ATR based Pivots mcbwHey everyone this is an exciting new script I have prepared for you.
I was reading an old forex bulletin article some time ago when I came across this: solar.murty.net (or you can download the full bulletin with lots of other good articles here: www.forexfactory.com).
You can already buy this for metatrader (www.mql5.com) so I figured to make it for free for tradingview.
This bulletin suggested that you can reasonably predict daily volatility by adding or subtracting multiples of the daily ATR to the daily opening. Using this you can choose multiples to use as price targets and alternatively as stop losses. For example, if you already have a sense of market direction you can buy at market open place a stop loss at - 1 daily ATR and a profit target at + 3 ATRs for a risk to reward ratio of 3. If you are looking for smaller/quicker moves with a ratio of 3 you can have a stop loss at -0.25 ATR and a take profit at +0.75 ATR.
Alternatively this article also suggests to use this method to catch volatility breakouts. If price is higher than the + 1 ATR area then you can safely assume it will be going to the +2 ATR area so you can put a buy stop at + 1 ATR with a profit target at + 2 ATR with a stop loss at +0.5 ATR to catch a volatility breakout with a risk to reward ratio of 2!
Even further there are methods that you can use with ATRs of multiple window sizes, for example by opening two copies of this indicator and measuring recent volatility with a 1 week window and long term volatility within a 1 month window. If the short term volatility is crossing the long term volatility then there is a high probability chance that even more price movement will occur.
However I have found that this method is good for more than daily volatility , it can also be used to measure weekly volatility , and monthly volatility and use these multiples as good long term price targets.
To select if you want daily, weekly, or monthly values of the ATR of volatility you're using go to the settings and click on the options in the "Opening period". The default window of the ATR here is 14 periods, but you can change this if you want to in "ATR period". Most importantly you are able to select which multiples of the ATR you would like to use in the settings in "ATR multiple 1" which is the green line, "ATR multiple 2" which is the blue line, and "ATR multiple 3" which is the purple line. You can select any values you want to put in these, the choice of 0.25, 0.5, and 1 is not special, some people use fibonacci numbers here or simply 0.33, 0.66, and 0.99.
Repainting issue: This script uses the daily value of the Average True Range (ATR), which measures the volatility that is happening today. If price becomes more volatile then the value of the ATR can increase throughout the day, but it can never decrease. What this means is that the ATR based pivots are able to expand away from the opening price, which should not affect the trades that you take based on these areas. If you base your take profit on one of these ATR multiples and the daily volatility increase this means that your take profit area will be closer to your entry than the ATR multiple. Meaning that your trades will be more conservative.
While this all may sound very technical it is super intuitive, throw this on your chart and play around with it :)
Happy trading!
Komut dosyalarını "META股价历史数据" için ara
Pentuple Exponential Moving Average (PEMA)This type of moving average was originally developed by Bruno Pio in 2010. I just ported the original code from MetaTrader 5. The method uses a linear combination of EMA cascades to achieve better smoothness. Well, actually you can create your own X-uple EMA, but be sure that the combination' coefficients are valid.
Quadruple Exponential Moving Average (QEMA)This type of moving average was originally developed by Bruno Pio in 2010. I just ported the original code from MetaTrader 5.
Normalized Volume OscillatorThis volume indicator works best on comparatively small timeframes (15 minutes, for example).
Based on:
- Normalized Volume Oscillator - indicator for MetaTrader 4
- Using Tick Volume in Forex: A Clear NVO Based Example
See also:
- Are price updates a good proxy for actual traded volume in FX?
S/R BarryThis is the "S/R Barry" MetaTrader indicator, shown here: www.forexfactory.com
You can increase the FractalLen input value to show more-significant structures.
Here's and example with the default FractalLen value (3):
Here's an example with a higher FractalLen value (10):
Written by Christopher Sebastian. Send questions to csebastian3@gmail.com
Basic MAAll-in-one basic indicators:
- MA Fast (12)
- MA Medium (26)
- MA Slow (200)
- Parabolic SAR www.investopedia.com
- Dynamic Fibonnaci channel with 2 channels - www.forexstrategiesresources.com
Vegas TunnelThis indicator adds and subtracts fib levels from the moving average. I suppose profits are meant to be taken at certain levels. Additionally, it may help in finding tops and bottoms. There's more info here: www.forexstrategiesresources.com
The fib levels should be changed depending on time frame:
short) 5, 8, 13, 21
intermediate) 34, 55, 89, 144
long) 55, 89, 144, 233
Waddah Attar Explosion [LazyBear]This is a port of a famous MT4 indicator, as requested by user @maximus71. This indicator uses MACD/BB to track trend direction and strength. Author suggests using this indicator on 30mins.
Explanation from the indicator developer:
"Various components of the indicator are:
Dead Zone Line: Works as a filter for weak signals. Do not trade when the red or green histogram is below it.
Histograms:
- Red histogram shows the current down trend.
- Green histogram shows the current up trend.
- Sienna line shows the explosion in price up or down.
Signal for ENTER_BUY: All the following conditions must be met.
- Green histo is raising.
- Green histo above Explosion line.
- Explosion line raising.
- Both green histo and Explosion line above DeadZone line.
Signal for EXIT_BUY: Exit when green histo crosses below Explosion line.
Signal for ENTER_SELL: All the following conditions must be met.
- Red histo is raising.
- Red histo above Explosion line.
- Explosion line raising.
- Both red histo and Explosion line above DeadZone line.
Signal for EXIT_SELL: Exit when red histo crosses below Explosion line. "
All of the parameters are configurable via options page. You may have to tune it for your instrument.
