AetherEdge - Bayesian Changepoint Detection🖊️ Overview
AE-BCP is a Bayesian detector of structural breaks (Adams & MacKay, 2007). Rather than flagging regime shifts with a hard threshold, it maintains a posterior distribution over the run length — the number of bars since the last changepoint — and updates it recursively with every new observation. A Gaussian conjugate predictive (on standardized returns or log-volatility) scores how surprising each bar is under each run-length hypothesis. Beliefs self-evolve recursively, and P(run length = 0) is the live probability that a structural break just occurred. The classic triangular run-length posterior is painted as a heatmap.
🔶 Key Features
BOCPD engine — recursively updates the run-length posterior into growth and changepoint probabilities, outputting structural breaks as a probability.
Self-evolving recursive Bayesian update — each run-length hypothesis's predictive model (sufficient statistics) and the posterior update online with every observation.
Changepoint probability (soft detection) — P(run length = 0) as a continuous 0–1 probability; threshold crossings are marked on price.
Run-length posterior heatmap — the time × run-length × probability triangular heatmap (BOCPD's signature visual), aligned to the price timeline.
Expected run length (regime age) — estimates how many bars the current regime has lasted, collapsing to zero at changepoints (shown as a line).
Volatility or drift — monitor log squared returns to detect volatility-regime changes, or returns to detect drift changes.
Live statistics panel — changepoint probability, regime age, MAP run length, last changepoint, and hazard rate.
Non-repainting design — all updates on confirmed bars only, with no look-ahead.
🧠 Technical Architecture
The monitored feature (Volatility mode = log squared return, Returns mode = return) is standardized over a long window, fixing the predictive variance at ~1. On each confirmed bar, the predictive probability of each run-length hypothesis r is pred(x_t|r) = N(x_t | m_r, σ²(1+1/r)) (m_r = the run's mean). From these, growth P(r_t=r+1) ∝ P(r_{t-1}=r)·pred·(1−H) and changepoint P(r_t=0) ∝ Σ_r P(r_{t-1}=r)·pred·H are computed and normalized. H is the hazard rate (= 1 / mean regime length), the prior probability of a changepoint.
Each run-length's sufficient statistics (sum of the run's observations) update as sum = sum + x_t on growth and sum = 0 (prior) on a changepoint. Run length is truncated at Rmax for tractability. Outputs are the changepoint probability P(r_t=0), expected run length E =Σr·P(r), and MAP run length argmax P(r). The posterior is binned into a rolling buffer and, on the last bar, drawn as a heatmap (boxes) aligned to the price timeline.
🎯 Three design choices stand out. First, standardization fixes the predictive variance, allowing a robust Gaussian-conjugate implementation with no gamma functions. Second, monitoring log squared returns turns "variance changes" into "mean changes," so a simple mean-change model captures volatility-regime breaks. Third, confining updates to confirmed bars keeps the historical posterior non-repainting.
⚙️ Recommended Settings & Tuning Guide
As a crypto starting point — BTC/ETH (1D, 4H): Monitor = Volatility, mean regime length 60, standardization length 200, max run length 100, changepoint threshold 0.30; volatility-regime breaks are clearly marked. For more frequent turns: lower mean regime length toward 30 (higher hazard, more sensitive) and lower the threshold to 0.25. To suppress noise: raise mean regime length to 100 and the threshold to 0.40.
Per parameter: Mean regime length is the key knob (hazard = its reciprocal) — shorter detects changepoints more often, longer is conservative. Monitor selects Volatility (vol breaks) or Returns (drift changes) for your purpose. Standardization length sets the baseline scale window (longer is steadier). Max run length sets how far back regimes are retained. Changepoint threshold sets marker sensitivity.
💡 How to Use in Practice
The core read is changepoint probability × regime age. When the changepoint probability is low and stable and the regime age keeps rising, the current regime (trend or range) is persisting — strategies aligned with that premise tend to work. The moment the changepoint probability spikes above the threshold (diamond marker fires) signals the volatility or drift structure has changed — a point to review existing positions or switch strategy to the new regime. Each time the heatmap triangle resets (run length collapses to zero), you can see the market entering a new phase visually.
For multi-timeframe work, read higher-timeframe changepoints for major structural turns and execute on a lower timeframe. It also serves as a meta-filter to run trend or mean-reversion strategies only while the regime is stable.
⚠️ Important Notes
Nothing displays until the warmup period (default 200 bars) completes. Reloading the indicator rebuilds the posterior from scratch — learning state is not persisted. This is a Gaussian-conjugate model with a known (≈1, via standardization) predictive variance that detects mean changes in the monitored feature (Volatility mode captures volatility changes via the log-squared transform). Run length is truncated at Rmax, so for very long regimes the expected run length saturates near the cap. The changepoint probability is a posterior belief, not a certain verdict, and detection requires evidence to accumulate, so it lags by a few bars. Updates occur on confirmed bars only.
🚨 Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial or investment advice. Past performance is not indicative of future results. All trading involves risk. Use it alongside your own thorough testing and sound risk management; all trading decisions remain solely your own responsibility. Gösterge
AetherEdge - Principal Component Analysis🖊️ Overview
AE-PCA extracts the market's eigen-state from the correlation structure of a basket of assets. It builds a rolling correlation matrix online and extracts the leading principal components — PC1 (market factor), PC2 (rotation/dispersion) — via power iteration with deflation. From the eigenvalues it derives the Absorption Ratio (λ₁/N) — the share of basket variance explained by one factor — which reveals, at a glance, the "everything moves together" systemic fragility of the market. The eigenbasis continuously re-orients each bar to the current correlation structure.
🔶 Key Features
Online PCA engine — builds a rolling correlation matrix with forgetting and extracts the top two principal components by power iteration (heavy use of the matrix type).
Absorption Ratio (systemic stress) — λ₁/N quantifies market concentration = fragility; sharp rises capture the "correlation convergence" that precedes crashes.
Self-evolving eigenbasis — eigenvectors are warm-started and re-converged each bar, tracking shifts in correlation smoothly (subspace tracking) with sign continuity preserved.
Phase-space comet — projects the live return vector onto PC1/PC2 and traces the market's path through factor space as a comet trail on a floating canvas to the right of the chart.
Factor loadings — identifies the asset that loads most heavily on PC1 (the one leading the market).
Dispersion gauge — 1 − Absorption Ratio shows the degree of diversification.
Live statistics panel — absorption ratio, cumulative (PC1+PC2), eigenvalues λ₁/λ₂, dispersion, lead asset, and PC1/PC2 scores.
Macro-overlay design — the basket is independent of the chart symbol, so you can overlay market-wide stress on any chart you view. Confirmed-bar updates, no look-ahead.
🧠 Technical Architecture
From 6 asset returns, first and second moments (means, covariances) are updated online with forgetting factor λ, then divided by each asset's standard deviation to build the correlation matrix R (N×N). PC1 is found by power iteration v ← Rv/‖Rv‖, with eigenvalue λ₁ from the Rayleigh quotient. Then deflation R₂ = R − λ₁v₁v₁ᵀ is applied, and PC2 obtained by power iteration with Gram-Schmidt orthogonalization. Since the correlation matrix has trace N, the absorption ratio is λ₁/N and the cumulative is (λ₁+λ₂)/N.
Factor scores are computed by projecting the standardized current returns z_i=(r_i−μ_i)/σ_i onto the eigenvectors (PC1 score = Σz_i·v₁_i). Eigenvectors are warm-started from the previous bar for fast convergence and sign stability across bars (PC1 is oriented so Σv₁ > 0). A high absorption ratio means "correlation convergence = single-factor dominance = fragility"; a low one means "dispersion = diversification." All updates occur on confirmed bars.
🎯 Three design choices stand out. First, using the correlation (not covariance) matrix yields a scale-free absorption ratio that isn't dominated by a single high-volatility asset. Second, warm-starting the eigenvectors suppresses sign flips and flicker, giving smooth scores. Third, confining updates to confirmed bars keeps historical values non-repainting.
⚙️ Recommended Settings & Tuning Guide
As a crypto starting point — a basket of the 6 majors (BTC/ETH/SOL/BNB/XRP/ADA), 1D/4H: adaptation λ = 0.97, Calm threshold 0.40, Stress threshold 0.60; crypto-wide risk-on/off separates cleanly. For nimbler anomaly detection: lower λ toward 0.95 to react faster to correlation shifts, and raise the Stress threshold to 0.65 so only genuine convergence triggers, reducing noise.
