MACD + Scaled DoubleCCIDouble CCI Histo on top, MacD histo on bottom. Long when both sides are green, short when both sides are red.
Fighter
FF
THE WINNER
CHICKEN DINNER!
지표 및 전략
Perfect MA Touch (EMA/SMA + Font Size) – ExtendedThis is an extension of the Perfect MA touch with 6 total spaces for the Moving Averages.
When the candle touches the MA for the first time it will have a 1, and then the 5 the time it will leave a 5. Make you trading decisions with help from the 5 candle high and low.
Relative Strength IndexHere, RSI and Volume are used side by side. When the orange middle band is crossed upwards by the RSI lines, it indicates an upward direction, while a downward cross suggests a downward trend.
The RSI 70 level is a critical zone that indicates the stock is overbought and should be approached with caution. RSI 30 and below suggest the stock is oversold and potential buyers may start to appear in these areas.
YASINKARACA EMA5-13-21-34-55This is an indicator consisting of EMA5, EMA13, EMA21, EMA34, and EMA55 plotted below the chart. What you need to pay attention to is that when the white-colored EMA55 is at the bottom and EMA5 is at the top, it indicates that the trend is upwards. If the opposite is true, the trend has turned downwards.
Wishing you success and hoping you use it in good days.
Polygot Moving AveragesDescription
This is essentially a source merger of Bollinger Bands by Trading View and Simple Moving Averages by stoxxinbox. My additions and subtractions are minimal. There is the BB MA, which I default at 5d, and the other 4 averages are the standard 21, 50, 100, 200, day moving averages. I default the averaging method to WMA (Weighted Moving Average). The method of averaging can be changed as also can the lengths of the inputs to match user preferences. This is what I wanted for an indicator and didn't find.
Usage
The same as you would use any other BB or MA indicator. The benefit of this one is that it has 4 MAs, one MA with the Bollinger Bands attached, and the colours adjusted to be easy on the eyes when using high contrast themes, to be discernible yet sit quietly in the background with lines and candle sticks everywhere shouting for attention. I use it as a base first indicator which I can hide easily (imagine hiding five MA indicators individually constantly) when the more serious indicators come into play.
HTF 30-m Visualiser for 3M - ADK - WHTF 30-m Visualiser — use on 3-minute charts
Purpose – gives 3-minute scalpers an unobtrusive snapshot of the last completed 30-minute candle.
Visual elements
Two dotted verticals show the 30-m candle’s start and an “early” finish one 3-min bar before the real close (27 min span).
Vertical colour follows candle direction: green for up, red for down.
Dotted green horizontal at the 30 m open and red horizontal at its close, confined between the verticals.
Verticals extend only from that candle’s low to its high.
Data window – self-prunes to keep roughly two days of 30-m structure (~48 candles) so the chart stays light.
Typical uses – aligning micro entries with 30-m bias, marking session blocks, anchoring VWAP or order-flow studies to reliable HTF pivots.
Momentum + Keltner Stochastic Combo)The Momentum-Keltner-Stochastic Combination Strategy: A Technical Analysis and Empirical Validation
This study presents an advanced algorithmic trading strategy that implements a hybrid approach between momentum-based price dynamics and relative positioning within a volatility-adjusted Keltner Channel framework. The strategy utilizes an innovative "Keltner Stochastic" concept as its primary decision-making factor for market entries and exits, while implementing a dynamic capital allocation model with risk-based stop-loss mechanisms. Empirical testing demonstrates the strategy's potential for generating alpha in various market conditions through the combination of trend-following momentum principles and mean-reversion elements within defined volatility thresholds.
1. Introduction
Financial market trading increasingly relies on the integration of various technical indicators for identifying optimal trading opportunities (Lo et al., 2000). While individual indicators are often compromised by market noise, combinations of complementary approaches have shown superior performance in detecting significant market movements (Murphy, 1999; Kaufman, 2013). This research introduces a novel algorithmic strategy that synthesizes momentum principles with volatility-adjusted envelope analysis through Keltner Channels.
2. Theoretical Foundation
2.1 Momentum Component
The momentum component of the strategy builds upon the seminal work of Jegadeesh and Titman (1993), who demonstrated that stocks which performed well (poorly) over a 3 to 12-month period continue to perform well (poorly) over subsequent months. As Moskowitz et al. (2012) further established, this time-series momentum effect persists across various asset classes and time frames. The present strategy implements a short-term momentum lookback period (7 bars) to identify the prevailing price direction, consistent with findings by Chan et al. (2000) that shorter-term momentum signals can be effective in algorithmic trading systems.
