PG Mean revision price to vwma and MAsHere's a concise breakdown for your users:
- Selection of Moving Average Type:- Choose VWMA, EMA, or SMA, along with the source (e.g., closing price) and length for the calculation.
- Price-MA Difference Calculation:- Calculates the difference between the closing price and the selected moving average.
- Additional Moving Averages:- Applies three customizable moving averages (MA1, MA2, MA3) to the price-MA difference.
- Dynamic Plotting:- Plots the price-MA difference in red, and overlays the moving averages (blue, orange, purple). MA1 can be dynamically colored red/green based on its trend.
- Zero Reference Line:- Includes a horizontal line at zero for easy visual reference.
This tool helps analyze price trends and deviations for better trading decisions!
Indicators and strategies
Vietnamese Stocks: Multi-Ticker Fibonacci AlertThis Pine Script™ indicator is designed specifically for traders monitoring the Vietnamese stock market (HOSE, HNX). Its primary goal is to automate the tracking of Fibonacci retracement levels across a large list of stocks, alerting you when prices breach key support zones.
Core Functionality:
The script calculates Fibonacci retracement levels (23.6%, 38.2%, 50%, 61.8%, 78.6%) for up to 40 tickers simultaneously. The calculation is based on the highest high and lowest low identified since a user-defined Start Time. This allows you to anchor the Fibonacci analysis to a specific market event, trend start, or time period relevant to your strategy.
What it Does For You:
Automated Watchlist Scanning: Instead of drawing Fib levels on dozens of charts, select one of the two pre-configured watchlists (up to 40 symbols each, customizable in settings) populated with popular Vietnamese stocks.
Time-Based Fibonacci: Define a Start Time in the settings. The script uses this date to find the subsequent highest high and lowest low for each symbol in your chosen watchlist, forming the basis for the Fib calculation.
Intelligent Alerts: Get notified via TradingView's alerts when the candle closing price of any stock in your active watchlist falls below the critical 38.2%, 50%, 61.8%, or 78.6% levels relative to its own high/low range since the start time. Alerts are consolidated for efficiency.
Visual Aids:
- Plots the same time-based Fibonacci levels directly on your current chart symbol for quick reference.
- Includes an optional on-chart table showing which monitored stocks are currently below key Fib levels (enable "Show Debug Info").
- Features experimental background coloring to highlight potential bullish signals on the current chart.
Configuration:
Start Time: Crucial input – sets the anchor point for Fib calculations.
WatchList Selection: Choose between WatchList #1 (Bluechip/Midcap focus) or WatchList #2 (Defensive/Other focus) using the boolean toggles.
Symbol Customization: Easily replace the default symbols with your preferred Vietnamese stocks directly in the indicator settings.
Notification Prefix: Add custom text to the beginning of your alert messages.
Alert Setup: Remember to create an alert in TradingView, selecting this indicator and the alert() condition, usually with "Once Per Bar Close" frequency.
This tool is open-source under the MPL 2.0 license. Feel free to use, modify, and learn from it.
tafirstlibGeneral Purpose: Starts by stating it's a collection of utility functions for technical analysis.
Core Functionality Areas: Mentions key categories like:
Extrema detection (isMin, isMax, etc.)
Condition checking over time (isMachedInRange, isContinuous, etc.)
Rate of change analysis (isSlowDown)
Moving average calculation (getMA)
Advanced Features: Highlights the more complex functions:
Visualization helpers (getColorNew)
Moving Regression (mr) for smoothing/trend
Cycle analysis (bpDom)
Overall Goal: Concludes by stating the library's aim – simplifying development and enabling complex analysis.
Library "tafirstlib"
TODO: add library description here
isSlowDown(data)
isSlowDown
Parameters:
data (float) : array of numbers
Returns: boolean
isMin(data, maeLength)
isMin
Parameters:
data (float) : array of numbers
maeLength (int) : number
Returns: boolean
isMax(data, maeLength)
isMax
Parameters:
data (float) : array of numbers
maeLength (int) : number
Returns: boolean
isMinStopped(data, maeLength)
isMinStopped
Parameters:
data (float) : array of numbers
maeLength (int) : number
Returns: boolean
isMaxStopped(data, maeLength)
isMaxStopped
Parameters:
data (float) : array of numbers
maeLength (int) : number
Returns: boolean
isLongMinStopped(data, maeLength, distance)
isLongMinStopped
Parameters:
data (float) : array of numbers
maeLength (int) : number
distance (int) : number
Returns: boolean
isLongMaxStopped(data, maeLength, distance)
isLongMaxStopped
Parameters:
data (float) : array of numbers
maeLength (int) : number
distance (int) : number
Returns: boolean
isMachedInRangeSkipCurrent(data, findRange, findValue)
isMachedInRangeSkipCurrent
Parameters:
data (bool) : array of numbers
findRange (int) : number
findValue (bool) : number
Returns: boolean
isMachedInRange(data, findRange, findValue)
isMachedInRange
Parameters:
data (bool) : array of numbers
findRange (int) : number
findValue (bool) : number
Returns: boolean
isMachedColorInRange(data, findRange, findValue)
isMachedColorInRange isMachedColorInRange(series color data, int findRange, color findValue)
Parameters:
data (color) : series of color
findRange (int) : int
findValue (color) : color
Returns: boolean
countMachedInRange(data, findRange, findValue)
countMachedInRange
Parameters:
data (bool) : array of numbers
findRange (int) : number
findValue (bool) : number
Returns: number
getColor(data)
getColor
Parameters:
data (float) : array of numbers
Returns: color
getColorNew(data)
getColorNew
Parameters:
data (float) : array of numbers
Returns: color
isColorBetter(color_data)
isColorBetter
Parameters:
color_data (color) : array of colors
Returns: boolean
isColorWorst(color_data)
isColorWorst
Parameters:
color_data (color) : array of colors
Returns: boolean
isColorBetter2(color_data)
isColorBetter2
Parameters:
color_data (color) : array of colors
Returns: boolean
isColorWorst2(color_data)
isColorWorst2
Parameters:
color_data (color) : array of colors
Returns: boolean
isDecreased2Bar(data)
isDecreased2Bar
Parameters:
data (float) : array of numbers
Returns: boolean
isContinuousAdvance(targetSeries, range2Find, howManyException)
isContinuousAdvance
Parameters:
targetSeries (bool) : array of booleans
range2Find (int) : number
howManyException (int) : number
Returns: boolean
isContinuous(targetSeries, range2Find, truefalse)
isContinuous
Parameters:
targetSeries (bool) : array of booleans
range2Find (int) : number
truefalse (bool) : boolean
Returns: boolean
isContinuousNotNow(targetSeries, range2Find, truefalse)
isContinuousNotNow
Parameters:
targetSeries (bool) : array of booleans
range2Find (int) : number
truefalse (bool) : boolean
Returns: boolean
isContinuousTwoFactors(targetSeries, range2Find, truefalse)
isContinuousTwoFactors
Parameters:
targetSeries (bool) : array of booleans
range2Find (int) : number
truefalse (bool) : boolean
Returns: boolean
findEventInRange(startDataBarIndex, neededDataBarIndex, currentBarIndex)
findEventInRange
Parameters:
startDataBarIndex (int) : number
neededDataBarIndex (int) : number
currentBarIndex (int) : number
Returns: boolean
findMin(firstdata, secondata, thirddata, forthdata)
findMin
Parameters:
firstdata (float) : number
secondata (float) : number
thirddata (float) : number
forthdata (float) : number
Returns: number
findMax(firstdata, secondata, thirddata, forthdata)
findMax
Parameters:
firstdata (float) : number
secondata (float) : number
thirddata (float) : number
forthdata (float) : number
Returns: number
getMA(src, length, mav)
getMA
Parameters:
src (float) : number
length (simple int) : number
mav (string) : string
Returns: number
mr(mrb_src, mrb_window, mrb_degree)
Parameters:
mrb_src (float)
mrb_window (int)
mrb_degree (int)
bpDom(maeLength, bpw, mult)
Parameters:
maeLength (int)
bpw (float)
mult (float)
Ultimate Moving Average Crossover Indicator by SAMQUANT📈 Ultimate Moving Average Crossover Indicator | All-in-One MA Strategy
Unlock the power of multiple moving averages in one versatile indicator designed to give you clear, actionable signals in any market condition.
