down within an overbought area, display a sell marker.
Identify local peaks and troughs in the proprietary momentum series and compare to price highs and lows over a configurable range. When divergence criteria are met, display bullish or bearish divergence labels
Evaluate five independent sentiment measures—price bar bias, smoothed oscillator bias, range oscillator bias, traditional momentum crossover bias, and an external market trend bias—and assign each a +1 (bullish), –1 (bearish), or 0 (neutral) vote.
Average the five votes to produce an overall sentiment score. If the average exceeds a positive threshold, label the bias as bullish; if it falls below a negative threshold, label it as bearish; otherwise label it neutral.
Update the on-screen bias table at regular intervals, showing each individual metric’s value and vote, as well as the combined sentiment label.
Apply color fills to highlight extreme zones in the background and draw horizontal guideline bands around those extremes.
In complex visual mode, draw a cloud-like band that instantly changes color when momentum shifts. In simple mode, plot only a clean line of the normalized reading in a contrasting color.
Expose alert triggers whenever a buy/sell signal, divergence confirmation, or bias flip occurs, for use in automated notifications.
Inputs
Here is how each input affects the indicator:
Trading Style (very conservative / conservative / neutral / aggressive / very aggressive)
Determines how sensitive the indicator is to extreme readings. Conservative settings require more pronounced market deviations before signaling a reversal; aggressive settings signal more frequently at smaller deviations.
Slope Detection Index (integer)
Controls how many bars back the indicator looks to compare momentum for inflection detection. Lower numbers respond more quickly but can be noisy; higher numbers smooth out short-term fluctuations.
Visual Mode (simple / complex)
Simple mode plots only the normalized momentum line, colored according to the chosen palette. Complex mode draws a candle-style block for each bar—showing the range of momentum movement within that bar—with colored fills that switch instantly when momentum direction changes.
Color Scheme (multiple themes)
Select from preset color palettes to style bullish vs. bearish elements (fills, lines, labels). Options include bright neon tones, classic contrasting pairs, dark-mode palettes, and more, ensuring signals stand out against any chart background.
Enable Background Highlighting (true / false)
When true, extreme overbought or oversold zones are shaded in a semi-transparent color behind the main pane. This helps traders “see” when the market is in a normalized extreme state without relying solely on lines or markers.
Show Helper Scale Lines (true / false)
When true, hidden horizontal lines force the vertical scale to include a fixed range of extreme values—even if the indicator rarely reaches them—so traders always know where the most extreme limits lie.
Enable Divergence Detection (true / false)
Toggles whether the script looks for divergences between price and the proprietary momentum reading. When enabled, bullish/bearish divergence markers appear automatically whenever defined conditions are met.
Pivot Lookback Left & Pivot Lookback Right (integers)
Define how many bars to the left and right the indicator examines when identifying a local peak or trough in the momentum reading. Adjust these to capture divergences on different swing lengths.
Minimum and Maximum Bars Between Pivots (integers)
Set the minimum and maximum number of bars allowed between two identified peaks or troughs for a valid divergence. This helps filter out insignificant or overly extended divergence patterns.
Show Bias Table (true / false)
When enabled, displays a small table in the upper-right corner summarizing five independent sentiment votes and the combined bias label. Disable to keep the pane focused on only the momentum series and signals.
Features
1. Extreme-zone highlighting
Overbought and oversold areas appear as colored backgrounds when the proprietary momentum reading crosses dynamically determined thresholds. This gives an immediate visual cue whenever the market moves into a highly extreme condition.
2. Discrete reversal markers
Whenever momentum shifts direction within an extreme zone, the indicator plots a concise “Buy” or “Sell” label directly on the normalized series. These signals combine both extreme-zone detection and inflection confirmation, reducing false triggers.
3. Dynamic divergence flags
Local peaks and troughs of the proprietary momentum reading are continuously compared to corresponding price points. Bullish divergence (momentum trough rising while price trough falls) and bearish divergence (momentum peak falling while price peak rises) are flagged with small labels and lines. These alerts help traders anticipate reversals before price charts show clear signals.
