Summit LineThe Summit Line is an advanced momentum and confluence indicator designed to simplify complex market data into clean, actionable dot signals.
It blends MACD, RSI, moving averages and Volume Strength, giving traders a real time gauge of momentum shifts and exhaustion points.
🟢 Green Dot: Bullish confluence
🔴 Red Dot: Bearish confluence
🟡 Gold Dot: “A+” setup, rare alignment of all core metrics, typically at high-probability reversal or breakout zones.
Unlike noisy indicators, Summit Line filters weak signals using RSI slope, volume surges, and EMA trend structure, keeping the chart clean and accurate.
Every dot is pinned along a flat zero baseline for visual simplicity, ideal for combining with the Summit cloud or other price overlays.
M-oscillator
Moving Average Convergence Divergence ProThis script is an advanced and highly customizable version of the classic Moving Average Convergence Divergence (MACD) indicator for TradingView. It builds upon the standard MACD by adding professional features like divergence detection, visual enhancements, configurable alerts, and optional smoothing, making it a more powerful tool for technical analysis.
Key Features and Functionality
Enhanced Visual Customization:
Toggleable Elements: You can independently show or hide the main MACD line, signal line, histogram, and the fill area between the lines.
Customizable Colors: All elements (bullish, bearish, signal line, divergence markers) can be colored to your preference.
Dynamic Histogram: The histogram uses a gradient effect, becoming more transparent during weaker momentum and more opaque during stronger momentum.
Optional EMA Smoothing:
Includes an option to apply an Exponential Moving Average (EMA) to the main MACD line, which can help smooth out noise and provide clearer signals.
Built-in Divergence Detection:
Automatically scans for classic bullish and bearish divergences between price and the MACD line.
Bullish Divergence: Price makes a lower low, but the MACD line makes a higher low (and is above the zero line).
Bearish Divergence: Price makes a higher high, but the MACD line makes a lower high (and is below the zero line).
These are clearly marked with triangle shapes at the top and bottom of the indicator panel.
Comprehensive Alert Conditions:
The script is pre-configured to generate alert conditions for:
Bullish Crossover (MACD line crosses above Signal line)
Bearish Crossunder (MACD line crosses below Signal line)
Bullish Divergence Detection
Bearish Divergence Detection
This allows traders to set up automated notifications directly within TradingView.
Clear Visual Cues:
The entire indicator's background changes color to signal key events:
Green for a bullish crossover.
Red for a bearish crossunder.
Light Green for a bullish divergence.
Light Red for a bearish divergence.
How to Use the Indicator
Signal Generation:
Crossover: The most common signal. A buy signal occurs when the MACD line crosses above the signal line (especially near or below the zero line). A sell signal occurs when it crosses below.
Zero Line: The MACD line crossing above the zero line is considered bullish, and crossing below is bearish.
Divergence: Divergences can be powerful signals for potential trend reversals. A bullish divergence suggests selling pressure may be exhausting, while a bearish divergence suggests buying pressure may be waning.
Customization for Your Strategy:
If you find the standard MACD too noisy, enable the "Show EMA of MACD" option to smooth the main line.
If you only care about crossovers, you can turn off the histogram and fill to reduce visual clutter.
Use the divergence detection to spot high-probability reversal setups that other traders might miss.
SZO - Signal Zone Oscillator ## Signal Zone Oscillator - SZO
**Created by:** @TraderCurses
**Version:** 1.0 (October 2025)
### ▌ OVERVIEW
The Signal Zone Oscillator (SZO) is a comprehensive momentum tool designed to provide a clearer, more nuanced view of market dynamics. It synthesizes three of the most powerful classic indicators—RSI, a unique MACD Ratio, and the Stochastic oscillator—into a single, unified signal.
The indicator's core feature is the **"Signal Zone"**: a colored area between the main oscillator line and its moving average filter. This zone makes it incredibly easy to visualize shifts in momentum, trends, and potential entry/exit points.
### ▌ KEY FEATURES
* **Composite Formula:** Combines RSI, MACD Ratio, and Stochastic using a weighted average to measure underlying market momentum.
* **The Signal Zone:** The flagship feature. The area between the SZO line and its filter is colored **green** in a bullish context (SZO above filter) and **red** in a bearish context (SZO below filter).
* **Dynamic Coloring:** Both the main SZO line and its filter change color dynamically, providing instant feedback on direction and strength.
* **Zero-Line Reference:** A dashed zero line acts as a classic equilibrium level, helping to confirm stronger bullish or bearish momentum.
* **Fully Customizable:** Every parameter is adjustable. You can change the lengths, sources, and even the weights of the core indicators from the settings menu.
* **Built-in Alerts:** Comes with pre-configured alerts for crossovers of the filter and the zero line, allowing you to automate your monitoring.
### ▌ HOW TO USE IT
The SZO provides several clear signals for traders:
1. **Bullish Signal:**
* The SZO line crosses **above** its filter.
* The Signal Zone turns **green**.
* A cross above the zero line can be used as further confirmation of strong bullish momentum.
2. **Bearish Signal:**
* The SZO line crosses **below** its filter.
* The Signal Zone turns **red**.
* A cross below the zero line can be used as further confirmation of strong bearish momentum.
3. **Divergences:**
* Like any oscillator, look for divergences between the SZO's peaks/troughs and the price action to spot potential reversals.
This tool is designed for traders who want to cut through the noise and get a clear, actionable signal from multiple momentum sources at once. Happy trading!
XAUUSD EMA20/50 + RSI + MACD + ATR Stops(with manual ADX)_VladevThe strategy is that when EMA20 crosses below EMA50 in a downward direction, RSI is below 50, and MACD histogram is in red, I enter a SELL/SHORT position, and vice versa, when EMA20 crosses above EMA50 in an upward direction, the RSI is above 50, and the MACD histogram is green, I enter a BUY/LONG position.
I want you to take a detailed look at my strategy and tell me how you can improve it to make it more successful! Also, give me some ideas on how to position Take Profit and Stop Loss!
Translated with DeepL.com (free version)
XAU_VladevXAUUSD EMA-RSI-MACD ATR Strategy that analyse the chart and by combining Oscillators, EMA's and trend way, strategy creates exact StopLoss and TakeProfit areas
SEVENX Free|SuperFundedSEVENX — Modular Multi-Signal Scanner (SuperFunded)
What it is
SEVENX combines seven classic signals—MACD, OBV, RSI, Stochastics, CCI, Momentum, and an optional ATR volatility filter—into a modular gate. You can toggle each condition on/off, and a BUY/SELL arrow prints only when all enabled conditions agree. Text labels are optional.
Why this is not a simple mashup
・Most “combo” scripts just overlay indicators. SEVENX is a strict consensus engine:
・Each condition is binary and user-switchable.
・The final signal is the logical AND of all enabled checks (no hidden weights).
・Signals fire only on confirmed events (e.g., RSI crossing a level, Stoch K/D cross), which makes entries rule-driven and reproducible.
This yields a transparent, vendor-grade workflow where traders can start simple (2–3 gates) and tighten selectivity by enabling more gates.
How it works (concise)
・MACD: macd_line > signal_line (buy) / < (sell).
・OBV trend: OBV > OBV_MA (buy) / < (sell).
・RSI bounce/drop: crossover(RSI, Oversold) (buy) / crossunder(RSI, Overbought) (sell).
・Stoch cross: %K crosses above %D (buy) / below (sell).
・CCI rebound/pullback: crossover(CCI, -Level) (buy) / crossunder(CCI, +Level) (sell).
・Momentum: Momentum > 0 (buy) / < 0 (sell).
・ATR filter (optional): ATR > ATR_MA must also be true (both sides).
・Final signal: AND of all enabled conditions. If you enable none on a side, that side will not print.
Parameters (UI mapping)
Buy Signal (group: “— Buy Signal —”)
・MACD Golden Cross / OBV Uptrend / RSI Bounce from Oversold / Stochastic Golden Cross / CCI Rebound from Oversold / Momentum > 0 / ATR Volatility Filter (on/off)
Sell Signal (group: “— Sell Signal —”)
・MACD Dead Cross / OBV Downtrend / RSI Drop from Overbought / Stochastic Dead Cross / CCI Pullback from Overbought / Momentum < 0 / ATR Volatility Filter (on/off)
Indicator Settings
・MACD: Fast/Slow/Signal lengths.
・RSI: Length, Overbought/Oversold levels.
・Stochastics: %K length, %D smoothing, overall smoothing.
・CCI: Length, Level (±Level used).
・Momentum: Length.
・OBV: MA length for trend baseline.
・ATR: ATR length, ATR MA length (for the filter).
Display
・Show Text (BUY/SELL text on the markers), Buy/Sell Text Colors.
Practical usage
・Start simple: Enable 2 conditions (e.g., MACD + RSI). If signals are too frequent, add OBV or Momentum; if still frequent, enable ATR filter.
・Mean-reversion vs trend:
・For trend-following, prefer MACD/OBV/Momentum gates.
・For reversal bounces, add RSI/CCI gates and keep Stoch for timing.
・Tuning sensitivity:
・Raise RSI Oversold/Overbought thresholds to make bounces rarer.
・Increase ATR_MA length to smooth the volatility baseline.
・Risk first: Plan SL/TP independently (e.g., structure levels or R-multiples). SEVENX focuses on entry qualification, not exits.
Repainting & confirmation
Signals depend on cross events and are best treated on bar close. Intrabar flips can occur before a bar closes; for strict rules, confirm on closed bars in your strategy.
Disclaimer
No indicator can guarantee outcomes. News, liquidity, and spread conditions can invalidate signals. Trade responsibly and manage risk.
This indicator is being released on a trial basis and may be discontinued at our discretion.
