Strategy
Sonic R (13-34-89) by DQT Sonic R System - EMA 13-34-89-200
Description:
The Sonic R indicator is built upon a multi-layered Exponential Moving Average (EMA) system combined with a Price Action Channel (PAC), designed to identify market trends, dynamic support/resistance zones, and high-probability trade entries.
Core Components:
1. Price Action Channel (PAC) — EMA 34 Band
The PAC is calculated using EMA 34 applied to High, Low, and Close prices, forming a dynamic channel that represents the short-term equilibrium zone. Price above the channel signals bullish momentum; price below signals bearish pressure.
2. EMA Trend System:
🟡 EMA 13 — Fast-reacting short-term trend, captures immediate price momentum
🔴 EMA 34 — Core support/resistance zone displayed as a red band, acts as the market's heartbeat
🟣 EMA 89 — Medium-term trend filter, smooths out market noise
🟢 EMA 200 — Long-term trend anchor, defines the overall market direction
How to Use:
Price above all EMAs → strong uptrend, prioritize buy setups
Price below all EMAs → strong downtrend, prioritize sell setups
Price inside the red EMA 34 band → market consolidating, wait for breakout confirmation
EMAs stacked in order (13 > 34 > 89 > 200) → trend is clean and strong, highest confidence entries
Best Used On: All timeframes — most effective on H1, H4, and Daily charts. Indicator
Indicator
Indicator
Strategy
Daubechies D4 Denoising [LB]Concept
The Daubechies D4 Wavelet Denoising indicator applies a multi‑level discrete wavelet transform using the compactly supported Daubechies D4 wavelet (Ingrid Daubechies, 1992) combined with Donoho's universal threshold (Donoho & Johnstone, 1994). It separates price into approximation (trend) and detail (noise) coefficients, attenuates noise via soft thresholding, and reconstructs a denoised price curve that directly overlays the chart.
Mathematical Foundation
The Daubechies D4 wavelet is defined by four scaling coefficients h and four wavelet coefficients g , forming quadrature mirror filters that satisfy perfect reconstruction. At each level, the input array a is circularly convolved with h and g , then downsampled by two to produce the approximation a' and detail d' :
a' = SUM_m h * a
d' = SUM_m g * a
This process is iterated J times. The universal threshold lambda is estimated for each detail array independently using the median absolute deviation (MAD) of the coefficients :
sigma = MAD / 0.6745
lambda = sigma * sqrt(2 * log N)
Soft thresholding is then applied to each detail coefficient x :
threshold(x) = sign(x) * max(|x| - lambda, 0)
Finally, the denoised signal is reconstructed by upsampling, convolution with synthesis filters, and summation of approximation and detail contributions.
What Problem Does It Solve ?
Classical moving averages and low‑pass filters eliminate noise at the cost of significant lag and do not adapt to the local structure of the data. The Daubechies D4 wavelet denoising preserves sharp transitions (edges) while removing high‑frequency noise, offering a lag‑free, adaptive smoothing that respects the multi‑scale nature of price action.
How To Interpret
Denoised line above price – the smoothed trend is stronger than the current raw price; underlying momentum remains positive despite transient dips.
Denoised line below price – the smoothed trend is weaker; price is correcting within a larger structure.
Denoised line flattening or changing direction – a regime shift may be underway; the multi‑scale trend is losing or gaining momentum.
Parameters
Source – price field to denoise (default close).
Decomposition Levels – number of wavelet decomposition iterations. Higher levels remove lower‑frequency components, producing a smoother but more slowly reacting line.
Window Length (power of 2) – analysis window size. Must be a power of two for the dyadic decomposition; the indicator automatically adjusts to the largest valid power of two if an invalid value is entered.
Reference
Daubechies I., "Ten Lectures on Wavelets", Society for Industrial and Applied Mathematics, 1992.
Donoho D.L. & Johnstone I.M., "Ideal Spatial Adaptation by Wavelet Shrinkage", Biometrika, Vol. 81, No. 3, pp. 425‑455, 1994. Indicator
Pro Scanner Multi-Symbol Trend & Momentum Scanner
OVERVIEW
This indicator scans up to 15 user-defined symbols and presents them in a
single color-coded dashboard on your chart. Instead of flipping between charts,
you get a consolidated view of price, change, trend bias, RSI and a combined
signal for every symbol in your watchlist.
