RSI Analytic Volume Matrix [RAVM] Overview
RSI Analytic Volume Matrix is an overlay indicator that turns classic RSI into a multi-layered market-reading engine. Instead of treating RSI 30 and 70 as simple buy/sell lines, RAVM combines RSI geometry (angle and acceleration), statistical volume analysis, and a 5×5 VSA-inspired matrix to describe what is really happening inside each candle.
The script is designed as an educational and analytical tool. It does not generate trading signals. Instead, it helps you read the market context, understand where the pressure is coming from (buyers vs. sellers), and see how price, momentum, and volume interact in real time.
Concept & Philosophy
RAVM is built around a hierarchical logic and a few core ideas:
• Hierarchical State Machine: First, RSI defines a context (where we are in the 0–100 range). Then the geometric engine evaluates the angle-of-turn of RSI using a Z-Score. Only after a meaningful geometric event is detected does the system promote a bar to a potential setup (warning vs. confirmed).
• Geometric Primacy: The angle and acceleration of RSI (RSI geometry) are more important than the raw RSI level itself. RAVM uses a geometric veto: if the geometric trigger is not confirmed, the confidence score is capped below 50%, even if volume looks interesting.
• RSI Beyond 30 and 70: Being above 70 or below 30 is not treated as an automatic overbought/oversold signal. RAVM treats those zones as contextual factors that contribute only a partial portion of the final score, alongside geometry, total volume expansion, buy/sell balance, and delta power.
• Volume Decomposition: Volume is decomposed into total, buy-side, sell-side, and delta components. Each of these is normalized with a Z-Score over a shared statistical window, so RSI geometry and volume live in the same statistical context.
• Educational Scoring Pipeline: RAVM builds a 0–100 "Quantum Score" for each detected setup. The score expresses how strong the story is across four dimensions: geometry (RSI angle-of-turn), total volume expansion, which side is driving that volume (buyers vs. sellers), and the power of delta. The score is designed for learning and weighting, not for mechanical trade entries.
• VSA Matrix Engine: A 5×5 matrix combines momentum states and volume dynamics. Each cell corresponds to an interpreted VSA-style scenario (Absorption, Distribution, No Demand, Stopping Volume, Strong Reversal, etc.), shown both as text and as a heatmap dashboard on the chart.
How RAVM Works
1. RSI Context & Geometry
RAVM starts with a classic RSI, but it does not stop at simple level checks. It computes the velocity and acceleration of RSI and normalizes them via a Z-Score to produce an Angle-of-Turn metric (Z-AoT). This Z-AoT is then mapped into a 0–1 intensity value called MSI (Momentum Shift Intensity).
The script monitors both classic RSI zones (around 30 and 70) and geometric triggers. Entering the lower or upper zone is treated as a contextual event only. A setup becomes "confirmed" when a significant geometric turn is detected (based on Z-AoT thresholds). Otherwise, the bar is at most a warning.
2. Volume & Statistical Engine
The volume engine can work in two modes: a geometric approximation (based on candle structure) or a more precise intrabar mode using up/down volume requests. In both cases, RAVM builds a volume packet consisting of:
• Total volume
• Buy-side volume
• Sell-side volume
• Delta (buy – sell)
Each of these series is normalized using a Z-Score over the same statistical window that is used for RSI geometry. This allows RAVM to answer questions such as: Is total volume exceptional on this bar? Is the expansion mostly coming from buyers or from sellers? Is delta unusually strong or weak compared to recent history?
3. Scoring System (Quantum Score)
For each bar where a setup is active, RAVM computes a 0–100 score intended as an educational confidence measure. The scoring pipeline follows this sequence:
A. RSI Geometry (MSI): Measures the strength of the RSI angle-of-turn via Z-AoT. This has geometric primacy over simple level checks.
B. RSI Zone Context: Being below 30 or above 70 contributes only a partial bonus to the score, reflecting the idea that these zones are context, not automatic signals. Mildly supportive zones (e.g., RSI below 50 for bullish contexts) can also contribute with lower weight.
