Indicator
Delta Ladder Order Flow [UAlgo]Delta Ladder Order Flow is an overlay order flow visualizer that builds a per bar delta ladder using lower timeframe candles as an intrabar proxy. For each recent bar, the script pulls the underlying lower timeframe open, high, low, close, and volume arrays, then distributes volume into discrete price buckets. Each bucket accumulates estimated buy volume and sell volume, producing a ladder that resembles a footprint style view.
The display focuses on three core outputs:
A delta heatmap ladder where each price level is colored by net delta dominance
A Point of Control highlight that marks the highest total volume level inside the bar
A stacked imbalance detector that scans diagonally across levels to identify aggressive one sided participation and optionally projects that stack forward
The system is designed with stability controls for real world chart conditions. It includes dynamic scaling to prevent excessive level counts on high range bars, object budgeting through bars to draw limits, and text filtering to reduce clutter.
🔹 Features
1) Intrabar Resolution via Lower Timeframe Data
The ladder is constructed using request.security_lower_tf. You select an Intrabar Resolution timeframe that must be lower than the chart timeframe. The script then receives arrays of LTF candles for each chart bar and uses them as a proxy for footprint style aggregation.
This approach provides a practical order flow approximation on PulseWire charts without requiring native tick level data.
2) Ladder Aggregation with Tick Size Multiplier
Price levels are aggregated using the symbol mintick multiplied by a user multiplier. Increasing the multiplier produces thicker ladder steps and fewer levels. Decreasing it produces finer granularity but increases the number of boxes drawn.
This control is critical for balancing detail versus performance across different symbols and volatility regimes.
3) Dynamic Scaling to Prevent High Range Bar Overload
A single volatile bar can contain too many price steps if the granularity is too fine. To prevent crashes, the script estimates how many steps would be required for the bar and increases the effective step size when the raw step count exceeds Max Levels per Bar.
This keeps rendering stable even during high volatility events while still maintaining a consistent ladder representation.
4) Buy, Sell, and Neutral Volume Attribution
Each LTF candle’s direction is inferred from its open and close:
Close above open is treated as buy side volume
Close below open is treated as sell side volume
Close equal open is treated as neutral and split evenly between buy and sell
Volume is then distributed across the price buckets covered by the LTF candle range so that wide candles spread their influence across multiple levels.
5) Delta Heatmap Ladder with Intensity Scaling
Each price bucket computes delta as buy volume minus sell volume and total volume as the sum of both. Ladder cells are colored positive or negative based on delta sign, and transparency is scaled by how dominant the delta is relative to the maximum total volume level inside that bar. This yields a compact heatmap where strong imbalances visually stand out.
A square root curve is applied to intensity to improve mid tone visibility without making everything fully opaque.
6) Point of Control Highlight
The ladder tracks the price level with the highest total volume and marks it as the Point of Control. When enabled, the POC row uses a dedicated border color and a stronger border width so the acceptance anchor is immediately visible.
7) Stacked Imbalance Detection and Projection
The script can detect stacked diagonal imbalances. It compares volume across adjacent price levels using a diagonal logic similar to footprint tools:
Bullish diagonal checks buy volume at a level versus sell volume at the level below
Bearish diagonal checks sell volume at a level versus buy volume at the level above
An imbalance requires the winning side to exceed the losing side by the configured Imbalance Ratio and also exceed a minimum volume threshold to filter low volume noise. When consecutive imbalanced levels reach the Stacked Levels count, the stack is marked and optionally extended forward as a zone.
Stack members also override normal heatmap coloring and are rendered more solid for emphasis.
8) Clean Visual Controls
Several options support readability:
Bars to Draw limits workload and object count
Show Delta Values can be toggled on or off
Min Delta to Show Text filters small prints
Ladder Width percent controls how wide the ladder is relative to the bar space
Text size can be adjusted for different chart zoom levels
Box outline can be hidden by default for a cleaner footprint aesthetic
🔹 Calculations
1) Intrabar data acquisition (lower timeframe arrays)
The script requests arrays of LTF OHLCV values for each chart bar using request.security_lower_tf.
ltf_open = request.security_lower_tf(syminfo.tickerid, tf_input, open)
ltf_close = request.security_lower_tf(syminfo.tickerid, tf_input, close)
ltf_high = request.security_lower_tf(syminfo.tickerid, tf_input, high)
ltf_low = request.security_lower_tf(syminfo.tickerid, tf_input, low)
ltf_vol = request.security_lower_tf(syminfo.tickerid, tf_input, volume)
These arrays contain the lower timeframe candles that make up each chart bar. Each chart bar index has its own embedded array.
2) Base tick step (bucket size control)
Bucket size starts from mintick multiplied by Tick Size Multiplier.
var float base_tick_step = syminfo.mintick * tick_size_mult
This is the baseline price increment used to build the ladder levels.
3) Last bar execution model (performance design)
The script only builds and draws ladders when barstate.islast is true. It then reconstructs the last N bars using an index offset.
if barstate.islast
int start_idx = math.max(0, bar_index - bars_to_draw + 1)
for i = start_idx to bar_index
int offset = bar_index - i
float arr_o = ltf_open
float arr_c = ltf_close
float arr_h = ltf_high
float arr_l = ltf_low
float arr_v = ltf_vol
This design dramatically reduces CPU and memory load compared to updating every bar.
4) Dynamic scaling per bar (anti crash protection)
For each bar, the script estimates how many price steps would be needed using the current bucket size. If that count exceeds Max Levels per Bar, it increases the step size only for that bar.
float bar_h = high
float bar_l = low
float bar_range = bar_h - bar_l
float raw_steps = bar_range / base_tick_step
int scaler = 1
if raw_steps > max_levels_per_bar
scaler := int(math.ceil(raw_steps / max_levels_per_bar))
float current_tick_step = base_tick_step * scaler
Result:
Calm bars use fine granularity
High range bars are automatically compressed into fewer buckets
5) LTF candle direction classification (buy, sell, neutral)
Each LTF candle is classified using its open and close. Neutral candles split volume evenly.
bool is_buy = c > o
bool is_sell = c < o
bool is_neutral = c == o
This is a heuristic proxy for aggressor side. It is not true bid ask data.
