EMA 9/21/50 + VWAP + MACD + RSI Pro [v6]Overview:
A powerful multi-indicator tool combining Exponential Moving Averages (EMA 9, 21, 50), Volume-Weighted Average Price (VWAP), Moving Average Convergence Divergence (MACD), and Relative Strength Index (RSI) into a single, easy-to-read system. Designed for traders who want a clean, all-in-one dashboard for trend analysis, momentum confirmation, and overbought/oversold conditions.
Key Features:
1. Triple EMA System (9, 21, 50)
Identifies short-term and medium-term trends.
Bullish Signal: EMA 9 > EMA 21 > EMA 50 (Green Highlight)
Bearish Signal: EMA 9 < EMA 21 < EMA 50 (Red Highlight)
Helps confirm trend direction and potential reversals.
2. VWAP (Volume-Weighted Average Price)
Tracks intraday fair value price based on volume.
Bullish: Price above VWAP (Green)
Bearish: Price below VWAP (Red)
3. MACD (Standard 12, 26, 9 Settings)
Shows momentum shifts.
Bullish: MACD line > Signal line (Green)
Bearish: MACD line < Signal line (Red)
Histogram confirms strength of momentum.
4. RSI (14-Period Default)
Identifies overbought (>70) and oversold (<30) conditions.
Red: Overbought (Potential Reversal)
Green: Oversold (Potential Bounce)
5. Signal Dashboard (Top-Right Table)
Real-time summary of all indicators in one place.
Color-coded for quick interpretation (Green = Bullish, Red = Bearish).
How to Use This Indicator?
✅ Trend Confirmation:
Trade in the direction of EMA alignment (9 > 21 > 50 for uptrends).
Use VWAP as dynamic support/resistance.
✅ Momentum Entries:
Look for MACD crossovers while RSI is not extreme.
Avoid buying when RSI > 70 or selling when RSI < 30 (unless strong trend).
✅ Mean Reversion:
Fade extreme RSI readings (overbought/oversold) when price is at key levels.
Who Is This For?
✔ Swing Traders – EMA + MACD combo for trend-following.
✔ Day Traders – VWAP + EMA for intraday bias.
✔ RSI Traders – Clear overbought/oversold signals.
Settings Customization:
Adjust EMA lengths, RSI periods, and MACD settings as needed.
Toggle VWAP visibility on/off.
Why Use This Script?
📌 All-in-One: No need for multiple indicators cluttering your chart.
📌 Visual Clarity: Color-coded signals for quick decision-making.
📌 Flexible: Works on any timeframe (1M, 5M, 1H, Daily, etc.).
Install now and enhance your trading strategy with a professional-grade multi-indicator system!
Not a financial advice. Use at your own discretion and always apply risk management
ابحث في النصوص البرمجية عن "one一季度财报"
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal:
Yearly Quarters = 4 quarters of three months each.
Monthly Quarters = 4 quarters of one week each.
Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function.
Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day.
Sessions Quarters = 4 quarters of 90 minutes each.
90 Minute Quarters = 4 quarters of 22.5 minutes each.
Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each:
Q1 - January, February, March.
Q2 - April, May, June (True Open, April Open).
Q3 - July, August, September.
Q4 - October, November, December.
S&P 500 E-mini Futures (daily candles) — Monthly Cycle.
Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day):
Q1 - Week 1: first Monday of the month.
Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price).
Q3 - Week 3: third Monday of the month.
Q4 - Week 4: fourth Monday of the month.
S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle.
Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action:
Q1 - Monday.
Q2 - Tuesday (True Open, Daily Candle Open Price).
Q3 - Wednesday.
Q4 - Thursday.
S&P 500 E-mini Futures (1 hour candles) — Daily Cycle.
Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity:
Q1 - 18:00 - 00:00 Asia.
Q2 - 00:00 - 06:00 London (True Open).
Q3 - 06:00 - 12:00 NY AM.
Q4 - 12:00 - 18:00 NY PM.
S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle.
6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT):
Asian Session
Q1 - 18:00 - 19:30
Q2 - 19:30 - 21:00 (True Open)
Q3 - 21:00 - 22:30
Q4 - 22:30 - 00:00
London Session
Q1 - 00:00 - 01:30
Q2 - 01:30 - 03:00 (True Open)
Q3 - 03:00 - 04:30
Q4 - 04:30 - 06:00
NY AM Session
Q1 - 06:00 - 07:30
Q2 - 07:30 - 09:00 (True Open)
Q3 - 09:00 - 10:30
Q4 - 10:30 - 12:00
NY PM Session
Q1 - 12:00 - 13:30
Q2 - 13:30 - 15:00 (True Open)
Q3 - 15:00 - 16:30
Q4 - 16:30 - 18:00
S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle.
Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters:
Asian Session
Q1/1 18:00:00 - 18:22:30
Q2 18:22:30 - 18:45:00
Q3 18:45:00 - 19:07:30
Q4 19:07:30 - 19:30:00
Q2/1 19:30:00 - 19:52:30 (True Session Open)
Q2/2 19:52:30 - 20:15:00
Q2/3 20:15:00 - 20:37:30
Q2/4 20:37:30 - 21:00:00
Q3/1 21:00:00 - 21:23:30
etc. 21:23:30 - 21:45:00
London Session
00:00:00 - 00:22:30 (True Daily Open)
00:22:30 - 00:45:00
00:45:00 - 01:07:30
01:07:30 - 01:30:00
01:30:00 - 01:52:30 (True Session Open)
01:52:30 - 02:15:00
02:15:00 - 02:37:30
02:37:30 - 03:00:00
03:00:00 - 03:22:30
03:22:30 - 03:45:00
03:45:00 - 04:07:30
04:07:30 - 04:30:00
04:30:00 - 04:52:30
04:52:30 - 05:15:00
05:15:00 - 05:37:30
05:37:30 - 06:00:00
New York AM Session
06:00:00 - 06:22:30
06:22:30 - 06:45:00
06:45:00 - 07:07:30
07:07:30 - 07:30:00
07:30:00 - 07:52:30 (True Session Open)
07:52:30 - 08:15:00
08:15:00 - 08:37:30
08:37:30 - 09:00:00
09:00:00 - 09:22:30
09:22:30 - 09:45:00
09:45:00 - 10:07:30
10:07:30 - 10:30:00
10:30:00 - 10:52:30
10:52:30 - 11:15:00
11:15:00 - 11:37:30
11:37:30 - 12:00:00
New York PM Session
12:00:00 - 12:22:30
12:22:30 - 12:45:00
12:45:00 - 13:07:30
13:07:30 - 13:30:00
13:30:00 - 13:52:30 (True Session Open)
13:52:30 - 14:15:00
14:15:00 - 14:37:30
14:37:30 - 15:00:00
15:00:00 - 15:22:30
15:22:30 - 15:45:00
15:45:00 - 15:37:30
15:37:30 - 16:00:00
16:00:00 - 16:22:30
16:22:30 - 16:45:00
16:45:00 - 17:07:30
17:07:30 - 18:00:00
S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
Statistical OHLC Projections [neo|]█ OVERVIEW
Statistical OHLC Projections is an indicator designed to offer users a customizable deep-dive on measuring historical price levels for any timeframe. The indicator separates price into two distinct levels, "Manipulation" and "Distribution", where the idea is that for higher timeframe candles, e.g. an up-close candle, the distance from the open to the bottom of the wick would constitute the Manipulation, and the rest would be considered the Distribution. By measuring out these levels, we can gain insight on how far the market may move from higher timeframe opens to their manipulations and distributions, and apply this knowledge to our analysis.
IMPORTANT: Since levels are based on the lookback available on your chart, if the levels aren't being displayed this likely means you don't have enough lookback for your selected timeframe. To check this, enable the stat table to see how many values are available for your timeframe, and either reduce the lookback or increase your chart timeframe.
█ CONCEPTS
The core concept revolves around understanding market behavior through the lens of historical candle structure. The indicator dissects OHLC data to provide statistical boundaries of expected price movement.
- Manipulation Levels: These represent the areas typically seen as liquidity grabs or false moves where price extends in one direction before reversing.
- Distribution Levels: These highlight where the bulk of directional movement tends to occur, often following the manipulation move.
The tool aggregates this data across your selected timeframe to inform you of potential levels associated with it.
█ FEATURES
Multiple Display Types: Display statistical data through two sleek styles, areas or lines. Where areas represent the area between two customizable lookback values, and lines represent one average value.
Adjustable Timeframe Selection: Whether you want to see data based on the 1D chart, or the 1W chart, anything is possible. Simply change the timeframe on the dropdown menu and if there is sufficient lookback the indicator will adjust to your requested timeframe.
Customizable Historical Lookback: By default, the indicator will measure the average 60 values of your requested timeframe, however this may be adjusted to be higher or lower based on your preference. If you want to measure recent moves, 10-20 lookback may be better for you, or if you want more data for less volatile instruments, a value of 100 may be better.
Historical Display: Prevent historical levels from being removed by unchecking the "Remove Previous Drawings" option, this will allow you to examine how the levels previously interacted with price.
NY Midnight Anchoring: By checking the "Use NY Midnight" option, you may see the projection anchored to the New York midnight open time, which is often a significant level on indices.
Alerts: You may enable alerts for any of the indicator's provided levels to stay informed, even when off the charts.
█ How to use
To use the indicator, simply apply it to your chart and modify any of your desired inputs.
By default, the indicator will provide levels for the "1D" timeframe, with a desired lookback of 60, on most instruments and plans this can be gotten when you are on the 30 minute timeframe or above.
