MSS, BOS, and FVG Trend ConfirmationSwing High and Swing Low Detection:
We're identifying the swing high and swing low using a length parameter that helps us find significant peaks and troughs. This is essential for both the MSS and BOS checks.
Market Structure Shift (MSS):
We check if the recent swing high is greater than the previous swing high (for an uptrend) and if the recent swing low is higher than the previous swing low. The same logic applies for a downtrend.
Break of Structure (BOS):
The script checks if the current price breaks above the last swing high for an uptrend or below the last swing low for a downtrend.
Fair Value Gap (FVG):
A FVG is detected when there's a significant imbalance. The script looks for cases where the price has moved sharply, and there might be a gap to fill.
Candle Color:
If MSS, BOS, and FVG all align to confirm an uptrend, the candle will turn blue.
If all three indicators align to confirm a downtrend, the candle will turn grey.
Signals:
For visual confirmation, we plot shapes above or below bars indicating when the uptrend or downtrend is confirmed.
Indicatori e strategie
True Seasonal Pattern [tradeviZion]True Seasonal Pattern: Uncover Hidden Market Cycles
Markets have rhythms and patterns that repeat with surprising regularity. The True Seasonal Pattern indicator reveals these hidden cycles across different timeframes, helping you anticipate potential market movements based on historical seasonal tendencies.
What This Indicator Does
The True Seasonal Pattern analyzes years of historical price data to identify recurring seasonal trends. It then plots these patterns on your chart, showing you both the historical pattern and future projection based on past seasonal behavior.
Automatic Timeframe Detection: Works with Monthly, Weekly, and Daily charts
Historical Pattern Analysis: Analyzes up to 100 years of data (customizable)
Future Projection: Projects the seasonal pattern ahead on your chart
Smart Smoothing: Applies appropriate smoothing based on your timeframe
How to Use This Indicator
Add the indicator to a Daily, Weekly, or Monthly chart (not designed for intraday timeframes)
The indicator automatically detects your chart's timeframe
The blue line shows the historical seasonal pattern
Watch for potential turning points in the pattern that align with other technical signals
Seasonal patterns work best as a supporting factor in your analysis, not as standalone trading signals. They are particularly effective in markets with well-established seasonal influences.
Best Applications
Futures Markets: Commodities and futures often show strong seasonal tendencies due to production cycles, weather patterns, and economic factors
Stock Indices: Many stock markets demonstrate regular seasonal patterns (like the "Sell in May" phenomenon)
Individual Stocks: Companies with seasonal business cycles often show predictable price patterns
Practical Applications
Identify potential turning points based on historical seasonal patterns
Plan entries and exits around seasonal tendencies
Add seasonal context to your existing technical analysis
Understand why certain months or periods might show consistent behavior
Pro Tip: For best results, use this tool on instruments with at least 5+ years of historical data. Longer timeframes often reveal more reliable seasonal patterns.
Important Notes
This indicator works best on Daily, Weekly, and Monthly timeframes - not intraday charts
Seasonal patterns are tendencies, not guarantees
Always combine seasonal analysis with other technical tools
Past patterns may not repeat exactly in the future
// Sample of the seasonal calculation approach
float yearHigh = array.max(currentYearHighs)
float yearLow = array.min(currentYearLows)
// Calculate seasonality for each period
for i = 0 to array.size(currentYearCloses) - 1
float periodClose = array.get(currentYearCloses, i)
if not na(periodClose) and yearHigh != yearLow
float seasonality = (periodClose - yearLow) / (yearHigh - yearLow) * 100
I developed this indicator to help traders incorporate seasonal analysis into their trading approach without the complexity of traditional seasonal tools. Whether you're analyzing agricultural commodities, energy futures, or stock indices, understanding the seasonal context can provide valuable insights for your trading decisions.
Remember: Markets don't always follow seasonal patterns, but when they do, being aware of these tendencies can give you a meaningful edge in your analysis.
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
Inputs and What They Mean (Read Carefully)
📊 Main Signal Inputs
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
Personal Note to Mods and Traders:
Yes, this statement is DIFFERENT, because this script IS different. If you see this taken down for some technicality (charting labels etc.), know I will fix, adapt, and repost until the system and its truth are visible to the community.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz, powered by DAFE Trading Systems.
