Doppler Velocity Shift [JOAT]DOPPLER VELOCITY SHIFT
A trend-acceleration / exhaustion detector built on the Doppler shift principle : a stationary observer (the baseline frequency) compared to a moving source (the instant frequency) produces a measurable shift whose sign tells you whether the source is approaching (compression / acceleration) or receding (rarefaction / exhaustion). For markets the analogue is simple: when the residual wave's oscillation frequency is slower than its long-run baseline, momentum is accelerating into the trend; when it is faster than baseline, the trend is exhausting into chop.
The Doppler analogue, translated
The script's pipeline:
Detrend price by subtracting an EMA (configurable length). The result is a residual wave oscillating around zero.
Optionally normalise by ATR so the wave amplitude is regime-aware.
Count zero-crossings of the residual over a short window — this gives the instant frequency .
Count zero-crossings over a long window — this gives the baseline frequency .
Compute the Doppler shift = (instant − baseline) / baseline. Positive shift = faster than baseline → exhaustion. Negative shift = slower than baseline → acceleration.
EMA-smooth the shift to reduce flicker.
The output is a percentage that is intuitive to read: +0.30 means oscillations are 30% faster than baseline (approaching exhaustion); −0.30 means 30% slower (accelerating into trend).
Two-threshold event detection
Exhaustion — shift > +exhaustion threshold (default +0.30) for N consecutive bars (configurable, default 3). Fires the Exhaustion label.
Acceleration — shift < −acceleration threshold (default −0.30) for N consecutive bars. Fires the Acceleration label.
Frequency Anomaly — when |shift| crosses threshold × multiplier (default 2.0× → ±0.60). The anomaly alert fires and the chart background tints accordingly.
A configurable Event Cooldown (default 8 bars) prevents same-type events from stacking. A multi-bar confirmation gate prevents single-bar noise from triggering events.
Visual system
Detrend residual line (overlay) with configurable transparency and cosmetic display scale.
Vertical event lines at each Acceleration / Exhaustion event, with optional full-height extension for emphasis.
Event labels — Unicode glyphs by default (toggleable to plain text ACCEL / EXHAUST).
Frequency anomaly background tint when the |shift| crosses the anomaly trigger.
Pane companion (toggleable, on by default) — plots instant frequency, baseline frequency, and Doppler shift % in a separate pane below the chart.
A locked Cyber Aqua palette (electric blue acceleration / hot pink exhaustion / muted blue-gray stable on a near-black ground) gives the indicator a distinctive physics-inspired identity.
Dashboard
Monospaced table, positionable to any of nine corners, with row-fade gradient. Surfaces:
Instant frequency (zero-crossings in the short window).
Baseline frequency (zero-crossings in the long window).
Doppler shift % (signed).
Current status (ACCEL / EXHAUST / STABLE).
Last event direction with bars-ago.
Configuration: detrend length, frequency window, baseline window.
Anomaly flag when triggered.
Alerts
Three alert conditions, each independently controllable:
Trend Acceleration (shift < −threshold for N bars)
Approaching Exhaustion (shift > +threshold for N bars)
Frequency Anomaly (|shift| > threshold × multiplier)
How to read it
Two reads, in order of conviction:
Acceleration label after a quiet period — the script's intended trend-entry signal. Frequency has slowed, meaning the residual is making fewer mid-line crossings — the wave has lengthened and is now committed in one direction. Pair with a directional indicator for entry.
Exhaustion label inside an extended trend — the script's intended trend-exit signal. Frequency has risen above baseline — the residual is making more crossings, meaning the trend is fragmenting. Reduce / exit trend exposure; the next move is often a reversal.
The Frequency Anomaly alert is the script's headline event — when |shift| spikes far past threshold the market is in an extreme state, almost always associated with either an explosive breakout (acceleration anomaly) or an exhaustion blowoff (exhaustion anomaly).
Suggested settings
Defaults (detrend EMA 20, frequency window 40, baseline window 200, smoothing EMA 3, ±0.30 thresholds, 3-bar confirmation) are tuned for 15m–1H on liquid markets. For lower timeframes drop windows proportionally (10 / 20 / 100). For HTF (4H+) raise windows (30 / 80 / 400). The ATR-normalised residual is the recommended default — without it, the script's behaviour drifts on instruments with changing volatility levels.
Originality
The Doppler shift is a fundamental result of classical physics; the financial-market analogue and its implementation here are original. The pipeline — the EMA-detrended residual wave with optional ATR normalisation, the rolling zero-crossing frequency estimator at two scales, the (instant − baseline) / baseline shift formula, the EMA-smoothed shift, the multi-bar confirmed event classifier with cooldown, the anomaly multiplier layer, the vertical event line render, the pane-companion three-series overlay, and the dashboard — is JOAT-original. No third-party code reused. The use of oscillation-frequency shift as a trend acceleration / exhaustion metric is the original quantitative contribution.
Limitations
Zero-crossing frequency estimation is noisy on short windows; the smoothing input (default 3) exists to suppress that. The frequency-anomaly trigger is a heuristic — it tells you the market is in a rare state, not which direction it will resolve. Events confirm only after the multi-bar threshold; events are non-repainting but lag by the confirmation window.
-made with passion by jackofalltrades
Indicator
Precision Price Gamma [PGamma]Here's the full updated description with all the fixes — car analogy corrected, image captions added, ready to copy:
Precision Price Gamma (PGamma) is a second-derivative momentum indicator that measures the acceleration of momentum, not momentum itself.
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WHY PGAMMA IS DIFFERENT
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Most momentum indicators tell you how strong a move is. PGamma tells you whether that strength is increasing or fading — going one step further by measuring whether momentum is strengthening or weakening. This allows PGamma to identify changes in market pressure before many trend-following indicators respond.
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THE FOUR STATES
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Γ↑ Accelerating — Bullish momentum is positive and still strengthening.
Γ⌃ Bull Weakening — Bullish momentum remains positive, but buying pressure is beginning to fade.
Γ↓ Bear Pressure — Bearish momentum is dominant and selling pressure continues to strengthen.
Γ⌄ Bear Exhaustion — Bearish momentum remains negative, but selling pressure is beginning to weaken.
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HOW IT WORKS
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PGamma smooths the source series, then computes the slope of that smoothed series — the first derivative, or Momentum. It then smooths Momentum and computes its slope — the second derivative, or Price Gamma. The four states are determined by the sign of both values simultaneously.
Momentum determines the current direction of market pressure. Gamma determines whether that pressure is strengthening or weakening. They often disagree near turning points — and those disagreements are often the most informative signals PGamma produces.
Think of it like driving a car. Momentum is your speed. Gamma is whether you are pressing the gas or the brake. You can be moving backward while pressing the brake — still moving backward, but slowing. That is negative momentum with positive gamma. In market terms, price may still be making lower lows, but each push down is losing force. That often precedes consolidation, a bounce, or a reversal.
Two examples of this disagreement are illustrated in the first two snapshots — a red candle during a green Gamma Timeline, and a green candle during an amber Gamma Timeline. The third snapshot illustrates when Momentum and Gamma align, showing a green candle with a green Gamma Timeline during Accelerating state.
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THE STATE MATRIX
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Momentum | Gamma | State
+ | + | Accelerating
+ | - | Bull Weakening
- | - | Bear Pressure
- | + | Bear Exhaustion
Momentum and Gamma often disagree near turning points. A positive Gamma reading while Momentum remains negative does not mean the market is bullish — it means bearish momentum is losing acceleration. Those disagreements are where PGamma is most useful.
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UNDERSTANDING THE DASHBOARD
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State — Combines Momentum and Price Gamma into one of the four market conditions above. Read the State row first.
Momentum — The first derivative of price. Positive = bullish momentum dominates. Negative = bearish momentum dominates.
Gamma — The second derivative of momentum. Above Zero = momentum is accelerating. Below Zero = momentum is decelerating. Gamma often changes direction before Momentum, making it useful for identifying transitions in market pressure.