2.2 Keltner Channels
Keltner Channels, as formalized by Chester Keltner (1960) and later modified by Linda Bradford Raschke, represent a volatility-based envelope system that plots bands at a specified distance from a central exponential moving average (Keltner, 1960; Raschke & Connors, 1996). Unlike traditional Bollinger Bands that use standard deviation, Keltner Channels typically employ Average True Range (ATR) to establish the bands' distance from the central line, providing a smoother volatility measure as established by Wilder (1978).
2.3 Stochastic Oscillator Principles
The strategy incorporates a modified stochastic oscillator approach, conceptually similar to Lane's Stochastic (Lane, 1984), but applied to a price's position within Keltner Channels rather than standard price ranges. This creates what we term "Keltner Stochastic," measuring the relative position of price within the volatility-adjusted channel as a percentage value.
3. Strategy Methodology
3.1 Entry and Exit Conditions
The strategy employs a contrarian approach within the channel framework:
Long Entry Condition:
Close price > Close price periods ago (momentum filter)
KeltnerStochastic < threshold (oversold within channel)
Short Entry Condition:
Close price < Close price periods ago (momentum filter)
KeltnerStochastic > threshold (overbought within channel)
Exit Conditions:
Exit long positions when KeltnerStochastic > threshold
Exit short positions when KeltnerStochastic < threshold
This methodology aligns with research by Brock et al. (1992) on the effectiveness of trading range breakouts with confirmation filters.
3.2 Risk Management
Stop-loss mechanisms are implemented using fixed price movements (1185 index points), providing definitive risk boundaries per trade. This approach is consistent with findings by Sweeney (1988) that fixed stop-loss systems can enhance risk-adjusted returns when properly calibrated.
3.3 Dynamic Position Sizing
The strategy implements an equity-based position sizing algorithm that increases or decreases contract size based on cumulative performance:
$ContractSize = \min(baseContracts + \lfloor\frac{\max(profitLoss, 0)}{equityStep}\rfloor - \lfloor\frac{|\min(profitLoss, 0)|}{equityStep}\rfloor, maxContracts)$
This adaptive approach follows modern portfolio theory principles (Markowitz, 1952) and Kelly criterion concepts (Kelly, 1956), scaling exposure proportionally to account equity.
4. Empirical Performance Analysis
Using historical data across multiple market regimes, the strategy demonstrates several key performance characteristics:
Enhanced performance during trending markets with moderate volatility
Reduced drawdowns during choppy market conditions through the dual-filter approach
Optimal performance when the threshold parameter is calibrated to market-specific characteristics (Pardo, 2008)
5. Strategy Limitations and Future Research
While effective in many market conditions, this strategy faces challenges during:
Rapid volatility expansion events where stop-loss mechanisms may be inadequate
Prolonged sideways markets with insufficient momentum
Markets with structural changes in volatility profiles
Future research should explore:
Adaptive threshold parameters based on regime detection
Integration with additional confirmatory indicators
Machine learning approaches to optimize parameter selection across different market environments (Cavalcante et al., 2016)
References
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L., Nobrega, J. P., & Oliveira, A. L. (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55, 194-211.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (2000). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
Kaufman, P. J. (2013). Trading systems and methods (5th ed.). John Wiley & Sons.
Kelly, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Keltner, C. W. (1960). How to make money in commodities. The Keltner Statistical Service.
Lane, G. C. (1984). Lane's stochastics. Technical Analysis of Stocks & Commodities, 2(3), 87-90.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250.
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Pardo, R. (2008). The evaluation and optimization of trading strategies (2nd ed.). John Wiley & Sons.
Raschke, L. B., & Connors, L. A. (1996). Street smarts: High probability short-term trading strategies. M. Gordon Publishing Group.
Sweeney, R. J. (1988). Some new filter rule tests: Methods and results. Journal of Financial and Quantitative Analysis, 23(3), 285-300.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
Dynamic RSI Regression Bands (Zeiierman)█ Overview
The Dynamic RSI Regression Bands (Zeiierman) is a regression channel tool that dynamically resets based on RSI overbought and oversold conditions. It adapts to trend shifts in real time, creating a highly responsive regression framework that visualizes market sentiment and directional momentum with every RSI-triggered event.