📌 Key Features:
- Supports **all major moving averages**:
- **SMA, EMA, WMA, HMA, RMA, DEMA, TEMA**, and more.
- Each MA is **fully customizable** with different lengths and types for ultimate flexibility.
- **Binary Long/Short signals** based on crossover logic—perfect for alerts, strategies, or discretionary trading.
- **Dynamic background coloring**:
- **Green** for bullish trends
- **Red** for bearish trends
Quickly gauge market direction at a glance.
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🚀 Why Use This Indicator?
✅ Combines the strength of all major MA types
✅ Customizable to fit any trading style—scalping, swing, or trend following
✅ Built-in alerts ready for your next trade
✅ Visually intuitive with built-in signal clarity
✅ Excellent tool for **confluence-based** strategies
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Great trades start with great tools. Clarity, precision, and flexibility—this indicator brings it all to your charts. Trade smarter, not harder.
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> ⚠️ **Disclaimer:**
This script is intended for **educational and informational purposes only**. It does not constitute financial advice. Past performance is not indicative of future results. Always practice sound risk management and test strategies thoroughly before using real capital.
Best Fit Linear Regression with StdDev BandsBest Fit Linear Regression with Standard Deviation Bands
The Best Fit Linear Regression with StdDev Bands is a custom TradingView indicator designed to analyze price trends and volatility over a specified number of bars. It plots a linear regression line representing the best fit for the selected price data, accompanied by optional standard deviation bands to visualize price dispersion.
📈 Key Features
Linear Regression Line: Calculates the best-fit line over a user-defined number of bars, providing a clear visualization of the prevailing price trend.
TradingView
Standard Deviation Bands: Optional upper and lower bands set at a multiple of the standard deviation from the regression line, indicating potential support and resistance levels.
Price Source Selection: Choose between using the closing price or the midpoint (average of high and low) for calculations.
Weighting Options: Apply True Range weighting to emphasize periods of higher volatility in the regression calculation.
Trend Strength Indicator: Displays a normalized strength value between -1 and 1, indicating the direction and magnitude of the trend.
Customizable Appearance: Adjust line color, width, label position, and background color to suit your preferences.
Extendable Lines: Option to extend the regression and standard deviation lines beyond the visible bars for projection purposes.
⚙️ Input Parameters
Bars to Analyze: Number of bars to include in the regression calculation (default: 100).
Price Value: Select "Close" or "Midpoint" as the data source for calculations.
Weighting Method: Choose between "None" or "True Range" weighting.
Line Color & Width: Customize the color and thickness of the regression line.
Label Position: Place the informational label at the start, center, or end of the regression line.
Label Background Color: Set the background color for the informational label.
Extend Line Beyond Visible Bars: Option to project the regression line into future bars.
Show Standard Deviation Bands: Toggle the visibility of the standard deviation bands.
Standard Deviation Multiplier: Set the multiplier for the standard deviation bands (default: 1.0).
StdDev Bands Color: Customize the color and transparency of the standard deviation bands.
🧮 How It Works
Data Collection: Gathers price data based on the selected source (Close or Midpoint) over the specified number of bars.
Weighting (Optional): Applies True Range weighting if selected, giving more importance to bars with higher volatility.
Regression Calculation: Computes the slope and intercept of the best-fit line using the least squares method.
Standard Deviation: Calculates the standard deviation of the price data from the regression line to determine the dispersion.
Plotting: Draws the regression line and, if enabled, the upper and lower standard deviation bands.
Labeling: Displays a label indicating the trend direction (Bullish, Bearish, or Neutral), strength percentage, and standard deviation value.
📊 Interpretation
Trend Direction: The slope of the regression line indicates the trend direction.
Trend Strength: The normalized strength value provides insight into the magnitude of the trend.
Price Position: Prices near or beyond the standard deviation bands may indicate overbought or oversold conditions.
TradingView
🛠️ Use Cases
Trend Analysis: Identify and confirm the direction and strength of market trends.
Volatility Assessment: Gauge market volatility through the width of the standard deviation bands.
Support and Resistance: Use the standard deviation bands to identify potential support and resistance levels.
Trade Timing: Assist in determining optimal entry and exit points based on price interaction with the regression line and bands.
This indicator is particularly useful for traders seeking a statistical approach to trend analysis, offering customizable options to tailor the tool to various trading strategies and preferences.
MACD Liquidity Tracker SystemMACD Liquidity Tracker System
🔹 Enhanced MACD with candle coloring, entry markers, and customizable signal logic.
🧠 Features:
This tool combines a color-coded MACD histogram with signal-based candle colors and small shape markers (🔼🔽) for clear market momentum and entry visualization.
📊 Visuals:
MACD Histogram (Sub-panel):
4 dynamic colors to show momentum direction:
🔹 Bright Blue = MACD > 0 & rising (strong bullish)
🔹 Dark Blue = MACD > 0 & falling (weakening bullish)
🔹 Bright Magenta = MACD < 0 & falling (strong bearish)
🔹 Dark Magenta = MACD < 0 & rising (weakening bearish)
Price Candles (Main Chart):
🔹 Bright Blue = Active Long signal
🔹 Bright Magenta = Active Short signal
Entry Markers:
🔼 Blue triangle (below candle) = Start of Long
🔽 Magenta triangle (above candle) = Start of Short
⚙️ System Types (select in settings):
Normal:
🔹 Long = MACD > 0
🔹 Short = MACD < 0
Fast: (Based on histogram color)
🔹 Long = Bright Blue OR Dark Magenta
🔹 Short = Dark Blue OR Bright Magenta
Safe:
🔹 Long = Only Bright Blue
🔹 Short = All other colors
🔔 Alerts:
Alerts trigger only on the first bar of a new Long/Short signal.
Easy to set up using TradingView’s alert system.
📌 How to Use:
Add the indicator to your chart
Open settings and select a System Type
Adjust MACD parameters if needed
Use histogram color + candle color for momentum and signal confirmation
Set alerts for clean entries if desired
💡 Ideal for traders seeking visual clarity and flexible MACD-based strategies.
Aviad SMC Flow🔹 Aviad SMC Flow – Smart Structure & Zones Indicator
A professional SMC-based indicator for identifying:
✅ BoS – Break of Structure
✅ CHoCH – Change of Character
✅ MSS – Market Structure Shift
✅ Automated Support & Resistance Zones
✅ Liquidity Grab and Reversal Points
✅ Market Structure with historical display
Optimized for 1H and lower timeframes.
