Rebound V-Fib RT CloserRebound V-Fib RT Closer
The price-axis mirror of Rebound V-Fib RT for normal (linear) price charts. It detects an inverted-V peak (run-up then breakdown), draws the slanted V-Fib, resistance line, V-Ladder and baseball closer, marks trend entries, and exposes trend/resistance readouts - fast enough for second-scale charts and the Pine Screener.
For US equities on intraday/daily timeframes. Adjust 'Trading hours per day' for other markets (default 6.5).
Drawing-focused: there is no back-test, technical rating, resistance/exit signal, trailing stop, or lower-timeframe request. Trend geometry and rates update every bar; resistance detection and all drawing run on the last bar. Signals and drawings update on the live bar and confirm at close (they repaint intrabar) - for confirmed-only entry alerts, choose "Once Per Bar Close".
DIFFERENCES FROM Rebound V-Fib RT
Mirrors the whole detection in price: an inverted-V peak instead of a V-bottom, a breakdown leg instead of a rebound, a resistance ceiling instead of a support floor, and Fib targets projected downward
The trend entry is shown as a single entry-bar background tint (red) plus an alert, computed from the live bar's rates / V-Fib / lead
Inputs keep their positive magnitudes; the breakdown direction lives in the comparison signs (breakdown rate is negative, prior run-up rate is positive)
OUTPUTS
Overlay:
Slanted Fib band (multi-colored levels), red breakdown line, purple resistance diagonal
V-Ladder - purple key levels (0.236 / 0.5 / 1.0 / 1.618 / 2.272 / 3.0) between the previous and current resistance
Baseball closer - emoji below the first bar that reached each V-Ladder level
V-Fib Ratio label on the last bar
Entry-bar background tint (red) when a trend entry is marked
Status line + Data Window + Screener:
V-Fib - current V-Fib Ratio (how far price has dropped down the slanted Fib band; the value equals the Fib level number)
V-Trend - net rate (breakdown + run-up), %/day
Sup%/d - resistance slope, %/day
Data Window + Screener:
Age - bars since the current trend entry (0 when not in a setup). Recommended Pine Screener filter: Age 1 ~ 7
SupAge - days since the current resistance line was established
SupLead% - close below resistance, as % of close (negative)
Lead% - leading days x breakdown rate. Negative means price is leading the breakdown below the downtrend baseline
Up%/d, Down%/d - trend slopes, %/day (Up%/d is the active breakdown leg, negative; Down%/d is the prior run-up, positive)
Note: Pine Screener is limited to 500 bars of history; the resistance readouts (SupAge, Sup%/d, SupLead%) are computed on the last bar only.
INPUTS
General:
Lookback bars - inverted-V detection window
Trading hours per day - intraday day-to-bar conversion for the %/day readouts (6.5 = US equities)
Trend detection:
Min run-up bars / Min breakdown bars - minimum bars from bottom to peak / from peak to now
Trend entry:
Min breakdown rate - reject if breakdown slope magnitude is below this (%/day)
Run-up rate limit - constrains the prior run-up; default 0 requires run-up >= 0, more negative requires a steeper run-up
Min V-Trend - reject unless breakdown + run-up rate clears the gate
Min / Max entry V-Fib - lower / upper bound of the entry window on the slanted Fib band
Min entry leading drop - minimum leading drop required at entry
Unlock V-Fib - re-arm the entry once V-Fib drops past this (one signal per setup)
Display:
Show baseball closer - toggle the V-Ladder emoji
Show trend entry - toggle the entry-bar background tint
DISCLAIMER
This script is provided "AS IS" without warranty of any kind. It is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results. The author is not liable for any losses arising from the use of this script. Trade at your own risk.
Indicator
Markowitz Frontier Compass [JOAT]Markowitz Frontier Compass
Introduction
Markowitz Frontier Compass compares the chart symbol against a peer basket using inverse-volatility weights, correlation drag, diversification benefit, factor scores, and active risk budget.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Inverse-Volatility Basket
Each peer receives an inverse-volatility weight to form a portfolio-context benchmark.
2. Correlation Drag
Average pairwise correlation reduces diversification value when assets move together.