Unlike static regression models, this indicator recalibrates its slope and deviation bands only after the RSI crosses predefined thresholds, helping traders pinpoint new phases of momentum, exhaustion, or reversal.
You’re not just measuring the trend — you’re tracking when and where the trend deserves to be re-evaluated.
█ The Assumption:
"A major momentum shift (RSI crossing OB/OS) signals a potential regime change, and thus, the trend model should be recalibrated from that point."
Instead of using a fixed-length regression (which assumes trend relevance over a static window), this script resets the regression calculation every time RSI crosses into extreme territory. The underlying idea is that extreme RSI levels often represent emotional peaks in market behavior and are statistically likely to be followed by a new price structure.
█ How It Works
⚪ RSI-Based Channel Reset
RSI is monitored continuously
If RSI crosses above the Overbought level, the indicator resets and starts a new regression channel
If RSI crosses below the Oversold level, the same reset logic applies
These events act as “anchor points” for dynamic trend analysis
⚪ Regression Channel Logic
A custom linear regression is calculated from the RSI reset point forward
The lookback grows with each bar after the reset, up to a user-defined max
Regression lines are drawn from the reset point to the current bar
⚪ Standard Deviation Bands
Upper and lower bands are plotted around the regression line using the standard deviation
These serve as dynamic volatility envelopes, great for spotting breakouts or reversals
⚪ Rejection Markers
If price hits the upper/lower band and then closes back inside it, a rejection marker is plotted
Helps visualize failed breakouts and areas of absorption or reversal pressure
█ How to Use
⚪ Detect Trend Shifts
Use the RSI resets to identify when the trend might be starting fresh.
⚪ Watch the Bands for Volatility Extremes
Use the outer bands as soft areas of potential reversal or momentum breakout.
⚪ Spot Rejections for Potential Entry Signals
If price moves outside a band but then quickly returns inside, it often means the breakout failed, and price may reverse.
█ Settings Explained
RSI Length – How many bars RSI uses. Shorter = faster.
OB / OS Levels – Crossing these triggers a regression reset.
Base Regression Length – Max number of bars regression can use post-reset.
StdDev Multiplier – Controls band width from the regression line.
Min Bars After Reset – Ensures channel doesn’t form immediately; waits for structure.
Show Reset Markers – Triangles mark where RSI crossed OB/OS.
Show Rejection Markers – Circles mark where the price rejected the channel edge.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
HL2 Moving Average with BandsThis indicator is designed to assist traders in identifying potential trade entries and exits for S&P 500 (ES) and Nasdaq-100 (NQ) futures. It calculates a Simple Moving Average (SMA) based on the HL2 value (average of high and low prices) of the current candle over a user-defined lookback period (default: 200 periods). The indicator plots this SMA as a blue line, providing a smoothed reference for price trends.
Additionally, it includes upper and lower bands calculated as a percentage (default: 0.5%) above and below the SMA, plotted as green and red lines, respectively. These bands act as dynamic thresholds to identify overbought or oversold conditions. The indicator generates trade signals based on price action relative to these bands:
Long Entry: A green upward triangle is plotted below the candle when the close crosses above the upper band, signaling a potential buy.
Close Long: A red square is plotted above the candle when the close crosses back below the upper band, indicating an exit for the long position.
Short Entry: A red downward triangle is plotted above the candle when the close crosses below the lower band, signaling a potential sell.
Close Short: A green square is plotted below the candle when the close crosses back above the lower band, indicating an exit for the short position.
The script is customizable, allowing users to adjust the SMA length and band percentage to suit their trading style or market conditions. It is plotted as an overlay on the price chart for easy integration with other technical analysis tools.
Recommended Time Frame and Settings for Trading S&P 500 and Nasdaq-100 Futures
Based on research and market dynamics for S&P 500 (ES) and Nasdaq-100 (NQ) futures, the 5-minute chart is recommended as the optimal time frame for day trading with this indicator. This time frame strikes a balance between capturing intraday trends and filtering out excessive noise, which is critical for futures trading due to their high volatility and leverage. The 5-minute chart aligns well with periods of high liquidity and volatility, such as the U.S. market open (9:30 AM–11:00 AM EST) and the afternoon session (2:00 PM–4:00 PM EST), when institutional traders are most active.
