Balanced/Unbalanced MarketWhen market chooses to go uptrend or downtrend, the equilibrium between buyers and sellers vanishes and the trend with the different qualifications forms. The number of balanced and unbalanced periods of a trend can relate to it's weakness/strength.
Using indicators like ichimoku can initially help us to simply understand these concept.
So simply:
1- When Kj (Kijunsen=Ichimoku baseline) become flat, it shows the equilibrium between buyers and sellers. In line 13 of the script code, we can see the condition for this. In this case, better to use Kj=52 as it's closer to the concept of equilibrium market and contains more flat periods.
Also we can use Kj ==Kj and Kj ==Kj instead, to filter the balanced bars more.
2- When Kj stand higher or lower than it's previous value, it can be used as determiner for bullishness and bearishness of the market. In lines 16,19 of the script code, we can see the conditions for this. In this case, better to use Kj=26 as it's closer to the concept of trend market.
Cari dalam skrip untuk "ichimoku"
AlfredFxPro - Ichimoku_Trends_AlertsOur powerful Ichimoku Trend Following Scalping Indicator now with LIVE Alerts ( Buy, Sell, Exit Buy, Exit Sell) straight to your PC + Mobile.
*** NO REPAINT *** What you see is what you get. It will fire a signal as soon as the bar close
The (AlfredFxPro - Ich_Trends) uses one element of the famous Ichimoku and combine the signal with two custom volatility indicators to predict potential trends and determine the strength of the trend to keep you in as long as the trend is running or get you out as soon as possible with min loss.
Combine the signal with price action breakout patterns and you have a solid indicator.
It's a very powerful tool to add to your analysis, and make it your own.
**Try on Demo First**
Works best on high volatility instruments
Works on All Assets ( Forex, Crypto, Commodities , Gold , Stocks)
Suggested Timeframes (15min, 30min, 1Hr, 4Hr, D)
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Send us a message for Access!
THIS INDICATOR IS PRIVATE & AVAILABLE FOR MEMBERS ONLY!
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How to Set Alerts :
**Example Buy Signal Alert
-> Go to GBP/NZD 4Hr Timeframe
-> Click Add new Alert
-> Condition -> Select : AlfredFxPro - Ich_Trends
-> Select : Buy Alert
-> Option : Once Per Bar Close
-> Notify on App + POP Up
-> Message: Write: ""Buy 4Hr""
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**Example Exit Buy Signal Alert
-> Go to GBP/NZD 4Hr Timeframe
-> Click Add new Alert
-> Condition -> Select : AlfredFxPro - Ich_Trends
-> Select : Long Exit Alert
-> Option : Once Per Bar Close
-> Notify on App + POP Up
-> Message: Write : ""Exit Buy 4Hr""
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You repeat the same process for "Sell, and Exit Sell" for any pair on any timeframe you want.
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**********Important***********
1) Enter on a Buy and Exit from the same time frame don't mix signals from time frames ( Treat each time frame as an individual trade).
2) Important to set the Alert option: ""Once Per Bar Close"", otherwise you'll get wrong signals.
*************************
Send us a message for Access!
THIS INDICATOR IS PRIVATE & AVAILABLE FOR MEMBERS ONLY!
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Dr.ManiaTemel olarak teknik analizlerde kullanılabilecek en yaygın komutların hepsinin bir arada olduğu (Ichimoku, MavilimW, Bollinger, Oklar, Hareketli Ortalamaları) komuttur.
Ichimoku+MavilimW+BB+Arrow+MAVCOMBO
Thunder and Lightning 1.0Modified ichimoku indicator as given by Akira Takahashi in "Ichimoku Thunder and Lightning Clouds"
Bollinger Band and moving averageThis script help you to show :
- Bollinger Bands
- 3 moving average to choose + 1 hma 120 + vegas wave (lenght and type : sma , ema , vwma , etc.)
- Color candle when RSI is oversold/overbought
- Regular divergence (only base on CCI oscillator)
- Identify resistance/support with Ichimoku cloud or personnal "Duf" cloud
- For cryptos (btc/eth/ltc/eos), MACD cross filtered (red/green arrow)
- Japanese pattern recognition : morning star, evening star
Ce script permet d'afficher les éléments suivants :
- Bandes de Bollinger
- 3 Moyennes Mobiles à choisir + 1 hma 120 + vegas wave (longueur et type : sma , ema , vwma , etc.)
- Coloration de bougies quand surachat/survente RSI
- Affichage de divergence (basé sur l'oscillateur CCI )
- Possibilité d'afficher nuage Ichimoku ou nuage perso "Duf" pour zone de résistance/support
- Pour les cryptos (btc/eth/ltc/eos), possibilité d'afficher le croisement MACD filtré (flèche rouge/verte)
- Détection des chandeliers japonais suivants : Étoile filante, Étoile du soir, Étoile du matin, Avalement baissier, Avalement haussier, Pendu, Ligne Perçante et Couverture en nuage noir)
Money Machine God MAThis is intended for cryptocurrencies.
Top Down
BB, RSI, MACD
The dark green nand pink are bollinger bands. When the green line (RSI) crosses them becareful. When the green line crosses the red line then you have a buy signal. The white line is the MACD. A sell signal is when the green line is below the white line. You can use this for exploding coins at 1 and 3 minutes.
MA
These are moving averages, 7 21 77 and 231. When the green line is above the white, orange, and red then you have a buy signal. The green line is the most important. You can get a buy signal once green is above red for shorter plays.
Ichimoku
Cyan line above orange line also known as TK cross is a buy signal. Cloud breakout is when the price is above the cloud. The 20 60 120 30 allows for less false positives.
Ichimoku on steroids
Once the cyan line crosses the middle cyan line or the 0 value, then that is a buy signal.
Tensor CloudIntroducing the Tensor Cloud. This is probably the best indicator I've come up with so far. I'm really proud of it. Ichimoku is a brilliant system. It's been around for over half a century and I praise Goichi Hosoda for his brilliant work. However, it's time for something new. I love math and this indicator really showcases that. The Tensor Cloud is an indicator of its own. It is not related to Ichimoku at all. The only thing they have in common is that they both form clouds. The maths in Tensor Cloud are 100% apart.
The Tensor Cloud is mostly comprised of some special forms of linear regression. Let's do a rundown.
Future Span A (Green)
This is one predictor using a linear regression technique. Future Span A is one of the two lines that makes up a Tensor Cloud. From here on out it will traditionally be colored green. It can be used as both a predictor on its own and comprising the Tensor Cloud. This can also be viewed as sort of a long signal when crossing up Future Span B. This line can also be used to help identify levels of support and resistance.
Future Span B (Red)
This is another form of linear regression meant specifically to work alongside Future Span A. This is the second line that comprises a Tensor Cloud. From here on out it will traditionally be colored red. It can be used both as a predictor on its own and comprising the Tensor Cloud. This can also be viewed as sort of a short signal when crossing down through Future Span A. This line can also be used to help identify levels of support and resistance.
Safe (White)
The Safe is a moving average taken of Future Span A and Future Span B. It is highly predictive. From here on out it will traditionally be colored white.
Tip (Fuchsia)
This is yet another form of regression and is highly predictive. The Tip can also be used to help judge trend strength and probability of reversal. More study is of course needed. More on that later in this description. From here on out it will traditionally be colored fuchsia. This line can also be used to help identify levels of support and resistance.
The Tensor Cloud
The space between Future Span A and Future Span B is shaded in green or red, depending on which Future Span is on top. If Future Span A is on top, the Tensor Cloud will be green. This is considered a long signal. If Future Span B is on top, the Tensor Cloud will be colored red. This is a short signal. Attention should also be given to other factors such as:
The position of price in relation to the Tensor Cloud (Under, inside or above).
The position of Tip in relation to the Tensor Cloud.
Crosses of Future Span A and Future Span B.