Bias — A simplified interpretation combining Momentum and Gamma into a single directional context label.
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GAMMA TIMELINE
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The Gamma Timeline displays the historical sequence of Price Gamma states as a continuous color band along the bottom of the chart. Each colored segment represents one bar, allowing traders to quickly identify transitions between acceleration, weakening, pressure, and exhaustion without obscuring price action. Green for Accelerating, amber for Bull Weakening, red for Bear Pressure, sky blue for Bear Exhaustion. Toggle on or off in Display settings.
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GETTING STARTED
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1. Add PGamma to any chart. It works on all instruments and timeframes.
2. In Settings → Display, choose your panel position and size.
3. In Settings → Calculation, adjust Momentum Smoothing, Momentum Length, and Gamma Length to suit your timeframe. Default values are calibrated for intraday 1m–60m charts.
4. Read the State row first. Then use Momentum and Gamma to understand why the state is what it is.
5. Use Bias as a quick at-a-glance directional context.
6. Use the Gamma Timeline to read state history across the session at a glance.
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HOW TO USE IT
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PGamma is not a buy or sell signal. Think of PGamma as a market condition indicator rather than a trade signal. Use it as a confirmation layer alongside your existing methodology. Typical applications:
• Confirming trend continuation when State shows Accelerating.
• Identifying weakening rallies before reversals when State shows Bull Weakening.
• Recognizing building pressure before visible breakdowns when State shows Bear Pressure.
• Spotting exhaustion during extended trends when State shows Bear Exhaustion.
When used alongside a GEX level tool, price approaching a Call Wall with Γ⌃ Bull Weakening is a different setup than price approaching the same level with Γ↑ Accelerating. PGamma makes that distinction visible.
Because PGamma analyzes smoothed momentum rather than candle color, bullish candles can appear during Bear Pressure and bearish candles can appear during Bull Weakening. This reflects underlying momentum conditions rather than individual price bars — and is often an early warning of what is developing beneath the surface.
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WORKS WELL ALONGSIDE
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PGamma complements indicators that identify where important price levels exist.
• Trend indicators
• Moving averages
• Volume Profile
• VWAP
• Options Gamma Exposure (GEX)
• Support and Resistance
• Market Structure
These tools identify where price may react. PGamma helps evaluate how price is behaving as it approaches those levels.
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WHAT THIS TOOL IS NOT
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PGamma measures changes in momentum. It does not predict future prices or guarantee reversals. Use it as analytical context alongside your existing trading methodology.
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SETTINGS OVERVIEW
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Calculation: Source, Momentum Smoothing, Momentum Length, Gamma Length
Display: Show Dashboard, Panel Position (6 locations), Panel Size (Small / Normal / Large), Show Gamma Timeline Indicator
Arc Radius Trend [JOAT]Arc Radius Trend
Introduction
Arc Radius Trend is an open-source, overlay-based trend-following system that replaces the static ATR band of conventional supertrend-style indicators with a curved, acceleration-responsive radius. The band does not scale linearly with volatility alone — it also responds to how fast price is accelerating or decelerating, expanding when momentum surges and tightening when price action becomes uniform. This gives it a shape that mirrors how institutional participants view momentum: not as a constant envelope, but as one that breathes with the market.
The problem ART solves is over-sensitivity. Standard ATR-based trailing stops flip direction too freely during acceleration events, producing false exits at exactly the moment when the trend is strongest. By expanding the radius during acceleration, ART gives trends room to breathe without permanently widening the band for all conditions.
Core Concepts
1. Velocity and Acceleration from Price
ART computes price velocity as the EMA of the bar-to-bar change in close, and acceleration as the EMA of the change in velocity. Both use the same smoothing length. Acceleration is normalized by ATR so that it is dimensionless and comparable across instruments and timeframes:
velocity = ta.ema(ta.change(close), accelLength)
accel = ta.ema(ta.change(velocity), accelLength)
accelNorm = atr > 0 ? accel / atr : 0.0
2. Curved Radius Scaling
The base radius is ATR multiplied by a configurable multiplier. The acceleration norm is then used to scale that radius with a power function, creating a nonlinear expansion curve. The exponent (Curve Strength) controls how aggressively acceleration widens the band:
radiusScale = math.pow(1.0 + math.min(math.abs(accelNorm), 2.0), curvePower)
radius = atr * baseMult * radiusScale
3. Ratcheting Band Logic
The active band ratchets in the direction of the current trend. When price is above the band (bull), the lower band is preserved at its maximum achieved value, preventing it from retreating while the trend holds. The trend flips when price closes through the opposite band:
trend := close > upperBand ? 1 : close < lowerBand ? -1 : nz(trend , 1)
activeBand = trend == 1 ? lowerBand : upperBand
4. JOAT Institutional Expansion Layer
Each JOAT indicator carries a shared Expansion Layer — an adaptive spine built from price efficiency, Shannon entropy, Parkinson range volatility, and a market impact ratio. The spine tracks the dominant flow using an KAMA-style adaptive constant, and its width is scaled by ATR ratio, range volatility, and noise. Stress and calm rails extend beyond the outer context boundary and change color based on composite stress readings. Bull and bear regime shift nodes mark confirmed directional transitions in the expansion layer state.
Features
Curved radius expansion: Band width nonlinearly expands during price acceleration events
Ratcheting trend band: Lower band preserved on bull trend, upper band preserved on bear trend — no backward drift
Outer envelope: A second ring outside the active band provides an extended volatility reference
Trend-state candle coloring: Candles tinted to reflect current trend direction
Regime flip nodes: Circle markers on the active band at confirmed bull and bear regime transitions
JOAT Expansion Layer: Adaptive spine with efficiency/entropy scoring, context box, stress rails, calm rails, and shift nodes
Stress and calm telemetry rails: Outer halos that widen with impact ratio and volatility stress
Dashboard (top right): Live display of trend state, active band level, normalized acceleration, and last flip
All signals on confirmed bars: No repainting — all state changes fire only on barstate.isconfirmed
Input Parameters
Radius Model:
Radius ATR Length: ATR period for radius computation (default: 21)
Base Radius Multiplier: Baseline band width in ATR units (default: 2.4)
Acceleration Smoothing: EMA length for velocity and acceleration (default: 8)
Curve Strength: Power applied to acceleration scale — higher values expand the band more aggressively (default: 1.35)
Outer Envelope: Multiplier for the secondary outer ring (default: 1.65)
Display:
Trend-State Candles toggle
Show Dashboard toggle
JOAT Expansion Layer:
Efficiency, Entropy, Impact lengths; Adaptive Fast/Slow periods; Context Width
Spine, Context Box, Regime Nodes, Candle Tint, Projection Bars, and Opacity toggles
Independently configurable Bull, Bear, Neutral, and Accent colors
How to Use This Indicator
Step 1: Establish trend direction
Read the active band color and the dashboard. Green indicates bull trend; red indicates bear. Use this as the primary directional filter for entries.
Step 2: Watch for confirmed flip nodes
Circle markers at confirmed trend reversals mark the bar where the band direction changed. These are not entry signals — they are context anchors. Evaluate what triggered the flip (structural break, momentum loss) before acting.
Step 3: Use the outer envelope as a volatility reference
When price extends to the outer envelope, the market is in elevated acceleration. This is not necessarily a reversal signal — it may indicate trend continuation with excess momentum.
Step 4: Read the Expansion Layer spine
The JOAT spine color and state convey institutional flow independent of the ART band. Bull spine with bull ART band is high-confidence alignment. Divergence between the two (e.g., bull ART, neutral spine) suggests weakening conditions.