4. Multi-factor sentiment dashboard
Five independent “votes” are tallied each bar:
• Price bar bias (based on recent bar structure)
• Smoothed oscillator bias (based on a popular momentum oscillator)
• Range oscillator bias (based on an overbought/oversold oscillator)
• Traditional momentum crossover bias (whether momentum is above or below its own smoothing)
• External market trend bias (derived from a major currency index’s short-term trend)
Each vote is +1 (bullish), –1 (bearish), or 0 (neutral). The average of these votes produces an overall sentiment label (Bullish, Bearish, or Neutral). The table updates periodically, showing each metric’s value, its vote, and the combined bias.
5. Versatile visual modes
Simple mode: Plots a single normalized momentum line in a chosen color. Ideal for clean charts.
Complex mode: Renders each bar’s momentum range as a candle-like block, with filled bodies that immediately change color when momentum direction flips. Edge lines emphasize the high/low range of momentum for that bar. This mode makes subtle momentum shifts visually striking.
6. Configurable sensitivity profiles
Five risk profiles (very conservative → very aggressive) automatically adjust how extreme the momentum reading must be before signaling. Conservative traders can wait for only the most dramatic reversals, while aggressive traders can capture more frequent, smaller mean-reversion moves.
7. Customizable color palettes
Twenty distinct color themes let users match the indicator to any chart background. Each theme defines separate colors for bullish fills, bearish fills, the momentum series, and divergence labels. Options range from classic contrasting pairs to neon-style palettes to dark-mode complements.
8. Unified plotting interface
Instead of scattering multiple indicators in separate panes, Uptrick: Mean Reversion consolidates everything—normalized momentum, background shading, threshold bands, reversal labels, divergence flags, and bias table—into a single indicator pane. This reduces screen clutter and places all relevant information in one view.
9. Built-in alert triggers
Six alert conditions are exposed:
Mean reversion buy signal (momentum flips in oversold zone)
Mean reversion sell signal (momentum flips in overbought zone)
Bullish divergence confirmation
Bearish divergence confirmation
Bias flip to bullish (when combined sentiment shifts from non-bullish to bullish)
Bias flip to bearish (when combined sentiment shifts from non-bearish to bearish)
Traders can attach alerts to any of these conditions to receive real-time notifications.
10. Scale anchoring
By forcing invisible horizontal lines at fixed extreme levels, the indicator ensures that the vertical axis always includes those extremes—even if the normalized reading rarely reaches them. This constant frame of reference helps traders judge how significant current readings are.
Line features:
Conclusion
Uptrick: Mean Reversion offers a layered, all-in-one approach to spotting countertrend opportunities. By converting price movement into a proprietary normalized momentum scale, it highlights extreme overbought and oversold zones. Inflection detection within those extremes produces clear reversal markers. Embedded divergence logic calls out hidden momentum weaknesses. A five-factor sentiment dashboard helps gauge whether a reversal signal aligns with broader market context. Users can tailor sensitivity, visual presentation, and color schemes, making it equally suitable for minimalist or richly detailed chart layouts. Optimized for lower timeframes, Uptrick: Mean Reversion helps traders anticipate statistically significant mean reversion moves.
Disclaimer
This indicator is provided for informational purposes only. It does not guarantee any trading outcome. Trading carries inherent risks, including the potential loss of invested capital. Users should perform their own due diligence, apply proper risk management, and consult a financial professional if needed. Past performance does not ensure future results.
Stochastic RainbowThe Stochastic Rainbow indicator is a multi-layered momentum oscillator designed to provide a comprehensive view of market dynamics by combining multiple stochastic oscillators of varying periods. This approach allows traders to analyze both short-term and long-term momentum within a single visual framework, enhancing decision-making for entries and exits.
🔧 Indicator Settings and Customization
Select from various moving average methods (e.g., SMA, EMA, DEMA, TEMA, WMA, VWMA, RMA, T3) to smooth the stochastic lines. Different methods can affect the responsiveness of the indicator.
The indicator computes five sets of stochastic oscillators with Fibonacci values.
Each %K line is smoothed using the selected moving average type, and a corresponding %D line is plotted for each %K.
🎨 Visual Interpretation
The Stochastic Rainbow indicator plots multiple %K and %D lines, each with distinct colors for easy differentiation.
Additionally, horizontal dotted lines are drawn at levels 80 (Upper Band), 50 (Midline), and 20 (Lower Band) to indicate overbought, neutral, and oversold conditions, respectively.
📈 Trading Strategies Using Stochastic Rainbow
The multi-layered structure of the Stochastic Rainbow allows for nuanced analysis.