C. Total Volume Expansion: A normalized Volume Power term expresses how exceptional the total volume is relative to its recent distribution. If there is no meaningful volume expansion, the score remains modest even if RSI geometry looks interesting.
D. Which Side Is Driving the Volume: RAVM then checks whether the expansion is primarily on the buy side or the sell side, using Z-Score statistics for buy and sell volume separately. This stage does not yet rely on delta as a power metric; it simply answers the question: "Is this expansion mostly driven by buyers, sellers, or both?"
E. Delta as Final Power: Only at the final stage does the script bring in delta and its Z-Score as a measure of how one-sided the pressure really is. A strong negative delta during a bullish context, for example, can highlight absorption, while a strong positive delta against a bearish context can highlight distribution or a buying climax.
If a setup is not geometrically confirmed (for example, a simple entry into RSI 30/70 without a strong geometric turn), RAVM caps the final score below 50%. This "Geometric Veto" enforces the idea that RSI geometry must confirm before a scenario can be considered high-confidence.
4. Overlay UI & Smart Labels
RAVM is an overlay indicator: all information is drawn directly on the price chart, not in a separate pane. When a setup is active, a smart label is attached to the bar, together with a vertical connector line. Each label shows:
• Direction of the setup (bullish or bearish)
• Trigger type (classic OS/OB vs. geometric/hidden)
• Status (warning vs. confirmed)
• Quantum Score as a percentage
Confirmed setups use stronger colors and solid connectors, while warnings use softer colors and dotted connectors. The script also manages label placement to avoid overlap, keeping the chart clean and readable.
In addition to labels, a dashboard table is drawn on the chart. It displays the currently active matrix scenario, the dominant bias, a short textual interpretation, the full 5×5 heatmap, and summary metrics such as RSI, MSI, and Volume Power.
RSI Is Not Just 30 and 70
One of the central design decisions in RAVM is to treat RSI 30 and 70 as context, not as fixed buy/sell buttons. Many traders mechanically assume that RSI below 30 means "buy" and RSI above 70 means "sell". RAVM explicitly rejects this simplification.
Instead, the script asks a series of deeper questions: How sharp is the angle-of-turn of RSI right now? Is total volume expanding or contracting? Is that expansion dominated by buyers or sellers? Is delta confirming the move, or is there a hidden absorption or distribution taking place?
In the scoring logic, being in a lower or upper RSI zone contributes only part of the final score. Geometry, volume expansion, the buy/sell split, and delta power all have to align before a high-confidence scenario emerges. This makes RAVM much closer to a structured market-reading tool than a classic overbought/oversold indicator.
Matrix User Manual – Reading the 5×5 Grid
The heart of RAVM is its 5×5 matrix, where the vertical axis represents momentum states (M1–M5) and the horizontal axis represents volume dynamics (V1–V5). Each cell in this grid corresponds to a VSA-style scenario. The dashboard highlights the currently active cell and prints a textual description so you can read the story at a glance.
1. Confirmation Scenarios
These scenarios occur when momentum direction and volume expansion are aligned:
• Bullish Confirmation / Strong Reversal: Momentum is shifting strongly upward (often from a depressed RSI context), and expanded volume is driven mainly by buyers. Often seen as a strong bullish reversal or continuation signal from a VSA perspective.
• Bearish Confirmation / Strong Drop: Momentum is turning decisively downward, and expanded volume is driven mainly by sellers. This maps to strong bearish continuation or sharp reversal patterns.
2. Absorption & Stopping Volume
• Absorption: Total volume expands, but the dominant flow is opposite to the recent price move or the geometric bias. For example, heavy selling volume while the geometric context is bullish. This can indicate smart money quietly absorbing orders from the crowd.
• Stopping Volume: Exceptionally high volume appears near the end of an extended move, while momentum begins to decelerate. Price may still print new extremes, but the effort vs. result relationship signals potential exhaustion and the possibility of a turn.
3. Distribution & Buying Climax
• Distribution: Heavy buying volume appears within a bearish or topping context. Rather than healthy accumulation, this often represents larger players offloading inventory to late buyers. The matrix will typically flag this as a bearish-leaning scenario despite strong upside prints.