3. Factor Composite
Quality, momentum, low-volatility, and carry-style behavior are combined.
4. Risk Budget
Institutional grade, entropy, concentration, and factor state become active or defensive budget context.
frontierScore = efficiency + diversification - correlationDrag - concentration
Features
Peer basket context
Inverse-volatility weighting
Correlation drag and diversification benefit
Factor composite and allocation entropy
Risk-on, defense, and factor-prime states
Input Parameters
Peer symbols
Return window and smoothing
Risk-free annual percent
Correlation stress and concentration gates
Display toggles and HUD position
How to Use This Script
Use MFC as cross-asset context. Risk-on or factor-prime states suggest constructive basket behavior; defense states warn of stress.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
MFC is original in combining portfolio theory, factor scoring, entropy, and risk-budget logic in one open-source study.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
AG Pro Reversal Pattern Quality Scanner [AGPro Series]AG Pro Reversal Pattern Quality Scanner
Overview / What it does
AG Pro Reversal Pattern Quality Scanner is an overlay tool designed to detect and visualize selected classical reversal structures directly on the chart while adding a structured quality layer to each valid setup. The script focuses on four widely recognized reversal formations: Double Top, Double Bottom, Head & Shoulders, and Inverse Head & Shoulders.
Instead of marking every possible structural resemblance, the script applies a filtered detection workflow based on pivot structure, pattern width, peak or trough equality, pullback depth, neckline logic, and an internal quality model. The goal is not simply to identify a shape, but to highlight formations that display more balanced structure and more usable context.
Each detected pattern can be displayed with a pattern box, a projected neckline, and a quality label that summarizes the pattern type, directional bias, quality score, and grade. This makes the script suitable for traders who want a structured visual map of potential reversal zones rather than a raw pattern-highlighting tool with no ranking logic.
The indicator is built for chart reading and workflow support. It does not attempt to forecast future price movement with certainty, and it should not be interpreted as a standalone trade system. Its role is to help users organize reversal structures, compare them visually, and focus on higher-quality formations when reviewing price action.
Unique Edge
The main distinction of this script is that it does not treat all reversal patterns as equivalent. A detected pattern is further evaluated through a composite quality framework that considers structural symmetry, pullback depth, and volume behavior during formation and break conditions.
For Double Top and Double Bottom structures, the script checks whether the two peaks or troughs remain sufficiently close to each other within a defined tolerance and whether the intermediate pullback is large enough to make the structure meaningful. For Head & Shoulders and Inverse Head & Shoulders structures, the script evaluates shoulder symmetry, time symmetry, and relative positioning of the head against the shoulders.
The volume component is not used as a promise of confirmation. It is used as an additional contextual factor inside the quality score. In general terms, contracting volume during formation and stronger participation during the break candidate can improve the overall score when those conditions are present.
Another important part of the design is visual prioritization. The script does not only draw the structure. It also attempts to keep the chart readable by organizing labels, neckline extensions, and pattern boxes in a way that preserves interpretation. The result is a cleaner reversal-pattern map that aims to be more practical than a simple shape detector.
Methodology
The script begins with swing pivot detection. These pivots act as the structural foundation for all pattern candidates. Once enough pivot highs and lows are available, the script evaluates whether recent pivot sequences fit the requirements of one of the supported reversal structures.
For Double Top detection, the script checks whether two recent highs are similar enough, whether the interim low forms a valid neckline reference, whether the pattern width stays within defined limits, and whether price has broken below the neckline. For Double Bottom detection, the logic is mirrored on the bullish side through two similar lows, an interim high as the neckline reference, and a bullish break condition above that neckline.
For Head & Shoulders detection, the script evaluates a sequence of three pivot highs where the middle high must exceed the two shoulders. It then estimates neckline structure from the lows between those highs and applies symmetry and pullback checks before accepting the setup. Inverse Head & Shoulders applies the same structural concept in reverse using pivot lows.
After a valid break condition is detected, the script calculates a composite quality score. This score is based on user-controlled weights for volume behavior, symmetry, and pullback depth. The final output is normalized into a 1 to 10 quality scale, then translated into a grade label for easier scanning.