SEVENX — モジュラー型マルチシグナル・スキャナー（日本語）
概要
SEVENXは、MACD / OBV / RSI / ストキャス / CCI / モメンタム / ATRフィルターの7条件を個別オン・オフで制御し、有効化した条件がすべて満たされたときだけBUY/SELL矢印を表示する、合意（AND）型シグナルインジです。テキスト表示も任意。
独自性・新規性
・各条件はブラックボックスではなく明示的なブール判定で、最終シグナルは有効化した条件のAND。
・RSIのレベルクロスやStochのK/Dクロスなど、確定イベントで判定するため、再現性の高いルール運用が可能。少数条件から始めて、必要に応じて段階的に厳格化できます。
動作要点
・MACD：線がシグナル上/下。
・OBV：OBVがOBVのMAより上/下。
・RSI：RSIがOSを上抜け（買い）/OBを下抜け（売り）。
・Stoch：%Kが%Dを上抜け/下抜け。
・CCI：CCIが**−Levelを上抜け**（買い）/+Levelを下抜け（売り）。
・Momentum：0より上/下。
・ATRフィルター（任意）：ATR > ATR_MA を満たすこと（買い/売り共通）。
・最終サイン：有効化した条件のAND。そのサイドで1つも有効化していなければサインは出ません。
実践ヒント
・まずは2条件（例：MACD＋RSI）でテスト → 多すぎるならOBV/MomentumやATRフィルターを追加。
・トレンド重視：MACD/OBV/Momentumを主軸に。
・押し目・戻り目狙い：RSI/CCIを追加、Stochでタイミング調整。
・感度調整：RSIのOB/OSを広げる、ATR_MAを長くする等で厳しめに。
・出口は別設計：SL/TPは価格帯やR倍数などで管理を。
再描画と確定
確定足基準で判断すると安定します。足確定前はクロスが行き来することがあります。
免責
シグナルの機能は保証されません。イベントや流動性で無効化する場合があります。資金管理のうえ自己責任でご利用ください。
このインジケーターは試験公開のため、弊社の裁量で公開を停止する場合があります。
MINE CBPR Pro ✦ v217.1MINE CBPR ✦ Pro is a next-generation universal indicator that combines Channel Breakout structure with Pivot Reversal logic to detect precise turning points across any market. Built for versatility, it adapts seamlessly from stocks and indices to crypto futures, and performs with exceptional precision even on ultra-short timeframes such as the 1-minute and 5-minute charts.
This system integrates advanced volatility filters and structural validation layers to reduce noise and highlight only high-probability reversal signals. Every component has been optimized to balance responsiveness and stability, providing traders with actionable insights in both trending and ranging markets.
Currently undergoing comprehensive backtesting and optimization, MINE CBPR ✦ Pro represents the latest evolution of the MINE series — engineered for traders who demand speed, accuracy, and reliability across all assets and timeframes. We hope you look forward to it.
MagnetOsc Turbo [ZuperView]MagnetOsc Turbo is a dual-timeframe momentum oscillator that identifies overbought and oversold regions with magnetic precision.
Instead of relying on a single timeframe (like RSI or Stochastics), it compares momentum between your main chart and a higher timeframe to confirm when a move is truly overextended or simply pausing.
It works like a magnet:
Like poles repel → Push signal = momentum exhaustion (reversal setup)
Opposite poles attract → Pull signal = short-term reversal within a trend
This multi-timeframe approach helps you read momentum as a conversation between 2 timeframes, not just a number crossing 80 or 20.
📌 Key features
🔸 Dynamic multi-timeframe momentum analysis
MagnetOsc Turbo compares 2 oscillators – one from your current chart and one from a higher timeframe that you define.
You can freely select:
Higher-timeframe type: tick, minute, range, volume, day…
Value ratio: 2×, 3×, 5×, 6×, or 7×…
By comparing momentum from both frames, it helps you avoid false reversals – moments when one chart screams “Overbought” while the higher timeframe still has strength to push further.
Tip:
Use a higher timeframe that’s 4 – 6× larger than your trading chart:
100 Tick → 500 Tick
1 Min → 5 – 10 Min
This keeps your Pull and Push signals balanced and meaningful.
🔸 Threshold levels — Defining OB/OS zones
There are 2 sets of thresholds:
#1: Hidden (for the lower timeframe)
#2: Visible (for the higher timeframe)
These define the Overbought (OB) and Oversold (OS) boundaries.
Default levels (80/20) work for most markets, but:
Tighten zones (70/30) → earlier but more frequent signals.
Widen zones (80/20) → fewer but higher-quality signals.
🔸 Pull & Push signal logic
The magnetic principle drives the signal engine:
Both signal types are generated automatically by analyzing oscillator states across timeframes.
However, for better discipline and clarity, it’s recommended to trade only one signal type (Pull or Push) depending on your style.
🔸 Built-in price-action confirmation
To reduce false entries, each signal is validated against candle behavior using OHLC data.
This allows MagnetOsc Turbo to recognize strong reversal candles and provide earlier, more reliable entries than lagging oscillators.
You’ll notice that Pull/Push signals often align with the first strong candle after momentum disagreement – a high-probability setup many traders miss with basic RSI or Stochastics.
🔸 Clean, intuitive visual interface
The oscillator window is designed for clarity:
Displays both lower- and higher-timeframe momentum in a single panel.
Colored zones visualize attraction or repulsion between timeframes.
On-chart markers show exact signal points.
Toggle Pull/Push signal display as desired.
When both lines and zones share the same color → Attraction (Pull)
When they differ → Repulsion (Push)
You can literally see the magnetic force – an elegant way to understand what’s happening beneath the candles.
📌 Customization
Every market and trader is different, so MagnetOsc Turbo offers deep flexibility:
Choose from 11 types of moving averages for smoothing.
Adjust oscillator period and smoothing length.
Control Signal Split (minimum bars between signals).
Limit the number of signals per OB/OS area via Quantity Per Area.
Fine-tune thresholds (Upper & Lower for both timeframes).
By tweaking these, you can make the indicator more aggressive or conservative.
Examples:
Tight thresholds → more signals, faster reactions (scalpers).
Wider thresholds → fewer but stronger signals (swing traders).
If your chart looks noisy, increase the OSC Period or enable smoothing.
📌 Trading Tips
🔸 Choose your style
Scalpers: focus on Pull signals. These appear more often and align with short bursts of counter-momentum.
Swing traders: focus on Push signals. These highlight exhaustion zones that often precede larger reversals.
🔸 Define your timeframe pair
A good ratio is 1 : 4–6 between your trading and higher timeframe.
Examples:
100 Tick → 400–600 Tick
1 Min → 5–10 Min
🔸 Manage frequency
Use Signal Split and Quantity Per Area to prevent over-signaling.
For example, limit to 2 Pull signals per overbought zone – keeping only the cleanest opportunities.
MagnetOsc Turbo transforms a simple oscillator into a multi-timeframe momentum map.
It shows how lower and higher timeframes attract or repel each other, revealing the true rhythm of market energy.
Sicari Momentum OscillatorSicari Momentum Oscillator (SMO)
What is it?
The Sicari Momentum Oscillator (SMO) is a price–volume momentum framework designed to quantify directional conviction in the market. It measures the acceleration of price movement relative to underlying participation, highlighting when momentum is being confirmed or contradicted by volume flow.
i) Uses exponential moving averages (EMAs) to calculate momentum rather than SMAs for faster response
ii) Identifies bullish and bearish divergences between price and momentum to anticipate exhaustion
iii) Integrates On-Balance Volume (OBV) to map volume momentum in real time
iv) Flags confluence where both price and volume momentum align, signalling stronger continuation potential
How it works
i) When EMAs expand or contract, the histogram adjusts dynamically to visualise the strength and direction of momentum
ii) Divergences appear when price and oscillator move in opposite directions - often preceding local tops or bottoms
iii) OBV is processed through the same EMA structure to produce a clean, comparable momentum curve
iv) Confluence dots appear only when both price and volume momentum agree in direction, marking periods of high-quality momentum
How to use it
i) Combine with the main Sicari indicator to validate directional bias and detect early trend transitions
ii) Watch for divergence to anticipate potential reversals or waning momentum
iii) Confluence dots indicate alignment between price and participation - a signal of underlying market strength or weakness
🟢 Bullish confluence when both price and volume expand upward
🔴 Bearish confluence when both contract in unison
The SMO distills the market’s internal rhythm into a single, adaptive pulse - delivering institutional-grade precision, clarity, and timing within the Sicari ecosystem.
Smart Auto Levels Renko Pro $ [ #Algo ] ( Fx, Alt, Crypto ) : Smart Levels is Smart Trades 🏆
"Smart Auto Levels Renko Pro $ ( Fx, Alt, Crypto ) " indicator is specially designed for " Crypto, Altcoins, Forex pairs, and US exchange" . It gives more power to day traders, pull-back / reverse trend traders / scalpers & trend analysts. This indicator plots the key smart levels , which will be automatically drawn at the session's start or during the session, if specific input is selected.
🔶 Usage and Settings :
A :
⇓ ( *refer 📷 image ) ⇓
B :
⇓ ( *refer 📷 images ) ⇓
🔷 Features :
a : automated smart levels with #algo compatibility.
b : plots Trend strength ▲, and current candle strength count value label.
c : ▄▀ RENKO Emulator engine ( plots *Non-repaintable #renko data as a line chart over the standard chart).
d : session 1st candle's High, Low & 50% levels ( irrespective of chart time-frame ).
e : 1-hour High & Low levels of specific candle ( from the drop-down menu ), for any global
market crypto / altcoins / forex or USA exchange symbols.
f : previous Day / Week / Month, chart High & Low.
g : pivot point levels of the Daily, Weekly & Monthly charts.
h : 2 class types of ⏰ alerts ( only signals or #algo execution ).
i : auto RENKO box size (ATR-based) table for 31 symbols (5 Default non-editable symbols,
6 US exchange symbols, 14 Alt-coins, 6 Forex pairs.)
j : auto processes " daylight saving time 🌓" data and plots accordingly.
💠Note: "For key smart levels, it processes data from a customized time frame, which is not available for the *free Trading View subscription users , and requires a premium plan." By this indicator, you have an edge over the paid subscription plan users and can automatically plot the Non-repaintable RENKO emulator for the current chart on the Trading View free Plan for any time-frame ."