• Buying Climax: A surge of buy-side volume near the end of a strong uptrend, with momentum starting to weaken. From a VSA point of view, this is often the last push where retail aggressively buys what smart money is selling.
4. No Demand & No Supply
• No Demand: Price attempts to rise but does so on low, non-expansive volume. The market is not interested in following the move, and the lack of participation often precedes weakness or sideways action.
• No Supply: Price tries to push lower on thin volume. Selling pressure is limited, and the lack of supply can precede stabilization or recovery if buyers step back in.
5. Trend Exhaustion
• Uptrend Exhaustion: Momentum remains nominally bullish, but the quality of volume deteriorates (e.g., more effort, less net result). The matrix marks this as an uptrend losing internal strength, often after a series of aggressive moves.
• Downtrend Exhaustion: Similar logic in the opposite direction: strong prior downtrend, but increasingly inefficient downside progress relative to the volume invested. This can precede accumulation or a relief rally.
6. Effort vs. Result Scenarios
• Bullish Effort, Little Result: Buyers invest notable volume, but price progress is limited. This may reveal hidden selling into strength or a lack of follow-through from the broader market.
• Bearish Effort, Little Result: Sellers push volume, but price does not decline proportionally. This can indicate absorption of selling pressure and potential underlying demand.
7. Neutral, Churn & Thin Markets
• Neutral / Thin Market: Momentum and volume both remain muted. RAVM marks these as neutral cells where aggressive decision-making is usually less attractive and observing the broader structure is more important.
• High Volume Churn / Volatility: Both sides are active with high volume but limited directional progress. This can correspond to battle zones, local ranges, or high volatility rotations where the main message is conflict rather than clear trend.
Inputs & Options
RAVM includes several input groups to adapt the tool to your preferences:
• Localization: Multiple language options for all labels and dashboard text (e.g., English, Farsi, Turkish, Russian).
• RSI Core Settings: RSI length, source, and upper/lower contextual zones (typically around 30 and 70).
• Geometric Engine: Z-AoT sigma thresholds, confirmation ratios, and normalization window multiplier. These control how sensitive the script is to RSI angle-of-turn events.
• Volume Engine: Choice between geometric approximation and intrabar up/down volume, Z-Score thresholds for volume expansion, and related parameters.
• Visual Interface: Toggles for smart labels, dashboard table, font sizes, dashboard position, and color themes for bullish, bearish, and warning states.
Disclaimer
RSI Analytic Volume Matrix is provided for educational and research purposes only. It does not constitute financial advice and is not a signal generator. Any trading decisions you make based on this tool, or any other, are entirely your own responsibility. Always consider your own risk management rules and conduct your own analysis.
Bestsignal
Smart Money Support/Resistance - LiteSmart Money Support/Resistance — Lite
Overview & Methodology
This indicator identifies support and resistance as zones derived from concentrated buying and selling pressure, rather than relying solely on traditional swing highs/lows. Its design focuses on transparency: how data is sourced, how zones are computed, and how the on‑chart display should be interpreted.
Lower‑Timeframe (LTF) Data
The script requests Up Volume, Down Volume, and Volume Delta from a lower timeframe to expose intrabar order‑flow structure that the chart’s native timeframe cannot show. In practical terms, this lets you see where buyers or sellers briefly dominated inside the body of a higher‑timeframe bar.
bool use_custom_tf_input = input.bool(true, title="Use custom lower timeframe", tooltip="Override the automatically chosen lower timeframe for volume calculations.", group=grpVolume)
string custom_tf_input = input. Timeframe("1", title="Lower timeframe", tooltip="Lower timeframe used for up/down volume calculations (default 5 seconds).", group=grpVolume)
import TradingView/ta/10 as tvta
resolve_lower_tf(useCustom, customTF) =>
useCustom ? customTF :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
get_up_down_volume(lowerTf) =>
= tvta.requestUpAndDownVolume(lowerTf)
var float upVolume = na
var float downVolume = na
var float deltaVolume = na
string lower_tf = resolve_lower_tf(use_custom_tf_input, custom_tf_input)
= get_up_down_volume(lower_tf)
upVolume := u_tmp
downVolume := d_tmp
deltaVolume := dl_tmp
• Data source: TradingView’s ta.requestUpAndDownVolume(lowerTf) via the official TA library.