Per parameter: Adaptation λ is the main knob — near 0.99 correlations are smooth and long-run; near 0.95 they respond quickly to shocks. Calm/Stress thresholds should be tuned to your basket's composition and its typical absorption ratio (closer to uncorrelated → lower λ₁/N; strongly correlated → higher). Comet length / canvas width tune the phase-space display. The basket can be freely swapped for the assets whose correlation you want to track.
💡 How to Use in Practice
The core read is the absorption-ratio regime. When the ratio is low and stable (CALM), the market is diversified and stock-picking tends to work. When it spikes into the Stress zone, correlations have converged into an "everything moves together" fragile state — a cue to reduce concentration as a leading sign of self-reinforcing declines or risk-off. When the phase-space comet stretches strongly in one direction, the market is factor-driven (trending); when it swirls near the center, it's ranging/rotating. The Lead Asset is the one currently driving the whole market.
For multi-timeframe work, read the higher-timeframe absorption ratio for the macro risk backdrop and execute single-name trades on the lower timeframe. Paired with trend and volatility tools, it serves as a top-level risk filter (e.g., avoid fading during stress spikes).
⚠️ Important Notes
This indicator fetches external data (request.security) for 6 symbols. Specifying invalid or illiquid symbols drops their contribution and degrades accuracy — compose the basket from liquid symbols. Nothing displays until warmup completes. Reloading the indicator rebuilds the correlation moments from scratch — learning state is not persisted. The absorption ratio is a proxy for systemic fragility (akin to Kritzman's absorption ratio), not a directional signal by itself. The sign of the PC2 score is arbitrary. The phase-space comet is drawn in the chart's right margin, so display requires right-side space. Power iteration is an approximation of the top two components, and updates occur on confirmed bars only.
🚨 Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial or investment advice. Past performance is not indicative of future results. All trading involves risk. Use it alongside your own thorough testing and sound risk management; all trading decisions remain solely your own responsibility. Gösterge
AetherEdge - Gaussian Mixture Regimes🖊️ Overview
AE-GMM is a self-evolving regime detector that treats the market as a probability distribution rather than carving it up with rigid rules. It models the joint distribution of momentum × volatility as a mixture of K Gaussian components — one per regime — and keeps learning their means, variances, and weights through online Expectation-Maximization with forgetting. Every bar receives a soft probability vector (a posterior) over regimes, rendered as a flowing probability ribbon that lets the market's state blend and shift before your eyes.
🔶 Key Features
Gaussian mixture + online EM engine — the E-step (responsibilities) and M-step (sufficient statistics) run every bar, estimating the regime distribution incrementally.
Self-evolving forgetting mechanism — a forgetting factor λ weights recent data, so the model quietly reshapes itself as regimes emerge and dissolve.
Soft probability ribbon — the K regime probabilities, stacked into a flow in the lower pane; not hard boundaries, but "how much of each regime is present now."
Semantic regime coloring — each component is auto-colored by the character of its learned centroid (Risk-On / Range / Risk-Off / Stress), sidestepping the label-switching problem.
Projection onto price — force_overlay tints the main chart's background by the dominant regime, deepening with confidence.
Live statistics panel — dominant regime, confidence, per-regime probabilities, regime duration, the adaptation factor λ, and model fit (log-likelihood).
Diagonal-covariance robustness — no matrix inversion, numerically stable; learning on confirmed bars only, with no look-ahead.
🧠 Technical Architecture
The feature space is two-dimensional — a momentum axis (z-scored ATR-unit trend deviation) and a volatility axis (z-scored log realized-volatility). Each component is a diagonal-covariance Gaussian with mean μ_k, variance σ²_k, and weight π_k. Every bar, responsibilities (posteriors) are computed as γ_k(x) = π_k·N(x|μ_k,σ²_k) / Σ_j π_j·N(x|μ_j,σ²_j), normalized stably via log-sum-exp in the log domain.
Learning proceeds by incremental EM. On each confirmed bar, the sufficient statistics (responsibility mass N_k, Σγx, Σγx²) are updated with a forgetting factor λ, and π_k, μ_k, σ²_k are re-derived from them. Lower λ weights recent data and adapts quickly; higher λ acts as longer memory and stays steady. Components are initialized spread around a ring in feature space, starting from diverse regimes and migrating toward the data. Each regime's color is decided every bar from its learned centroid (high volatility → Stress; positive momentum → Risk-On; negative → Risk-Off; in between → Range).
🎯 Three design choices stand out. First, soft responsibilities let regime transitions be expressed as a blend of probabilities — the "in-between" is visible. Second, character-based coloring keeps colors meaningful regardless of index shuffling. Third, confining parameter updates to confirmed bars — with only the forming bar's posterior updating live — keeps historical output non-repainting.
⚙️ Recommended Settings & Tuning Guide
As a crypto starting point — BTC/ETH (1D, 4H): K = 3, λ = 0.99, standardization length 200, vol length 20; Risk-On / Range / Stress separate cleanly. High-volatility names (SOL, XRP): lower λ toward 0.97 for faster adaptation, and set K = 4 to split Stress into upside vs downside stress, revealing the internal structure of rough action.
Per parameter: λ (adaptation) is the key knob — near 0.999 regimes are smooth and persistent; near 0.95 they switch nimbly. K (regimes) ranges from 2 (on/off) to 4 (finer states). Standardization length sets the feature baseline window — longer is steadier, shorter more locally adaptive. Stress Vol (z) sets how much of a volatility rise counts as "Stress."
💡 How to Use in Practice
The core read is dominant regime × confidence. When the ribbon is thick in a single color (high confidence) and stable, strategies aligned with that regime tend to work (trend-following in Risk-On, fading in Range). When ribbon colors blend, it signals a regime transition — a cue to cut size or stand aside. When the Stress (amber) probability rises, volatility is expanding — useful for staging breakouts or de-risking.
For multi-timeframe work, read the higher-timeframe regime for the backdrop and execute on a lower timeframe. With the price-chart background tint enabled, regime "epochs" sit directly over the candles, making context easy to combine with trend or volume tools.
⚠️ Important Notes
Regimes are hidden until the warmup period (default 200 bars) completes. Reloading the indicator, or changing settings, makes the model relearn across the entire history from scratch — learning state is not persisted. This is a diagonal-covariance approximation and does not explicitly model correlation between features. Regime probabilities are the model's probabilistic beliefs, not certain forecasts. Parameters update on confirmed bars, while the forming bar's probabilities move live.
🚨 Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial or investment advice. Past performance is not indicative of future results. All trading involves risk. Use it alongside your own thorough testing and sound risk management; all trading decisions remain solely your own responsibility. Gösterge
AetherEdge - Q-Learning Regime Agent🖊️ Overview
AE-QRA is a reinforcement-learning agent that learns its policy from experience, right on your chart. It discretizes the market into 27 regimes (Trend × Momentum × Volatility) and learns which action to take in each — Short, Flat, or Long — by maximizing reward through tabular Q-learning. No instructions, no labels: the agent relies on reward alone, sharpening its judgment as it shifts from exploration to exploitation.
🔶 Key Features
A real Q-learning engine — the TD(0) update Q(s,a) ← Q(s,a) + α runs every bar, updating a value table over states × actions.
Reward function — reward = position × next-bar return − turnover cost. Profitable decisions are reinforced; needless trading is penalized.
Exploration–exploitation, made real — an ε-greedy policy whose ε decays over time, automatically shifting from random exploration to exploiting the learned policy.
Policy heatmap — the learned policy across 27 regimes, visualized as a 9-cell color grid at the live volatility slice; the cell for the current regime glows.
Regime coloring — bars and background are tinted by the agent's current stance, growing more saturated with conviction.
Action-flip markers — triangle markers mark switches to Long or Short.
Live statistics panel — action, conviction, exploration rate ε, cumulative reward (policy P&L), regime coverage, and the current state.
Fully deterministic, non-repainting design — the exploration RNG is seed-fixed; learning and decisions occur on confirmed bars only, on a one-bar lag.
🧠 Technical Architecture
The state space is built from three discrete features — ATR-unit trend deviation (↓/·/↑), RSI momentum (↓/·/↑), and volatility percentile rank (low/mid/high). Their product gives 27 states, with three actions (Short = −1 / Flat = 0 / Long = +1). The value table Q is persisted as a var matrix (27 × 3).