⬇ Take a deep dive 👁️🗨️ into the Smart levels trading Basic Demonstration ⬇
▄▀ 1: "RENKO Emulator Engine" ⭐ , plots a noiseless chart for easy Top/Bottom set-up analysis. 11 types of 💼 asset classes options available in the drop-down menu.
LTP is tagged to the current RSI value ➕ volatility color change for instant quick decisions.
⇓ ( *refer 📷 image ) ⇓
🟣 2: "Trend Strength ▲ Label with color condition.
The strength of the trend will be shown as a number label ( for the current candle ), and the ▲ color format represents the strength of the trend. Can be utilized as an Entry or Exit condition.
⇓ ( *refer 📷 image ) ⇓
🟠 3: plots "Session first candle High, low, and 50%" levels ( irrespective of chart time-frame ), which are critical levels for an intraday trader with add-on levels of Previous Day, Week & Month High and Low levels.
⇓ ( *refer 📷 image ) ⇓
🔵 4: plots "Hourly chart candle" High & Low levels for the specific candles, selected from the drop-down menu with Pivot Points levels of Daily, Weekly, Monthly chart.
⇓ ( *refer 📷 image ) ⇓
🔲 5: "Auto RENKO box size" ( ATR based ) : This indicator is specially designed for 'Renko' trading enthusiasts, where the Box size of the ' Renko chart ' for intraday or swing trading ( ATR based ) , automatically calculated for the selected ( editable ) symbols in the table.
⇓ ( *refer 📷 image ) ⇓
*NOTE :
Table symbols (Non-editable) for 2 USA index, XAU, BTC, ETH.
Symbols (editable) for USA index/stocks.
Table Symbols (editable) for alt-coins.
Table Symbols (editable) for Forex pairs.
⏰ 6: "Alert functions."
⇓ ( *refer 📷 image ) ⇓
◻ : Total 7 signal alerts can be possible in a Single alert.
◻ : Total 10 #algo alerts , ( must ✔ tick the Consent check box for algo execution ).
Note: : alert with RSI ( *manual ✍ input value ) condition.
After selecting alert/alerts ( signals 7 / #algo 10 ), an additional RSI condition can also be used as an input to trigger the alert.
ex: alert = { 🟠 𝟭 Hr 🕯 H & L ➕ ✅ RSI✍ } condition, will trigger the alert when both conditions meet simultaneously.
This Indicator will work like a Trading System . It is different from other indicators, which give Signals only. This script is designed to be tailored to your personal trading style by combining user input components to create your own comprehensive strategy . The synergy between the components is key to its usefulness.
🚀 It focuses on the key Smart Levels and gives you an Extra edge over others.
✅ HOW TO GET ACCESS :
You can see the Author's instructions below to get instant access to this indicator & our premium indicator suites. If you like any of my Invite-Only indicators, kindly DM and let me know!
⚠ RISK DISCLAIMER :
All content provided by "@TradeWithKeshhav" is for informational & educational purposes only.
It does not constitute any financial advice or a solicitation to buy or sell any securities of any type. All investments / trading involve risks. Past performance does not guarantee future results / returns.
Regards :
Team @TradeWithKeshhav
Happy trading and investing!
MTF Advanced DMI [NexusSignals]The MTF Advanced DMI is a multi-timeframe (MTF) enhancement of the classic Directional Movement Index (DMI) and Average Directional Index (ADX) indicator. It provides traders with insights into trend strength, direction, and momentum across multiple timeframes simultaneously. This version of DMI extends the single-timeframe analysis by incorporating two higher timeframes, allowing for better alignment of trends (e.g., confirming a short-term signal with longer-term context). It includes visual plots, a customizable data table showing MTF data, and expanded alert conditions for trend changes, consolidations, and reversals. Ideal for multi-timeframe strategies, trend confirmation, or avoiding false signals in volatile markets.
Key features include:
Multi-Timeframe Analysis: Displays DMI/ADX data for the current chart timeframe, plus two user-defined higher timeframes (e.g., 4H and 1D).
A trend strength metric that quantifies bullish/bearish dominance on each timeframe.
A dynamic table summarizing real-time MTF values, with color-coded signals, arrows, and buy/sell pressure percentages.
Visual fills and arrows for intuitive trend reading.
Built-in alerts for key events, including MTF-specific conditions (note: higher TF alerts may repaint due to live candle calculations via request.security).
How It Works
The indicator calculates DMI/ADX on three timeframes: the current chart TF, a mid-higher TF (default: 4H), and a highest TF (default: 1D).
For each:
+DI (Plus Directional Indicator): Upward movement strength.
-DI (Minus Directional Indicator): Downward movement strength.
ADX: Overall trend strength.
Trend Strength: ((+DI - -DI) / (+DI + -DI)) * ADX – positive for bullish, negative for bearish.
Buy/Sell %: Percentage of buyer/seller control in the candle based on HLC.
Plots focus on the current TF:
Strength Histogram: Color-coded (green bullish, red bearish).
ADX Line: White, with direction arrows.
+DI/-DI Lines: Green/red, with fills above 15 for strong trends.
Horizontal lines at 15 (consolidation) and 25 (strong trend).
The table (optional) shows data for the current timeframe candle, previous current timeframe candle, and the two higher TFs (if different from current), enabling quick cross-TF comparisons.
Inputs
General Settings:
DMI Length (default: 14): Period for +DI/-DI.
ADX Smoothing (default: 14): ADX period.
ADX Consolidation Threshold (default: 15): Low ADX suggests sideways.
ADX Stronger Trend Threshold (default: 25): High ADX indicates strong trends.
Higher Timeframe (default: 240/4H): Mid-level TF for MTF analysis.
Highest Timeframe (default: 1D): Top-level TF for broader context.
Threshold for Strong Bullish/Bearish DMI Strength (defaults: 10 / -10): For strength alerts.
Table Settings:
Show Table? (default: true): Toggle table visibility
Table Text Color, Header Color, Text Size (default: small)
Position (default: middle_right): Customize for your chart
Interpretation
Bullish Alignment: +DI > -DI across TFs, rising +DI (↑), Strength > 0 (green), Buy% > Sell%. Stronger if ADX > 25 on higher TFs.
Bearish Alignment: -DI > +DI, rising -DI (↑), Strength < 0 (red), Sell% > Buy%. Confirm with rising ADX on MTF.
Consolidation: +DI/-DI < 20 and ADX ≤ 15 (blue fill). Check if higher TFs show the same for range-bound confirmation.
Crossovers: +DI above -DI for bullish; reverse for bearish. MTF agreement reduces false signals.
Fills: Highlight dominant trends above 15 (green bullish, maroon bearish).
MTF Insight: Use the table to spot divergences (e.g., bullish current TF but bearish on daily) for potential reversals.
Combine with support/resistance or other momentum oscillators like macd, rsi, stochastic for robust strategies. Test on various assets and TFs to find the best settings that suit your trading style.
Alerts
Includes 20 alert conditions, with MTF extensions (higher TF alerts may repaint – use with caution for live trading):
Strength crossing 0 or bullish/bearish thresholds (on current and higher TFs).
+DI/-DI crossovers (bullish/bearish) on current TF.
ADX above strong threshold.
+DI/-DI above 25 or below 15.
Consolidation detection.
MTF-specific: Strength changes on higher TFs (e.g., "Strength Above Bullish Threshold on TF1").
Configure in TradingView by selecting from the alert dropdown.
Usage Tips
Select higher TFs that suit your strategy (e.g., 1H chart with 4H and Daily for day trading).
Use the table for at-a-glance MTF alignment without switching charts.
Customize appearance to avoid clutter on busy setups.
Backtest thoroughly, especially noting potential repainting on higher TFs.
Adaptive MACD Fusion (Dual-Core Momentum Engine)Adaptive MACD Fusion merges two complementary engines - an *Adaptive MACD Core* and a *Phase Momentum Core* - into a single self-tuning framework.
It’s built for traders who need early, stable, and volatility-aware momentum confirmation without lag or repaint.
Core Architecture
Adaptive MACD Core
Reconstructs classic MACD with z-score normalization and dynamic length adjustment driven by volatility energy.
It adapts automatically between calm and trending regimes for smoother responsiveness.
Volatility Gating System
A logistic ATR-based gate dynamically adjusts signal strength between 0.5 and 1.5.
It suppresses fake impulses during quiet markets and amplifies valid ones in breakouts.
Higher-Timeframe Confirmation
Synchronizes local momentum with higher-timeframe direction using adaptive state decay.
Avoids false reversals by maintaining trend persistence.
Phase Momentum Core
Tracks short-term acceleration/deceleration phases using adaptive EMAs with directional boosts.
Confirms valid shifts and filters market noise — acting as a zero-lag complement to MACD.
Unified Visualization Layer
Merged color logic enables viewing either MACD-only, Phase-only, or combined (Merged) signals in a single visual system.
Key Features
✅ Dual-core adaptive momentum engine
✅ Dynamic volatility weighting
✅ Regime-aware z-score normalization
✅ Persistent higher-timeframe trend memory
✅Multi-mode color & alert system
Conceptual Summary
This is not a cosmetic MACD tweak.
Adaptive MACD Fusion combines structural momentum (MACD) and phase acceleration (short-term engine) to form a coherent adaptive system.
It delivers earlier entries, smoother exits, and consistent cross-regime performance.
Disclosure
This indicator is published as *closed-source* to protect the proprietary adaptive-fusion and volatility-weighting logic.
The architecture, concepts, and functional behavior are fully described above so that traders can understand how it works, how to use it, and what makes it unique — in compliance with TradingView’s House Rules on originality and closed-source publication.
Z-Score Momentum | MisinkoMasterThe Z-Score Momentum is a new trend analysis indicator designed to catch reversals, and shifts in trends by comparing the "positive" and "negative" momentum by using the Z-Score.
This approach helps traders and investors get unique insight into the market of not just Crypto, but any market.
A deeper dive into the indicator
First, I want to cover the "Why?", as I believe it will ease of the part of the calculation to make it easier to understand, as by then you will understand how it fits the puzzle.