6) Align LTF candle range to bucket grid
The candle low and high are rounded to the current tick step so bucket prices align cleanly.
float low_aligned = math.round(l / current_tick_step) * current_tick_step
float high_aligned = math.round(h / current_tick_step) * current_tick_step
7) Step counting and volume per step
The script computes how many bucket levels the candle touches and divides volume equally across them.
int steps = int(math.round((high_aligned - low_aligned) / current_tick_step)) + 1
if steps > 500
steps := 500
float vol_per_step = v / steps
This means wide candles distribute volume across more ladder cells, while tight candles concentrate volume into fewer cells.
8) Writing volume into the ladder map (PriceLevel storage)
Each chart bar owns a DeltaLadder with a map of price to PriceLevel. Each PriceLevel stores buy and sell volume. Volume is added step by step.
type PriceLevel
float price
float buy_vol = 0.0
float sell_vol = 0.0
type DeltaLadder
int bar_idx
map levels
float min_price = 10000000.0
float max_price = 0.0
float max_vol_level = 0.0
float poc_price = na
float poc_vol = 0.0
The add method updates volumes and also tracks max volume and POC:
method add_volume(DeltaLadder this, float price, float vol, bool is_buy, bool is_neutral) =>
if not this.levels.contains(price)
this.levels.put(price, PriceLevel.new(price))
PriceLevel lvl = this.levels.get(price)
if is_neutral
lvl.buy_vol += vol * 0.5
lvl.sell_vol += vol * 0.5
else if is_buy
lvl.buy_vol += vol
else
lvl.sell_vol += vol
float t = lvl.total()
if t > this.max_vol_level
this.max_vol_level := t
if t > this.poc_vol
this.poc_vol := t
this.poc_price := price
The main loop calls this method for each bucket level touched by each LTF candle:
for p = 0 to steps - 1
float level_price = low_aligned + (p * current_tick_step)
ladder.add_volume(level_price, vol_per_step, is_buy, is_neutral)
9) Delta and total volume formulas
Delta and total are defined as methods on PriceLevel.
method delta(PriceLevel this) =>
this.buy_vol - this.sell_vol
method total(PriceLevel this) =>
this.buy_vol + this.sell_vol
These values drive both coloring and POC selection.
10) Stacked imbalance detection (diagonal footprint logic)
Prices are sorted so neighbor comparisons are correct. A stack_map stores whether each price belongs to a bullish or bearish stacked run.
float prices = ladder.levels.keys()
array.sort(prices)
map stack_map = map.new()
Diagonal comparisons:
Bullish diagonal compares BuyVol at level i with SellVol at level below i minus 1
Bearish diagonal compares SellVol at level i with BuyVol at level above i plus 1
Bullish check includes a zero handling rule:
if i > 0
float p_below = array.get(prices, i-1)
PriceLevel lvl_below = ladder.levels.get(p_below)
if lvl_below.sell_vol == 0
if lvl.buy_vol > imb_min_vol
direction := 1
else
if lvl.buy_vol > lvl_below.sell_vol * imb_ratio and lvl.buy_vol > imb_min_vol
direction := 1
Bearish check includes symmetric logic:
if i < array.size(prices) - 1
float p_above = array.get(prices, i+1)
PriceLevel lvl_above = ladder.levels.get(p_above)
if lvl_above.buy_vol == 0
if lvl.sell_vol > imb_min_vol
direction := -1
else
if lvl.sell_vol > lvl_above.buy_vol * imb_ratio and lvl.sell_vol > imb_min_vol
direction := -1
Runs are tracked and only accepted if the number of consecutive levels meets the stacked requirement:
if math.abs(i - run_start_idx) >= stack_count
for k = run_start_idx to i - 1
stack_map.put(array.get(prices, k), run_dir)
The script also draws a projected zone for the detected stack band:
box.new(right_time, p_top + current_tick_step/2, right_time + 1000 * 60 * 60 * 24, p_bot - current_tick_step/2,
xloc=xloc.bar_time, border_width=0, bgcolor=color.new(c_stack, 85), extend=extend.right)
11) Heatmap intensity and transparency mapping
For each price level, intensity is computed as abs(delta) relative to the maximum total volume level in the bar, then curved and mapped into transparency.
float intensity = ladder.max_vol_level > 0 ? math.abs(delta) / ladder.max_vol_level : 0
intensity := math.min(intensity, 1.0)
float curved_intensity = math.sqrt(intensity)
float transp = 97 - (curved_intensity * 57)
Stacked members force stronger visibility:
if stack_map.contains(p)
intensity := 1.0
transp := 30
12) POC marking in the drawing pass
POC is detected during volume accumulation, then used in rendering to upgrade the border style for that cell.
bool is_poc = show_poc and (p == ladder.poc_price)
color border_c = is_poc ? col_poc : col_outline
int border_w = is_poc ? 2 : 1
13) Delta text rendering filter
Text labels are optional and can be filtered by a minimum absolute delta threshold.
if show_text and math.abs(delta) >= text_threshold
string txt = str.tostring(delta, format.volume)
label.new(int((left_time + right_time)/2), p, txt,
xloc=xloc.bar_time, style=label.style_none,
textcolor=txt_col, size=text_size)
Indicator
Key Price Levels Daily Ver [structJCWL]As an independent developer and active trader, I built this tool to address a personal frustration: the lack of precision in standard session-level indicators. For those who trade based on market micro-structure, a level that is "approximately" correct is a logic error.
Key Price Levels Daily Ver is an engineering implementation focused on reconstructing session data with surgical accuracy. It is designed for traders who require reliable, noise-filtered benchmarks to anchor their daily execution.
THE ENGINEERING LOGIC:
1-Second (1S) Intrabar Reconstruction : Standard scripts often rely on daily-bar data, which can be imprecise. This tool re-aggregates the session using 1-Second (1S) granularity . By processing every sub-candle, it ensures that POC, Value Area, and Extremes are anchored to the true weight of capital commitment.
The 15-Minute Threshold (Technical Rationale) : To maintain the high fidelity of 1S data aggregation, this indicator is optimized for timeframes ≤ 15 minutes . Calculating micro-structure on higher timeframes leads to data thinning and reduced precision—limitations I refuse to accept in my personal trading setup.
Adaptive Visual Hierarchy (Fade & Limits) : To prevent visual clutter, I’ve integrated Fade Strength and Timeframe Limits . Lines automatically adjust their transparency or visibility based on your current timeframe, ensuring that the most relevant levels remain clear while secondary noise recedes.