Buy/Sell Signal - RSI + EMA + MACDSignal 'Buy' if all of the following three conditions are true
Rsi crosses above 55
Ema 9 crosses over ema 21
Macd histogram shows second green on
Signal 'Sell' if all of the following three conditions are true
Rsi crosses below 45
Ema 9 crosses below Ema 21
Macd histogram shows second red on
Durbtrade BBW Bollinger Bands Width (+EMA) [Main Chart]If green arrow comes then it means volatility is coming
53 ToolkitTest
No functions
5-minute candlestick 3-tick rule: How to find a rebound point (short-term bottom) when a correction comes after an uptrend
The most stable way to make a profit when trading short-term is to accurately determine the point of rebound in the 'rise -> fall -> rebound' pattern.
Based on the premise that a decline is followed by a rebound, this is a formula created by analyzing the patterns of coins that frequently rebound.
Prevents being bitten at the high point by forcibly delaying the entry point according to market conditions. (HOW?)
Mostly 5-minute and 15-minute candles are used, but 30-minute candles can also be used depending on the situation.
Parsifal.Swing.CompositeThe Parsifal.Swing.Composite indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators such as:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module serves as an indicator facilitating judgment of the current swing state in the underlying market.
________________________________________
Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These oscillations—or swings—within the trend are inherently tradable.
They can be approached:
• One-sidedly, aligning with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions as well.
Note: Mean reversions in strong trends often manifest as sideways consolidations, making one-sided trades more stable.
________________________________________
The Parsifal Swing Suite
The modules aim to provide additional insights into the swing state within a trend and offer various trigger points to assist with entry decisions.
All modules in the suite act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., RSI, which is constrained between 0% and 100%).
________________________________________
The Parsifal.Swing.Composite – Specifics
This module consolidates multiple insights into price swing behavior, synthesizing them into an indicator reflecting the current swing state.
It employs layered bagging and smoothing operations based on standard price inputs (OHLC) and classical technical indicators. The module integrates several slightly different sub-modules.
Process overview:
1. Per candle/bin, sub-modules collect directional signals (up/down), with each signal casting a vote.
2. These votes are aggregated via majority counting (bagging) into a single bin vote.
3. Bin votes are then smoothed, typically with short-term EMAs, to create a sub-module vote.
4. These sub-module votes are aggregated and smoothed again to generate the final module vote.
The final vote is a score indicating the module’s assessment of the current swing state. While it fluctuates in a range, it's not a true oscillator, as most inputs are normalized via Z-scores (value divided by standard deviation over a period).
• Historically high or low values correspond to high or low quantiles, suggesting potential overbought or oversold conditions.
• The chart displays a fast (orange) and slow (white) curve against a solid background state.
• Extreme values followed by curve reversals may signal upcoming mean-reversions.
Background Value:
• Value > 0: shaded green → bullish mode
• Value < 0: shaded red → bearish mode
• The absolute value indicates confidence in the mode.
________________________________________
How to Use the Parsifal.Swing.Composite
Several change points in the indicator serve as potential entry triggers:
• Fast Trigger: change in slope of the fast curve
• Trigger: fast line crossing the slow line or change in the slow curve’s slope
• Slow Trigger: change in sign of the background value
These are illustrated in the introductory chart.
Additionally, market highs and lows aligned with swing values may act as pivot points, support, or resistance levels for evolving price processes.
________________________________________
As always, supplement this indicator with other tools and market information. While it provides valuable insights and potential entry points, it does not predict future prices. It reflects recent tendencies and should be used judiciously.
________________________________________
Extensions
All modules in the Parsifal Swing Suite are simple yet adaptable, whether used individually or in combination.
Customization options:
• Weights in EMAs for smoothing are adjustable
• Bin vote aggregation (currently via sum-of-experts) can be modified
• Alternative weighting schemes can be tested
Advanced options:
• Bagging weights may be historical, informational, or relevance-based
• Selection algorithms (e.g., ID3, C4.5, CAT) could replace the current bagging approach
• EMAs may be generalized into expectations relative to relevance-based probability
• Negative weights (akin to wavelet transforms) can be incorporated
WaveFunction MACD (TechnoBlooms)WaveFunction MACD — The Next Generation of Market Momentum
WaveFunction MACD is an advanced hybrid momentum indicator that merges:
• The classical MACD crossover logic (based on moving averages)
• Wave physics (modeled through phase energy and cosine functions)
• Hilbert Transform theory from signal processing
• The concept of a wavefunction from quantum mechanics, where price action is seen as a probabilistic energy wave—not just a trend.