On each confirmed bar, the agent first observes the reward of its previous action (position × realized return − switching cost), then updates that value via TD(0) using the maximum Q at the next state. It then selects the next action ε-greedily. ε decays as ε = ε_min + (ε_start − ε_min)·exp(−step/decay) — exploratory early on (frequent random actions), exploiting the learned policy as it matures. Conviction is computed as the separation of the three Q-values at the current state and feeds both the background tint and the panel. Because the RNG is a deterministic LCG, the policy is reproducible under identical settings.
🎯 Three design choices stand out. First, embedding a switching cost in the reward suppresses over-trading at the learning level and makes Flat a meaningful choice. Second, confining learning and decisions to confirmed bars on a one-bar lag eliminates future leakage. Third, the deliberately compact 27-state design helps the policy converge even on shorter histories.
⚙️ Recommended Settings & Tuning Guide
As a crypto starting point — BTC/ETH (1D, 4H): α = 0.10, γ = 0.95, ε-Start = 0.90, ε-Decay = 500, switching cost 3 bps; this yields clean trend adaptation. High-volatility names (SOL, XRP): raise switching cost to 5–8 bps to curb trade frequency, and shorten ε-Decay toward 300 so the agent reaches the exploitation phase faster through the noise.
Per parameter: Learning rate α sets adaptation speed — 0.15–0.25 in fast-rotating regimes, 0.05–0.10 in stable ones. Discount γ sets foresight — higher weights long-run reward (0.95–0.99 for swings, 0.85–0.92 for scalps). ε-Decay sets the length of the exploration phase — larger explores longer and learns more cautiously. Switching cost doubles as a direct knob on trade frequency.
💡 How to Use in Practice
The core read is the agent's stance × conviction. A flip to Long (triangle marker) with high conviction and a rising cumulative reward reads as a tailwind for buying dips. The policy heatmap is a powerful context tool: by reading the colors of the cells adjacent to the current regime (the glowing cell), you can anticipate how the agent will act if the market shifts slightly. When ε is still high, the policy is undecided, so treat signals as informational only.
For multi-timeframe work, confirm the macro bias from the higher-timeframe stance (1D), then execute aligned flips on a lower timeframe (1H–4H). Layered over market structure (S/R, order blocks) or volume, it adds which regime, and with what conviction, the agent chooses to go long — useful confirmation context.
⚠️ Important Notes
Until the warmup period (default 300 bars) and the exploration phase pass, actions are largely exploratory (random). Reloading the indicator, or changing settings/seed, makes the agent relearn across the entire history from scratch — learning state is not persisted. The panel's "Policy P&L" is an in-sample, while-learning metric that does not fully account for switching cost or fill slippage; it is not a backtest or forward result. The 27-state tabular design is intentionally coarse — it learns a regime policy, not fine price structure. Decisions update on confirmed bars, and the agent's stance is not a direct buy/sell instruction.
🚨 Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial or investment advice. Past performance is not indicative of future results. All trading involves risk. Use it alongside your own thorough testing and sound risk management; all trading decisions remain solely your own responsibility. Gösterge
Volatility Bands Using t-Distribution & Prediction IntervalsThis indicator is a statistical tool designed to project a dynamic range where the next asset price is expected to fall within a specific level of confidence.
Unlike standard volatility bands, a prediction interval is a statistical range that estimates where a single future observation will fall, given a specific probability. Because predicting a single future outcome introduces more inherent uncertainty than predicting an average, these bands are wider and mathematically tighter for forecasting next-bar anomalies.
How it Works
This indicator uses a Student's t-distribution (or an optional z-distribution for performance) to calculate historical volatility thresholds.
Finding the Estimated t-distribution
When you select a 95% Confidence Level, the script sets an error alpha of 5% (1 - 0.95). Because asset price movement can deviate to either the upside or downside, it splits this error equally into both tails (a two-tailed test). The script normalizes this, targeting an exact area of 0.025 (2.5%) in the extreme tails of the curve.
To find where that target area lies, the script reconstructs the Probability Density Function (PDF) of the Student's t-distribution. The height of the curve depends heavily on the Degrees of Freedom (df = length - 1).
Because Pine Script doesn't have a native Gamma function, the script uses double factorials to calculate the complex math coefficients. If your sample size (length) is exceptionally high (>300), the t-distribution naturally mirrors a regular normal distribution, so it switches to a standard Gaussian curve equation to save some time.
// Calculate double factorial
double_fac(int n) =>
float res = 1.0
int curr = n
while curr > 1
res := res * curr
curr := curr - 2
res
// t-distribution formula
cur_dist(float x, int cur_df) =>
float res = 0.0
if cur_df > 300
res := 0.3989422804014326779 * math.exp(-x * x * 0.5)
else
float coeff = double_fac(cur_df - 1) / (math.sqrt(cur_df) * double_fac(cur_df - 2) * (cur_df % 2 == 0 ? 2.0 : math.pi))
res := coeff * math.pow(1.0 + x * x / cur_df, -0.5 * (cur_df + 1))
res
To find the approximate t-value that corresponds to our target tail area, the script performs numerical integration using the Trapezoid Rule (trapezoid_reverse). This is the most time consuming part.
// Reverse trapezoidal to calculate t-value from area
trapezoid_reverse(float p, int cur_df) =>
float max_p = 0.5
float max_stat = 300.0
float add_prec = 1.0
float result_i = 0.0
if p == max_p
result_i := 100000000.0 // Infinity
else
float trap_sum = 0.0
float gap_width = p / (add_prec * 1250.0)
float i = 0.0
float last_func = cur_dist(0.0, cur_df)
while trap_sum < (2500.0 * add_prec) and i < max_stat
i := i + gap_width
trap_sum := trap_sum + last_func
last_func := cur_dist(i, cur_df)
trap_sum := trap_sum + last_func
result_i := i
result_i
Calculating the Prediction Interval
Once the t-critical value is found, it is then put into the standard prediction interval formula. The script uses EMA instead of SMA to improve responsiveness to current trends.
float prediction_interval_top = mean + tCrit * stdev * math.sqrt(1 + 1/length)
float prediction_interval_bot = mean - tCrit * stdev * math.sqrt(1 + 1/length)
Because the calculations for the t-distribution estimates are computationally expensive, you can select the lookback window for using the t-distribution. You can also choose to use the faster z-score for historical bars.
Note 1: The larger the sample size, the smaller you may have to set your lookback window in order to fit within the execution time limits.
You can use this for:
Overbought/Oversold, Mean reversion signals
Dynamic Stop-loss/Take-profit (SL/TP)
1. Overbought/Oversold/Mean Reversion
The indicator creates a red background to indicate that the candlestick has broken above the top 95% prediction interval band. It can be interpreted as a potential reversal.
2. Dynamic Stop-loss/Take-profit (SL/TP)
You can utilize the plotted mean and the confidence interval as entry/exit points. For example, you could put a stop-loss at the bottom band, and a take profit at the top band.
Alerts:
Price Above Top PI (Close crossed out)
Price Below Bottom PI (Close crossed out)
High Above Top PI (Wick touched/pierced top)
Low Below Bottom PI (Wick touched/pierced bottom)
Settings:
Length: The size of the sample for the standard deviation & mean calculations. 30 is recommended.
Source: Used for standard deviation & mean calculations. For example: Changing the source to 'high' would make the indicator predict the range of the next 'high'.
Confidence Level: Dictates how wide the bands should be. A 95% confidence level is default. Must be entered as a decimal between 0 and 1.
Lookback Length: Used to limit the amount of bars to back calculate the prediction interval using the t-distribution. Default is 300.
Use z-score: Use the z-score to calculated past values. Note that this will introduce error. For example, for a sample size of 30 and a 95% confidence level, using a z-score instead of a t-score will introduce a ~4.2% error in your interval width, causing your actual prediction interval to drop from 95% down to ~94.0%.
Background Colors:
Green: The low/close of the candle breached the lower band. Potential bullish reversal.
Red: The high/close of the candle breached the upper band. Potential bearish reversal.
Limitations:
The indicator assumes that the data follows a bell curve, which the markets do not.
The indicator may lag behind actual price action.
The indicator may produce false signals.
The indicator does not predict future prices.
Disclaimer: All trading decisions and responsibilities rest solely on the user of the indicator. Gösterge
50-MA Extension Dot [ATR / % / Points]50-MA Extension Dot marks when price has moved a defined distance above a daily moving-average anchor. The goal of the script is to help traders study when price becomes extended relative to its daily trend structure, rather than judging a move by price alone.