Indicator Limitations
Acceleration-driven radius expansion may produce very wide bands during high-velocity events, temporarily reducing the band's usefulness as a stop reference
The ratchet mechanism preserves the band in the trend direction — during prolonged consolidation, the band will not tighten until a directional break occurs
On very low-liquidity instruments, the ATR-based radius may be structurally noisy; increasing the ATR length reduces this
Arc Radius Trend does not generate entries. It identifies directional state and provides a trailing reference level
Originality Statement
Arc Radius Trend is original in its use of normalized price acceleration as a multiplicative, power-scaled modifier to ATR radius. Existing supertrend variants use static ATR multiples or linear volatility adjustments. The combination of:
Velocity → acceleration derivation applied to a curved radius (not a flat multiplier)
Power-function scaling that produces nonlinear radius expansion only during acceleration events
Ratcheting band logic that is conditioned on the curved radius (not a fixed channel)
An institutional expansion layer carrying efficiency, entropy, Parkinson range vol, and impact scoring as a second independent context layer
...makes ART a structurally distinct contribution rather than a parameter variation of existing published work.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any instrument. Trading involves substantial risk of loss. Past behavior of this indicator does not guarantee future results. All signals should be validated within a complete trading framework that includes risk management. The author is not responsible for trading losses resulting from the use of this indicator.
-Made with passion by jackofalltrades
Indicator
Kinetic Inertia Field [JOAT]Kinetic Inertia Field
Introduction
Kinetic Inertia Field models price like a noisy particle using velocity, acceleration, jerk, kinetic energy, potential displacement, and equilibrium deviation.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Velocity and Acceleration
Log returns are normalized by volatility to create velocity, then differentiated into acceleration and jerk.
2. Kinetic Energy
Inverse volatility acts as a mass proxy and squared velocity creates energy context.
3. Equilibrium Displacement
A regression/VWAP blend creates a fair path and ATR-normalized displacement.
4. Inertia Field
Energy, acceleration, and displacement combine into inertial up, inertial down, or elastic state.
kineticEnergy = 0.5 * mass * velocity * velocity
Features
Velocity, acceleration, and jerk model
Kinetic and potential energy scoring
Regression/VWAP equilibrium
Energy rails and impulse trace
K+ and K- labels plus snapback markers
Input Parameters
Velocity smoothing
Volatility memory
Equilibrium horizon
Energy and inertia gates
Cooldown and display toggles
How to Use This Script
Use K+ and K- as confirmed high-energy state changes. Gold markers show elastic snapback conditions.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
KIF is original in applying kinetic energy, potential displacement, and inertia scoring to price-state analysis.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Nexus Kinetic Reactor [JOAT]Nexus Kinetic Reactor
Introduction
Nexus Kinetic Reactor estimates price as a noisy state process. It tracks state, velocity, uncertainty, confidence, and optional projection cones.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Recursive State Estimate
A smoothing lambda updates the estimated price state bar by bar.
2. Velocity Regime
Changes in the state estimate create velocity and acceleration-style context.
3. Uncertainty Bands
Noise windows and sigma bands show how uncertain the current estimate is.
4. Confidence Gate
Signals require tracking confidence and expectancy thresholds before labels appear.
state := state + lambdaAdjustment * (price - state)
Features
Recursive price-state estimator
Velocity and acceleration regime logic
Uncertainty bands
Projection cone
Blocked signal markers and dashboard
Input Parameters
Smoothing lambda and noise window
ATR length and velocity threshold
Minimum confidence and expectancy
Band sigma and projection bars
Cone, candle, and panel toggles
How to Use This Script
Use the state estimate and uncertainty bands as kinetic context. Labels only appear when the model clears confidence and expectancy gates.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
Nexus is original in combining state estimation, velocity gating, uncertainty bands, expectancy filtering, and projection visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Parabolic Move Detector [AGPro Series]🚀 Parabolic Move Detector
A dedicated framework for identifying, measuring, and classifying parabolic price acceleration across any asset and any timeframe. Built on a single transparent metric — Parabolic Pace — the tool objectively detects the start bar of a parabolic move, tracks its age, scores its intensity on a 0-100 scale, classifies its lifecycle phase, and contextualizes each move against the asset's own historical parabolic events.
🔹 OVERVIEW
Parabolic moves are notoriously difficult to recognize in real time. By the time they look obvious, the move is already late-stage. Conventional momentum tools (RSI, MACD, standard ROC) measure speed, not the underlying structural character of a parabolic move. They fire constantly on ordinary trends and miss what makes a parabolic move structurally different: the rate at which price is covering ATR-sized distance per bar.
Parabolic Move Detector closes that gap with a single, transparent metric. It measures how many ATRs price has moved per bar over a configurable lookback window. That is the literal mathematical definition of a parabolic move: sustained directional travel at an unusual speed relative to recent volatility. The framework auto-calibrates per timeframe and per asset, so a 15m memecoin pump and a 1D large-cap rally are measured with the same structural definition.
🔹 UNIQUE EDGE
Most acceleration or momentum indicators in the public space fall into two buckets: oscillators with hardcoded thresholds that need retuning per symbol, or composite "trend strength" meters that blur acceleration into raw trend direction. This tool is different in four concrete ways:
1. Single-metric detection engine. The entire detection pipeline is driven by one transparent number: Parabolic Pace = cumulative price move divided by cumulative ATR over the lookback. No percentiles, no hidden regressions, no black-box composite. This makes the tool easy to audit, fast to calibrate, and consistent across assets.
2. ATR-normalized by design. Because pace is expressed in ATRs per bar, it is inherently timeframe-adaptive and asset-adaptive. No need to retune for BTC vs a thin-volume altcoin, or for 15m vs 1W.
3. Four-phase state machine. Each move is classified through a deterministic lifecycle — Accelerating → Peaking → Decelerating → Exhaustion — with explicit transition conditions rather than heuristic labels. This turns a vague concept ("it looks parabolic") into a reproducible state with measurable transitions.
4. Per-asset historical statistics. The tool logs every completed parabolic cycle on the current chart, filters out micro-events, and reports the average duration and average drawdown from peak. That gives structural context no oscillator provides: what has this specific asset actually done the last N times it went parabolic.
🔹 METHODOLOGY
Core detection pipeline:
• Pace is computed as (close − close ) divided by (ATR14 × N), where N is the lookback window. The result is the number of ATRs traveled per bar.
• Pace is lightly smoothed with a short SMA to reduce single-bar noise.
• Detection triggers when smoothed pace exceeds the Pace Threshold and the move is directionally up.
• A minimum-duration filter requires the pace condition to persist for N consecutive bars before confirming the start, eliminating single-bar spikes.
• A post-move cooldown prevents the same move being re-detected as multiple events.
State machine transitions:
• Idle → Accelerating : pace sustained above threshold for the minimum duration.
• Accelerating → Peaking : Acceleration Score drops >20% from its cycle peak while still elevated.
• Any phase → Decelerating : score drops below 40% of cycle peak.
• Decelerating → Exhaustion : pace rolls over below half-threshold, and the move has lived at least 6 bars.
• Exhaustion → Idle : cooldown bars elapsed and score collapsed.
Acceleration Score (0-100) is a direct function of pace: score rises linearly with pace and receives a small persistence bonus for sustained upward momentum, capped at 100.
Historical statistics:
Each time a full cycle closes on the chart, the tool checks whether the move traveled at least the minimum ATRs from start to peak. If it qualifies, duration (start bar to peak bar) and drawdown from move high to subsequent low are averaged into rolling per-asset statistics.
🔹 STATES AND VISUALS
• Parabolic Zone : gradient background across the active move. Color reflects phase (brand blue in Accelerating, indigo in Peaking, amber in Decelerating). Intensity scales with Acceleration Score.
• Parabolic Start label : marks the confirmed start bar of a new move.
• Peaking / Decelerating labels : mark phase transitions. Labels are automatically suppressed within a confluence window to prevent stacking.
• Exhaustion label : marks the bar where the move has structurally collapsed.
• Duration Projection : dotted forward line sized to the asset's historical average parabolic duration, shown only while a move is active.