✨ Key Features of WaveFunction MACD
• Wave Energy Logic : Instead of using just price and MA differences, this indicator computes phase-corrected momentum using the cosine of the wave phase angle — revealing the true energy behind market moves.
• Phase-Based Trend Detection : It reads cycle phases using Hilbert Transform-like logic, allowing you to spot momentum before it becomes visible in price.
• Ultra-Smooth Flow : The main line and histogram are built to follow price flow smoothly — eliminating much of the noise found in traditional MACD indicators.
• Signal Amplification via Energy Histogram : The histogram doesn’t just show momentum changes — it shows the intensity of wave energy, allowing you to confirm the strength of the trend.
• Physics-Driven Structure : The algorithm is rooted in real-world wave mechanics, bringing a scientific edge to trading — ideal for traders who believe in natural models like cycles and harmonics.
• Trend Confirmation & Early Reversals : It can confirm strong trends and also catch subtle shifts that often precede big reversals — giving you both reliability and anticipation.
• Ready for Fusion : Designed to work seamlessly with liquidity zones, price action, order blocks, and structure trading — a perfect fit for modern trading systems.
🧪 The Science Behind It
This tool blends:
• Hilbert Transform: Measures the phase of a waveform (price cycle) to detect turning points
• Cosine Phase Energy: Calculates true wave energy using the cosine of the phase angle, revealing the strength behind price movements
• Quantum Modeling: Views price like a wavefunction, offering predictive insight based on phase dynamics
Wx Stop Loss BetaWx Stop Loss Beta is an adaptive stop-loss overlay intended for discretionary entry management in medium- to long-term trades. It integrates a volatility filter, support-based logic, and capital protection constraints.
• Manual Entry Price: User inputs their actual entry point
• Volatility Anchor: Stop-loss adjusts using ATR (customizable length and multiplier)
• Support Reference: Based on swing low over a configurable lookback period
• Loss Cap: Maximum allowable loss percentage from entry price (hard floor)
• Trailing Logic: Stop-loss only moves upward (never lowers), adapting to favorable price action
• Output: Displays a horizontal line at the stop-loss level and renders its value in the data window
Warning: This tool is experimental and has not been formally backtested. It is provided as-is for manual strategy enhancement. Use at your own discretion, and validate thoroughly in a paper or sandbox environment before relying on it in live trading. Feedback and critique are encouraged.
SPX Intraday Call SignalThis indicator identifies intraday SPX call option trade setups based on a simple trend and momentum strategy. It detects when the 9-period EMA crosses above the 21-period EMA (bullish momentum) while price is trading above the VWAP (confirming intraday bullish bias) and the RSI (14) is above 55 (confirming momentum strength). The indicator is designed to trigger only during a defined trading window between 9:45 AM and 11:30 AM ET and plots a signal only once per day (the first valid setup) to avoid overtrading. It also includes alert conditions for automated notifications when a valid setup is detected.
AWR_WaveTrend MutltitimeframeWaveTrend Oscillator is a port of a famous TS/MT indicator
The WT Multi-Timeframe indicator consists of several lines representing different time frames: monthly (red), weekly (yellow), daily (green), 4-hour (purple), and lower units (blue).
It helps analyze trends and potential turning points, allowing one to decide whether to follow the trend or take contrarian positions.
You can choose which timeframes you want to display for the current period or for the last period closed.
In a few seconds, you perfectly see the selected timeframes trends.
When the oscillator (WT1 designed as a line) is above the overbought band (53 to 63) and crosses down the WT2 (signaled by a x), it is usually a good SELL signal.
Similarly, when the oscillator crosses above the WT2 (signal = triangle) when below the Oversold band ( (-53 to -63)), it is a good BUY signal.
You can also check the cross between differents WT1 (daily and weekly seems to be very effective).
An wt1 of a lower timeframe can also be blocked by an higher timeframe WT.