Reliability by Design : In 24/7 markets, script stability is paramount. I have implemented defensive programming (including a 98,000-unit memory circuit breaker ) to prevent overflows during extreme volatility. I strive for absolute dependability; if you encounter any issues, your feedback is highly welcome as we refine and improve this tool together.
作为一名独立开发者与实战交易者，我构建此工具是为了解决一个长期的困扰：标准时段指标精度的缺失。对于基于市场微观结构进行交易的人来说，“大约准确”的水位本身就是一种逻辑错误。
Key Price Levels Daily Ver 是我对日内关键水位线的个人工程化实现，专注于以“外科手术式”的精度重构时段数据。它专为那些需要可靠、过滤噪音的基准位来锚定日内执行的交易者而设计。
核心设计逻辑：
1秒级微观重构 (1S Precision) ：我不满足于直接调用现成的日线数据。脚本通过扫描 1秒 (1S) 微观颗粒度数据 来重构整个交易时段，确保 POC 和价值区的计算基准来自于最真实的成交细节。
15分钟周期硬限制 ：为了保证 1S 数据聚合的极致精度，本脚本仅限在 15分钟及以下周期 运行。在更长周期调用微观数据会导致精度大幅下降。作为开发者，我不允许“大约准确”的逻辑存在于我的系统里。
自适应视觉层级 (Fade & Limits) ：通过内置的 淡化强度 (Fade) 与 周期限制 (Limits) ，水位线会根据你当前的图表周期自动调节透明度或可见性。
可靠性设计 ：在 24/7 不间断的交易中，脚本的稳定性至关重要。我在代码底层加入了防御性设计（包括 98,000 数组容量熔断机制 ），旨在防止极端行情下的计算溢出或图表崩溃。我追求的是一个能让人放心的工具，若你在使用中发现任何问题，欢迎随时反馈，我们共同完善。
Feedback & Interaction:
As a personal project, this script is continuously refined. I welcome any bug reports or suggestions for improvement to make this tool even more robust for the community.
Compliance & Credits:
Author: structJCWL (Independent Developer & Trader)
License: Mozilla Public License 2.0 (MPL 2.0)
Attribution: Core data aggregation and state-machine logic are 100% original implementations Indicator
Institutional Alpha Vector | D_QUANT Institutional Alpha Vector | D_QUANT
Overview
The Institutional Alpha Vector (IAV) is an original trend-following framework that replaces single-indicator bias with a Weighted Composite Score . Instead of relying on a simple moving average, this script aggregates four distinct quantitative dimensions—Price, Momentum, Volatility, and Volume—into a normalized value called the "Alpha Vector."
The goal of this tool is to identify "Institutional Consensus"—periods where multiple mathematical models align in the same direction, reducing the likelihood of false breakouts in choppy markets.
How It Works: The Quantitative Engines
The script calculates four independent signals. For each module, a state is stored (1 for Bullish, -1 for Bearish, 0 for Neutral).
1. Price Filter (Hull Moving Average):
The script uses an HMA (a weighted moving average that reduces lag by using the square root of the period). A signal is triggered when the price crosses over/under this "Spine."
2. Volatility Regime (RMA + ATR):
This module uses a Moving Average (RMA) combined with an Average True Range (ATR) offset. It acts as a volatility filter that price must move beyond 1 ATR from the mean to register a trend, ensuring the market isn't just "drifting."
3. Momentum Physics (ADX/DMI):
Based on J. Welles Wilder’s Directional Movement Index. It checks if the is above (or vice versa) but only if the ADX (Average Directional Index) is above a user-defined threshold (default: 10), confirming the presence of a strong trend.
4. Institutional Flow (Chaikin Money Flow):
This confirms price action with volume. It calculates the accumulation/distribution of money flow over a specific period. A signal is only valid if the CMF is positive (Bullish) or negative (Bearish).
The Alpha Vector Calculation
This is the core "originality" of the script. The indicator takes the active modules and calculates a Composite Score :
This results in a value between -1.0 and +1.0 .
* High Confidence Long: When the score exceeds +0.1 (adjustable).
* High Confidence Short: When the score drops below -0.1 (adjustable).
* Neutral Zone: When the score is near 0, the script colors the bars grey, signaling a lack of institutional consensus.
Visual Intelligence: The "Electric Conduit"
The script visualizes market energy through a custom rendering engine:
* The Spine: A central line representing the HMA trend.
* The Conduit (Fill): A dynamic gradient that expands or contracts based on the ATR (Average True Range) . This allows traders to see "volatility expansion" (wide ribbon) vs "compression" (tight ribbon) at a glance.
* Bar Coloring : Automatically aligns the chart candles with the Alpha Vector state to remove cognitive load.
How to Use
1. Define your Strategy: In the settings, you can toggle specific modules. If you are trading a low-volume asset, you might disable the **CMF** module.
2. Identify the Consensus: Look for the ribbon to change from Grey (Neutral) to Cyan/Gold.
3. Monitor the HUD: A small dashboard in the bottom right displays the live Alpha Vector score. A score of 1.0 means all four engines are in 100% bullish agreement.
Disclaimer: Trading involves significant risk. This tool is for educational and analytical purposes and does not constitute financial advice. Indicator
StO Price Action - Level ReactionShort-Summary
- Multi-timeframe reaction indicator for M5, M15, M30, H1, H4
- Monitors price interaction with higher timeframe levels (Daily, Weekly, H4)
- Detects whether price touches or breaks choosen levels
- Fully configurable colors, visibility and alerts per timeframe and level type
Full Description
Overview
- Tracks market reaction on significant levels across multiple timeframes
- Designed to identify intraday reactions to higher timeframe structure
- Supports both bullish and bearish reactions, with separate visual cues
- Alerts can be enabled to notify traders of touches or breaks
Core Logic
- Choice between detecting a touch or a break of the level
- Configurable reference level: Open, High or Low
- Lookback period can be set to target specific levels from previous candles
Timeframe Reactions
- Supported intraday reaction timeframes: M5, M15, M30, H1, H4, Daily, Weekly
- Each reaction type can be individually toggled for display
- Bullish and bearish reactions have separate color settings
- Alerts configurable per timeframe and reaction type
Alerting
- Alerts can be triggered for touches or breaks
- Supports separate alerts for each timeframe and each direction (bull/bear)
- Useful for real-time monitoring of key level interactions
Notes
- Intended as a market reaction tool not a standalone entry signal
- Helps traders confirm if price respects or violates higher timeframe levels Indicator
[HFT] Leaky Bucket: FPGA-Based Order Flow SimulationDescription:
This indicator is a functional simulation of a hardware-based "Leaky Bucket" algorithm, typically used in FPGA (Field-Programmable Gate Array) chips for High-Frequency Trading (HFT) and network traffic shaping.