Tensor Twist
Whenever Future Span A and Future Span B cross (In either direction), this is called a Tensor Twist. If Future Span A is crossing up, this is a long Tensor Twist. If Future Span B is crossing up, this is a short Tensor Twist.
Closing Summary
Much study needs to be done. This is a brand new technique. It's up to all of you to help figure out the best ways to use it. I may still add other components to this indicator but it's pretty solid as is. You will notice that the two integer inputs are set to 27. Twenty-seven is a very important number in mathematics. The details of that are beyond the scope of this description but from here on out, the traditional setting for those will be 27. You will notice that I am not yet releasing the source code to this indicator. For now, it will remain protected. Once I have enough feedback and we're all happy with the final result, I will release the code for the world to have. I have no wish of keeping this closed-source (As profitable as that might be). I just want it to help as many people as possible.
Please share this on social media so we can attract as many testers to give feedback as possible. For publishing this for free, that's all I ask in return. That way it will be as solid as possible when I release the source code.
Enjoy!
Cloud, MA & BB Signal ConvergenceA combination of 3 popular lagging indicators (Ichimoku Cloud, Moving Average and Bollinger Bands) that generates a signal when all 3 of those lagging indicators are bullish or bearish.
Bullish is represented with a green dot above price. Bearish is represented with a red dot below price.
PARAMETERS:
1) Ichimoku Cloud
-Bullish Kumo
-Price above Kumo
-Chikou span above price
-Tenkan-sen and Kijun-sen above Kumo
-Tenkan-sen above Kijun-sen
-Price above Tenkan-sen
*opposite for bearish
Note: cloud settings is the popular settings for cryptocurrency advocated by @CarpeNoctom.
2) Moving Average
-MA1 greater than MA2
-MA2 greater than MA3
-MA3 greater than MA4
-MA4 greater than MA5
*opposite for bearish
Note: Put your MA setting from lowest to highest on MA1-MA5 respectively to generate more accurate signals.
3) Bollinger Bands
-price closed above upper band at least once
*opposite for bearish
Note: Put your MA setting from lowest to highest on MA1-MA5 respectively to generate more accurate signals.
P.S. Still on early alpha stage.
Musashi-Naoko
This is a customized Ichimoku Indicator with a built in trend concept. It will assist as a filter when entering trades, thereby improving Ichimoku performance.
LEGAL STUFF:
Risk Disclosure
Futures , forex, stock, crypto and derivative trading contains substantial risk and is not for every investor. An investor could potentially lose all or more than the initial investment. Risk capital is money that can be lost without jeopardizing ones’ financial security or life style. Only risk capital should be used for trading and only those with sufficient risk capital should consider trading. Past performance is not necessarily indicative of future results
Hypothetical Performance Disclosure
Hypothetical performance results have many inherent limitations, some of which are described below. no representation is being made that any account will or is likely to achieve profits or losses similar to those shown; in fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk of actual trading. for example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all which can adversely affect trading results
Fibonacci CloudInspired by Ichimoku Fibonacci Hybrid , this indicator is for those who don't mind a lot of lines. All lines represent Fib ratios: thicker lines are fibs for a longer period, while thinner lines are fibs for a shorter period.
- Dynamic S/R
- Overbought/Oversold zones
- Trend indicator
- Customisable periods
- Fast/Slow crossovers
See what works for you!
Rene Band LightRene Band Light
안녕하세요 르네입니다.
르네밴드가 퍼블리시된 이후 많은 사랑을 받았습니다.
이에 일부 기능을 제한한 무료버전인 RENE BAND light를 공개합니다.
정식버젼 링크 :
정식 유료버전과 핵심기능들은 동일합니다.
1) 히트밴드의 표시
2) 과매수, 과매도 경고 마커표시
3) 6개의 이동평균선 표시
4) 일목균형표까지 하나의 지표로 통합
다만 제한사항이 있는데 이는 다음과 같습니다.
1) 히트밴드, 이동평균선, 일목균형표 등의 수치 세팅값 변경 불가
* 기본셋팅 :
이평선 : 타입 SMA ,길이 7 14 21 50 100 200
볼린저밴드(히트밴드 내부밴드) : EMA basis, multiplier 2.1, base ma length 21
일목균형표 : 기본값과 동일.
2) 매물대 자동표시 보조기능 삭제
많은 관심과 이용 부탁드립니다.
사용하시다가 정식버젼이 필요하시면 PM(개인메시지)를 주세요.
감사합니다
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Hello, It's Rene.
Let me introduce the light version of Rene Band which is free to use.
Core features are the same
1) Plotting Heatbands
2) Display Oversold, overbought warning maker
3) 6 moving averages
4) ichimoku clouds are integrated
But there are few limitations as follows
1) Setting values are fixed (heatband, MAs, clouds)
* Default value :
MA : Type SMA ,Length 7 14 21 50 100 200
Bollinger band : EMA basis, multiplier 2.1, base ma length 21
ichimoku : same as defalt
2) Auto plotting support / resistance line feature is deleted
Thanks for your attention and hope you find it useful.
If you need original version(paid version), just PM me.
Trend Bars with Okuninushi Line Filter# Trend Bars with Okuninushi Line Filter: A Powerful Trading Indicator
## Introduction
The **Trend Bars with Okuninushi Line Filter** is an innovative technical indicator that combines two powerful concepts: trend bar analysis and the Okuninushi Line filter. This indicator helps traders identify high-quality trending moves by analyzing candle body strength relative to the overall price range while ensuring the price action aligns with the dominant market structure.
## What Are Trend Bars?
Trend bars are candles where the body (distance between open and close) represents a significant portion of the total price range (high to low). These bars indicate strong directional momentum with minimal indecision, making them valuable signals for trend continuation.
### Key Characteristics:
- **Strong directional movement**: Large body relative to total range
- **Minimal upper/lower shadows**: Shows sustained pressure in one direction
- **High conviction**: Represents decisive market action
## The Okuninushi Line Filter
The Okuninushi Line, also known as the Kijun Line in Ichimoku analysis, is calculated as the midpoint of the highest high and lowest low over a specified period (default: 52 periods).
**Formula**: `(Highest High + Lowest Low) / 2`
This line acts as a dynamic support/resistance level and trend filter, helping to:
- Identify the overall market bias
- Filter out counter-trend signals
- Provide confluence for trade entries
## How the Indicator Works
The indicator combines these two concepts with the following logic:
### Bull Trend Bars (Green)
A candle is colored **green** when ALL conditions are met:
1. **Bullish candle**: Close > Open
2. **Strong body**: |Close - Open| ≥ Threshold × (High - Low)
3. **Above trend filter**: Close > Okuninushi Line
### Bear Trend Bars (Red)
A candle is colored **red** when ALL conditions are met:
1. **Bearish candle**: Close < Open
2. **Strong body**: |Close - Open| ≥ Threshold × (High - Low)
3. **Below trend filter**: Close < Okuninushi Line
### Neutral Bars (Gray)
All other candles that don't meet the complete criteria are colored **gray**.