Signals & Alerts
The script can generate pattern-based alert conditions for:
- Double Top
- Double Bottom
- Head & Shoulders
- Inverse Head & Shoulders
These alerts are tied to the script’s internal structural conditions and neckline break logic. As with any chart-based alert workflow, users should confirm that the selected settings match their market, timeframe, and execution style.
Visual output can include:
- Pattern boxes
- Neckline lines
- Neckline labels
- Pattern quality labels
- Break candle highlighting
- Information panel with detection statistics
The quality label is intended to summarize the detected structure, not to guarantee outcome quality. A higher score means the pattern aligned more closely with the script’s internal criteria. It does not mean the setup must succeed.
Key Inputs
The script includes adjustable inputs for both detection behavior and presentation. Key controls include:
- Swing Pivot Length
- Peak / Trough Equality tolerance
- Minimum Pullback Between Peaks or Troughs
- Minimum and Maximum Pattern Width
- Minimum Quality to Display
- Weighting of volume, symmetry, and pullback depth inside the quality score
- Box, neckline, and pattern-label visibility
- Global label size
- Panel font size
- Panel position
- Neckline extension length
- Pattern-specific alert toggles
These controls make it possible to adapt the scanner to different chart densities, volatility profiles, and personal visual preferences.
Limitations & Transparency
This indicator is a rule-based pattern scanner. It is not a predictive engine, and it does not claim that all detected formations will lead to continuation or reversal. Classical chart structures can fail, invalidate, or behave differently depending on volatility, trend strength, liquidity conditions, timeframe, and broader market context.
Pattern recognition on live charts is inherently sensitive to pivot settings and bar structure. Small changes in pivot length, equality tolerance, or minimum pullback can materially change how many formations appear. Because of that, users should treat the script as a configurable analytical framework rather than a universal template.
The quality score is an internal ranking model built from the script’s own criteria. It is meant to help compare setups inside the same framework. It should not be interpreted as an objective probability model, a performance promise, or a substitute for independent trade management.
Volume analysis also depends on the reliability and characteristics of the symbol’s reported data. On some instruments, volume may be less informative or behave differently than expected. Users should evaluate this in the context of their own market.
Risk Disclosure
This script is provided for chart analysis, workflow organization, and educational use. It does not provide financial advice, investment advice, or guaranteed trade signals. All trading and investment decisions remain the sole responsibility of the user.
Reversal patterns can fail even when they appear clean and well-structured. Breaks can reverse, neckline moves can trap participants, and high-scoring formations can still underperform. Risk management, confirmation process, position sizing, and overall strategy design remain essential.
Use this tool as a structured visual aid inside a broader decision-making process, not as a standalone reason to enter or exit a position. Indicator
Gold Inverse Correlation TrackerGold Inverse Correlation Tracker - Professional Multi-Asset Analysis
What This Indicator Does:
This indicator monitors the real-time correlation between Gold and five key financial assets that historically move inversely (opposite) to gold prices. It displays these relationships across three different timeframes simultaneously, giving you both short-term trading signals and long-term trend confirmation.