Why 5-minute? It allows traders to react to short-term price movements while avoiding the rapid fluctuations of 1-minute charts, which can be prone to false signals in choppy markets. It also provides enough data points to make the SMA and bands meaningful without the lag associated with longer time frames like 15-minute or hourly charts.
Recommended Settings
SMA Length: Set to 200 periods. This longer lookback period smooths the HL2 data, reducing noise and providing a reliable trend reference for the 5-minute chart. A 200-period SMA helps identify significant trend shifts without being overly sensitive to minor price fluctuations.
Band Percentage: 0.5% is more suitable for the volatility of ES and NQ futures on a 5-minute chart, as it generates fewer but higher-probability signals. Wider bands (e.g., 1%) may miss short-term opportunities, while narrower bands (e.g., 0.1%) may produce excessive false signals.
Trading Session Recommendations
Futures markets for ES and NQ are open nearly 24 hours (Sunday 6:00 PM EST to Friday 5:00 PM EST, with a daily break from 4:00 PM–5:00 PM EST), but not all hours are equally optimal due to varying liquidity and volatility. The best times to trade with this indicator are:
U.S. Market Open (9:30 AM–11:00 AM EST): This period is characterized by high volume and volatility, driven by the opening of U.S. equity markets and economic data releases (e.g., 8:30 AM EST reports like CPI or GDP). The indicator’s signals are more reliable during this window due to strong order flow and price momentum.
Afternoon Session (2:00 PM–4:00 PM EST): After the lunchtime lull, volume picks up as institutional traders return, and news or FOMC announcements often drive price action. The indicator can capture breakout moves as prices test the upper or lower bands.
Pre-Market (7:30 AM–9:30 AM EST): For traders comfortable with lower liquidity, this period can offer opportunities, especially around 8:30 AM EST economic releases. However, use tighter risk management due to wider spreads and potential volatility spikes.
Additional Tips
Avoid Low-Volume Periods: Steer clear of trading during low-liquidity hours, such as the overnight session (11:00 PM–3:00 AM EST), when spreads widen and price movements can be erratic, leading to false signals from the indicator.
Combine with Other Tools: Enhance the indicator’s effectiveness by pairing it with support/resistance levels, Fibonacci retracements, or volume analysis to confirm signals. For example, a long entry signal above the upper band is stronger if it coincides with a breakout above a key resistance level.
Risk Management: Given the leverage in futures (e.g., Micro E-mini contracts require ~$1,200 margin for ES), use tight stop-losses (e.g., below the lower band for longs or above the upper band for shorts) to manage risk. Aim for a risk-reward ratio of at least 1:2.
Test Settings: Backtest the indicator on a demo account to optimize the SMA length and band percentage for your specific trading style and risk tolerance. Micro E-mini contracts (MES for S&P 500, MNQ for Nasdaq-100) are ideal for testing due to their lower capital requirements.
Why These Settings and Time Frame?
The 5-minute chart with a 200-period SMA and 0.5% bands is tailored for the volatility and liquidity of ES and NQ futures during peak trading hours. The longer SMA period ensures the indicator captures meaningful trends, while the 0.5% bands are tight enough to signal actionable breakouts but wide enough to avoid excessive whipsaws. Trading during high-volume sessions maximizes the likelihood of valid signals, as institutional participation drives clearer price action.
By focusing on these settings and time frames, traders can leverage the indicator to capitalize on the dynamic price movements of S&P 500 and Nasdaq-100 futures while managing the inherent risks of these markets.
Options Volume ProfileOptions Volume Profile
Introduction
Unlock institutional-level options analysis directly on your charts with Options Volume Profile - a powerful tool designed to visualize and analyze options market activity with precision and clarity. This indicator bridges the gap between technical price action and options flow, giving you a comprehensive view of market sentiment through the lens of options activity.
What Is Options Volume Profile?
Options Volume Profile is an advanced indicator that analyzes call and put option volumes across multiple strikes for any symbol and expiration date available on TradingView. It provides a real-time visual representation of where money is flowing in the options market, helping identify potential support/resistance levels, market sentiment, and possible price targets.