## Customizable Parameters
### Trend Bar Threshold
- **Range**: 10% to 100%
- **Default**: 75%
- **Purpose**: Controls how "strong" a candle must be to qualify as a trend bar
**Threshold Effects:**
- **Low (10-30%)**: More sensitive, catches smaller trending moves
- **Medium (50-75%)**: Balanced approach, filters out most noise
- **High (80-100%)**: Very selective, only captures the strongest moves
### Okuninushi Line Length
- **Default**: 52 periods
- **Purpose**: Determines the lookback period for calculating the midpoint
- **Common Settings**:
- 26 periods: More responsive to recent price action
- 52 periods: Standard setting, good balance
- 104 periods: Longer-term trend perspective
## Trading Applications
### 1. Trend Continuation Signals
- **Green bars**: Look for bullish continuation opportunities
- **Red bars**: Consider bearish continuation setups
- **Gray bars**: Exercise caution, mixed signals
### 2. Market Structure Analysis
- Clusters of same-colored bars indicate strong trends
- Alternating colors suggest choppy, indecisive markets
- Transition from red to green (or vice versa) may signal trend changes
### 3. Entry Timing
- Use colored bars as confirmation for existing trade setups
- Wait for color alignment with your market bias
- Avoid trading during predominantly gray periods
### 4. Risk Management
- Gray bars can serve as early warning signs of weakening trends
- Color changes might indicate appropriate exit points
- Use in conjunction with other risk management tools
## Advantages
1. **Dual Filtering**: Combines momentum (trend bars) with trend direction (Okuninushi Line)
2. **Visual Clarity**: Immediate visual feedback through candle coloring
3. **Customizable**: Adjustable parameters for different trading styles
4. **Versatile**: Works across multiple timeframes and instruments
5. **Objective**: Rule-based system reduces subjective interpretation
## Limitations
1. **Lagging Nature**: Based on historical price data
2. **False Signals**: Can produce whipsaws in choppy markets
3. **Parameter Sensitivity**: Requires optimization for different instruments
4. **Market Conditions**: May be less effective in ranging markets
## Best Practices
### Optimization Tips:
- **Volatile Markets**: Use higher thresholds (80-90%)
- **Steady Trends**: Use moderate thresholds (60-75%)
- **Short-term Trading**: Shorter Okuninushi Line periods (26)
- **Long-term Analysis**: Longer Okuninushi Line periods (104+)
### Combination Strategies:
- Pair with volume indicators for confirmation
- Use alongside support/resistance levels
- Combine with other trend-following indicators
- Consider market context and overall trend direction
## Conclusion
The Trend Bars with Okuninushi Line Filter offers traders a sophisticated yet intuitive way to identify high-quality trending moves. By combining the momentum characteristics of trend bars with the directional filter of the Okuninushi Line, this indicator helps traders focus on the most promising opportunities while avoiding low-probability setups.
Remember that no single indicator should be used in isolation. Always consider market context, risk management, and other technical factors when making trading decisions. The true power of this indicator lies in its ability to quickly highlight periods of strong, aligned price action – exactly what trend traders are looking for.
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*Disclaimer: This article is for educational purposes only and should not be considered as financial advice. Always conduct your own research and consider your risk tolerance before making any trading decisions.*
Thunder & Lightning Kumo + Keltner + Simple Lightning SignalsThe Thunder & Lightning Kumo + Keltner + Simple Lightning Signals combines Ichimoku Cloud dynamics with Keltner Channels for advanced trend analysis.
It highlights volatility zones through the Keltner bands while tracking trend strength via the custom Thunder & Lightning Kumo.
Simple Lightning Signals provide clear, visual buy and sell triggers based on cloud breakouts.
This multi-layered approach helps identify both momentum shifts and breakout entries with precision.
Ideal for traders seeking a balance between trend-following and volatility-based confirmation.
Swing Guardrail — 30-sec Midterm Check (EBITDA Margin & EV/EBITDWhat it does
Before a short-term swing entry, this indicator right-sizes positions by a quick midterm (3–12m) durability screen using two fundamentals:
EBITDA Margin (TTM) → earning power / operational resilience
EV/EBITDA (TTM) → price tag vs earning capacity (payback feel)
A high-contrast table (top-right) shows both metrics and a verdict:
PASS — both meet thresholds → normal size
HALF — only one meets → reduce size
FAIL — neither meets → avoid
Why check “midterm” for a short-term trade?
Short swings still face earnings/news gaps, failed breakouts, and regime shifts. Names with weak margins or stretched valuation tend to break faster and deeper. A 30-sec durability check helps you:
Filter fragile setups (avoid expensive + weakening names)
Stabilize drawdowns (size down when quality/price don’t align)
Keep timing unchanged while improving risk-adjusted returns
Inputs (defaults)
Min EBITDA Margin % (TTM): 8%
Max EV/EBITDA (TTM): 12
Dark chart? High-contrast colors
How to use with a swing system
Get your entry from price/volume (e.g., Ichimoku cloud break, Kijun reclaim, Tenkan>Kijun; or your A/B/C rules).
Run this check only to set size (not timing).
Optional alerts: Once per bar close for PASS / HALF / FAIL.
Size mapping & event guard
PASS → 100% of your planned size
HALF → ~50% size / tighter stops
FAIL → watchlist only
If earnings < ~10 JP business days, drop one tier; ≤3 days → avoid.
Sector guides (tweak as needed)
Software/Internet: Margin ≥ 15%, EV/EBITDA ≤ 18
Industrials/Consumer: Margin ≥ 8%, EV/EBITDA ≤ 12
Retail: Margin ≥ 5–7%, EV/EBITDA ≤ 10–12
Edge cases / substitutions
Banks/Insurers/REITs or net-cash/negative EBITDA: EV/EBITDA may mislead → consider Net Debt/EBITDA or sector metrics (CET1/LTV/DSCR).
Sparse data / fresh listings: numbers may be NA until updates.
Notes & limitations
Data via request.financial() (TTM/most-recent). Some tickers/regions can show NA until fundamentals refresh.
This is a risk-screen / sizing tool, not a buy/sell signal.
Disclaimer
Educational use only. Not investment advice.
日本語
タイトル
スイング用ガードレール―中期“壊れにくさ”30秒チェック（EBITDAマージン & EV/EBITDA, TTM）
概要
短期スイングのエントリー前に、中期（3〜12か月）の耐久性を2指標で素早く確認し、ポジションサイズを決めるためのツールです。
EBITDAマージン（TTM）：事業の稼ぐ力・体力
EV/EBITDA（TTM）：その体力に対する“値札”（回収年数の感覚）
右上の高コントラスト表に数値と判定を表示：
PASS：両方クリア → 通常サイズ
HALF：片方のみ → サイズ半分
FAIL：両方NG → 見送り
なぜ短期でも“中期”を確認？
短期でも決算・ニュースのギャップ、ブレイク失敗、地合い転換は起きます。マージンが弱い／割高すぎる銘柄は崩れやすく、戻りも鈍い傾向。30秒の耐久性チェックで
脆いセットアップを回避
ドローダウンを平準化（サイズで吸収）
タイミングは変えずに、リスク調整後リターンの改善を狙えます。
入力（既定）
最低EBITDAマージン：8%
最大EV/EBITDA：12
黒背景向け：高コントラスト表示
使い方（スイング手法と併用）
まずは価格シグナル（一目の雲上抜け／基準線回復／転換線>基準線、またはA/B/Cルール）。
本インジの判定でサイズのみ決定（エントリーのタイミングは出しません）。
任意でバー確定アラート（PASS/HALF/FAIL）を設定。
サイズ目安 & イベント抑制
PASS：計画サイズ100%
HALF：約50%（ストップもタイトに）
FAIL：見送り
決算まで≦10営業日なら1段階サイズダウン、≦3営業日は原則見送り。
セクター目安（調整推奨）
ソフト/ネット：マージン 15%以上、EV/EBITDA 18以下
工業/一般消費：マージン 8%以上、EV/EBITDA 12以下
小売：マージン 5〜7%以上、EV/EBITDA 10〜12以下
例外・代替
銀行・保険・REIT／ネットキャッシュ・EBITDAマイナス：EV/EBITDAは適さない場合 → Net Debt/EBITDAやCET1/LTV/DSCR等で補助。
新規上場・データ薄：更新までNAのことあり。
注意
データは request.financial() を使用。更新前はNAの可能性。
本ツールはリスク確認／サイズ調整用で、売買シグナルではありません。
免責
情報提供のみ。投資判断は自己責任で。
🏆 AI Gold Master IndicatorsAI Gold Master Indicators - Technical Overview
Core Purpose: Advanced Pine Script indicator that analyzes 20 technical indicators simultaneously for XAUUSD (Gold) trading, generating automated buy/sell signals through a sophisticated scoring system.