Trend Confirmation:
When all %K lines are above 50 and aligned in ascending order (short-term above long-term), it suggests a strong uptrend.
Conversely, when all %K lines are below 50 and aligned in descending order, it indicates a strong downtrend.
Overbought/Oversold Conditions:
If the shorter-term %K lines (e.g., %K 5,3 and %K 8,3) enter the overbought zone (>80) while longer-term lines remain below, it may signal a potential reversal.
Similarly, if shorter-term lines enter the oversold zone (<20) while longer-term lines remain above, it could indicate an upcoming bullish reversal.
Crossovers:
A bullish signal occurs when a %K line crosses above its corresponding %D line.
A bearish signal occurs when a %K line crosses below its corresponding %D line.
Divergence Analysis:
If price makes a new high while the %K lines do not, it may indicate bearish divergence and a potential reversal.
If price makes a new low while the %K lines do not, it may indicate bullish divergence and a potential reversal.
⚙️ Adjusting Settings for Optimal Use
The Stochastic Rainbow's flexibility allows traders to adjust settings to match their trading style and the specific asset's behavior:
Short-Term Trading: Use shorter periods (e.g., 5 for %K) and more responsive moving averages (e.g., WMA, VWMA, EMA, DEMA, TEMA, HMA) to capture quick market movements.
Long-Term Trading: Opt for longer periods (e.g., 55 for %K) and smoother moving averages (e.g., SMA, RMA, T3) to filter out noise and focus on broader trends.
Volatile Markets: Consider using the T3 moving average for its smoothing capabilities, helping to reduce false signals in choppy markets.
By experimenting with different settings, traders can fine-tune the indicator to better suit their analysis and improve decision-making.
Stochastic XThe "Stochastic X" script is a customizable momentum oscillator designed to help traders identify potential overbought and oversold conditions, as well as trend reversals, by analyzing the relationship between a security's closing price and its price range over a specified period. This indicator is particularly useful for traders looking to fine-tune their entry and exit points based on momentum shifts.
🔧 Indicator Settings and Customization
The script offers several user-configurable settings to tailor the indicator to specific trading strategies:
In addition to the source type, %K Period, %D Period, and Signal line periods you can now change moving average calculation for the stochastic and signal lines.
This script allows selection among various moving average methods (e.g., SMA, EMA, WMA, T3) for smoothing the %K and signal lines. Different methods can affect the responsiveness of the indicator.
🎨 Interpreting Background Colors
The script enhances visual analysis by changing the background color of the indicator panel based on the %K line's value:
Green Background: Indicates that the %K line is above 50, suggesting bullish momentum.
Red Background: Signifies that the %K line is below 50, pointing to bearish momentum.
Light Green Overlay: Appears when the %K line exceeds 80, highlighting overbought conditions.
Light Red Overlay: Shows up when the %K line falls below 20, indicating oversold conditions.
These visual cues assist traders in quickly assessing market momentum and potential reversal.
📈 Trading Strategies Using Stochastic X
Traders can utilize the Stochastic X indicator in various ways:
Overbought/Oversold Conditions:
A %K value above 80 may suggest that the asset is overbought, potentially signaling a price correction.
A %K value below 20 could indicate that the asset is oversold, possibly leading to a price rebound.
Signal Line Crossovers:
When the %K line crosses above the signal line, it may be interpreted as a bullish signal.
Conversely, a %K line crossing below the signal line might be seen as a bearish signal.
Divergence Analysis:
If the price makes a new high while the %K line does not, this bearish divergence could precede a price decline.
If the price hits a new low but the %K line forms a higher low, this bullish divergence might signal an upcoming price increase.
Trend Confirmation:
Sustained %K values above 50 can confirm an uptrend.
Persistent %K values below 50 may validate a downtrend.
In this chart, observe how the background colors change in response to the %K line's value, providing immediate visual feedback on market conditions. The crossovers between the %K and signal lines offer potential entry and exit points, while the overbought and oversold overlays help identify possible reversal zones.
⚙️ Adjusting Settings for Optimal Use
The Stochastic X indicator's flexibility allows traders to adjust settings to match their trading style and the specific asset's behavior:
Short-Term Trading: Use shorter periods (e.g., 5 for %K) and more responsive moving averages (e.g., WMA, VWMA, EMA, DEMA, TEMA, HMA) to capture quick market movements.