Key Features
Comprehensive Options Data Visualization
Dynamic strike-by-strike volume profile displayed directly on your chart
Real-time tracking of call and put volumes with custom visual styling
Clear display of important value areas including POC (Point of Control)
Value Area High/Low visualization with customizable line styles and colors
BK Daily Range Identification
Secondary lines marking significant volume thresholds
Visual identification of key strike prices with substantial options activity
Value Area Cloud Visualization
Configurable cloud overlays for value areas
Enhanced visual identification of high-volume price zones
Detailed Summary Table
Complete breakdown of call and put volumes per strike
Percentage analysis of call vs put activity for sentiment analysis
Color-coded volume data for instant pattern recognition
Price data for both calls and puts at each strike
Custom Strike Selection
Configure strikes above and below ATM (At The Money)
Flexible strike spacing and rounding options
Custom base symbol support for various options markets
Use Cases
1. Identifying Key Support & Resistance
Visualize where major options activity is concentrated to spot potential support and resistance zones. The POC and Value Area lines often act as magnets for price.
2. Analyzing Market Sentiment
Compare call versus put volume distribution to gauge directional bias. Heavy call volume suggests bullish sentiment, while heavy put volume indicates bearish positioning.
3. Planning Around Institutional Activity
Volume profile analysis reveals where professional traders are positioning themselves, allowing you to align with or trade against smart money.
4. Setting Precise Targets
Use the POC and Value Area High/Low lines as potential profit targets when planning your trades.
5. Spotting Unusual Options Activity
The color-coded volume table instantly highlights anomalies in options flow that may signal upcoming price movements.
Customization Options
The indicator offers extensive customization capabilities:
Symbol & Data Settings : Configure base symbol and data aggregation
Strike Selection : Define number of strikes above/below ATM
Expiration Date Settings : Set specific expiry dates for analysis
Strike Configuration : Customize strike spacing and rounding
Profile Visualization : Adjust offset, width, opacity, and height
Labels & Line Styles : Fully configurable text and visual elements
Value Area Settings : Customize POC and Value Area visualization
Secondary Line Settings : Configure the BK Daily Range appearance
Cloud Visualization : Add colored overlays for enhanced visibility
How to Use
Apply the indicator to your chart
Configure the expiration date to match your trading timeframe
Adjust strike selection and spacing to match your instrument
Use the volume profile and summary table to identify key levels
Trade with confidence knowing where the real money is positioned
Perfect for options traders, futures traders, and anyone who wants to incorporate institutional-level options analysis into their trading strategy.
Take your trading to the next level with Options Volume Profile - where price meets institutional positioning.
Daily Levels & Stats Pro - [Aspect] v4.0# Description of the "Daily Levels & Stats Pro - v4.0" Indicator
This indicator is a powerful tool for market analysis through the lens of key daily levels and statistical price movement indicators. It allows you to display important trading session opening levels, daily statistical movements, and high volatility zones on the price chart.
## Main Indicator Functions:
### Key Time Levels:
- **Daily Open (DO)** - daily trading session opening level at 02:00
- **NY Midnight (NYM)** - New York session opening level at 06:00
- **Trade Open (TO)** - active trading opening level at 10:00
### Analysis Zones:
- **Previous Close Zone (PCZ)** - previous day's closing zone (displayed on M5 timeframe)
- **Open Day Zone (ODZ)** - current day's opening zone (displayed on M5 timeframe)
### Statistical Price Movement Levels:
- **Min** - minimum statistical movement from DO
- **Max** - maximum statistical movement from DO
- **Aver** - average statistical movement from DO
- **Dev-** - lower deviation of movement from DO
- **Dev+** - upper deviation of movement from DO
### TO Impulse Movement Statistical Levels:
- **Aver TO** - average statistical movement from TO
- **Dev+ TO** - upper deviation of movement from TO
- **Max TO** - maximum statistical movement from TO
## Indicator Features:
- Complete customization of colors, styles, and line widths for all levels
- Ability to select time for each main level
- Adjustment of the number of bars for level display
- Automatic calculation of level values relative to DO and TO
- Visual display of TO-levels starts 3 bars before the actual TO point, providing better visual perception
- Ability to enable/disable individual levels and zones
- Automatic updates and resets when the day changes
- Adaptive text labels to mark levels
This indicator is excellent for traders who use statistical data and daily support/resistance levels in their trading strategy. It is particularly useful for DAX40 and other highly liquid instruments where daily trading statistics are important for making trading decisions.
BOS & CHoCH Alert Coin Holding by DTVThis is a comprehensive indicator that combines the concepts of Break of Structure (BOS) and Change of Character (CHoCH) in the Smart Money Concepts style, and automatically sends alerts whenever a CHoCH signal occurs immediately after the most recent BOS.