Key Features
📊 Multi-Indicator Analysis
Processes 20 indicators: RSI, MACD, Bollinger Bands, EMA crossovers, Stochastic, Williams %R, CCI, ATR, Volume, ADX, Parabolic SAR, Ichimoku, MFI, ROC, Fibonacci retracements, Support/Resistance, Candlestick patterns, MA Ribbon, VWAP, Market Structure, and Cloud MA
Each indicator generates BUY (🟢), SELL (🔴), or NEUTRAL (⚪) signals
⚖️ Dual Scoring Systems
Weighted System: Each indicator has configurable weights (10-200 points, total 1000), with higher weights for critical indicators like RSI (150) and MACD (150)
Simple Count System: Basic counting of BUY vs SELL signals across all indicators
🎯 Signal Generation
Configurable thresholds for both systems (weighted score threshold: 400-600 recommended)
Dynamic risk management with ATR-based TP/SL levels
Signal strength filtering to reduce false positives
📈 Advanced Configuration
Customizable thresholds for all 20 indicators (RSI levels, Stochastic bounds, Williams %R zones, etc.)
Dynamic weight bonuses that adapt to dominant market trends
Risk management with configurable TP1/TP2 multipliers and stop losses
🎛️ Visual Interface
Real-time master table displaying all indicators, their values, weights, and current signals
Visual trading signals (triangles) with detailed labels
Optional TP/SL lines and performance statistics
💡 Optimization Features
Gold-specific parameter tuning
Trend analysis with configurable lookback periods
Volume spike detection and volatility analysis
Multi-timeframe compatibility (15m, 1H, 4H recommended)
The system combines traditional technical analysis with modern weighting algorithms to provide comprehensive market analysis specifically optimized for gold trading.
Ragazzi è una meraviglia, pronto all uso, già configurato provatelo divertitevi e fate tanti soldoni poi magari una piccola donazione spontanea sarebbe molto gradita visto il tempo, risorse e gli insulti della moglie che mi diceva che perdevo tempo, fatemi sapere se vi piace.
nel codice troverete una descrizione del funzionamento se vi vengono in mente delle idee per migliorarlo contattatemi troverete i mie contatti in tabella un saluto.
Trend Continuation — Compact HUD Pane 🖥️ Trend Continuation HUD Panel — Multi-Factor Dashboard
This panel is your trend continuation command center ⚡. Instead of guessing which filters are in play, the HUD shows you a real-time checklist of up to 6 confluence filters — with clear ✔ and ✖ signals.
🔍 What it shows
Each row = one filter. Green ✔ means it’s passing in the trend direction, red ✖ means it’s failing, grey ✖ means neutral/inactive.
✔ Ichimoku (9/26/52/26) → Above/Below cloud + Tenkan/Kijun order
✔ MACD (12/26/9) → Histogram slope & zero-line alignment
✔ RSI / MFI (14) → Momentum ≥60 bull / ≤40 bear
✔ ADX (14) → Strength ≥20 and rising
✔ EMA Alignment (9/21/55/233) (optional) → Stack order confirms trend engine
✔ ATR Slope (14) (optional) → Expanding volatility filter
📊 Score Line (0–6 scale)
At the bottom of the HUD you’ll see a colored score plot:
🟢 5–6 = A-Grade Trend Environment → strongest continuation regimes
🟡 3–4 = Mixed Bag → wait for clarity
🔴 0–2 = Fail Zone → stay flat, no trend support
🎯 How to use it
Scan the HUD first → wait until Score ≥5 and most rows are ✔ green.
Then check Overlay labels/arrows → only take signals while HUD is green (trend environment confirmed).
Adjust strictness with minChecks:
• Normal Days → Score ≥4 acceptable (partial TP style).
• Trend Days → Demand Score ≥5 (stacked, high-conviction runs).
🧩 Best Practices
⏰ Focus on London & NY sessions (HUD grays out off-hours).
🔄 Keep the HUD & Overlay in sync (same EMA/ATR/session settings).
⚡ Use the HUD as your filter, Overlay as your trigger → keeps you aligned with your trading plan and risk model.
Trend Continuation Filter - 🚀 Trend Continuation Filter — Multi-Factor Overlay
This overlay plots bullish / bearish continuation labels & arrows only when the market has enough confluence behind the move. Think of it as your “trend gatekeeper” — cutting out weak setups and highlighting only those with real momentum + structure.
🔍 Built-in Filters
✔ Ichimoku Cloud → trend bias + Tenkan/Kijun confirmation
✔ MACD (12/26/9) → acceleration via histogram slope
✔ RSI / MFI (14) → momentum quality (≥60 bullish / ≤40 bearish)
✔ ADX (14) → strength check (≥20 and rising)
➕ EMA Alignment (9/21/55/233) (optional)
➕ ATR Slope (14) (optional)
🎯 How it works
✅ Prints a Bull Continuation label/arrow when ≥4 filters align to the upside
✅ Prints a Bear Continuation label/arrow when ≥4 filters align to the downside
⚙️ minChecks input lets you adjust the strictness:
• Normal Days → set to 4 (more frequent, flexible)
• Trend Days → raise to 5–6 (fewer, high-conviction setups)
📈 Best Practices
⏰ Focus on London & New York sessions for clean expectancy
🧩 Pair with a HUD/Dashboard panel to see exactly which filters are active
T-Virus Sentiment [hapharmonic]🧬 T-Virus Sentiment: Visualize the Market's DNA
Remember the iconic T-Virus vial from the first Resident Evil? That powerful, swirling helix of potential has always fascinated me. It sparked an idea: what if we could visualize the market's underlying health in a similar way? What if we could capture the "genetic code" of market sentiment and contain it within a dynamic, 3D indicator? This project is the result of that idea, brought to life with Pine Script.
The indicator's main goal is to measure the strength and direction of market sentiment by analyzing the "genetic code" of price action through a variety of trusted indicators. The result is displayed as a liquid level within a DNA helix, a bubble density representing buying pressure, and a T-Virus mascot that reflects the overall mood.
🧐 Core Concept: How It Works
The primary output of the indicator is the "Active %" gauge you see on the right side of the vial. This percentage represents the overall sentiment score, calculated as an average from 7 different technical analysis tools. Each tool is analyzed on every bar and assigned a score from 1 (strong bearish pressure) to 5 (strong bullish potential).
In this indicator, we re-imagine market dynamics through the lens of a viral outbreak. A strong bear market is like a virus taking hold, pulling all technical signals down into a state of weakness. Conversely, a powerful bull market is like an antiviral serum ; positive signals rise and spread toward the top of the vial, indicating that the system is being injected with strength.
This is not just another line on a chart. It's a comprehensive sentiment dashboard designed to give an immediate, at-a-glance understanding of the confluence between 7 classic technical indicators. The incredible 3D model of the vial itself was inspired by a design concept found here .
⚛️ The 4 Core Elements of T-Virus Sentiment
These four elements work in harmony to give a complete, multi-faceted picture of market sentiment. Each component tells a different part of the story.
The Virus Mascot: An instant emotional cue. This character provides the quickest possible read on the overall market mood, combining sentiment with volume pressure.
The Antiviral Serum Level: The main quantitative output. This is the liquid level in the DNA helix and the percentage gauge on the right, representing the average sentiment score from all 7 indicators.
Buy Pressure & Bubble Density: This visualizes volume flow. The density of bubbles represents the intensity of accumulation (buying) versus distribution (selling). It's the "power" behind the move.
The Signal Distribution: This shows the confluence (or dispersion) of sentiment. Are all signals bullish and clustered at the top, or are they scattered, indicating a conflicted market? The position of the indicator labels is crucial, as each is assigned to one of five distinct zones:
Base Bottom: The market is at its weakest. Signals here suggest strong bearish control and distribution.
Lower Zone: The market is still bearish, but signals may be showing early signs of accumulation or bottoming.
Neutral Core (Center): A state of balance or sideways consolidation. The market is waiting for a new direction.
Upper Zone: Bullish momentum is becoming clear. Signals are strengthening and showing bullish control.