When price reaches or extends beyond a manipulation level, observe how it reacts and whether it rejects from that level, if it does this may be an indication that the candle for the timeframe you selected may be reversing.
█ SETTINGS AND OPTIONS
Customize the indicator’s behavior, timeframe sources, and visual appearance to fit your analysis style. Each setting has been designed with flexibility in mind, whether you're working on lower or higher timeframes.
Display Mode: Switch between different display styles for levels: - Default: Shows all statistical levels as individual lines.
- Areas: Plots filled zones between two customizable lookbacks to represent the range between them.
This is ideal for visually mapping high-probability zones of price activity.
Timeframe Settings:
- Show First/Second Timeframe: Choose to show one or both timeframe projections simultaneously.
- First Timeframe / Second Timeframe: Define the higher timeframe candle you want to base calculations on (e.g., 1D, 1W).
- Use NY Midnight: When enabled and using the daily timeframe, the levels will be anchored to the New York Midnight Open (00:00 EST), a key institutional timing reference, especially useful for indices and forex.
Calculation Settings:
- Main Lookback Period: The number of historical candles used in the statistical calculations. A lower number focuses on recent price action, while a higher number smooths results across broader history.
- First Lookback / Second Lookback: Used when “Areas” mode is selected to define the range of the shaded zone. For example, an area from 20 to 60 candles creates a band between short- and long-term price behavior averages.
Visual Settings:
- Line Style: Set your preferred visual style: Solid, Dashed, or Dotted.
- Remove Previous Drawings: When enabled, only the most recent projection is shown on the chart. Disable to retain previous levels and visually backtest their reactions over time.
Color Settings:
Customize each level independently to match your chart theme:
- Manipulation High/Low
- Distribution High/Low
- Open Level
- Label Text Color
Premium/Discount Zones:
- Enable Premium/Discount Zones: Overlay price zones above and below equilibrium to visualize potential overbought (premium) and oversold (discount) areas.
- Premium/Discount Colors: Fully customizable zone colors for clarity and emphasis.
Table Settings:
- Show Statistics Table: Adds an on-chart table summarizing key levels from your active timeframe(s).
- Table Cell Color: Set the background color of the table cells for visibility.
- Table Position: Choose from preset chart locations to position the table where it works best for your layout.
Alerts:
Stay on top of price interactions with key levels even when you're away from the charts.
- Manipulation Hits (High)
- Manipulation Hits (Low)
- Distribution Hits (High)
- Distribution Hits (Low)
Uptrick: Z-Score FlowOverview
Uptrick: Z-Score Flow is a technical indicator that integrates trend-sensitive momentum analysi s with mean-reversion logic derived from Z-Score calculations. Its primary objective is to identify market conditions where price has either stretched too far from its mean (overbought or oversold) or sits at a statistically “normal” range, and then cross-reference this observation with trend direction and RSI-based momentum signals. The result is a more contextual approach to trade entry and exit, emphasizing precision, clarity, and adaptability across varying market regimes.
Introduction
Financial instruments frequently transition between trending modes, where price extends strongly in one direction, and ranging modes, where price oscillates around a central value. A simple statistical measure like Z-Score can highlight price extremes by comparing the current price against its historical mean and standard deviation. However, such extremes alone can be misleading if the broader market structure is trending forcefully. Uptrick: Z-Score Flow aims to solve this gap by combining Z-Score with an exponential moving average (EMA) trend filter and a smoothed RSI momentum check, thus filtering out signals that contradict the prevailing market environment.
Purpose
The purpose of this script is to help traders pinpoint both mean-reversion opportunities and trend-based pullbacks in a way that is statistically grounded yet still mindful of overarching price action. By pairing Z-Score thresholds with supportive conditions, the script reduces the likelihood of acting on random price spikes or dips and instead focuses on movements that are significant within both historical and current contextual frameworks.
Originality and Uniquness
Layered Signal Verification: Signals require the fulfillment of multiple layers (Z-Score extreme, EMA trend bias, and RSI momentum posture) rather than merely breaching a statistical threshold.
RSI Zone Lockout: Once RSI enters an overbought/oversold zone and triggers a signal, the script locks out subsequent signals until RSI recovers above or below those zones, limiting back-to-back triggers.
Controlled Cooldown: A dedicated cooldown mechanic ensures that the script waits a specified number of bars before issuing a new signal in the opposite direction.
Gradient-Based Visualization: Distinct gradient fills between price and the Z-Mean line enhance readability, showing at a glance whether price is trading above or below its statistical average.
Comprehensive Metrics Panel: An optional on-chart table summarizes the Z-Score’s key metrics, streamlining the process of verifying current statistical extremes, mean levels, and momentum directions.
Why these indicators were merged
Z-Score measurements excel at identifying when price deviates from its mean, but they do not intrinsically reveal whether the market’s trajectory supports a reversion or if price might continue along its trend. The EMA, commonly used for spotting trend directions, offers valuable insight into whether price is predominantly ascending or descending. However, relying solely on a trend filter overlooks the intensity of price moves. RSI then adds a dedicated measure of momentum, helping confirm if the market’s energy aligns with a potential reversal (for example, price is statistically low but RSI suggests looming upward momentum). By uniting these three lenses—Z-Score for statistical context, EMA for trend direction, and RSI for momentum force—the script offers a more comprehensive and adaptable system, aiming to avoid false positives caused by focusing on just one aspect of price behavior.
Calculations
The core calculation begins with a simple moving average (SMA) of price over zLen bars, referred to as the basis. Next, the script computes the standard deviation of price over the same window. Dividing the difference between the current price and the basis by this standard deviation produces the Z-Score, indicating how many standard deviations the price is from its mean. A positive Z-Score reveals price is above its average; a negative reading indicates the opposite.
To detect overall market direction, the script calculates an exponential moving average (emaTrend) over emaTrendLen bars. If price is above this EMA, the script deems the market bullish; if below, it’s considered bearish. For momentum confirmation, the script computes a standard RSI over rsiLen bars, then applies a smoothing EMA over rsiEmaLen bars. This smoothed RSI (rsiEma) is monitored for both its absolute level (oversold or overbought) and its slope (the difference between the current and previous value). Finally, slopeIndex determines how many bars back the script compares the basis to check whether the Z-Mean line is generally rising, falling, or flat, which then informs the coloring scheme on the chart.
Calculations and Rational
Simple Moving Average for Baseline: An SMA is used for the core mean because it places equal weight on each bar in the lookback period. This helps maintain a straightforward interpretation of overbought or oversold conditions in the context of a uniform historical average.
Standard Deviation for Volatility: Standard deviation measures the variability of the data around the mean. By dividing price’s difference from the mean by this value, the Z-Score can highlight whether price is unusually stretched given typical volatility.
Exponential Moving Average for Trend: Unlike an SMA, an EMA places more emphasis on recent data, reacting quicker to new price developments. This quicker response helps the script promptly identify trend shifts, which can be crucial for filtering out signals that go against a strong directional move.
RSI for Momentum Confirmation: RSI is an oscillator that gauges price movement strength by comparing average gains to average losses over a set period. By further smoothing this RSI with another EMA, short-lived oscillations become less influential, making signals more robust.
SlopeIndex for Slope-Based Coloring: To clarify whether the market’s central tendency is rising or falling, the script compares the basis now to its level slopeIndex bars ago. A higher current reading indicates an upward slope; a lower reading, a downward slope; and similar readings, a flat slope. This is visually represented on the chart, providing an immediate sense of the directionality.
Inputs
zLen (Z-Score Period)
Specifies how many bars to include for computing the SMA and standard deviation that form the basis of the Z-Score calculation. Larger values produce smoother but slower signals; smaller values catch quick changes but may generate noise.
emaTrendLen (EMA Trend Filter)
Sets the length of the EMA used to detect the market’s primary direction. This is pivotal for distinguishing whether signals should be considered (price aligning with an uptrend or downtrend) or filtered out.
rsiLen (RSI Length)
Defines the window for the initial RSI calculation. This RSI, when combined with the subsequent smoothing EMA, forms the foundation for momentum-based signal confirmations.
rsiEmaLen (EMA of RSI Period)
Applies an exponential moving average over the RSI readings for additional smoothing. This step helps mitigate rapid RSI fluctuations that might otherwise produce whipsaw signals.
zBuyLevel (Z-Score Buy Threshold)
Determines how negative the Z-Score must be for the script to consider a potential oversold signal. If the Z-Score dives below this threshold (and other criteria are met), a buy signal is generated.
zSellLevel (Z-Score Sell Threshold)
Determines how positive the Z-Score must be for a potential overbought signal. If the Z-Score surpasses this threshold (and other checks are satisfied), a sell signal is generated.
cooldownBars (Cooldown (Bars))
Enforces a bar-based delay between opposite signals. Once a buy signal has fired, the script must wait the specified number of bars before registering a new sell signal, and vice versa.
slopeIndex (Slope Sensitivity (Bars))
Specifies how many bars back the script compares the current basis for slope coloration. A bigger slopeIndex highlights larger directional trends, while a smaller number emphasizes shorter-term shifts.
showMeanLine (Show Z-Score Mean Line)
Enables or disables the plotting of the Z-Mean and its slope-based coloring. Traders who prefer minimal chart clutter may turn this off while still retaining signals.