More info:
Author note: www.forex-tsd.com
Video (French): www.youtube.com
List of my other indicators:
- GDoc: docs.google.com
- Chart:
Chaithanya Tattva Volume Zones📜 "Chaitanya Tattva" Volume Zones:-
A Sacred Framework of Supply, Demand & Market Energy
In the world of financial markets, price is said to reflect all information. But the true pulse of the market — its life force, its intent, and its moment of truth — is most vividly expressed not in price itself, but in volume.
Chaitanya Tattva Volume Zones is a spiritually inspired volume-based tool that transforms your chart into a canvas of market consciousness, revealing moments where supply and demand engage in visible energetic spikes. These moments are often disguised as ordinary candles, but with this tool, you uncover zones of intent — footprints left by the market’s deeper intelligence.
🌟 Why “Chaitanya Tattva”?
Chaitanya (चैतन्य) is a Sanskrit word meaning consciousness, awareness, or the spark of life energy. It is that which animates — the subtle intelligence behind all movement.
Tattva (तत्त्व) refers to essence, truth, or the underlying principle of a thing. In classical yogic philosophy, the tattvas are the elemental building blocks of reality.
Together, Chaitanya Tattva represents the conscious essence — the living pulse that animates the market through volume surges and imbalances.
This tool is not just a technical indicator — it is a spiritual observation device that aligns with the rhythm of volume and price action. It doesn't predict the market. It reveals when the market has already spoken — loudly, clearly, and energetically.
📈 What Does the Tool Do?
Chaitanya Tattva Volume Zones identifies exceptional volume spikes within the recent price history and visually marks the areas where market intent has been most active.
Specifically, the tool:
Scans for volume spikes that exceed all the volume of the last N bars (default is 20)
Confirms whether the spike happened on a bullish candle (close > open) or bearish candle (close < open)
For a bullish spike, it marks a Supply Zone — the area between the high and close of the candle
For a bearish spike, it marks a Demand Zone — the area between the low and close
Visually paints these zones with soft translucent boxes (red for supply, green for demand) that extend forward across multiple bars
🧘♂️ The Spiritual Framework
🔴 Supply = "Agni" — The Fire of Expansion
When a bullish candle erupts with historically high volume, it symbolizes the fire (Agni) of market optimism and upward expansion. It means that buyers have absorbed available supply at that level and established dominance — but such fire may also signal exhaustion, making it a potential supply barrier if price returns.
These Supply Zones are areas where:
Sellers are likely to re-engage
Smart money may be unloading
Future resistance can be anticipated
But unlike traditional indicators, this tool doesn’t guess. It reacts only to a clear volume-based event — when market energy surges — and locks in that awareness through zone marking.
🟢 Demand = "Prithvi" — The Grounding of Price
On the other hand, a bearish candle with extremely high volume represents the Earth (Prithvi) — grounding the price with firm hands. A strong volume drop often means buyers are stepping in, absorbing the selling pressure.
These Demand Zones are areas where:
Buying interest is proven
Market memory is stored
Future support can be expected
By respecting these zones, you're aligning your trading with natural market boundaries — not theoretical ones.
🧠 How Is It Different from Regular Volume Tools?
While most volume indicators show bars on a lower panel, they leave interpretation up to the trader. “High” or “low” becomes subjective.
Chaitanya Tattva Volume Zones is different:
It quantifies "spike": a bar must exceed all previous N volumes
It qualifies the intent: was the spike bullish or bearish?
It marks zones on the price chart: no need to guess levels
It preserves market memory: the zones persist visually for easy reference
In essence, this tool doesn’t just report volume — it interprets volume’s context and visually encodes it into the chart.
🧘 How to Use
1. Support/Resistance Mapping
Use the tool to understand where volume proved itself. If price revisits a red zone, expect possible rejection (resistance). If price revisits a green zone, expect possible absorption (support).
2. Entry Triggers
You may enter:
Long near demand zones if bullish confirmation appears
Short near supply zones if bearish confirmation appears
3. Stop Placement
Stops can be placed just beyond the zone boundary to align with areas where smart money historically defended.
4. Breakout Confidence
When price breaks through one of these zones with momentum, it often signals a new energetic wave — the old balance has been overcome.
🔔 Key Features
Volume spike detection across any timeframe
Clear visual zones — no clutter, no lag
Highly customizable: zone width, volume lookback, colors
Philosophy-aligned with supply and demand theory, Wyckoff, and Order Flow
🌌 A Metaphysical View of Volume
In yogic science, volume is akin to Prana — life-force energy. A market is not moved by price alone but by intent, force, and participation — all encoded in volume.
Just as a human body pulses with blood when action intensifies, the market pulses with volume when institutional decisions are made.
These pulses become sacred footprints — and Chaitanya Tattva Volume Zones helps you walk mindfully among them.
🔮 Final Thoughts
In a sea of indicators that shout at you with every tick, Chaitanya Tattva is calm. It speaks only when energy concentrates, only when the market sends a signal born of intent.
It doesn’t predict.
It doesn’t repaint.
It simply shows the truth, when the truth becomes undeniable.
Like a sage that speaks only when needed, it waits for volume to prove itself — then draws a memory into space, a zone where traders can re-align their actions with what the market has already honored.
Use it not just to trade —
But to listen.
To observe.
To follow the Chaitanya — the conscious pulse of the market’s own breath.
Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD)
Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis
The Revolutionary Concept: When Physics Meets Trading
After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits.
The Core Innovation: Ergodic Theory Applied to Markets
What Makes Markets Ergodic or Non-Ergodic?