HOW IT WORKS
For each symbol, the script requests data on a timeframe you choose and computes:
- LTP: the latest close.
- Chg%: percentage change vs the previous bar of the selected timeframe
(set the Scanner Timeframe to "D" for daily change).
- Trend: bullish (up) when price is above its EMA, bearish (down) when below.
EMA length is adjustable.
- RSI: standard Relative Strength Index with adjustable length; cells are shaded
for overbought (above 70) and oversold (below 30).
- Signal: a combined read from trend direction and RSI — BUY when trend is up
and RSI is firm, SELL when trend is down and RSI is weak, neutral otherwise.
The table can be sorted by percentage change so the strongest movers rise to the top.
HOW TO USE
1. Add the indicator to any chart.
2. In settings, enter your symbols in EXCHANGE:TICKER form (e.g. NSE:RELIANCE).
3. Set the scanner timeframe, EMA length and RSI length to match your style.
4. Use the dashboard to see which symbols share the same trend and momentum bias.
It is meant as a quick filter to shortlist symbols for closer analysis on
their own charts.
SETTINGS
- Scanner Timeframe, Trend EMA Length, RSI Length
- Sort by % change (on/off)
- Table position and text size
- 15 editable symbols
NOTES
This tool is for analysis and education only. It does not predict future prices
and is not financial advice. Reliable results require a valid data feed for each
symbol. Always do your own research and manage risk. Indicator
Indicator
Indicator
Indicator
Indicator
XRP HODLER Framework / Infinity Signal v2.0The XRP HODLER Framework is a long-term investor decision-support indicator designed to help identify when market conditions may be favorable for:
• Cost Averaging Down
• Cost Averaging Up
• Reducing Risk
• Waiting for Alignment
The indicator combines multiple market measurements into a single framework that is easy to interpret and designed to remove emotion from the decision-making process.
Core Components
The framework evaluates:
• Relative Strength Index (RSI)
• Stochastic RSI
• Money Flow Index (MFI)
• Optional Fear & Greed Sentiment
These components are combined into a scoring system that determines overall market pressure and investor positioning.
Value Zone
Value Zones identify periods where accumulation conditions are developing while price remains below the long-term trend.
These zones are intended to represent potential Cost Average Down environments.
The objective is not to identify an exact bottom, but to identify areas where value may be improving.
Trend Confirmation
Trend Confirmation Zones identify periods where accumulation conditions remain favorable while price trades above the long-term trend.
These zones are intended to represent potential Cost Average Up environments.
Rather than buying weakness, investors may choose to add to positions after evidence of trend recovery appears.
Reduce Risk
Reduce Risk Zones identify periods where market conditions may be becoming increasingly extended.
These zones may be useful for:
• Profit-taking evaluation
• Exposure reduction
• Risk management review
The framework is not designed to identify exact market tops.
Instead, it highlights areas where risk may be increasing.
Market Pressure Dashboard
The dashboard displays:
• Market State
• Market Pressure
• HODLER Mode
• RSI
• Stochastic RSI
• MFI
• Fear & Greed
• Buy Score
• Sell Score
• Final Signal
This allows investors to quickly assess current market conditions from a single location.
Final Signals
COST AVERAGE DOWN
Multiple accumulation conditions are aligning while price remains below the long-term trend.
COST AVERAGE UP
Multiple accumulation conditions are aligning while price remains above the long-term trend.
REDUCE RISK
Multiple risk conditions are aligning, and market conditions may be becoming increasingly
extended.
How To Use
Step 1
Select the timeframe you wish to analyze.
Many long-term investors prefer the Weekly chart, while active investors may prefer the Daily chart.
Step 2
Monitor the HODLER MODE row.
COST AVERAGE DOWN
Potential value conditions may be developing below the long-term trend.
COST AVERAGE UP
Accumulation conditions remain favorable while price trades above the long-term trend.
Step 3
Review the Buy Score and Sell Score.
Higher Buy Scores indicate increasing accumulation pressure.
Higher Sell Scores indicate increasing risk pressure.
Step 4
Review the Final Signal.
WAIT FOR ALIGNMENT
Remain patient.
COST AVERAGE DOWN
Potential value accumulation conditions are present.