Features
Statistical Core (Z-Score Detection):
This feature computes the Z-Score by taking the difference between the current price and the basis (SMA) and dividing by the standard deviation. In effect, it translates price fluctuations into a standardized measure that reveals how significant a move is relative to the typical variation seen over the lookback. When the Z-Score crosses predefined thresholds (zBuyLevel for oversold and zSellLevel for overbought), it signals that price could be at an extreme.
How It Works: On each bar, the script updates the SMA and standard deviation. The Z-Score is then refreshed accordingly. Traders can interpret particularly large negative or positive Z-Score values as scenarios where price is abnormally low or high.
EMA Trend Filter:
An EMA over emaTrendLen bars is used to classify the market as bullish if the price is above it and bearish if the price is below it. This classification is applied to the Z-Score signals, accepting them only when they align with the broader price direction.
How It Works: If the script detects a Z-Score below zBuyLevel, it further checks if price is actually in a downtrend (below EMA) before issuing a buy signal. This might seem counterintuitive, but a “downtrend” environment plus an oversold reading often signals a potential bounce or a mean-reversion play. Conversely, for sell signals, the script checks if the market is in an uptrend first. If it is, an overbought reading aligns with potential profit-taking.
RSI Momentum Confirmation with Oversold/Overbought Lockout:
RSI is calculated over rsiLen, then smoothed by an EMA over rsiEmaLen. If this smoothed RSI dips below a certain threshold (for example, 30) and then begins to slope upward, the indicator treats it as a potential sign of recovering momentum. Similarly, if RSI climbs above a certain threshold (for instance, 70) and starts to slope downward, that suggests dwindling momentum. Additionally, once RSI is in these zones, the indicator locks out repetitive signals until RSI fully exits and re-enters those extreme territories.
How It Works: Each bar, the script measures whether RSI has dropped below the oversold threshold (like 30) and has a positive slope. If it does, the buy side is considered “unlocked.” For sell signals, RSI must exceed an overbought threshold (70) and slope downward. The combination of threshold and slope helps confirm that a reversal is genuinely in progress instead of issuing signals while momentum remains weak or stuck in extremes.
Cooldown Mechanism:
The script features a custom bar-based cooldown that prevents issuing new signals in the opposite direction immediately after one is triggered. This helps avoid whipsaw situations where the market quickly flips from oversold to overbought or vice versa.
How It Works: When a buy signal fires, the indicator notes the bar index. If the Z-Score and RSI conditions later suggest a sell, the script compares the current bar index to the last buy signal’s bar index. If the difference is within cooldownBars, the signal is disallowed. This ensures a predefined “quiet period” before switching signals.
Slope-Based Coloring (Z-Mean Line and Shadow):
The script compares the current basis value to its value slopeIndex bars ago. A higher reading now indicates a generally upward slope, while a lower reading indicates a downward slope. The script then shades the Z-Mean line in a corresponding bullish or bearish color, or remains neutral if little change is detected.
How It Works: This slope calculation is refreshingly straightforward: basis – basis . If the result is positive, the line is colored bullish; if negative, it is colored bearish; if approximately zero, it remains neutral. This provides a quick visual cue of the medium-term directional bias.
Gradient Overlays:
With gradient fills, the script highlights where price stands in relation to the Z-Mean. When price is above the basis, a purple-shaded region is painted, visually indicating a “bearish zone” for potential overbought conditions. When price is below, a teal-like overlay is used, suggesting a “bullish zone” for potential oversold conditions.
How It Works: Each bar, the script checks if price is above or below the basis. It then applies a fill between close and basis, using distinct colors to show whether the market is trading above or below its mean. This creates an immediate sense of how extended the market might be.
Buy and Sell Labels (with Alerts):
When a legitimate buy or sell condition passes every check (Z-Score threshold, EMA trend alignment, RSI gating, and cooldown clearance), the script plots a corresponding label directly on the chart. It also fires an alert (if alerts are set up), making it convenient for traders who want timely notifications.
How It Works: If rawBuy or rawSell conditions are met (refined by RSI, EMA trend, and cooldown constraints), the script calls the respective plot function to paint an arrow label on the chart. Alerts are triggered simultaneously, carrying easily recognizable messages.
Metrics Table:
The optional on-chart table (activated by showMetrics) presents real-time Z-Score data, including the current Z-Score, its rolling mean, the maximum and minimum Z-Score values observed over the last zLen bars, a percentile position, and a short-term directional note (rising, falling, or flat).
Current – The present Z-Score reading
Mean – Average Z-Score over the zLen period
Min/Max – Lowest and highest Z-Score values within zLen
Position – Where the current Z-Score sits between the min and max (as a percentile)
Trend – Whether the Z-Score is increasing, decreasing, or flat
Conclusion
Uptrick: Z-Score Flow offers a versatile solution for traders who need a statistically informed perspective on price extremes combined with practical checks for overall trend and momentum. By leveraging a well-defined combination of Z-Score, EMA trend classification, RSI-based momentum gating, slope-based visualization, and a cooldown mechanic, the script reduces the occurrence of false or premature signals. Its gradient fills and optional metrics table contribute further clarity, ensuring that users can quickly assess market posture and make more confident trading decisions in real time.
Disclaimer
This script is intended solely for informational and educational purposes. Trading in any financial market comes with substantial risk, and there is no guarantee of success or the avoidance of loss. Historical performance does not ensure future results. Always conduct thorough research and consider professional guidance prior to making any investment or trading decisions.
SCE GANN PredictionsThis is a script designed to give an insight on price direction from being above or below a GANN Value.
What Are GANN Waves?
The SCE GANN Predictions indicator is inspired by the work of W.D. Gann, a renowned trader who believed that price movements follow geometric and mathematical patterns. GANN waves use past price behavior—specifically momentum or "velocity"—to forecast where prices might head next.
How Does the Indicator Work?
Calculating Velocity
The script starts by measuring the "velocity" of price movement over a user-defined lookback period (denoted as n). This velocity is the average difference between the close and open prices over n bars. Think of it as the market’s speed in a given direction.
Predicting the Future Price
Using this velocity, the indicator estimates a future price after a specific time horizon—calculated as n + n*2 bars into the future (e.g., if n = 15, it predicts 45 bars ahead). It scales the velocity by a ratio (Gr) to determine the "end price." This is the raw GANN prediction.
Optimizing the Ratio (Gr)
The key to a good prediction is finding the right Gr. The script tests a range of Gr values (from Gr_min to Gr_max, stepping by Gr_step) and evaluates each one by calculating the sum of squared errors (SSE) between the predicted prices and the actual historical close prices. The Gr with the lowest SSE is deemed "optimal" and used for the final prediction.
Smoothing with an SMA
The raw GANN prediction is then smoothed using a simple moving average (SMA) over the lookback period (n). This SMA is plotted on your chart, serving as a dynamic trend line. The plot’s color changes based on the current price: teal if the close is above the SMA (bullish), and red if below (bearish).
Visuals
This example shows how the value explains price strength and changes color. When the price is above the line, and it’s green, we’re showing an up trend. The opposite is when the price is below the line, and it’s red, showing a down trend.
We can see that there may be moments where price drops under the value for just that one bar.
In scenarios with sideways price action, even though the price crosses, there is no follow through. This is a shortcoming of the overall concept.
Customizable Inputs
Timeframe: Choose the timeframe for analysis (default is 2 minutes).
Show GANN Wave: Toggle the GANN SMA plot on or off (default is true).
Lookback Period (Gn): Set the number of bars for velocity and SMA calculations (default is 15).
Min Ratio (Gr_min): The lower bound for the Gr optimization (default is 0.05).
Max Ratio (Gr_max): The upper bound for Gr (default is 0.2).
Step for Gr (Gr_step): The increment for testing Gr values (default is 0.01).
How to Use SCE GANN Predictions
Trend Direction
The colored SMA provides a quick visual cue. Teal suggests an uptrend, while red hints at a downtrend. Use this to align your trades with the broader momentum.
Crossover Signals
Watch for the close price crossing the GANN SMA. A move above could signal a buy opportunity, while a drop below might indicate a sell. Combine this with other indicators for confirmation.
Fine-Tuning
Experiment with the lookback period (Gn) and Gr range to optimize for your market. Shorter lookbacks might suit fast-moving assets, while longer ones could work for slower trends.
Like any technical tool, SCE GANN Predictions isn’t a crystal ball. It’s based on historical data and mathematical assumptions, so it won’t always be spot-on.
External Signals Strategy TesterExternal Signals Strategy Tester
This strategy is designed to help you backtest external buy/sell signals coming from another indicator on your chart. It is a flexible and powerful tool that allows you to simulate real trading based on signals generated by any indicator, using input.source connections.
🔧 How It Works
Instead of generating signals internally, this strategy listens to two external input sources:
One for buy signals
One for sell signals
These sources can be connected to the plots from another indicator (for example, custom indicators, signal lines, or logic-based plots).
To use this:
Add your indicator to the chart (it must be visible on the same pane as this strategy).
Open the settings of the strategy.
In the fields Buy Signal and Sell Signal, select the appropriate plot (line, value, etc.) from the indicator that represents the buy/sell logic.
The strategy will open positions when the selected buy signal crosses above 0, and sell signal crosses above 0.
This logic can be easily adapted by modifying the crossover rule inside the script if your signal style is different.
⚙️ Features Included
✅ Configurable trade direction:
You can choose whether to allow long trades, short trades, or both.
✅ Optional close on opposite signal:
When enabled, the strategy will exit the current position if an opposite signal appears.
✅ Optional full position reversal:
When enabled, the strategy will close the current position and immediately open an opposite one on the reverse signal.