Key Features:
BOS Detection: Identifies BOS on both bullish and bearish trends based on Swing High/Low levels over a customizable lookback period.
Instant CHoCH Identification: Captures CHoCH immediately after a BOS, stores the CHoCH level, and monitors for a subsequent break back.
Automatic “CHoCH after BOS” Alerts: Only triggers when CHoCH happens right after an unprocessed BOS, ensuring you never miss critical signals.
Visual Overlay: Plots the CHoCH level on the chart and attaches a “CHoCH” label at the exact breakout point for easy historical reference.
User Parameters:
Lookback Swing Length (default 50): Number of bars used to calculate Swing High/Low.
Structure Display: Toggle labels for BOS and CHoCH in both internal and swing structures.
Confluence Filter: Filters out weak breakouts to reduce noise.
Label Count & Size, Colors: Customize to suit personal preferences and chart aesthetics.
Quick Start Guide:
Install: Paste the script into TradingView’s Pine Editor, save, and add it to your chart.
Add Alerts: In TradingView’s Alert dialog, select “Bullish CHoCH after BOS” or “Bearish CHoCH after BOS” to receive notifications via email or popup.
Monitor: Whenever the price breaks the stored CHoCH level after a BOS, a popup will appear and a “CHoCH” label will be placed on the chart, helping you make timely decisions.
With this indicator, you can proactively capture key structural shifts in the market and optimize your trading strategy based on clear, reliable signals.
Advanced Order Flow Indicatorbest order flow indicator can be used with i types of indicators and is best with 1 hour time frame
Volume Aggression Monitor📌 Volume Aggression Monitor — Overview
This indicator helps identify buying and selling pressure (aggression) in real-time by analyzing how market participants are executing trades. It is composed of three main components:
🔍 What Does It Show?
🧭 1. The Thermometer (Above Candles)
🟢 Green Arrow (▲) → Buy Aggression: Buyers are lifting the ask.
🔴 Red Arrow (▼) → Sell Aggression: Sellers are hitting the bid.
⚪ Gray Square (■) → Neutral: No significant price movement or aggression.
💡 Neutral in this context means:
The price barely moved during the candle (open-close % change < direction_threshold, default 0.05%).
No clear buyer or seller dominance. It often appears during low volatility, equilibrium, or market indecision periods. This prevents noise and false directional readings due to random micro-movements.
📊 2. Percentage Panel
A table displaying recent trades or candle data (from a lower timeframe). Colored arrows indicate the direction of aggression (buy/sell). Shows volume, delta, and aggression %.
✅ Use it to:
Track clusters of buy/sell aggression. Spot momentum builds.
⏱️ 3. Cumulative Times & Sales Bar
A horizontal progress bar representing cumulative aggression.
Positive = Buy Aggression dominates.
Negative = Sell Aggression dominates.
📉 Even in sideways price movement, this bar shows who is winning the fight under the surface.
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🧠 How to Use It:
🔹 Confirm Trades
Use the thermometer and aggression signals to confirm your strategy entries (e.g., breakouts, pullbacks, support/resistance).
🔹 Detect Dominance
Observe who is in control: buyers or sellers? Are they pressing or hesitating?
🔹 Filter Market Noise
The neutral state avoids misinterpreting small, meaningless movements as strong signals.
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Component | Meaning
🌡️ Thermometer (▲ ▼ ■) | Who’s in control in each candle
📊 Percentage Panel | Trade details: direction, delta, aggression
📈 Cumulative T&S Bar | Overall aggression bias over time
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YASINKARACA MACD + VolumeMACD, especially when above the ZERO line, indicates that the direction of the stock is upward.
The MACD line is colored green, while the MACD signal line is colored red.
When the MACD line crosses above the signal line, it generates a BUY signal. When the MACD line crosses below the signal line, it generates a SELL signal.
Histograms are represented in green when positive, and in red when negative.
Stochastic Strategy Table with Trend (1m–4H) + Toggle📊 Multi-Timeframe Stochastic Strategy Table with Trend Detection
This script is designed for intraday and swing traders who want to monitor Stochastic momentum across multiple timeframes in real-time — all directly on the main chart.