🔹 KEY INPUTS
Detection group:
• Pace Lookback — window over which parabolic pace is measured.
• Pace Threshold — minimum ATRs-per-bar required to qualify as parabolic.
• Minimum Move Duration — bars of sustained pace required before confirming a start.
• Minimum Event Size — minimum ATR-normalized move size required to log an event in historical statistics.
• Post-Move Cooldown — minimum bars after a completed move before a new one can start.
Historical Stats group:
• Show Duration Projection — toggle the forward projection line.
• Projection Length — forward projection cap in bars.
Visuals group:
• Parabolic Zone Background, Ambient Score Tint, Parabolic Start Label, Exhaustion Warning Label, Phase Transition Labels — all independently toggleable.
Style group:
• Label Size, Panel Size, Help Text Size — default Normal.
• Panel Location — six anchor positions.
• Panel Theme — Dark or Light.
Alerts group:
• Parabolic Start, Peaking Phase Reached, Exhaustion Detected — individually toggleable alerts.
🔹 HOW TO USE
• On any asset and any timeframe, wait for a confirmed Accelerating phase. The Parabolic Start label marks the reference bar.
• Track the Acceleration Score as the move develops. A score climbing toward 60-100 indicates a textbook parabolic.
• Compare Move Age against the panel's Avg Duration statistic. Moves significantly older than the asset's historical average are in late-cycle territory.
• Compare Move Change % against the Avg Reversal statistic for post-move drawdown context.
• Watch for the Peaking transition — this is the first structural deceleration, not a reversal call.
• The Exhaustion state marks where pace has decisively collapsed and the move is structurally over.
• Combine with your existing trend, structure, or volume framework. This tool is designed to complement directional analysis, not replace it.
🔹 LIMITATIONS AND TRANSPARENCY
• The tool detects and classifies acceleration structure. It does not predict reversals, tops, or bottoms. Avg Reversal is a post-cycle statistic computed from completed events on the current chart, not a forward-looking forecast.
• Historical statistics require completed cycles on the chart. Newly loaded symbols with few prior parabolic events will show low sample sizes until more cycles complete.
• The tool confirms a move only after pace has been sustained for the minimum duration. The start label is therefore plotted retroactively on its true start bar, which is the correct academic behavior for a sustained-condition detector.
• All computations are on confirmed bar close logic. No repainting of historical signals once a bar closes.
• The Pace metric requires a valid ATR reading, so at least 14+ bars of history are needed before the tool becomes active on a fresh chart.
🔹 RISK DISCLOSURE
This script is an analytical tool provided for educational and research purposes only. It is not a trading strategy, not financial advice, and does not generate buy or sell recommendations. Trading any market involves substantial risk of loss. All decisions and their consequences are the sole responsibility of the user. Past behavior of parabolic cycles on any asset does not guarantee future behavior.
Indicator
Ferrum Pressure Gauge [JOAT]Ferrum Pressure Gauge
Introduction
The Ferrum Pressure Gauge is an open-source composite momentum-volume oscillator that fuses three independent pressure measurements — volume-weighted momentum, price velocity with acceleration, and RSI-derived trend pressure — into a single index displayed in a separate pane. The index is paired with a signal (resonance) line, and the space between them is filled with an 8-layer gradient that visually communicates momentum intensity at a glance. Dynamic non-repainting zones adapt to recent range, divergence detection identifies price-vs-index fractures, and a precursor engine spots early reversal conditions before the main index confirms them.
Most momentum oscillators measure a single dimension — either price momentum or volume momentum, but rarely both in a unified way. FPG addresses this by weighting price changes by volume activity through a logarithmic volume impact function, then combining that with velocity, acceleration, and RSI into a composite reading. The result is an oscillator that responds to both the speed and the conviction behind price moves.
Core Engine: Fusion Reactor
The composite index is built from three sub-components:
1. Volume-Weighted Momentum (Net Flow)
Price changes are scaled by a logarithmic volume impact function that amplifies moves occurring on above-average volume while dampening moves on thin volume:
float vRatio = ta.sma(volume, 3) / ta.sma(volume, volPeriod)
float vwMom = pChange * math.log(1 + vRatio * volSens)
The logarithmic scaling prevents extreme volume spikes from producing absurdly large momentum readings while still giving meaningful weight to elevated volume. Fast and slow EMAs of this volume-weighted momentum produce a dual-speed flow, and their difference (smoothed) becomes the Net Flow component.
2. Price Velocity and Acceleration
Velocity measures the average price change per bar over the fast period. Acceleration is the change in velocity — it detects whether momentum is building or fading. These are combined with the volume ratio and scaled to produce the Flow Strength component.
3. RSI Trend Pressure
RSI is centered around zero (RSI - 50) and smoothed, providing a bounded measure of trend pressure that complements the unbounded volume-weighted components.
The three components are averaged and passed through a final WMA smoothing pass to produce the Pressure Index. A separate EMA of the index produces the Resonance (signal) line.
8-Layer Gradient Fill
The space between the Pressure Index and the Resonance Line is divided into 8 equal segments, each filled with progressively increasing transparency. This creates a smooth gradient that is dense and vivid when momentum is strong (large gap between index and signal) and thin and faded when momentum is weak. The gradient direction and color shift based on whether the index is positive or negative and whether it is in the upper or lower crucible zone.
Dynamic Crucible Boundaries (Non-Repainting Zones)
Rather than using fixed overbought/oversold levels, FPG calculates dynamic zones based on the recent range of the index:
float rHi = ta.highest(idx, zoneLen)
float rLo = ta.lowest(idx, zoneLen)
float volF = (rHi - rLo) / 2
float upperZ = math.min(60, 30 + volF * 0.3)
float lowerZ = math.max(-60, -30 - volF * 0.3)
The offset on highest/lowest ensures these zones never repaint. They widen during volatile periods and tighten during calm ones, adapting the overbought/oversold thresholds to current market conditions rather than using arbitrary fixed levels.
Volume Climax (Surge Detection)
The indicator percentile-ranks current volume against a configurable lookback (default 100 bars). When volume exceeds the 90th percentile, a surge is detected. The edge-triggered SURGE label fires only on the first bar of the spike, marking potential climax events where institutional-scale volume enters the market.
Exhaustion Index (Fatigue Meter)
When the Pressure Index dwells in an extreme zone (above upper or below lower boundary), a fatigue counter increments each bar. The fatigue percentage rises linearly toward 100% over a configurable horizon (default 20 bars). Fatigue is classified as NONE, MILD, BUILDING, or CRITICAL. Critical fatigue warns that momentum has been stretched for an extended period and reversal probability is elevated.
Fracture Detection (Divergence)
The indicator detects classic divergences between price and the Pressure Index:
Bullish Fracture: Price is falling (making lower lows) while the Pressure Index is rising — hidden buying pressure beneath falling prices.
Bearish Fracture: Price is rising (making higher highs) while the Pressure Index is falling — hidden selling pressure beneath rising prices.
Fracture signals are confirmed-bar only and placed outside the crucible boundaries to avoid overlapping with the main index plot.
Precursor Engine (Early Reversal Detection)
The precursor engine identifies conditions where the fast and slow flow lines cross while the main index is on the opposite side of zero:
IGNITION (Bullish Precursor): Fast flow crosses above slow flow while the Pressure Index is still negative — early bullish momentum building before the index turns positive.
QUENCH (Bearish Precursor): Fast flow crosses below slow flow while the Pressure Index is still positive — early bearish momentum building before the index turns negative.
These signals often lead the main index crossover by several bars, providing an early warning system.