In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading:
Ergodic Markets (Mean-Reverting)
- Time averages equal ensemble averages
- Historical patterns repeat reliably
- Price oscillates around equilibrium
- Traditional indicators work well
Non-Ergodic Markets (Trending)
- Path dependency dominates
- History doesn't predict future
- Price creates new equilibrium levels
- Momentum strategies excel
The Mathematical Framework
The Ergodic Score combines three critical divergences:
Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3
Where:
Price Divergence: How far current price deviates from market consensus
Return Divergence: Momentum differential between instrument and market
Volatility Divergence: Volatility regime misalignment
Market Stress: Adaptive multiplier based on current conditions
The Ensemble Analysis Revolution
Beyond Single-Instrument Analysis
Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach:
Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves
Filters False Signals: Requires broader market confirmation
Identifies Regime Shifts: Detects when entire market structure changes
Provides Context: Shows if moves are isolated or systemic
Dynamic Threshold Adaptation
Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions:
Base Threshold = SMA(Ergodic Score, Lookback × 3)
Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity
Final Threshold = Smoothed(Base + Adaptive)
This creates context-aware signals that remain effective across different market environments.
The Confidence Engine: Know Your Signal Quality
Multi-Factor Confidence Scoring
Every signal receives a confidence score based on:
Signal Clarity (0-35%): How decisively the ergodic threshold is crossed
Momentum Strength (0-25%): Rate of ergodic change
Volatility Alignment (0-20%): Whether volatility supports the signal
Market Quality (0-20%): Price convergence and path dependency factors
Real-Time Confidence Updates
The Live Confidence metric continuously updates, showing:
- Current opportunity quality
- Market state clarity
- Historical performance influence
- Signal recency boost
- Visual Intelligence System
Adaptive Ergodic Field Bands
Dynamic bands that expand and contract based on market state:
Primary Color: Ergodic state (mean-reverting)
Danger Color: Non-ergodic state (trending)
Band Width: Expected price movement range
Squeeze Indicators: Volatility compression warnings
Quantum Wave Ribbons
Triple EMA system (8, 21, 55) revealing market flow:
Compressed Ribbons: Consolidation imminent
Expanding Ribbons: Directional move developing
Color Coding: Matches current ergodic state
Phase Transition Signals
Clear entry/exit markers at regime changes:
Bull Signals: Ergodic restoration (mean reversion opportunity)
Bear Signals: Ergodic break (trend following opportunity)
Confidence Labels: Percentage showing signal quality
Visual Intensity: Stronger signals = deeper colors
Professional Dashboard Suite
Main Analytics Panel (Top Right)
Market State Monitor
- Current regime (Ergodic/Non-Ergodic)
- Ergodic score with threshold
- Path dependency strength
- Quantum coherence percentage
Divergence Metrics
- Price divergence with severity
- Volatility regime classification
- Strategy mode recommendation
- Signal strength indicator
Live Intelligence
- Real-time confidence score
- Color-coded risk levels
- Dynamic strategy suggestions
Performance Tracking (Left Panel)
Signal Analytics
- Total historical signals
- Win rate with W/L breakdown
- Current streak tracking
- Closed trade counter
Regime Analysis
- Current market behavior
- Bars since last signal
- Recommended actions
- Average confidence trends
Strategy Command Center (Bottom Right)
Adaptive Recommendations
- Active strategy mode
- Primary approach (mean reversion/momentum)
- Suggested indicators ("weapons")
- Entry/exit methodology
- Risk management guidance
- Comprehensive Input Guide
Core Algorithm Parameters
Analysis Period (10-100 bars)
Scalping (10-15): Ultra-responsive, more signals, higher noise
Day Trading (20-30): Balanced sensitivity and stability
Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes
Divergence Threshold (0.5-5.0)
Hair Trigger (0.5-1.0): Catches every wiggle, many false signals
Balanced (1.5-2.5): Good signal-to-noise ratio
Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance
Path Memory (20-200 bars)
Short Memory (20-50): Recent behavior focus, quick adaptation
Medium Memory (50-100): Balanced historical context
Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag
Signal Spacing (5-50 bars)
Aggressive (5-10): Allows rapid-fire signals
Normal (15-25): Prevents clustering, maintains flow
Conservative (30-50): Major setups only Default: 15 - optimal trade frequency
Ensemble Configuration
Select markets for consensus analysis:
SPY: Broad market sentiment
QQQ: Technology leadership
IWM: Small-cap risk appetite
DIA: Blue-chip stability
More instruments = stronger consensus but potentially diluted signals
Visual Customization
Color Themes (6 professional options):
Quantum: Cyan/Pink - Modern trading aesthetic
Matrix: Green/Red - Classic terminal look
Heat: Blue/Red - Temperature metaphor
Neon: Cyan/Magenta - High contrast
Ocean: Turquoise/Coral - Calming palette
Sunset: Red-orange/Teal - Warm gradients
Display Controls:
- Toggle each visual component
- Adjust transparency levels
- Scale dashboard text
- Show/hide confidence scores
- Trading Strategies by Market State
- Ergodic State Strategy (Primary Color Bands)
Market Characteristics
- Price oscillates predictably
- Support/resistance hold
- Volume patterns repeat
- Mean reversion dominates
Optimal Approach
Entry: Fade moves at band extremes
Target: Middle band (equilibrium)
Stop: Just beyond outer bands
Size: Full confidence-based position
Recommended Tools
- RSI for oversold/overbought
- Bollinger Bands for extremes
- Volume profile for levels
- Non-Ergodic State Strategy (Danger Color Bands)
Market Characteristics
- Price trends persistently
- Levels break decisively
- Volume confirms direction
- Momentum accelerates
Optimal Approach
Entry: Breakout from bands
