Histogram by RumiancevRumiancev Histogram R/S/M
Rumiancev Histogram R/S/M is an open-source momentum indicator designed to combine three analytical layers in a single pane: a histogram-based Ergodic-style momentum model, two optional EMA overlays applied directly to the histogram, and an optional Adaptive RSI module with its own signal line and centered levels.
The goal of this script is to provide a compact but flexible momentum workspace. Instead of forcing the user to stack several separate tools on the chart, this script brings the main momentum histogram, short smoothing overlays, and an additional adaptive strength filter together in one place. The result is a cleaner workflow for traders who want to read momentum shifts, short-term acceleration, slowing conditions, and auxiliary RSI-style confirmation from a single panel.
General idea
The script is built around a normalized momentum histogram. It measures bar-to-bar price change, smooths that movement in multiple stages, and compares directional movement against total movement. This allows the oscillator to focus not only on whether price is rising or falling, but also on how efficiently price is moving in one direction relative to overall fluctuation.
A signal line is applied to the main oscillator value, and the histogram represents the distance between the oscillator and that signal. This makes the histogram useful for tracking momentum expansion and momentum contraction around the zero line.
In addition to the histogram, the script can display two optional EMA lines derived from the histogram itself. These lines help users visually filter short-term noise and better judge whether recent histogram movement is strengthening, fading, or transitioning.
The script also includes an optional Adaptive RSI module. This is not plotted in the classic RSI panel style. Instead, it is centered around zero and scaled so it can coexist with the histogram in the same pane. This gives the user an extra confirmation layer without requiring a separate indicator window.
How the main histogram works
The core oscillator uses the change in closing price from one bar to the next. First, the script calculates the raw directional change. Then it calculates the absolute value of that same change. These two series represent direction and total movement.
Both series are then smoothed in two stages. The first stage uses the selected fast smoothing method and fast length. The second stage uses the selected slow smoothing method and slow length. After these smoothing steps, the script divides the smoothed directional movement by the smoothed absolute movement and multiplies the result by 100. This creates a normalized momentum reading.
That normalized reading becomes the main oscillator value. A separate signal line is then calculated using the selected signal smoothing method and signal length. The histogram is the difference between the main oscillator and the signal line.
This construction allows the histogram to react to changing momentum conditions while remaining more structured than a simple unsmoothed rate-of-change style plot.
How to read the histogram
When the histogram is above zero, the main oscillator is above its signal line, which suggests positive momentum pressure. When the histogram is below zero, the main oscillator is below its signal line, which suggests negative momentum pressure.
If histogram bars are growing while already above zero, that often means bullish momentum is strengthening. If histogram bars are shrinking above zero, bullish pressure may still be present, but it is losing force. The same logic applies below zero: expanding negative bars can suggest increasing bearish pressure, while shrinking negative bars can suggest that bearish momentum is weakening.
The zero line is the main structural reference. Crosses above and below zero can be used to identify transitions in short-term momentum balance. However, like any momentum tool, the histogram should be interpreted in context, especially when price is ranging or when volatility suddenly expands.
EMA overlays on the histogram
The script includes two optional EMA lines, named Yellow EMA and Blue EMA in the settings. These are calculated from the histogram values, not from price.
Their purpose is visual smoothing. Some traders prefer to read the raw histogram alone. Others prefer to see one or two smoothed references that make short swings easier to interpret. Because these EMAs are applied to the histogram, they can help reveal whether momentum is accelerating into a move, flattening, or starting to roll over before a more visible shift in the histogram bars occurs.
The Yellow EMA is typically used as the faster smoothing line, while the Blue EMA can be treated as the slower companion line. Users may keep both hidden, display one of them, or display both depending on their preferred chart-reading style.
Adaptive RSI module
The Adaptive RSI included in this script is designed as an auxiliary momentum filter rather than a standard standalone RSI replacement. Instead of using the classic up-close versus down-close averaging approach only, this version evaluates directional pressure using the relationship between recent range expansion, recent range contraction, and ordinary bar-to-bar movement.
The script first examines the highest and lowest values over the selected RSI length. From there it measures whether the recent range is expanding upward, expanding downward, or whether current movement is better represented by the direct step from one bar to the next. That directional movement is then smoothed, compared to its absolute magnitude, and transformed into an RSI-style value centered around 50.
To make this RSI usable inside the same pane as the histogram, the script recenters it around zero by subtracting 50 and then multiplying the result by the RSI Scale input. The signal line for the Adaptive RSI is calculated separately using its own signal length and smoothing mode.
This gives the user a secondary confirmation line that can be visually aligned with the histogram without opening another indicator panel.
How to read the Adaptive RSI in this script
Because the Adaptive RSI is centered and scaled, it should not be interpreted exactly like a classic RSI pane. Its purpose here is relative confirmation.
If the Adaptive RSI is rising and the histogram is also strengthening, the two layers are confirming each other. If the histogram is trying to recover while the Adaptive RSI remains weak or rolls over quickly, that may suggest the move has limited follow-through. If both the histogram and the Adaptive RSI signal line turn together, momentum alignment is clearer. If one improves while the other lags, the market may be in transition or lacking conviction.
The optional overbought, midline, and oversold levels provide extra visual structure for this centered RSI display. Since the RSI is scaled into the histogram pane, these levels are translated into centered equivalents instead of being shown as standard 70, 50, and 30 horizontal lines in a separate RSI panel.
Input settings explained
Fast Length controls the first smoothing stage of the main momentum calculation. Smaller values make the oscillator more responsive. Larger values make it smoother and slower.
Slow Length controls the second smoothing stage of the main oscillator. Increasing it generally reduces noise further and creates a more stable but slower-moving histogram.
Signal Length controls how quickly the oscillator signal line responds. A shorter signal length makes the histogram react faster because the gap between oscillator and signal changes more quickly. A longer signal length tends to produce smoother histogram transitions.
Fast Smoothing determines the smoothing method used in the first stage of the oscillator calculation. Slow Smoothing determines the smoothing method used in the second stage. Signal Smoothing determines the smoothing method used for the oscillator signal line. Available choices are EMA, SMA, RMA, WMA, HMA, and TMA.
Yellow EMA enables or disables the first histogram EMA overlay. Blue EMA enables or disables the second histogram EMA overlay.
Yellow EMA Length sets the period for the faster EMA overlay on the histogram. Blue EMA Length sets the period for the second EMA overlay.
Show Adaptive RSI enables or disables the centered Adaptive RSI line.
Show RSI Signal enables or disables the signal line of the Adaptive RSI.
Show RSI Levels enables or disables the centered overbought, midline, and oversold reference levels for the Adaptive RSI display.
RSI Source defines which price source is used for the Adaptive RSI calculation. The default is HLC3, but the user can choose any source supported by Pine input.source.
RSI Length controls the lookback used by the Adaptive RSI model.
RSI Smoothing selects the smoothing method applied inside the Adaptive RSI calculation.
RSI Signal Length controls the smoothing length of the Adaptive RSI signal line.
Signal Smoothing in the RSI section selects the smoothing method used for the Adaptive RSI signal line.
RSI Scale controls how strongly the centered RSI is expanded or compressed inside the histogram pane. Lower values make the RSI layer more compact. Higher values make it visually more pronounced.
RSI Overbought sets the upper reference threshold used by the Adaptive RSI.
RSI Oversold sets the lower reference threshold used by the Adaptive RSI.
Smoothing modes explained briefly
EMA responds relatively quickly and is often a good default for momentum work.
SMA is straightforward and balanced, but usually a bit slower in turning points.
RMA is smoother and often produces steadier transitions.
WMA places more emphasis on recent values than SMA.
HMA is generally more responsive and may suit users who want faster turning behavior with reduced lag.
TMA is heavily smoothed and may suit users who prefer a calmer visual structure over fast reaction.
Different smoothing combinations can materially change the character of the indicator. A user looking for responsiveness may prefer faster lengths and more reactive smoothing types. A user focused on broader trend pressure may prefer heavier smoothing and longer lengths.
Practical ways to use the script
One common approach is to use the histogram as the primary trigger layer and the Adaptive RSI as a confirmation filter. In that workflow, the user watches for histogram recovery from negative values, histogram expansion above zero, or histogram contraction below zero, then checks whether the Adaptive RSI is moving in the same direction.