Command Panel (Dashboard)
A 9-row monospace dashboard displays:
PRESSURE: Current Pressure Index value with color reflecting zone position
RESONANCE: Current signal line value
FLOW: Net flow delta (fast minus slow) — the raw momentum differential
FLUX: Volume ratio (short/long SMA) — values above 1.2 indicate elevated activity
CRUCIBLE: Current dynamic upper and lower zone boundaries
SURGE: Whether volume is currently in a climax state (ACTIVE / QUIET)
FATIGUE: Exhaustion classification with percentage (NONE / MILD / BUILDING / CRITICAL)
DELTA: Histogram value (index minus signal) — positive = bullish momentum, negative = bearish
Input Parameters
Fusion Reactor:
Ignition Cycle: Fast EMA period (default 8)
Sustain Cycle: Slow EMA period (default 21)
Flux Epoch: Volume SMA lookback (default 14)
Flux Amplifier: Volume impact scaling (default 1.5)
Forge Smoothing / Temper Pass: Composite and final smoothing
Resonance Layer:
Resonance Period: Signal line EMA (default 12)
Crucible Boundaries: Toggle dynamic zones
Boundary Lookback: Zone calculation window (default 50)
Volume Climax:
Enable Surge Detection / Surge Percentile / Surge Lookback
Exhaustion Index:
Enable Fatigue Meter / Fatigue Horizon: Bars in extreme zone before max fatigue
Fracture Detection:
Show Fractures / Fracture Lookback: Divergence detection parameters
Precursor Engine:
Show Precursors: Toggle early reversal signals
How to Use This Indicator
Use the Pressure Index crossing above/below the Resonance Line as a momentum confirmation signal — similar to MACD crossovers but volume-weighted.
Watch for IGNITION/QUENCH precursor signals — they often lead the main crossover by several bars and can provide earlier entries.
FRACTURE (divergence) signals are among the most reliable warnings of trend exhaustion. A bullish fracture during a downtrend suggests hidden accumulation.
Monitor the Fatigue meter when the index is in an extreme zone. CRITICAL fatigue combined with a fracture signal is a high-probability reversal setup.
SURGE markers highlight institutional-scale volume events. A surge occurring at a crucible boundary often marks a climax reversal point.
The 8-layer gradient provides instant visual feedback — dense, vivid fills indicate strong momentum conviction; thin, faded fills indicate weakening momentum.
Limitations
Like all momentum oscillators, FPG is lagging — it confirms momentum after it has begun, not before.
Divergence (fracture) signals can persist for extended periods before price reverses. They indicate weakening momentum, not guaranteed reversals.
Precursor signals are early by design and therefore have a higher false-positive rate than confirmed crossover signals.
Volume-weighted calculations are less reliable on instruments with inconsistent or unreported volume data.
The Fatigue meter is a heuristic based on time-in-zone, not a statistical probability. Extended trends can maintain extreme readings longer than expected.
Dynamic zones adapt to recent range but may lag during sudden regime changes.
Originality Statement
This indicator is original in its composite fusion approach. While MACD, RSI, and volume analysis are established concepts individually, FPG is justified because:
The logarithmic volume-weighted momentum calculation provides a unique fusion of price change and volume conviction that differs from standard MACD or OBV approaches.
Three independent sub-components (volume-weighted flow, velocity/acceleration, RSI pressure) are composited into a single index, providing multi-dimensional momentum measurement.
The 8-layer gradient fill between index and signal line creates a visual momentum density map not found in standard oscillators.
Dynamic non-repainting crucible boundaries adapt overbought/oversold levels to current conditions rather than using fixed thresholds.
The Exhaustion Index tracks time-in-extreme-zone as a fatigue metric, adding a temporal dimension to momentum analysis.
The Precursor Engine identifies early flow crossovers while the main index is on the opposite side, providing leading signals ahead of the main crossover.
Volume Climax detection via percentile ranking integrates institutional-scale volume event identification directly into the oscillator.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Momentum oscillators describe the current state of price momentum but do not predict future price direction. Overbought conditions can persist in strong trends, and oversold conditions can deepen in bear markets. Always use proper risk management and conduct your own analysis before making trading decisions. The author is not responsible for any losses incurred from using this tool.
-Made with passion by officialjackofalltrades
Indicator
Indicator
Triple Derivative EngineMost momentum indicators tell you where the price is. The Triple Derivative Engine tells you how fast it's getting there, whether that speed is increasing or fading, and whether the acceleration itself is changing direction — three layers of motion analysis extracted from a single smoothed price signal, all normalized to a common ±100 scale so every layer is directly comparable at a glance.
How It Works
Step 1 — Smoothing
Raw price is too noisy to differentiate reliably. TDE first passes your source through one of three selectable filters to extract the underlying motion curve before computing any derivatives.
Savitzky-Golay (default) fits a 2nd-order polynomial to a moving window of bars using Gram polynomial coefficients. Unlike a moving average, it preserves the shape of peaks and troughs rather than smoothing them away. Window sizes of 5, 7, 9, 11, 13, and 15 are supported, each with exact integer coefficients — no approximation. This gives the best phase response of the three filters: signals appear earlier and with less distortion.
Gaussian weights each past bar by a bell-curve function of its distance from the current bar. Sigma controls how quickly the weights fall off. Softer and more trailing than SG, useful when you want a cleaner curve at the cost of a slight lag.
Kalman is a single-state recursive filter that continuously estimates the "true" price by balancing how much it trusts the new measurement (R) versus how much the underlying process is expected to move (Q). It adapts bar-to-bar, making it the most responsive of the three with the least lag, but also the most sensitive to sharp moves.
Step 2 — Finite Difference Derivatives
Once the smoothed signal sm is computed, three derivatives are calculated using standard finite difference formulas:
Velocity (1st derivative): sm − sm — the rate of change of price. Positive means price is rising, negative means it is falling. The magnitude tells you how fast.
Acceleration (2nd derivative): sm − 2·sm + sm — the rate of change of velocity. Positive means momentum is building; negative means it is fading, even if price is still moving in the same direction.
Jerk (3rd derivative): sm − 3·sm + 3·sm − sm — the rate of change of acceleration. A leading indicator of acceleration reversals. When jerk crosses zero, acceleration is about to change direction.
Step 3 — Normalization
Each derivative is divided by its rolling peak absolute value over the normalization lookback window, then scaled to ±100. This keeps all three series on the same axis and comparable to each other, regardless of the instrument's price level or volatility. A velocity reading of +80 and an acceleration reading of +80 carry equivalent relative meaning within their own histories.
Signals
Zero Crosses
Every time a derivative crosses the zero line, a marker appears at the top or bottom of the panel. Each derivative has a distinct shape to avoid confusion:
Velocity (Circle): Bottom (bullish) / Top (bearish)
Acceleration (Diamond): Bottom (bullish) / Top (bearish)
Jerk (Square): Bottom (bullish) / Top (bearish)
Each set of markers is independently gated by its visibility toggle, so you only see the crosses for the series you have enabled.
Velocity cross — the most direct signal. When velocity crosses above zero, price momentum has turned positive on the source timeframe. Below zero, it has turned negative.
Acceleration cross — a timing tool, not a trend signal. When acceleration crosses above zero while velocity is still positive, the move is re-accelerating. When acceleration crosses below zero while velocity is still positive, the move is losing steam — the trend continues, but is starting to exhaust. Acceleration reversals frequently precede velocity reversals by several bars.
Jerk cross — the earliest signal in the chain. Jerk crossing zero means acceleration is about to change direction. By itself, jerk is noisy, but when it aligns with acceleration near a zero cross, it can give a meaningful early warning.
Divergence Markers (Triangles)
Divergence fires when acceleration crosses zero while velocity is still extreme — specifically when |vn| > 30. This combination means the move has been strong enough to be considered extended, but the underlying force driving it is already reversing.
Bear divergence (▼ triangle, top): Acceleration crosses below zero while velocity is still elevated above +30. The upswing's engine is cutting out while the price is still high. Historically, this precedes deceleration into a stall or reversal.