Top Cap: The market is "heating up" with strong bullish sentiment, potentially nearing overbought conditions.
🐂🐻 The Virus Mascot: The At-a-Glance Indicator
This character acts as a shortcut to confirm market health. It combines the sentiment score with volume, preventing false confidence in a low-volume rally.
Its state is determined by a dual-check: the overall "Antiviral Serum Level" and the "Buy Pressure" must both be above 50%.
Green & Smiling: The 'all clear' signal. This means that not only is the overall technical sentiment bullish, but it's also being supported by real buying pressure. This is a sign of a healthy bull market.
Red & Angry: A warning sign. This appears if either the sentiment is weak, or a bullish sentiment is not being confirmed by buying volume. The latter could indicate a potential "bull trap" or an exhaustive move.
This mascot can be disabled from the settings page under "Virus Mascot Styling" if a cleaner look is preferred.
🫧 Bubble Density: Gauging Buy vs. Sell Pressure
The bubbles visualize the battle between buyers and sellers. There are two modes to control how this is calculated:
Mode 1: Visible Range (The 'Big Picture' View)
This default mode is best for getting a broad, contextual understanding of the current session. It dynamically analyzes the volume of every single candlestick currently visible on the screen to calculate the buy/sell pressure ratio. It answers the question: "Over the entire period I'm looking at, who is in control?" As you zoom in or out, the calculation adapts.
Mode 2: Custom Lookback (The 'Precision' View)
This mode is for traders who need to analyze short-term pressure. You can define a fixed number of recent bars to analyze, which is perfect for scalping or understanding the volume dynamics leading into a key level. It answers the question: "What is happening right now ?" In the example above, a lookback of 2 focuses only on the most recent action, clearly showing intense, immediate selling pressure (few bubbles) and a corresponding drop in the sentiment score to 29%.
ℹ️ Interactive Tooltips: Dive Deeper
We believe in transparency, not 'black box' indicators. This feature transforms the indicator from a visual aid into an active learning tool.
Simply hover the mouse over any indicator label (like EMA, OBV, etc.) to get a detailed tooltip. It will explain the specific data points and thresholds that signal met to be placed in its current zone. This helps build trust in the signals and allows users to fine-tune the indicator settings to better match their own trading style.
🎯 The Scoring Logic Breakdown
The "Antiviral Serum Level" gauge is the average score from 7 technical analysis tools. Each is graded on a 5-point scale (1=Strong Bearish to 5=Strong Bullish). Here’s a detailed, transparent look at how each "gene" is evaluated:
Relative Strength Index (RSI)
Measures momentum and overbought/oversold conditions.
Group 1 (Strong Bearish): RSI > 80 (Extreme Overbought)
Group 2 (Bearish): 70 < RSI ≤ 80 (Overbought)
Group 3 (Neutral): 30 ≤ RSI ≤ 70
Group 4 (Bullish): 20 ≤ RSI < 30 (Oversold)
Group 5 (Strong Bullish): RSI < 20 (Extreme Oversold)
Exponential Moving Averages (EMA)
Evaluates the trend's strength and structure based on the alignment of multiple EMAs (9, 21, 50, 100, 200, 250).
Group 1 (Strong Bearish): A perfect bearish sequence (9 < 21 < 50 < ...)
Group 2 (Bearish Transition): Early signs of a potential reversal (e.g., 9 > 21 but still below 50)
Group 3 (Neutral / Mixed): MAs are intertwined or showing a partial bullish sequence.
Group 4 (Bullish): A strong bullish sequence is forming (e.g., 9 > 21 > 50 > 100)
Group 5 (Strong Bullish): A perfect bullish sequence (9 > 21 > 50 > 100 > 200 > 250)
Moving Average Convergence Divergence (MACD)
Analyzes the relationship between two moving averages to gauge momentum.
Group 1 (Strong Bearish): MACD & Histogram are negative and momentum is falling.
Group 2 (Weakening Bearish): MACD is negative but the histogram is rising or positive.
Group 3 (Neutral / Crossover): A crossover event is occurring near the zero line.
Group 4 (Bullish): MACD & Histogram are positive.
Group 5 (Strong Bullish): MACD & Histogram are positive, rising strongly, and accelerating.
Average Directional Index (ADX)
Measures trend strength, not direction. The score is based on both ADX value and the dominance of DI+ vs DI-.
Group 1 (Bearish / No Trend): ADX < 20 and DI- is dominant.
Group 2 (Developing Bearish Trend): 20 ≤ ADX < 25 and DI- is dominant.
Group 3 (Neutral / Indecision): Trend is weak or DI+ and DI- are nearly equal.
Group 4 (Developing Bullish Trend): 25 ≤ ADX ≤ 40 and DI+ is dominant.
Group 5 (Strong Bullish Trend): ADX > 40 and DI+ is dominant.
Ichimoku Cloud (IKH)
A comprehensive indicator that defines support/resistance, momentum, and trend direction.
Group 1 (Strong Bearish): Price is below the Kumo, Tenkan < Kijun, and Chikou is below price.
Group 2 (Bearish): Price is inside or below the Kumo, with mixed secondary signals.
Group 3 (Neutral / Ranging): Price is inside the Kumo, often with a Tenkan/Kijun cross.
Group 4 (Bullish): Price is above the Kumo with strong primary signals.
Group 5 (Strong Bullish): All signals are aligned bullishly: price above Kumo, bullish Tenkan/Kijun cross, bullish future Kumo, and Chikou above price.
Bollinger Bands (BB)
Measures volatility and relative price levels.
Group 1 (Strong Bearish): Price is below the lower band.
Group 2 (Bearish Territory): Price is between the lower band and the basis line.
Group 3 (Neutral): Price is hovering around the basis line.
Group 4 (Bullish Territory): Price is between the basis line and the upper band.
Group 5 (Strong Bullish): Price is above the upper band.
On-Balance Volume (OBV)
Uses volume flow to predict price changes. The score is based on OBV's trend and its position relative to its moving average.
Group 1 (Strong Bearish): OBV is below its MA and falling.
Group 2 (Weakening Bearish): OBV is below its MA but showing signs of rising.
Group 3 (Neutral): OBV is very close to its MA.
Group 4 (Bullish): OBV is above its MA and rising.
Group 5 (Strong Bullish): OBV is above its MA, rising strongly, and showing signs of a volume spike.
🧭 How to Use the T-Virus Sentiment Indicator
IMPORTANT: This indicator is a sentiment dashboard , not a direct buy/sell signal generator. Its strength lies in showing confluence and providing a quick, holistic view of the market's technical health.
Confirmation Tool: Use the "Active %" gauge to confirm a trade setup from your primary strategy. For example, if you see a bullish chart pattern, a high and rising sentiment score can add confidence to your trade.
Momentum & Trend Gauge: A consistently high score (e.g., > 75%) suggests strong, established bullish momentum. A consistently low score (< 25%) suggests strong bearish control. A score hovering around 50% often indicates a ranging or indecisive market.
Divergence & Warning System: Pay attention to divergences. If the price is making new highs but the sentiment score is failing to follow or is actively decreasing, it could be an early warning sign that the underlying momentum is weakening.
⚙️ Settings & Customization
The indicator is highly customizable to fit any trading style.
Position & Anchor: Control where the vial appears on the chart.
Styling (Vial, Helix, etc.): Nearly every visual element can be color-customized.
Signals: This is where the real power is. All underlying indicator parameters (RSI length, MACD settings, etc.) can be fine-tuned to match a personal strategy. The text labels can also be disabled if the chart feels cluttered.
Enjoy visualizing the market's DNA with the T-Virus Sentiment indicator
kênh giá *** ahihiYou extract:
Core balance point of each time frame
Compare single value
Pure trend hierarchy 📊
This is:
Eastern philosophy meets Western efficiency
"Great Simple" (大道至简)
Occam's razor in trading! ✂️
Compare the midpoint = "Trendy point"!