✅ Risk Management Tools:
You can define:
Take Profit (TP): Position will be closed once the specified profit (in %) is reached.
Stop Loss (SL): Position will be closed if the price drops to the specified loss level (in %).
BreakEven (BE): Once the specified profit threshold is reached, the strategy will move the stop-loss to the entry price.
📌 If any of these values (TP, SL, BE) are set to 0, the feature is disabled and will not be applied.
🧪 Best Use Cases
Backtesting signals from custom indicators, without rewriting the logic into a strategy.
Comparing the performance of different signal sources.
Testing external indicators with optional position management logic.
Validating strategies using external filters, oscillators, or trend signals.
📌 Final Notes
You can visualize where the strategy detected buy/sell signals using green/red markers on the chart.
All parameters are customizable through the strategy settings panel.
This strategy does not repaint, and it processes signals in real-time only (no lookahead bias).
Chop ZonesThis indicator plots two "zones" in the form of shaded boxes, one between PMH and PML and one between PDH and PDL, the area that is shaded more has the highest probability of price action to be "choppy", the lesser shaded area has less probability for "choppy" action whilst outside the shaded areas there is high probability of a trend.
This indicator can be used to determine one of the three types of day:
Chop day
Bullish trend day
Bearish trend day
Chop day example today on AMEX:SPY
Bullish trend day example on NASDAQ:DLTR
Bearish trend day example on NASDAQ:UAL
Bitcoin Polynomial Regression ModelThis is the main version of the script. Click here for the Oscillator part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines. The Oscillator version can be found here.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Bitcoin Polynomial Regression OscillatorThis is the oscillator version of the script. Click here for the other part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
TimeMapTimeMap is a visual price-reference indicator designed to help traders rapidly visualize how current price levels relate to significant historical closing prices. It overlays your chart with reference lines representing past weekly, monthly, quarterly (3-month), semi-annual (6-month), and annual closing prices. By clearly plotting these historical price references, TimeMap helps traders quickly gauge price position relative to historical market structure, aiding in the identification of trends, support/resistance levels, and potential reversals.
How it Works:
The indicator calculates the precise number of historical bars corresponding to weekly, monthly, quarterly, semi-annual, and annual intervals, dynamically adjusting according to your chart’s timeframe (intraday, daily, weekly, monthly) and chosen market type (Stocks US, Crypto, Forex, or Futures). Historical closing prices from these periods are plotted directly on your chart as horizontal reference lines.
For intraday traders, the script accurately calculates historical offsets considering regular and extended trading sessions (e.g., pre-market and after-hours sessions for US stocks), ensuring correct positioning of historical lines.
User-Configurable Inputs Explained in Detail:
Market Type:
Allows you to specify your trading instrument type, automatically adjusting calculations for:
- Stocks US (default): 390 minutes per regular session (780 minutes if extended hours enabled), 5 trading days/week.
- Crypto: 1440 minutes/day, 7 trading days/week.
- Forex: 1440 minutes/day, 5 trading days/week.
- Futures: 1320 minutes/day, 5 trading days/week.
Show Weekly Close:
When enabled, plots a line at the exact closing price from one week ago. Provides short-term context and helps identify recent price momentum.
Show Monthly Close:
When enabled, plots a line at the exact closing price from one month ago. Helpful for evaluating medium-term price positioning and monthly trend strength.
Show 3-Month Close:
When enabled, plots a line at the exact closing price from three months ago. Useful for assessing quarterly market shifts, intermediate trend changes, and broader market sentiment.
Show 6-Month Close:
When enabled, plots a line at the exact closing price from six months ago. Useful for identifying semi-annual trends, significant price pivots, and longer-term support/resistance levels.
Show 1-Year Close:
When enabled, plots a line at the exact closing price from one year ago. Excellent for assessing long-term market direction and key annual price levels.
Enable Smoothing:
Activates a Simple Moving Average (SMA) smoothing of historical reference lines, reducing volatility and providing clearer visual references. Recommended for traders preferring less volatile reference levels.
Smoothing Length:
Determines the number of bars used in calculating the SMA smoothing of historical lines. Higher values result in smoother but slightly delayed reference lines; lower values offer more immediate yet more volatile levels.
Use Extended Hours (Intraday Only):
When enabled (only applicable for Stocks US), it accounts for pre-market and after-hours trading sessions, providing accurate intraday historical line calculations based on extended sessions (typically 780 minutes/day total).
Important Notes and Compliance:
- This indicator does not provide trading signals, recommendations, or predictions. It serves purely as a visual analytical tool to supplement traders’ existing methods.
- Historical lines plotted are strictly based on past available price data; the indicator never accesses future data or data outside the scope of Pine Script’s standard capabilities.
- The script incorporates built-in logic to avoid runtime errors if insufficient historical data exists for a selected timeframe, ensuring robustness even with limited historical bars.
- TimeMap is original work developed exclusively by Julien Eche (@Julien_Eche). It does not reuse or replicate third-party or existing open-source scripts.
Recommended Best Practices:
- Use TimeMap as a complementary analytical reference, not as a standalone strategy or trade decision-making tool.
- Adapt displayed historical periods and smoothing settings based on your trading style and market approach.
- Default plot colors are optimized for readability on dark-background charts; adjust as necessary according to your preference and chart color scheme.
This script is published open-source to benefit the entire TradingView community and fully complies with all TradingView script publishing rules and guidelines.
Trend Catcher SwiftEdgeTrend Catcher SwiftEdge
Overview
The Trend Catcher SwiftEdge is a simple yet effective tool designed to help traders identify potential trend directions using two Simple Moving Averages (SMAs). It plots two SMAs based on the high and low prices of the chart, visually highlights trend conditions, and provides buy/sell labels to assist with trade entries. This indicator is best used as part of a broader trading strategy and should not be relied upon as a standalone signal generator.
How It Works
Two SMAs: The indicator calculates two SMAs: one based on the lowest price (Low) and one based on the highest price (High) over a user-defined period (default: 20).
Dynamic Colors:
Green: When the price is above both SMAs (indicating a potential uptrend).
Red: When the price is below both SMAs (indicating a potential downtrend).
Purple: When the price is between the SMAs (indicating consolidation).
The SMAs and the background between them change color dynamically to reflect the current trend condition.
Buy/Sell Labels:
A "Buy" label appears when an entire candlestick (including its low) crosses above both SMAs, marking the start of a potential uptrend.
A "Sell" label appears when an entire candlestick (including its high) crosses below both SMAs, marking the start of a potential downtrend.
To reduce noise, only one label is shown per trend direction. The indicator resets when the price enters the consolidation zone (purple), allowing for a new signal when the next trend begins.
Settings
SMA Length: Adjust the period of the SMAs (default: 20). A longer period smooths the SMAs and focuses on larger trends, while a shorter period makes the indicator more sensitive to price changes.
How to Use
Add the indicator to your chart.
Look for "Buy" labels to consider potential long entries during uptrends (green zone).
Look for "Sell" labels to consider potential short entries during downtrends (red zone).
Use the purple consolidation zone to prepare for potential breakouts.
Always combine this indicator with other forms of analysis (e.g., support/resistance, volume, or other indicators) to confirm signals.
Important Notes
This indicator is a tool to assist with identifying trend directions and potential entry points. It does not guarantee profits and should be used as part of a comprehensive trading strategy.
False signals can occur, especially in choppy or ranging markets. Consider using additional filters or confirmations to improve reliability.
Backtest the indicator on your chosen market and timeframe to understand its behavior before using it in live trading.
Feedback
If you have suggestions or feedback, feel free to leave a comment. Happy trading!
Quarterly Theory ICT 03 [TradingFinder] Precision Swing Points🔵 Introduction
Precision Swing Point (PSP) is a divergence pattern in the closing of candles between two correlated assets, which can indicate a potential trend reversal. This structure appears at market turning points and highlights discrepancies between the price behavior of two related assets.
PSP typically forms in key timeframes such as 5-minute, 15-minute, and 90-minute charts, and is often used in combination with Smart Money Concepts (SMT) to confirm trade entries.
PSP is categorized into Bearish PSP and Bullish PSP :
Bearish PSP : Occurs when an asset breaks its previous high, and its middle candle closes bullish, while the correlated asset closes bearish at the same level. This divergence signals weakness in the uptrend and a potential price reversal downward.
Bullish PSP : Occurs when an asset breaks its previous low, and its middle candle closes bearish, while the correlated asset closes bullish at the same level. This suggests weakness in the downtrend and a potential price increase.
🟣 Trading Strategies Using Precision Swing Point (PSP)
PSP can be integrated into various trading strategies to improve entry accuracy and filter out false signals. One common method is combining PSP with SMT (divergence between correlated assets), where traders identify divergence and enter a trade only after PSP confirms the move.
Additionally, PSP can act as a liquidity gap, meaning that price tends to react to the wick of the PSP candle, making it a favorable entry point with a tight stop-loss and high risk-to-reward ratio. Furthermore, PSP combined with Order Blocks and Fair Value Gaps in higher timeframes allows traders to identify stronger reversal zones.
In lower timeframes, such as 5-minute or 15-minute charts, PSP can serve as a confirmation for more precise entries in the direction of the higher timeframe trend. This is particularly useful in scalping and intraday trading, helping traders execute smarter entries while minimizing unnecessary stop-outs.
🔵 How to Use
PSP is a trading pattern based on divergence in candle closures between two correlated assets. This divergence signals a difference in trend strength and can be used to identify precise market turning points. PSP is divided into Bullish PSP and Bearish PSP, each applicable for long and short trades.