Long-Term Trading: Opt for longer periods (e.g., 14 for %K) and smoother moving averages (e.g., SMA, RMA, T3) to filter out noise and focus on broader trends.
Volatile Markets: Consider using the T3 moving average for its smoothing capabilities, helping to reduce false signals in choppy markets.
By experimenting with different settings, traders can fine-tune the indicator to better suit their analysis and improve decision-making.
Precision Stochastic DivergenceThis indicator is designed to identify potential market turning points and continuations by detecting Regular and Hidden divergences between closing price action and the Stochastic momentum oscillator. It utilizes specific default parameters (Stochastic: 40,4,3; Pivot Lookback: 5,5 based on close) and incorporates specialized filtering logic for signal qualification.
Core Functionality & Features:
Divergence Detection: Identifies standard Regular (potential reversal) and Hidden (potential continuation) divergence patterns. Logic has been optimized for accurate detection of both types.
Precision Filter Mechanism (Regular Divergences): Employs a unique dual-level validation process:
Requires the initial pivot's Stochastic value (%D) to meet Overbought (>80) or Oversold (<20) criteria.
Requires the subsequent pivot's Stochastic value (%D) to reside within a precisely defined range (Default parameterization: Bullish 19-30, Bearish 70-81). This aims to filter divergences based on specific momentum conditions following an initial extreme reading.
Standard Filter (Hidden Divergences): Filters Hidden Divergence signals by requiring both associated Stochastic pivot values to remain outside the primary Overbought/Oversold zones (i.e., >20 for Bullish, <80 for Bearish).
Signal Plotting: Displays 'R' (Regular) and 'H' (Hidden) markers on the chart upon confirmation of filtered divergence conditions. Relevant Stochastic threshold levels and filter range boundaries are plotted for visual reference.
Configuration & Usage Notes:
Parameterization: The default settings (Stochastic: 40,4,3; Pivots: 5,5; Levels: 80/20; Ranges: 19-30 / 70-81) have been specifically calibrated. For optimal performance according to the intended methodology, modification of these core parameters is strongly discouraged.
EMA Filter: Note that EMA trend filtering functionality has been intentionally removed from this version of the indicator.
Applicable Timeframes: While adaptable, performance consistency has been observed on the Hourly (1H) timeframe. Lower intervals such as 6m and 10m are considered optimal secondary timeframes, with 5m and 15m also demonstrating viability depending on market conditions.
Instrument Applicability & Validation:
!!!WARNING FOR GOLD TRADERS!!!
Low time frame spot gold (xauusd) mysteriously proves to give more incorrect signals than every other asset I have tested although higher timeframes like hourlies still signal as intended. The reason MAY be because of not enough testing.
The underlying principle of Stochastic divergence is applicable to various instruments, including Cryptocurrencies (Bitcoin, Ethereum) and Major Indices (SP500, NASDAQ, etc.).
However, the efficiency of this indicator's specific parameterization is contingent upon the volatility profile and price dynamics of the selected instrument.
Mandatory Validation: Rigorous backtesting and/or simulated trading on the specific instrument and timeframe is imperative prior to live deployment. This validation is crucial to ascertain performance characteristics and confirm alignment with individual trading plans and risk management protocols.
By Matthew James
Disclaimer:
Trading involves substantial risk. This indicator serves as an analytical tool and does not constitute financial advice or a guarantee of future results. Users assume full responsibility for their trading decisions. Always employ robust risk management practices.
Quad Rotation StochasticQuad Rotation Stochastic
The Quad Rotation Stochastic is a powerful and unique momentum oscillator that combines four different stochastic setups into one tool, providing an incredibly detailed view of market conditions. This multi-timeframe stochastic approach helps traders better anticipate trend continuations, reversals, and momentum shifts with greater precision than traditional single stochastic indicators.
Why this indicator is useful:
Multi-layered Momentum Analysis: Instead of relying on one stochastic, this script tracks four independent stochastic readings, smoothing out noise and confirming stronger signals.
Advanced Divergence Detection: It automatically identifies bullish and bearish divergences for each stochastic, helping traders spot potential reversals early.
Background Color Alerts: When a configurable number (e.g., 3 or 4) of the stochastics agree in direction and position (overbought/oversold), the background colors green (bullish) or red (bearish) to give instant visual cues.