The indicator tracks:
US Dollar Index (DXY) - Historical correlation: -0.63
Real Interest Rates (TIPS) - Historical correlation: -0.82 (strongest inverse relationship)
10-Year Treasury Yield - Nominal interest rate proxy
S&P 500 (SPX) - Equity market sentiment (variable correlation)
VIX - Volatility index (optional, flight-to-safety indicator)
Why Inverse Correlations Matter for Gold Trading:
Understanding inverse correlations is critical for gold traders because:
Predictive Power - When assets move opposite to gold consistently, you can use their strength/weakness to predict gold's next move
Hedging Opportunities - Strong inverse correlations let you hedge gold positions by trading the inverse asset
Regime Detection - When correlations break down, it signals a market regime change or increased uncertainty
Confirmation Signals - Multiple strong inverse correlations validate your gold trade thesis
Risk Management - Knowing what moves against gold helps you understand your portfolio's true exposure
The Science Behind the Numbers:
Real interest rates have the strongest inverse correlation to gold (approximately -0.82) because:
Gold pays no yield or dividend
When real rates rise, the opportunity cost of holding gold increases
Investors shift to interest-bearing assets when they offer positive real returns
When real rates go negative, gold becomes relatively more attractive
The US Dollar shows strong inverse correlation (approximately -0.63) because:
Gold is priced in US dollars globally
A stronger dollar makes gold more expensive for foreign buyers, reducing demand
A weaker dollar makes gold cheaper internationally, increasing demand
Both compete as reserve assets and stores of value
Why the Indicator is Weighted This Way:
Three Timeframe Approach:
Short-term (20 periods) - Captures recent correlation shifts for day trading and swing trading
Medium-term (50 periods) - The primary signal - balances noise reduction with responsiveness
Long-term (100 periods) - Confirms structural correlation trends for position trading
Correlation Thresholds:
Strong Inverse (<-0.7) - Statistically significant inverse relationship; highest confidence for inverse trades
Moderate Inverse (<-0.3) - Meaningful inverse relationship; still useful but less reliable
Weak Inverse (<0.0) - Slight inverse tendency; correlation may be breaking down
Positive (>0.0) - Assets moving together; inverse relationship has failed
How to Use This Indicator:
For Inverse Trading Strategies:
When DXY shows RED correlation (<-0.7), consider shorting DXY when gold is strong
When Real Rates show RED correlation, rising rates = falling gold (and vice versa)
When multiple assets show strong inverse correlation, confidence is highest
For Regime Detection:
All RED = Classic gold market behavior; correlations intact
Mixed colors = Transitional market; be cautious
All GREEN/GRAY = Correlation breakdown; paradigm shift occurring
For Hedging:
Use assets with strong inverse correlation to hedge gold positions
When correlation weakens, reduce hedge size
When correlation strengthens, increase hedge effectiveness
Alert System:
The indicator includes built-in alerts for:
Individual assets crossing strong inverse threshold
Multiple assets simultaneously showing strong inverse correlation (highest probability setup)
Correlation breakdowns that may signal regime changes
Color Guide:
RED - Strong inverse correlation (<-0.7) - Best inverse trading opportunity
ORANGE - Moderate inverse (<-0.3) - Useful but less reliable
YELLOW - Weak inverse (<0.0) - Correlation weakening
GRAY - Weak positive (0.0 to 0.7) - Assets moving together
GREEN - Strong positive (>0.7) - Inverse relationship broken
Recommended Settings:
Day Trading (1H-4H charts):
Short: 14 periods
Medium: 30 periods
Long: 60 periods
Swing Trading (Daily charts):
Short: 20 periods (default)
Medium: 50 periods (default)
Long: 100 periods (default)
Position Trading (Weekly charts):
Short: 10 periods
Medium: 20 periods
Long: 50 periods
Pro Tips:
Watch for divergences - when gold moves but correlations don't confirm
Correlation breakdowns often precede major trend reversals
The Medium-term (50p) correlation is plotted on the chart as your primary reference
Use the Status column for quick assessment of each asset's relationship
Set alerts for "Multiple Strong Inverse" to catch highest-probability setups
Important Notes:
This indicator is designed for Gold charts only (XAUUSD, GLD, GC1!, etc.)
Correlations are not static - they change over time based on market conditions
A correlation of -0.82 means 82% of gold's price movements can be explained by real interest rates
Always combine with other technical analysis and fundamental factors
Past correlations do not guarantee future relationships
Based on Research:
The correlation coefficients used in this indicator are based on peer-reviewed research:
Erb & Harvey (1997-2012): Real rates to gold correlation of -0.82
World Gold Council (2024): US Dollar to gold correlation of -0.63
Multiple academic studies confirming gold's inverse relationship with opportunity cost assets
Use this indicator to trade smarter, hedge better, and understand the macro forces driving gold prices.
Indicator
Dynamic Jurik RSX w/ Fisher Transform█ Introduction
The Dynamic Jurik RSX with Fisher Transform is a powerful and adaptive momentum indicator designed for traders who seek a non-laggy view of price movements. This script is based on the classic Jurik RSX (Relative Strength Index). It also includes features such as the dynamic overbought and oversold limits, the Inverse Fisher Transform, trend display, slope calculations, and the ability to color extremes for better clarity.