Another approach is to focus on momentum quality rather than signals. In that case, the user may ignore exact crosses and instead study whether histogram bars are expanding, flattening, or diverging in behavior from price structure. The EMA overlays can be helpful here because they smooth the histogram without hiding its basic structure.
Some users may also treat the script as a trend-phase tool. Sustained positive histogram behavior combined with a stable or rising Adaptive RSI can support a bullish phase reading. Sustained negative histogram behavior combined with weak Adaptive RSI behavior can support a bearish phase reading. Mixed readings can indicate consolidation, transition, or an early reversal attempt that still lacks confirmation.
Important interpretation notes
This indicator is designed to measure momentum structure, not to predict the future. It should not be treated as a standalone trading system.
Momentum indicators can remain strong or weak for longer than expected during trending conditions. They can also produce frequent transitions during sideways markets. For that reason, this script is best used with price structure, higher timeframe context, risk management, and the user’s own trade process.
No divergence module is included in this version. The focus of the script is the histogram engine, histogram EMA overlays, and the Adaptive RSI confirmation layer.
Who this script may be useful for
This script may be useful for traders who want a momentum-focused indicator that remains visually compact while still offering more than a single raw oscillator line. It can suit discretionary traders who read chart structure manually, as well as users who want a clean supporting tool for directional bias, momentum confirmation, or timing refinement.
It may be especially useful for users who like histogram-based momentum analysis but also want an additional internal filter without loading a second separate RSI pane.
Open-source note
This script is published as open-source so traders and Pine users can study the logic, verify how it works, adapt it to their own process, and build on it if they find it useful. Indicator
Cadence Refracted Oscillator [JOAT]Cadence Refracted Oscillator
Introduction
The Cadence Refracted Oscillator is an open-source multi-layer momentum analysis tool built in Pine Script v6. It combines three distinct momentum methodologies — Spectral-Filtered RSI, Stochastic Momentum Index (SMI), and Cumulative Volume Delta (CVD) divergence detection — into a single composite oscillator displayed in a separate pane below the chart. The indicator produces a blended momentum reading (0-100), a gradient histogram, a signal line with crossover detection, Z-score extreme markers, and Wyckoff absorption alerts. It is designed for traders who want a deeper, noise-reduced view of momentum that goes beyond what a standard RSI or stochastic can provide.
The key innovation is the spectral filtering stage. Instead of applying RSI directly to raw price, the indicator first passes price data through a Discrete Fourier Transform (DFT) to extract dominant frequency components, then applies RSI-weighted filtering to produce a cleaner, less noisy momentum signal. This filtered signal is then blended with the Stochastic Momentum Index to create a composite that captures both trend momentum and mean-reversion potential.
Why This Indicator Exists
Standard momentum oscillators have well-known limitations. RSI is noisy on lower timeframes and produces frequent false signals in choppy markets. Stochastic oscillators are fast but whipsaw-prone. Neither incorporates volume information. This indicator addresses these issues by layering three complementary approaches:
Spectral-Filtered RSI: Applies a Discrete Fourier Transform to extract the dominant price cycle, then weights the filtered output by RSI distance from the midpoint. This removes high-frequency noise while preserving the meaningful momentum signal. The result is a smoother RSI that responds to genuine trend changes rather than random fluctuations.
Stochastic Momentum Index: Measures where the close is relative to the midpoint of the recent high-low range, double-smoothed with configurable EMA periods. Unlike classic stochastic which measures close relative to the range boundaries, SMI measures distance from the center — making it more sensitive to directional momentum and less prone to ceiling/floor effects.
CVD Divergence: Tracks Cumulative Volume Delta (buy volume minus sell volume) and compares it to price extremes. When price makes a new low but CVD is higher than its previous low, buying pressure is diverging from price — a bullish signal. The reverse applies for bearish divergences. This adds a volume-based confirmation layer that pure price-based oscillators lack.
How the Spectral Filter Works
The spectral filtering process uses a Discrete Fourier Transform — the same mathematical tool used in signal processing, audio analysis, and scientific computing — to decompose price data into frequency components:
// Discrete Fourier Transform implementation
// Decomposes price into frequency components
// DC component (index 0) represents the dominant trend
// Higher harmonics represent shorter-term oscillations
The process works in four stages:
Stage 1 — Short RSI Weighting: A short-period RSI is calculated and converted to an "absolute distance from 50" value. Bars where RSI is far from 50 (strong momentum) receive higher weight in the filter.
Stage 2 — Forward DFT: Price data is transformed into the frequency domain using a configurable number of harmonics (default 3). The magnitude spectrum is extracted, and the DC component (the dominant low-frequency trend) becomes the filtered subject.
Stage 3 — RSI-Weighted Smoothing: The filtered subject is smoothed using the RSI absolute distance as weights. This means the filter responds more to bars with strong momentum and less to bars with weak, indecisive momentum.
Stage 4 — Final RSI: RSI is calculated on the filtered data with the main length (default 21). A divergence component (rate of change of the spectral RSI) is added to create the final Cadence RSI value.
The result is an RSI-like oscillator that is significantly smoother than standard RSI while still being responsive to genuine trend changes. The Fourier harmonics parameter controls how many frequency components are retained — fewer harmonics produce a smoother signal, more harmonics preserve more detail.
Stochastic Momentum Index Component
The SMI component provides a complementary momentum perspective. While the spectral RSI focuses on trend momentum, the SMI captures where price sits within its recent range:
The lookback period defines the range (highest high, lowest low)
The distance from the midpoint of that range is double-smoothed with two EMA passes
The range itself is also double-smoothed and halved to create the denominator
The resulting value oscillates between -100 and +100, where positive values indicate price is above the range midpoint and negative values indicate it is below
This is normalized to 0-100 for blending with the spectral RSI
The SMI is particularly useful for detecting mean-reversion opportunities. When the spectral RSI shows a trend but the SMI is at an extreme, it suggests the trend may be overextended.
Composite Blending
The final composite oscillator blends the spectral RSI (60% weight) with the normalized SMI (40% weight). This weighting prioritizes the trend-following spectral RSI while incorporating the mean-reversion sensitivity of the SMI. The composite oscillates between 0 and 100, with 50 as the neutral midpoint.
The histogram displays the difference from 50, making it easy to see momentum direction and intensity at a glance. Positive histogram bars indicate bullish momentum, negative bars indicate bearish momentum, and the gradient coloring intensifies with momentum strength.
Signal Line and Crossovers
An EMA-based signal line (default 9 periods) is applied to the composite. Crossovers between the composite and signal line provide timing signals:
Bull Cross: Composite crosses above the signal line — momentum is accelerating upward
Bear Cross: Composite crosses below the signal line — momentum is decelerating or reversing
The distance between composite and signal line indicates momentum conviction — wide separation means strong momentum, tight convergence suggests a potential cross is forming
Z-Score Extreme Detection
The indicator calculates a Z-score of the composite value over a configurable lookback (default 50 bars). When the Z-score exceeds +2.0 or falls below -2.0, the momentum is at a statistical extreme — more than two standard deviations from the mean. These events are marked with square markers and indicate:
Potential exhaustion of the current move
High probability of mean reversion
Possible climax buying or selling
Z-score extremes are not automatic reversal signals — strong trends can sustain extremes for extended periods. They are best used as warnings to tighten stops or take partial profits.
Wyckoff Absorption Detection
The indicator detects Wyckoff absorption events — bars where volume is significantly above average (1.5x) but the price range is significantly below average (0.5x). This pattern indicates that large institutional orders are being filled without moving price, which often precedes a directional breakout. Absorption markers appear as circles at the midline.
Visual Design
The indicator uses a "Solar Flare" color theme — golds, ambers, magentas, and plasma purples on a dark background:
Composite Line: Neon glow effect with three layered plots (outer glow at 85% transparency, mid glow at 65%, core line at full intensity). Color adapts to trend state — gold/amber for bullish, magenta/red for bearish, ash for neutral.
Gradient Histogram: 10-level color gradient from bright gold (strong bull) through amber to magenta (strong bear). Rising momentum within a direction intensifies the color.