🟣 Bullish PSP
A Bullish PSP forms when, at a market turning point, the middle candle of one asset closes bearish while the correlated asset closes bullish. This discrepancy indicates weakness in the downtrend and a potential price reversal upward.
Traders can use this as a signal for long (buy) trades. The best approach is to wait for price to return to the wick of the PSP candle, as this area typically acts as a liquidity level.
f PSP forms within an Order Block or Fair Value Gap in a higher timeframe, its reliability increases, allowing for entries with tight stop-loss and optimal risk-to-reward ratios.
🟣 Bearish PSP
A Bearish PSP forms when, at a market turning point, the middle candle of one asset closes bullish while the correlated asset closes bearish. This indicates weakness in the uptrend and a potential price decline.
Traders use this pattern to enter short (sell) trades. The best entry occurs when price retests the wick of the PSP candle, as this level often acts as a resistance zone, pushing price lower.
If PSP aligns with a significant liquidity area or Order Block in a higher timeframe, traders can enter with greater confidence and place their stop-loss just above the PSP wick.
Overall, PSP is a highly effective tool for filtering false signals and improving trade entry precision. Combining PSP with SMT, Order Blocks, and Fair Value Gaps across multiple timeframes allows traders to execute higher-accuracy trades with lower risk.
🔵 Settings
Mode :
2 Symbol : Identifies PSP and PCP between two correlated assets.
3 Symbol : Compares three assets to detect more complex divergences and stronger confirmation signals.
Second Symbol : The second asset used in PSP and correlation calculations.
Third Symbol : Used in three-symbol mode for deeper PSP and PCP analysis.
Filter Precision X Point : Enables or disables filtering for more precise PSP and PCP detection. This filter only identifies PSP and PCP when the base asset's candle qualifies as a Pin Bar.
Trend Effect : By changing the Trend Effect status to "Off," all Pin bars, whether bullish or bearish, are displayed regardless of the current market trend. If the status remains "On," only Pin bars in the direction of the main market trend are shown.
Bullish Pin Bar Setting : Using the "Ratio Lower Shadow to Body" and "Ratio Lower Shadow to Higher Shadow" settings, you can customize your bullish Pin bar candles. Larger numbers impose stricter conditions for identifying bullish Pin bars.
Bearish Pin Bar Setting : Using the "Ratio Higher Shadow to Body" and "Ratio Higher Shadow to Lower Shadow" settings, you can customize your bearish Pin bar candles. Larger numbers impose stricter conditions for identifying bearish Pin bars.
🔵 Conclusion
Precision Swing Point (PSP) is a powerful analytical tool in Smart Money trading strategies, helping traders identify precise market turning points by detecting divergences in candle closures between correlated assets. PSP is classified into Bullish PSP and Bearish PSP, each playing a crucial role in detecting trend weaknesses and determining optimal entry points for long and short trades.
Using the PSP wick as a key liquidity level, integrating it with SMT, Order Blocks, and Fair Value Gaps, and analyzing higher timeframes are effective techniques to enhance trade entries. Ultimately, PSP serves as a complementary tool for improving entry accuracy and reducing unnecessary stop-outs, making it a valuable addition to Smart Money trading methodologies.
Premarket Gap MomoTrader(SC)🚀 Pre-Market Momentum Trader | Dynamic Position Sizing 🔥
📈 Trade explosive pre-market breakouts with confidence! This algorithmic strategy automatically detects high-momentum setups, dynamically adjusts position size, and ensures risk control with a one-trade-per-day rule.
⸻
🎯 Key Features
✅ Pre-Market Trading (4:00 - 9:30 AM EST) – Only trades during the most volatile session for early breakouts.
✅ Dynamic Position Sizing – Adapts trade size based on candle strength:
• ≥90% body → 100% position
• ≥85% body → 50% position
• ≥75% body → 25% position
✅ 1 Trade Per Day – Avoids overtrading by allowing only one high-quality trade daily.
✅ Momentum Protection – Stays in the trade as long as:
• Every candle remains green (no red candles).
• Each new candle has increasing volume (confirming strong buying).
✅ Automated Exit – Closes position if:
• A red candle appears.
• Volume fails to increase on a green candle.
⸻
🔍 How It Works
📌 Entry Conditions:
✔️ Candle gains ≥5% from previous close.
✔️ Candle is green & body size ≥75% of total range.
✔️ Volume >15K (confirming liquidity).
✔️ Occurs within pre-market session (4:00 - 9:30 AM EST).
✔️ Only the first valid trade of the day is taken.
📌 Exit Conditions:
❌ First red candle after entry → Exit trade.
❌ First green candle with lower volume → Exit trade.
⸻
🏆 Why Use This?
🔹 Eliminates Fake Breakouts – No trade unless volume & momentum confirm.
🔹 Prevents Overtrading – Restricts to one quality trade per day.
🔹 Adaptable to Any Market – Works on stocks, crypto, or forex.
🔹 Hands-Free Execution – No manual chart watching required!
⸻
🚨 Important Notes
📢 Not financial advice. Trading involves risk—always backtest & practice on paper trading before using real money.
📢 Enable pre-market data in your TradingView settings for accurate results.
📢 Optimized for 1-minute & 5-minute timeframes.
🔔 Like this strategy? Leave a comment, share your results, and don’t forget to hit Follow for more strategies! 🚀🔥
DTFX Algo Zones [SamuraiJack Mod]CME_MINI:NQ1!
Credits
This indicator is a modified version of an open-source tool originally developed by Lux Algo. I literally modded their indicator to create the DTFX Algo Zones version, incorporating additional features and refinements. Special thanks to Lux Algo for their original work and for providing the open-source code that made this development possible.
Introduction
DTFX Algo Zones is a technical analysis indicator designed to automatically identify key supply and demand zones on your chart using market structure and Fibonacci retracements. It helps traders spot high-probability reversal areas and important support/resistance levels at a glance. By detecting shifts in market structure (such as Break of Structure and Change of Character) and highlighting bullish or bearish zones dynamically, this tool provides an intuitive framework for planning trades. The goal is to save traders time and improve decision-making by focusing attention on the most critical price zones where market bias may confirm or reverse.
Logic & Features
• Market Structure Shift Detection (BOS & CHoCH): The indicator continuously monitors price swings and marks significant structure shifts. A Break of Structure (BOS) occurs when price breaks above a previous swing high or below a swing low, indicating a continuation of the current trend. A Change of Character (ChoCH) is detected when price breaks in the opposite direction of the prior trend, often signaling an early trend reversal. These moments are visually marked on the chart, serving as anchor points for new zones. By identifying BOS and ChoCH in real-time, the DTFX Algo Zones indicator ensures you’re aware of key trend changes as they happen.
• Auto-Drawn Fibonacci Supply/Demand Zones: Upon a valid structure shift, the indicator plots a Fibonacci-based zone between the breakout point and the preceding swing high/low (the source of the move). This creates a shaded area or band of Fibonacci retracement levels (for example 38.2%, 50%, 61.8%, etc.) representing a potential support zone in an uptrend or resistance zone in a downtrend. These supply/demand zones are derived from the natural retracement of the breakout move, highlighting where price is likely to pull back. Each zone is essentially an auto-generated Fibonacci retracement region tied to a market structure event, which traders can use to anticipate where the next pullback or bounce might occur.
• Dynamic Bullish and Bearish Zones: The DTFX Algo Zones indicator distinguishes bullish vs. bearish zones and updates them dynamically as new price action unfolds. Bullish zones (formed after bullish BOS/ChoCH) are typically highlighted in one color (e.g. green or blue) to indicate areas of demand/support where price may bounce upward. Bearish zones (formed after bearish BOS/ChoCH) are shown in another color (e.g. red/orange) to mark supply/resistance where price may stall or reverse downward. This color-coding and real-time updating allow traders to instantly recognize the market bias: for instance, a series of bullish zones implies an uptrend with multiple support levels on pullbacks, while consecutive bearish zones indicate a downtrend with resistance overhead. As old zones get invalidated or new ones appear, the chart remains current with the latest key levels, eliminating clutter from outdated levels.
• Flexible Customization: The indicator comes with several options to tailor the zones to your trading style. You can filter which zones to display – for example, show only the most recent N zones or limit to only bullish or only bearish zones – helping declutter the chart and focus on recent, relevant levels. There are settings to control zone extension (how far into the future the zones are drawn) and to automatically invalidate zones once they’re no longer relevant (for instance, if price fully breaks through a zone or a new structure shift occurs that supersedes it). Additionally, the Fibonacci retracement levels within each zone are customizable: you can choose which retracement percentages to plot, adjust their colors or line styles, and decide whether to fill the zone area for visibility. This flexibility ensures the DTFX Algo Zones can be tuned for different markets and strategies, whether you want a clean minimalist look or detailed zones with multiple internal levels.
Best Use Cases
DTFX Algo Zones is a versatile indicator that can enhance various trading strategies. Some of its best use cases include:
• Identifying High-Probability Reversal Zones: Each zone marks an area where price has a higher likelihood of stalling or reversing because it reflects a significant prior swing and Fibonacci retracement. Traders can watch these zones for entry opportunities when the market approaches them, as they often coincide with order block or strong supply/demand areas. This is especially useful for catching trend reversals or pullbacks at points where risk is lower and potential reward is higher.