Unlike standard volume indicators (like OBV or CMF) that rely on floating-point Moving Averages (EMA/SMA), this script uses Bitwise Integer Math to simulate hardware registers. This approach removes the lag associated with smoothing and provides a raw, "tick-by-tick" representation of Order Flow exhaustion.
█ Underlying Concepts (How it works)
Integer Math & Bitwise Logic: The script eschews standard float calculations for int registers. Instead of division, it uses Bitwise Right Shift (>>) to simulate the "leak" rate. This mimics how hardware processes data streams with near-zero latency.
The Leaky Bucket Model:
Flow (Input): Volume * Price Delta flows into a "Bucket" (Accumulator Register).
Leak (Output): The bucket leaks at a constant rate determined by the Decay Shift.
Saturation: If the Flow > Leak, the bucket fills. We simulate a 32-bit integer saturation limit (sat_limit). When the bucket hits this limit, it represents "Panic Buying/Selling" — the market capability to absorb orders is saturated.
█ Uniqueness & Originality This is custom-built code, not a mashup of existing indicators. It translates hardware logic (Verilog/VHDL concepts) into Pine Script:
It introduces a "Saturation Warning" mechanism that detects when volume pressure exceeds mathematical limits.
It implements a "Gray Line" Strategy, focusing on volatility decay rather than momentum initiation.
█ How to Use: The "Gray Line" Strategy
This tool is designed for Mean Reversion and Exhaustion Trading, specifically on M1 to M5 timeframes.
Do NOT trade the breakout: When you see massive Green (Long) or Purple (Short) bars, this indicates "Extreme Momentum". Do not enter yet. Wait.
Wait for the "Gray Line": The signal is generated when the Extreme Momentum stops and the bar turns Gray (Neutral).
Signal L (Long): Generated when a sequence of Extreme Short bars (Purple) ends, and the histogram returns to Gray/Maroon. This confirms sellers are exhausted.
Signal S (Short): Generated when a sequence of Extreme Long bars (Green) ends, and the histogram returns to Gray/Teal. This confirms buyers are exhausted.
█ Disclaimer This script is intended for educational purposes regarding HFT algorithms and Order Flow analysis. It does not provide financial advice. Indicator
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POC Migration Velocity (POC-MV) [PhenLabs]📊POC Migration Velocity (POC-MV)
Version: PineScript™v6
📌Description
The POC Migration Velocity indicator revolutionizes market structure analysis by tracking the movement, speed, and acceleration of Point of Control (POC) levels in real-time. This tool combines sophisticated volume distribution estimation with velocity calculations to reveal hidden market dynamics that conventional indicators miss.
POC-MV provides traders with unprecedented insight into volume-based price movement patterns, enabling the early identification of continuation and exhaustion signals before they become apparent to the broader market. By measuring how quickly and consistently the POC migrates across price levels, traders gain early warning signals for significant market shifts and can position themselves advantageously.
The indicator employs advanced algorithms to estimate intra-bar volume distribution without requiring lower timeframe data, making it accessible across all chart timeframes while maintaining sophisticated analytical capabilities.
🚀Points of Innovation
Micro-POC calculation using advanced OHLC-based volume distribution estimation
Real-time velocity and acceleration tracking normalized by ATR for cross-market consistency
Persistence scoring system that quantifies directional consistency over multiple periods
Multi-signal detection combining continuation patterns, exhaustion signals, and gap alerts
Dynamic color-coded visualization system with intensity-based feedback
Comprehensive customization options for resolution, periods, and thresholds
🔧Core Components
POC Calculation Engine: Estimates volume distribution within each bar using configurable price bands and sophisticated weighting algorithms
Velocity Measurement System: Tracks the rate of POC movement over customizable lookback periods with ATR normalization
Acceleration Calculator: Measures the rate of change of velocity to identify momentum shifts in POC migration
Persistence Analyzer: Quantifies how consistently POC moves in the same direction using exponential weighting
Signal Detection Framework: Combines trend analysis, velocity thresholds, and persistence requirements for signal generation
Visual Rendering System: Provides dynamic color-coded lines and heat ribbons based on velocity and price-POC relationships
🔥Key Features
Real-time POC calculation with 10-100 configurable price bands for optimal precision
Velocity tracking with customizable lookback periods from 5 to 50 bars
Acceleration measurement for detecting momentum changes in POC movement
Persistence scoring to validate signal strength and filter false signals
Dynamic visual feedback with blue/orange color scheme indicating bullish/bearish conditions
Comprehensive alert system for continuation patterns, exhaustion signals, and POC gaps
Adjustable information table displaying real-time metrics and current signals
Heat ribbon visualization showing price-POC relationship intensity
Multiple threshold settings for customizing signal sensitivity
Export capability for use with separate panel indicators
🎨Visualization
POC Connecting Lines: Color-coded lines showing POC levels with intensity based on velocity magnitude
Heat Ribbon: Dynamic colored ribbon around price showing POC-price basis intensity
Signal Markers: Clear exhaustion top/bottom signals with labeled shapes
Information Table: Real-time display of POC value, velocity, acceleration, basis, persistence, and current signal status
Color Gradients: Blue gradients for bullish conditions, orange gradients for bearish conditions
📖Usage Guidelines
POC Calculation Settings
POC Resolution (Price Bands): Default 20, Range 10-100. Controls the number of price bands used to estimate volume distribution within each bar
Volume Weight Factor: Default 0.7, Range 0.1-1.0. Adjusts the influence of volume in POC calculation
POC Smoothing: Default 3, Range 1-10. EMA smoothing period applied to the calculated POC to reduce noise
Velocity Settings
Velocity Lookback Period: Default 14, Range 5-50. Number of bars used to calculate POC velocity
Acceleration Period: Default 7, Range 3-20. Period for calculating POC acceleration
Velocity Significance Threshold: Default 0.5, Range 0.1-2.0. Minimum normalized velocity for continuation signals
Persistence Settings
Persistence Lookback: Default 5, Range 3-20. Number of bars examined for persistence score calculation
Persistence Threshold: Default 0.7, Range 0.5-1.0. Minimum persistence score required for continuation signals
Visual Settings
Show POC Connecting Lines: Toggle display of colored lines connecting POC levels
Show Heat Ribbon: Toggle display of colored ribbon showing POC-price relationship
Ribbon Transparency: Default 70, Range 0-100. Controls transparency level of heat ribbon
Alert Settings
Enable Continuation Alerts: Toggle alerts for continuation pattern detection
Enable Exhaustion Alerts: Toggle alerts for exhaustion pattern detection