I've also add small items down the graph that correspond at specific situation :
🌟 WT1 from 1H to D are below WT1 Weekly and below -50
🤿 WT1 from 1H to D are above WT1 Weekly and above 50
🌋WT1 daily is going up and crossing WT1 weekly
🪂 WT1 daily is going down and crossing WT1 weekly
Let's see some example :
1 : See the effect of a cross down between W and M (yellow and red)
2 : A yellow triangle (wt1 weekly cross up wt2 weekly) in a nice zone
3 : See the effect of a cross up between W and M (yellow and red)
4 : See the effect of a cross down between W and M (yellow and red) in a nice zone
5 : A yellow triangle (wt1 weekly cross up wt2 weekly) in a nice zone
Etc...
Machine Learning: ARIMA + SARIMADescription
The ARIMA (Autoregressive Integrated Moving Average) and SARIMA (Seasonal ARIMA) are advanced statistical models that use machine learning to forecast future price movements. It uses autoregression to find the relationship between observed data and its lagged observations. The data is differenced to make it more predictable. The MA component creates a dependency between observations and residual errors. The parameters are automatically adjusted to market conditions.
Differences
ARIMA - This excels at identifying trends in the form of directions
SARIMA - Incorporates seasonality. It's better at capturing patterns previously seen
How To Use
1. Model: Determine if you want to use ARIMA (better for direction) or SARIMA (better for overall prediction). You can click on the 'Show Historic Prediction' to see the direction of the previous candles. Green = forecast ending up, red = forecast ending down
2. Metrics: The RMSE% and MAPE are 10 day moving averages of the first 10 predictions made at candle close. They're error metrics that compare the observed data with the predicted data. It is better to use them when they're below 8%. Higher timeframes will be higher, as these models are partly mean-reverting and higher TFs tend to trend more. Better to compare RMSE% and MAPE with similar timeframes. They naturally lag as data is being collected
3. Parameter selection: The simpler, the better. Both are used for ARIMA(1,1,1) and SARIMA(1,1,1)(1,1,1)5. Increasing may cause overfitting
4. Training period: Keep at 50. Because of limitations in pine, higher values do not make for more powerful forecasts. They will only criminally lag. So best to keep between 20 and 80
XAU/USD StrategyTrade CAPITALCOM:GOLD (XAU/USD) effortlessly — our advanced Buy/Sell Bot does the hard work for you.
✅ Low-risk strategy
✅ Starts with just $10
✅ Ideal for beginners and passive traders
Let the bot analyze the market and execute trades automatically.
📈 Get started today and watch your trading go hands-free!
AWR_Oscillateur de DéviationThis indicator calculates linear regression index according to several configurable periods.
There are a total of eight configurable periods.
Each time, the indicator will calculate for each specified range the best linear regression line & then it will plot it as an oscillator.
For example, if the price is at 2 standard deviation of his linear regression line, it will plot it at 2 on the graph. etc...
It will currently be configured by default between 0 and 5000 UT, which provides both a short-term and a very long-term view.
You can set a specific color for each linear regression index.
As a reminder, the linear regression line is based on the least squares method, meaning: the more the price deviates from its regression line, the more statistically likely it is to return to its regression line. From two standard deviations or minus two standard deviations, it is generally statistically proven that we will trend towards the regression line over time.
Here are some key applications:
1. Trend Identification – you can use it to identify the general direction of each period by analysing the slope of linear regression index
2. Support and Resistance Levels – Regression channels help traders identify support and resistance zones, providing insight into optimal entry and exit points in a trend.
3. You can also use the short period linear regression index vs the long period linear regression index to identify important pivot points.
I've added red & blue color to help to identify excess points. Be careful, an excess can be more excessive than expected... ;-)
StarterPack MAsThis indicator includes 5 moving averages widely used in modern price action analysis:
EMA 9 (green): captures recent candle momentum
SMA 20 (gold): classic reference for pullbacks
SMA 50 (red): dynamic short- to mid-term support and resistance
SMA 200 (blue): long-term trend foundation
EMA 400 (pink): used by traders tracking institutional moves
Perfect for identifying trend direction, balance zones, and key confluence areas.
Use it with strategy and discipline. Moving averages show the path — execution is up to you.
[blackcat] L3 Adaptive Trend SeekerOVERVIEW
The indicator is designed to help traders identify dynamic trends in various markets efficiently. It employs advanced calculations including Dynamic Moving Averages (DMAs) and multiple moving averages to filter out noise and provide clear buy/sell signals 📈✨. By utilizing innovative algorithms that adapt to changing market conditions, this tool enables users to make informed decisions across different timeframes and asset classes.