The script supports three extension methods: ATR Extension, Percent, and Points. ATR Extension compares the distance from price to the daily moving average against the instrument’s daily ATR, making the reading volatility-adjusted. Percent mode measures how far price is above the moving average in percentage terms. Points mode measures the raw point distance above the moving-average anchor.
The moving-average type, moving-average length, threshold method, threshold value, ATR length, and extension source are customizable so traders can study past moves and build their own rules. For example, users can test how a symbol historically behaved when it became one ATR, two ATRs, a fixed percentage, or a fixed point distance above its daily moving-average reference.
When the selected threshold is reached, the script plots a small dot above the candle. The dot is not a standalone buy or sell signal. It is a visual marker showing that price has reached a defined extension zone relative to the chosen daily moving-average reference.
The script can also display the daily moving average, an optional threshold line, and a small table showing the current daily moving average, daily ATR, extension price, percentage distance from the moving average, ATR percentage, and ATR extension value.
This tool is useful for studying stretched moves, breakout extensions, momentum exhaustion, and conditions where price may be moving too far too quickly above its daily trend anchor. Because different symbols have different volatility profiles, the customizable inputs allow traders to compare past extensions and develop rules that fit their own process.
This indicator does not predict future price movement. It is a contextual extension tool designed to measure distance from a daily trend reference and help traders research historical extension behavior. Gösterge
Squeeze Vector [Gabremoku]Squeeze Vector is a squeeze-based volatility breakout tool that combines Bollinger/Keltner compression detection, directional pressure flow, and a first-expansion state machine to help traders identify high-probability post-squeeze breakout setups.
The core idea is simple: compression precedes expansion. When Bollinger Bands shrink inside Keltner Channels, the market is coiling — and when that squeeze releases, the first directional signal can carry strong momentum. This script gives that process a structured visual and logical framework.
Core Concept — Squeeze → Release → Direction
A BB/KC squeeze occurs when Bollinger Bands, which reflect price volatility through standard deviation, contract inside Keltner Channels, which reflect typical range through ATR. This gap between the two envelopes is used as a proxy for volatility compression.
When BB width becomes smaller than KC width, the script identifies a Squeeze state. When it releases, the script enters an Armed state and opens a short post-squeeze window during which it looks for the first valid directional expansion.
Importantly, the squeeze release alone does not confirm direction. That is why the script adds multiple expansion confirmation filters before triggering a signal.
What it shows
Squeeze Vector Oscillator — a single line that rises as BB/KC compression increases. When it crosses above 50, the squeeze is active. The oscillator turns purple during squeeze states for fast visual identification.
Pressure Flow Histogram — a volume-weighted directional pressure value that reads where price closed within the candle range and weights it by volume relative to its moving average. Positive values indicate bullish pressure, negative values indicate bearish pressure.
Bollinger Overlay on Price — during squeeze states, the script renders Bollinger Bands directly on the main chart with gradient fills, making it easy to see where price is relative to the compressed structure.
LONG / SHORT signals — primary directional signals are placed on the main chart after a post-squeeze expansion bar meets all required conditions. Optional lighter repeat markers can be shown for follow-through confirmation.
Dashboard with live checklist — the on-chart dashboard shows the current state, regime, pressure, vector value, and a 6-point checklist for both long and short setups, with filled/empty circles to show how many conditions are currently met.
Signal Logic
The signal engine works as a state machine with three phases:
Squeeze — BB/KC compression is active. No signal is generated. The dashboard shows SQUEEZE.
Armed — the squeeze just released. The script opens a short expansion window and waits for directional confirmation. The dashboard shows ARMED.
Expansion signal — within the expansion window, if a valid directional bar forms with sufficient pressure, body size, and break condition, a LONG or SHORT label is placed on the main chart.
Signal direction is confirmed by checking:
Basis side: price above or below the BB basis
Pressure: smoothed directional pressure above threshold
Strong pressure: optional stronger filter
Body quality: minimum body-to-candle-range ratio
Break condition: higher high or lower low
Regime: optional EMA 200 trend filter
When both long and short conditions are simultaneously valid, the stronger pressure side wins. If pressure is equal, raw pressure bias decides.
States and Dashboard
The dashboard tracks the full machine at a glance:
Row Content
SQZ Squeeze ON / OFF
SEQ ARMED or READY
REG Trend regime (BULL / BEAR / OFF)
BIAS Current directional pressure bias
P Pressure Flow value
V Vector Oscillator value
Checklist 6-point LONG and SHORT condition matrix
The checklist can be set to appear only during Squeeze or Armed states to reduce visual noise when no setup is forming.
Features
✅ Bollinger/Keltner squeeze detection via ratio oscillator
✅ Volume-weighted directional pressure flow
✅ Post-squeeze first expansion state machine
✅ Armed → signal transition logic
✅ 6-point entry checklist for both long and short
✅ EMA 200 regime filter
✅ Bollinger overlay with gradient fill during squeeze
✅ LONG / SHORT signal labels on main chart
✅ Optional follow-through repeat markers
✅ Repeat window filter to suppress signal clustering
✅ Strategy mode: Long, Short, or Both
✅ Fully configurable dashboard with size and offset settings
✅ Alert conditions for BUY, SELL, and squeeze activation
How to use
A practical workflow:
Watch for the Vector Oscillator to cross above 50 and turn purple — that is the squeeze state.
When it releases below 50, the dashboard switches to ARMED.
In the expansion window, check the checklist: more filled circles on one side indicate stronger directional alignment.
A LONG or SHORT label confirms a valid first expansion signal.
Use the Pressure Flow histogram to gauge how strong and consistent the directional push is.
The squeeze release alone is not a signal. Direction is only confirmed when the expansion bar quality, pressure, and structure checks all align.
Notes
Like all squeeze-based tools, Squeeze Vector is most effective when used alongside price structure context. Squeezes release into strong moves, but not every release produces a sustained trend — volume, higher timeframe context, and support/resistance levels can all affect follow-through quality.
Author: Gabremoku
Pine Script v6 Gösterge
Adaptive Trend Ribbon [Alpha Extract]A sophisticated adaptive trend-following framework that combines volatility-responsive moving averages, ribbon stack analysis, ATR-based trend rails, ADX confirmation, pullback continuation signals, and a real-time confidence dashboard into one complete market regime tool. The indicator is designed to identify bullish and bearish trend environments, filter weak conditions, highlight confirmed trend flips, and provide structured stop guidance through an adaptive ATR rail. By adjusting ribbon sensitivity based on current volatility, the system aims to stay responsive during expansion phases while remaining smoother during quieter market conditions.
🔶 Adaptive Volatility-Based Ribbon Engine
Implements a multi-layer adaptive EMA ribbon that automatically modifies its effective moving-average lengths based on current volatility conditions. When volatility expands, the ribbon becomes more responsive by shortening its dynamic length. When volatility contracts, the ribbon lengthens to reduce noise and avoid unnecessary whipsaw.
volRatioRaw = atrAverage > 0 ? atr / atrAverage : 1.0
volRatio = clamp(volRatioRaw, 0.35, 2.75)
emaFast = adaptiveEma(src, baseFast, volRatio, adaptStrength)
This creates a trend ribbon that adapts to the market environment instead of relying on fixed moving-average behaviour across all conditions.
🔶 Six-Layer Trend Structure
Uses six adaptive moving averages ranging from fast to anchor length to define market structure across multiple trend speeds. The ribbon includes fast, mid, slow, and anchor components, allowing traders to see whether short-term momentum is aligned with broader trend direction.
A clean bullish trend forms when the ribbon is stacked from fastest above slowest, while a clean bearish trend forms when the ribbon is stacked from fastest below slowest. Mixed ribbon conditions indicate compression, transition, or weaker directional conviction.
🔶 Bullish & Bearish Stack Detection
Identifies strong directional alignment through full ribbon stack confirmation. Bullish stack conditions require every faster ribbon layer to sit above the slower layer beneath it, while bearish stack conditions require the opposite alignment.
This gives traders a simple way to distinguish clean trend environments from sideways or indecisive price action.
🔶 ATR Trend Rail System
Features a built-in ATR-based trend stop that acts as the main regime rail. The rail flips direction when price breaks through the active stop level, creating a clear bullish or bearish trend state.
longCandidateStop = railBasis - atr * atrMult
shortCandidateStop = railBasis + atr * atrMult
railDirection := close < trendStop ? -1 : 1
The stop can be based on the ribbon midline, close, or HL2, giving traders flexibility in how the trend rail is anchored.