COST AVERAGE UP
Trend recovery conditions are present.
REDUCE RISK
Market conditions may be becoming increasingly extended.
Step 5
Use the framework as a decision-support tool rather than a prediction tool.
The objective is not to identify exact tops or bottoms.
The objective is to identify improving or deteriorating market conditions while maintaining discipline and consistency.
WAIT FOR ALIGNMENT
Market conditions remain mixed, and additional confirmation may be required.
Important Notes
The XRP HODLER Framework is designed to identify changing probabilities rather than predict future prices.
No indicator can consistently identify exact market tops or bottoms.
This framework is intended to provide structure, discipline, and context for long-term investors.
Disclaimer
This script is provided for educational and informational purposes only.
It does not constitute financial advice, investment advice, trading advice, or a recommendation to buy or sell any financial instrument.
Always conduct your own research and use proper risk management. Indicator
Indicator
Indicator
Indicator
Indicator
Indicator
Indicator
Strategy
Indicator
Household Equity Allocation -- Positioning Gauge█ OVERVIEW
This indicator plots, in its own pane, the percentage of United States household financial assets held in corporate equities, requested live from the Federal Reserve Z.1 financial accounts. It ranks the current reading against an embedded multi-decade history, classifies it into posture zones, and reports an indicative long-horizon estimate, presenting household equity positioning as a slow, low-frequency context gauge rather than a price-derived trading signal.
█ HISTORY / BACKGROUND
The series shown is published by the Federal Reserve Board in the Z.1 Financial Accounts of the United States, formerly the Flow of Funds, available quarterly since 1945. It measures households' directly and indirectly held corporate equities as a share of their financial assets. Its use as a forward-looking context measure was popularized by the analyst writing as Philosophical Economics in 2013, who examined its historical relationship with subsequent long-horizon equity returns and contrasted it with Robert Shiller's cyclically adjusted price-to-earnings ratio.
The conceptual basis is an accounting identity rather than a behavioral model: investors in aggregate must hold the entire outstanding supply of equities, so the equity share of household assets can rise only when equity prices rise relative to the supply of other assets. The measure is therefore a positioning and relative-valuation reading expressed in committed dollars, not a sentiment survey. The script applies no proprietary transformation to the series; it requests the published values and contextualizes them.
█ HOW IT WORKS
- The script requests the series named by the FRED series input (default FRED:BOGZ1FL153064486Q) with request.security at a quarterly (3M) resolution, lookahead disabled and gaps off, taking the published close as the current allocation reading.
- A fixed baseline of annual year-end values from 1945 through 2025 is loaded once into an array on the first bar. After a hardcoded cutoff (Q4 2025) the script appends each new distinct live reading to that array, so the baseline extends automatically as new quarters are published.
- A percentile routine counts the baseline entries less than or equal to the current reading and returns that count as a percentage of the array size, giving the reading's full-history percentile.
- The reading is classified into one of four zones by comparison against the three threshold inputs: below Bottom-quintile , below Top-quintile , below Above historical range , or at or above it. Each zone maps to a color and a posture label.
- An indicative estimate is computed as a fixed linear function of the reading, with intercept 12.338 and slope -0.3978, using constants hardcoded in the script. When the reading exceeds the in-sample maximum of 38.7, the estimate is marked as an extrapolation.
- The allocation is drawn as a line colored by the active zone. Three dashed horizontal lines mark the thresholds, and an optional background tint shades the pane by zone. An optional table in the top right reports the current value, its full-history percentile, the posture, the indicative estimate (flagged when extrapolated), the in-sample maximum, and the data source. The table is built only on the last bar.
█ HOW TO USE
The output is read from the pane and the table.
- The line and its color show where positioning currently sits: green for the lowest band, gold for a neutral band, amber for an elevated band, and red for a reading above the historical range. The posture label in the table names the same state.
- The dashed lines are the zone thresholds, and the optional background tint repeats the active zone for quick reading.
- The table states the current value, its percentile against the full history, the posture, and the indicative long-horizon estimate, with a flag when that estimate is extrapolated beyond the historical range.