Target: Trail with expanding bands
Stop: Inside opposite band
Size: Scale in with trend
Recommended Tools
- Moving average alignment
- ADX for trend strength
- MACD for momentum
- Advanced Features Explained
Quantum Coherence Metric
Measures phase alignment between individual and ensemble behavior:
80-100%: Perfect sync - strong mean reversion setup
50-80%: Moderate alignment - mixed signals
0-50%: Decoherence - trending behavior likely
Path Dependency Analysis
Quantifies how much history influences current price:
Low (<30%): Technical patterns reliable
Medium (30-50%): Mixed influences
High (>50%): Fundamental shift occurring
Volatility Regime Classification
Contextualizes current volatility:
Normal: Standard strategies apply
Elevated: Widen stops, reduce size
Extreme: Defensive mode required
Signal Strength Indicator
Real-time opportunity quality:
- Distance from threshold
- Momentum acceleration
- Cross-validation factors
Risk Management Framework
Position Sizing by Confidence
90%+ confidence = 100% position size
70-90% confidence = 75% position size
50-70% confidence = 50% position size
<50% confidence = 25% or skip
Dynamic Stop Placement
Ergodic State: ATR × 1.0 from entry
Non-Ergodic State: ATR × 2.0 from entry
Volatility Adjustment: Multiply by current regime
Multi-Timeframe Alignment
- Check higher timeframe regime
- Confirm ensemble consensus
- Verify volume participation
- Align with major levels
What Makes EMD Unique
Original Contributions
First Ergodic Theory Trading Application: Transforms abstract physics into practical signals
Ensemble Market Analysis: Revolutionary multi-market divergence system
Adaptive Confidence Engine: Institutional-grade signal quality metrics
Quantum Coherence: Novel market alignment measurement
Smart Signal Management: Prevents clustering while maintaining responsiveness
Technical Innovations
Dynamic Threshold Adaptation: Self-adjusting sensitivity
Path Memory Integration: Historical dependency weighting
Stress-Adjusted Scoring: Market condition normalization
Real-Time Performance Tracking: Built-in strategy analytics
Optimization Guidelines
By Timeframe
Scalping (1-5 min)
Period: 10-15
Threshold: 0.5-1.0
Memory: 20-30
Spacing: 5-10
Day Trading (5-60 min)
Period: 20-30
Threshold: 1.5-2.5
Memory: 40-60
Spacing: 15-20
Swing Trading (1H-1D)
Period: 40-60
Threshold: 2.0-3.0
Memory: 80-120
Spacing: 25-35
Position Trading (1D-1W)
Period: 60-100
Threshold: 3.0-5.0
Memory: 100-200
Spacing: 40-50
By Market Condition
Trending Markets
- Increase threshold
- Extend memory
- Focus on breaks
Ranging Markets
- Decrease threshold
- Shorten memory
- Focus on restores
Volatile Markets
- Increase spacing
- Raise confidence requirement
- Reduce position size
- Integration with Other Analysis
- Complementary Indicators
For Ergodic States
- RSI divergences
- Bollinger Band squeezes
- Volume profile nodes
- Support/resistance levels
For Non-Ergodic States
- Moving average ribbons
- Trend strength indicators
- Momentum oscillators
- Breakout patterns
- Fundamental Alignment
- Check economic calendar
- Monitor sector rotation
- Consider market themes
- Evaluate risk sentiment
Troubleshooting Guide
Too Many Signals:
- Increase threshold
- Extend signal spacing
- Raise confidence minimum
Missing Opportunities
- Decrease threshold
- Reduce signal spacing
- Check ensemble settings
Poor Win Rate
- Verify timeframe alignment
- Confirm volume participation
- Review risk management
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques.
Transform market chaos into trading clarity with Ergodic Market Divergence.
Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Walk Forward PatternsINTRO
In Euclidean geometry, every mathematical output has a planar projection. 'Walk Forward Patterns' can be considered a practical example of this concept. On the other hand, this indicator might also be viewed as an experiment in 'how playing with Lego as a child contributes to time series analysis' :)
OVERVIEW
This script dynamically generates the necessary optimization and testing ranges for Walk Forward Analysis based on user-defined bar count and length inputs. It performs automatic calculations for each step, offers 8 different window options depending on the inputs, and visualizes the results dynamically. I should also note that most of the window models consist of original patterns I have created.
ADDITIONAL INFO : WHAT IS WALK FORWARD ANALYSIS?
Although it is not the main focus of this indicator, providing a brief definition of Walk Forward Analysis can be helpful in correctly interpreting the results it generates. Walk Forward Analysis (WFA) is a systematic method for optimizing parameters and validating trading strategies. It involves dividing historical data into variable segments, where a strategy is first optimized on an in-sample period and then tested on an out-of-sample period. This process repeats by shifting the windows forward, ensuring that each test evaluates the strategy on unseen data, helping to assess its robustness and adaptability in real market conditions.
ORIGINALITY
There are very few studies on Walk Forward Analysis in TradingView. Even worse, there are no any open-source studies available. Someone has to start somewhere, I suppose. And in my personal opinion, determining the optimization and backtest intervals is the most challenging part of WFA. These intervals serve as a prerequisite for automated parameter optimization. I felt the need to publish this pattern module, which I use in my own WFA models, partly due to this gap on community scripts.
INDICATOR MECHANICS
To use the indicator effectively, you only need to perform four simple tasks:
Specify the total number of bars in your chart in the 'Bar Index' parameter.
Define the optimization (In-Sample Test) length.
Define the testing (Out-Of-Sample Test) length.
Finally, select the window type.
The indicator automatically models everything else (including the number of steps) based on your inputs. And the result; you now have a clear idea of which bars to use for your Walk Forward tests!