🔶 Regime Flip Signal Logic
Generates long and short signals when the trend rail flips direction and the confirmation conditions are satisfied. A bullish signal occurs when the regime flips into bullish structure, while a bearish signal occurs when the regime flips into bearish structure.
Signals are filtered through ADX and directional movement confirmation when enabled, helping reduce low-quality flips during weak or choppy market conditions.
🔶 ADX & Directional Movement Confirmation
Integrates ADX confirmation to measure whether the market has enough directional strength to justify a trend signal. The system also checks directional movement by comparing +DI and -DI, allowing bullish regimes to favour positive directional pressure and bearish regimes to favour negative directional pressure.
This confirmation layer helps separate true trend expansion from random price movement.
🔶 Pullback Continuation Alerts
Includes optional pullback continuation logic designed to identify trend resumption after price interacts with the adaptive ribbon. When price pulls into the ribbon area and then closes back in the trend direction, the system can trigger continuation alerts.
This is useful for traders who prefer entering after a trend has already been established rather than only trading the initial regime flip.
🔶 Confidence Scoring Framework
Calculates a real-time trend confidence score by combining multiple components of trend quality, including ribbon stack alignment, price position relative to the ATR rail, ADX strength, directional movement, and spread between fast and anchor ribbon layers.
The score provides a quick snapshot of how strong and confirmed the current trend environment is.
🔶 Dynamic Trend Coloring System
Uses adaptive color logic to visually represent bullish, bearish, and neutral/mixed conditions. Candles, ribbon lines, fills, the ATR stop rail, and the status panel all update according to the current regime.
When ADX confirmation is enabled but the filter has not passed, the system fades the trend color to show that the regime exists but confirmation is weaker.
🔶 Real-Time Status Panel
Features a compact dashboard that displays the most important trend information directly on the chart. The panel includes:
• Current regime
• Confidence percentage
• Confirmation status
• ADX value
• Volatility ratio
• Ribbon stack condition
• Active stop level
This allows traders to quickly assess whether the market is bullish, bearish, filtered, mixed, or entering a stronger trend phase.
🔶 Flexible Risk Rail Basis
Allows the ATR stop rail to be calculated from different price references depending on the trader’s preferred style. Ribbon Mid creates a smoother institutional-style trend rail, Close makes the rail more reactive, and HL2 provides a balanced price reference.
This flexibility makes the indicator suitable for both faster trend-following styles and slower swing-trend systems.
🔶 Clean Overlay Visual Design
Displays the full adaptive ribbon directly on price with optional candle coloring, background regime shading, trend stop plotting, and signal markers. The ribbon uses layered transparency to maintain chart readability while still showing the strength and direction of the trend structure.
The result is a clean visual layout that can be used as a primary trend framework or as a confirmation layer alongside other systems.
🔶 Comprehensive Alert System
Includes alerts for the most important trend events:
• Adaptive Ribbon Long
• Adaptive Ribbon Short
• Bullish Pullback Continuation
• Bearish Pullback Continuation
• Long Trend Exit
• Short Trend Exit
These alerts allow traders to monitor trend flips, pullback continuations, and invalidation events without needing to constantly watch the chart.
🔶 Why Choose Adaptive Trend Ribbon ?
This indicator provides a complete adaptive trend-following environment by combining responsive moving-average structure, volatility-adjusted behaviour, ATR-based trend rails, ADX confirmation, continuation logic, and live confidence scoring. Instead of relying on a single moving average or fixed trend signal, it evaluates multiple layers of trend quality before confirming direction.
The adaptive ribbon helps traders understand whether the market is strongly aligned, weakening, transitioning, or mixed. The ATR rail provides a clear trend invalidation reference, while the confidence panel gives immediate context on whether the trend has enough structure and strength behind it. Perfect for trend-following traders, swing traders, momentum traders, and systematic traders who want a cleaner way to identify confirmed bullish and bearish regimes with built-in risk guidance. Gösterge
SoSa Smart Trend ProSoSa Smart Trend Pro
Advanced All-in-One Trading Indicator
SoSa Smart Trend Pro is a powerful institutional-grade trading indicator designed to help traders identify high-probability opportunities through advanced trend analysis, volume confirmation, momentum filters, Fair Value Gap detection, market structure analysis, and session-based trading tools.
Built for Forex, Stocks, Futures, Indices, and Cryptocurrency markets, SoSa Smart Trend Pro combines multiple professional trading concepts into a single indicator, allowing traders to make faster, smarter, and more confident decisions.
🚀 Core Features
📈 Advanced Trend Detection
Choose from multiple moving average types:
EMA
SMA
WMA
VWMA
RMA
HMA
DEMA
TEMA
Bollinger Basis
The moving average dynamically changes color to instantly identify market conditions:
🟢 Bullish Trend
🔴 Bearish Trend
🟡 Neutral Market
🕯️ Smart Engulfing Pattern Detection
Automatically detects:
Bullish Engulfing Patterns
Bearish Engulfing Patterns
Advanced body-size filtering helps eliminate weak setups and highlights stronger reversal opportunities.
📊 Volume Confirmation System
Filters market signals using real-time volume analysis.
Features include:
Volume SMA comparison
Adjustable volume multiplier
High-volume breakout confirmation
Helping traders avoid low-quality entries during weak market participation.
⚡ Institutional Fair Value Gap Detection
Automatically identifies market imbalances used by professional traders.
Includes:
Bullish Fair Value Gaps
Bearish Fair Value Gaps
ATR-based minimum gap sizing
Adjustable zone extensions
Dynamic FVG management
Ideal for identifying retracements, continuation setups, and liquidity zones.
🗽 New York Session Tracker
Monitor the most active trading session with:
Automatic New York Session Box
Session High & Low Tracking
Session Labels
Extended High/Low Levels
Perfect for traders who focus on market open volatility and liquidity sweeps.
🔵 Dynamic Support & Resistance Levels
Automatically plots key market structure zones based on pivot analysis.
Benefits:
Identifies potential reversal areas
Highlights important reaction zones
Improves entry and exit timing
📉 RSI Momentum Filter
Built-in Relative Strength Index analysis:
Custom RSI Length
Overbought Detection
Oversold Detection
Trade Confirmation Filter
Adds an additional layer of momentum validation.
〰️ MACD Confirmation Engine
Uses MACD crossover and histogram strength to confirm momentum.
Detects:
Bullish Momentum
Bearish Momentum
Trend Continuation Opportunities
Reducing false entries and increasing signal quality.
〰️ Bollinger Bands Integration
Monitor market volatility with built-in Bollinger Bands.
Features:
Adjustable Length
Adjustable Deviation Multiplier
Volatility Expansion Detection
Useful for breakout and mean-reversion strategies.
🎯 Smart Buy & Sell Signals
Signals are generated only when multiple confirmations align.
Signal conditions may include:
✅ Trend Direction
✅ Moving Average Confirmation
✅ Engulfing Pattern Detection
✅ Volume Confirmation
✅ RSI Validation
✅ MACD Confirmation
This multi-layer approach helps filter market noise and improve trade quality.
📊 Confidence Score Technology
Every trade signal includes a confidence rating from 0% to 100%.
The score is calculated using:
Trend Strength
Volume Activity
Fair Value Gap Confirmation
Engulfing Patterns
MACD Momentum
Price Structure Alignment
Allowing traders to quickly assess the quality of each setup.
🖥️ Professional Market Dashboard
The integrated information panel displays:
Market Trend
Volume Status
RSI Condition
MACD Status
Fair Value Gap Activity
New York Session Status
Confidence Score
Current Trading Signal
All critical market information is available in one location.
🔔 Real-Time Trading Alerts
Receive alerts for:
Buy Signals
Sell Signals
RSI Overbought Conditions
RSI Oversold Conditions
Bullish FVG Detection
Bearish FVG Detection
New York Session Open
Stay connected to the market without constantly watching the chart.
💎 Why Traders Choose SoSa Smart Trend Pro
✔ Combines multiple indicators into one
✔ Reduces chart clutter
✔ Improves signal quality
✔ Identifies institutional market imbalances
✔ Tracks trend, momentum, volume, and volatility
✔ Provides confidence-based trade scoring
✔ Suitable for scalpers, day traders, swing traders, and position traders
✔ Works across Forex, Crypto, Stocks, Futures, and Indices
Trade Smarter. Trade With Confidence.