• Spotting Key Support and Resistance: The automatically drawn zones act as dynamic support (below price) and resistance (above price) levels. Instead of manually drawing Fibonacci retracements or support/resistance lines, you get an instant map of the key levels derived from recent price action. This helps in quickly identifying where the next bounce (support) or rejection (resistance) might occur. Swing traders and intraday traders alike can use these zones to set alerts or anticipate reaction areas as the market moves.
• Trend-Following Entries: In a trending market, the indicator’s zones provide ideal areas to join the trend on pullbacks. For example, in an uptrend, when a new bullish zone is drawn after a BOS, it indicates a fresh demand zone – buying near the lower end of that zone on a pullback can offer a low-risk entry to ride the next leg up. Similarly, in a downtrend, selling rallies into the highlighted supply zones can position you in the direction of the prevailing trend. The zones effectively serve as a roadmap of the trend’s structure, allowing trend traders to buy dips and sell rallies with greater confidence.
• Mean-Reversion and Range Trading: Even in choppy or range-bound markets, DTFX Algo Zones can help find mean-reversion trades. If price is oscillating sideways, the zones at extremes of the range might mark where momentum is shifting (ChoCH) and price could swing back toward the mean. A trader might fade an extended move when it reaches a strong zone, anticipating a reversion. Additionally, if multiple zones cluster in an area across time (creating a zone overlap), it often signifies a particularly robust support/resistance level ideal for range trading strategies.
In all these use cases, the indicator’s ability to filter out noise and highlight structurally important levels means traders can focus on higher-probability setups and make more informed trading decisions.
Strategy – Pullback Trading with DTFX Algo Zones
One of the most effective ways to use the DTFX Algo Zones indicator is trading pullbacks in the direction of the trend. Below is a step-by-step strategy to capitalize on pullbacks using the zones, combining the indicator’s signals with sound price action analysis and risk management:
1. Identify a Market Structure Shift and Trend Bias: First, observe the chart for a recent BOS or ChoCH signal from the indicator. This will tell you the current trend bias. For instance, a bullish BOS/ChoCH means the market momentum has shifted upward (bullish bias), and a new demand zone will be drawn. A bearish structure break indicates downward momentum and creates a supply zone. Make sure the broader context supports the bias (e.g., if multiple higher timeframe zones are bullish, focus on long trades).
2. Wait for the Pullback into the Zone: Once a new zone appears, don’t chase the price immediately. Instead, wait for price to retrace back into that highlighted zone. Patience is key – let the market come to you. For a bullish setup, allow price to dip into the Fibonacci retracement zone (demand area); for a bearish setup, watch for a rally into the supply zone. Often, the middle of the zone (around the 50% retracement level) can be an optimal area where price might slow down and pivot, but it’s wise to observe price behavior across the entire zone.
3. Confirm the Entry with Price Action & Confluence: As price tests the zone, look for confirmation signals before entering the trade. This can include bullish reversal candlestick patterns (for longs) or bearish patterns (for shorts) such as engulfing candles, hammers/shooting stars, or doji indicating indecision turning to reversal. Additionally, incorporate confluence factors to strengthen the setup: for example, check if the zone overlaps with a key moving average, a round number price level, or an old support/resistance line from a higher timeframe. You might also use an oscillator (like RSI or Stochastic) to see if the pullback has reached oversold conditions in a bullish zone (or overbought in a bearish zone), suggesting a bounce is likely. The more factors aligning at the zone, the more confidence you can have in the trade. Only proceed with an entry once you see clear evidence of buyers defending a demand zone or sellers defending a supply zone.
4. Enter the Trade and Manage Risk: When you’re satisfied with the confirmation (e.g., price starts to react positively off a demand zone or shows rejection wicks in a supply zone), execute your entry in the direction of the original trend. Immediately set a stop-loss order to control risk: for a long trade, a common placement is just below the demand zone (a few ticks/pips under the swing low that formed the zone); for a short trade, place the stop just above the supply zone’s high. This way, if the zone fails and price continues beyond it, your loss is limited. Position size the trade so that this stop-loss distance corresponds to a risk you are comfortable with (for example, 1-2% of your trading capital).
5. Take Profit Strategically: Plan your take-profit targets in advance. A conservative approach is to target the origin of the move – for instance, in a long trade, you might take profit as price moves back up to the swing high (the 0% Fibonacci level of the zone) or the next significant zone or resistance level above. This often yields at least a 1:1 reward-to-risk ratio if you entered around mid-zone. More aggressive trend-following traders may leave a portion of the position running beyond the initial target, aiming for a larger move in line with the trend (for example, new higher highs in an uptrend). You can also trail your stop-loss upward behind new higher lows (for longs) or lower highs (for shorts) as the trend progresses, locking in profit while allowing for further gains.
6. Monitor Zone Invalidation: Even after entering, keep an eye on the behavior around the zone and any new zones that may form. If price fails to bounce and instead breaks decisively through the entire zone, respect that as an invalidation – the market may be signaling a deeper reversal or that the signal was false. In such a case, it’s better to exit early or stick to your stop-loss than to hold onto a losing position. The indicator will often mark or no longer highlight zones that have been invalidated by price, guiding you to shift focus to the next opportunity.
Risk Management Tips:
• Always use a stop-loss and don’t move it farther out in hope. Placing the stop just beyond the zone’s far end (the swing point) helps protect you if the pullback turns into a larger reversal.
• Aim for a favorable risk-to-reward ratio. With pullback entries near the middle or far end of a zone, you can often achieve a reward that equals or exceeds your risk. For example, risking 20 pips to make 20+ pips (1:1 or better) is a prudent starting point. Adjust targets based on market structure – if the next resistance is 50 pips away, consider that upside against your risk.
• Use confluence and context: Don’t take every zone signal in isolation. The highest probability trades come when the DTFX Algo Zone aligns with other analysis (trend direction, chart patterns, higher timeframe support/resistance, etc.). This filtered approach will reduce trades taken in weak zones or counter-trend traps.
• Embrace patience and selectivity: Not all zones are equal. It can be wise to skip very narrow or insignificant zones and wait for those that form after a strong BOS/ChoCH (indicating a powerful move). Larger zones or zones formed during high-volume times tend to produce more reliable pullback opportunities.
• Review and adapt: After each trade, note how price behaved around the zone. If you notice certain Fib levels (like 50% or 61.8%) within the zone consistently provide the best entries, you can refine your approach to focus on those. Similarly, adjust the indicator’s settings if needed – for example, if too many minor zones are cluttering your screen, limit to the last few or increase the structure length parameter to capture only more significant swings.
⸻
By combining the DTFX Algo Zones indicator with disciplined confirmation and risk management, traders can improve their timing on pullback entries and avoid chasing moves. This indicator shines in helping you trade what you see, not what you feel – the clearly marked zones and structure shifts keep you grounded in price action reality. Whether you’re a trend trader looking to buy the dip/sell the rally, or a reversal trader hunting for exhaustion points, DTFX Algo Zones provides a robust visual aid to elevate your trading decisions. Use it as a complementary tool in your analysis to stay on the right side of the market’s structure and enhance your trading performance.
PSP - NQ ES YMThe PSP - NQ ES YM indicator tracks the price movements of the NQ, ES, and YM futures to identify correlation and divergence between them.
🔸 Orange dot (above candle) → When NQ and ES have opposite trends (one up, one down).
🔹 Blue dot (below candle) → When YM differs from either NQ or ES, but NQ and ES are aligned.
🟠🔹 Both dots on the same candle → When NQ and ES differ, and one of them also differs from YM.
🟢 Green dot (above candle at 12 AM NY time) → Marks the daily open at 12 AM New York time.
This helps traders spot market divergence patterns between major indices and potential trading opportunities. 🚀
Clustering & Divergences (RSI-Stoch-CCI) [Sam SDF-Solutions]The Clustering & Divergences (RSI-Stoch-CCI) indicator is a comprehensive technical analysis tool that consolidates three popular oscillators—Relative Strength Index (RSI), Stochastic, and Commodity Channel Index (CCI)—into one unified metric called the Score. This Score offers traders an aggregated view of market conditions, allowing them to quickly identify whether the market is oversold, balanced, or overbought.
Functionality:
Oscillator Clustering: The indicator calculates the values of RSI, Stochastic, and CCI using user-defined periods. These oscillator values are then normalized using one of three available methods: MinMax, Z-Score, or Z-Bins.
Score Calculation: Each normalized oscillator value is multiplied by its respective weight (which the user can adjust), and the weighted values are summed to generate an overall Score. This Score serves as a single, interpretable metric representing the combined oscillator behavior.
Market Clustering: The indicator performs clustering on the Score over a configurable window. By dividing the Score range into a set number of clusters (also configurable), the tool visually represents the market’s state. Each cluster is assigned a unique color so that traders can quickly see if the market is trending toward oversold, balanced, or overbought conditions.
Divergence Detection: The script automatically identifies both Regular and Hidden divergences between the price action and the Score. By using pivot detection on both price and Score data, the indicator marks potential reversal signals on the chart with labels and connecting lines. This helps in pinpointing moments when the price and the underlying oscillator dynamics diverge.
Customization Options: Users have full control over the indicator’s behavior. They can adjust:
The periods for each oscillator (RSI, Stochastic, CCI).
The weights applied to each oscillator in the Score calculation.
The normalization method and its manual boundaries.
The number of clusters and whether to invert the cluster order.
Parameters for divergence detection (such as pivot sensitivity and the minimum/maximum bar distance between pivots).