Signal Line: Plasma purple with glow effect
Zone Fills: Subtle fills between threshold lines — gold tint in the bull zone, magenta tint in the bear zone, ash in the neutral zone
OB/OS Fills: When the composite enters overbought (>75) or oversold (<25) territory, a colored fill highlights the extreme
SMI Reference: A thin blue line showing the normalized SMI for comparison
Markers: Triangles for signal crossovers, diamonds for CVD divergences, squares for Z-score extremes, circles for absorption
HUD Dashboard
The real-time HUD displays 14 metrics:
Composite value with color-coded bull/bear/neutral state
Trend direction (Bullish/Bearish/Neutral)
Z-Score value with classification (Extreme Bull/Bear, Strong, Normal)
Momentum Percentile Rank (0-100%)
SMI value
Signal Line distance (Wide/Moderate/Tight)
Volume Flow direction (Buying/Selling/Neutral) from CVD
Spectral RSI component value
Momentum Strength percentage with classification (Very Strong to Very Weak)
Overbought/Oversold pressure state
Divergence status (Bull Div/Bear Div/None)
Current mode description (Bull Momentum/Bear Momentum/Consolidating)
Input Parameters
Spectral RSI:
RSI Length: Main RSI period (default: 21)
Source: Price source (default: close)
Filter Length: Short RSI period for weighting (default: 12)
Fourier Harmonics: Number of DFT components (default: 3). Lower = smoother, higher = more detail.
Stochastic Momentum:
SMI Lookback: Range period (default: 13)
SMI Smooth 1/2: Double-smoothing EMA periods (default: 25/2)
Signal Length: Signal line EMA period (default: 13)
Volume Delta:
Show CVD Divergence: Toggle divergence detection
CVD Divergence Lookback: Period for comparing CVD extremes to price extremes (default: 14)
Levels:
Overbought/Oversold: Extreme thresholds (default: 75/25)
Bull/Bear Threshold: Trend classification levels (default: 58/42)
How to Use This Indicator
Step 1: Read the Composite Direction
Above 58 = bullish momentum. Below 42 = bearish momentum. Between = consolidation. The histogram makes this immediately visible.
Step 2: Watch for Signal Crossovers
Bull crosses (composite above signal) in the lower half of the range are potential long entries. Bear crosses in the upper half are potential short entries. Crosses near the midline are less significant.
Step 3: Check for Divergences
CVD divergences at price extremes are powerful reversal warnings. A bullish CVD divergence at an oversold composite reading is a high-probability long setup.
Step 4: Monitor Z-Score Extremes
Z-score beyond +/-2.0 warns of potential exhaustion. Consider tightening stops or taking partial profits when the Z-score reaches extreme levels.
Step 5: Use Absorption as Early Warning
Absorption events (high volume, small range) often precede breakouts. When absorption appears near a threshold level, be prepared for a directional move.
Best Practices
The spectral filter works best on timeframes with sufficient data — 5-minute and above is recommended
Fewer Fourier harmonics (2-3) produce a smoother, more trend-following signal. More harmonics (5-8) produce a more responsive but noisier signal.
The composite is most reliable when the spectral RSI and SMI agree. Divergence between the two components suggests mixed conditions.
CVD divergences are most significant at overbought/oversold extremes
Z-score extremes in trending markets can persist — do not blindly fade them
The signal line crossover is a timing tool, not a standalone entry signal. Combine with price action and structure analysis.
Absorption events are context-dependent — they are most meaningful near support/resistance levels
Limitations
The DFT calculation is computationally intensive. Very high harmonic counts may slow chart loading on lower timeframes with large datasets.
The spectral filter introduces a small amount of lag compared to raw RSI. This is the tradeoff for noise reduction.
CVD divergence detection uses a simple comparison of extremes over the lookback period. It may miss complex divergences or flag simple pullbacks as divergences.
Buy/sell volume separation is estimated from candle direction, not true order flow data.
The composite blending weights (60/40) are fixed. Different instruments or timeframes might benefit from different weights.
Z-score extremes are relative to the lookback period. A Z-score of +2.0 over 50 bars may not be extreme over 200 bars.
Like all oscillators, this indicator can remain at extremes during strong trends. It is not a contrarian tool by default.
Technical Implementation
Built with Pine Script v6 using:
Custom Discrete Fourier Transform implementation (forward and inverse) with configurable harmonics
RSI-weighted spectral filtering for noise reduction
Double-smoothed Stochastic Momentum Index with normalization
Cumulative Volume Delta tracking with divergence detection
Z-score calculation for statistical extreme identification
Wyckoff absorption detection (effort vs result)
10-level gradient histogram coloring function
Multi-layer neon glow effect on composite and signal lines
barstate.isconfirmed gating on all signal markers
10 alert conditions covering threshold crosses, divergences, signal crossovers, and Z-score extremes
Originality Statement
This indicator is original in its synthesis of spectral analysis with momentum oscillators and volume delta. While RSI, stochastic, and CVD are established concepts, this indicator is justified because:
The Discrete Fourier Transform spectral filtering applied to RSI calculation is a novel approach that significantly reduces noise while preserving signal responsiveness
The RSI-weighted filtering stage ensures the spectral filter responds more to high-momentum bars and less to noise, creating an adaptive smoothing mechanism
Blending spectral RSI with SMI combines trend-following and mean-reversion perspectives into a single composite that captures both dimensions of momentum
CVD divergence detection adds a volume-based confirmation layer that pure price-based oscillators cannot provide
Z-score extreme detection provides statistical context for momentum readings, helping traders distinguish between normal momentum and genuine extremes
Wyckoff absorption integration connects volume analysis with momentum analysis in a way that standard oscillators do not
The Solar Flare theme with gradient histogram and neon glow provides immediate visual clarity about momentum direction and intensity
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Momentum oscillators measure the rate and direction of price change — they do not predict future price movement. Overbought conditions can persist in strong uptrends, and oversold conditions can persist in strong downtrends. Signal crossovers and divergences are probabilistic, not deterministic. Past momentum patterns do not guarantee future behavior. Always use proper risk management and never risk more than you can afford to lose. The author is not responsible for any losses incurred from using this indicator.
-Made by officialjackofalltrades
Indicator
SMI Fractal Iron HMASMI FRACTAL IRON HMA
Professional Multi-Engine Trading Overlay
Version 7.0 • February 2026 • Pine Script™ v6 • Overlay Indicator
By NPR21
FIVE INTEGRATED ENGINES
Fractal Pivots │ SMI Filter │ HMA Forecast │ Risk Management │ Short Trend Dashboard
DESCRIPTION
SMI Fractal Iron HMA integrates five complementary analytical engines into a single overlay indicator, designed so that each component addresses a different dimension of trade analysis — structure, momentum, trend context, risk parameters, and real-time directional scoring — and the outputs of each engine reinforce or qualify the signals of the others.
▸ Fractal Pivot Detection
Identifies structural swing highs and lows using fractal pivot logic with a key innovation: the left-side structural lookback and the right-side confirmation delay are split into two independent inputs. This allows traders to maintain high structural selectivity (catching only significant swing points) while independently controlling how many bars of confirmation are required before a signal prints. Setting Right Bars to zero enables zero-delay mode where the label appears on the forming bar itself.
▸ Stochastic Momentum Index (SMI) Filter
A double-smoothed EMA of the price-to-midpoint relationship, scaled to a configurable range. When enabled as a filter, long signals only print when SMI is rising and short signals only print when SMI is falling. Signals opposing the current momentum direction are silently suppressed, reducing noise without adding visual clutter.
▸ HMA Trend Duration Forecast
Tracks the Hull Moving Average slope to determine trend state. Each completed trend’s duration is stored in a rolling sample. The historical average projects the probable length of the current trend. On the chart: a white arrow line shows the forecast window, a Trend ↑ Up Real or Trend ↓ Down Real label updates in real time with the current bar count, and a Prob: label shows the forecasted duration. HMA BUY and HMA SELL labels print at each trend change with optional price display.
▸ Risk Management System
Activates on each confirmed pivot signal and draws five horizontal levels: Entry, Stop Loss (configurable in points or percentage), and three Take Profit tiers calculated as Reward:Risk multiples. Features include:
•TP hit tracking — each level changes to dashed with a check-mark label when price reaches it.
•Trailing stop — moves to breakeven at a configurable threshold, then trails by a fixed offset.
•TP2+ reversal exit — after TP2 is hit, closes the trade if price reverses by a specified distance before TP3.
•P&L dashboard — real-time display of direction, entry, current P&L in the selected currency, R:R ratio, dollar risk/reward at each TP, bars in trade, HMA trend direction, and probable trend length.