🔎 What This Script Does
This script builds a compact, color-coded table that displays:
✅ %K and %D values of the Stochastic oscillator
✅ Cross direction (K > D or K < D)
✅ Overbought/Oversold zone conditions
✅ Short-term trend detection via %K movement
It covers ten timeframes:
1m, 2m,3m,5m, 15m, 30m, 1H, 2H, 3H, 4H
🟩 How to Use It
Trend colors in header:
🟢 Green = %K is rising (uptrend)
🔴 Red = %K is falling (downtrend)
⚪ Gray = flat or neutral
Cross Row:
Green background = Bullish (%K > %D)
Red background = Bearish (%K < %D)
Zone Row:
Green = Oversold (%K and %D below 20)
Red = Overbought (%K and %D above 80)
Gray = Neutral zone
Use Case:
Look for multiple timeframes aligning in trend
Enter trades on short timeframes (e.g. 5m) when HTFs confirm direction
Especially powerful when used with price action on 5m/15m candles
⚙️ Configurable Inputs
%K Length
%K Smoothing
%D Length
Table location
Table size
💡 Why This Script Is Unique
Shows true higher timeframe Stochastic values (not interpolated from current chart)
Works in real-time with consistent updates
Trend direction is visualized without needing extra space
Built for serious intraday traders who rely on clean data and signal alignment
🙏 Credits & Notes
This tool was created to solve a real problem: getting accurate HTF stochastic data in a clean, real-time, decision-friendly format.
I built it for my own use — and now I'm sharing it for luck, and for anyone else looking to trade more clearly and confidently.
Feel free to fork, customize, or build upon it.
Good luck, and trade safe! 🍀💹
TrendBoxThis indicator is called "TrendBox," designed to help traders analyze daily price ranges using several technical indicators. Below is a breakdown of its functionality, purpose, and key components:
Purpose
The script overlays indicators on a chart to assess whether the price is above or below key levels:
VWAP (Volume Weighted Average Price, based on the chart's timeframe).
Daily Market Open (fetched from the daily timeframe).
Daily 4-period VWMA (Volume Weighted Moving Average, fetched from the daily timeframe).
VIX-based expected range (high and low levels calculated using the VIX index).
It also displays a status box (optional) summarizing whether the price is above or below these levels, helping traders quickly evaluate market conditions.
Midpoint of Last 3 CandlesThis indicator highlights the market structure by plotting the midpoints of the current and previous two candles. It draws a horizontal line at the average of the high and low for each of these candles, giving a visual cue of the short-term balance point in price action. These midpoints can act as dynamic support and resistance levels, helping traders assess areas of potential reaction or continuation.
Each line is color-coded for clarity: green represents the current candle, orange marks the previous candle, and yellow indicates the one before that. All lines extend into the future on the chart, allowing you to see how price interacts with these levels as new candles form. This simple yet effective tool can be useful in various strategies, especially those focused on price action, scalping, or intraday analysis.
LTF HTF CANDLE fast deployThe "LTF Candle Fast Deploy" script allows you to clearly and dynamically display candles from lower timeframes (LTF) and higher timeframes (HTF) on the same chart. With the cursor function, it becomes simple to move the end line and analyze completely different points. You can configure the number of candles and timeframes, as well as customize colors and borders. One of its key features is temporal alignment: the last LTF candle is forced to coincide with a defined end date (end_date), with a transparent background applied to highlight the area around this date.
Additionally, the script supports two different timeframes, allowing you to simultaneously compare two series of candles, with adjustable width and spacing options to better fit the chart. A summary table can be displayed in an overlay to show information about timeframes and the amount of candles, while a triangle visually marks the candle corresponding to the end date.
Finally, there are performance limits in place to ensure optimal functioning, such as the maximum number of bars analyzed and a limit on the offset, to prevent slowdowns in the chart.
--------------------------------------------------KEY FEATURES--------------------------------------------------
1. **Display of HTF and LTF Candles**
This feature allows you to plot on the chart a configurable number (Amount of Candles) of candles from both a lower timeframe (e.g., 30m) and a higher timeframe (e.g., 4H). The candles are drawn using `box.new` for the body and `line.new` for the wicks, with customizable colors and borders.
2. **Temporal Alignment on Start and End Dates**
The user defines an "end_date" (configurable by the user). The last LTF candle is forced to horizontally align with the corresponding bar at the end_date, calculating a dynamic offset. A semi-transparent background is applied to all bars near the end_date to highlight the concluding period. By simply moving the cursor, you can shift the focus to another area.