Designed for real Smart Money Concepts (SMC) trading.
Perfect for intraday traders, swing traders, and scalpers.
Wick Anomaly DetectorWick Anomaly Detector
This script helps identify candles with unusually large wicks compared to their body size — a common sign of price anomalies, false prints, or low-liquidity moves.
🔍 What it does:
Flags candles with upper or lower wicks that exceed a user-defined ratio (default: 3x the body size)
Helps traders spot suspicious spikes or “bad ticks,” especially in pre-market or illiquid stocks
📈 Use it to:
Avoid fake breakouts
Confirm real price action
Clean up your technical analysis
Customize the wick-to-body threshold as needed. Add volume filters or time filters for more precision.
Created for educational purposes — use with proper risk management!
Auto Support Resistance Channels [TradingFinder] Top/Down Signal🔵 Introduction
In technical analysis, a price channel is one of the most widely used tools for identifying and tracking price trends. A price channel consists of two parallel trendlines, typically drawn from swing highs (resistance) and swing lows (support). These lines define dynamic support and resistance zones and provide a clear framework for interpreting price fluctuations.
Drawing a channel on a price chart allows the analyst to more precisely identify entry points, exit levels, take-profit zones, and stop-loss areas based on how the price behaves within the boundaries of the channel.
Price channels in technical analysis are generally categorized into three types: upward channels with a positive slope, downward channels with a negative slope, and horizontal (range-bound) channels with near-zero slope. Each type offers unique insights into market behavior depending on the price structure and prevailing trend.
Structurally, channels can be formed using either minor or major pivot points. A major channel typically reflects a stronger, more reliable structure that appears on higher timeframes, whereas a minor channel often captures short-term fluctuations or corrective movements within a larger trend.
For instance, a major downward channel may indicate sustained selling pressure across the market, while a minor upward channel could represent a temporary pullback within a broader bearish trend.
The validity of a price channel depends on several factors, including the number of price touches on the channel lines, the symmetry and parallelism of the trendlines, the duration of price movement within the channel, and price behavior around the median line.
When a price channel is broken, it is generally expected that the price will move in the breakout direction by at least the width of the channel. This makes price channels especially useful in breakout analysis.
In the following sections, we will explore the different types of price channels, how to draw them accurately, the structural differences between minor and major channels, and key trade interpretations when price interacts with channel boundaries.
Up Channel :
Down Channel :
🔵 How to Use
A price channel is a practical tool in technical analysis for identifying areas of support, resistance, trend direction, and potential breakout zones. The structure consists of two parallel trendlines within which price fluctuates.
Traders use the relative position of price within the channel to make informed trading decisions. The two primary strategies include range-based trades (buying low, selling high) and breakout trades (entering when price exits the channel).
🟣 Up Channel
In an upward channel, price moves within a positively sloped range. The lower trendline acts as dynamic support, while the upper trendline serves as dynamic resistance. A common strategy involves buying near the lower support and taking profit or selling near the upper resistance.
If price breaks below the lower trendline with strong volume or a decisive candle, it can signal a potential trend reversal. Channels constructed from major pivots generally reflect dominant uptrends, while those based on minor pivots are often corrective structures within a broader bearish movement.
🟣 Down Channel
In a downward channel, price moves between two negatively sloped lines. The upper trendline functions as resistance, and the lower trendline as support. Ideal entry for short trades occurs near the upper boundary, especially when confirmed by bearish price action or a resistance level.
Exit targets are typically located near the lower support. If the upper boundary is broken to the upside, it may be an early sign of a bullish trend reversal. Like upward channels, a major down channel represents broader selling pressure, while a minor one may indicate a brief retracement in a bullish move.
🟣 Range Channel
A horizontal or range-bound channel is characterized by price oscillating between two nearly flat lines. This type of channel typically appears during sideways markets or periods of consolidation.
Traders often buy near the lower boundary and sell near the upper boundary to take advantage of contained volatility. However, fake breakouts are more frequent in range-bound structures, so it is important to wait for confirmation through candlestick signals and volume. A confirmed breakout beyond the channel boundaries can justify entering a trade in the direction of the breakout.
🔵 Settings
Pivot Period :This parameter defines how sensitive the channel detection is. A higher value causes the algorithm to identify major pivot points, resulting in broader and longer-term channels. Lower values focus on minor pivots and create tighter, short-term channels.
🔔 Alerts
Alert Configuration :
Enable or disable the full alert system
Set a custom alert name
Choose the alert frequency: every time, once per bar, or on bar close
Define the time zone for alert timestamps (e.g., UTC)
Channel Alert Types :
Each channel type (Major/Minor, Internal/External, Up/Down) supports two alert types :
Break Alert : Triggered when price breaks above or below the channel boundaries
React Alert : Triggered when price touches and reacts (bounces) off the channel boundary
🎨 Display Settings
For each of the eight channel types, you can customize:
Visibility : show or hide the channel
Auto-delete previous channels when new ones are drawn
Style : line color, thickness, type (solid, dashed, dotted), extension (right only, both sides)
🔵 Conclusion
The price channel is a foundational structure in technical analysis that enables traders to analyze price movement, identify dynamic support and resistance zones, and locate potential entry and exit points with greater precision.
When constructed properly using minor or major pivots, a price channel offers a consistent and intuitive framework for interpreting market behavior—often simpler and more visually clear than many other technical tools.
Understanding the differences between upward, downward, and range-bound channels—as well as recognizing the distinctions between minor and major structures—is critical for selecting the right trading strategy. Upward channels tend to generate buying opportunities, downward channels prioritize short setups, and horizontal channels provide setups for both mean-reversion and breakout trades.
Ultimately, the reliability of a price channel depends on various factors such as the number of touchpoints, the duration of the channel, the parallelism of the lines, and how the price reacts to the median line.
By taking these factors into account, an experienced analyst can effectively use price channels as a powerful tool for trend forecasting and precise trade execution. Although conceptually simple, successful application of price channels requires practice, pattern recognition, and the ability to filter out market noise.
Stock metrics and valueThis indicator shows:
- the valuation metrics for a stock on a table on top right: PE, EPS, dividend, ROIC, ROE, ROA, EPS growth, FCF growth, Equity growth, revenue Growth
- the fair value and the value with 50% margin of safety as chart lines
The lines will be red when they are above the current price and red when they are below the current price.
The colors on the table will be red when the values are below 10% and green when they are above, that means when everything is green the metrics for the stock are good.
Money Flow Pulse💸 In markets where volatility is cheap and structure is noisy, what matters most isn’t just the move — it’s the effort behind it. Money Flow Pulse (MFP) offers a compact, color-coded readout of real-time conviction by scoring volume-weighted price action on a five-tier scale. It doesn’t try to predict reversals or validate trends. Instead, it reveals the quality of the move in progress: is it fading , driving , exhausting , or hollow ?
🎨 MFP draws from the traditional Money Flow Index (MFI), a volume-enhanced momentum oscillator, but transforms it into a modular “pressure readout” that fits seamlessly into any structural overlay. Rather than oscillating between extremes with little interpretive guidance, MFP discretizes the flow into clean, color-coded regimes ranging from strong inflow (+2) to strong outflow (–2). The result is a responsive diagnostic layer that complements, rather than competes with, tools like ATR and/or On-Balance Volume.