• Plan capabilities: higher‑tier subscriptions unlock seconds‑based charts and allow more historical bars per chart. This expands both the temporal depth of LTF data and the precision of short‑horizon analysis, while base tiers provide minute‑level data suitable for day/short‑swing studies.
• Coverage clarity: a small on‑chart Coverage Panel reports the active lower timeframe, the number of bars covered, and the latest computed support/resistance ranges so you always know the bounds of valid LTF input.
Core Method
1) Data acquisition (LTF)
The script retrieves three series from the chosen lower timeframe:
– Up Volume (buyers)
– Down Volume (sellers)
– Delta (Up – Down)
2) Rolling window & extrema
Over a user‑defined lookback (Global Volume Period), the algorithm builds rolling arrays of completed bars and scans for extrema:
– Buyers_max / Buyers_min from Up Volume
– Sellers_max / Sellers_min from Down Volume
Only completed bars are considered; the current bar is excluded for stability.
3) Price mapping
The extrema are mapped back to their source candles to obtain price bounds:
– For “maximum” roles the algorithm uses the relevant candle highs.
– For “minimum” roles it uses the relevant candle lows.
These pairs define candidate resistance (max‑based) and support (min‑based) zones or vice versa.
4) Zone construction & minimum width
To ensure practicality on all symbols, zones enforce a minimum vertical thickness of two ticks. This prevents visually invisible or overly thin ranges on instruments with tight ticks.
5) Vertical role resolution
When both max‑ and min‑based zones exist, the script compares their midpoints. If, due to local price structure, the min‑based zone sits above the max‑based zone, display roles are swapped so the higher zone is labeled Resistance and the lower zone Support. Colors/widths are updated accordingly to keep the visual legend consistent.
6) Rendering & panel
Two horizontal lines and a filled box represent each active zone. The Coverage Panel (bottom‑right by default) prints:
– Lower‑timeframe in use
– Number of bars covered by LTF data
– Current Support and Resistance ranges
If the two zones overlap, an additional “Range Market” note is shown.
Key Inputs
• Global Volume Period: shared lookback window for the extrema search.
• Lower timeframe: user‑selectable override of the automatically resolved lower timeframe.
• Visualization toggles: independent show/hide controls and colors for maximum (resistance) and minimum (support) zones.
• Coverage Panel: enable/disable the single‑cell table and its readout.
Operational Notes
• The algorithm aligns all lookups to completed bars (no peeking). Price references are shifted appropriately to avoid using the still‑forming bar in calculations.
• Second‑based lower timeframes improve granularity for scalping and very short‑term entries. Minute‑based lower timeframes provide broader coverage for intraday and short‑swing contexts.
• Use the Coverage Panel to confirm the true extent of available LTF history on your symbol/plan before drawing conclusions from very deep lookbacks.
Visual Walkthrough
A step‑by‑step image sequence accompanies this description. Each figure demonstrates how the indicator reads LTF volume, locates extrema, builds price‑mapped zones, and updates labels/colors when vertical order requires it.
Chart Interpretation
This chart illustrates two distinct perspectives of the Smart Money Support/Resistance — Lite indicator, each derived from different lookback horizons and lower-timeframe (LTF) resolutions.
1- Short-term view (43 bars, 10-second LTF)
Using the most recent 43 completed bars with 10-second intrabar data, the algorithm detects that both maximum and minimum volume extrema fall within a narrow range. The result is a clearly identified range market: resistance between 178.15–184.55 and support between 175.02–179.38.
The Coverage Panel (bottom-right) confirms the scope of valid input: the lower timeframe used, number of bars covered, and the resulting zones. This short-term scan highlights how the indicator adapts to limited data depth, flagging sideways structure where neither side dominates.
2 - Long-term view (120 bars, 30-second LTF)
Over a wider 120-bar lookback with higher-granularity 30-second data, broader supply and demand zones emerge.
– The long-term resistance zone captures the concentration of buyers and sellers at the upper boundary of recent price history.