Enable POC Gap Alerts: Toggle alerts for significant POC gaps
Gap Threshold: Default 2.0 ATR, Range 0.5-5.0. Minimum gap size to trigger alerts
✅Best Use Cases
Identifying trend continuation opportunities when POC velocity aligns with price direction
Spotting potential reversal points through exhaustion pattern detection
Confirming breakout validity by monitoring POC gap behavior
Adding volume-based context to traditional technical analysis
Managing position sizing based on POC-price basis strength
⚠️Limitations
POC calculations are estimations based on OHLC data, not true tick-by-tick volume distribution
Effectiveness may vary in low-volume or highly volatile market conditions
Requires complementary analysis tools for complete trading decisions
Signal frequency may be lower in ranging markets compared to trending conditions
Performance optimization needed for very short timeframes below 1-minute
💡What Makes This Unique
Advanced Estimation Algorithm: Sophisticated method for calculating POC without requiring lower timeframe data
Velocity-Based Analysis: Focus on POC movement dynamics rather than static levels
Comprehensive Signal Framework: Integration of continuation, exhaustion, and gap detection in one indicator
Dynamic Visual Feedback: Intensity-based color coding that adapts to market conditions
Persistence Validation: Unique scoring system to filter signals based on directional consistency
🔬How It Works
Volume Distribution Estimation:
Divides each bar into configurable price bands for volume analysis
Applies sophisticated weighting based on OHLC relationships and proximity to close
Identifies the price level with maximum estimated volume as the POC
Velocity and Acceleration Calculation:
Measures POC rate of change over specified lookback periods
Normalizes values using ATR for consistent cross-market performance
Calculates acceleration as the rate of change of velocity
Signal Generation Process:
Combines trend direction analysis using EMA crossovers
Applies velocity and persistence thresholds to filter signals
Generates continuation, exhaustion, and gap alerts based on specific criteria
💡Note:
This indicator provides estimated POC calculations based on available OHLC data and should be used in conjunction with other analysis methods. The velocity-based approach offers unique insights into market structure dynamics but requires proper risk management and complementary analysis for optimal trading decisions. Indicator
Volume-Weighted Money Flow [sgbpulse]Overview
The VWMF indicator is an advanced technical analysis tool that combines and summarizes five leading momentum and volume indicators (OBV, PVT, A/D, CMF, MFI) into one clear oscillator. The indicator helps to provide a clear picture of market sentiment by measuring the pressure from buyers and sellers. Unlike single indicators, VWMF provides a comprehensive view of market money flow by weighting existing indicators and presenting them in a uniform and understandable format.
Indicator Components
VWMF combines the following indicators, each normalized to a range of 0 to 100 before being weighted:
On-Balance Volume (OBV): A cumulative indicator that measures positive and negative volume flow.
Price-Volume Trend (PVT): Similar to OBV, but incorporates relative price change for a more precise measure.
Accumulation/Distribution Line (A/D): Used to identify whether an asset is being bought (accumulated) or sold (distributed).
Chaikin Money Flow (CMF): Measures the money flow over a period based on the close price's position relative to the candle's range.
Money Flow Index (MFI): A momentum oscillator that combines price and volume to measure buying and selling pressure.
Understanding the Normalized Oscillators
The indicator combines the five different momentum indicators by normalizing each one to a uniform range of 0 to 100 .
Why is Normalization Important?
Indicators like OBV, PVT, and the A/D Line are cumulative indicators whose values can become very large. To assess their trend, we use a Moving Average as a dynamic reference line . The Moving Average allows us to understand whether the indicator is currently trending up or down relative to its average behavior over time.
How Does Normalization Work?
Our normalization fully preserves the original trend of each indicator.
For Cumulative Indicators (OBV, PVT, A/D): We calculate the difference between the current indicator value and its Moving Average. This difference is then passed to the normalization process.
- If the indicator is above its Moving Average, the difference will be positive, and the normalized value will be above 50.
- If the indicator is below its Moving Average, the difference will be negative, and the normalized value will be below 50.
Handling Extreme Values: To overcome the issue of extreme values in indicators like OBV, PVT, and the A/D Line , the function calculates the highest absolute value over the selected period. This value is used to prevent sharp spikes or drops in a single indicator from compromising the accuracy of the normalization over time. It's a sophisticated method that ensures the oscillators remain relevant and accurate.
For Bounded Indicators (CMF, MFI): These indicators already operate within a known range (for example, CMF is between -1 and 1, and MFI is between 0 and 100), so they are normalized directly without an additional reference line.
Reference Line Settings:
Moving Average Type: Allows the user to choose between a Simple Moving Average (SMA) and an Exponential Moving Average (EMA).
Volume Flow MA Length: Allows the user to set the lookback period for the Moving Average, which affects the indicator's sensitivity.
The 50 line serves as the new "center line." This ensures that, even after normalization, the determination of whether a specific indicator supports a bullish or bearish trend remains clear.
Settings and Visual Tools
The indicator offers several customization options to provide a rich analysis experience:
VWMF Oscillator (Blue Line): Represents the weighted average of all five indicators. Values above 50 indicate bullish momentum, and values below 50 indicate bearish momentum.
Strength Metrics (Bullish/Bearish Strength %): Two metrics that appear on the status line, showing the percentage of indicators supporting the current trend. They range from 0% to 100%, providing a quick view of the strength of the consensus.
Dynamic Background Colors: The background color of the chart automatically changes to bullish (a blue shade by default) or bearish (a default brown-gray shade) based on the trend. The transparency of the color shows the consensus strength—the more opaque the background, the more indicators support the trend.
Advanced Settings:
- Background Color Logic: Allows the user to choose the trigger for the background color: Weighted Value (based on the combined oscillator) or Strength (based on the majority of individual indicators).
- Weights: Provides full control over the weight of each of the five indicators in the final oscillator.
Using the Data Window
PulseWire provides a useful Data Window that allows you to see the exact numerical values of each normalized oscillator separately, in addition to the trend strength data.