5️⃣ MFP uses a normalized MFI value smoothed over 13 periods and classified into a 5-tier readout of Volume-Driven Conviction :
🍆 Exhaustion Inflow — usually a top or blowoff; not strength, but overdrive (+2)
🥝 Active Inflow — supportive of trend continuation (+1)
🍋 Neutral — chop, coil, or fakeouts (0)
🍑 Selling Intent — weakening structure, possible fade setups (-1)
🍆 Exhaustion Outflow — often signals forced selling or accumulation traps (-2)
🎭 These tiers are not arbitrary. Each one is tuned to reflect real capital behavior across timeframes. For instance, while +1 may support continuation, +2 often precedes exhaustion — especially on the lower timeframes. Similarly, a –1 reading during a pullback suggests sell-side pressure is building, but a shift to –2 may mean capitulation is already underway. The difference between the two can define whether a move is tradable continuation or strategic exhaustion .
🌊 The MFI ROC (Rate of Change) feature can be toggled to become a volatility-aware pulse monitor beneath the derived MFI tier. Instead of scoring direction or structure, ROC reveals how fast conviction is changing — not just where it’s headed, but how hard it's accelerating or decaying. It measures the raw Δ between the current and previous MFI values, exposing bursts of energy, fading pressure, or transitional churn .
🎢 Visually, ROC appears as a low-opacity area fill, anchored to a shared lemon-yellow zero line. When the green swell rises, buying pressure is accelerating; when the red drops, flow is actively deteriorating. A subtle bump may signal early interest — while a steep wave hints at an emotional overreaction. The ROC value itself provides numeric insight alongside the raw MFI score. A reading of +3.50 implies strong upside momentum in the flow — often supporting trend ignition. A score of –6.00 suggests rapid deceleration or full exhaustion — often preceding reversals or failed breakouts.
・ MFI shows you where the flow is
・ ROC tells you how it’s behaving
😎 This blend reveals not just structure or intent — but also urgency . And in flow-based trading, urgency often precedes outcome.
🧩 Divergence isn’t delay — it’s disagreement . One of the most revealing features of MFP is how it exposes momentum dissonance — situations where price and flow part ways. These divergences often front-run pivots , traps , or velocity stalls . Unlike RSI-style divergence, which whispers of exhaustion, MFI divergence signals a breakdown in conviction. The structure may extend — but the effort isn’t there.
・ Price ▲ MFI ▼ → Effortless Markup : Often signals distribution or a grind into liquidity. Without rising MFI, the rally lacks true flow participation — a warning of fragility.
・ Price ▼ MFI ▲ → Absorption or Early Accumulation : Price breaks down, but money keeps flowing in — a hidden bid. Watch for MFI tier shifts or ROC bursts to confirm a reversal.
🏄♂️ These moments don’t require signal overlays or setup hunting. MFP narrates the imbalance. When price breaks structure but flow does not — or vice versa — you’re not seeing trend, you’re seeing disagreement, and that's where edge begins.
💤 MFP is especially effective on intraday charts where volume dislocations matter most. On the 1H or 15m chart, it helps distinguish between breakouts with conviction versus those lacking flow. On higher timeframes, its resolution softens — it becomes more of a drift indicator than a trigger device. That’s by design: MFP prioritizes pulse, not position. It’s not the fire, it’s the heat.
📎 Use MFP in confluence with structural overlays to validate price behavior. A ribbon expansion with rising MFP is real. A compression breakout without +1 flow is "fishy". Watch how MFP behaves near key zones like anchored VWAP, MAs or accumulation pivots. When MFP rises into a +2 and fails to sustain, the reversal isn’t just technical — it’s flow-based.
🪟 MFP doesn’t speak loudly, but it never whispers without reason. It’s the pulse check before action — the breath of the move before the breakout. While it stays visually minimal on the chart, the true power is in the often overlooked Data Window, where traders can read and interpret the score in real time. Once internalized, these values give structure-aware traders a framework for conviction, continuation, or caution.
🛜 MFP doesn’t chase momentum — it confirms conviction. And in markets defined by noise, that signal isn’t just helpful — it’s foundational.
RSI+Stoch Band Oscillator📈 RSI + Stochastic Band Oscillator
Overview:
The RSI + Stochastic Band Oscillator is a technical indicator that combines the strengths of both the Relative Strength Index (RSI) and the Stochastic Oscillator. Instead of using static thresholds, this indicator dynamically constructs upper and lower bands based on the RSI and Stochastic overbought/oversold zones. It then measures the relative position of the current price within this adaptive range, effectively producing a normalized oscillator.
Key Components:
RSI-Based Dynamic Bands:
Using RSI values and exponential moving averages of price changes, upper and lower dynamic bands are constructed.
These bands adjust based on overbought and oversold levels, offering a more responsive framework than fixed RSI thresholds.
Stochastic-Based Dynamic Bands:
Similarly, Stochastic %K and %D values are used to construct dynamic bands.
These adapt to overbought and oversold levels by recalculating potential high/low values within the lookback window.
Oscillator Calculation:
The oscillator (osc) is computed as the relative position of the current close within the combined upper and lower bands of both RSI and Stochastic.
This value is normalized between 0 and 100, allowing clear identification of extreme conditions.
Visual Features:
The oscillator is plotted as a line between 0 and 100.
Color-filled areas highlight when the oscillator enters extreme zones:
Above 100 with falling momentum: Red zone (potential reversal).
Below 0 with rising momentum: Green zone (potential reversal).
Additional trend conditions (falling/rising RSI, %K, and %D) are used to strengthen reversal signals by confirming momentum shifts.
TASC 2025.05 Trading The Channel█ OVERVIEW
This script implements channel-based trading strategies based on the concepts explained by Perry J. Kaufman in the article "A Test Of Three Approaches: Trading The Channel" from the May 2025 edition of TASC's Traders' Tips . The script explores three distinct trading methods for equities and futures using information from a linear regression channel. Each rule set corresponds to different market behaviors, offering flexibility for trend-following, breakout, and mean-reversion trading styles.
█ CONCEPTS
Linear regression
Linear regression is a model that estimates the relationship between a dependent variable and one or more independent variables by fitting a straight line to the observed data. In the context of financial time series, traders often use linear regression to estimate trends in price movements over time.
The slope of the linear regression line indicates the strength and direction of the price trend. For example, a larger positive slope indicates a stronger upward trend, and a larger negative slope indicates the opposite. Traders can look for shifts in the direction of a linear regression slope to identify potential trend trading signals, and they can analyze the magnitude of the slope to support trading decisions.
One caveat to linear regression is that most financial time series data does not follow a straight line, meaning a regression line cannot perfectly describe the relationships between values. Prices typically fluctuate around a regression line to some degree. As such, analysts often project ranges above and below regression lines, creating channels to model the expected extent of the data's variability. This strategy constructs a channel based on the method used in Kaufman's article. It measures the maximum distances from points on the linear regression line to historical price values, then adds those distances and the current slope to the regression points.
Depending on the trading style, traders might look for prices to move outside an established channel for breakout signals, or they might look for price action to reach extremes within the channel for potential mean reversion opportunities.
█ STRATEGY CALCULATIONS
Primary trade rules
This strategy implements three distinct sets of rules for trend, breakout, and mean-reversion trades based on the methods Kaufman describes in his article:
Trade the trend (Rule 1) : Open new positions when the sign of the slope changes, indicating a potential trend reversal. Close short trades and enter a long trade when the slope changes from negative to positive, and do the opposite when the slope changes from positive to negative.