Visual Enhancements:
Depending on the user’s preference, either the Score or the Cluster Index (derived from the clustering process) is plotted on the chart. Additionally, the script changes the color of the price bars based on the identified cluster, providing an at-a-glance visual cue of the current market regime.
Logic & Methodology:
Input Parameters: The script starts by accepting user inputs for clustering settings, oscillator periods, weights, divergence detection, and manual boundary definitions for normalization.
Oscillator Calculation & Normalization: It computes RSI, Stochastic, and CCI values from the price data. These values are then normalized using either the MinMax method (scaling between a lower and upper band) or the Z-Score method (standardizing based on mean and standard deviation), or using Z-Bins for an alternative scaling approach.
Score Computation: Each normalized oscillator is multiplied by its corresponding weight. The sum of these products results in the overall Score that represents the combined oscillator behavior.
Clustering Algorithm: The Score is evaluated over a moving window to determine its minimum and maximum values. Using these values, the script calculates a cluster index that divides the Score into a predefined number of clusters. An option to invert the cluster calculation is provided to adjust the interpretation of the clustering.
Divergence Analysis: The indicator employs pivot detection (using left and right bar parameters) on both the price and the Score. It then compares recent pivot values to detect regular and hidden divergences. When a divergence is found, the script plots labels and optional connecting lines to highlight these key moments on the chart.
Plotting: Finally, based on the user’s selection, the indicator plots either the Score or the Cluster Index. It also overlays manual boundary lines (for the chosen normalization method) and adjusts the bar colors according to the cluster to provide clear visual feedback on market conditions.
_________
By integrating multiple oscillator signals into one cohesive tool, the Clustering & Divergences (RSI-Stoch-CCI) indicator helps traders minimize subjective analysis. Its dynamic clustering and automated divergence detection provide a streamlined method for assessing market conditions and potentially enhancing the accuracy of trading decisions.
For further details on using this indicator, please refer to the guide available at:
Liquidations Levels [RunRox]📈 Liquidation Levels is an indicator designed to visualize key price levels on the chart, highlighting potential reversal points where liquidity may trigger significant price movements.
Liquidity is essential in trading - price action consistently moves from one liquidity area to another. We’ve created this free indicator to help traders easily identify and visualize these liquidity zones on their charts.
📌 HOW IT WORKS
The indicator works by marking visible highs and lows, points widely recognized by traders. Because many traders commonly place their stop-loss orders beyond these visible extremes, significant liquidity accumulates behind these points. By analyzing trading volume and visible extremes, the indicator estimates areas where clusters of stop-loss orders (liquidity pools) are likely positioned, giving traders valuable insights into potential market moves.
As shown in the screenshot above, the price aggressively moved toward Sell-Side liquidity. After sweeping this liquidity level for the second time, it reversed and began targeting Buy-Side liquidity. This clearly demonstrates how price moves from one liquidity pool to another, continually seeking out liquidity to fuel its next directional move.
As shown in the screenshot, price levels with fewer anticipated trader stop-losses are indicated by less vibrant, faded colors. When the lines become more saturated and vivid, it signals that sufficient liquidity - in the form of clustered stop-losses has accumulated, potentially attracting price movement toward these areas.
⚙️ SETTINGS
🔹 Period – Increasing this setting makes the marked highs and lows more significant, filtering out minor price swings.
🔹 Low Volume – Select the color displayed for low-liquidity levels.
🔹 High Volume – Select the color displayed for high-liquidity levels.
🔹 Levels to Display – Choose between 1 and 15 nearest liquidity levels to be shown on the chart.
🔹 Volume Sensitivity – Adjust the sensitivity of the indicator to volume data on the chart.
🔹 Show Volume – Enable or disable the display of volume values next to each liquidity level.
🔹 Max Age – Limits displayed liquidity levels to those not older than the specified number of bars.
✅ HOW TO USE
One method of using this indicator is demonstrated in the screenshot above.
Price reached a high-liquidity level and showed an initial reaction. We then waited for a second confirmation - a liquidity sweep followed by a clear market structure break - to enter the trade.
Our target is set at the liquidity accumulated below, with the stop-loss placed behind the manipulation high responsible for the liquidity sweep.
By following this approach, you can effectively identify trading opportunities using this indicator.
🔶 We’ve made every effort to create an indicator that’s as simple and user-friendly as possible. We’ll continue to improve and enhance it based on your feedback and suggestions in the future.
Tri-Fold BB(Trend-Strength)*indicator isn't preset to look as displayed, do so accordingly*
"Tri-Fold BB" is an indicator that utilizes three Bollinger Bands, each of different length as a way to represent trend strength. This allows one to see the trend strength relative to multiple timeframes: short, mid, and long term trend strength. This is helpful because it provides the user with a holistic view of the asset.
How it Works
The indicator is preset to utilizing three different Bollinger Bands with length: 20, 50, and 100. This indicator simply plots the price of an asset relative to its specified Bollinger Band. For an example, if the price of the asset were to surpass its 20BB standard deviations, it would display so accordingly, though from the perspective of lets say... the 100, it may have looked like it barely moved up a standard deviation relative to 100BB because the standard deviations of a 100BB are more spread out.
Its important to view the trend strength from multiple lengths because it allows one to gauge whether the short term trend strength is likely to hold or not. A better way to speculate on asset behavior.
Another way to view this indicator is similar to that of the BB% indicator, except this indicator allows us to view price relative to standard deviations, across multiple timeframes. More holistic, more utility provided.
Basic Understanding:
Each line = Standard Deviation (3 upper, 3 lower)
Mid-Line = Basis relative to BB(20sma, 50sma, 100sma)
If price goes under Basis, that means it crossed below their specified sma(significant bull or bear signal)
I've also added HMA's relative to each BB incase one were to decide in creating some sort of trading strategy with it. I personally don't use them but I understand that it could be helpful to some so I left it in there. If you don't like them then simply deselect them and then save your desired setup as default.
In regard to regular indications of bullish or bearishness, i'd like to add that I use this indicator for the sole purpose of providing an idea of trend strength. I personally am unsure to state that cross overs directly indicate that there is a bull or bear move because I've seen instances where the price of an asset went in a direction contrary to what it 'should' have if we were to use that cross over strategy. Though of course, feel free to use this indicator as desired.
Highs&Lows by HourHighs & Lows by Hour
Description:
Highs & Lows by Hour is a TradingView indicator that helps traders identify the most frequent hours at which daily high and low price points occur. By analyzing historical price data directly from the TradingView chart, this tool provides valuable insights into market timing, allowing traders to optimize their strategies around key price movements.
This indicator is specifically designed for the one-hour (H1) timeframe . It does not display any data on other timeframes , as it relies on analyzing daily highs and lows within hourly periods.
This indicator processes the available data based on the number of historical bars loaded in the TradingView chart. The number of analyzed bars depends on the TradingView subscription plan , which determines how much historical data is accessible.
Key Features:
Works exclusively on the H1 timeframe , ensuring accurate analysis of daily highs and lows
Hourly highs and lows analysis to identify the most frequent hours when the market reaches its daily high and low
Sorted by frequency, displaying the most significant trading hours in descending order based on their recurrence
Customizable table and colors to fit the chart theme and trading style
Useful for scalpers, day traders, and swing traders to anticipate potential price reversals and breakouts
How It Works:
The indicator scans historical price data directly from the TradingView chart to detect the hour at which daily highs and daily lows occur.
It counts the frequency of highs and lows for each hour of the trading day based on the number of available bars in the TradingView chart.
The recorded data is displayed in a structured table, sorted by frequency from highest to lowest.
Users can customize colors to enhance readability and seamlessly integrate the indicator into their analysis.
Why Use This Indicator?
Identify key market patterns by recognizing the most critical hours when price extremes tend to form
Improve timing for trades by aligning entries and exits with high-probability time windows
Enhance market awareness by understanding when market volatility is likely to peak based on historical trends
Important Notes:
This indicator works only on the one-hour (H1) timeframe . It will not display any data on other timeframes
Works well on Forex, stocks, crypto, and futures , especially for intraday traders
The indicator analyzes only the historical bars available on the TradingView chart, which varies depending on the TradingView subscription plan (Free, Pro, Pro+, Premium)
This indicator does not generate buy or sell signals but serves as a data-driven tool for market analysis
How to Use:
Apply the Highs & Lows by Hour indicator to a one-hour (H1) chart on TradingView
Review the table displaying the most frequent hours for daily highs and lows
Adjust colors and settings for better visualization
Use the data to refine trading decisions and align strategy with historical price behavior
HTF Candle Range Box (Fixed to HTF Bars)### **Higher Timeframe Candle Range Box (HTF Box Indicator)**
This indicator visually highlights the price range of the most recently closed higher-timeframe (HTF) candle, directly on a lower-timeframe chart. It dynamically adjusts based on the user-selected HTF setting (e.g., 15-minute, 1-hour) and ensures that the box is displayed only on the bars that correspond to that specific HTF candle’s duration.
For instance, if a trader is on a **1-minute chart** with the **HTF set to 15 minutes**, the indicator will draw a box spanning exactly 15 one-minute candles, corresponding to the previous 15-minute HTF candle. The box updates only when a new HTF candle completes, ensuring that it does not change mid-formation.
---
### **How It Works:**
1. **Retrieves Higher Timeframe Data**
The script uses TradingView’s `request.security` function to pull **high, low, open, and close** values from the **previously completed HTF candle** (using ` ` to avoid repainting). It also fetches the **high and low of the candle before that** (using ` `) for comparison.