A COMMONLY USED WINDOW SELECTION METHOD: ROLLING
A more concrete definition of Walk Forward Analysis, specifically for the widely used Rolling method, can be described as follows:
Parameters that have performed well over a certain period are identified (Optimization: In-Sample).
These parameters are then tested on a shorter, subsequent period (Backtest: Out-of-Sample).
The process is repeated forward in time (At each step, the optimization and backtest periods are shifted by the backtest length).
If the cumulative percentage profit obtained from the backtest results is greater than half of the historical optimization profit, the strategy is considered "successful."
If the strategy is successful, the most recent (untested) optimization values are used for live trading.
OTHER WINDOW OPTIONS
ANCHORED: That's a pattern based on progressively expanding optimization ranges at each step. Backtest ranges move forward in a staircase-like manner.
STATIC: Optimization ranges remain fixed, while backtest ranges are shifted forward.
BLOCKED: Optimization ranges are shifted forward in groups of three blocks. Backtest ranges are also shifted in a staircase manner, even at the cost of creating gaps from the optimization end bars.
TRIANGULAR: Optimization ranges are shifted forward in triangular regions, while backtest ranges move in a staircase pattern.
RATIO: The optimization length increases by 25% of the initial step’s fixed length at each step. In other words, the length grows by 25% of the first step's length incrementally. Backtest ranges always start from the bar where the optimization ends.
FIBONACCI: A variation of the Ratio method, where the optimization shift factor is set to 0.618
RANDOM WALK
Unlike the window models explained above, we can also generate optimization and backtest ranges completely randomly—offering almost unlimited variations! When you select the "Random" option in the "Window" parameter on the indicator interface, random intervals are generated based on various trigonometric calculations. By changing the numerical value in the '🐒' parameter, you can create entirely unique patterns.
WHY THE 🐒 EMOJI?
Two reasons.
First, I think that as humanity, we are a species of tailless primates who become happy when we understand things :). At least evolutionarily. The entire history of civilization is built on the effort to express the universe in a scale we can comprehend. 'Knowledge' is an invention born from this effort, which is why we feel happiness when we 'understand'. Second, I can't think of a better metaphor for randomness than a monkey sitting at a keyboard. See: Monkey Test.
Anyway, I’m rambling :)
NOTES
The indicator generates results for up to 100 steps. As the number of steps increases, the table may extend beyond the screen—don’t forget to zoom out!
FINAL WORDS
I haven’t published a Walk Forward script yet . However, there seem to be examples that can perform parameter optimization in the true sense of the word, producing more realistic results without falling into overfitting in my library. Hopefully, I’ll have the chance to publish one in the coming weeks. Sincerely thanks to Kıvanç Özbilgiç, Robert Pardo, Kevin Davey, Ernest P. Chan for their inspiring publishments.
DISCLAIMER
That's just a script, nothing more. I hope it helps everyone. Do not forget to manage your risk. And trade as safely as possible. Best of luck!
© dg_factor
MMRI Chart (Primary)The **Mannarino Market Risk Indicator (MMRI)** is a financial risk measurement tool created by financial strategist Gregory Mannarino. It’s designed to assess the risk level in the stock market and economy based on current bond market conditions and the strength of the U.S. dollar. The MMRI considers factors like the U.S. 10-Year Treasury Yield and the Dollar Index (DXY), which indicate investor confidence in government debt and the dollar's purchasing power, respectively.
The formula for MMRI uses the 10-Year Treasury Yield multiplied by the Dollar Index, divided by a constant (1.61) to normalize the risk measure. A higher MMRI score suggests increased market risk, while a lower score indicates more stability. Mannarino has set certain thresholds to interpret the MMRI score:
- **Below 100**: Low risk.
- **100–200**: Moderate risk.
- **200–300**: High risk.
- **Above 300**: Extreme risk, indicating market instability and potential downturns.
This tool aims to provide insight into economic conditions that may affect asset classes like stocks, bonds, and precious metals. Mannarino often updates MMRI scores and risk analyses in his public market updates.
[Pandora] Error Function Treasure Trove - ERF/ERFI/Sigmoids+PRAISE:
At this time, I have to graciously thank the wonderful minds behind the new "Pine Profiler Mode" (PPM). Directly prior to this release, it allowed me to ascertain script performance even more. While I usually write mostly in highly optimized Pine code, PPM visually identified a few bottlenecks that would otherwise be hard to identify. Anyone who contributed to PPMs creation and testing before release... BRAVO!!! I commend all of those who assisted in it's state-of-the-art engineering and inception, well done!
BACKSTORY:
This script is specifically being released in defense of another member, an exceptionally unique PhD. It was brought to my attention that a script-mod-event occurred, regarding the publishing of a measly antiquated error function (ERF) calculation within his script. This sadly resulted in the now former member jumping ship after receiving unmannerly responses amidst his curious inquiries as to why his erf() was modded. To forbid rusty and rudimentary formulations because a mod-on-duty is temporally offended by a non-nefarious release of code, is in MY opinion an injustice to principles of perpetuating open-source code intended to benefit thousands to millions of community members. While Pine is the heart and soul of TV, the mathematical concepts contributed from the minds of members is the inspirational fuel of curiosity that powers it's pertinent reason to exist and evolve.
It is an indisputable fact that most members are not greatly skilled Pine Poets. Many members may be incapable of innovating robust function code in Pine, even if they have one or more PhDs. We ALL come from various disciplines of mathematical comprehension and education. Some mathematicians are not greatly skilled at coding, while some coders are not exceptional at math. So... what am I to do to attempt to resolve this circumstantial challenge??? Those who know me best are aware that I will always side with "the right side of history" in order to accomplish my primary self-defined missions I choose to accept. Serving as an algorithmic advocate, I felt compelled to intercede by compiling numerous error functions into elegant code of very high caliber that any and every TV member may choose to employ, so this ERROR never happens again.