Trade channel breakouts (Rule 2) : Open new positions when prices cross outside the linear regression channel for the current sample. Close short trades and enter a long trade when the price moves above the channel, and do the opposite when the price moves below the channel.
Trade within the channel (Rule 3) : Open new positions based on price values within the channel's range. Close short trades and enter a long trade when the price is near the channel's low, within a specified percentage of the channel's range, and do the opposite when the price is near the channel's high. With this rule, users can also filter the trades based on the channel's slope. When the filter is active, long positions are allowed only when the slope is positive, and short positions are allowed only when it is negative.
Position sizing
Kaufman's strategy uses specific trade sizes for equities and futures markets:
For an equities symbol, the number of shares traded is $10,000 divided by the current price.
For a futures symbol, the number of contracts traded is based on a volatility-adjusted formula that divides $25,000 by the product of the 20-bar average true range and the instrument's point value.
By default, this script automatically uses these sizes for its trade simulation on equities and futures symbols and does not simulate trading on other symbols. However, users can control position sizes from the "Settings/Properties" tab and enable trade simulation on other symbol types by selecting the "Manual" option in the script's "Position sizing" input.
Stop-loss
This strategy includes the option to place an accompanying stop-loss order for each trade, which users can enable from the "SL %" input in the "Settings/Inputs" tab. When enabled, the strategy places a stop-loss order at a specified percentage distance from the closing price where the entry order occurs, allowing users to compare how the strategy performs with added loss protection.
█ USAGE
This strategy adapts its display logic for the three trading approaches based on the rule selected in the "Trade rule" input:
For all rules, the script plots the linear regression slope in a separate pane. The plot is color-coded to indicate whether the current slope is positive or negative.
When the selected rule is "Trade the trend", the script plots triangles in the separate pane to indicate when the slope's direction changes from positive to negative or vice versa. Additionally, it plots a color-coded SMA on the main chart pane, allowing visual comparison of the slope to directional changes in a moving average.
When the rule is "Trade channel breakouts" or "Trade within the channel", the script draws the current period's linear regression channel on the main chart pane, and it plots bands representing the history of the channel values from the specified start time onward.
When the rule is "Trade within the channel", the script plots overbought and oversold zones between the bands based on a user-specified percentage of the channel range to indicate the value ranges where new trades are allowed.
Users can customize the strategy's calculations with the following additional inputs in the "Settings/Inputs" tab:
Start date : Sets the date and time when the strategy begins simulating trades. The script marks the specified point on the chart with a gray vertical line. The plots for rules 2 and 3 display the bands and trading zones from this point onward.
Period : Specifies the number of bars in the linear regression channel calculation. The default is 40.
Linreg source : Specifies the source series from which to calculate the linear regression values. The default is "close".
Range source : Specifies whether the script uses the distances from the linear regression line to closing prices or high and low prices to determine the channel's upper and lower ranges for rules 2 and 3. The default is "close".
Zone % : The percentage of the channel's overall range to use for trading zones with rule 3. The default is 20, meaning the width of the upper and lower zones is 20% of the range.
SL% : If the checkbox is selected, the strategy adds a stop-loss to each trade at the specified percentage distance away from the closing price where the entry order occurs. The checkbox is deselected by default, and the default percentage value is 5.
Position sizing : Determines whether the strategy uses Kaufman's predefined trade sizes ("Auto") or allows user-defined sizes from the "Settings/Properties" tab ("Manual"). The default is "Auto".
Long trades only : If selected, the strategy does not allow short positions. It is deselected by default.
Trend filter : If selected, the strategy filters positions for rule 3 based on the linear regression slope, allowing long positions only when the slope is positive and short positions only when the slope is negative. It is deselected by default.
NOTE: Because of this strategy's trading rules, the simulated results for a specific symbol or channel configuration might have significantly fewer than 100 trades. For meaningful results, we recommend adjusting the start date and other parameters to achieve a reasonable number of closed trades for analysis.
Additionally, this strategy does not specify commission and slippage amounts by default, because these values can vary across market types. Therefore, we recommend setting realistic values for these properties in the "Cost simulation" section of the "Settings/Properties" tab.
FVG + Swings + ConfigurableOverview
This Pine Script v5 indicator highlights Fair Value Gaps (FVGs), plots swing‑high and swing‑low pivots, and marks single breakouts above the last swing‑high or below the last swing‑low by recoloring the breakout candle. Every aspect—gap size, count limits, colors, and feature toggles—is exposed as an input so you can tailor it to your own workflow.
Key Features
Fair Value Gaps
Detects bullish gaps when the high of bar i-2 is below the low of the current bar.
Detects bearish gaps when the low of bar i-2 is above the high of the current bar.
Draws a semi‑transparent rectangle spanning from bar i-2 to bar i + extension.
Automatically deletes oldest boxes when exceeding the user’s “Max FVG Boxes” limit.
Swing‑High / Swing‑Low Pivots
Identifies a swing‑high when the middle candle of a three‑bar sequence has the highest high.
Identifies a swing‑low when the middle candle has the lowest low.
Marks each pivot with a tiny dot above (high) or below (low) the bar.
Single Breakouts
Tracks the most recent swing‑high and swing‑low levels.
On the first close above the last swing‑high (or below the last swing‑low), recolors that single candle.
Prevents repeated coloring until a new swing pivot forms.
Full Customization
Show/Hide toggles for FVGs, swing pivots, breakouts.
Numeric inputs for FVG extension length and maximum retained boxes.
Color pickers for bullish/bearish gaps, swing pivots, and breakout candles.
Wavelet Smoothed Moving Average (TechnoBlooms)Wavelet Smoothed Moving Average (WSMA) is a part of the Quantum Price Theory (QPT) Series of indicators.
Overview:
The Wavelet Smoothed Moving Average (WSMA) is a trend-following indicator inspired by multi-level Haar Wavelet decomposition. Rather than using traditional wavelet basis functions, it emulates the core wavelet concept of multi-resolution analysis using nested simple moving averages (SMA).
How It Works:
WSMA applies three levels of smoothing:
• Level 1: SMA on price (base smoothing)
• Level 2: SMA on Level 1 output (further denoising)
• Level 3: SMA on Level 2 output (final approximation)
Why Use WSMA:
• Multi-Level Smoothing: Captures price structure across multiple time scales, unlike single-length MAs.
• Noise Reduction: Filters out short-term volatility and focuses on the underlying trend.
• Low Lag, High Clarity: Unlike traditional moving averages that react slowly or miss subtle shifts, WSMA’s layered smoothing delivers cleaner and more adaptive trend detection.
Unique Value:
• Wavelet-Inspired Design: Mimics core wavelet decomposition logic without the complexity of downsampling or basis functions.
• Perfect for Trend Confirmation: The final line (a3) can act as a trend filter, while the detail levels can help identify momentum shifts and volatility bursts.
• Fits Into Quantum Price Theory: As part of the QPT framework, WSMA bridges scientific theory with trading application, giving traders a deeper understanding of market structure and signal compression.
HTF FibonacciThis indicator displays Fibonacci lines for the selected previous HTF candle.
You can set its Fibs levels and colors.