•Auto-reset — clears all trade objects when a trade completes (SL, TP3, or TP2+ reversal), readying for the next signal.
▸ Short Trend Dashboard
A 5-component real-time scoring engine that votes on the current bar’s directional bias:
•Momentum (25 pts) — price change vs. ATR-scaled threshold.
•Candle Structure (25 pts) — body-to-range ratio and wick rejection analysis.
•Micro Trend (25 pts) — fast/slow EMA crossover with ATR-normalized gap scoring.
•Acceleration (25 pts) — bar-to-bar momentum change detecting speed gain or loss.
•Volume B/S (10 pts) — estimated buy vs. sell pressure from close position within bar range.
The composite score (0–100) produces a letter grade (A+, A, B, C) and a directional label (BULLISH, BEARISH, LEAN BULL/BEAR, or NEUTRAL). The TEMP Heat Gauge (0–100) blends seven sub-indicators (ROC, RSI, Stochastic, Volume Pressure, EMA Position, Candle, Acceleration) into a single temperature reading (HOT / WARM / NEUTRAL / COOL / COLD). Scalper Mode activates ultra-fast EMA and momentum presets optimized for 1–5 minute charts with Instant Flip detection for single-bar reversals.
▸ Why These Five Engines Together
Each engine answers a different question. The pivot engine identifies where structure turns. The SMI filter confirms whether momentum supports the signal. The HMA forecast provides how long the trend is likely to last. The risk management system defines how much is at stake. The Short Trend Dashboard gives a right now directional confidence score. Together they create a workflow: detect the turn, confirm direction, understand trend context, manage the trade, and monitor conviction — all from a single indicator.
HOW TO USE
▸ Getting Started
1.Add the indicator to your chart. Default settings (Left 5 / Right 1) provide a balanced starting point with strong structural selectivity and minimal delay.
2.BUY labels appear below swing lows. SELL labels appear above swing highs. In Confirmed + Preview mode, semi-transparent labels flicker during bar formation and lock solid at bar close.
3.Use the HMA colored line and trend forecast labels to understand the broader trend context. HMA BUY and HMA SELL labels mark each trend change.
4.Enable Risk Management to see SL/TP lines and the P&L dashboard on each confirmed signal.
5.Monitor the Short Trend Dashboard for real-time confirmation. CONSENSUS +4/5 or +5/5 indicates strong alignment across all components.
▸ Tuning the Pivot Detection
•Left 5 / Right 5: Maximum accuracy. Pivot must be highest/lowest of 11 bars. 5-bar confirmation delay. Best for identifying only major swing points.
•Left 5 / Right 1: Strong selectivity, minimal delay. Preview label flickers on the confirmation bar. Good balance for scalping and active trading.
•Left 5 / Right 0: Zero-delay mode. Label appears on the pivot bar during formation. Fastest possible signal. Useful for scalping when combined with the SMI filter.
•Left 8–10 / Right 0: Zero delay with larger left lookback to compensate for missing right-side confirmation.
▸ Configuring Risk Management
•Enable the Risk Management Overlay toggle. Set Stop Loss in points (e.g., MNQ: 3–5 pts) or as a percentage of entry price.
•Set TP1, TP2, TP3 as Reward:Risk multiples (defaults: 2:1, 3:1, 4:1). Adjust to your trading style.
•Set Point Value for your instrument: MNQ = 2, MES = 5, MYM = 0.5, MGC = 10, MCL = 10.
•The P&L dashboard updates every bar showing dollar P&L, R:R ratio, and TP hit status.
•Enable trailing stop for trades that run: set breakeven threshold, trail start, and trail offset distances.
▸ Reading the Short Trend Dashboard
•Direction + Score: BULLISH/BEARISH/LEAN with a score of 0–100. Grade A+ or A = high conviction.
•TEMP Heat Gauge: Above 70 = HOT (overbought). Below 30 = COLD (oversold). 45–55 = NEUTRAL.
•CONSENSUS: Total vote out of 5 components. +4/5 or +5/5 = strong directional alignment.
•Scalper Mode: Ultra-fast presets for 1–5 min charts. Instant Flip marks single-bar reversals with ** notation.
▸ Label Display Options
•Stack: Label sits directly on the high/low with offset ticks. Text stacks vertically with optional timestamp.
•Pointer: Label offset to the side with a pointer coming off the corner pointing at the exact high/low of the bar.
•Timestamp: Five formats: HH:mm, HH:mm:ss, h:mm a, MMM dd HH:mm, MMM dd. Uses the chart’s time zone.
▸ Suggested Starting Settings
•Scalping (1–5 min): Left 5, Right 1, HMA Length 9–14, Scalper Mode ON, SL 3–5 pts
•Day Trading (5–15 min): Left 5, Right 2–3, HMA Length 14–20, Scalper Mode OFF, SL 5–10 pts
•Swing Trading (1H–4H): Left 5, Right 5, HMA Length 20–50, Scalper Mode OFF, SL 10–25 pts
•Zero-Lag Mode: Left 7–10, Right 0, SMI Filter ON, HMA Length 14, Scalper Mode ON
DISCLAIMER
This indicator is a technical analysis tool designed to assist with identifying potential swing reversal points, trend direction, and trade risk parameters. It is not a standalone trading system and does not constitute financial advice. No indicator can predict future price movement. Past performance of any signal methodology does not guarantee future results. Always use proper risk management and consider multiple sources of analysis. The author assumes no responsibility for trading losses. Use at your own risk. Indicator
ROC + SMI Auto Adjust
This indicator combines the Rate of Change (ROC) and the Stochastic Momentum Index (SMI) with automatically adjusted parameters for different time frames (short, medium, long). It normalizes the ROC to match the SMI levels, displays the ROC as a histogram and the SMI as lines, highlights overbought/oversold zones and includes a settings table. Ideal for analyzing momentum on different time frames.
Key Features:
Automatic Parameter Adjustment:
The script detects the current chart time frame (e.g. 1-minute, 1-hour, daily) and adjusts the parameters for the ROC and SMI accordingly.
Parameters such as ROC length, SMI length and smoothing periods are optimized for short, medium and long term time frames.
Rate of Change (ROC):
ROC measures the percentage change in price over a specified period.
The script normalizes the ROC values to match the SMI range, making it easier to compare the two indicators on the same scale.
The ROC is displayed as a histogram, where positive values are colored green and negative values are colored red.
Stochastic Momentum Index (SMI):
SMI is a momentum oscillator that identifies overbought and oversold conditions.
The script calculates the SMI and its signal line, plotting them on the chart.
Overbought and oversold levels are displayed as dotted lines for convenience.
SMI and SMI Signal Crossover:
When the main SMI crosses the signal line from below upwards, it may be a buy signal (bullish signal).
When the SMI crosses the signal line from above downwards, it may be a sell signal (bearish signal).
Configurable Inputs:
Users can use the automatically adjusted settings or manually override the parameters (e.g. ROC length, SMI length, smoothing periods).
Overbought and oversold levels for SMI are also configurable.
Parameter Table:
A table is displayed on the chart showing the current parameters (e.g. timeframe, ROC length, SMI length) for transparency and debugging.
The position of the table is configurable (e.g. top left, bottom right).
How it works:
The script first detects the chart timeframe and classifies it as short-term (e.g. 1M, 5M), medium-term (e.g. 1H, 4H) or long-term (e.g. D1, W1).
Based on the timeframe, it sets default values for the ROC and SMI parameters.
ROC and SMI are calculated and normalized so that they can be compared on the same scale.
ROC is displayed as a histogram, while SMI and its signal line are displayed as lines.
Overbought and oversold levels are displayed as horizontal lines.
Use cases:
Trend identification: ROC helps to identify the strength of the trend, while SMI indicates overbought/oversold conditions.
Momentum analysis: The combination of ROC and SMI provides insight into both price momentum and potential reversals.
Time frame flexibility: The auto-adjustment feature makes the script suitable for scalping (short-term), swing trading (medium-term) and long-term investing.
Indicator
Smart Money Index + True Strength IndexThe Smart Money Index + True Strength Index indicator is a combination of two popular technical analysis indicators: the Smart Money Index (SMI) and the True Strength Index (TSI). This combined indicator helps traders identify potential entry points for long and short positions based on signals from both indexes.