After weeks of contemplation into algorithms I knew little about, I prioritized myself to resolve an unanticipated matter by creating advanced formulas of exquisitely crafted error functions refined to the best of my current abilities. My aversion for unresolved problems motivated me to eviscerate error function insufficiencies with many more rigid formulations beyond what is thought to exist. ERF needed a proper algorithmic exorcism anyways. In my furiosity, I contemplated an array of madMAXimum diplomatic demolition methods, choosing the chain saw massacre technique to slaughter dysfunctionalities I encountered on a battered ERF roadway. This resulted in prolific solutions that should assuredly endure the test of time. Poetically, as you will come to see, I am ripping the lid off of Pandora's box of error functions in this case to correct wrongs into a splendid bundle of rights for members.
INTENTION:
Error function (ERF) enthusiasts... PREPARE FOR GLORY!! The specific purpose of this script is to deprecate classic error functions with the creation of a fierce and formidable army of superior formulations, each having varying attributes of computational complexity with differing absolute error ranges in their results for multiple compute scenarios. This is NOT an indicator... It is intended to allow members to embark on endeavors to advance the profound knowledge base of this growing worldwide community of 60+ million inquisitive minds. For those of you who believe computational mathematics and statistics is near completion at its finest; I am here to inform you, this is ridiculous to ponder. We are no where near statistical excellence that can and will exist eventually. At this time, metaphorically speaking, we are merely scratching microns off of the surface of the skin of a statistical apple Isaac Newton once pondered.
THIS RELEASE:
Following weeks of pondering methodical experiments beyond the ordinary, I am liberating these wild notions of my error function explorations to the entire globe as copyleft code, not just Pine. This Pandora's basket of ERFs is being openly disclosed for the sake of the sanctity of mathematics, empirical science (not the garbage we are told by CONTROLocrats to blindly trust), revolutionary cutting edge engineering, cosmology, physics, information technology, artificial intelligence, and EVERY other mathematical branch of human knowledge being discovered over centuries. I do believe James Glaisher would favor my aims concerning ERF aspirations embracing the "Power of Pine".
The included functions are intended for TV members to use in any way they see fit. This is a gift to ALL members to foster future innovative excellence on this platform. Any attempt to moderate this code without notification of "self-evident clear and just cause" will be considered an irrevocable egregious action. The original foundational PURPOSE of establishing script moderation (I clearly remember) was primarily to maintain active vigilance over a growing community against intentional nefarious actions and/or behaviors in blatant disrespect to other author's works AND also thwart rampant copypasting bandit operations, all while accommodating balanced principles of fairness for an educational community cause via open source publishing that should support future algorithmic inventions well beyond my lifespan.
APPLICATIONS:
The related error functions are used in probability theory, statistics, and numerous and engineering scientific disciplines. Its key characteristics and applications are innumerable in computational realms. Its versatility and significance make it a fundamental tool in arenas of quantitative analysis and scientific research...
Probability Theory - Is widely used in probability theory to calculate probabilities and quantiles of the normal distribution.
Statistics - It's related to the Gaussian integral and plays a crucial role in statistics, especially in hypothesis testing and confidence interval calculations.
Physics - In physics, it arises in the study of diffusion equations, quantum mechanics, and heat conduction problems.
Engineering - Applications exist in engineering disciplines such as signal processing, control theory, and telecommunications.
Error Analysis - It's employed in error analysis and uncertainty quantification.
Numeric Approximations - Due to its lack of a closed-form expression, numerical methods are often employed to approximate erf/erfi().
AI, LLMs, & MACHINE LEARNING:
The error function (ERF) is indispensable to various AI applications, particularly due to its relation to Gaussian distributions and error analysis. It is used in Gaussian processes for regression and classification, probabilistic inference for Bayesian networks, soft margin computation in SVMs, neural networks involving Gaussian activation functions or noise, and clustering algorithms like Gaussian Mixture Models. Improved ERF approximations can enhance precision in these applications, reduce computational complexity, handle outliers and noise better, and improve optimization and convergence, possibly leading to more accurate, efficient, and robust AI systems.
BONUS ALGORITHMS:
While ERFs are versatile, its opposite also exists in the form of inverse error functions (ERFIs). I have also included a modified form of the inverse fisher transform along side MY sigmoid (sigmyod). I am uncertain what sigmyod() may be used for, but it's a culmination of my examinations deep into "sigmoid domains", something I am fascinated by. Whatever implications it may possess, I am unveiling it along with it's cousin functions. For curious minds, this quality of composition seen here is ideally what underlies what I would term "Pandora functionality" that empowers my Pandora indication. I go through hordes of formulations, testing, and inspection to find what appears to be the most beneficial logical/mathematical equation to apply...
SCRIPT OPERATION:
To showcase the characteristics and performance of my ERF/ERFI formulations, I devised a multi-modal script. By using bar_index , I generated a broad sequence of numeric values to input into the first ERF/ERFI parameter. These sequences allow you to inspect the contours of the error function's outputs for both ERF and ERFI. When combined with compute-intensive precision functions (CIPFs), the polynomial function output values can be subtracted from my CIPFs to obtain results of absolute error, displaying the accuracy of the many polynomial estimation functions I tuned in testing for Pine's float environment.