You can use this window to:
Get more detailed information on each indicator: Viewing the precise numerical data of each of the five indicators can help in making trading decisions.
Calibrate weights: If you want to manually adjust the indicator weights (in the settings menu), you can do so while tracking the impact of each indicator on the weighted oscillator in the Data Window.
The indicator's default setting is an equal weight of 20% for each of the five indicators.
Alert Conditions
The indicator comes with a variety of built-in alerts that can be configured through the PulseWire alerts menu:
VWMF Cross Above 50: An alert when the VWMF oscillator crosses above the 50 line, indicating a potential bullish momentum shift.
VWMF Cross Below 50: An alert when the VWMF oscillator crosses below the 50 line, indicating a potential bearish momentum shift.
Bullish Strength: High But Not Absolute Consensus: An alert when the bullish trend strength reaches 60% or more but is less than 100%, indicating a high but not absolute consensus.
Bullish Strength at 100%: An alert when all five indicators (MFI, OBV, PVT, A/D, CMF) show bullish strength, indicating a full and absolute consensus.
Bearish Strength: High But Not Absolute Consensus: An alert when the bearish trend strength reaches 60% or more but is less than 100%, indicating a high but not absolute consensus.
Bearish Strength at 100%: An alert when all five indicators (MFI, OBV, PVT, A/D, CMF) show bearish strength, indicating a full and absolute consensus.
Summary
The VWMF indicator is a powerful, all-in-one tool for analyzing market momentum, money flow, and sentiment. By combining and normalizing five different indicators into a single oscillator, it offers a holistic and accurate view of the market's underlying trend. Its dynamic visual features and customizable settings, including the ability to adjust indicator weights, provide a flexible experience for both novice and experienced traders. The built-in alerts for momentum shifts and trend consensus make it an effective tool for spotting trading opportunities with confidence. In essence, VWMF distills complex market data into clear, actionable signals.
Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
Indicator
Indicator
Indicator
Library
Indicator
VWAP RangeThe VWAP Range indicator is a highly versatile and innovative tool designed with trading signals for trading the supply and demand within consolidation ranges.
What's a VWAP?
A VWAP (Volume Weighted Average Price) represents an equilibrium point in the market, balancing supply and demand over a specified period. Unlike simple moving averages, VWAP gives more weight to periods with higher volume. This is crucial because large volumes indicate significant trading activity, often by institutional traders, whose actions can reflect deeper market insights or create substantial market movements. The VWAP is also often used as a benchmark to evaluate the efficiency of executed trades. If a trader buys below the VWAP and sells above it, they are generally considered to have transacted favourably.
This is how it works:
Multiple VWAP Anchors:
This indicator uses multiple VWAPs anchored to different optional time periods, such as Daily, Weekly, Monthly, as well as to the highest high a lowest low within those periods. This multiplicity allows for a comprehensive view of the market’s average price based on volume and price, tailored to different trading styles and strategies.
Dynamic and Fixed Periods:
Traders can choose between using dynamic ranges, which reset at the start of each selected period, and specifying a date and time for a particular fixed range to trade. This flexibility is crucial for analyzing price movements within specific ranges or market phases.
Fixed ranges allow VWAPs to be calculated and anchored to a significant market event, the beginning of a consolidation phase or after a major news announcement.
Signal Generation:
The indicator generates buy and sell signals based on the relationship of the price to the VWAPs. It also allows for setting a maximum number of signals in one direction to avoid overtrading or pyramiding. Be sure to wait for the candle close before trading on the signals.
Average Buy/Sell Signal Lines:
Lines can be plotted to display the average buy and sell signal prices. The difference between the lines shows the average profit per trade when trading on the signals in that range. It's a good way to see how profitable a range is on average without backtesting the signals. The lines will also often turn into support and resistance areas, similar to value areas in a volume profile.
Customizable Settings:
Traders have control over various settings, such as the VWAP calculation method and bar color. There are also tooltips for every function.
Hidden Feature:
There's a subtle feature in this indicator: if you have 'Indicator values' turned on in PulseWire, you'll see a Sell/Buy Ratio displayed only in the status line. This ratio indicates whether there are more sell signals than buy signals in a range, regardless of the Max Signals setting. A red value above 1 suggests that the market is trending upward, indicating you might want to hold your long positions a bit longer. Conversely, a green value below 1 implies a downward trend.
Indicator
Indicator
Machine Learning: MFI Heat Map [YinYangAlgorithms]Overview:
MFI Heat Maps are a visually appealing way to display the values of 29 different MFIs at the same time while being able to make sense of it. Each plot within the Indicator represents a different MFI value. The higher you get up, the longer the length that was used for this MFI. This Indicator also features the use of Machine Learning to help balance the MFI levels. It doesn’t solely rely upon Machine Learning but instead incorporates a growing length MFI averaged with the Machine Learning MFI at any given index.
For instance, say we are calculating the 10th plot from the bottom, the MFI would be an average of:
MFI(source, 11)
Machine Learning MFI at Index of 10
We do it this way as they both help smooth each other out without relying solely on just one calculation method.
Due to plot limitations, you are capped at 28 Plot Amounts within this indicator, but that is still quite a bit of information you can glean from a Heat Map.
The Machine Learning used in this indicator is of the K-Nearest Neighbor (KNN). It uses a Fast and Slow MFI calculation then sorts through them over Machine Learning Length and calculates the differences between them. It then slices off KNN length to create our Max/Min Distances allotted. It adds the average between Fast and Slow MFIs to a Viable Distances array if their distances are within the KNN Min/Max distance. It then averages all distances in the Viable Distances array and returns the result.
The result of the KNN Function is saved to another ML Data array whose length is that of Plot Amount (Heat Map Size). This way each Index of the ML Data array can be indexed according to the Heat Map Size.
The Average of the ML Data array is the MFI line (white) that you’ll see plotted on the Indicator. There is also the SMA of the MFI Average (orange) which is likewise plotted. These plots allow you to visualize where the ML MFI is sitting and can potentially be useful for seeing when the MFI Average and SMA cross over and under each other.
We’ve heard many people talk highly of RSI, but sadly not too many even refer to MFI. MFI oftentimes may be overlooked, especially with new traders who may not even know what it is. Essentially MFI is an RSI but it also incorporates Volume into its calculations, which in our opinion leads to a more accurate reading; afterall, what is price movement without Volume.
Tutorial:
You may be thinking, this Indicator looks appealing to the eye, but how do I benefit from it trading wise?