Main Components:
Smart Money Index (SMI):
The SMI measures the difference between the closing and opening price of a candle multiplied by the trading volume over a certain period of time. This allows you to assess the activity of large players ("smart money") in the market. If the SMI value is above a certain threshold (smiThreshold), it may indicate a bullish trend, and if lower, it may indicate a bearish trend.
True Strength Index (TSI):
The TSI is an oscillator that measures the strength of a trend by comparing the price change of the current bar with the previous bar. It uses two exponential moving averages (EMAS) to smooth the data. TSI values can fluctuate around zero, with values above the overbought level indicating a possible downward correction, and values below the oversold level signaling a possible upward correction.
Parameters:
SMI Length: Defines the number of candles used to calculate the average SMI value. The default value is 14.
SMI Threshold: A threshold value that is used to determine a buy or sell signal. The default value is 0.
Length of the first TSI smoothing (tsiLength1): The length of the first EMA for calculating TSI. The default value is 25.
Second TSI smoothing length (tsiLength2): The length of the second EMA for additional smoothing of TSI values. The default value is 13.
TSI Overbought level: The level at which the market is considered to be overbought. The default value is 25.
Oversold level TSI: The level at which it is considered that the market is in an oversold state. The default value is -25.
Logic of operation:
SMI calculation:
First, the difference between the closing and opening price of each candle (close - open) is calculated.
This difference is then multiplied by the trading volume.
The resulting product is averaged using a simple moving average (SMA) over a specified period (smiLength).
Calculation of TSI:
The price change relative to the previous bar is calculated (close - close ).
The first EMA with the length tsiLength1 is applied.
Next, a second EMA with a length of tsiLength2 is applied to obtain the final TSI value.
The absolute value of price changes is calculated in the same way, and two emas are also applied.
The final TSI index is calculated as the ratio of these two values multiplied by 100.
Graphical representation:
The SMI and TSI lines are plotted on the graph along with their respective thresholds.
For SMI, the line is drawn in orange, and the threshold level is dotted in gray.
For the TSI, the line is plotted in blue, the overbought and oversold levels are indicated by red and green dotted lines, respectively.
Conditions for buy/sell signals:
A buy (long) signal is generated when:
SMI is greater than the threshold (smi > smiThreshold)
TSI crosses the oversold level from bottom to top (ta.crossover(tsi, oversold)).
A sell (short) signal is generated when:
SMI is less than the threshold (smi < smiThreshold)
TSI crosses the overbought level from top to bottom (ta.crossunder(tsi, overbought)).
Signal display:
When the conditions for a long or short are met, labels labeled "LONG" or "SHORT" appear on the chart.
The label for the long is located under the candle and is colored green, and for the short it is above the candle and is colored red.
Notification generation:
The indicator also supports notifications via the PulseWire platform. Notifications are sent when conditions arise for a long or short position.
This combined indicator provides the trader with the opportunity to use both SMI and TSI signals simultaneously, which can improve the accuracy of trading decisions.
Indicator
SMI Ergodic Indicator/Oscillator▮ Introduction
The Stochastic Momentum Index Ergodic Indicator (SMII) is a technical analysis tool designed to predict trend reversals in the price of an asset.
It functions as a momentum oscillator, measuring the ratio of the smoothed price change to the smoothed absolute price change over a given number of previous periods.
The Ergodic SMI is based on the True Strength Index (TSI) and integrates a signal line, which is an exponential moving average (EMA) of the SMI indicator itself.
It provides a clearer picture of market trends than the traditional stochastic oscillator by incorporating the concept of "ergodicity", which helps remove market noise.
On ther other hand, the Stochastic Momentum Index Ergodic Oscillator (SMIO) is a histogram that measures the difference between TSI and it's signal line.
By default, in PulseWire both SMII and SMIO are provided independently.
Here in this script these two indicators are combined, providing a more comprehensive view of price direction and market strength.
▮ Motivation: why another indicator?
The intrinsic value of this indicator lies in the fact that it allows fine adjustments in both calculation parameters, data source and visualization, features that are not present in the standard indicators or similar.
Also, trend lines breakouts and divergences detector were added.
▮ What to look for
When using the indicator, there are a few things to look out for.
First, look at the SMI signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMI and the price.
If price is rising but the SMI is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMI is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
Divergences can be considered in both indicator and/or histogram.
Examples:
▮ Notes
The indicator presented here offers both the "SMII" and the "SMIO", that is, the "Stochastic Momentum Index Ergodic Indicator" together with the "Stochastic Momentum Index Ergodic Oscillator" (histogram), as per the documentation described in reference links.
So it is important to highlight the differences in relation to my other indicator, Stochastic Momentum Index (SMI) Refurbished .
This last one is purely based on the **SMI**, which is implemented using smoothed ratio between the relative range and the high/low range.
Although they may seem the same in some situations, the calculation is actually different. The TSI tends to be more responsive at the expense of being noisier, while the SMI tends to be smoother. Which of these two indicators is best depends on the situation, the context, and the analyst's personal preference.
Please refer to reference links to more info.
▮ References
SMI documentation
SMII documentation
SMIO documentation
Indicator
SMI Ergodic Indicator/Oscillator of Money Flow Index▮ Introduction
The Stochastic Momentum Index Ergodic (SMII) indicator is a technical analysis tool designed to predict trend reversals in the price of an asset.
It functions as a momentum oscillator, measuring the ratio of the smoothed price change to the smoothed absolute price change over a given number of previous periods.
The Ergodic SMI is based on the True Strength Index (TSI) and integrates a signal line, which is an exponential moving average (EMA) of the SMI indicator itself.
The Ergodic SMI oscillator provides a clearer picture of market trends than the traditional stochastic oscillator by incorporating the concept of 'ergodicity', which helps remove market noise.
On ther other hand, MFI (Money Flow Index) is a technical analysis indicator used to measure the inflow of money into an asset and thus help identify buying and selling pressure in a given financial instrument.
When these two indicators are combined, they can provide a more comprehensive view of price direction and market strength.
▮ Motivation: why another indicator?
By combining SMII with MFI, we can gain even more insights into the market.
One way to do this is to use the MFI as an input to the SMII, rather than just using price.
This means we are measuring momentum based on buying and selling pressure rather than just price.
Furthermore, there is the possibility of making several fine adjustments to both the calculation and visualization parameters that are not present in other indicators.
▮ What to look for
When using the SMII MFI indicator, there are a few things to look out for.
First, look at the SMII signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMII and the price.
If price is rising but the SMII is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMII is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
Divergences can be considered in both indicator and/or histogram.
Examples:
▮ Notes
The indicator presented here offers both the 'SMII' and the 'SMIO', that is, the 'Stochastic Momentum Index Ergodic Indicator' together with the 'Stochastic Momentum Index Ergodic Oscillator' (histogram), as per the documentation described in reference links.
So it is important to highlight the differences in relation to my other indicator, the 'Stochastic Momentum Index (SMI) of Money Flow Index (MFI)':
This last one is purely based on the SMI , which is implemented using SMA smoothing for the relative range and the high/low range.
Although they may seem the same in some situations, the calculation is actually different. The TSI tends to be more responsive at the expense of being noisier, while the SMI tends to be smoother. Which of these two indicators is best depends on the situation, the context, and the analyst's personal preference.
Please refer to reference links to more info.
▮ References
SMI documentation
SMII documentation
SMIO documentation
MFI documentation Indicator
Harmonic Trend Fusion [kikfraben]📈 Harmonic Trend Fusion - Your Personal Trading Assistant
This versatile tool combines multiple indicators to provide a holistic view of market trends and potential signals.
🚀 Key Features:
Multi-Indicator Synergy: Benefit from the combined insights of Aroon, DMI, MACD, Parabolic SAR, RSI, Supertrend, and SMI Ergodic Oscillator, all in one powerful indicator.
Customizable Plot Options: Tailor your chart by choosing which signals to visualize. Whether you're interested in trendlines, histograms, or specific indicators, the choice is yours.
Color-Coded Trends: Quickly identify bullish and bearish trends with the color-coded visualizations. Stay ahead of market movements with clear and intuitive signals.
Table Display: Stay informed at a glance with the interactive table. It dynamically updates to reflect the current market sentiment, providing you with key information and trend direction.
Precision Control: Fine-tune your analysis with precision control over indicator parameters. Adjust lengths, colors, and other settings to align with your unique trading strategy.