Bull divergence (▲ triangle, bottom): Acceleration crosses above zero while velocity is still depressed below −30. The downswing is losing power from the bottom. Historically, this precedes a deceleration of selling and a potential recovery.
Divergence markers are rarer than zero crosses by design. They represent a specific confluence, not a general crossover signal.
Regime Background
The panel background is tinted to reflect the current momentum regime:
Velocity > 0 and Acceleration > 0: Accelerating bull - Cyan tint
Velocity < 0 and Acceleration < 0: Accelerating bear - Red tint
No tint: Decelerating or mixed - Neutral
The regime is also displayed in the info table with four states: ▲ Accelerating, ↗ Decelerating, ↘ Recovering, ▼ Falling.
Signal Line
An EMA of velocity (default length 9) is plotted as a thin white line over the velocity histogram. Velocity crossing its own signal line is an additional early entry cue, analogous to the MACD signal cross but applied directly to the derivative layer.
Settings
⏱ Timeframe
Source Timeframe — the timeframe on which the smoothed signal is computed before derivatives are taken. Options: Auto, Chart, 5m, 15m, 1H, 4H, 1D, 1W.
Auto scales to a fixed higher timeframe based on your current chart: below 5m → 15m, below 15m → 1H, below 1H → 4H, below 4H → 1D, otherwise 1W. This allows the indicator to show higher-timeframe derivative structure on any intraday chart without manual adjustment.
The chart uses the same timeframe as the chart is on. Useful when you want the derivatives of the chart's own bars rather than a higher context.
🔬 Smoothing Filter
Filter — selects the smoothing method: Savitzky-Golay (recommended), Gaussian, or Kalman.
SG Window (SG only) — odd integer from 5 to 15. Controls the width of the polynomial fitting window. Larger windows produce smoother derivatives with (window−1)/2 additional bars of lag. Window 9 is the default and a good general-purpose choice. Use 5 or 7 for faster signals on volatile instruments; 13 or 15 for cleaner derivatives on smooth trends.
Gaussian Length (Gaussian only) — number of bars in the weighted sum. Longer = smoother.
Gaussian Sigma (Gaussian only) — controls the standard deviation of the bell curve. Lower values concentrate weight on recent bars; higher values spread it more evenly.
Kalman Q — Process Noise (Kalman only) — how much the filter expects the price to move on its own each bar. Higher Q makes the filter track price more closely with less smoothing. Range 0.0001–1.0, default 0.01.
Kalman R — Measurement Noise (Kalman only) — how much the filter distrusts the raw price measurement. Higher R produces more smoothing and more lag. Range 0.01–50.0, default 1.0.
📈 Derivatives & Display
Price Source — the input series to smooth and differentiate. Defaults to close. Can be set to any source, including hl2, ohlc4, or another indicator's output via the source selector.
Normalization Lookback — the rolling window (in bars) over which each derivative is scaled to ±100. Shorter windows (e.g., 50) make the indicator more responsive to recent extremes; longer windows (e.g., 200–500) provide a more stable baseline. Default 100.
Signal EMA Length — the length of the EMA applied to normalized velocity to produce the signal line. Default 9.
Velocity (1st deriv) — show/hide the velocity histogram and line, and its zero-crossing markers.
Acceleration (2nd deriv) — show/hide the acceleration line and its zero-cross diamond markers.
Jerk (3rd deriv) — show/hide the jerk line and its zero-crossing square markers. Hidden by default as it is primarily useful for advanced analysis.
Signal Line on Velocity — show/hide the EMA signal line overlay on velocity.
Divergence Markers — show/hide the bear/bull divergence triangle markers.
🎨 Colors
All seven colour elements are individually configurable: Velocity (up/down), Acceleration (up/down), Jerk (up/down), and the Signal line.
Alerts
Eight alert conditions are available:
Velocity → Positive: Velocity crosses above zero
Velocity → Negative: Velocity crosses below zero
Momentum Trough: Acceleration crosses above zero
Momentum Peak: Acceleration crosses below zero
Jerk → Positive: Jerk crosses above zero
Jerk → Negative: Jerk crosses below zero
Bullish Divergence: Acceleration recovers while velocity is below −30
Bearish Divergence: Acceleration rolls over while velocity is above +30
Reading the Indicator Together
The three layers are designed to be read in sequence, from slowest to fastest signal:
Check velocity for trend direction — is the move positive or negative?
Check acceleration for conviction — is the move building or fading?
Check jerk for early warning — is acceleration about to change?
A high-confidence setup aligns all three: velocity positive, acceleration positive and rising, jerk positive. As a move matures, acceleration will peak and roll over first, while velocity remains elevated — that is the divergence condition. Velocity eventually follows. Jerk will often signal the peak of acceleration one step earlier still.
No single cross is a trade signal on its own. TDE is a momentum structure tool. It is most useful when combined with price structure, support/resistance levels, and a defined higher timeframe bias. Indicator
Pulse Mean AcceleratorPulse Mean Accelerator (PMA) | MisinkoMaster
Pulse Mean Accelerator (PMA) is a high-speed adaptive trend engine designed to dynamically accelerate or stabilize its behavior depending on how aggressively price moves relative to its underlying structure. Instead of acting like a traditional moving average that simply lags behind price, PMA attempts to anticipate momentum expansion by accelerating when price pulses strengthen and stabilizing when market movement slows.
The result is a responsive yet smooth trend-following tool that adapts to both trending and consolidating markets. PMA is particularly useful for traders who want earlier participation in expanding trends without sacrificing structural clarity.
By combining adaptive acceleration, volatility awareness, and layered smoothing, PMA balances speed and stability to help traders remain aligned with developing momentum.
Key Features
Adaptive acceleration that reacts when price movement intensifies
Automatically slows down during consolidation to reduce noise
Multiple moving average types supported for flexibility
Volatility-aware responsiveness adjustment
Optional confirmation logic to filter weak signals
Multiple smoothing modes for balancing speed vs stability
Dynamic candle coloring reflecting active trend state
Automatic Long and Short markers when direction changes
Works across fast intraday and slower swing environments
Designed to reduce lag while preserving structure
How It Works
Pulse Mean Accelerator begins with a moving average structure but enhances it by measuring how aggressively price moves relative to that baseline. When price starts moving faster than the average, acceleration increases, allowing the indicator to catch up quickly.
When price slows or becomes erratic, acceleration reduces, preventing excessive reaction to noise.
Volatility measurements are incorporated to scale this acceleration, ensuring that responsiveness adapts naturally to current market conditions. Strong moves result in quicker adaptation, while quiet markets lead to smoother, calmer behavior.
Additional smoothing layers can then be applied, allowing traders to choose between faster responsiveness or more stable structure depending on their trading style.
Optional confirmation logic ensures that signals are not triggered solely by temporary price spikes, helping filter weaker moves.
The outcome is a moving average framework that behaves more like a dynamic trend engine rather than a static lagging indicator.
Trend Detection Logic
Trend direction is determined by how price behaves relative to the accelerated mean structure.
Bullish phases occur when price maintains strength above the adaptive mean while momentum confirms upward pressure. Bearish phases occur when price weakens below the structure and downward momentum dominates.
Signals appear when participation shifts strongly enough to confirm directional change, helping traders detect transitions from consolidation to expansion phases.
Acceleration Behavior
A defining characteristic of PMA is its pulse acceleration mechanism.
• Strong price pulses increase responsiveness
• Weak or slow price movement reduces acceleration
• Volatility conditions influence adaptation speed
• Structure remains smooth when momentum is weak
This dynamic adjustment helps traders enter trends earlier while avoiding excessive reactions during sideways markets.
Smoothing Modes
PMA includes multiple smoothing options so users can tune responsiveness:
• Raw acceleration for fastest reaction
• Exponential stabilization for balanced behavior
• Additional smoothing layers for structural clarity
• Double smoothing for maximum noise reduction
This flexibility allows PMA to be tailored for scalping, intraday trading, or higher-timeframe trend following.