This versatile indicator serves both novice and experienced traders seeking reliable ways to navigate volatile environments. Its primary objective is to simplify complex trend analysis into actionable insights, making it an indispensable addition to any trader’s arsenal ⚙️🎯.
FEATURES
Customizable Dynamic Moving Average: Calculates an adaptive moving average tailored to specific needs using customizable coefficients.
Trend Identification: Utilizes multi-period moving averages (e.g., short-term, medium-term, long-term) to discern prevailing trends accurately.
Crossover Alerts: Provides visual cues via labels when significant crossover events occur between key indicators.
Adjusted MA Plots: Displays steplines colored according to the current trend direction (green for bullish, red for bearish).
Historical Price Analysis: Analyzes historical highs and lows over specified periods, ensuring robust trend identification.
Conditional Signals: Generates bullish/bearish conditions based on predefined rules enhancing decision-making efficiency.
HOW TO USE
Script Installation:
Copy the provided code and add it under Indicators > Add Custom Indicator within TradingView.
Choose an appropriate name and enable it on your desired charts.
Parameter Configuration:
Adjust the is_trend_seeker_active flag to activate/deactivate the core functionality as needed.
Modify other parameters such as smoothing factors if more customized behavior is required.
Interpreting Trends:
Observe the steppled lines representing the long-term/trend-adjusted moving averages:
Green indicates a bullish trend where prices are above the dynamically calculated threshold.
Red signifies a bearish environment with prices below respective levels.
Pay attention to labels marked "B" (for Bullish Crossover) and "S" (for Bearish Crossover).
Signal Integration:
Incorporate these generated signals within broader strategies involving support/resistance zones, volume data, and complementary indicators for stronger validity.
Use crossover alerts responsibly by validating them against recent market movements before execution.
Setting Up Alerts:
Configure alert notifications through TradingView’s interface corresponding to crucial crossover events ensuring timely responses.
Backtesting & Optimization:
Conduct extensive backtests applying diverse datasets spanning varied assets/types verifying robustness amidst differing conditions.
Refine parameters iteratively improving overall effectiveness and minimizing false positives/negatives.
EXAMPLE SCENARIOS
Swing Trading: Employ the stepline crossovers coupled with momentum oscillators like RSI to capitalize on intermediate trend reversals.
Day Trading: Leverage rapid adjustments offered by short-medium term MAs aligning entries/exits alongside intraday volatility metrics.
LIMITATIONS
The performance hinges upon accurate inputs; hence regular recalibration aligning shifting dynamics proves essential.
Excessive reliance solely on this indicator might lead to missed opportunities especially during sideways/choppy phases necessitating additional filters.
Always consider combining outputs with fundamental analyses ensuring holistic perspectives while managing risks effectively.
NOTES
Educational Resources: Delve deeper into principles behind dynamic moving averages and their significance in technical analysis bolstering comprehension.
Risk Management: Maintain stringent risk management protocols integrating stop-loss/profit targets safeguarding capital preservation.
Continuous Learning: Stay updated exploring evolving financial landscapes incorporating new methodologies enhancing script utility and relevance.
THANKS
Thanks to all contributors who have played vital roles refining and optimizing this script. Your valuable feedback drives continual enhancements paving way towards superior trading experiences!
Happy charting, and here's wishing you successful ventures ahead! 🌐💰!
AWR Optimized LR (Multiple)Attached you will find the indicator that calculates linear regression lines according to several configurable periods.
There are a total of eight configurable periods.
Each time, the indicator will calculate for each specified range the best linear regression line & channel (2 standard regressions) for that period and then plot it on the graph.
It will currently be configured by default between 0 and 5000 UT, which provides both a short-term and a very long-term view.
You can set a specific color for each linear regression channels.
As a reminder, the linear regression line is based on the least squares method, meaning: the more the price deviates from its regression line, the more statistically likely it is to return to its regression line. From two standard deviations or minus two standard deviations), it is generally statistically proven that we will trend towards the regression line over time.
Application of Regression Lines in Trading
Regression lines are widely used in trading and financial analysis to understand market trends and make informed predictions. Here are some key applications:
1. Trend Identification – Traders use regression lines to visualize the general direction of a stock or asset price, helping to confirm an upward or downward trend.