🛠️ How to Use:
Customize Your View: Select which indicators to display and adjust plot options to suit your preferences.
Table Insights: Monitor the dynamic table for real-time updates on market sentiment and trend direction.
Indicator Parameters: Experiment with different lengths and settings to find the combination that aligns with your trading style.
Whether you're a seasoned trader or just starting, Harmonic Trend Fusion equips you with the tools you need to navigate the markets confidently. Take control of your trading journey and enhance your decision-making process with this comprehensive trading assistant. Indicator
Stochastic Momentum Index (SMI) of Money Flow Index (MFI)"He who does not know how to make predictions and makes light of his opponents, underestimating his ability, will certainly be defeated by them."
(Sun Tzu - The Art of War)
▮ Introduction
The Stochastic Momentum Index (SMI) is a technical analysis indicator that uses the difference between the current closing price and the high or low price over a specific time period to measure price momentum.
On the other hand, the Money Flow Index (MFI) is an indicator that uses volume and price to measure buying and selling pressure.
When these two indicators are combined, they can provide a more comprehensive view of price direction and market strength.
▮ Improvements
By combining SMI with MFI, we can gain even more insights into the market. One way to do this is to use the MFI as an input to the SMI, rather than just using price.
This means we are measuring momentum based on buying and selling pressure rather than just price.
Another way to improve this indicator is to adjust the periods to suit your specific trading needs.
▮ What to look
When using the SMI MFI indicator, there are a few things to look out for.
First, look at the SMI signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMI MFI and the price.
If price is rising but the SMI MFI is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMI MFI is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
In the examples below, I show the use in conjunction with the price SMI, in which the MFI SMI helps to anticipate divergences:
In summary, the SMI MFI is a useful indicator that can provide valuable insights into market direction and price strength.
By adjusting the timeframes and paying attention to divergences and signal line crossovers, traders can use it as part of a broader trading strategy.
However, remember that no indicator is a magic bullet and should always be used in conjunction with other analytics and indicators to make informed trading decisions. Indicator
Stochastic Momentum Index (SMI) Refurbished▮Introduction
Stochastic Momentum Index (SMI) Indicator is a technical indicator used in technical analysis of stocks and other financial instruments.
It was developed by William Blau in 1993 and is considered to be a momentum indicator that can help identify trend reversal points.
Basically, it's a combination of the True Strength Index with a signal line to help identify turning points in the market.
SMI uses the stochastic formula to compare the current closing price of an asset with the maximum and minimum price range over a specific period.
He then compares this ratio to a short-term moving average to create an indicator that oscillates between -100 and +100.
When the SMI is above 0, it is considered positive, indicating that the current price is above the short-term moving average.
When it is below 0, it is considered negative, indicating that the current price is below the short-term moving average.
Traders use the SMI to identify potential trend reversal points.
When the indicator reaches an extreme level above +40 or below -40, a trend reversal is possible.
Furthermore, traders also watch for divergences between the SMI and the asset price to identify potential trading opportunities.
It is important to remember that the SMI is a technical indicator and as such should be used in conjunction with other technical analysis tools to get a complete picture of the market situation.
▮ Improvements
The following features were added:
1. 7 color themes, for TSI, Signal and Histogram.
2. Possibility to customize moving average type for TSI/Signal.
3. Dynamic Zones.
4. Crossing Alerts.
5. Alert points on specific ranges.
5. Coloring of bars according to TSI/Signal/Histogram.
▮ Themes
Examples:
▮ About Dynamic Zones
'Most indicators use a fixed zone for buy and sell signals.
Here's a concept based on zones that are responsive to the past levels of the indicator.'
The concept of Dynamic Zones was described by Leo Zamansky ( Ph .D.) and David Stendahl, in the magazine of Stocks & Commodities V15:7 (306-310).
Basically, a statistical calculation is made to define the extreme levels, delimiting a possible overbought/oversold region.
Given user-defined probabilities, the percentile is calculated using the method of Nearest Rank.
It is calculated by taking the difference between the data point and the number of data points below it, then dividing by the total number of data points in the set.
The result is expressed as a percentage.
This provides a measure of how a particular value compares to other values in a data set, identifying outliers or values that are significantly higher or lower than the rest of the data.
▮ What to look for
1. Divergences/weakening of a trend/reversal:
2. Supports, resistances, pullbacks:
3. Overbought/Oversold Points:
▮ Thanks and Credits
- PulseWire and PineCoders: for SMI and Moving Averages
- allanster: for Dynamic Zones Indicator
MomentumIndicatorsLibrary "MomentumIndicators"
This is a library of 'Momentum Indicators', also denominated as oscillators.
The purpose of this library is to organize momentum indicators in just one place, making it easy to access.
In addition, it aims to allow customized versions, not being restricted to just the price value.
An example of this use case is the popular Stochastic RSI.
# Indicators:
1. Relative Strength Index (RSI):
Measures the relative strength of recent price gains to recent price losses of an asset.
2. Rate of Change (ROC):
Measures the percentage change in price of an asset over a specified time period.
3. Stochastic Oscillator (Stoch):
Compares the current price of an asset to its price range over a specified time period.
4. True Strength Index (TSI):
Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the
absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized
in a range between 100 and -100.
5. Stochastic Momentum Index (SMI):
Combination of the True Strength Index with a signal line to help identify turning points in the market.
6. Williams Percent Range (Williams %R):
Compares the current price of an asset to its highest high and lowest low over a specified time period.
7. Commodity Channel Index (CCI):
Measures the relationship between an asset's current price and its moving average.
8. Ultimate Oscillator (UO):
Combines three different time periods to help identify possible reversal points.
9. Moving Average Convergence/Divergence (MACD):
Shows the difference between short-term and long-term exponential moving averages.
10. Fisher Transform (FT):
Normalize prices into a Gaussian normal distribution.
11. Inverse Fisher Transform (IFT):
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is through the
application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity, to a scale limited
between -1 and +1, allowing them to be more easily visualized and compared.
12. Premier Stochastic Oscillator (PSO):
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing average of
the %K value, resulting in a symmetric scale of 1 to -1
# Indicators of indicators:
## Stochastic:
1. Stochastic of RSI (Relative Strengh Index)
2. Stochastic of ROC (Rate of Change)
3. Stochastic of UO (Ultimate Oscillator)
4. Stochastic of TSI (True Strengh Index)
5. Stochastic of Williams R%
6. Stochastic of CCI (Commodity Channel Index).
7. Stochastic of MACD (Moving Average Convergence/Divergence)
8. Stochastic of FT (Fisher Transform)
9. Stochastic of Volume
10. Stochastic of MFI (Money Flow Index)
11. Stochastic of On OBV (Balance Volume)
12. Stochastic of PVI (Positive Volume Index)
13. Stochastic of NVI (Negative Volume Index)
14. Stochastic of PVT (Price-Volume Trend)
15. Stochastic of VO (Volume Oscillator)
16. Stochastic of VROC (Volume Rate of Change)
## Inverse Fisher Transform:
1.Inverse Fisher Transform on RSI (Relative Strengh Index)
2.Inverse Fisher Transform on ROC (Rate of Change)
3.Inverse Fisher Transform on UO (Ultimate Oscillator)
4.Inverse Fisher Transform on Stochastic
5.Inverse Fisher Transform on TSI (True Strength Index)
6.Inverse Fisher Transform on CCI (Commodity Channel Index)
7.Inverse Fisher Transform on Fisher Transform (FT)
8.Inverse Fisher Transform on MACD (Moving Average Convergence/Divergence)
9.Inverse Fisher Transfor on Williams R% (Williams Percent Range)
10.Inverse Fisher Transfor on CMF (Chaikin Money Flow)
11.Inverse Fisher Transform on VO (Volume Oscillator)
12.Inverse Fisher Transform on VROC (Volume Rate of Change)
## Stochastic Momentum Index:
1.Stochastic Momentum Index of RSI (Relative Strength Index)
2.Stochastic Momentum Index of ROC (Rate of Change)
3.Stochastic Momentum Index of VROC (Volume Rate of Change)
4.Stochastic Momentum Index of Williams R% (Williams Percent Range)
5.Stochastic Momentum Index of FT (Fisher Transform)
6.Stochastic Momentum Index of CCI (Commodity Channel Index)
7.Stochastic Momentum Index of UO (Ultimate Oscillator)
8.Stochastic Momentum Index of MACD (Moving Average Convergence/Divergence)
9.Stochastic Momentum Index of Volume
10.Stochastic Momentum Index of MFI (Money Flow Index)
11.Stochastic Momentum Index of CMF (Chaikin Money Flow)
12.Stochastic Momentum Index of On Balance Volume (OBV)
13.Stochastic Momentum Index of Price-Volume Trend (PVT)
14.Stochastic Momentum Index of Volume Oscillator (VO)
15.Stochastic Momentum Index of Positive Volume Index (PVI)
16.Stochastic Momentum Index of Negative Volume Index (NVI)
## Relative Strength Index:
1. RSI for Volume
2. RSI for Moving Average
rsi(source, length)
RSI (Relative Strengh Index). Measures the relative strength of recent price gains to recent price losses of an asset.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of RSI
roc(source, length)
ROC (Rate of Change). Measures the percentage change in price of an asset over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of ROC
stoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Compares the current price of an asset to its price range over a specified time period.