ABCD Pattern Recognition: The script recognizes "shield" patterns when Stochastic 4 remains stuck at extreme levels (above 90 or below 10) for a set time, warning of potential trend continuation setups.
Super Signal Alerts: If all four stochastics align in extreme conditions and slope in the same direction, the indicator plots a special "Super Signal," offering high-confidence entry opportunities.
Why this indicator is unique:
Quad Confirmation Logic: Combining four different stochastics makes this tool much less prone to false signals compared to using a single stochastic.
Customizable Divergence Coloring: Traders can choose to have divergence lines automatically match the stochastic color for clear visual association.
Adaptive ABCD Shields: Innovative use of bar counting while a stochastic remains extreme acts as a "shield," offering a unique way to filter out minor fake-outs.
Flexible Configuration: Each stochastic's sensitivity, divergence settings, and visual styling can be fully customized, allowing traders to adapt it to their own strategy and asset.
Example Usage: Trading Bitcoin with Quad Rotation Stochastic
When trading Bitcoin (BTCUSD), you might set the minimum count (minCount) to 3, meaning three out of four stochastics must be in agreement to trigger a background color.
If the background turns green, and you notice an ABCD Bullish Shield (Green X), you might look for bullish candlestick patterns or moving average crossovers to enter a long trade.
Conversely, if the background turns red and a Super Down Signal appears, it suggests high probability for further downside, giving you strong confirmation to either short BTC or avoid entering new longs.
By combining divergence signals with background colors and the ABCD shields, the Quad Rotation Stochastic provides a layered confirmation system that gives traders greater confidence in their entries and exits — particularly in fast-moving, volatile markets like Bitcoin.
Stochastic Overlay - Regression Channel (Zeiierman)█ Overview
The Stochastic Overlay – Regression Channel (Zeiierman) is a next-generation visualization tool that transforms the traditional Stochastic Oscillator into a dynamic price-based overlay.
Instead of leaving momentum trapped in a lower subwindow, this indicator projects the Stochastic oscialltor directly onto price itself — allowing traders to visually interpret momentum, overbought/oversold conditions, and market strength without ever taking their eyes off price action.
⚪ In simple terms:
▸ The Bands = The Stochastic Oscillator — but on price.
▸ The Midline = Stochastic 50 level
▸ Upper Band = Stochastic Overbought Threshold
▸ Lower Band = Stochastic Oversold Threshold
When the price moves above the midline → it’s the same as the oscillator moving above 50
When the price breaks above the upper band → it’s the same as Stochastic entering overbought.
When the price reaches the lower band →, think of it like Stochastic being oversold.
This makes market conditions visually intuitive. You’re literally watching the oscillator live on the price chart.
█ How It Works
The indicator layers 3 distinct technical elements into one clean view:
⚪ Stochastic Momentum Engine
Tracks overbought/oversold conditions and directional strength using:
%K Line → Momentum of price
%D Line → Smoothing filter of %K
Overbought/Oversold Bands → Highlight potential reversal zones
⚪ Volatility Adaptive Bands
Dynamic bands plotted above and below price using:
ATR * Stochastic Scaling → Creates wider bands during volatile periods & tighter bands in calm conditions
Basis → Moving average centerline (EMA, SMA, WMA, HMA, RMA selectable)
This means:
→ In strong trends: Bands expand
→ In consolidations: Bands contract
⚪ Regression Channel
Projects trend direction with different models:
Logarithmic → Captures non-linear growth (perfect for crypto or exponential stocks)
Linear → Classic regression fit
Adaptive → Dynamically adjusts sensitivity
Leading → Projects trend further ahead (aggressive mode)
Channels include:
Midline → Fair value trend
Upper/Lower Bounds → Deviation-based support/resistance
⚪ Heatmap - Bull & Bear Power Strength
Visual heatmeter showing:
% dominance of bulls vs bears (based on close > or < Band Basis)
Automatic normalization regardless of timeframe
Table display on-chart for quick visual insight
Dynamic highlighting when extreme levels are reached
⚪ Trend Candlestick Coloring
Bars auto-color based on trend filter:
Above Basis → Bullish Color
Below Basis → Bearish Color
█ How to Use
⚪ Trend Trading
→ Use Band direction + Regression Channel to identify trend alignment
→ Longs favored when price holds above the Basis
→ Shorts favored when price stays below the Basis
→ Use the Bull & Bear heatmap to asses if the bulls or the bears are in control.