Before we get into our visual examples, let's talk briefly about what makes Heat Maps in general a useful tool for trading. Heat Maps give us the ability to visualize and understand lots of data while removing the clutter. We can understand the data of 29 different MFIs without having to look at and decipher 29 different MFI plots. When you overlay too many MFI lines on top of each other, they can be very difficult to read and oftentimes end up actually hindering your Technical Analysis. For this reason, we have a simple solution to this problem; Heat Maps. This MFI Heat Map allows you to easily know (in a relative %) what the MFI level is for varying lengths. For Instance, the First (bottom) plot indexes an MFI of (K(0) (loop of Plot Amount) + Smoothing Length (default 1)) = 1. Since this is indexing (usually) a very low length, it will change much quicker. Whereas the Last (top) plot indexes an MFI of (K(27) (loop of Plot Amount) + Smoothing Length (default 1)) = 28. This is indexing a much higher length of MFI which results in the MFI the higher you go up in the Heat Map to move much slower.
Heat Maps give us the ability to see changes happening over multiple MFIs at the same time, which can be very useful for seeing shifts in MFI / Momentum. Remember, MFI incorporates Volume, so even if the price goes up a lot, if there was low volume, the MFI won’t move as much as an RSI would. However, likewise, if there is high volume but low price movement, the MFI will move slightly more than the RSI.
Heat Maps change color based on their MFI level. If the MFI is >= 90 it is HOT (red), if the MFI <= 9 it is COLD (teal, think of ICE). Green represents an MFI of 50-59 and Dark Blue represents an MFI of 40-49. Green and Dark blue are the most common colors as all the others are more ‘Extreme’ MFI levels.
Okay, time to get to the Examples :
Since there is so much going on in Heat Maps, we’ve decided to focus this tutorial to this specific area and talk about individual locations before talking about it as a whole.
If you refer to the example above where there are 2 white circles; these white circles are highlighting a key location you’ll be wanting to identify within your Heat Maps, many things are happening here:
The MFI crossed over the SMA (bullish).
The Heat Map started changing from mid/dark Blue (30-50 MFI) to Green (50-59 MFI) around the midline (the 50% dashed like).
The Lower levels of the Heat Map are turning Yellow/Orange/Red (60-100 MFI).
The Upper Levels of the Heat Map are still Light Blue - Green (10-50 MFI).
The 4 Key points above, all point towards potential Bullish Momentum changes. You’re likely wondering, but why? Let's discuss about each one in more specific detail:
1. The MFI crossed over the SMA (bullish): What this tells us is that the current MFI Average is now greater than its average over the last (default) 16 bars. This means there's been a large amount of Money Flow (Price and Volume) recently (subjectively based on the last (default) 16 average). This is one of the leading Bullish / Bearish signals you will see within this Indicator. You can enable Signals within the Settings and/or even add Alerts for when these crossings occur.
2. The Heat Map started changing from mid/dark Blue (30-50 MFI) to Green (50-59 MFI) around the midline (the 50% dashed like): This shows us that the index’s in the mid (if using all 28 heat map plots it would be at 14) has already received some of this momentum change. If you look at the second white circle (right), you’ll also notice the higher MFI plot indexes are also green. This is because since their length is long they still have some momentum and strength from the first white circle (left). Just because the first white circle failed in its bullish push, doesn’t mean it didn’t achieve momentum that would later on help to push the price up.
3. The Lower levels of the Heat Map are turning Yellow/Orange/Red (60-100 MFI): It occurred somewhat in the left white circle, but mainly in the right white circle. This shows us the MFI is very high on the lower lengths, this may lead to the current, middle and higher length MFIs following suit soon. Remember it has to work its way up, the higher levels can’t go red unless the lower levels go red first and the higher levels can also lag quite a bit behind and take awhile to catch up, this is normal, expected and meant to happen. Vice versa is also true with getting higher levels to go cold (light teal (think of ICE)).
4. The Upper Levels of the Heat Map are still Light Blue - Green (10-50 MFI): You might think at first that this is a bad thing, but it's not! Remember you want to be Fearful when others are Greedy and Greedy when others are Fearful! You don’t want to buy when the higher levels have a high MFI, you want to buy when you see the momentum pushing up in the lower MFI levels (getting yellow/orange/red in the low levels) while it is still Cold in the higher levels (BLUE OR GREEN, nothing higher than green as it is already slightly too high). There will be many times that it is Yellow or possibly Orange in the high levels and the bullish push still happens, but this is much more risky! The key to trading is to minimize risks while maximizing potential.
Hopefully now you’re getting an idea of how to spot potential bullish momentum changes, but what about bearish momentum changes? Technically they are the exact opposite, so we don’t need to go into as much detail, but lets still take a look at a few examples:
In the example above we marked the 3 times where it was displaying overly bullish characteristics. We marked the bullish momentum occurring with arrows. If you look closely at the start of the arrow to where it finishes, you’ll notice how the heat (HOT)(RED) works its way up from the lower levels to the higher levels. We then see the MFI to SMA cross under. In all 3 of these examples the heat made it all the way to the top of the chart. These are all very bearish signals that represent a bearish momentum movement that may occur soon.
Also, please note, the level the MFI is at DOES matter! That line isn’t there simply for you to see when there are crosses over and under. The MFI is considered to be Overbought when it is greater than 70 (the upper white dashed line, it is just formatted to be on a different scale cause there are 28 plots, but it represents 70). The MFI is considered to be Oversold when it is less than 30 (the lower white dashed line).
If we look to the left a little here where a big drop in price occurred shortly after our MFI and SMA crossed, would we have been able to identify it using the Heat Maps? Likely, No. There was some color change in the lower levels a few bars prior that went yellow/orange/red but before this cross happened they all went back to Dark Blue. In the middle section when the cross happened it was only Green and Yellow and in the upper section we are Blue. This would be a very risky trade to go on as the only real Bearish Indication was the MFI to SMA cross under. Remember, you want to reduce risk, you don’t want to simply trade on everytime the MFI and SMA cross each other or you’ll be getting yourself into many risky trades based on false signals.
Based on what you’ve learned above, can you see the signs that are indicating where this white circle may have potential for a bullish momentum change?
Now that we are more zoomed in, you may also be noticing there are colors to the price bars. This can be disabled in the settings, but just so you know what they mean, let’s zoom in a little more and talk about it.