SoSa Smart Trend Pro is built to provide a complete market analysis solution, combining trend identification, momentum confirmation, institutional concepts, and intelligent signal generation into one professional-grade trading tool. 📈🔥
Tagline:
"See the Trend. Trust the Signal. Trade with Confidence." 🚀 Gösterge
Gaspard98 - Carter Squeeze On Chart / Signals# Gaspard98 — Carter Squeeze On Chart / Signals
## Overview
The **Carter Squeeze** is an on-chart implementation of John Carter's well-known *TTM Squeeze* concept, rebuilt as a clean overlay with discrete **Buy / Sell signals**. It detects periods of volatility compression — when a market coils up before an expansion move — and fires a directional signal the moment that energy is released.
Unlike a classic momentum-pane squeeze, everything here lives directly on the price chart: compression state, momentum bias, trend, and entries are all visible at a glance, with no second window to monitor.
---
## The Concept Behind the Squeeze
Carter's method is built on a single, elegant observation: **when Bollinger Bands contract inside the Keltner Channels, the market is in a low-volatility "squeeze."** Volatility is mean-reverting, so a tight squeeze tends to be followed by a sharp expansion. The trade is not the squeeze itself — it's the *release* (the "fire"), taken in the direction of momentum.
This script measures that compression at **three intensity levels** (TTM Squeeze Pro style) rather than a single on/off state, so you can distinguish a mild coil from an extreme one.
---
## How It Works
**1. Compression detection**
Bollinger Bands (default 20, 2.0) are compared against three Keltner Channels built from the average True Range, at multipliers 2.0 / 1.5 / 1.0:
- **No squeeze** — bands are outside the widest Keltner (market is expanding)
- **Low compression** — mild coil
- **Mid compression** — moderate coil
- **High compression** — the tightest state; bands sit inside the narrowest channel
**2. Momentum**
A linear-regression oscillator measures price relative to the mid-channel (the classic Carter momentum formula). Its sign defines directional bias (bullish / bearish) and its slope defines whether momentum is accelerating or fading.
**3. Signals**
The default trigger is the **squeeze fire**: the bar where compression releases. A **BUY** prints if momentum is positive at the release, a **SELL** if it is negative. An optional alternative mode triggers on a **momentum zero-cross** instead.
---
## Signal Logic & Filtering
- **Trigger — Squeeze fire** (default): entry on the release of a compression, in the direction of momentum. This is the purest expression of Carter's method.
- **Trigger — Momentum cross**: entry when momentum crosses the zero line, regardless of squeeze state.
- **Require accelerating momentum** (default on): only allows a BUY when momentum is rising and a SELL when it is falling, filtering out weak, fading releases.
- **Confirm on close** (default on): signals evaluate only on closed bars, making them **non-repainting**. Disable it for faster, intrabar-reactive signals at the cost of mid-bar flicker.
---
## Visual Features
- **Buy / Sell labels** plotted directly below / above the bars.
- **Squeeze state dots** along the bottom of the chart, color-coded by intensity:
- green = no squeeze
- blue = low compression
- orange = mid compression
- red = high compression
- **Background tint** while a squeeze is active (color reflects intensity).
- **Candle coloring** driven by momentum (bright = accelerating, faded = fading).
- **Trend line** (the basis) colored by momentum bias.
- **Status table** in the top-right corner showing squeeze level, momentum value + direction, current bias, and the last signal.
- Optional **Bollinger + Keltner band overlay** so you can visualize the compression itself.
---
## Settings
**Squeeze**
- Source, Bollinger length & multiplier
- Keltner length and the three compression multipliers (low / mid / high)
**Signals**
- Trigger mode (Squeeze fire / Momentum cross)
- Require accelerating momentum
- Confirm on close (non-repaint)
**Visual**
- Toggle bands, background, dots, candle coloring, trend line, status table
- Custom Buy / Sell colors
---
## How to Use It
1. Watch for a tightening sequence — dots moving from green toward orange and red signal building compression.
2. The **brighter the candles** and the larger the momentum value, the stronger the directional conviction.
3. A signal prints when the squeeze releases. Treat the release as a *timing* tool, not a standalone system — combine it with structure, higher-timeframe trend, and your own risk management.
4. Tighter compressions (red) before a fire tend to precede the cleanest expansions.
Works on any market and timeframe (futures, indices, FX, crypto, equities). Higher timeframes generally yield fewer but cleaner signals.
---
## Alerts
Two alert conditions are built in — **BUY** and **SELL** — ready to attach in TradingView's alert dialog. The default message embeds the ticker and close price and can be reshaped for any webhook or automation endpoint.
---
## Notes
- Default Bollinger / Keltner parameters follow Carter's classic 20-period configuration; adjust to your instrument's volatility profile.
- With *Confirm on close* enabled, signals are fixed once the bar closes and do not repaint.
---
*This indicator is a technical-analysis tool provided for educational and informational purposes only. It is not financial advice and does not guarantee any outcome. Trading involves substantial risk of loss — always test thoroughly and manage risk according to your own plan.* Gösterge
Guppy MMA Mean Reversion SignalsThe Guppy MMA Mean Reversion System is a trend-following mean reversion tool designed to identify high-probability pullbacks within established trends. By combining the classic Guppy Multiple Moving Average (GMMA) with volatility, volume, and momentum filters, this script aims to reduce the "noise" often found in standard moving average cross strategies.
The Concept: Why this Works
Standard GMMA indicators are excellent for visualizing trend strength but often lack precise entry triggers or filters to avoid entering during periods of low volume or extreme exhaustion. This script addresses these limitations by integrating four distinct analytical components:
- GMMA Ribbons (Trend & Reversion Zones) : We use two groups of EMAs (Short-term and Long-term). The Long-term group defines the "institutional" trend. Our entry logic looks for price to revert from the short-term trend back into the long-term trend zone—a classic sign of a healthy pullback.
- CVD Confluence (Volume Confirmation) : Using Cumulative Volume Delta (CVD) based on candle-body delta approximations, the script ensures that volume flow supports the entry direction. This prevents entering pullbacks that lack the necessary buying/selling pressure to resume the trend.
- ATR Volatility Filter (Statistical Spacing) : To avoid "choppy" entries, this filter requires the price to be at a statistically significant distance from the EMA based on market volatility (ATR). This ensures you are entering at a true "discount" rather than in a sideways market.
- RSI Exhaustion Filter (Momentum Safety) : We utilize RSI to ensure that a reversion hasn't reached an overextended state. For example, it prevents buying a pullback if the RSI indicates the asset is already in an overbought exhaustion phase.
How to Use
- Long Entries (Green Circles) : Triggers when the Long-term ribbon is bullish, and price pulls back to touch the Long-term EMA group, provided the CVD, ATR, and RSI conditions are met.
- Short Entries (Red Circles) : Triggers when the Long-term ribbon is bearish, and price rallies to touch the Long-term EMA group, filtered by volume and momentum.
- Exits (Labels) : Exit signals appear when price successfully reverts back to the "fast" Short-term group, marking the completion of the mean reversion move.
Key Features & Customization
- Independent Toggles : You can independently turn on/off buy signals, sell signals, and their respective exits to suit your specific trading style (e.g., only trading the long side).
- Signal Cooldown : Includes a customizable "bar count" cooldown to prevent multiple overlapping signals during high-volatility periods.
- Comprehensive Settings : Fully adjustable EMA lengths, ATR multipliers, and RSI thresholds to adapt the system to different timeframes and asset classes (Crypto, Forex, Stocks).
Settings Guide
- Use ATR Filter : Increase the multiplier for more conservative, wider entries.
- Use CVD Filter : Enable to ensure volume delta is trending with your entry.
- Use RSI Filter : Helps avoid "catching falling knives" by filtering out trades during extreme momentum spikes. Gösterge
Gösterge
Bollinger Band [scoopup]Overview
A Bollinger Bands–based indicator that shows trend direction (up/down) through the basis line color, displays band width (volatility) as a percentage, and marks the most recent meaningful lows (demand zones) on the weekly and daily timeframes as boxes. It lets you view statistical volatility and the real low zones where buying previously stepped in — all on a single chart.
Default settings are Length 21 and StdDev 1.618, based on the Fibonacci number (21) and the golden ratio (1.618).
Components
1. Bollinger Bands (Upper / Basis / Lower)
Defaults: Length 21, StdDev 1.618
Upper band, basis (middle), and lower band. The bands widen and narrow with volatility.