⚪ Mean Reversion
→ Look for price to interact with Upper or Lower Band extremes
→ Stochastic reaching OB/OS zones further supports reversals
⚪ Momentum Confirmation
→ Crossovers between %K and %D can confirm continuation or divergence signals
→ Especially powerful when happening at band boundaries
⚪ Strength Heatmap
→ Quickly visualize current buyer vs seller control
→ Sharp spikes in Bull Power = Aggressive buying
→ Sharp spikes in Bear Power = Heavy selling pressure
█ Why It Useful
This is not a typical Stochastic or regression tool. The tool is designed for traders who want to:
React dynamically to price volatility
Map momentum into volatility context
Use adaptive regression channels across trend styles
Visualize bull vs bear power in real-time
Follow trends with built-in reversal logic
█ Settings
Stochastic Settings
Stochastic Length → Period of calculation. Higher = smoother, Lower = faster signals.
%K Smoothing → Smooths the Stochastic line itself.
%D Smoothing → Smooths the moving average of %K for slower signals.
Stochastic Band
Band Length → Length of the Moving Average Basis.
Volatility Multiplier → Controls band width via ATR scaling.
Band Type → Choose MA type (EMA, SMA, WMA, HMA, RMA).
Regression Channel
Regression Type → Logarithmic / Linear / Adaptive / Leading.
Regression Length → Number of bars for regression calculation.
Heatmap Settings
Heatmap Length → Number of bars to calculate bull/bear dominance.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Log Regression Oscillator Channel [BigBeluga]
This unique overlay tool blends logarithmic trend analysis with dynamic oscillator behavior. It projects RSI, MFI, or Stochastic lines directly into a log regression channel on the price chart — offering an intuitive way to detect overbought/oversold momentum within the broader price structure.
🔵Key Features:
Logarithmic Regression Channel:
➣ Draws a trend-based channel using logarithmic regression, adapting to price growth curvature over time.
➣ Features upper, lower, and optional midline boundaries to visualize trend flow and range extremes.
Oscillator Overlay (RSI / MFI / Stochastic):
➣ Projects your chosen oscillator inside the channel using dynamic polylines.
➣ Allows switching between RSI, Money Flow Index, or Stochastic for versatile momentum insight.
Threshold-Based Scaling:
➣ The top and bottom of the channel represent traditional oscillator thresholds (e.g., RSI 70/30).
➣ Users can modify the scale in settings to customize what "overbought" or "oversold" means visually.
Signal Line Integration:
➣ Adds a yellow moving average (signal line) for smoother confirmation of oscillator turns.
➣ Helps identify divergence, momentum shifts, and fakeouts with better clarity.
Live Oscillator Readout:
➣ Displays the real-time oscillator value at the right edge of the chart.
➣ Ensures traders stay aware of current momentum levels without switching panels.
🔵Usage:
Momentum Context:
➣ When the oscillator touches the upper regression band, it may signal local overbought pressure.
➣ Touching the lower band may indicate oversold conditions within the current log trend.
Divergence Detection:
➣ Use the oscillator’s behavior relative to the channel slope to spot divergence from price.
➣ For example, RSI rising inside a falling channel can flag early trend shifts.
Trend-Sensitive Entries:
➣ Combine oscillator signals with log channel direction to filter trades in trend alignment.
➣ Signal line crossovers inside the channel act as early warning for momentum turns.
The Log Regression Oscillator Channel transforms how traders view classic momentum tools. By embedding oscillators into a logarithmic trend structure, it offers unmatched clarity on momentum positioning relative to price expansion. Ideal for swing traders, mean-reverters, or trend followers looking to sharpen entries and exits with style.
Currency Strength AnalyzerThis indicator calculates and ranks the strength of eight major currencies (AUD, CAD, CHF, EUR, GBP, JPY, NZD, USD) based on a stochastic-based scoring system. It retrieves forex pair data and determines each currency's relative strength using a customized scoring method.
Features:
Uses stochastic (Stoch) indicators to calculate bullish/bearish strength.
Aggregates scores for each currency based on multiple forex pairs.
Sorts currencies from strongest to weakest.
Displays results in a dynamically updated table.
Highlights the strongest and weakest currencies on the chart.
This tool helps traders identify potential trends and reversals in the forex market by visually comparing currency strengths in real-time.