2. Price Predictions – Linear regression models assist in estimating future price movements based on historical data, allowing traders to anticipate changes.
3. Risk Assessment – By analyzing the slope and variation of a regression line, traders can gauge market volatility and potential risks.
4. Support and Resistance Levels – Regression channels help traders identify support and resistance zones, providing insight into optimal entry and exit points in a trend.
5. You can also use the short period linear regression channels vs the long period linear regression channels to identify important pivot points.
Distance to EMASimple indicator to show the distance to the H1 50 EMA in a number of common time frames below and above. Useful as a quick glance to spot divergences in price before a reversion to the mean / polarity reversal.
Note that this is multi-timeframe but the distances are calculated differently depending upon context.
There are some presets where the distance is calculated to the H1 50 EMA when in timeframes below this:
M1, M4, M15 & H1 all calculate based upon the price distance to the H1 50 EMA, since this is a useful directional indicator for lower timeframes to see where we are wrt H1 without having to switch.
However above the H1, there's H4, H8 and H12 presets - but these use the 1D 50 EMA since I generally use these in HTF calculations.
Any other timeframe will use whatever the indicator is set up as in the options menu.
Daily Range % with Conditional SPX DirectionThis indicator visualizes the short-term market sentiment by combining the trend of the S&P 500 index (SPX) with daily price volatility (DP%).
Key Features:
Calculates a 5-period Exponential Moving Average (EMA) of SPX to detect trend direction:
Rising EMA → Uptrend
Falling EMA → Downtrend
Calculates a 5-period Simple Moving Average (SMA) of Daily Price Range % (DP%) to assess volatility trend:
Rising DP% → Increasing volatility
Falling DP% → Decreasing volatility
Background Colors:
Green: SPX trend up & volatility down → Bullish
Yellow:
SPX trend up & volatility up, or
SPX trend down & volatility down → Neutral
Red: SPX trend down & volatility up → Bearish
On-screen Labels:
Displays SPX trend direction (⬆️ / ⬇️)
Displays volatility direction (⬆️ / ⬇️)
Displays overall market sentiment: Bullish / Neutral / Bearish
This tool is designed to help traders quickly assess the relationship between trend and volatility, aiding in market environment analysis and discretionary trading decisions.
Automatic HTF MA CloudsAutomatically display higher time frame HTF clouds based on presets.
Fifteen selections in total. Default settings based on Barky's DTF concepts.
Five presets left blank.
A simple table display CTF and HTF. Can be turned off in settings.
CTF1 1m → HTF1 5m
CTF2 2m → HTF2 10m
CTF3 10m → HTF3 1h
CTF4 1h → HTF4 4h
CTF5 4h → HTF5 1d
CTF6 1d → HTF6 1w
CTF7 1w → HTF7 1M
CTF8 1M → HTF8 3M
CTF9 3M → HTF9 6M
CTF10 6M → HTF10 12M
CTF11 blank → HTF11 blank
CTF12 blank → HTF12 blank
CTF13 blank → HTF13 blank
CTF14 blank → HTF14 blank
CTF15 blank → HTF15 blank
Daily Range % with Conditional SPX DirectionThis indicator visualizes the short-term market sentiment by combining the trend of the S&P 500 index (SPX) with daily price volatility (DP%).
Key Features:
Calculates a 5-period Exponential Moving Average (EMA) of SPX to detect trend direction:
Rising EMA → Uptrend
Falling EMA → Downtrend
Calculates a 5-period Simple Moving Average (SMA) of Daily Price Range % (DP%) to assess volatility trend:
Rising DP% → Increasing volatility
Falling DP% → Decreasing volatility
Background Colors:
Green: SPX trend up & volatility down → Bullish
Yellow:
SPX trend up & volatility up, or
SPX trend down & volatility down → Neutral
Red: SPX trend down & volatility up → Bearish
On-screen Labels:
Displays SPX trend direction (⬆️ / ⬇️)
Displays volatility direction (⬆️ / ⬇️)
Displays overall market sentiment: Bullish / Neutral / Bearish
This tool is designed to help traders quickly assess the relationship between trend and volatility, aiding in market environment analysis and discretionary trading decisions.