HTF options: 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours and 1 day
Bijnor Pivot ExtendedOverview: The Bijnor Pivot Extended (BP+) indicator is a powerful visual tool designed to help traders identify key price levels using Fibonacci-based pivots. It dynamically plots Support and Resistance levels based on your chosen timeframe (Daily, Weekly, or Monthly) and displays them only for the current session, reducing chart clutter and improving focus.
🔧 Features:
📆 Pivot Timeframe Selection: Choose between Daily, Weekly, or Monthly pivots.
🎯 Fibonacci Pivot Levels:
Central Pivot (P)
Resistance: R1, R2, R3, R4 (Extended)
Support: S1, S2, S3, S4 (Extended)
🎨 Full Customization:
Toggle labels and prices on/off
Position labels to the left or right
Change line width and individual colors for pivot, support, and resistance lines
🧠 Smart Line Plotting:
Lines are drawn only during the selected session, keeping your chart clean
🕹️ Max Performance: Optimized to stay lightweight with max_lines_count and max_labels_count set to 500
🧭 How to Use It:
Use this indicator to:
Plan entries and exits around key Fibonacci pivot zones
Identify overbought/oversold zones at R3/R4 and S3/S4
Enhance your intraday, swing, or positional trading setups
Combine with price action, candlestick patterns, or volume for maximum edge.
✅ Bonus:
This script is ideal for traders looking for a minimalist yet powerful pivot framework, with extended levels for breakout or reversal scenarios.
DEMA Trend Oscillator Strategy📌 Overview
The DEMA Trend Oscillator Strategy is a dynamic trend-following approach based on the Normalized DEMA Oscillator SD.
It adapts in real-time to market volatility with the goal of improving entry accuracy and optimizing risk management.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main goal of this strategy is to respond quickly to sudden price movements and trend reversals,
by combining momentum-based signals with volatility filters.
It is designed to be user-friendly for traders of all experience levels.
✨ Key Features
Normalized DEMA Oscillator: A momentum indicator that normalizes DEMA values on a 0–100 scale, allowing intuitive identification of trend strength
Two-Bar Confirmation Filter: Requires two consecutive bullish or bearish candles to reduce noise and enhance entry reliability
ATR x2 Trailing Stop: In addition to fixed stop-loss levels, a trailing stop based on 2× ATR is used to maximize profits during strong trends
📊 Trading Rules
Long Entry:
Normalized DEMA > 55 (strong upward momentum)
Candle low is above the upper SD band
Two consecutive bullish candles appear
Short Entry:
Normalized DEMA < 45 (downward momentum)
Candle high is below the lower SD band
Two consecutive bearish candles appear
Exit Conditions:
Take-profit at a risk-reward ratio of 1.5
Stop-loss triggered if price breaks below (long) or above (short) the SD band
Trailing stop activated based on 2× ATR to secure and extend profits
💰 Risk Management Parameters
Symbol & Timeframe: Any (AUDUSD 5M example)
Account size (virtual): $3000
Commission: 0.4PIPS(0.0004)
Slippage: 2 pips
Risk per trade: 5%
Number of trades (backtest):534
All parameters can be adjusted based on broker specifications and individual trading profiles.
⚙️ Trading Parameters & Considerations
Indicator: Normalized DEMA Oscillator SD
Parameter settings:
DEMA Period (len_dema): 40
Base Length: 20
Long Threshold: 55
Short Threshold: 45
Risk-Reward Ratio: 1.5
ATR Multiplier for Trailing Stop: 2.0
🖼 Visual Support
The chart displays the following visual elements:
Upper and lower SD bands (±2 standard deviations)
Entry signals shown as directional arrows
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by “Normalized DEMA Oscillator SD” by QuantEdgeB,
but introduces enhancements such as a two-bar confirmation filter and an ATR-based trailing stop.
Compared to conventional trend-following strategies, it offers superior noise filtering and profit optimization.
✅ Summary
The DEMA Trend Oscillator Strategy is a responsive and practical trend-following method
that combines momentum detection with adaptive risk management.
Its visual clarity and logical structure make it a powerful and repeatable tool
for traders seeking consistent performance in trending markets.
⚠️ Always apply appropriate risk management. This strategy is based on historical data and does not guarantee future results.
Multi Timeframe Altered Money Flow Index by CoffeeShopCryptoMoney Flow Index is a long used tool in trading markets, understanding to where money is moving and most importantly when its going there.
One of the biggest challenges was the when part. Because seeing it on your current trading chart timeframe is easy but it gets difficult if youre attempting a top-down-analysis of market structure vs price performance.
The new formula presented by @CoffeeshopCrypto is a key solution to this timeframe analysis issue. Seems like I may have solved the "glitch-In-The-Matrix".
The issue was always setting a secondary MFI on your chart and telling the system you wanted to watch the 1 hour MFI from a 5 minute chart.
To do this you need to wait for 12 candles to close on your 5 minute chart before you can get a 1hour MFI value. The move may have already happend and you may be too late. If there was only a better faster way to see the changing values of the High Timeframe Money Flow Index in real time without changing chart times and losing place......oh wait.....there is one now!
This tool allows you to tell it what timeframe you are looking at,
and what you want to compare it to.
It runs the calculation in the background automatically to give you the real time values of your High Timeframe chart setting on the chart you are looking at.
How to trade Long
When both the LFT and HTF Money flow cross above ZERO, they are both in uptrend
How to trade Short
When both the LFT and HTF Money flow cross below ZERO, they are both in downtrend
What happens when Low timeframe is inside the high timeframe:
If High timeframe MFI is below zero but the LFT MFI is above it and still below zero, you have lost your short term downtrend. The opposite is true when the high timeframe MFI is above zero.
A strong constant comparative trend is when your low timeframe MFI is leading your High timeframe MFI.
Personal Settings:
In my usage, i find it best to multiply my trading chart timeframe by 3 and use that number as my high timeframe MFI setting
This works on ANY chart time you want. For example you are not locked to the standard built TradingView chart times.
If you trade on a 7 minute timeframe, you can set your HTF to 21.
7 * 3 = 21
CSCMultiTimeframeToolsLibrary "CSCMultiTimeframeTools"
Calculates instant higher timeframe values for higher timeframe analysis with zero lag.
getAdjustedLookback(current_tf_minutes, higher_tf_minutes, length)
Calculate adjusted lookback period for higher timeframe conversion.
Parameters:
current_tf_minutes (int) : Current chart timeframe in minutes (e.g., 5 for 5m).
higher_tf_minutes (int) : Target higher timeframe in minutes (e.g., 15 for 15m).
length (int) : Base length value (e.g., 14 for RSI/MFI).
Returns: Adjusted lookback period (length × multiplier).
Purpose and Benefits of the TimeframeTools Library
This library is designed to solve a critical pain point for traders who rely on higher timeframe (HTF) indicator values while analyzing lower timeframe (LTF) charts. Traditional methods require waiting for multiple candles to close—for example, to see a 1-hour RSI on a 5-minute chart, you’d need 12 closed candles (5m × 12 = 60m) before the value updates. This lag means missed opportunities, delayed signals, and inefficient decision-making.
Why Traders Need This
Whether you’re scalping (5M/15M) or swing trading (1H/4H), this library bridges the gap between timeframes, giving you HTF context in real time—so you can act faster, with confidence.