A host of numeric input settings are wildly adjustable to inspect values/curvatures across the range of numeric input sequences. Very large numbers, such as Divisor:100,000,100/Offset:200,000,000 for ERF modes or... Divisor:100,000,100/Offset:100,000,000 for ERFI modes, will display miniscule output values calculated from input values in close proximity to 0.0 for the various estimates, similar to a microscope. ERFI approximations very near in proximity to +/-1.0 will always yield large deviations of absolute error. Dragging/zooming your chart or using the Offset input will aid with visually clipping off those ERFI extremes where float precision functions cannot suffice.
NOTICE:
perf() and perfi() are intended for precision computation (as good as it basically gets) in a float environment. However, they are CPU intensive (especially perfi). I wouldn't recommend these being used in ANY Pine script unless it's an "absolute necessity" to do so to accomplish your goal. I only built them to obtain "absolute error curvatures" of the error functions for the polynomial approximations. These are visible in the accuracy modes in the indicator Settings.
Price SextantThe provided Pine Script™ code is for a technical analysis indicator called "Price Sextant." This indicator helps visualize the price position relative to its linear regression and standard deviation levels. Here's a brief description:
Price Sextant Indicator:
Purpose:
The Price Sextant indicator aims to show the current price's deviation from the linear regression line by dividing the price chart into different zones or sextants.
Components:
Linear Regression: The script calculates a linear regression line based on the closing prices over a specified length (default is 50 bars).
Standard Deviation Sections: It then computes standard deviation levels from the linear regression, creating upper and lower sections around the regression line.
Scoring: Each section is assigned a numerical score, and labels with corresponding scores are displayed on the chart.
Arrow and Midline: An arrow is drawn to indicate the current price's position in relation to the regression line and standard deviation bands. It changes color based in what section it is:
orange section shows a ranging price, below orange section -1 arrow turns red and show down trend and if arrow above +1 section it turns green and show strong up trend of price.
A midline is plotted to mark the position of the linear regression line.
Sextant Description:
In navigation, a sextant is an instrument used to measure the angle between two visible objects.
In the context of this indicator, the term "Sextant" is likely used metaphorically to describe the division of the price chart into six sections or zones based on the linear regression and standard deviation bands.
This indicator can help traders identify potential overbought or oversold conditions, as well as assess the strength and direction of the trend.
Please note that the effectiveness of the indicator depends on various factors, and it's advisable to use it in conjunction with other analysis tools for a comprehensive trading strategy.
[blackcat] L1 Volatility Quality Index (VQI)The Volatility Quality Index (VQI) is an indicator used to measure the quality of market volatility. Volatility refers to the extent of price changes in the market. VQI helps traders assess market stability and risk levels by analyzing price volatility. This introduction may be a bit abstract, so let me help you understand it with a comparative metaphor if you're not immersed in various technical indicators.
Imagine you are playing a jump rope game, and you notice that sometimes the rope moves fast and other times it moves slowly. This is volatility, which describes the speed of the rope. VQI is like an instrument specifically designed to measure rope speed. It observes the movement of the rope and provides a numerical value indicating how fast or slow it is moving. This value can help you determine both the stability of the rope and your difficulty level in jumping over it. With this information, you know when to start jumping and when to wait while skipping rope.
In trading, VQI works similarly. It observes market price volatility and provides a numerical value indicating market stability and risk levels for traders. If VQI has a high value, it means there is significant market volatility with relatively higher risks involved. Conversely, if VQI has a low value, it indicates lower market volatility with relatively lower risks involved as well. The calculation involves dividing the range by values obtained from calculating Average True Range (ATR) multiplied by a factor/multiple.
The purpose of VQI is to assist traders in evaluating the quality of market volatility so they can develop better trading strategies accordingly.
Therefore, VQI helps traders understand the quality of market volatility for better strategy formulation and risk management—just like adjusting your jumping style based on rope speed during jump-rope games; traders can adjust their trading decisions based on VQI values.
The calculation of VQI indicator depends on given period length and multiple factors: Period length is used to calculate Average True Range (ATR), while the multiple factor adjusts the range of volatility. By dividing the range by values and multiplying it with a multiple, VQI numerical value can be obtained.
VQI indicator is typically presented in the form of a histogram on price charts. Higher VQI values indicate better quality of market volatility, while lower values suggest poorer quality of volatility. Traders can use VQI values to assess the strength and reliability of market volatility, enabling them to make wiser trading decisions.
It should be noted that VQI is just an auxiliary indicator; traders should consider other technical indicators and market conditions comprehensively when making decisions. Additionally, parameter settings for VQI can also be adjusted and optimized based on individual trading preferences and market characteristics.
Ratio Smoothed, Volume Weighted Moving AverageThis is experimental moving average doesn't use a period/length but instead buffers the price per share and transfers that price per share at a given ratio per bar while also releasing the previous values at a decay ratio.
The idea is that volume is the engine by which the price moves but spikes in volume can cause noise. By having a buffer of price per share units, this VWMA style indicator can behave more like a WMA combined with volume (VAWMA) but smooths out the noise of recent volume. The end result is a price movement that is smooth but also still based strongly up on the average price per share and will always eventually catch up to the true price per share value.
A metaphor to understand this could be a bucket with a hole in it where water is flowing sporadically into the bucket. The level of water in the bucket may change drastically but instead of all the water emptying out immediately, it is throttled by the hole in the bottom. As the level rises, the water pressure increases and the flow increases so that the virtual bucket never has a chance to fill up but also never really empties either.