2. Basis Line Trend Color (Daily-based)
The color of the middle basis line indicates trend direction.
Logic: over a set lookback, it compares the cumulative size of the "close-to-lower" area (red) versus the "upper-to-close" area (green).
Red area dominant → uptrend → basis line GREEN
Green area dominant → downtrend → basis line RED
The longer the close stays near the lower band (larger red area), the more it is read as base-building before a move higher.
This color is always calculated from Daily data, regardless of the chart timeframe. Whether you view it on the 15m, 1h, or 4h chart, the daily trend color stays consistent.
3. Fill
Upper band ↔ close: semi-transparent green
Close ↔ lower band: semi-transparent red
Lets you quickly read where the close sits within the bands.
4. Band Width (%)
Formula: (Upper − Lower) / Basis × 100
Displays the current band width in a corner table as Band Width: X.XX%.
Lower = volatility contraction (squeeze) → often precedes a large move; higher = volatility expansion.
The Data Window also shows band width % and band width (price difference), including on historical bars.
5. Recent Lows
Weekly recent low = yellow box / Daily recent low = red box
Shows only the most recent pivot (swing) low that sits below the current close. (Lows above the close are skipped; if the latest low is above the close, the prior low is used instead.)
Box height spans the low ↔ the close at that point, and extends to the right to show a still-valid support/demand zone.
How to Read It
Basis green + close near the lower band → watch for a potential bounce after base-building.
Basis red + close near the upper band → watch for overextension/pullback risk.
Band Width % contracting (squeeze) → watch for an upcoming volatility expansion.
Recent low boxes (yellow/red) act as first support candidates on a pullback. A close below the box signals support failure.
Key Settings
Bollinger Bands: Source, Length (default 21), StdDev (default 1.618), Band Color / Width / Style
Basis Line: Show Basis, Basis Width, Ratio Length, Up / Down Color
Fill: Show Fill, Upper / Lower Fill Transparency
Band Width: Show Band Width %, Table Position, Text Size
Recent Lows: weekly/daily toggles, Pivot Length, Box Color
Tips
This is a supporting tool for reading trend direction + volatility + support zones together, not a standalone trade signal.
Reliability increases when the daily trend color and a recent low box line up in the same area.
Adjust StdDev and Ratio Length to fit each instrument's volatility.
Disclaimer
This indicator is for reference only and does not guarantee trading profits. All trading decisions and responsibility rest solely with the user. Gösterge
Tristan HTF Master - Multi Timeframe OverlayWelcome to my indicator, a powerful multi-timeframe (MTF) visualization tool designed specifically for traders who rely on "Candle Behavior Strategies" and precise timing strategies. I use this indicator as an orientation
If you base your trades on the internal mechanics of Higher Timeframe (HTF) candles—such as tracking the open, high, low, and close of a 1-hour candle while executing on the 1-minute or 5-minute chart—this indicator is built for you.
The Core Concept: Time-Based Candle Behavior: Depending on your strategy in my opinion it is best suited for Time Based Strategies.
This indicator was developed with a specific structural trading strategy in mind (heavily inspired by concepts of "Tom Trades" Candle Behavior Reversal. So respects to him. The core philosophy revolves around observing how a Higher Timeframe candle (e.g., the 1H candle) behaves during its lifespan.
Often, in ranging or consolidating markets, a 1H candle will exhibit a distinct pattern:
First 30 Minutes (The Trap): The market creates a sudden Liquidity Sweep accompanied by an Overextension. This often traps breakout traders.
The Reversal (At ~30 Mins): Right around the midpoint of the candle's lifespan, the market loses momentum, reverses, and creates a Type 3 Market Shift / Break of Structure (BoS) on the lower timeframes.
Last 30 Minutes (The Retrace): The price retraces back into the HTF candle's range, often pulling back up to 50% of the initial overextension before the candle closes.
Because precise timing is everything in this strategy, the Tristan HTF Master visually draws the HTF candle directly onto your lower timeframe chart from the very first second it opens. You can visually track exactly when the 30-minute mark is reached without having to constantly switch timeframes or check the clock.
How to Trade the Strategy Using This Indicator
While this tool can be used for any MTF strategy, here is the optimal step-by-step setup it was designed for:
Market Condition: Identify a ranging market. Avoid massive, aggressive trending environments. Look for longs in the lower third of the range, and shorts in the upper third.
The Setup: Wait for a Liquidity Sweep and an Overextension during the first half of the HTF candle (e.g., the first 30 mins of the 1H box).
The Trigger: Look for a Type 3 Market Shift (Break of Structure) on the lower timeframe, confirming the exhaustion of the overextension.
The Entry: Pull your Fibonacci tool over the Type 3 shift. Place a limit order at the 50% retracement level of that shift (ideally backed by a factual shift confirmation).
Stop Loss (SL): Placed strictly above the local high (for shorts) or below the local low (for longs) of the sweep.
Take Profit (TP): Target the 50% retracement level of the entire initial overextension.
Indicator Features
Dynamic HTF Boxes: Overlays 15m, 30m, 1H, or 4H candles perfectly onto your current LTF chart. The boxes span the full width of the time period from the moment they open.
100% Transparent Bodies: The HTF box bodies are fully transparent. This allows you to clearly read the internal Lower Timeframe (LTF) price action without visual clutter.
Real-Time Wicks: The wicks of the HTF candle update dynamically in the center of the box as new highs and lows are formed.
Live Countdown Timer: Includes a clean, built-in countdown label attached to the active HTF candle, showing exactly how much time is left until the candle closes.
Disclaimer: This script and the described strategy are for educational purposes only and do not constitute financial advice. Past performance is not indicative of future results. Always backtest strategies thoroughly and manage your risk appropriately. Gösterge
quick levels and zonesManual Levels and Zones Plotter is a lightweight, high-utility tool designed to instantly map out your entire technical analysis framework from a single text block. Simply paste your raw text notes, level levels, or automated scanner outputs directly into the indicator settings, and the script handles the rest.
🚀 Key Features
Instant Bulk Plotting: Parses multiple lines of text simultaneously. No more manual line drawings or repeating actions for every single price point.
Dynamic Range & Zone Detection: If a line contains a price range (e.g., 742–746 major resistance zone), the script automatically detects it and draws a shaded visual box (zone) instead of a single line.
Smart Color Coding: Automatically identifies key market terms within your text notes and applies contextual color profiles:
🔴 Red: Exhaustion, Resistance, Outliers
🟢 Green: Support, Expansion Targets
🟠 Orange: Pivot points, Line-in-the-sand levels
⚪ Gray: Standard micro or unclassified levels
Smart Label Staggering: Labels are dynamically staggered off the right edge of the price action (bar_index + spacer) to prevent overlap and maintain a pristine, readable chart view.
Replay & Real-Time Performance Optimized: Built using persistent garbage-collection arrays running strictly on barstate.islast. It renders flawlessly during historical Bar Replay sessions without lagging your chart or cluttering background memory.
🛠 How to Use It
Open the indicator settings window.
In the "Paste Levels Here" text area, paste your levels. Each level must be on its own line, starting with the numeric price value.
Example format:
Plaintext
766.70 outlier monthly resistance
742–746 major resistance zone
733.55 daily pivot / line in the sand
708.43 weekly support
Toggle "Extend Across Entire Screen?" to choose between historical infinite projections or localized, clean right-side tracking. Gösterge
Ultimate Scalp MoBo + RSI + Mult-MA + MACD ConfigurationOverview
The Ultimate Scalp Configuration is a comprehensive trend-following and pullback execution system designed specifically for scalpers and day traders. Rather than simply overlaying indicators, this script synchronizes three distinct technical layers—Trend, Volatility-Adjusted Momentum, and Price Action—to identify high-probability entries at the precise moment a pullback ends and a trend resumes.
How It Works (The "Synergy")
This script uses a modular approach to filtering out "market noise," which is the primary challenge in lower-timeframe scalping:
- The Trend Layer (Multi-MA Engine): The script utilizes a fanned-out Moving Average structure (9, 50, and 200 lengths). Users can choose from 12 advanced MA types, including Zero-Lag EMA (ZLEMA) and Fractal Adaptive Moving Average (FRAMA). These are used to determine the "Path of Least Resistance." A signal only fires when the trend is perfectly aligned (Fast > Medium > Slow).