Recommended timeframe: the underlying data is quarterly and the script requests it at a quarterly resolution regardless of the chart's timeframe, so the displayed value is identical on every chart timeframe. A monthly or weekly chart on a long-history instrument is suggested only so the plotted line spans a useful visual range; the value and table do not depend on the chart timeframe or the chart symbol. Because the series is slow and lagged, it is intended for strategic, low-frequency context, not intraday or short-term use.
█ SETTINGS
- FRED series (symbol, default FRED:BOGZ1FL153064486Q): the economic series the script requests and contextualizes.
- Shade posture zones (on or off, default on): toggles the background tint that colors the pane by the active zone.
- Show info table (on or off, default on): toggles the top-right summary table.
- Bottom-quintile (cheap) below (number, default 14.0): the upper bound of the lowest zone, in percent.
- Top-quintile (underweight) above (number, default 28.0): the level above which the reading is treated as elevated.
- Above historical range above (number, default 39.0): the level above which the reading is treated as beyond the historical range.
█ WHAT MAKES IT ORIGINAL
The script does not compute a price-based study. It is a self-contained method for contextualizing a single external economic series on a chart. Its construction is specific: it pulls the series live through request.security; it ranks the current reading against a historical distribution embedded directly in the script and extended automatically after a cutoff date, so the percentile is point-in-time and does not depend on how much chart history is loaded; it maps the reading to posture zones by user thresholds; and it computes an indicative estimate from a fixed linear fit while explicitly flagging when the current reading lies beyond the data range that produced the fit. The combination of an embedded, self-extending baseline for percentile ranking, the posture zoning, and the extrapolation flag, presented together for this macro series in one pane and table, is what distinguishes it. It applies no proprietary formula on price; the contribution is the contextualization method.
█ NOTES / LIMITATIONS
- Data dependence: the script plots an external economic series, not chart price, and requires access to the configured economic symbol through your data subscription. If the symbol cannot be resolved the request returns na, the line does not plot, and the table shows n/a.
- Chart history and rendering: the percentile baseline and the table are independent of chart history because the baseline is embedded in the script, but the plotted line spans only the bars loaded on the chart, so on a short chart the visible line is short. The table is built only on the last bar.
- Frequency and revision: the source is quarterly and reported with a lag, so the value changes only when a new quarter is published, and the most recent value can be revised by the source.
- Request behavior: the series is requested with lookahead disabled, so no future data is placed on historical bars, and values are carried forward between releases. Historical readings do not repaint; only the most recent reading can change as the source releases or revises a quarter.
- Baseline granularity and cutoff: the embedded baseline holds one value per year (annual year-end) from 1945 through 2025, and live values are appended only after the hardcoded Q4 2025 cutoff, so the percentile reference is annual before that date and extends quarterly thereafter.
- Extrapolation: the indicative estimate is fit over readings up to 38.7, and current readings exceed that, so the estimate lies outside the fitted range and is flagged as such.
- Symbol scope: the script is independent of the chart symbol and can be applied to any chart, since it does not read the chart's price.
This script displays historical economic data and a derived estimate for research and educational purposes. It is not investment advice. Indicator
HAP 3 Pressure BandsHAP 3D Pressure Bands
HAP (Hybrid Adaptive Pressure Bands) is a price-overlay indicator designed to visualize momentum pressure, volatility compression, and expansion directly on the chart without requiring a separate oscillator panel.
Unlike traditional Bollinger Bands, which are built purely from price volatility, HAP derives its structure from RSI behavior and projects that information back onto the price chart. This creates a dynamic pressure field that adapts to both momentum and volatility conditions.
The indicator calculates an RSI-based equilibrium zone and transforms it into a price-scaled band structure. The result is a visual representation of market pressure, allowing traders to identify periods of contraction, expansion, and potential breakout conditions.
━━━━━━━━━━━━━━━━━━━━
HOW IT WORKS
━━━━━━━━━━━━━━━━━━━━
• RSI Engine
The core of the indicator is built around RSI. The average RSI and its standard deviation create an adaptive momentum envelope.
• Dynamic Price Projection
Instead of displaying RSI in a separate panel, HAP converts RSI deviations into price-scaled bands using market volatility. This projects momentum information directly onto the chart.
• 3D Pressure Bands
The layered fills create a depth effect that highlights areas of compression and expansion. The visual intensity increases as pressure builds inside the structure.