█ Key Features:
• RSX: The Relative Strength Index (RSX) in this script is based on Jurik’s RSX, which is smoother than the traditional RSI and aims to reduce noise and lag. This script calculates the RSX using an exponential smoothing technique and adaptive adjustments.
• Inverse Fisher Transform: This script can optionally apply the Inverse Fisher Transform to the RSX, which helps to normalize the RSX values, compressing them between -1 and 1. The inverse transformation makes it easier to spot extreme values (overbought and oversold conditions) by enhancing the visual clarity of those extremes. It also smooths the curve over a user-defined period in hopes of providing a more consistent signal.
• Dynamic Limits: The dynamic overbought and oversold limits are calculated based on the RSX's recent high and low values. The limits adjust dynamically depending on market conditions, making them more relevant to current price action.
• Slope Display: The slope of the RSX is calculated as the rate of change between the current and previous RSX value. The slope is displayed as dots when the slope exceeds the threshold designated by the user, providing visual cues for momentum shifts.
• Trend Coloring: Optionally, the user can also enable a trend-based display. It is simply based on current value of RSX versus the previous one. If RSX is rising then the trend is bullish, if not, then the trend is bearish.
• Coloring Extremes: Users can configure the RSX to color the chart when prices enter extreme conditions, such as overbought or oversold zones, providing visual cues for market reversals.
█ Attached Chart Notes:
• Top Panel: Enabled dynamic limits, Trend display, standard Jurik RSX with 20 lookback period, and Slope display.
• Middle Panel: Enabled dynamic limits, Extremes display, and standard Jurik RSX with 20 lookback period.
• Bottom Panel: Enabled dynamic limits, Trend display, Inverse Fisher Transform with 14 lookback period and 9 smoothing period. and Slope display.
█ Credits:
Special thanks to Everget for providing the original script. The script was also slightly modified based on updates from outside sources.
█ Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always conduct your own research and consult a professional before making any trading decisions. Indicator
[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.
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Multifactor Inverse Fisher Strategy (ps4)Best for higher time frames - 30m, 1H, 2H, 3H, 4H, D this strategy uses several factors that are pushed through an Inverse Fisher Transform (IFT). The higher the TF, the better the performance, up to 98%, but the number of deals tends to drop). Middle time frames (5m, 15m) look viable with Scaled Price (Scaled %P) and MFI factors. The factor list can be extended to include cci, stoch, rsi_stoch, emo, macd, cog, dpo, roc, accdist, cctbb, mom, awesome, tva, etc. Some of them need to be rescaled to a 0..100 interval. The IFT produces a value in the -1..1 interval (see: www.mesasoftware.com). This indicator does NOT repaint. Strategy
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Inverse Fisher Transform on STOCHASTIC (modified graphics)Modified the graphic representation of the script from John Ehlers - From California, USA, he is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception). John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or sell. Hopefully, the signals are clear and unequivocal. However, more often than not your decision to pull the trigger is accompanied by crossing your fingers. Even if you have placed only a few trades you know the drill. In this article I will show you a way to make your oscillator-type indicators make clear black-or-white indication of the time to buy or sell. I will do this by using the Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of your indicators. In the past12 I have noted that the PDF of price and indicators do not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the familiar bell-shaped curve where the long “tails” mean that wide deviations from the mean occur with relatively low probability. The Fisher Transform can be applied to almost any normalized data set to make the resulting PDF nearly Gaussian, with the result that the turning points are sharply peaked and easy to identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is compressive. The Inverse Fisher Transform is found by solving equation 1 for x in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If the input falls between –0.5 and +0.5, the output is nearly the same as the input. For larger absolute values (say, larger than 2), the output is compressed to be no larger than unity. The result of using the Inverse Fisher Transform is that the output has a very high probability of being either +1 or –1. This bipolar probability distribution makes the Inverse Fisher Transform ideal for generating an indicator that provides clear buy and sell signals. Indicator
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