Parameters:
kLength
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Oscillator and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Oscillator and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Oscillator and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
stoch(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Customized source. Compares the current price of an asset to its price range over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
kLength : (int) Period of loopback to calculate the stochastic
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Stoch and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Stoch and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Stoch and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
tsi(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet)
TSI (True Strengh Index). Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized in a range between 100 and -100.
Parameters:
source : (float) Source of series (close, high, low, etc.)
shortLength : (int) Short length
longLength : (int) Long length
maType : (int) Type of Moving Average for TSI
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) TSI
smi(sourceTSI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
SMI (Stochastic Momentum Index). A TSI (True Strengh Index) plus a signal line.
Parameters:
sourceTSI : (float) Source of series for TSI (close, high, low, etc.)
shortLengthTSI : (int) Short length for TSI
longLengthTSI : (int) Long length for TSI
maTypeTSI : (int) Type of Moving Average for Signal of TSI
almaOffsetTSI : (float) Offset for Arnaud Legoux Moving Average
almaSigmaTSI : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSetTSI : (int) Offset for Least Squares Moving Average
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
Returns: A tuple with TSI, signal of TSI and histogram of difference
wpr(source, length)
Williams R% (Williams Percent Range). Compares the current price of an asset to its highest high and lowest low over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of Williams R%
cci(source, length, maType, almaOffset, almaSigma, lsmaOffSet)
CCI (Commodity Channel Index). Measures the relationship between an asset's current price and its moving average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
maType : (int) Type of Moving Average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) Series of CCI
ultimateOscillator(fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Combines three different time periods to help identify possible reversal points.
Parameters:
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
ultimateOscillator(source, fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Customized source. Combines three different time periods to help identify possible reversal points.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
macd(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet)
MACD (Moving Average Convergence/Divergence). Shows the difference between short-term and long-term exponential moving averages.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Period for fast moving average
slowLength : (int) Period for slow moving average
signalLength : (int) Signal length
maTypeFast : (int) Type of fast moving average
maTypeSlow : (int) Type of slow moving average
maTypeMACD : (int) Type of MACD moving average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: A tuple with MACD, Signal, and Histgram
fisher(length)
Fisher Transform. Normalize prices into a Gaussian normal distribution.
Parameters:
length
Returns: A tuple with Fisher Transform and signal
fisher(source, length)
Fisher Transform. Customized source. Normalize prices into a Gaussian normal distribution.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length
Returns: A tuple with Fisher Transform and signal
inverseFisher(source, length, subtrahend, denominator)
Inverse Fisher Transform.
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is
through the application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity,
to a scale limited between -1 and +1, allowing them to be more easily visualized and compared.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period for loopback
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of Inverse Fisher Transform
premierStoch(length, smoothlen)
Premier Stochastic Oscillator (PSO).
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing
average of the %K value, resulting in a symmetric scale of 1 to -1.
Parameters:
length : (int) Period for loopback
smoothlen : (int) Period for smoothing
Returns: (float) Series of PSO
premierStoch(source, smoothlen, subtrahend, denominator)
Premier Stochastic Oscillator (PSO) of custom source.
Normalizes the source by applying a five-period double exponential smoothing average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
smoothlen : (int) Period for smoothing
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of PSO
stochRsi(sourceRSI, lengthRSI, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceRSI
lengthRSI
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochRoc(sourceROC, lengthROC, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceROC
lengthROC
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochUO(fastLength, middleLength, slowLength, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
fastLength
middleLength
slowLength
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochWPR(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochFT(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVolume(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMFI(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochOBV(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochNVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVT(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVROC(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
iftRSI(sourceRSI, lengthRSI, lengthIFT)
Parameters:
sourceRSI
lengthRSI
lengthIFT
iftROC(sourceROC, lengthROC, lengthIFT)
Parameters:
sourceROC
lengthROC
lengthIFT
iftUO(fastLength, middleLength, slowLength, lengthIFT)
Parameters:
fastLength
middleLength
slowLength
lengthIFT
iftStoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD, lengthIFT)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
lengthIFT
iftTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftFisher(length, lengthIFT)
Parameters:
length
lengthIFT
iftMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftWPR(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftMFI(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftCMF(length, lengthIFT)
Parameters:
length
lengthIFT
iftVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftVROC(length, lengthIFT)
Parameters:
length
lengthIFT
smiRSI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiROC(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVROC(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiWPR(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCCI(source, length, maTypeCCI, almaOffsetCCI, almaSigmaCCI, lsmaOffSetCCI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
maTypeCCI
almaOffsetCCI
almaSigmaCCI
lsmaOffSetCCI
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiUO(fastLength, middleLength, slowLength, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
fastLength
middleLength
slowLength
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVol(shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMFI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCMF(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiOBV(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVT(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiNVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
rsiVolume(length)
Parameters:
length
rsiMA(sourceMA, lengthMA, maType, almaOffset, almaSigma, lsmaOffSet, lengthRSI)
Parameters:
sourceMA
lengthMA
maType
almaOffset
almaSigma
lsmaOffSet
lengthRSI Library
Multi SMI Ergodic OscillatorThe Multi SMI Ergodic Oscillator (Multi SMIEO) indicator can be used to identify potential buy and sell signals based on the relationship between the TSI and EMA lines.
The script is creating an indicator that plots multiple (3) sets of Time Series Indicator (TSI-Indicator) and Exponential Moving Average (EMA-Signal) lines as a single indicator.
The TSI is a momentum oscillator that helps identify overbought and oversold conditions. It is calculated using the close prices of an asset, a short-term moving average, and a long-term moving average. The script uses three different pairs of input values for the short-term and long-term periods, which can be adjusted by the user.
The EMA is a type of moving average that gives more weight to recent prices. It is calculated by applying a weighting factor to the most recent price, and then adding that weighted value to the previous EMA value. The script uses three different input values for the length of the EMA, which can also be adjusted by the user.
After calculating the TSI and EMA for each set, the script plots them on the same graph, with different colors and widths to differentiate them. The three sets of TSI and EMA lines are plotted to allow the user to compare the results of different periods. The script also plots a horizontal line at zero, which is used as a reference point for the oscillations of the indicator lines.
One way to use this indicator is to look for crossovers between the TSI and the EMA lines. A bullish crossover occurs when the TSI crosses above the EMA. This suggests that the buying pressure is increasing and a potential buy signal is generated. A bearish crossover occurs when the TSI crosses below the EMA. This suggests that the selling pressure is increasing and a potential sell signal is generated.
Some other ways that the indicator can be used include:
1. Identifying trends: The TSI and EMA lines can be used to identify the direction of the trend. An uptrend is present when the TSI and EMA lines are both trending upwards, while a downtrend is present when the TSI and EMA lines are both trending downwards.
2. Overbought and oversold conditions: The TSI can be used to identify overbought and oversold conditions. When the TSI is above the upper limit of the range, the asset is considered overbought and may be due for a price correction. Conversely, when the TSI is below the lower limit of the range, the asset is considered oversold and may be due for a price rebound.
3. Confirming price action: The Multi SMIEO indicator can be used to confirm price action. If a bullish divergence is present, it confirms a potential bullish reversal. If a bearish divergence is present, it confirms a potential bearish reversal.