- The Volatility Layer (MoBo Bands): Momentum Breakout (MoBo) Bands are derived from Standard Deviation. They act as a volatility filter, ensuring that a "Buy" or "Sell" signal only occurs when the price has enough momentum to break out of its immediate value area.
- The Momentum Filter (RSI & MACD): To prevent "buying the top," the script cross-references the Relative Strength Index (RSI) and MACD Histogram. These ensure that momentum is not only trending but is actively accelerating in the direction of the trade.
- The Execution Layer (EMA Touch & Price Action): The primary trigger is a mean-reversion "touch" of the 9-period Fast EMA. To confirm the reversal, the script scans for one of eight institutional candlestick patterns (e.g., Morning/Evening Stars, Tweezers, or Pin Bars).
Key Features
- 12 Selectable MA Types: Adapt to different market conditions (Forex, Crypto, or Futures) by switching between GMA, VIDYA, KAMA, and more.
- Advanced Price Action Detection: Integrated logic for Hammer, Shooting Star, Tweezer, Inside Bar, and Dark Cloud patterns as signal requirements.
- Secondary Volatility Filters: Built-in ADX (Trend Strength) and ATR (Volatility) filters to keep you out of sideways, low-volume markets.
- Signal Cooldown: Prevents repetitive "over-trading" by enforcing a minimum bar distance between consecutive signals.
- Dynamic TP/SL Zones: The 50 and 200 MAs are highlighted as primary dynamic levels for taking profit or placing trailing stops.
How To Use
Identify the Trend: Ensure the 50 (Orange) and 200 (Blue) MAs are fanned out and the price is above/below them.
- Wait for the Pullback: Look for the price to return and "touch" the 9 EMA (Signal Line).
The Entry: Enter on the BUY or SELL label, which signifies that the pullback has met all MoBo, RSI, MACD, and Candlestick requirements.
- Management: Use the Orange MA (50) as your first Take Profit or "Break Even" zone, and the Blue MA (200) as your ultimate trend reversal stop. Gösterge
Adaptive Flow & Volatility BaselineMost retail indicators fail because they ask a single, one-dimensional question: What is the price doing?
The One Line is a multi-factor state machine designed to filter out the noise that traps retail traders. Instead of relying on lagging moving averages, it requires the mathematical confluence of price expansion, directional money flow, higher-timeframe alignment, and implied volatility (VIX) to validate a trend. If the institutional data does not support the move, the indicator stays flat, keeping you out of the chop.
Core Mechanics
Under the hood, this script processes four institutional data pillars into a single, easy-to-read baseline:
Adaptive Efficiency Smoothing (KAMA): The baseline blends a VWMA and SMA, dynamically adjusted by Kaufman’s Efficiency Ratio (ER). During strong trends, the line tracks price closely. When the market turns into a noisy, inefficient mess, the alpha drops and the line goes completely flat.
Directional Volume Flow (VFI): Rather than using raw volume—which can be easily skewed by a single block trade—the model calculates a Volume Flow Indicator (VFI). It caps anomalous volume spikes and tracks whether the underlying money flow is actually accumulating or distributing.
Macro IV Filter (VIX): Equities do not move in a vacuum. The model continuously pulls real-time VIX data. A bullish breakout will only trigger if the VIX is in a state of crush (falling), and a bearish breakdown requires the VIX to be expanding.
Non-Repainting MTF Trend: A strict, non-repainting higher-timeframe filter ensures you are never taking intraday signals against the macro structural trend.
How to Read the Chart
The indicator operates in three distinct regimes, represented by the color of the baseline and the surrounding volatility cloud (fueled by an exponentially smoothed ATR).
Green (Bullish Regime): Price has broken above the upper volatility band, VFI shows net accumulation, the higher-timeframe trend is up, and the VIX is cooperating. Action: Look for long entries on pullbacks to the baseline.
Red (Bearish Regime): Price has broken below the lower volatility band, VFI shows net distribution, the higher-timeframe trend is down, and the VIX is expanding. Action: Look for short entries or put options.
Gray (Chop / Trap Zone): The market is mathematically inefficient. This triggers when price reverts inside the bands, volume dries up, or a structural divergence occurs (e.g., price is rising but VFI money flow suddenly turns negative). Action: Capital preservation. Sit on your hands.
Trading Playbook & Best Practices
The "Trap" Exit: The smartest feature of this indicator is its dynamic reversion. If you are in a valid Green trend, but the underlying money flow (VFI) suddenly flips negative, the line will instantly turn Gray. Do not wait for price to hit your stop-loss. If the line turns gray, the institutional support for the move has vanished. Exit or trim your position.
Asset Class: This model was built specifically for highly liquid, volume-heavy instruments like SPY, QQQ, and ES/NQ futures.
Timeframes: It thrives on the 3-minute, 5-minute, and 15-minute charts. (Ensure the "Macro Timeframe" input is set appropriately higher than your chart timeframe, e.g., a 30m MTF on a 5m chart).
Trade the regime, not the noise. Gösterge
Strongest Price NodesStrongest Price Nodes highlights the price levels where the market has built the strongest activity across recent sessions.
Instead of displaying a full profile or filling the chart with too many levels, this indicator extracts only the most important price nodes and plots them directly on the chart as clean decision levels.
These nodes represent areas where price has spent time, traded volume, or built both time and volume together.
In simple terms, the indicator helps answer one question: Where has the market shown the strongest acceptance?
What It Shows? The indicator plots two types of nodes:
1. Historical Price Nodes
Historical nodes are calculated from completed sessions using the selected lookback period.
They show where the strongest market participation occurred in recent history.
These levels can act as important areas for reaction, support, resistance, retest, breakout confirmation, or mean reversion.
2. Developing Session Node
The developing session node shows the strongest value area forming during the current session.
It updates live as the session develops.To keep the chart clean, the developing session node is always limited to one level.
Calculation Modes The indicator includes three profile modes:
Volume
Finds price levels where the most volume traded.
Time
Finds price levels where price spent the most time.
Volume x Time
Finds price levels where both volume and time align.
This mode is useful for identifying stronger acceptance zones because it combines participation with time spent at price.
Why These Nodes Matter
Strong price nodes often become important market reference points.
Price may pause around them, reject from them, retest them after a breakout, rotate back toward them, or use them as support or resistance.
A strong node is not a buy or sell signal by itself. It is a decision zone. What matters is how price behaves when it reaches the node.
Display Controls
Nodes can be displayed as lines or ATR-based zones.
ATR-based zones adjust automatically with market volatility.
The extension mode can also be controlled.
You can choose to stop levels at session end, extend them for a fixed number of bars, extend them to the right, extend them to the left, or extend them in both directions.
This helps keep the chart clean and avoids unnecessary infinite lines when they are not needed.
How Traders Can Use It
Use historical nodes to mark important prior value areas.
Use the developing node to understand where the current session is building value.
If price holds above a node, it may suggest acceptance.
If price rejects from a node, it may suggest failed acceptance.
If price breaks away and later retests the node, it can become a useful continuation or reversal area.
The indicator works best when combined with price action, VWAP, session highs and lows, trend context, and volume behavior.
Summary
Strongest Price Nodes is built for traders who want a cleaner way to identify important price levels.
It focuses only on the strongest areas of market activity and removes unnecessary profile clutter.
The goal is not to predict direction.
The goal is to show where the market has accepted price and where the next important reaction may happen.
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Takhtupuria Sniper Pro: All-in-OneUltimate Sniper Pro: All-in-One
This is an advanced, comprehensive scalping tool designed to consolidate essential trading indicators into a single, user-friendly workspace. It is built to help traders analyze market trends, volatility, and institutional price levels efficiently.
Core Features included in this script:
EMA Settings: Includes both 21 EMA and 200 EMA to provide clear trend direction and support/resistance confirmation.
Alligator Indicator: A powerful tool for identifying market consolidation and catching the start of a trend burst.
Bollinger Bands (BB): Used to measure volatility and identify potential mean reversion opportunities in fast-moving markets.
VWAP: A critical tool for tracking institutional-level price averages.
Customization & Control:
Flexibility: Users can toggle each component (EMA, Alligator, BB, VWAP) on or off from the Inputs tab to suit their specific trading style.
Full Customization: All colors, line thicknesses, and styles are fully editable in the Style tab, allowing you to customize the tool to match your preferred chart setup.
This indicator is designed for traders seeking a clean, "All-in-One" solution to eliminate chart clutter and improve decision-making speed. Gösterge