How This Library Eliminates the Waiting Game
By dynamically calculating the adjusted lookback period, the library allows:
Real-time HTF values on LTF charts – No waiting for candle closes.
Accurate conversions – A 14-period RSI on a 1-hour chart translates to 168 periods (14 × 12) on a 5-minute chart, ensuring mathematical precision.
Flexible application – Works with common indicators like RSI, MFI, CCI, and moving averages (though confirmations should be done before publishing under your own secondary use).
Key Advantages Over Manual Methods
Speed: Instantly reflects HTF values without waiting for candle resolutions.
Adaptability: Adjusts automatically if the user changes timeframes or lengths.
Consistency: Removes human error in manual period calculations.
Limitations to Note
Not a magic bullet – While it solves the lag issue, traders should still:
Validate signals with price action or additional confirmations.
Be mindful of extreme lookback lengths (e.g., a 200-period daily SMA on a 1-minute chart requires 28,800 periods, which may strain performance).
Weighted Ichimoku StrategyLSE:HSBA
The Ichimoku Kinko Hyo indicator is a comprehensive tool that combines multiple signals to identify market trends and potential buying/selling opportunities. My weighted variant of this strategy attempts to assign specific weights to each signal, allowing for a more nuanced and customizable approach to trend identification. The intent is to try and make a more informed trading decision based on the cumulative strength of various signals.
I've tried not to make it a mishmash of this and that + MACD + RSI and on and on; most people have their preferred indicator that focuses on just that that they can use in conjunction.
The signals used can be grouped into two groups the 'Core Ichimoku Signals' & the 'Additional Signals' (at the end you will find the signals and their assigned weights followed by the thresholds where they align).
The Core Ichimoku Signals are the primary signals used in Ichimoku analysis, including Kumo Breakout, Chikou Cross, Kijun Cross, Tenkan Cross, and Kumo Twist.
While the Additional Signals provide further insights and confirmations, such as Kijun Confirmation, Tenkan-Kijun Above Cloud, Chikou Above Cloud, Price-Kijun Cross, Chikou Span Signal, and Price Positioning.
Entries are triggered when the cumulative weight of bullish signals exceeds a specified buy threshold, indicating a strong uptrend or potential trend reversal.
Exits are initiated when the cumulative weight of bearish signals surpasses a specified sell threshold, or when additional conditions such as consolidation patterns or ATR-based targets are met.
There are various exit types that you can choose between, which can be used separately or in conjunction with one another. As an example you might want to exit on a different condition during consolidation periods than during other periods or just use ATR with some other backstop.
They are listed in evaluation order i.e. ATR trumps all, Consolidation exit trumps the regular Kumo sell and so on:
**ATR Sell**: Exits trades based on ATR-based profit targets and stop-losses.
**Consolidation Exit**: Exits trades during consolidation periods to reduce drawdown.
**Sell Below Kumo**: Exits trades when the price is below the Kumo, indicating a potential downtrend.
**Sell Threshold**: Exits trades when the cumulative weight of bearish signals surpasses a specified sell threshold.
There are various 'filters' which are really behavior modifiers:
**Kumo Breakout Filter**: Requires price to close above the Kumo for buy signals (essentially a entry delay).
**Whipsaw Filter**: Ensures trend strength over specified days to reduce false signals.
**Buy Cooldown**: Prevents new entries until half the Kijun period passes after an exit (prevents flapping).
**Chikou Filter**: Delays exits unless the previous close is below the Chikou Span.
**Consolidation Trend Filter**: Prevents consolidation exits if the trend is bullish (rare, but happens).
Then there are some debugging options. Ichimoku periods have some presets (personally I like 8/22/44/22) but are freely configurable, preset to the traditional values for purists.
The list of signals and most thresholds follow, play around with them. Thats all.
Cheers,
**Core Ichimoku Signals**
**Kumo Breakout**
- 30 (Bullish) / -30 (Bearish)
- Indicates a strong trend when the price breaks above (bullish) or below (bearish) the Kumo (cloud). This signal suggests a significant shift in market sentiment.
**Chikou Cross**
- 20 (Bullish) / -20 (Bearish)
- Shows the relationship between the Chikou Span (lagging span) and the current price. A bullish signal occurs when the Chikou Span is above the price, indicating a potential uptrend. Conversely, a bearish signal occurs when the Chikou Span is below the price, suggesting a downtrend.
**Kijun Cross**
- 15 (Bullish) / -15 (Bearish)
- Signals trend changes when the Tenkan-sen (conversion line) crosses above (bullish) or below (bearish) the Kijun-sen (base line). This crossover is often used to identify potential trend reversals.
**Tenkan Cross**
- 10 (Bullish) / -10 (Bearish)
- Indicates short-term trend changes when the price crosses above (bullish) or below (bearish) the Tenkan-sen. This signal helps identify minor trend shifts within the broader trend.
**Kumo Twist**
- 5 (Bullish) / -5 (Bearish)
- Shows changes in the Kumo's direction, indicating potential trend shifts. A bullish Kumo Twist occurs when Senkou Span A crosses above Senkou Span B, and a bearish twist occurs when Senkou Span A crosses below Senkou Span B.
**Additional Signals**
**Kijun Confirmation**
- 8 (Bullish) / -8 (Bearish)
- Confirms the trend based on the price's position relative to the Kijun-sen. A bullish signal occurs when the price is above the Kijun-sen, and a bearish signal occurs when the price is below it.
**Tenkan-Kijun Above Cloud**
- 5 (Bullish) / -5 (Bearish)
- Indicates a strong bullish trend when both the Tenkan-sen and Kijun-sen are above the Kumo. Conversely, a bearish signal occurs when both lines are below the Kumo.
**Chikou Above Cloud**
- 5 (Bullish) / -5 (Bearish)
- Shows the Chikou Span's position relative to the Kumo, indicating trend strength. A bullish signal occurs when the Chikou Span is above the Kumo, and a bearish signal occurs when it is below.
**Price-Kijun Cross**
- 2 (Bullish) / -2 (Bearish)
- Signals short-term trend changes when the price crosses above (bullish) or below (bearish) the Kijun-sen. This signal is similar to the Kijun Cross but focuses on the price's direct interaction with the Kijun-sen.
**Chikou Span Signal**
- 10 (Bullish) / -10 (Bearish)
- Indicates the trend based on the Chikou Span's position relative to past price highs and lows. A bullish signal occurs when the Chikou Span is above the highest high of the past period, and a bearish signal occurs when it is below the lowest low.
**Price Positioning**
- 10 (Bullish) / -10 (Bearish)
- Shows indecision when the price is between the Tenkan-sen and Kijun-sen, indicating a potential consolidation phase. A bullish signal occurs when the price is above both lines, and a bearish signal occurs when the price is below both lines.
**Confidence Level**: Highly Sensitive
- **Buy Threshold**: 50
- **Sell Threshold**: -50
- **Notes / Significance**: ~2–3 signals, very early trend detection. High sensitivity, may capture noise and false signals.
**Confidence Level**: Entry-Level
- **Buy Threshold**: 58
- **Sell Threshold**: -58
- **Notes / Significance**: ~3–4 signals, often Chikou Cross or Kumo Breakout. Very sensitive, risks noise (e.g., false buys in choppy markets).
**Confidence Level**: Entry-Level
- **Buy Threshold**: 60
- **Sell Threshold**: -60
- **Notes / Significance**: ~3–4 signals, Kumo Breakout or Chikou Cross anchors. Entry point for early trends.