4. Multiple time frame analysis: By using different periods for the TSI and EMA lines, the indicator can be used to analyze the asset on multiple time frames. It can be useful to compare the results of different periods to get a better understanding of the asset's price movements.
5. Risk management: This indicator can be used as an element of risk management strategy, it can help traders to identify overbought and oversold conditions to set stop loss or take profit levels.
The Multi SMI Ergodic Oscillator (Multi SMIEO) is a versatile indicator that can be used in a number of ways to analyze the price movements of an asset. It can be used to identify potential buy and sell signals, trends, overbought and oversold conditions, and to confirm price action. By using different periods for the TSI and EMA lines, the indicator can also be used to analyze the asset on multiple time frames. However, it is important to remember that indicators are based on historical data, and past performance does not guarantee future results.
It is important to use the indicator as part of a comprehensive trading strategy that includes risk management and other analysis techniques, such as fundamental and technical analysis. It is also important to keep in mind that indicators are not a standalone solution for trading, they should be used in conjunction with other market analysis and research techniques to generate better results.
Lastly, it is important to keep in mind that trading in financial markets comes with a certain level of risk and it is crucial to always have a proper risk management plan in place. Never invest more than you can afford to lose.
Indicator
Indicator
All TimeFrame OscillatorsI have always fighted to understand the market direction because it looks different on different timeframes.
I wanted an indicator where I can see all the different timeframes at once.
This indicator shows already existing oscillators but not only in the current chart's timeframe, but all the most important higer timeframes at once.
I have started with the stoch, then added as many oscillators as I could.
Experimenting with this I have saw that confluence of 4H 1D and 1W Stoch can be very interesting and can highlight higher timeframe take profit areas and sometimes major tops/bottoms.
Also bounces can be interesting when a lower timeframe stoch is bounced or rejected from a higher one.
Oscillators:
Stoch - Stochastic Oscillator
SMI - Stochastic Momentum Index
Rsi - Relative Strength Index
StochRsi - Stochastic RSI
WaveTrend - Vumanchu alias Market Cypher Wave Trend line
CCI - Commodity Channel Index
CCIStoch - Stochastic CCI
Williams Percent Range - Williams %R
Norm. MACD - Normalized Moving Average Convergence Divergence
Norm. MACD Hist - Normalized MACD Histogramm
PVT - Normalized Price Volume Trend
MFI - Money Flow Index
CMF - Chaikin Money Flow
Chande Momentum - Chande Momentum
Volume - Normalized Volume
CandleValue - Vumanchu alias Market Cypher MoneyFlow
BBWP - Bollinger Band Width Percentile
Line Type
Smooth: lines are smoothed, but the actualy not closed values are not shown
Step: Step lines, the actually open timeframes are calculated as they closed at the current values
Plot Oscillator or it's Slope:
its possible to not plot the oscillator but it's slope
Print dots when:
Cross Up/Down oversold/overbougt level - best for most oscillators. for example when Stoch crosses above 20 or below 80
Cross os/ob and the one higher TF is about to cross - when it's crosses beolw 80 and the higher timeframe oscillator is still above ans sloping down
Cross above/below middle line - for example on RSI being above or below 50 can be interesting
Print triangles when:
All Slope Match - all visible timeframe lines are pointing up or down at the same time
All above/belove middle line - all visible lines are above or belove the middle line
All above/belove middle line and slope match - like the previous one and the slope direction is the same
All above/below oversold/overbougt - all lines are above or below os/ ob. this is the default. it can be a very important confluence
Lower TF in order - 5, 15, 30, 60 minute timeframes are in order.
Higher TF in order - 4H 1D 1W in order (like 4H above 1D abd 1D above 1W). can be interesting at RSI
4H-1D in order - 4H 1D in order .
Print triangles
Print all triangles - print all triangles when the condition is met
Print only first triangles - only show when the condition starts to met
Print only last triangles - small triangles when the condition met first, large when last. tis is the default.
Timeframes to show:
You can turn on/off different timeframs to show or not from the list below:
1m 5m 15m 30m 1H 4H D 5D W M
This is for experimenting/ understanding the market direction on multiple timeframes at once.
Don't take it's signals (and any other indicator's) as exact trade signals. use it as confirmation instead.
Any comments, insights, ideas are welcome.
Indicator
Strategy
Combo Backtest 123 Reversal & Smart Money Index (SMI) This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
Smart money index (SMI) or smart money flow index is a technical analysis indicator demonstrating investors sentiment.
The index was invented and popularized by money manager Don Hays. The indicator is based on intra-day price patterns.
The main idea is that the majority of traders (emotional, news-driven) overreact at the beginning of the trading day
because of the overnight news and economic data. There is also a lot of buying on market orders and short covering at the opening.
Smart, experienced investors start trading closer to the end of the day having the opportunity to evaluate market performance.
Therefore, the basic strategy is to bet against the morning price trend and bet with the evening price trend. The SMI may be calculated
for many markets and market indices (S&P 500, DJIA, etc.)
The SMI sends no clear signal whether the market is bullish or bearish. There are also no fixed absolute or relative readings signaling
about the trend. Traders need to look at the SMI dynamics relative to that of the market. If, for example, SMI rises sharply when the
market falls, this fact would mean that smart money is buying, and the market is to revert to an uptrend soon. The opposite situation
is also true. A rapidly falling SMI during a bullish market means that smart money is selling and that market is to revert to a downtrend
soon. The SMI is, therefore, a trend-based indicator.
Some analysts use the smart money index to claim that precious metals such as gold will continually maintain value in the future.
WARNING:
- For purpose educate only
- This script to change bars colors. Strategy
Strategy
Strategy
Indicator
Indicator
Indicator
Smart Money Index (SMI) Backtest Attention:
If you would to use this indicator on the ES, you should have intraday data 60min in your account.
Smart money index (SMI) or smart money flow index is a technical analysis indicator demonstrating investors sentiment.
The index was invented and popularized by money manager Don Hays. The indicator is based on intra-day price patterns.
The main idea is that the majority of traders (emotional, news-driven) overreact at the beginning of the trading day
because of the overnight news and economic data. There is also a lot of buying on market orders and short covering at the opening.
Smart, experienced investors start trading closer to the end of the day having the opportunity to evaluate market performance.
Therefore, the basic strategy is to bet against the morning price trend and bet with the evening price trend. The SMI may be calculated
for many markets and market indices (S&P 500, DJIA, etc.)
The SMI sends no clear signal whether the market is bullish or bearish. There are also no fixed absolute or relative readings signaling
about the trend. Traders need to look at the SMI dynamics relative to that of the market. If, for example, SMI rises sharply when the
market falls, this fact would mean that smart money is buying, and the market is to revert to an uptrend soon. The opposite situation
is also true. A rapidly falling SMI during a bullish market means that smart money is selling and that market is to revert to a downtrend
soon. The SMI is, therefore, a trend-based indicator.
Some analysts use the smart money index to claim that precious metals such as gold will continually maintain value in the future.
You can change long to short in the Input Settings
WARNING:
- For purpose educate only
- This script to change bars colors. Strategy
Smart Money Index (SMI) Strategy Attention:
If you would to use this indicator on the ES, you should have intraday data 60min in your account.
Smart money index (SMI) or smart money flow index is a technical analysis indicator demonstrating investors sentiment.
The index was invented and popularized by money manager Don Hays. The indicator is based on intra-day price patterns.
The main idea is that the majority of traders (emotional, news-driven) overreact at the beginning of the trading day
because of the overnight news and economic data. There is also a lot of buying on market orders and short covering at the opening.
Smart, experienced investors start trading closer to the end of the day having the opportunity to evaluate market performance.
Therefore, the basic strategy is to bet against the morning price trend and bet with the evening price trend. The SMI may be calculated
for many markets and market indices (S&P 500, DJIA, etc.)
The SMI sends no clear signal whether the market is bullish or bearish. There are also no fixed absolute or relative readings signaling
about the trend. Traders need to look at the SMI dynamics relative to that of the market. If, for example, SMI rises sharply when the
market falls, this fact would mean that smart money is buying, and the market is to revert to an uptrend soon. The opposite situation
is also true. A rapidly falling SMI during a bullish market means that smart money is selling and that market is to revert to a downtrend
soon. The SMI is, therefore, a trend-based indicator.
Some analysts use the smart money index to claim that precious metals such as gold will continually maintain value in the future.
WARNING:
- This script to change bars colors. Indicator