3. **Customizable Dual Timeframe**
In addition to the primary LTF, the script supports a second timeframe (2nd Timeframe), with the same offset, buffer, and coloring logic. It is recommended to use an HTF or the same timeframe as the chart. This feature allows you to simultaneously compare two sets of candles from different timeframes on the same chart.
4. **Candle Width and Buffer Controls**
The width (Candle Width) and spacing (Candle Buffer) of the candles are variable, as is the extra horizontal offset (extra_offset). These parameters allow precise adjustment of the visual clutter and alignment with the chart bars.
5. **Summary Table in Overlay**
Upon the last tick (if activated), a table (Show Table) appears in one of the eight available positions (e.g., top right). The table displays:
- LTF: lower timeframe
- HTF: higher timeframe
- Ch TF: chart timeframe
- AoC: amount of candles
- c AoC: amount of chart candles corresponding to the observed zone
Additionally, a triangle (`plotshape`) is drawn above the candle corresponding to the end_date on the main chart to visually identify the alignment moment.
6. **Performance and Limit Management**
The script sets limits on the number of bars analyzed (max_bars_back, max_boxes_count) and an offset maximum (future limit of 500 bars) to prevent slowdowns or excessive drawing.
Enhanced Bollinger Bands📈 *Enhanced Bollinger Bands – Custom Indicator*
This custom indicator is a more flexible and informative version of the traditional *Bollinger Bands*, designed to help traders better visualize price volatility, trend direction, and breakout signals.
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🔍 Key Features:
✅ *Multiple Moving Average Options*
Choose between:
- *SMA (Simple Moving Average)*
- *EMA (Exponential Moving Average)*
- *WMA (Weighted Moving Average)*
This allows you to tailor the indicator to your trading strategy.
✅ *Dynamic Bands Based on Volatility*
The upper and lower bands are calculated using a user-defined standard deviation multiplier, showing volatility around the selected moving average.
✅ *Color-Coded Trend Visualization*
The bands change color based on the slope of the moving average:
- 🟢 *Green* when the trend is up
- 🔴 *Red* when the trend is down
- ⚪ *Gray* when the trend is flat
This helps traders visually confirm trend direction.
✅ *Optional Band Fill*
You can enable a shaded area between the upper and lower bands, making it easier to identify *volatility squeezes* and *expansions*.
✅ *Breakout Signal Arrows*
Automatic signal arrows appear when:
- 📈 Price *crosses above* the upper band (potential breakout)
- 📉 Price *crosses below* the lower band (potential breakdown)
These signals can help spot strong momentum entries.
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⚙️ Inputs:
- *MA Type:* SMA / EMA / WMA
- *Length:* Period for the moving average and standard deviation
- *Multiplier:* Standard deviation multiplier for band width
- *Source:*Price source (default: close)
- *Toggle Fill:* Turn band fill on/off
- *Toggle Signals:* Show or hide breakout arrows
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🧠 How to Use:
- Use band *tightening* as a sign of low volatility (possible breakout setup).
- Use band *expansion* to confirm high momentum moves.
- Use signal arrows for early entries on momentum plays.
- Combine with RSI, MACD, or volume indicators for confluence.
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Let me know if you want to write a version tailored for publishing on TradingView, including tags and disclaimers.
MTF Stoch RSI Confluence + Combined AlertMTF STOCH RSI CONFLUENCE INDICATOR 1m/5m/15m ( Scalping Indicator added on SRSI 1H)
IF all three Stoch are overbought(above 80) the indicator creates a red vertical line. If all Stoch are oversold(below 20) the indicator creates a green vertical line.
RULES!!!!
NEVER TRADE AGAINST THE TREND!!! This is super important!!!!
If 1H SRSI is above 80 with MTF overbouht and ZC is red (Downtrend) then we open a MR Short- (Prefered at PA Spikes) The same for opposites MR Longs.
If 1H SRSI is above 80 with the MTF oversold and ZC green then we can open a Long position. Prefered Momo Long. The same applies for opposite, hence momo short.
YASINKARACA EMA+ICHIMOKUThe combined use of EMA and Ichimoku is important. It is especially effective in identifying stocks that give BUY or SELL signals on the Daily and 4-Hour timeframes. When the candles are above the Ichimoku Cloud, stocks tend to move upwards, while when they are below the cloud, the direction tends to be downwards.
Wishing you success and hoping you use it in good days.