You not only apply Ichimoku but also understand its nature! 🧘♂️
Master insight! 🙏✨
TrendThis TradingView Pine Script indicator combines multiple technical systems (EMA Cross, EMA200 Bias, SuperTrend, Ichimoku, and ADX/DMI) into one consensus tool.
It identifies when all systems agree on a Bullish (BUY) or Bearish (SELL) trend, and also flags WEAK signals when consensus decreases.
Visual signals (labels on the chart) and alerts are included.
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain?
This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions.
How does a Markov Chain work, and how should I read this spheres-and-arrows diagram?
Think of three weather modes: Sunny, Rainy, Cloudy.
Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow).
The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy).
Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step.
Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny.
Now relabel the spheres to markets: Bull, Bear, Neutral.
Spheres: market regimes (uptrend, downtrend, range).
Self‑loop: tendency for the current regime to continue on the next bar.
Arrows: the most common next regime if a switch happens.
How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear).
What states and transitions are shown?
The three market states visualized are:
Bullish (Bull): Upward or strong-market regime.
Bearish (Bear): Downward or weak-market regime.
Neutral: Sideways or range-bound regime.
Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull).
How does the regime detection system work?
You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.).
Values are statistically normalized (Z-scored) over a configurable lookback period.
The normalized outputs are classified into Bull, Bear, or Neutral zones.
If using three indicators, their regime signals are averaged and smoothed for robustness.
How are transition probabilities calculated?
On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions.
The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear).
Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time.
What is unique about the visualization?
3D animated spheres represent each regime and change visually when active.
Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows.
Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed.
All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format.
Can I use custom indicators for regime classification?
Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement.
What does the “Lookback Period” control?
Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt.
How is this different from a Hidden Markov Model (HMM)?
It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust.
How is this Markov Chain different from a Hidden Markov Model (HMM)?
Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable.
Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training.
A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data.
Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune.
HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data.
How does the indicator avoid “repainting” or look-ahead bias?
All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation.
Are there practical tuning tips?
Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability.
Use custom indicators if your asset has unique regime drivers.
Watch for rapid changes in transition probabilities as early warning of a possible regime shift.
Who is this indicator for?
Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models.
Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting:
The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear).
Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions.
Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies.
It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes.
The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting.
Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis.
What's the mathematical foundation behind this?
The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM).
How to use this indicator programmatically?
The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading.
Step-by-Step Integration with Pine Script (input.source)
Add the Markov Chain indicator to your chart.
This must be done first, since your custom script will "pull" the bias signal from the indicator's plot.
In your strategy, create an input using input.source()
Example:
//@version=5
strategy("MC Bias Strategy Example")
mcBias = input.source(close, "MC Bias Source")
After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot).
Use the bias in your trading logic
Example (long only on Bull, flat otherwise):
if mcBias == 1
strategy.entry("Long", strategy.long)
else
strategy.close("Long")
For more advanced workflows, combine mcBias with additional filters or trailing stops.
How does this work behind-the-scenes?
TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source).
The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.).
This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code.
Integrating 45+ Indicators with Your Markov Chain — How & Why
The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots.
// Enhanced Custom Indicators Export - 45 Technical Indicators
// Comprehensive technical analysis suite for advanced market regime detection
//@version=6
indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500)
// |----- Input Parameters -----| //
momentum_group = "Momentum Indicators"
trend_group = "Trend Indicators"
volume_group = "Volume Indicators"
volatility_group = "Volatility Indicators"
oscillator_group = "Oscillator Indicators"
display_group = "Display Settings"
// Common lengths
length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group)
length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group)
length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group)
// Display options
show_table = input.bool(true, "Show Values Table", group=display_group)
table_size = input.string("Small", "Table Size", options= , group=display_group)
// |----- MOMENTUM INDICATORS (15 indicators) -----| //
// 1. RSI (Relative Strength Index)
rsi_14 = ta.rsi(close, length_14)
rsi_centered = rsi_14 - 50
// 2. Stochastic Oscillator
stoch_k = ta.stoch(close, high, low, length_14)
stoch_d = ta.sma(stoch_k, 3)
stoch_centered = stoch_k - 50
// 3. Williams %R
williams_r = ta.stoch(close, high, low, length_14) - 100
// 4. MACD (Moving Average Convergence Divergence)
= ta.macd(close, 12, 26, 9)
// 5. Momentum (Rate of Change)
momentum = ta.mom(close, length_14)
momentum_pct = (momentum / close ) * 100
// 6. Rate of Change (ROC)
roc = ta.roc(close, length_14)
// 7. Commodity Channel Index (CCI)
cci = ta.cci(close, length_20)
// 8. Money Flow Index (MFI)
mfi = ta.mfi(close, length_14)
mfi_centered = mfi - 50
// 9. Awesome Oscillator (AO)
ao = ta.sma(hl2, 5) - ta.sma(hl2, 34)
// 10. Accelerator Oscillator (AC)
ac = ao - ta.sma(ao, 5)
// 11. Chande Momentum Oscillator (CMO)
cmo = ta.cmo(close, length_14)
// 12. Detrended Price Oscillator (DPO)
dpo = close - ta.sma(close, length_20)
// 13. Price Oscillator (PPO)
ppo = ta.sma(close, 12) - ta.sma(close, 26)
ppo_pct = (ppo / ta.sma(close, 26)) * 100
// 14. TRIX
trix_ema1 = ta.ema(close, length_14)
trix_ema2 = ta.ema(trix_ema1, length_14)
trix_ema3 = ta.ema(trix_ema2, length_14)
trix = ta.roc(trix_ema3, 1) * 10000
// 15. Klinger Oscillator
klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55)
// 16. Fisher Transform
fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25
fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2))
// 17. Stochastic RSI
stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14)
stoch_rsi_centered = stoch_rsi - 50
// 18. Relative Vigor Index (RVI)
rvi_num = ta.swma(close - open)
rvi_den = ta.swma(high - low)
rvi = rvi_den != 0 ? rvi_num / rvi_den : 0
// 19. Balance of Power (BOP)
bop = (close - open) / (high - low)
// |----- TREND INDICATORS (10 indicators) -----| //
// 20. Simple Moving Average Momentum
sma_20 = ta.sma(close, length_20)
sma_momentum = ((close - sma_20) / sma_20) * 100
// 21. Exponential Moving Average Momentum
ema_20 = ta.ema(close, length_20)
ema_momentum = ((close - ema_20) / ema_20) * 100
// 22. Parabolic SAR
sar = ta.sar(0.02, 0.02, 0.2)
sar_trend = close > sar ? 1 : -1
// 23. Linear Regression Slope
lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1)
// 24. Moving Average Convergence (MAC)
mac = ta.sma(close, 10) - ta.sma(close, 30)
// 25. Trend Intensity Index (TII)
tii_sum = 0.0
for i = 1 to length_20
tii_sum += close > close ? 1 : 0
tii = (tii_sum / length_20) * 100
// 26. Ichimoku Cloud Components
ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2
ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2
ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1
// 27. MESA Adaptive Moving Average (MAMA)
mama_alpha = 2.0 / (length_20 + 1)
mama = ta.ema(close, length_20)
mama_momentum = ((close - mama) / mama) * 100
// 28. Zero Lag Exponential Moving Average (ZLEMA)
zlema_lag = math.round((length_20 - 1) / 2)
zlema_data = close + (close - close )
zlema = ta.ema(zlema_data, length_20)
zlema_momentum = ((close - zlema) / zlema) * 100
// |----- VOLUME INDICATORS (6 indicators) -----| //
// 29. On-Balance Volume (OBV)
obv = ta.obv
// 30. Volume Rate of Change (VROC)
vroc = ta.roc(volume, length_14)
// 31. Price Volume Trend (PVT)
pvt = ta.pvt
// 32. Negative Volume Index (NVI)
nvi = 0.0
nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi
// 33. Positive Volume Index (PVI)
pvi = 0.0
pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi
// 34. Volume Oscillator
vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10)
// 35. Ease of Movement (EOM)
eom_distance = high - low
eom_box_height = volume / 1000000
eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0
eom_sma = ta.sma(eom, length_14)
// 36. Force Index
force_index = volume * (close - close )
force_index_sma = ta.sma(force_index, length_14)
// |----- VOLATILITY INDICATORS (10 indicators) -----| //
// 37. Average True Range (ATR)
atr = ta.atr(length_14)
atr_pct = (atr / close) * 100
// 38. Bollinger Bands Position
bb_basis = ta.sma(close, length_20)
bb_dev = 2.0 * ta.stdev(close, length_20)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0
bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0