Financial MetricsGives a sneak peak into some of the important financial ratios described below:
1. P/E : price to earnings ratio (Green when P/E<15)
2. PEG: Price to earnings growth ratio (Green when PEG<1)
3. P/S: Price to sales ratio (Green when P/S<2)
4. EV/FCF: Enterprise Value to Free Cashflow ratio
5. OPM: Operating Profit Margin % (Green when OPM>15%)
6. D/E: Debt to equity ratio (Green when D/E<1)
7. ROE: Return on equity % (Green when ROE>15%)
8. Div_Yield: Dividend yield
Disclaimer: All the limits defined are based on the widely accepted general values, but are subjective to particular sector or group of stocks. For example IT stocks command higher valuation than cyclical stocks like metal. So Compare with other stocks of the same sector to reach any conclusion.
Heat Zone Relative Volatility Index 2.0v2 of Heat Zone RVI
• Updated aesthetics and added various alerts.
• The use of temperature descriptions with these Heat Zone scripts is more so metaphoric of the interpretations from what the RVI attempts to indicate primarily.
--- Due to the additions of the Overheated and Freezing Zones , the indicator-pane scaling is a little different from the original Heat Zone RVI .
Ex.)
--- If you like the scaling the way it was on v1, you can change it back by going into the settings , opening up the style page, and unchecking/turning off the Overheated Top Line as well as the Freezing Bottom Line . Otherwise, you can leave the settings be in regards to this matter.
Ex.)
Disclaimer : I am by no means a highly skilled or professional coder/programmer. I just enjoy dabbling and tinkering every now and again.
HOPE YOU ENJOY
Combo Backtest 123 Reversal & Awesome Oscillator (AO) This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator is based on Bill Williams` recommendations from his book
"New Trading Dimensions". We recommend this book to you as most useful reading.
The wisdom, technical expertise, and skillful teaching style of Williams make
it a truly revolutionary-level source. A must-have new book for stock and
commodity traders.
The 1st 2 chapters are somewhat of ramble where the author describes the
"metaphysics" of trading. Still some good ideas are offered. The book references
chaos theory, and leaves it up to the reader to believe whether "supercomputers"
were used in formulating the various trading methods (the author wants to come across
as an applied mathemetician, but he sure looks like a stock trader). There isn't any
obvious connection with Chaos Theory - despite of the weak link between the title and
content, the trading methodologies do work. Most readers think the author's systems to
be a perfect filter and trigger for a short term trading system. He states a goal of
10%/month, but when these filters & axioms are correctly combined with a good momentum
system, much more is a probable result.
There's better written & more informative books out there for less money, but this author
does have the "Holy Grail" of stock trading. A set of filters, axioms, and methods which are
the "missing link" for any trading system which is based upon conventional indicators.
This indicator plots the oscillator as a histogram where periods fit for buying are marked
as blue, and periods fit for selling as red. If the current value of AC (Awesome Oscillator)
is over the previous, the period is deemed fit for buying and the indicator is marked blue.
If the AC values is not over the previous, the period is deemed fir for selling and the indicator
is marked red.
WARNING:
- For purpose educate only
- This script to change bars colors.
Exploring UnicodeThis script demonstrates how to display Unicode characters and symbols, including emoji, in Pine:
• Part 1 displays multi-line labels on hi/lo pivots.
• Part 2 displays price/volume bumps using small up/down arrows plotted with plotchar() .
• Part 3 detects bounces and uses plotshape() to mark them.
You can use our `f_bounceFrom()` function from this part as confirmation for signals in your strategies.
Note that the labels displayed on pivots with the code in Part 1 are plotted in the past. In realtime, they would only appear where they are after 50 bars have elapsed from that point. The other plots are plotted on the bar where their conditions are detected.
You can display thousands of Unicode characters and symbols using Pine. As you can see with our script, it is very easy to do so. The challenge will often be to find the exact symbols you are looking for. Many websites exist to help you explore Unicode characters or symbols. The PineCoders Resources page contains a section presenting a few of them.
Duyck has a Unicode font function script containing functions to convert strings to monospaced Unicode representations. TradingView uses the Trebuchet font for most of its text, including text displayed with Pine scripts. While its numerals are monospace and will align vertically in labels text, Duyck's functions will be handy when you need to convert characters to a monospaced form, so they also align vertically in multi-line labels.
What is Unicode?
Unicode is to character encoding what Wikipedia is to knowledge; it holds codes to a good proportion of the characters or symbols used by humans, past or present. In the early days of computing, environments from different manufacturers often used different character encoding schemes, making transport between them difficult. Unicode solves that challenge. It is a comprehensive encoding scheme that visionaries from Xerox and Apple came up with in the late 80's. The addition of members from the Research Libraries Group, Sun Microsystems, Microsoft, Next and Metaphor created the "Unicode working group" and later, the Unicode Consortium , which continues to improve and manage the Unicode standard.
Theoretically, Unicode encodes values representing characters or glyphs —not their pictorial representations. The letters "A" or "a", or the blue heart emoji "💙" are each represented by a Unicode value. In practice, however, there are many different versions of the Latin alphabet in Unicode. That is how our low pivot label can display different representations of the letters "ITV". The exact rendition of Unicode symbols on a specific device is left to equipment manufacturers and typeface designers.
The current Unicode space is comprised of 17 planes of 65,536 characters each, which allows for more than one million code points . Planes are further divided into character blocks , which typically hold a character set corresponding to one script—or language. Emoticons are in the character block starting at U+1F600.
Look first. Then leap.
AlignedMA and Cumulative HighLow StrategyCombining the indicators:
1. Aligned Moving Average Index :
2. Cumulative High Low Index :
3. Supertrend
Works best in long only for crypto and precious metals.
My scenario is to present how much you can earn by investing 1000 for full 10 years. Hence, I am using fixed 1000 initial deposit and 100% equity per trade without any pyramiding. This allows us to compare gains to buy and hold.