**Confidence Level**: Moderate
- **Buy Threshold**: 65
- **Sell Threshold**: -65
- **Notes / Significance**: ~4–5 signals, balances sensitivity and reliability. Suitable for moderate risk tolerance.
**Confidence Level**: Conservative
- **Buy Threshold**: 70
- **Sell Threshold**: -70
- **Notes / Significance**: ~4–5 signals, emphasizes stronger confirmations. Reduces false signals but may miss some opportunities.
**Confidence Level**: Very Conservative
- **Buy Threshold**: 75
- **Sell Threshold**: -75
- **Notes / Significance**: ~5–6 signals, prioritizes high confidence. Minimizes risk but may enter trades late.
**Confidence Level**: High Confidence
- **Buy Threshold**: 80
- **Sell Threshold**: -80
- **Notes / Significance**: ~6–7 signals, very strong confirmations needed. Suitable for cautious traders.
**Confidence Level**: Very High Confidence
- **Buy Threshold**: 85
- **Sell Threshold**: -85
- **Notes / Significance**: ~7–8 signals, extremely high confidence required. Minimizes false signals significantly.
**Confidence Level**: Maximum Confidence
- **Buy Threshold**: 90
- **Sell Threshold**: -90
- **Notes / Significance**: ~8–9 signals, maximum confidence level. Ensures trades are highly reliable but may result in fewer trades.
**Confidence Level**: Ultra Conservative
- **Buy Threshold**: 100
- **Sell Threshold**: -100
- **Notes / Significance**: ~9–10 signals, ultra-high confidence. Trades are extremely reliable but opportunities are rare.
**Confidence Level**: Extreme Confidence
- **Buy Threshold**: 110
- **Sell Threshold**: -110
- **Notes / Significance**: All signals align, extreme confidence. Trades are almost certain but very few opportunities.
Dskyz (DAFE) AI Adaptive Regime - Beginners VersionDskyz (DAFE) AI Adaptive Regime - Pro: Revolutionizing Trading for All
Introduction
In the fast-paced world of financial markets, traders need tools that can keep up with ever-changing conditions while remaining accessible. The Dskyz (DAFE) AI Adaptive Regime - Pro is a groundbreaking TradingView strategy that delivers advanced, AI-driven trading capabilities to everyday traders. Available on TradingView (TradingView Scripts), this Pine Script strategy combines sophisticated market analysis with user-friendly features, making it a standout choice for both novice and experienced traders.
Core Functionality
The strategy is built to adapt to different market regimes—trending, ranging, volatile, or quiet—using a robust set of technical indicators, including:
Moving Averages (MA): Fast and slow EMAs to detect trend direction.
Average True Range (ATR): For dynamic stop-loss and volatility assessment.
Relative Strength Index (RSI) and MACD: Multi-timeframe confirmation of momentum and trend.
Average Directional Index (ADX): To identify trending markets.
Bollinger Bands: For assessing volatility and range conditions.
Candlestick Patterns: Recognizes patterns like bullish engulfing, hammer, and double bottoms, confirmed by volume spikes.
It generates buy and sell signals based on a scoring system that weighs these indicators, ensuring trades align with the current market environment. The strategy also includes dynamic risk management with ATR-based stops and trailing stops, as well as performance tracking to optimize future trades.
What Sets It Apart
The Dskyz (DAFE) AI Adaptive Regime - Pro distinguishes itself from other TradingView strategies through several unique features, which we compare to common alternatives below:
| Feature | Dskyz (DAFE) | Typical TradingView Strategies|
|---------|-------------|------------------------------------------------------------|
| Regime Detection | Automatically identifies and adapts to **four** market regimes | Often static or limited to trend/range detection |
| Multi‑Timeframe Analysis | Uses higher‑timeframe RSI/MACD for confirmation | Rarely incorporates multi‑timeframe data |
| Pattern Recognition | Detects candlestick patterns **with volume confirmation** | Limited or no pattern recognition |
| Dynamic Risk Management | ATR‑based stops and trailing stops | Often uses fixed stops or basic risk rules |
| Performance Tracking | Adjusts thresholds based on past performance | Typically static parameters |
| Beginner‑Friendly Presets | Aggressive, Conservative, Optimized profiles | Requires manual parameter tuning |
| Visual Cues | Color‑coded backgrounds for regimes | Basic or no visual aids |
The Dskyz strategy’s ability to integrate regime detection, multi-timeframe analysis, and user-friendly presets makes it uniquely versatile and accessible, addressing the needs of everyday traders who want professional-grade tools without the complexity.
-Key Features and Benefits
[Why It’s Ideal for Everyday Traders
⚡The Dskyz (DAFE) AI Adaptive Regime - Pro democratizes advanced trading by offering professional-grade tools in an accessible package. Unlike many TradingView strategies that require deep technical knowledge or fail in changing market conditions, this strategy simplifies complex analysis while maintaining robustness. Its presets and visual aids make it easy for beginners to start, while its adaptive features and performance tracking appeal to advanced traders seeking an edge.
🔄Limitations and Considerations
Market Dependency: Performance varies by market and timeframe. Backtesting is essential to ensure compatibility with your trading style.
Learning Curve: While presets simplify use, understanding regimes and indicators enhances effectiveness.
No Guaranteed Profits: Like all strategies, success depends on market conditions and proper execution. The Reddit discussion highlights skepticism about TradingView strategies’ universal success (Reddit Discussion).
Instrument Specificity: Optimized for futures (e.g., ES, NQ) due to fixed tick values. Test on other instruments like stocks or forex to verify compatibility.
📌Conclusion
The Dskyz (DAFE) AI Adaptive Regime - Pro is a revolutionary TradingView strategy that empowers everyday traders with advanced, AI-driven tools. Its ability to adapt to market regimes, confirm signals across timeframes, and manage risk dynamically. sets it apart from typical strategies. By offering beginner-friendly presets and visual cues, it makes sophisticated trading accessible without sacrificing power. Whether you’re a novice looking to trade smarter or a pro seeking a competitive edge, this strategy is your ticket to mastering the markets. Add it to your chart, backtest it, and join the elite traders leveraging AI to dominate. Trade like a boss today! 🚀
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
Heiken Ashi with RSI Colors📜 Description:
This indicator blends Heiken Ashi candlesticks with RSI-based color filters to help traders quickly assess both trend structure and momentum extremes in a single glance.
✅ Heiken Ashi Mode: Smooths out price action to highlight clearer trends and suppress noise
✅ RSI Coloring: Applies candle color changes based on whether RSI is overbought, oversold, or neutral
It allows traders to visually spot potential exhaustion zones, continuation trends, or early reversal areas with enhanced clarity.
🔧 Settings:
Use Heiken Ashi Candles: Toggle between standard candles and Heiken Ashi smoothed values
RSI Length: Controls the lookback for RSI calculation (default 14)
Overbought/Oversold Levels: Customize your thresholds for extreme conditions (default: 70/30)
🎨 Candle Color Logic:
Green (Lime): RSI is overbought → price may be overextended upward
Red: RSI is oversold → price may be overextended downward
Gray: RSI is between extremes → neutral momentum
💡 Use Cases:
Confirm trend momentum with Heiken Ashi structure
Spot potential reversal points using RSI extremes
Enhance entry/exit decisions by combining price action and momentum in a single visual