I had an attempt to create a momentum oscillator that would catch reversals and provide high tier accuracy while maintaining the main part => the speed.
I thought back to many concepts, divergences between averages?
- Did not work
Maybe a MACD rework?
- Did not work with what I tried :(
So I thought about statistics, Standard Deviation, Z-Score, Sharpe/Sortino/Omega ratio...
Wait, was that the Z-Score? I only tried the For Loop version of it :O
So on my way back from school I formulated a concept (originaly not like this but to that later) that would attempt to use the Z-Score as an accurate momentum oscillator.
Many ideas were falling out of the blue, but not many worked.
After almost giving up on this, and going to go back to developing my strategies, I tried one last thing:
What if we use divergences in the average, formulated like a Z-score?
Surprise-surprise, it worked!
Now to explain what I have been so passionately yapping about, and to connect the pieces of the puzzle once and for all:
The indicator compares the "strength" of the bullish/bearish factors (could be said differently, but this is my "speach bubble", and I think this describes it the best)
What could we use for the "bullish/bearish" factors?
How about high & low?
I mean, these are by definitions the highest and lowest points in price, which I decided to interpret as: The highest the bull & bear "factors" achieved that bar.
The problem here is comparison, I mean high will ALWAYS > low, unless the asset decided to unplug itself and stop moving, but otherwise that would be unfair.
Now if I use my Z-score, it will get higher while low is going up, which is the opposite of what I want, the bearish "factor" is weaker while we go up!
So I sat on my ret*rded a*s for 25 minutes, completly ignoring the fact the number "-1" exists.
Surprise surprise, multiplying the Z-Score of the low by -1 did what I wanted!
Now it reversed itself (magically). Now while the low keeps going down, the bear factor increases, and while it goes up the bear factor lowers.
This was btw still too noisy, so instead of the classic formula:
a = current value
b = average value
c = standard deviation of a
Z = (a-b)/c
I used:
a = average value over n/2 period
b = average value over n period
c = standard deviation of a
Z = (a-b)/c
And then compared the Z-Score of High to the Z-Score of Low by basic subtraction, which gives us final result and shows us the strength of trend, the direction of the trend, and possibly more, which I may have not found.
As always, this script is open source, so make sure to play around with it, you may uncover the treasure that I did not :)
Enjoy Gs!
RSI VWAP v1 [JopAlgo]RSI VWAP v1.1 made stronger by volume-aware!
We know there's nothing new and the original RSI already does an excellent job. We're just working on small, practical improvements – here's our take: The same basic idea, clearer display, and a single, specially developed rolling line: a VWAP of the RSI that incorporates volume (participation) into the calculation.
Do you prefer the pure classic?
You can still use Wilder or Cutler engines –
but the star here is the VW-RSI + rolling line.
This RSI also offers the possibility of illustrating a possible
POC (Point of Control - or the HAL or VAL) level.
However, the indicator does NOT plot any of these levels itself.
We have included an illustration in the chart for this!
We hope this version makes your decision-making easier.
What you’ll see
The RSI line with a 50 midline and optional bands: either static 70/30 or adaptive μ±k·σ of the Rolling Line.
One smoothing concept only: the Rolling Line (light blue) = VWAP of RSI.
Shadow shading between RSI and the Rolling Line (green when RSI > line, red when RSI < line).
A lighter tint only on the parts of that shadow that sit above the upper band or below the lower band (quick overbought/oversold context).
Simple divergence lines drawn from RSI pivots (green for regular bullish, red for regular bearish). No labels, no buy/sell text—kept deliberately clean.
What’s new, and why it helps
VW-RSI engine (default):
RSI can be computed from volume-weighted up/down moves, so momentum reflects how much traded when price moved—not just the direction.
Rolling Line (VWAP of RSI) with pure VWAP adaptation:
Low volume: blends toward a faster VWAP so early, thin starts aren’t missed.
Volume spikes: blends toward a slower VWAP so a single heavy bar doesn’t whip the curve.
You can reveal the Base Rolling (pre-adaptation) line to see exactly how much adaptation is happening.
Adaptive bands (optional):
Instead of fixed 70/30, use mean ± k·stdev of the Rolling Line over a lookback. Levels breathe with the market—useful in strong trends where static bounds stay pinned.
Minimal, readable panel:
One smoothing, one story. The shadow tells you who’s in control; the lighter highlight shows stretch beyond your lines.
How to read it (fast)
Bias: RSI above 50 (and a rising Rolling Line) → bullish bias; below 50 → bearish bias.
Trigger: RSI crossing the Rolling Line with the bias (e.g., above 50 and crossing up).
Stretch: Near/above the upper band, avoid chasing; near/below the lower band, avoid panic—prefer a cross back through the line.
Divergence lines: Use as context, not as standalone signals. They often help you wait for the next cross or avoid late entries into exhaustion.
Settings that actually matter
RSI Engine: VW-RSI (default), Wilder, or Cutler.
Rolling Line Length: the VWAP length on RSI (higher = calmer, lower = earlier).
Adaptive behavior (pure VWAP):
Speed-up on Low Volume → blends toward fast VWAP (factor of your length).
Dampen Spikes (volume z-score) → blends toward slow VWAP.
Fast/Slow Factors → how far those fast/slow variants sit from the base length.
Bands: choose Static 70/30 or Adaptive μ±k·σ (set the lookback and k).
Visuals: show/hide Base Rolling (ref), main shadow, and highlight beyond bands.
Signal gating: optional “ignore first bars” per day/session if you dislike open noise.
Starter presets
Scalp (1–5m): RSI 9–12, Rolling 12–18, FastFactor ~0.5, SlowFactor ~2.0, Adaptive on.
Intraday (15m–1H): RSI 10–14, Rolling 18–26, Bands k = 1.0–1.4.
Swing (4H–1D): RSI 14–20, Rolling 26–40, Bands k = 1.2–1.8, Adaptive on.
Where it shines (and limits)
Best: liquid markets where volume structure matters (majors, indices, large caps).
Works elsewhere: even with imperfect volume, the shadow + bands remain useful.
Limits: very thin/illiquid assets reduce the benefit of volume-weighting—lengthen settings if needed.
Attribution & License
Based on the concept and baseline implementation of the “Relative Strength Index” by TradingView (Pine v6 built-in).
Released as Open-source (MPL-2.0). Please keep the license header and attribution intact.
Disclaimer
For educational purposes only; not financial advice. Markets carry risk. Test first, use clear levels, and manage risk. This project is independent and not affiliated with or endorsed by TradingView.
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.
💸 Monetary Momentum Oscillator (MMO)Monetary Momentum Oscillator (MMO)
The Monetary Momentum Oscillator (MMO) measures the rate of change in the money supply (like M2, Fed Balance Sheet, or similar macro series) and applies a momentum-based RSI calculation to visualize liquidity acceleration and deceleration.
💡 Purpose:
MMO is designed for macro-level analysis — it identifies when monetary expansion is overheating (potential inflation or risk-on conditions) and when contraction is cooling off (liquidity tightening or deflationary stress).
📊 How It Works:
Calculates the percentage change of the selected data source over a chosen lookback period.
Applies an RSI transformation to visualize momentum extremes.
Overlays signal smoothing and highlights overheat/cooldown zones.
🔍 Interpretation:
Above 70 → Liquidity acceleration / overheating (potential inflationary impulse).
Below 30 → Liquidity deceleration / contraction (risk-off, tightening).
Crossovers → Momentum shifts that often precede macro trend reversals in risk assets.
⚙️ Best Used On:
Macroeconomic series such as M2SL, M2V, WALCL, or custom liquidity indexes.
Long-term charts (weekly or monthly) for detecting major monetary regime transitions.
🧩 Core Idea:
Liquidity is the real market engine — this oscillator quantifies its pulse.
Directional Indicator Crossovers v1[JopAlgo]Directional Indicator Crossovers v1 — the classic DMI, made clearer and easier to act on
We'd like to introduce you to a more relaxed, streamlined version of DI. While it may not seem like it at first glance, we've taken the D+/D- method as a starting point and developed our own version of this indicator: two lines, a smooth green/red field indicating who's in control, and clear crossover alerts for a flip. We deliberately chose the step line representation because it closely matches the candlestick patterns on the chart. Designed to help you react faster—without clutter.
What you’ll see
+DI (green) and −DI (red) using classic Wilder smoothing.
A soft control zone between the lines: green when +DI dominates, red when −DI dominates.
Crossover alerts (no labels, no background flooding)—just the turning points.
Why this helps
Instant bias: the shaded field tells you who’s in control without reading values.
Cleaner execution: minimal visuals keep focus on the handoff (+DI↔−DI) and your price levels.
Actionable by design: built-in alerts fire right at the flip to route into your workflow.
How to read it
Bias: Green zone → buyers lead. Red zone → sellers lead.
Trigger: Consider entries on the DI crossover that aligns with your higher-timeframe context (trend, S/R, OB).
Patience in chop: If flips are frequent in tight ranges, wait for sustained zone dominance or confirm on a higher TF.
Exit/flip: Opposite crossover or a clear loss of dominance.
Settings that matter
DI Length (default 14): Higher = calmer, fewer flips. Lower = faster, more signals.
Visuals: Keep the control zone on for quick reads; hide crossover marks if you prefer pure lines.
Alerts: Enable bullish and bearish DI cross alerts; connect to notifications or webhooks as needed.
Starter presets
Intraday (15m–1H): DI Length 12–14 for quicker handoffs.
Swing (4H–1D): DI Length 14–20 for cleaner signals.
Choppy assets: Nudge length higher to dampen noise.
Where it shines (and limits)
Best: Liquid markets (crypto majors, indices, large caps) where handoffs matter.
Works elsewhere: Still useful on slower pairs; extend length for stability.
Limit: Frequent flips in low-range sessions—pair with HTF bias or structure.
Alerts included
Bullish DI Crossover: +DI crosses above −DI.
Bearish DI Crossover: −DI crosses above +DI.