• Squeeze Detection
When band width contracts below its historical average, the indicator enters a squeeze state. This represents reduced volatility and potential energy accumulation.
• Release Signals
A squeeze release occurs when the market exits a compressed state. These events often precede strong directional moves and can help traders identify expansion phases.
━━━━━━━━━━━━━━━━━━━━
HOW TO USE
━━━━━━━━━━━━━━━━━━━━
Bullish Conditions:
• Price breaks and holds above the upper pressure band.
• Squeeze releases upward.
• RSI pressure expands after a compression phase.
Bearish Conditions:
• Price breaks and holds below the lower pressure band.
• Squeeze releases downward.
• Momentum pressure expands to the downside.
Neutral Conditions:
• Price remains inside the band structure.
• Market is balancing between buyers and sellers.
• Compression may be building for a future breakout.
━━━━━━━━━━━━━━━━━━━━
INTERPRETATION
━━━━━━━━━━━━━━━━━━━━
The bands should not be viewed as traditional support and resistance levels. Instead, they represent dynamic pressure zones where market participants are either accumulating energy or releasing it.
Narrow bands indicate compression.
Wide bands indicate expansion.
Breakouts outside the pressure field suggest a potential shift in market control.
HAP is not intended to predict future price movements. It is designed to visualize the relationship between momentum and volatility in a way that is intuitive, clean, and directly integrated into the price chart.
Best used alongside trend analysis, market structure, volume studies, and higher timeframe confirmation.
HAP 3D Pressure Bands
HAP (Hybrid Adaptive Pressure Bands), momentum baskısını, volatilite sıkışmasını ve genişlemesini doğrudan fiyat grafiği üzerinde göstermek amacıyla tasarlanmış bir fiyat üstü (overlay) göstergedir.
Klasik Bollinger Bantları yalnızca fiyat volatilitesine dayanırken, HAP yapısını RSI davranışından oluşturur ve bu bilgiyi tekrar fiyat grafiğine taşır. Böylece hem momentum hem de volatiliteyi dikkate alan dinamik bir baskı alanı oluşturur.
Gösterge, RSI'ın ortalama ve standart sapma yapısını kullanarak bir denge bölgesi hesaplar. Daha sonra bu yapı fiyat ölçeğine dönüştürülerek grafik üzerine yerleştirilir. Sonuç olarak yatırımcılar piyasadaki sıkışma, genişleme ve olası kırılım bölgelerini daha net görebilir.
━━━━━━━━━━━━━━━━━━━━
NASIL ÇALIŞIR?
━━━━━━━━━━━━━━━━━━━━
• RSI Motoru
Göstergenin temelinde RSI bulunur. RSI'ın ortalaması ve standart sapması adaptif bir momentum zarfı oluşturur.
• Dinamik Fiyat Projeksiyonu
RSI ayrı bir panelde gösterilmek yerine, fiyat volatilitesi kullanılarak fiyat grafiğine dönüştürülür. Böylece momentum bilgisi doğrudan fiyatın üzerinde görüntülenir.
• 3D Baskı Bantları
Katmanlı dolgu yapısı sıkışma ve genişleme bölgelerini görsel olarak daha belirgin hale getirir. Baskı arttıkça bantların görsel yoğunluğu da artar.
• Sıkışma (Squeeze) Tespiti
Bant genişliği kendi tarihsel ortalamasının altına düştüğünde gösterge sıkışma durumuna geçer. Bu durum genellikle volatilitenin azaldığını ve enerjinin biriktiğini gösterir.
• Release (Boşalma) Sinyalleri
Sıkışma sona erdiğinde oluşan release sinyalleri, piyasanın yeni bir hareket başlatabileceğini gösterir. Bu bölgeler çoğu zaman güçlü yönlü hareketlerin başlangıç noktaları olabilir.
━━━━━━━━━━━━━━━━━━━━
NASIL KULLANILIR?
━━━━━━━━━━━━━━━━━━━━
Yükseliş Senaryosu:
• Fiyat üst baskı bandının üzerine çıkar ve üzerinde tutunur.
• Squeeze yukarı yönlü sonlanır.
• Momentum baskısı sıkışma sonrasında genişlemeye başlar.
Düşüş Senaryosu:
• Fiyat alt baskı bandının altına iner ve altında kalır.