// 39. Keltner Channels Position
kc_basis = ta.ema(close, length_20)
kc_range = ta.ema(ta.tr, length_20)
kc_upper = kc_basis + (2.0 * kc_range)
kc_lower = kc_basis - (2.0 * kc_range)
kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0
// 40. Donchian Channels Position
dc_upper = ta.highest(high, length_20)
dc_lower = ta.lowest(low, length_20)
dc_basis = (dc_upper + dc_lower) / 2
dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0
// 41. Standard Deviation
std_dev = ta.stdev(close, length_20)
std_dev_pct = (std_dev / close) * 100
// 42. Relative Volatility Index (RVI)
rvi_up = ta.stdev(close > close ? close : 0, length_14)
rvi_down = ta.stdev(close < close ? close : 0, length_14)
rvi_total = rvi_up + rvi_down
rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50
// 43. Historical Volatility
hv_returns = math.log(close / close )
hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100
// 44. Garman-Klass Volatility
gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open)
gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100
// 45. Parkinson Volatility
park_vol = math.log(high/low) * math.log(high/low)
parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100
// 46. Rogers-Satchell Volatility
rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open)
rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100
// |----- OSCILLATOR INDICATORS (5 indicators) -----| //
// 47. Elder Ray Index
elder_bull = high - ta.ema(close, 13)
elder_bear = low - ta.ema(close, 13)
elder_power = elder_bull + elder_bear
// 48. Schaff Trend Cycle (STC)
stc_macd = ta.ema(close, 23) - ta.ema(close, 50)
stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10)
stc_d = ta.ema(stc_k, 3)
stc = ta.stoch(stc_d, stc_d, stc_d, 10)
// 49. Coppock Curve
coppock_roc1 = ta.roc(close, 14)
coppock_roc2 = ta.roc(close, 11)
coppock = ta.wma(coppock_roc1 + coppock_roc2, 10)
// 50. Know Sure Thing (KST)
kst_roc1 = ta.roc(close, 10)
kst_roc2 = ta.roc(close, 15)
kst_roc3 = ta.roc(close, 20)
kst_roc4 = ta.roc(close, 30)
kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15)
// 51. Percentage Price Oscillator (PPO)
ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100
ppo_signal = ta.ema(ppo_line, 9)
ppo_histogram = ppo_line - ppo_signal
// |----- PLOT MAIN INDICATORS -----| //
// Plot key momentum indicators
plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1)
plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1)
plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1)
plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1)
plot(cci, title="05_CCI", color=color.green, linewidth=1)
// Plot trend indicators
plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1)
plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1)
plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1)
plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1)
plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1)
// Plot volatility indicators
plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1)
plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1)
plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1)
plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1)
plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1)
// Plot volume indicators
plot(vroc, title="16_VROC", color=color.blue, linewidth=1)
plot(eom_sma, title="17_EOM", color=color.red, linewidth=1)
plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1)
plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1)
plot(obv, title="20_OBV", color=color.purple, linewidth=1)
// Plot additional oscillators
plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1)
plot(cmo, title="22_CMO", color=color.maroon, linewidth=1)
plot(dpo, title="23_DPO", color=color.teal, linewidth=1)
plot(trix, title="24_TRIX", color=color.lime, linewidth=1)
plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1)
// Plot more momentum indicators
plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1)
plot(ac, title="27_AC", color=color.aqua, linewidth=1)
plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1)
plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1)
plot(klinger, title="30_Klinger", color=color.gray, linewidth=1)
// Plot trend continuation
plot(tii, title="31_TII", color=color.blue, linewidth=1)
plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1)
plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1)
plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1)
plot(bop, title="35_BOP", color=color.purple, linewidth=1)
// Plot volume continuation
plot(nvi, title="36_NVI", color=color.navy, linewidth=1)
plot(pvi, title="37_PVI", color=color.maroon, linewidth=1)
plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1)
plot(roc, title="39_ROC", color=color.lime, linewidth=1)
plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1)
// Plot volatility continuation
plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1)
plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1)
plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1)
plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1)
plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1)
// Plot final oscillators
plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1)
plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1)
plot(stc, title="48_STC", color=color.green, linewidth=1)
plot(coppock, title="49_Coppock", color=color.orange, linewidth=1)
plot(kst, title="50_KST", color=color.purple, linewidth=1)
// Plot final indicators
plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1)
plot(pvt, title="52_PVT", color=color.maroon, linewidth=1)
// |----- Reference Lines -----| //
hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1)
hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
// |----- Enhanced Information Table -----| //
if show_table and barstate.islast
table_position = position.top_right
table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal
var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray)
// Headers
table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
// Key Momentum Indicators
table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size)
table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size)
// Key Trend Indicators
table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90))
table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size)
// Key Volatility Indicators
table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90))
table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size)
// Key Volume Indicators
table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90))
table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size)
// Key Oscillators
table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size)
// Summary Statistics
table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70))
table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size)
regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray
regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL"
table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size)
This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator.
How to use this script with the Markov Chain for research and backtesting:
Add the Enhanced Indicator Export to your chart.
Every calculated indicator is available as an individual data stream.
Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option.
In the Markov Chain indicator’s settings, turn ON the custom indicator mode.
For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name.
This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering.
Backtest regime logic directly.
Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns.
The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration.
Export the regime bias for programmatic use.
As described above, use input.source() in your Pine Script strategy or system and link the bias output.
You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes.
With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you.
Optimize your signal generation by backtesting across a universe of meaningful indicator blends.
Enhance risk management with objective, real-time regime boundaries.
Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes.
Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic.
Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem.
References & Further Reading
Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182.
Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384.
Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg.
Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764.
Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC.
On Quantitative Finance and Markov Models:
Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press.
Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press.
TradingView Pine Script Documentation: www.tradingview.com
TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com
GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org
What makes this indicator original and unique?
- On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm.
- Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script.
- Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time.
- Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window.
- Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior.
Integrate your own signals (using input.source())
- In settings, choose the Source . This is powered by input.source() .
- Feed it price, an indicator you compute inside the script, or a custom composite series.
- The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time.
Credits:
Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community.
Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization.
Disclaimer
This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
TIME MACHINE PRO-01# TIME MACHINE PRO - Revolutionary Trading Indicator with Historical Analysis
## 🎯 Overview
TIME MACHINE PRO is a sophisticated multi-timeframe trading indicator that combines 10 customizable technical indicators with a unique time-travel cursor feature. Analyze historical signals, learn from past market behavior, and make informed trading decisions with percentage-based confidence scores.