Attribution & License
Built on the Directional Movement Index concept by J. Welles Wilder Jr. (1978).
Independent Pine v6 implementation (not derived from TradingView’s built-in source).
Released as Open Source (MPL-2.0)—please keep the license header intact.
Disclaimer
For educational purposes only; not financial advice. Trading involves risk. Test first, use clear levels, and manage risk. This project is independent and not affiliated with or endorsed by TradingView.
Last Candle of Hour Highlighter (M1 + M5)Highlights the last candle of every hour on 1-minute (M1) and 5-minute (M5) charts, making it easier to spot session closes, breakouts, and end-of-hour price action at a glance.
Detailed Description / How to Use:
This indicator automatically detects the last candle of each hour and changes its colour for quick visual reference. It’s designed for traders who use short-term timeframes (M1, M5) and want a clean visual cue for hourly closes.
Features:
• Automatically detects M1 and M5 timeframes.
• Highlights the last candle of each hour with a customisable colour.
• Optional Bull/Bear mode: colour changes depending on candle direction.
• Simple and lightweight — does not affect chart performance.
Inputs / Settings:
1. Color by Bull/Bear – Toggle on to automatically colour the last candle green (bullish) or red (bearish) based on its close relative to the open.
2. Highlight Colour – Choose a single colour if Bull/Bear mode is off.
3. Bullish Colour – Choose the colour for bullish last candles.
4. Bearish Colour – Choose the colour for bearish last candles.
Usage Tips:
• Works best on 1-minute and 5-minute charts.
• Ideal for spotting end-of-hour reversals, breakout candles, and momentum shifts.
• Can be combined with other indicators like support/resistance or moving averages for more advanced strategies.
AlphaTrend - Medium Term Trend Probability Indicator on TOTALESWHAT IS ALPHATREND?
AlphaTrend is a consensus-based trend identification system that combines 7 independent trend detection methodologies into a single probability score. Designed for medium-term trading (days to weeks), it aggregates diverse analytical approaches—from volatility-adjusted moving averages to statistical oscillators—to determine directional bias with quantifiable confidence.
Unlike single-indicator systems prone to false signals during consolidation, AlphaTrend requires majority agreement across multiple uncorrelated methods before generating directional signals, significantly reducing whipsaws in choppy markets.
METHODOLOGY - THE 7-INDICATOR VOTING SYSTEM
Each indicator analyzes trend from a mathematically distinct perspective and casts a vote: +1 (bullish), -1 (bearish), or 0 (neutral). The average of all 7 votes creates the final probability score ranging from -1 (strong bearish) to +1 (strong bullish).
1. FLXWRT RMA (VOLATILITY-ADJUSTED BASELINE)
Method: RMA (Running Moving Average) with ATR-based dynamic bands
Calculation:
RMA = Running MA of price over 12 periods
ATR = Average True Range over 20 periods
Long Signal: Price > RMA + ATR
Short Signal: Price < RMA - ATR
Logic: Trend confirmed only when price breaks beyond volatility-adjusted boundaries, not just the moving average itself. This filters noise by requiring momentum sufficient to overcome recent volatility.
Why it works: Standard MA crossovers generate excessive false signals in ranging markets. Adding ATR bands ensures price has genuine directional momentum, not just minor fluctuations.
Settings:
RMA Length (12): Base trend smoothing
ATR Length (20): Volatility measurement period
2. BOOSTED MOVING AVERAGE (MOMENTUM-ENHANCED TREND)
Method: Double EMA with acceleration boost factor
Calculation:
EMA1 = EMA(close, length)
EMA2 = EMA(close, length/2) // Faster EMA
Boosted Value = EMA2 + sensitivity × (EMA2 - EMA1)
Final = EMA smoothing of Boosted Value
Logic: Amplifies the difference between fast and slow EMAs to emphasize trend momentum. The boost factor (1.3) accelerates response to directional moves while subsequent smoothing prevents over-reaction.
Why it works: Traditional MAs lag price action. The boost mechanism projects trend direction forward by amplifying the momentum differential between two EMAs, providing earlier signals without sacrificing reliability.
Settings:
Length (36): Base EMA period
Boost Factor (1.3): Momentum amplification multiplier
Originality: This is a proprietary enhancement to standard double EMA systems. Most indicators simply cross fast/slow EMAs; this one mathematically projects momentum trajectory.
3. HEIKIN ASHI TREND (T3-SMOOTHED CANDLES)
Method: Heikin Ashi candles with T3 exponential smoothing
Calculation:
Heikin Ashi candles = Smoothed OHLC transformation
T3 Smoothing = Triple-exponential smoothing (Tillson T3)
Signal: T3(HA_Open) crosses T3(HA_Close)
Logic: Heikin Ashi candles filter intrabar noise by averaging consecutive bars. T3 smoothing adds additional filtering using Tillson's generalized DEMA algorithm with custom volume factor.
Why it works: Regular candlesticks contain high-frequency noise. Heikin Ashi transformation creates smoother trends, and T3 smoothing eliminates remaining whipsaws while maintaining responsiveness. The T3 algorithm specifically addresses the lag-vs-smoothness tradeoff.
Settings:
T3 Length (13): Smoothing period
T3 Factor (0.3): Volume factor for T3 algorithm
Percent Squeeze (0.2): Sensitivity adjustment
Technical Note: T3 is superior to simple EMA smoothing because it applies the generalized DEMA formula recursively, reducing lag while maintaining smooth output.
4. VIISTOP (ATR-BASED TREND FILTER)
Method: Simple trend detection using price position vs smoothed baseline with ATR confirmation
Calculation:
Baseline = SMA(close, 16)
ATR = ATR(16)
Uptrend: Close > Baseline
Downtrend: Close < Baseline
Logic: The simplest component—pure price position relative to medium-term average. While basic, it provides a "sanity check" against over-optimized indicators.
Why it works: Sometimes the simplest approach is most robust. In strong trends, price consistently stays above/below its moving average. This indicator prevents the system from over-complicating obvious directional moves.
Settings:
Length (16): Baseline period
Multiplier (2.8): ATR scaling (not actively used in vote logic)
Purpose in Ensemble: Provides grounding in basic trend logic. Complex indicators can sometimes generate counterintuitive signals; ViiStop ensures the system stays aligned with fundamental price positioning.
5. NORMALIZED KAMA OSCILLATOR (ADAPTIVE EFFICIENCY-BASED TREND)
Method: Kaufman Adaptive Moving Average normalized to oscillator format
Calculation:
Efficiency Ratio = |Close - Close | / Sum(|Close - Close |, 8)
Smoothing Constant = ER × (Fast SC - Slow SC) + Slow SC
KAMA = Adaptive moving average using dynamic smoothing
Normalized = (KAMA - Lowest) / (Highest - Lowest) - 0.5
Logic: KAMA adjusts its smoothing speed based on market efficiency. In trending markets (high efficiency), it speeds up. In ranging markets (low efficiency), it slows down. Normalization converts absolute values to -0.5/+0.5 oscillator for consistent voting.
Why it works: Fixed-period moving averages perform poorly across varying market conditions. KAMA's adaptive nature makes it effective in both trending and choppy environments by automatically adjusting its responsiveness.
Settings:
Fast Period (9): Maximum responsiveness
Slow Period (21): Minimum responsiveness
ER Period (8): Efficiency calculation window
Normalization Lookback (35): Oscillator scaling period
Mathematical Significance: Kaufman's algorithm is one of the most sophisticated adaptive smoothing methods in technical analysis. The Efficiency Ratio mathematically quantifies trend strength vs noise.
6. LÉVY FLIGHT RSI (HEAVY-TAILED MOMENTUM)
Method: Modified RSI using Lévy distribution weighting for gains/losses
Calculation:
Weighted Gain = (Max(Price Change, 0))^Alpha
Weighted Loss = (-Min(Price Change, 0))^Alpha
RSI = 100 - (100 / (1 + RMA(Gain) / RMA(Loss)))
Centered RSI = RSI - 50
Logic: Standard RSI treats all price changes linearly. Lévy Flight RSI applies power-law weighting (Alpha = 1.5) to emphasize larger moves, modeling heavy-tailed distributions observed in real market data.
Why it works: Market returns exhibit "fat tails"—large moves occur more frequently than normal distribution predicts. Lévy distributions (Alpha between 1-2) better model this behavior. By weighting larger price changes more heavily, this RSI variant becomes more sensitive to genuine momentum shifts while filtering small noise.
Settings:
RSI Length (14): Standard period
Alpha (1.5): Lévy exponent (1=linear, 2=quadratic)
MA Length (12): Final smoothing
Originality: Standard RSI uses unweighted gains/losses. This implementation applies stochastic process theory (Lévy flights) from quantitative finance to create a momentum indicator more aligned with actual market behavior.
Mathematical Background: Lévy flights describe random walks with heavy-tailed step distributions, observed in financial markets, animal foraging patterns, and human mobility. Alpha=1.5 balances between normal distribution (Alpha=2) and Cauchy distribution (Alpha=1).
7. REGULARIZED-MA OSCILLATOR (Z-SCORED TREND DEVIATION)
Method: Moving average converted to z-score oscillator
Calculation:
MA = EMA(close, 19)
Mean = SMA(MA, 30)
Std Dev = Standard Deviation(MA, 30)
Z-Score = (MA - Mean) / Std Dev
Logic: Converts absolute MA values to statistical standard deviations from mean. Positive z-score = MA above its typical range (bullish), negative = below range (bearish).
Why it works: Raw moving averages don't indicate strength—a 50-day MA at $50k vs $60k has no contextual meaning. Z-scoring normalizes this to "how unusual is current MA level?" This makes signals comparable across different price levels and time periods.
Settings:
Length (19): Base MA period
Regularization Length (30): Statistical normalization window
Statistical Significance: Z-scores are standard in quantitative analysis. This indicator asks: "Is the current trend statistically significant or just random noise?"