Visual Signals
The indicator provides several visual cues for ease of interpretation:
• Candle coloring reflects active trend direction
• Adaptive mean and accelerated mean are plotted together
• Long and Short markers appear when trend shifts occur
• Filled areas highlight separation between price and structure
These features help traders read market structure quickly without relying on numerical interpretation.
Inputs Overview
Users can customize behavior through adjustable components including:
• Price source selection used in calculations
• Moving average type controlling base structure
• Length settings affecting responsiveness
• Acceleration sensitivity determining reaction speed
• Volatility measurement type influencing adaptation
• Smoothing mode selection for stability control
• Optional confirmation filtering for signal validation
These controls allow the tool to be tuned for both aggressive and conservative trading approaches.
Usage Notes
Ideal for traders needing faster adaptation to momentum expansion
Helps detect early stages of trend acceleration
Useful for filtering sideways noise while remaining reactive to breakouts
Works well in volatile assets where traditional averages lag
Can be combined with support/resistance or volume tools for confirmation
Higher smoothing settings suit swing traders, lower smoothing benefits intraday traders
Confirmation mode reduces false signals in choppy markets
Parameter tuning improves performance across different assets
Best Use Scenarios
Pulse Mean Accelerator performs particularly well in:
• Momentum expansion phases
• Breakouts from consolidation ranges
• Trend continuation environments
• High-volatility market conditions
• Assets showing periodic acceleration bursts
• Markets transitioning from low to high volatility
It is especially effective where traditional moving averages react too slowly to developing moves.
Summary
Pulse Mean Accelerator transforms traditional moving average logic into an adaptive trend engine capable of accelerating when price momentum expands and stabilizing during calm conditions. By blending acceleration, volatility awareness, and flexible smoothing, it provides traders with a faster yet structured view of market direction.
PMA is best suited for traders seeking earlier trend participation while maintaining smooth, readable structure across both fast-moving and consolidating markets. Indicator
Indicator
Indicator
Indicator
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Strategy
MultiLayer Acceleration/Deceleration Strategy [Skyrexio]Overview
MultiLayer Acceleration/Deceleration Strategy leverages the combination of Acceleration/Deceleration Indicator(AC), Williams Alligator, Williams Fractals and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Acceleration/Deceleration Indicator is used for creating signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Acceleration/Deceleration shall create one of two types of long signals (all details in "Justification of Methodology" paragraph). Buy stop order is placed one tick above the candle's high of last created long signal.
4. If price reaches the order price, long position is opened with 10% of capital.
5. If currently we have opened position and price creates and hit the order price of another one long signal, another one long position will be added to the previous with another one 10% of capital. Strategy allows to open up to 5 long trades simultaneously.
6. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about Acceleration/Deceleration signals. AC indicator is calculated using the Awesome Oscillator, so let's first of all briefly explain what is Awesome Oscillator and how it can be calculated. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO), where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now we can explain which AC signal types are used in this strategy. The first type of long signal is when AC value is below zero line. In this cases we need to see three rising bars on the histogram in a row after the falling one. The second type of signals occurs above the zero line. There we need only two rising AC bars in a row after the falling one to create the signal. The signal bar is the last green bar in this sequence. The strategy places the buy stop order one tick above the candle's high, which corresponds to the signal bar on AC indicator.
After that we can have the following scenarios:
Price hit the order on the next candle in this case strategy opened long with this price.
Price doesn't hit the order price, the next candle set lower high. If current AC bar is increasing buy stop order changes by the script to the high of this new bar plus one tick. This procedure repeats until price finally hit buy order or current AC bar become decreasing. In the second case buy order cancelled and strategy wait for the next AC signal.
If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. All open trades are closed when the trend shifts to a downtrend, as determined by the combination of the Alligator and Fractals described earlier.
Why we use AC signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC bars after period of falling AC bars indicates the high probability of local pull back end and there is a high chance to open long trade in the direction of the most likely main uptrend. The numbers of rising bars are different for the different AC values (below or above zero line). This is needed because if AC below zero line the local downtrend is likely to be stronger and needs more rising bars to confirm that it has been changed than if AC is above zero.
Why strategy use only 10% per signal? Sometimes we can see the false signals which appears on sideways. Not risking that much script use only 10% per signal. If the first long trade has been open and price continue going up and our trend approximation by Alligator and Fractals is uptrend, strategy add another one 10% of capital to every next AC signal while number of active trades no more than 5. This capital allocation allows to take part in long trades when current uptrend is likely to be strong and use only 10% of capital when there is a high probability of sideways.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.11.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -5.15%
Maximum Single Profit: +24.57%
Net Profit: +2108.85 USDT (+21.09%)
Total Trades: 111 (36.94% win rate)
Profit Factor: 2.391
Maximum Accumulated Loss: 367.61 USDT (-2.97%)
Average Profit per Trade: 19.00 USDT (+1.78%)
Average Trade Duration: 75 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 3h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters. Strategy
Velocity and Acceleration SignalsThe "Velocity and Acceleration Signals" indicator is a versatile tool designed to provide traders with valuable insights into price momentum and acceleration. By harnessing the power of mathematics and visualization, this indicator helps traders make informed decisions in the fast-paced world of financial markets.
Crunching the Numbers: How It Works
At its core, the indicator relies on two key concepts: velocity and acceleration. Here's how it operates:
-- Velocity Calculation : The indicator takes a step back in time, considering a user-defined historical period (typically around 14 bars). It calculates the velocity of price movements during this period. Velocity represents the speed at which an asset's price is changing and is derived by examining how much the price has moved between bars. Specifically, it computes the rate of change in price over time.
-- Acceleration Calculation : Building upon velocity, the indicator goes one step further and calculates acceleration. Acceleration signifies how quickly the velocity is changing. It quantifies whether the price is speeding up or slowing down in its ascent or descent.
-- Smoothing with EMA : To enhance clarity and reduce noise, the indicator smooths the velocity using an Exponential Moving Average (EMA) with a user-defined length. This smoothed velocity provides a more comprehensive view of the price momentum trend.
Visualizing Market Dynamics
The indicator doesn't just crunch numbers; it also paints a vivid picture of market sentiment:
-- Coloration : The indicator employs a color scheme to visualize market conditions. It uses lime for positive acceleration and fuchsia for negative acceleration. The color green represents positive smoothed velocity, while red denotes negative smoothed velocity. A gray hue signals a neutral or transitional phase.
-- Plotting Velocity and Acceleration : The indicator provides visual representations of both smoothed velocity and acceleration. Smoothed velocity is depicted as columns, with green or red coloring indicating the direction. Acceleration is displayed as a histogram, with lime or fuchsia bars showcasing bullish or bearish momentum. A gray zero line offers a reference point for changes in momentum direction.
-- Strong Up and Strong Down Conditions : For traders seeking distinctive signals, the indicator identifies "Strong Up" and "Strong Down" conditions. A "Strong Up" occurs when smoothed velocity crosses above a user-defined threshold, coupled with positive acceleration. Conversely, a "Strong Down" emerges when smoothed velocity crosses below another threshold, accompanied by negative acceleration. These conditions are marked with prominent triangular shapes.
Unlocking Trading Potential
Now, let's explore how traders can leverage the indicator:
-- Trend Confirmation : Traders can use this indicator to validate the prevailing market trend. A robust smoothed velocity, combined with acceleration in the same direction, can confirm the current trend.
-- Contrarian Signals : Extreme conditions signaled by a strong crossover or crossunder of the smoothed velocity threshold, along with appropriate acceleration, can hint at potential trend reversals.
-- Divergence Analysis : Savvy traders can employ this indicator to identify divergences between price movements and momentum. If the price exhibits higher highs while the indicator shows lower highs (or vice versa), it may signify a weakening or strengthening trend.