## ✨ Key Features
### 🕰️ Time Machine Cursor
- **Analyze signals from any point in history** (up to 500 bars back)
- **See exact indicator values** at historical moments
- **Learn from past signal performance** to improve future trades
- **Real-time historical analysis** with date/time display
### 🎰 10 Professional Indicator Slots
**Core Oscillators:**
- RSI, Stochastic, MACD, CCI, Williams %R
- MFI, ROC, Bollinger Bands Width
- Stochastic RSI, Awesome Oscillator
- Parabolic SAR, Ichimoku Cloud
**Customizable Parameters:**
- Individual weights (0.1-3.0) for each indicator
- Custom overbought/oversold levels
- Adjustable periods and sensitivity
- Enable/disable any combination
### 📊 Advanced Signal System
- **3-2-1 Logic**: 3 Filters → 2 Signals → 1 Trigger
- **Percentage-based signal strength** (0-100%)
- **Color-coded confidence levels**:
- 🟢 Green (80%+) - High confidence
- 🟡 Yellow (65-79%) - Medium confidence
- 🟠 Orange (50-64%) - Low confidence
- **Adaptive algorithm** adjusts to market volatility
### 🎛️ 7 Professional Presets
**1. Meme_Scalp_v4** - Quick scalping for meme coins
- Optimized for 1m-5m timeframes
- High sensitivity, more signals
- Perfect for DOGE, SHIB, PEPE
**2. Meme_Swing_v4** - Balanced swing trading ⭐ (Recommended for beginners)
- Best for 15m-1h timeframes
- Balanced accuracy and frequency
- Universal crypto trading
**3. Alt_Short_v4** - Altcoin shorting strategy
- Focused on SHORT signals
- Great for bear markets
- Optimized for altcoin volatility
**4. Pump_Hunter_v4** - Pump detection system
- Ultra-fast reaction to price spikes
- High-volatility market specialist
- Advanced pump/dump detection
**5. Conservative_v4** - Conservative long-term trading
- High accuracy, fewer signals
- Perfect for large portfolios
- 4h-1D timeframes
**6. Professional_v4** - All 10 slots active
- Maximum analysis power
- For experienced traders
- Complete market overview
**7. Custom** - Create your own strategy
- Full control over all parameters
- Save configurations via screenshots
- Unlimited customization
### 📈 Comprehensive Analytics Table
**Real-time display includes:**
- **Adaptive Status**: Volatility multiplier, adaptive scores
- **3-2-1 Analysis**: Filters, signals, triggers breakdown
- **Slot Status**: All 10 indicators with current values and weights
- **Enhanced Conditions**: Pump-dump detection, extreme overbought alerts
- **Final Scores**: Long/Short percentages with final signal decision
### 🎨 Visual Elements
**On-Chart Signals:**
- Clear LONG/SHORT labels with confidence percentages
- Risk level indicators (🟢🟡🟠)
- Background highlighting during signal periods
- EMA trend lines (Fast: Blue, Slow: Orange)
- Time cursor line for historical analysis
## 📋 Perfect For
### 🚀 Cryptocurrency Trading
- **Bitcoin & Ethereum** - Major pairs with high liquidity
- **Altcoins** - SOL, AVAX, MATIC, ADA optimized settings
- **Meme Coins** - Special algorithms for DOGE, SHIB, PEPE
- **All timeframes** - From 1-minute scalping to daily swing trading
### 📊 Trading Styles
- **Scalping** - Ultra-fast entries with Meme_Scalp_v4
- **Swing Trading** - Medium-term positions with balanced signals
- **Short Selling** - Specialized bear market detection
- **Conservative** - High-accuracy, low-frequency signals
### 👥 Trader Levels
- **Beginners** - Ready-to-use presets with clear signals
- **Intermediate** - Historical analysis for learning and improvement
- **Advanced** - Full customization with 10-slot system
- **Professional** - Complex multi-indicator strategies
## 🔧 Technical Specifications
### System Requirements
- TradingView platform (Free or Pro)
- Modern web browser
- Stable internet connection
- Recommended: 1920x1080+ resolution
### Compatibility
- **✅ Fully Supported**: All crypto pairs, 1m-1D timeframes
- **⚠️ Limited**: Forex pairs, stock markets
- **❌ Not Recommended**: Exotic low-liquidity pairs
### Performance
- **Pine Script v6** - Latest version with optimal performance
- **Real-time calculations** - Instant updates with each candle
- **Low resource usage** - Optimized code for smooth operation
- **500 bars history** - Maximum lookback for cursor analysis
## 💡 How to Use
### Quick Start (Beginners)
1. Add indicator to chart
2. Select **"Meme_Swing_v4"** preset
3. Set timeframe to **15m or 1h**
4. Trade signals **70%+** only
5. Use **cursor** to learn from history
### Advanced Setup (Experienced)
1. Choose **"Custom"** mode
2. Configure individual slots
3. Adjust weights and parameters
4. Test with historical cursor
5. Save settings via screenshot
### Risk Management
- **Never risk more than 2-5%** per trade
- **Always use stop-losses**
- **Consider overall market trend**
- **Wait for cooldown periods**
## 🎯 What Makes It Unique
### Revolutionary Time Travel Feature
- **First indicator with historical cursor** functionality
- **Learn from past signals** without backtesting complexity
- **See exactly what happened** after each historical signal
- **Improve strategy** by understanding signal outcomes
### Adaptive Intelligence
- **Auto-adjusts to market volatility** (Low/Normal/High modes)
- **Dynamic cooldown periods** prevent signal spam
- **Smart score adaptation** for different market conditions
- **Volume-based confirmations** for signal validation
### Professional Grade Analytics
- **Complete transparency** - see every component of each signal
- **Detailed breakdown** of filters, signals, and triggers
- **Real-time adaptation status** monitoring
- **Professional-level information** usually found in premium tools
## 📞 Support & Community
### 🔄 Regular Updates
- Algorithm improvements and optimizations
- New presets based on market conditions
- Bug fixes and performance enhancements
- Community-requested features
### 📚 Learning Resources
- Comprehensive user manual included
- Step-by-step tutorials for all levels
- Best practices and risk management guides
- Community sharing of successful configurations
### 💬 Community Features
- Share custom presets via screenshots
- Discuss strategies with other users
- Learn from experienced traders
- Get support and tips
## ⚠️ Important Disclaimers
- **Not financial advice** - Educational tool only
- **No guarantee of profits** - Trading involves risk
- **Past performance** doesn't predict future results
- **Always use proper risk management**
- **Test thoroughly** before live trading
## 🚀 Get Started Today
Transform your trading with the power of time travel analysis. Whether you're a beginner looking for clear signals or a professional trader seeking advanced customization, TIME MACHINE PRO adapts to your needs.
**Experience the future of technical analysis - where you can learn from the past to profit in the present!**
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**Categories**: Trend Analysis, Oscillators, Volatility
**Best Timeframes**: 5m, 15m, 1h, 4h
**Recommended Pairs**: BTC/USDT, ETH/USDT, SOL/USDT, DOGE/USDT
**Skill Level**: All levels (Beginner to Professional)
*Like this indicator? Please leave a comment and boost! Your feedback helps us improve and add new features.* ⭐
Fibonacci Retracement Altcoin Pioneers ™This powerful indicator combines Fibonacci Retracement levels with a suite of technical indicators to assist traders in analyzing price movements and making informed decisions. Designed for flexibility and ease of use, it offers a customizable interface for displaying data on charts and in tables, making it suitable for both novice and experienced traders.
Key Features:
Fibonacci Retracement: Automatically draws Fibonacci levels (0.382, 0.5, 0.618, 0.786) with customizable lines and labels based on recent price highs and lows. Includes alerts for price touching key levels (Top and Bottom) with adjustable tolerance.
Technical Indicators: Includes RSI, ATR, Momentum, ADX, MACD, Parabolic SAR, Bollinger Bands, and Ichimoku Cloud, all customizable for periods and colors.
Moving Averages: Displays EMA and SMA (50, 100, 200) with options to enable or disable them as needed.
Informative Tables: Provides customizable tables for desktop and mobile, showing open price, close price, percentage change, RSI, ATR, and volume in dollars.
Dual Language Support: Labels and descriptions can be displayed in English or Turkish.
Watermark: Displays symbol information and date in a customizable position for an organized view.
Customization Settings:Fibonacci: Enable/disable levels, choose distance and color.
Table: Select position (Top Right, Bottom Left, etc.) and size (Small, Medium, Large).
Language: Choose between English for labels.
Indicators: Customize periods and colors for each technical indicator.