AGGREGATION METHODOLOGY
Voting System:
Each indicator returns: +1 (bullish), -1 (bearish), or 0 (neutral)
Total Score = Sum of all 7 votes (-7 to +7)
Average Score = Total / 7 (-1.00 to +1.00)
Signal Generation:
Long Signal: Average > 0 (majority bullish)
Short Signal: Average < 0 (majority bearish)
Neutral: Average = 0 (perfect split or all neutral)
Why Equal Weighting:
Each indicator represents a fundamentally different analytical approach:
Volatility-adjusted (RMA, ViiStop)
Momentum-based (Boosted MA, Lévy RSI)
Adaptive smoothing (KAMA)
Statistical (MA Oscillator)
Noise-filtered (Heikin Ashi T3)
Equal weighting ensures no single methodology dominates. This diversification reduces bias and improves robustness across market conditions.
ORIGINALITY - WHY THIS COMBINATION WORKS
Traditional Multi-Indicator Approaches:
Combine similar indicators (multiple MAs, multiple oscillators)
Use arbitrary thresholds for each indicator
Don't normalize signals (hard to compare RSI to MACD)
Often just "if RSI > 70 AND MACD > 0 = buy"
AlphaTrend MTPI Innovations:
Methodological Diversity: Includes volatility-adaptive (RMA), momentum-enhanced (Boosted MA), efficiency-based (KAMA), heavy-tailed statistics (Lévy RSI), and smoothed candles (HA). No redundant indicators.
Binary Voting: Each indicator reduces to simple +1/-1/0 vote, making aggregation transparent and preventing any indicator from overwhelming the consensus.
Medium-Term Optimization: Parameter choices (12-36 period averages) specifically target multi-day to multi-week trends, not scalping or long-term positioning.
Advanced Mathematics: Incorporates Tillson T3, Kaufman Efficiency Ratio, Lévy distributions, and statistical z-scoring—not just basic MAs and RSIs.
No Overfit Risk: With 7 diverse components voting equally, the system can't overfit to any specific market regime. If trending markets favor KAMA, but choppy markets favor Boosted MA, the ensemble stays robust.
Why 7 Indicators, Not 3 or 10:
Fewer than 5: Insufficient diversification, single indicator failures impact results heavily
More than 9: Diminishing returns, redundancy increases, computational load grows
7 provides: Odd number (no ties), sufficient diversity, manageable complexity
VISUAL COMPONENTS
1. Bar Coloring:
Cyan bars: Bullish consensus (average score > 0)
Magenta bars: Bearish consensus (average score < 0)
No color: Neutral (score = 0 or date filter disabled)
2. MTPI Summary Table (Bottom Center):
MTPI Signal: Current directional bias (LONG/SHORT/NEUTRAL)
Average Score: Precise consensus reading (-1.00 to +1.00)
3. Indicator Status Table (Bottom Right):
Shows all 7 individual indicator scores
Score column: +1 (bullish), -1 (bearish), 0 (neutral)
Signal column: Text interpretation of each vote
Color-coded cells: Cyan (long), Magenta (short), Gray (neutral)
HOW TO USE
For Swing Trading (Recommended - Days to Weeks):
Entry Signals:
Strong Long: 5+ indicators bullish (score ≥ 0.71)
Standard Long: 4+ indicators bullish (score ≥ 0.57)
Weak Long: Simple majority (score > 0) — use with caution
Exit Signals:
Hard Stop: Score flips negative (consensus reverses)
Partial Take Profit: Score drops to +0.30 or below (weakening)
Trailing Stop: Use ATR-based stop below entry
Position Sizing:
Strong signals (|score| > 0.7): Full position
Moderate signals (0.4-0.7): 50-75% position
Weak signals (< 0.4): 25-50% or skip
For Trend Confirmation:
Use alongside your primary strategy for confluence
Only take trades when AlphaTrend agrees with your analysis
Avoid counter-trend trades when score is extreme (|score| > 0.7)
Best Timeframes:
4H: Primary timeframe for swing trading
1D: Position trading and major trend identification
1H: Active trading (shorter hold periods)
< 1H: Not recommended (designed for medium-term)
Market Conditions:
Trending markets: System excels (consensus emerges quickly)
Ranging markets: Expect mixed signals (score oscillates near zero)
High volatility: RMA and ViiStop provide stabilization
Low volatility: KAMA and Boosted MA maintain responsiveness
SETTINGS EXPLAINED
General Settings:
Use Date Filter: Enable/disable historical backtesting range
Start Date: When to begin signal generation (default: Jan 1, 2018)
Flxwrt RMA Settings:
RMA Length (12): Base trend smoothing
ATR Length (20): Volatility measurement period
Source: Price input (default: close)
Boosted MA Settings:
Length (36): Base EMA period
Boost Factor (1.3): Momentum amplification
Source: Price input
Heikin Ashi Settings:
Percent Squeeze (0.2): Sensitivity adjustment
T3 Factor (0.3): Tillson volume factor
T3 Length (13): Smoothing period
ViiStop Settings:
Length (16): Baseline period
Multiplier (2.8): ATR scaling
Source: Price input
KAMA Settings:
Fast Period (9): Maximum responsiveness
Slow Period (21): Minimum responsiveness
ER Period (8): Efficiency calculation
Normalization Lookback (35): Oscillator scaling
Levy RSI Settings:
RSI Length (14): Standard period
Alpha (1.5): Lévy exponent (power-law weighting)
MA Length (12): Final smoothing
Source: Price input
MA Oscillator Settings:
Length (19): Base MA period
Regularize Length (30): Z-score normalization window
PERFORMANCE CHARACTERISTICS
Strengths:
✅ Reduced whipsaws vs single indicators
✅ Works across varying market conditions (adaptive components)
✅ Transparent methodology (see every vote)
✅ Customizable to trading style via timeframe selection
✅ No curve-fitting (equal weighting, no optimization)
Limitations:
⚠️ Medium-term focus (not for scalping or very long-term)
⚠️ Lagging by design (consensus requires confirmation)
⚠️ Less effective in violent reversals (momentum carries votes)
⚠️ Requires clean price data (gaps/thin volume can distort)
ALERTS & AUTOMATION
No built-in alerts in current version (visual-only indicator). Users can create custom alerts based on:
Bar color changes (cyan to magenta or vice versa)
Average score crossing above/below thresholds
Specific indicator status changes in the table
BEST PRACTICES
Risk Management:
Never risk more than 1-2% per trade regardless of score
Use stop losses (ATR-based recommended)
Scale positions based on signal strength
Don't average down on losing positions
Combining with Other Analysis:
✅ Support/Resistance levels for entries
✅ Volume confirmation (accumulation/distribution)
✅ Market structure (higher highs/lower lows)
✅ Volatility regimes (adjust position size)
❌ Don't combine with redundant trend indicators (adds no value)
❌ Don't override strong consensus with gut feeling
❌ Don't use on news-driven spikes (wait for stabilization)
Backtesting Notes:
Use "Date Filter" to test specific periods
Forward-test before live deployment
Remember: consensus systems perform best in trending markets, expect reduced edge in ranges
IMPORTANT NOTES
Not a standalone strategy - Use with proper risk management
Requires clean data - Works best on liquid markets with tight spreads
Medium-term by design - Don't expect scalping signals
No magic - No indicator predicts the future; this shows current trend probability
Diversification within - The 7-component ensemble IS the diversification strategy
Not financial advice. This indicator identifies medium-term trend probability based on multi-component consensus. Past performance does not guarantee future results. Always use proper risk management and position sizing.
AlphaZ-Score - Bitcoin Market Cycle IndicatorWHAT IS ALPHAZ-SCORE?
AlphaZ-Score is a Bitcoin-specific market cycle indicator that identifies extreme market conditions (tops and bottoms) by aggregating up to 7 independent on-chain and market metrics into a single normalized z-score. Unlike traditional oscillators that analyze only price action, AlphaZ-Score incorporates blockchain fundamentals, investor profitability metrics, and capital flow data to determine where Bitcoin sits within its long-term market cycle.
The output ranges from -3 (extreme oversold/cycle bottom) to +3 (extreme overbought/cycle top), with readings beyond ±2 indicating high-probability reversal zones.
METHODOLOGY - THE 7-COMPONENT SYSTEM
Each component analyzes Bitcoin's market state from a unique perspective, then gets z-scored (statistical normalization) so all metrics can be compared on equal footing. The final score is a weighted average of all enabled indicators.
Default Configuration (3 indicators enabled):
Stablecoin Supply Ratio (SSRO)
MVRV Z-Score
SOPR Z-Score
Optional Advanced Components (4 indicators disabled by default):
Days Higher Streak Valuation (DHSV)
High Probability OB/OS (HPOB)
Risk Index Z-Score
Comprehensive On-chain Z-Score
COMPONENT BREAKDOWN
1. STABLECOIN SUPPLY RATIO OSCILLATOR (SSRO) - ENABLED BY DEFAULT
What it measures: Ratio of Bitcoin market cap to total stablecoin supply (USDT + USDC)
Data sources:
CRYPTOCAP:BTC - Bitcoin market cap
CRYPTOCAP:USDT - Tether market cap
CRYPTOCAP:USDC - USD Coin market cap
Logic:
SSR = BTC Market Cap / (USDT + USDC Supply)
Z-Score = Standardized SSR over 200 periods
Interpretation:
High SSR (positive z-score): Bitcoin overvalued relative to available stablecoin buying power → Overbought
Low SSR (negative z-score): Massive stablecoin reserves relative to BTC value → Potential bottom (dry powder)
Why it works: Stablecoins represent "dry powder" - capital waiting to enter crypto. When stablecoin supply is high relative to BTC value, it signals accumulation potential. When low, it suggests exhausted buying power.
2. MVRV Z-SCORE - ENABLED BY DEFAULT
What it measures: Market Value to Realized Value ratio, z-scored over 520 periods
Data source: INTOTHEBLOCK:BTC_MVRV
Logic:
MVRV = Market Cap / Realized Cap
Z-Score = (MVRV - Mean) / Std Dev
Interpretation:
High MVRV (positive z-score): Average holder in significant profit → Distribution phase
Low MVRV (negative z-score): Average holder near breakeven/loss → Accumulation phase
Why it works: MVRV compares Bitcoin's market price to its "fair value" (realized price = average cost basis of all coins). Extreme deviations historically mark cycle tops (MVRV > 3.5) and bottoms (MVRV < 1.0).