• Squeeze aşağı yönlü sonlanır.
• Momentum baskısı aşağı yönde genişler.
Nötr Senaryo:
• Fiyat bant yapısının içinde hareket eder.
• Alıcı ve satıcılar arasında denge oluşur.
• Gelecekteki olası kırılım için enerji birikiyor olabilir.
━━━━━━━━━━━━━━━━━━━━
YORUMLAMA
━━━━━━━━━━━━━━━━━━━━
Bu bantlar klasik destek ve direnç bölgeleri olarak değerlendirilmemelidir. HAP'ın amacı fiyatın etrafındaki baskı alanlarını göstermek ve piyasanın enerji biriktirdiği veya enerjiyi serbest bıraktığı bölgeleri görselleştirmektir.
Dar bantlar sıkışmayı,
Geniş bantlar genişlemeyi,
Bant dışı hareketler ise olası kontrol değişimini ifade eder.
HAP geleceği tahmin etmeyi amaçlayan bir gösterge değildir. Amaç, momentum ile volatilite arasındaki ilişkiyi sade, görsel ve anlaşılır bir yapıda fiyat grafiğinin üzerine taşımaktır.
En iyi sonuçlar trend analizi, piyasa yapısı, hacim çalışmaları ve üst zaman dilimi teyitleri ile birlikte kullanıldığında elde edilir.
Indicator
Generalized Fisher Transform [LB] Concept
The Generalized Fisher Transform extends John F. Ehlers' classic Fisher Transform (2002) by introducing an adjustable shape parameter that controls the sensitivity profile of the transformation. While the original Fisher Transform maps any normalized input to a near‑Gaussian output to highlight statistical extremes, this generalized version allows traders to emphasize central regions (shape < 1) or extreme tails (shape > 1) depending on their strategy.
Mathematical Foundation
The indicator first normalizes price to a bounded range using a rolling min‑max window of length N :
x = 2 × (P - L_min) / (H_max - L_min) - 1
A signed power is then applied with a shape factor p :
x_p = sign(x) × |x|^p
The generalized Fisher Transform is computed as :
F = 0.5 × ln( (1 + x_p) / (1 - x_p) )
When p = 1 , the formula reduces to the classic Fisher Transform. Values of p < 1 amplify sensitivity near zero (central price region), while p > 1 amplify sensitivity near the edges (extreme price region). The result is smoothed by an EMA for noise reduction.
What Problem Does It Solve ?
Classic oscillators such as RSI or Stochastic use fixed non‑linear mappings that cannot adapt to different market regimes or trader preferences. The classic Fisher Transform offers a single sensitivity profile. The Generalized Fisher Transform solves this by exposing the shape parameter p , giving traders direct control over where the indicator is most responsive — near the mean or near the extremes — without changing the underlying logic or introducing additional indicators.
How To Interpret
The indicator operates in two selectable modes :
Extremes Mode – the background turns red when Fisher exceeds the upper threshold (statistically overbought), and green when it drops below the lower threshold (statistically oversold). These zones suggest potential mean‑reversion.
Direction Mode – the background turns cyan when Fisher is above zero (bullish bias) and orange when below zero (bearish bias). This mode is suited for trend‑following or directional confirmation.
In both modes, the Fisher line crossing zero indicates a shift in the price distribution relative to its recent range.
Parameters
Source – price data used for the calculation (default: close).
Normalization Period – number of bars used to compute the rolling min‑max for the normalization.
Shape Factor – exponent applied to the normalized price before the Fisher transform. 1 = classic Fisher, < 1 = center‑sensitive, > 1 = tail‑sensitive.
Smoothing Period – EMA length applied to the raw Fisher output.
Coloration Mode – switches between "Extremes" (overbought/oversold highlighting) and "Direction" (bullish/bearish highlighting).
Upper Threshold – Fisher level above which the background turns red in Extremes mode.
Lower Threshold – Fisher level below which the background turns green in Extremes mode.
Reference
Ehlers J.F., "Using the Fisher Transform", Technical Analysis of Stocks & Commodities, Vol. 20, No. 11, pp. 40‑45, November 2002.
Ehlers J.F., "Cybernetic Analysis for Stocks and Futures", Chapter 4 – The Fisher Transform, John Wiley & Sons, 2004. Indicator