2. **Determines Breakout Behavior**
It compares the **last closed HTF candle** to the **one before it** to determine whether:
- It **broke above** the previous high.
- It **broke below** the previous low.
- It **broke both** the high and low.
- It **stayed within the previous candle’s range** (no breakout).
3. **Classifies the Candle & Assigns Color**
- **Green (Bullish)**
- Closes above the previous candle’s high.
- Breaks below the previous candle’s low but closes back inside the previous range **if it opened above** the previous high.
- **Red (Bearish)**
- Closes below the previous candle’s low.
- Breaks above the previous candle’s high but closes back inside the previous range **if it opened below** the previous low.
- **Orange (Neutral/Indecisive)**
- Stays within the previous candle’s range.
- Breaks both the high and low but closes inside the previous range without a clear bias.
4. **Box Placement on the Lower Timeframe**
- The script tracks the **bar index** where each HTF candle starts on the lower timeframe (e.g., every 15 bars on a 1-minute chart if HTF = 15 minutes).
- It **only displays the box on those bars**, ensuring that the range is accurately reflected for that time period.
- The box **resets and updates** only when a new HTF candle completes.
---
### **Key Features & Advantages:**
✅ **Clear Higher Timeframe Context:**
- The indicator provides a structured way to analyze HTF price action while trading in a lower timeframe.
- It helps traders identify **HTF support and resistance zones**, potential **breakouts**, and **failed breakouts**.
✅ **Fixed Box Display (No Mid-Candle Repainting):**
- The box is drawn **only after the HTF candle closes**, avoiding misleading fluctuations.
- Unlike other indicators that update live, this one ensures the trader is looking at **confirmed data** only.
✅ **Flexible Timeframe Selection:**
- The user can set **any HTF resolution** (e.g., 5min, 15min, 1hr, 4hr), making it adaptable for different strategies.
✅ **Dynamic Color Coding for Quick Analysis:**
- The **color of the box reflects the market sentiment**, making it easier to spot trends, reversals, and fake-outs.
✅ **No Clutter – Only Applies to the Relevant Bars:**
- Instead of spanning across the whole chart, the range box is **only visible on the bars belonging to the last HTF period**, keeping the chart clean and focused.
---
### **Example Use Case:**
💡 Imagine a trader is scalping on the **1-minute chart** but wants to factor in **HTF 15-minute structure** to avoid getting caught in bad trades. With this indicator:
- They can see whether the last **15-minute candle** was bullish, bearish, or indecisive.
- If it was **bullish (green)**, they may look for **buying opportunities** at lower timeframes.
- If it was **bearish (red)**, they might anticipate **a potential pullback or continuation down**.
- If the **HTF candle failed to break out**, they know the market is **ranging**, avoiding unnecessary trades.
---
### **Final Thoughts:**
This indicator is a **powerful addition for traders who combine multiple timeframes** in their analysis. It provides a **clean and structured way to track HTF price movements** without cluttering the chart or requiring constant manual switching between timeframes. Whether used for **intraday trading, swing trading, or scalping**, it adds an extra layer of confirmation for trade entries and exits.
🔹 **Best for traders who:**
- Want **HTF structure awareness while trading lower timeframes**.
- Need **confirmation of breakouts, failed breakouts, or indecision zones**.
- Prefer a **non-repainting tool that only updates after confirmed HTF closes**.
Let me know if you want any adjustments or additional features! 🚀
Candle Range Theory StrategyCandle Range Theory StrategyCandle Range Theory Strategy delves into the intricacies of price action analysis, focusing on the behavior of candlestick patterns within specific ranges. Traders employing this strategy aim to identify key support and resistance levels by analyzing the high and low points of significant candlesticks. The core principle lies in understanding that the range of a candle—defined by its opening, closing, high, and low prices—provides valuable insight into market sentiment and potential future movements.
To implement the Candle Range Theory Strategy effectively, one must first recognize the importance of different candle sizes. A long-bodied candle suggests strong momentum, pointing to a bullish or bearish bias, while a small-bodied candle indicates indecision or consolidation, often signaling potential reversals or breakouts. By plotting these candlesticks over a defined time frame, traders can ascertain whether the market is trending or range-bound.
Additionally, traders should consider the context in which these candles form. Analysis of the preceding price action can reveal whether current ranges are extensions of existing trends or indications of market fatigue. In particular, look for patterns such as engulfing candles, pin bars, or inside bars, as they often foreshadow forthcoming price fluctuations.
Moreover, combining the Candle Range Theory with other technical indicators, like moving averages or Fibonacci retracements, can offer a more comprehensive view of potential entry and exit points. By aligning candle patterns with broader market dynamics, traders can optimize their strategies, enhancing their probability of success while minimizing risk.
Lastly, maintaining a disciplined approach is crucial. Setting precise stop-loss and take-profit levels grounded in candle ranges can safeguard one's capital. Adhering to this framework allows traders to navigate the complexities of the market with greater confidence, ultimately leading to more informed and successful trading decisions. Embracing the nuances of Candle Range Theory not only sharpens analytical skills but also enriches one’s trading repertoire, paving the way for sustained profitability in the dynamic world of forex and equities.
Reversal rehersal v1This indicator was designed to identify potential market reversal zones using a combination of RSI thresholds (shooting range/falling range), candlestick patterns, and Fair Value Gaps (FVGs). By combining all these elements into one indicator, it allow for outputting high probability buy/sell signals for use by scalpers on low timeframes like 1-15 mins, for quick but small profits.
Note: that this has been mainly tested on DE40 index on the 1 min timeframe, and need to be adjusted to whichever timeframe and symbol you intend to use. Refer to the backtester feature for checking if this indicator may work for you.
The indicator use RSI ranges from two timeframes to highlight where momentum is building up. During these areas, it will look for certain candlestick patterns (Sweeps as the primary one) and check for existance of fair value gaps to further enhance the hitrate of the signal.
The logic for FVG detection was based on ©pmk07's work with MTF FVG tiny indicator. Several major changes was implemented though and incorporated into this indicator. Among these are:
Automatically adjustments of FVG boxes when mitigated partially and options to extend/cull boxes for performance and clarity.
Backtesting Table (Experimental):
This indicator also features an optional simplified table to review historical theoretical performance of signals, including win rate, profit/loss, and trade statistics. This does not take commision or slippage into consideration.
Usage Notes:
Setup:
1. Add the indicator to your chart.
2. Decide if you want to use Long or Short (or both).
3. If you're scalping on ie. 1 min time frame, make sure to set FVG's to higher timeframes (ie. 5, 15, 60).
4. Enable the 'Show backtest results' and adjust the 'Signals' og 'Take profit' and 'Stop loss' values until you are satisfied with the results.
Use:
1. Setup an alert based on either of the 'BullishShooting range' or 'BearishFalling range' alerts. This will draw your attention to watch for the possible setups.
2. Verify if there's a significant imbalance prior to the signal before taking the trade. Otherwise this may invalidate the setup.
3. Once a signal is shown on the graph (either Green arrow up for buys/Red arrow down for sells) - you should enter a trade with the given 'Take profit' and 'Stop loss' values.
4. (optional) Setup an alert for either the Strong/Weak signals. Which corresponds to when one of the arrows are printed.
Important: This is the way I use it myself, but use at own risk and remember to combine with other indicators for further confluence. Remember this is no crystal ball and I do not guarantee profitable results. The indicator merely show signals with high probability setups for scalping.
Next level scolilay swing timerThe "Next Level Scolilay Swing Timer" is an advanced TradingView indicator designed to help traders navigate trends, reversals, and swing opportunities with ease. It's built around several key concepts like ATR filtering, ZigZag analysis, and momentum-based trend detection, making it a powerful tool for identifying market direction and key trading opportunities.
One of the standout features is its ability to filter candles using the Average True Range (ATR). This ensures that the indicator focuses on meaningful price movements rather than noise. You can tweak the ATR settings to suit your trading style, deciding how much historical data to consider or even turning the filter off completely if you prefer.
The script also integrates a ZigZag algorithm to detect pivot points, which it uses to evaluate swings in price action. This feature comes with customizable settings for depth and sensitivity, allowing you to adjust how the script reacts to price fluctuations. By analyzing these swings, the indicator identifies key highs and lows, which play a big role in determining whether the market is trending up or down.
When it comes to trends, the script is smart and flexible. It doesn't just look for higher highs or lower lows; it also considers momentum and retracement levels to decide if a trend is gaining strength or reversing. For example, it uses one-third retracement logic to spot sudden shifts in market direction, which can be critical for catching reversals early. You can also enable features like fast trend switching, which reacts to single-candle events that might signal a trend break.
Visualization is another area where this script shines. It marks uptrends and downtrends directly on the chart with clear labels, so you can instantly see when a new trend starts. Pink arrows appear above candles to signal potential downtrends, while yellow arrows below candles indicate possible uptrends. These signals combine multiple layers of analysis, like swing validation, ATR filtering, and trend confirmation, to give you reliable insights.
What makes the Swing Timer especially useful is its flexibility. Whether you’re a trend trader looking to ride major market moves, a swing trader focused on pivot points, or someone hunting for reversals, you can customize the settings to fit your needs. You can adjust everything from ZigZag and ATR parameters to how trends are labeled and filtered. The result is a tool that adapts to your trading style while still providing clear and actionable signals.
In short, this script brings together a range of advanced trading concepts into one user-friendly package. It’s perfect for traders who want to see market trends clearly, identify opportunities with confidence, and stay ahead of sudden reversals—all without getting bogged down in unnecessary complexity.