Historical significance:
2017 top: MVRV z-score ~7
2018 bottom: MVRV z-score ~-1.5
2021 top: MVRV z-score ~6
2022 bottom: MVRV z-score ~-1.0
3. SOPR Z-SCORE - ENABLED BY DEFAULT
What it measures: Spent Output Profit Ratio, smoothed and z-scored
Data source: GLASSNODE:BTC_SOPR
Logic:
SOPR = Value of spent outputs / Value at creation
SOPR EMA = 7-period exponential moving average
Z-Score = Standardized SOPR EMA over 180 periods
Interpretation:
SOPR > 1 (positive z-score): Coins being spent at profit → Potential distribution
SOPR < 1 (negative z-score): Coins being spent at loss → Capitulation/bottom
Why it works: SOPR measures aggregate profitability of spent coins. When holders are forced to sell at losses (SOPR < 1), it indicates capitulation and potential bottoms. When everyone sells at profit (SOPR >> 1), it signals euphoria and potential tops.
4. DAYS HIGHER STREAK VALUATION (DHSV) - DISABLED BY DEFAULT
What it measures: Number of historical bars with prices higher than current level
Logic:
For last N bars, count how many had close > current close
Apply streak decay logic based on price threshold
Z-Score result over lookback period
Interpretation:
Few days higher (negative z-score): Price near all-time highs → Potential overbought
Many days higher (positive z-score): Price deep below historical levels → Oversold
Why it works: Measures how "expensive" current price is relative to history. When 90%+ of historical bars are higher, you're near cycle bottoms.
Settings:
Historical Bars (1000): How far back to look
Threshold & Decay: Sensitivity adjustments
5. HIGH PROBABILITY OVERBOUGHT/OVERSOLD (HPOB) - DISABLED BY DEFAULT
What it measures: Volume-weighted price momentum divergence
Logic:
Volume-weighted Hull MA vs Standard Hull MA
Difference normalized by 100-period SMA
Result inverted and scaled to match z-score range
Interpretation:
Positive score: Volume-weighted momentum diverging up → Overbought
Negative score: Volume-weighted momentum diverging down → Oversold
Why it works: When volume-weighted price movement diverges from standard price movement, it reveals institutional vs retail behavior mismatches.
Settings:
SVWHMA Length (50): Volume-weighted smoothing
HMA Length (50): Standard momentum baseline
Smooth Length (50): Final output smoothing
6. RISK INDEX Z-SCORE - DISABLED BY DEFAULT
What it measures: Modified Puell Multiple approach using realized cap
Data sources:
COINMETRICS:BTC_MARKETCAPREAL - Realized market cap
GLASSNODE:BTC_MARKETCAP - Current market cap
Logic:
Delta = Risk Multiplier × Realized Cap - Historical Realized Cap
Risk Index = (Delta / Market Cap × 100) / 24
Z-Score = Standardized Risk Index over 1500 periods
Interpretation:
High risk (positive z-score): Realized cap growth outpacing market cap → Overextended
Low risk (negative z-score): Market cap collapsed relative to realized cap → Undervalued
Why it works: Compares the rate of realized cap change to market cap. Rapid realized cap growth during low market cap periods signals accumulation.
7. COMPREHENSIVE ON-CHAIN Z-SCORE - DISABLED BY DEFAULT
What it measures: Average of three on-chain metrics: NUPL, SOPR, and MVRV
Data sources:
GLASSNODE:BTC_MARKETCAP - Current market cap
COINMETRICS:BTC_MARKETCAPREAL - Realized cap
GLASSNODE:BTC_SOPR - SOPR data
Logic:
NUPL = (Market Cap - Realized Cap) / Market Cap × 100
SOPR Z-Score = (SOPR - Mean) / Std Dev with EMA smoothing
MVRV = Market Cap / Realized Cap
Final Score = Average of all three z-scores
Interpretation:
Combines profitability (NUPL), spending behavior (SOPR), and valuation (MVRV) into single comprehensive on-chain metric.
AGGREGATION METHODOLOGY
Scoring System:
Each enabled indicator produces a z-score (typically -3 to +3 range)
Scores are weighted equally (weight = 1.0 for all)
Final output = Weighted average of all enabled indicators
Why Equal Weighting:
Each metric analyzes fundamentally different aspects of Bitcoin's market state. Equal weighting prevents any single data source from dominating and ensures diversification.
Customization:
Users can enable/disable indicators to:
Simplify analysis (3 core metrics)
Increase complexity (all 7 metrics)
Focus on specific aspects (only on-chain, only market-based, etc.)
INTERPRETATION GUIDE
Z-Score Ranges:
+3.0 and above - EXTREME OVERBOUGHT
Historical cycle tops
Maximum euphoria
High-probability distribution zone
Consider taking profits
+2.0 to +3.0 - OVERBOUGHT
Late bull market phase
Elevated risk
Cautious positioning recommended
-2.0 to +2.0 - NEUTRAL
Normal market conditions
Trend-following strategies appropriate
-2.0 to -3.0 - OVERSOLD
Early accumulation phase
Fear/capitulation stage
Begin DCA strategies
-3.0 and below - EXTREME OVERSOLD
Historical cycle bottoms
Maximum fear
High-probability accumulation zone
Prime buying opportunity
VISUAL COMPONENTS
1. Main Z-Score Line:
Dynamic color gradient based on value
Green shades: Oversold (buying opportunity)
Red shades: Overbought (distribution zone)
White: Neutral
2. Reference Lines:
0: Neutral baseline
±2: Overbought/Oversold thresholds
±3: Extreme zones (highest probability reversals)
3. Background Shading:
Light green: Oversold (-2 to -3)
Bright green: Extreme oversold (< -3)
Light red: Overbought (+2 to +3)
Bright red: Extreme overbought (> +3)
4. Bar Coloring:
Cyan bars: Oversold conditions
Red bars: Overbought conditions
Default: Neutral
5. Summary Table (Top Right):
Market State: Current condition (Extreme OB/OS, Overbought/Oversold, Neutral)
Z-Score Value: Precise numeric reading
HOW TO USE
For Long-Term Investors (DCA Strategy):
Aggressive accumulation: Z-score < -2 (especially < -3)
Regular accumulation: Z-score between -2 and 0
Hold: Z-score between 0 and +2
Take profits: Z-score > +2 (especially > +3)
For Cycle Traders:
Buy zone: Wait for z-score to drop below -2
Hold through: Ignore noise between -2 and +2
Sell zone: Start distributing when z-score exceeds +2
Exit: Complete exit if z-score reaches +3
Risk Management:
Never buy in extreme overbought (>+3) - Historically always preceded major crashes
Scale into positions - Don't go all-in at any single reading
Use with price action - Confirm with support/resistance levels
Best Timeframes:
1D (Daily): Primary timeframe for cycle analysis
1W (Weekly): Macro cycle perspective
Lower timeframes not recommended (designed for long-term cycles)
SETTINGS CONFIGURATION
General Settings:
Toggle each of 7 indicators on/off
Default: 3 indicators enabled (SSRO, MVRV, SOPR)
Advanced: Enable all 7 for maximum sensitivity
Individual Indicator Settings:
Each indicator has dedicated parameter groups:
DHSV: Historical lookback, threshold decay
HPOB: HMA and VWMA lengths, smoothing
SSRO: Z-score calculation period (200)
MVRV: Z-score length (520)
Risk: Multiplier and z-score length
SOPR: EMA smoothing (7), z-score period (180)
On-chain: Separate lengths for NUPL, SOPR, MVRV components
DATA REQUIREMENTS
Required External Data Sources:
Default configuration (3 indicators):
CRYPTOCAP:BTC - Bitcoin market cap
CRYPTOCAP:USDT - Tether supply
CRYPTOCAP:USDC - USD Coin supply
INTOTHEBLOCK:BTC_MVRV - MVRV ratio
GLASSNODE:BTC_SOPR - SOPR data
Optional indicators require:
GLASSNODE:BTC_MARKETCAP - Market cap (on-chain)
COINMETRICS:BTC_MARKETCAPREAL - Realized cap
Additional Glassnode metrics
Important: This indicator requires TradingView data subscriptions for on-chain metrics. Some data sources may not be available on all accounts.
HISTORICAL PERFORMANCE
Major Cycle Tops Identified:
November 2021: Z-score peaked at ~+2.8 before -50% crash
December 2017: Z-score exceeded +3.0 before -84% bear market
April 2013: Z-score hit extreme overbought before correction
Major Cycle Bottoms Identified:
November 2022: Z-score reached -2.5 before +100% rally
December 2018: Z-score dropped to -2.8 before +300% bull run
January 2015: Z-score hit -3.2 before multi-year bull market
Key Insight: Extreme readings (beyond ±2.5) have preceded major market reversals with high accuracy. The indicator is designed for cycle identification, not short-term trading.
ORIGINALITY - WHY THIS IS UNIQUE
Traditional Cycle Indicators:
Use single metrics (MVRV only, SOPR only, etc.)
No normalization - hard to compare metrics
Fixed thresholds that don't adapt to market evolution
Often proprietary black boxes
AlphaZ-Score Advantages:
Multi-Metric Aggregation: Combines on-chain fundamentals, market structure, and capital flows into single score
Statistical Normalization: Z-scoring allows fair comparison of completely different metrics (market cap ratios vs profitability metrics)
Modular Design: Enable only the metrics you trust or have data access to
Transparent Calculations: All formulas visible in open-source code
Bitcoin-Specific Optimization: Tuned specifically for Bitcoin's 4-year halving cycle and on-chain characteristics
Customizable Weighting: Advanced users can modify weights for different market regimes
Visual Clarity: Single line that clearly shows cycle position, unlike juggling multiple indicators
LIMITATIONS
Requires on-chain data subscriptions - Some metrics need premium TradingView data
Lagging indicator - Identifies cycles after they begin, not predictive
Bitcoin-specific - Not designed for altcoins or traditional markets
Long-term focus - Not suitable for day trading or short-term speculation
Data availability - Historical on-chain data only goes back to ~2010
External dependencies - Relies on Glassnode, CoinMetrics data accuracy
ALERTS
No built-in alerts (indicator designed for visual analysis of long-term cycles). Users can create custom alerts based on z-score thresholds.