– The long-term support zone anchors to the opposite side of the distribution, derived from maxima and minima of both buying and selling pressure.
These zones reflect deeper structural levels where market participants previously committed significant volume.
Combined Perspective
By aligning the short-term and long-term outputs, the chart shows how the indicator distinguishes immediate consolidation (range market) from more durable support and resistance levels derived from extended history. This dual resolution approach makes clear that support and resistance are not static lines but dynamic zones, dependent on both timeframe depth and the resolution of intrabar volume data.
Hazel nut BB Strategy, volume base- lite versionHazel nut BB Strategy, volume base — lite version
Having knowledge and information in financial markets is only useful when a trader operates with a well-defined trading strategy. Trading strategies assist in capital management, profit-taking, and reducing potential losses.
This strategy is built upon the core principle of supply and demand dynamics. Alongside this foundation, one of the widely used technical tools — the Bollinger Bands — is employed to structure a framework for profit management and risk control.
In this strategy, the interaction of these tools is explained in detail. A key point to note is that for calculating buy and sell volumes, a lower timeframe function is used. When applied with a tick-level resolution, this provides the most precise measurement of buyer/seller flows. However, this comes with a limitation of reduced historical depth. Users should be aware of this trade-off: if precise tick-level data is required, shorter timeframes should be considered to extend historical coverage .
The strategy offers multiple configuration options. Nevertheless, it should be treated strictly as a supportive tool rather than a standalone trading system. Decisions must integrate personal analysis and other instruments. For example, in highly volatile assets with narrow ranges, it is recommended to adjust profit-taking and stop-loss percentages to smaller values.
◉ Volume Settings
• Buyer and seller volume (up/down volume) are requested from a lower timeframe, with an option to override the automatic resolution.
• A global lookback period is applied to calculate moving averages and cumulative sums of buy/sell/delta volumes.
• Ratios of buyers/sellers to total volume are derived both on the current bar and across the lookback window.
◉ Bollinger Band
• Bands are computed using configurable moving averages (SMA, EMA, RMA, WMA, VWMA).
• Inputs allow control of length, standard deviation multiplier, and offset.
• The basis, upper, and lower bands are plotted, with a shaded background between them.
◉ Progress & Proximity
• Relative position of the price to the Bollinger basis is expressed as percentages (qPlus/qMinus).
• “Near band” conditions are triggered when price progress toward the upper or lower band exceeds a user-defined threshold (%).
• A signed score (sScore) represents how far the close has moved above or below the basis relative to band width.
◉ Info Table
• Optional compact table summarizing:
• - Upper/lower band margins
• - Buyer/seller volumes with moving averages
• - Delta and cumulative delta
• - Buyer/seller ratios per bar and across the window
• - Money flow values (buy/sell/delta × price) for bar-level and summed periods
• The table is neutral-colored and resizable for different chart layouts.
◉ Zone Event Gate
• Tracks entry into and exit from “near band” zones.
• Arming logic: a side is armed when price enters a band proximity zone.
• Trigger logic: on exit, a trade event is generated if cumulative buyer or seller volume dominates over a configurable window.
◉ Trading Logic
• Orders are placed only on zone-exit events, conditional on volume dominance.
• Position sizing is defined as a fixed percentage of strategy equity.
• Long entries occur when leaving the lower zone with buyer dominance; short entries occur when leaving the upper zone with seller dominance.
◉ Exit Rules
• Open positions are managed by a strict priority sequence:
• 1. Stop-loss (% of entry price)
• 2. Take-profit (% of entry price)
• 3. Opposite-side event (zone exit with dominance in the other direction)
• Stop-loss and take-profit levels are configurable
◉ Notes
• This lite version is intended to demonstrate the interaction of Bollinger Bands and volume-based dominance logic.
• It provides a framework to observe how price reacts at band boundaries under varying buy/sell pressure, and how zone exits can be systematically converted into entry/exit signals.
When configuring this strategy, it is essential to carefully review the settings within the Strategy Tester. Ensure that the chosen parameters and historical data options are correctly aligned with the intended use. Accurate back testing depends on applying proper configurations for historical reference. The figure below illustrates sample result and configuration type.