Navigating Limitations
As with any trading tool, it's essential to acknowledge the indicator's limitations:
-- Lookback Period : The indicator's effectiveness may vary based on the chosen historical period. Longer periods smooth out fluctuations but may lag in capturing recent changes in sentiment.
-- Threshold Sensitivity : Interpreting threshold crossovers or crossunders can be subjective. Traders should carefully fine-tune these threshold values based on their trading strategy and market conditions.
-- Context Matters : The indicator focuses solely on velocity and acceleration signals and does not incorporate other critical factors such as trading volume, market news, or fundamental analysis. Therefore, traders should use it in conjunction with additional indicators and analysis techniques.
While the primary focus is on trend and momentum analysis, this indicator indirectly provides information about volatility as well. Rapid changes in velocity and acceleration can indicate increasing volatility in the market, which may be of interest to traders looking for opportunities during volatile conditions.
However, this indicator doesn't directly measure volume. To incorporate volume analysis into your trading strategy, you may want to combine this indicator with volume-based indicators or consider other tools specifically designed for volume analysis.
In conclusion, this indicator is a valuable ally for traders looking to decode market dynamics and make data-driven trading decisions. While it offers powerful insights, it's crucial to recognize its limitations and deploy it as part of a comprehensive trading strategy. Indicator
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Acceleration-Based MA Slope PredictionHello traders,
I developed this indicator while working on a trading strategy using moving average slope and acceleration, and I found the concept interesting enough to share it.
Let me briefly explain this indicator.
----About White Plot----
1. Calculate the first derivative approximation at the current point of the Moving Average, and then calculate the second derivative approximation to obtain the 'Acceleration'.
2. Where the acceleration is 0, it signifies a change in the force of the moving average.
3. Therefore, by drawing a parabola based on the acceleration at that time, can depict the parabolic shape of the moving average.
This is represented as a white circle on the indicator.
4. These circles are reset at the next point where the acceleration is 0, indicating a change in the parabolic force.
If the moving average rises more sharply than the predicted value of the rising parabola, a more drastic increase is expected.
5. In this case, you can start risk management around the time the drawn parabola breaks.
(The actual MA is represented by green/red lines)
6. Before the trend changes, i.e., before the direction of the moving average changes, there is a section where the acceleration is 0, and this is represented on the chart as follows.
(The lower indicator shows the acceleration of the corresponding parabola)
----About Red Plot----
1. Calculate the first derivative approximation of the moving average value, the 'slope'.
2. Where the slope is 0, it represents the extreme point of the parabola.
3. Therefore, by using the acceleration at that point as the coefficient of the quadratic function and setting the extreme point as a vertex, we can draw a quadratic function. This is represented as a red circle on the indicator.
(Keep in mind that the actual moving average is not a quadratic function; this is a "forced" quadratic function assuming the parabola is maintained)
4. These circles are reset at the next extreme point where the slope is 0, and a new quadratic function is created.
Based on the formula obtained in the above process, you can predict the future moving average through 'offset'.
5. That is, if the x value at the current point is 'k', you can predict the moving average one candle ahead by substituting (k+1) into the quadratic function.
The predicted value at the past position is shown as a red circle.
6. The smoother the chosen moving average, the fewer extreme points will appear, and the higher the likelihood of the parabola fitting.
For the T3 set as the default value, it shows very high accuracy even when predicting about 20 candles ahead.
On the other hand, rough moving averages like SMA have limited prediction value.
(SMA 60, offset = 10)
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The moving average with a very high level of accuracy is JMA (Jurik Moving Average). However, since the code for this moving average is not public, I recommend those interested to check it through my code.
Additionally, I believe the code of this indicator I've uploaded has significant utility.
As an example, you can use the breaking point of the parabola predicted by the acceleration to determine when the force changes again for entries/losses. There are many other possible applications as well.
I look forward to seeing more excellent results from this indicator.
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안녕하세요 트레이더여러분.
이 지표는, 제가 이동평균선의 기울기와 가속도를 이용하여 매매를 하기 위한 지표를 개발하다가, 흥미로운 내용이라고 판단하여 만들게 되었습니다.
이 지표에 대해 간단히 설명드리겠습니다.
----하얀색 플롯에 대해----
1. 이동평균선이 진행되는 현재 시점에서 미분의 근사값을 구하고, 다시 한 번 미분의 근사값을 구해서 '가속도'를 얻습니다.
2. 가속도가 0이 되는 곳은, 곧 해당 이동평균선의 힘이 바뀌는 곳을 의미합니다.
3. 따라서, 그 당시 시점 기준으로 포물선을 그려낸다면, 가속도를 이용하여 해당 이동평균선의 포물선을 그려낼 수 있습니다. 이것은 지표의 하얀색점로서 표기됩니다.
4. 이 때, 이러한 점들은 다음의 가속도가 0이 되는 지점, 즉 포물선의 힘이 바뀌는 곳에서 다시 초기화됩니다.
5. 올라가고 있던 포물선에서의 예측치보다 이동평균선이 더 급하게 올라간다면, 더욱 급격한 상승이 예상됩니다. 이 경우, 그려지고있는 포물선이 깨질 때쯤부터 리스크 관리를 시작할 수 있습니다.
(녹색/빨간색의 선으로 실제 MA를 표현했습니다. 거슬리시면 '모습'가셔서 끄셔도 좋습니다. )
6. 추세가 변경되기 전, 즉 이동평균선의 방향이 바뀌기 전에는 가속도가 0이 되는 구간이 존재하고, 그것이 차트 위에 다음과같이 표현됩니다.
(하단의 지표는, 해당 포물선의 가속도을 나타냅니다)
----붉은색 플롯에 대해----
1. 이동평균선 값을 미분 근사값 즉, '기울기'를 구합니다.
2. 기울기가 0이 되는 곳은, 포물선이 극점이 되는 곳을 뜻합니다.
3. 따라서, 해당 시점의 가속도를 2차함수의 계수로 하여, 또한 해당 극점을 하나의 꼭지점으로 설정하여,이차함수를 그려낼 수 있습니다. 이것은 지표의 빨간색점으로서 표현됩니다.
(실제 이동평균선은 2차함수가 아니기에, 포물선이 유지된다는 가정 하에 "억지로"만들어낸 이차함수입니다)
4. 이 때, 이러한 점은 다음 극점이 0이 되는 곳에서 초기화되고 이차함수가 만들어집니다.
5. 위의 과정에서 얻은 식을 바탕으로 'offset'을 통해 미래의 이동평균선을 예측할 수 있습니다.
즉, 현재시점의 x값을 'k'라고 한다면, (k+1)을 이차함수에 대입하여 1캔들 앞의 이동평균선을 예측할 수 있습니다.
해당 예측치가 지나간 자리는, 빨간색점을 통해 보여집니다.
6. 선택한 이동평균선이 스무스할수록 극점은 덜 등장하게되고, 포물선의 위치가 맞아들어갈 가능성이 높습니다.
현재 디폴트값으로 설정된 T3의 경우, 약 20캔들 앞을 예측해도 매우 높은 정확도를 보여줍니다.
반면에, SMA와 같이 울퉁불퉁한 이동평균선은 가능한 예측치가 크지 않습니다.
(SMA 60, offset=10)
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매우 높은 수준의 정확도를 보여준 이동평균선은 JMA(Jurik Moving Average)입니다. 다만 이 이동평균선은 코드가 공개되지 않았기때문에, 관심있으신 분은 저의 코드를 통해 한번 확인해보시길 권장드립니다.
추가로, 제가 올린 이 지표의 코드는 이용가치가 높다고 생각합니다.
하나의 예시로서, 가속도로 예측한 포물선이 깨지는 곳을 기준으로, 힘이 다시 한 번 바뀌는 것을 이용해 진입/로스를 할 수 있습니다. 그 외에도 매우 다양한 활용이 가능합니다.
이 지표를 통해 더욱 좋은 새로운 결과물이 나오길 기대해봅니다. Indicator
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