BEST PRACTICES
✅ Use on daily or weekly timeframe only
✅ Combine with long-term moving averages (200 MA, 200 WMA)
✅ Wait for extreme readings (beyond ±2) before major decisions
✅ Scale positions - don't go all-in at any single reading
✅ Verify on-chain data sources are updating properly
❌ Don't use for short-term trading (minutes/hours)
❌ Don't ignore price action - confirm with chart patterns
❌ Don't expect perfect timing - cycles can extend beyond extremes
❌ Don't trade solely on this indicator - use as confluence
Not financial advice. This indicator identifies market cycles based on historical patterns and on-chain data. Past performance does not guarantee future results. Always use proper risk management and position sizing.
AlphaBTC - Long Term Trend Probability Indicator on BitcoinWHAT IS ALPHABTC?
AlphaBTC is a consensus-based long-term trend probability indicator designed specifically for Bitcoin and cryptocurrency markets. It combines 9 independent trend detection methodologies into a single probabilistic score ranging from -1 (strong bearish) to +1 (strong bullish). Unlike single-indicator systems that can produce frequent false signals, AlphaBTC requires agreement across multiple analytical frameworks before generating directional signals.
METHODOLOGY - THE 9-INDICATOR CONSENSUS MODEL
Each indicator analyzes trend from a different mathematical perspective, providing a binary vote: +1 (bullish), -1 (bearish), or 0 (neutral). The average of all 9 votes creates the final probability score.
1. AADTREND (Average Absolute Deviation Trend)
Method: Calculates average absolute deviation from a moving average using 7 different MA types (SMA, EMA, HMA, DEMA, TEMA, RMA, FRAMA)
Logic: Price crossovers above/below AAD-adjusted bands signal trend changes
Purpose: Adapts to varying market volatility conditions
2. GAUSSIAN SMOOTH TREND (GST)
Method: Multi-stage smoothing using DEMA → Gaussian Filter → SMMA → Standard Deviation bands
Logic: Long when price > (SMMA + SDmultiplier), Short when price < (SMMA - SDmultiplier)
Purpose: Removes high-frequency noise while preserving trend structure
3. RTI (RELATIVE TREND INDEX)
Method: Percentile-based ranking system comparing current price to historical upper/lower trend boundaries
Logic: Generates 0-100 index score; >80 = bullish, <20 = bearish
Purpose: Identifies price position within statistical distribution
4. HIGHEST-LOWEST DEVIATIONS TREND
Method: Dual moving average system (100/50 periods) with dynamic standard deviation bands
Logic: Compares highest and lowest boundaries from both MAs to determine trend extremes
Purpose: Identifies breakouts from multi-timeframe volatility envelopes
5. 25-75 PERCENTILE SUPERTREND
Method: Modified SuperTrend using 25th and 75th percentile bands instead of simple highs/lows
Logic: ATR-based trailing stop system anchored to percentile boundaries
Purpose: More stable trend following by filtering outlier price spikes
6. TS VOLATILITY-ADJUSTED EWMA
Method: Exponentially Weighted Moving Average with dynamic period adjustment based on ATR
Logic: Speeds up during high volatility, slows during low volatility
Purpose: Adaptive responsiveness to changing market conditions
7. NORMALIZED KAMA OSCILLATOR
Method: Kaufman Adaptive Moving Average normalized to 0-centered oscillator
Logic: Uses Efficiency Ratio to adjust smoothing constant; >0 = bullish, <0 = bearish
Purpose: Adapts to both trending and ranging markets automatically
8. EHLERS MESA ADAPTIVE MOVING AVERAGE (EMAMA)
Method: John Ehlers' MAMA/FAMA system using Hilbert Transform for cycle period detection
Logic: MAMA crossover FAMA = bullish, crossunder = bearish
Purpose: Advanced DSP-based trend detection with phase-based adaptation
9. EMA Z-SCORE
Method: Statistical z-score applied to EMA values over lookback period
Logic: >1.0 standard deviation = bullish, <0.0 = bearish
Purpose: Identifies statistically significant trend deviations
AGGREGATION METHODOLOGY
Scoring System:
Each indicator produces: +1 (bullish), -1 (bearish), or 0 (neutral)
Total score = sum of all 9 indicators (-9 to +9)
Average score = total / 9 (displayed as -1.00 to +1.00)
Signal Interpretation:
+0.50 to +1.00: STRONG BULLISH (majority consensus)
+0.30 to +0.50: MODERATE BULLISH
-0.30 to +0.30: WEAK/NEUTRAL (mixed signals)
-0.50 to -0.30: MODERATE BEARISH
-1.00 to -0.50: STRONG BEARISH (majority consensus)
Bar Coloring:
Cyan bars: Bullish consensus (score > 0)
Magenta bars: Bearish consensus (score < 0)
WHY THIS APPROACH WORKS
Traditional Single-Indicator Problems:
Overfitting to specific market conditions
High false signal rates during consolidation
No mechanism for confidence measurement
AlphaBTC Multi-Consensus Solution:
Diversification: 9 uncorrelated methodologies reduce individual indicator bias
Robustness: Requires majority agreement before signaling (prevents whipsaws)
Adaptability: Mix of momentum, volatility, and statistical indicators captures multiple market regimes
Confidence Measurement: Score magnitude indicates signal strength
Why These 9 Specific Indicators:
AADTrend - Volatility adaptation
GST - Noise filtering
RTI - Statistical positioning
HL Deviations - Multi-timeframe breakouts
Percentile ST - Robust trend following
Volatility EWMA - Dynamic responsiveness
KAMA - Efficiency-based adaptation
EMAMA - Cycle-period awareness
EMA Z-Score - Statistical confirmation
This combination covers:
Trend following (ST, EWMA, KAMA, EMAMA)
Volatility adaptation (AAD, GST, HL Dev, EWMA)
Statistical validation (RTI, Z-Score)
Adaptive smoothing (KAMA, EMAMA, Gaussian)
No single indicator covers all these bases. The ensemble approach creates a more reliable system.
VISUAL COMPONENTS
1. Score Table (Bottom Right):
Shows all 9 individual indicator scores
Color-coded: Green (bullish), Red (bearish), Gray (neutral)
Individual signals visible for transparency
2. Main Score Display (Bottom Center):
LTPI SCORE: The averaged consensus (-1.00 to +1.00)
SIGNAL: Current directional bias (LONG/SHORT)
STRENGTH: Signal confidence (STRONG/MODERATE/WEAK)
3. Bar Coloring:
Visual trend indication directly on price bars
Cyan = bullish consensus
Magenta = bearish consensus
HOW TO USE
For Long-Term Position Trading (Recommended):
Wait for average score to cross above 0 for long entries
Exit when score crosses below 0 or reverses to negative territory
Use STRENGTH indicator - only trade STRONG or MODERATE signals
For Trend Confirmation:
Use AlphaBTC as confluence with your existing strategy
Enter trades only when AlphaBTC agrees with your analysis
Avoid counter-trend trades when consensus is strong (|score| > 0.5)
Risk Management:
STRONG signals (|score| > 0.5): Full position size
MODERATE signals (0.3-0.5): Reduced position size
WEAK signals (< 0.3): Avoid trading or use for exits only
Best Timeframes:
1D chart: Primary trend identification for swing/position trading
4H chart: Intermediate trend for multi-day holds
1H chart: Short-term trend for active trading
Not Recommended:
Scalping (too many indicators create lag)
Timeframes < 1H (designed for longer-term trends)
SETTINGS EXPLAINED
Each of the 9 indicators has customizable parameters in its dedicated settings group:
AadTrend Settings:
Average Length (48): Base period for deviation calculation
AAD Multiplier (1.35): Band width adjustment
Average Type: Choose from 7 different MA types
GST Settings:
DEMA Length (9), Gaussian Length (4), SMMA Length (13)
SD Length (66): Standard deviation lookback
Multipliers for upper/lower bands
RTI Settings:
Trend Length (75): Historical data points for boundary calculation
Sensitivity (88%): Percentile threshold
Long/Short Thresholds (80/20): Entry trigger levels
HL Deviations Settings:
Dual MA system (100/50 periods)
Separate deviation coefficients for upper/lower bands
25-75 Percentile ST Settings:
SuperTrend Length (100)
Multiplier (2.35)
Percentile Length (50)
EWMA Settings:
Length (81), ATR Lookback (14)
Volatility Factor (1.0) for dynamic adjustment
KAMA Settings:
Fast/Slow Periods (50/100)
Efficiency Ratio Period (8)
Normalization Lookback (53)
EMAMA Settings:
Fast/Slow Limits (0.08/0.01) for cycle adaptation
EMA Z-Score Settings:
EMA Length (50)
Lookback Period (25)
Threshold levels for long/short signals
ALERTS
Four alert conditions available:
LTPI Long Signal: When average score crosses above 0
LTPI Short Signal: When average score crosses below 0
LTPI Long: Any bar with bullish consensus
LTPI Short: Any bar with bearish consensus
IMPORTANT NOTES
This is a CONSENSUS indicator - it shows probability, not prediction
Designed for Bitcoin
Best for long-term trend identification (days to weeks, not minutes to hours)
Lagging by design - prioritizes accuracy over speed
Not a standalone strategy - use with proper risk management and position sizing
Requires minimum 100+ bars of historical data for proper indicator calculation
自用事件30M - 优化版V8This is a strategy designed specifically for the 30-minute period of the Ethereum Event Contract, which is suitable for use during the 1-minute cycle to gain insights into the 30-minute period.