We’ve condensed the Indicator a bit so you can see the bars better here. The colors that are displayed on these bars are the Heat Map value for your MFI (the white line in the Indicator). This way you can better see when the Price is Hot and Cold. As you may see while looking, the colors generally go from cold to hot when bullish momentum is happening and hot to cold when bearish momentum is happening. We don’t recommend solely looking at the bars as indicators to MFI momentum change, as seeing the Heat Map will give you much more data; however it can be nice to see the Heat Map projected on the bars rather than trying to eyeball it yourself or hover over each bar specifically to see their levels.
We will conclude our Tutorial here. Hopefully this has given you some insight to how useful Heat Maps can be and why it works well with a Machine Learning (KNN) Model applied to the MFI.
PLEASE NOTE: You can adjust the line width for the Heat Map within the settings. If you condense the Indicator a lot or have a small screen, likely use a length of 1-2. If you have it stretched out or a large screen, a length of 2-3 will work nice. You just don’t want to have the lines overlapping or it defeats the purpose of a Heat Map. Also, the bigger the linewidth, generally you’ll want to increase the Transparency within the Settings also as it can get quite bright and hurt your eyes over time.
Settings:
MFI:
Show MFI and SMA Crossing Signals: MFI and SMA Crossing is one of the leading Bullish and Bearish Signals in this Indicator. You can also add alerts for these signals.
Plot Amount: How many plots are used in this Heat Map. (2 - 28).
Source: The Source to use in all MFI calculations.
Smooth Initial MFI Length: How much to smooth the Fast and Slow MFI calculation by. 1 = No smoothing.
MFI SMA Length: What length we smooth the MFI Average over to get our MFI SMA.
Machine Learning:
Average MFI data by adding a lookback to the Source: While populating our Heat Map with the MFI's, should use use the Source each MFI Length increase or should we also lookback a Source each MFI Length Increase.
KNN Distance Requirement: To be a valid KNN, it needs to abide by a Distance calculation. Generally only Max is used, but you can change it if it suits your trading style better.
Machine Learning Length: How much ML data should we store? The longer the length generally the smoother the result; which may not be as accurate for something like a Heat Map, so keeping this relatively low may lead to more accurate results.
KNN Length: How many KNN are used in the slice to calculate max/min distance allowed.
Fast Length: Fast MFI length used in KNN to calculate distances by comparing its distance with the Slow MFI Length.
Slow Length: Slow MFI length used in KNN to calculate distances by comparing its distance with the Fast MFI Length.
Smoothing Length: When populating our Heat Map, at what length do we start our MFI calculations with (A Higher value with result in a slower and more smoothed MFI / Heat Map).
Colors:
Change Bar Color: Change bar colors to MFI Avg Color.
Heat Map Transparency: If there isn't any transparency it can be a little hard on the eyes. The Greater the Line Width, generally the more transparency you'll want for your eyes.
Line Width: Set how wide the Heat Map lines are
MFI 90-100 Color: Color when the MFI is between these levels.
MFI 80-89 Color: Color when the MFI is between these levels.
MFI 70-79 Color: Color when the MFI is between these levels.
MFI 60-69 Color: Color when the MFI is between these levels.
MFI 50-59 Color: Color when the MFI is between these levels.
MFI 40-49 Color: Color when the MFI is between these levels.
MFI 30-39 Color: Color when the MFI is between these levels.
MFI 20-29 Color: Color when the MFI is between these levels.
MFI 10-19 Color: Color when the MFI is between these levels.
MFI 0-100 Color: Color when the MFI is between these levels.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING! Indicator
EMAFlowLibrary "EMAFlow"
Functions that manipulate a set of 5 MAs created within user-supplied maximum and minimum lengths. The MAs are spaced out (within the range) in a way that approximates how Fibonnaci numbers are spaced.
Using MA flow, as opposed to simple crosses of the minimum and maximum lengths, gives more detail, and can result in faster changes and more resistance to chop, depending how you use it.
f_emaFlowBias()
@function f_emaFlowBias: Gives a bullish or bearish bias reading based on the EMA flow from the user-supplied range.
@param int _min: The minimum length of the EMA set.
@param int _max: The maximum length of the EMA set.
@param: string _source: The source for the EMA set. Must be in standard format (open, close, ohlc4, etc.)
@returns: An integer, representing the bias: 1 is bearish, 2 is slightly bearish, 3 is neutral, 4 is slightly bullish, 5 is bullish.
Library
Equity Bond Currency DashboardDepicts demand-flow between Equities, Bonds and Currencies of 6 countries. Useful in tracking the flow of smart money and checking the dynamics of inter-connected markets.
Principle:
DXY lies at the heart of the diagram with usd-currency pairs of 5 countries connected to it. When demand for a currency increases it strengthens against Dollar. This is depicted by a line from DXY to the currency indicating demand flow from Dollar to the currency (DXY is only an indicative symbol for Dollar, the currency may not be part of the dollar index). Similarly when Dollar strengthens against the currency, demand flow is depicted by a line from the currency to DXY. Currency blocks are connected to Equity and Bond Yields of the respective countries. Equities and Bonds, when bought, takes the demand from the respective currencies and vice versa.
Overall, the demand flows in the direction of arrows. The flow is incomplete without commodities, import/export, interest/inflation rates of countries, however, the diagram most of the times explains why an asset class is performing the way it is.
Left side bar of each block is very similar to OHLC candles except for the following -
Instead of wicks, top and bottom of the bar represents high and low for the selected time-frame
Open and close are normalised for high and low
Bar border is red if close < prev.close, green if close >= prev.close
Other notes:
The diagram requires at least 200 bars in the chart to render. Please select the symbol and time-frame that contain at least 200 bars.
The diagram requires a live market to render the flow. To check flows on historical bars, set the option from settings.
Desired indices could be selected for countries of choice. Default settings point to futures wherever possible to have the markets live simultaneously across the countries.
Indicator
UFO + Realtime Divergences (UO x MFI)UFO + Realtime Divergences (UO x MFI) + Alerts
The UFO is a hybrid of two powerful oscillators - the Ultimate Oscillator (UO) and the Money Flow Index (MFI)
Features of the UFO include:
- Optional divergence lines drawn directly onto the oscillator in realtime.
- Configurable alerts to notify you when divergences occur, as well as centerline crossovers.
- Configurable lookback periods to fine tune the divergences drawn in order to suit different trading styles and timeframes.
- Background colouring option to indicate when the oscillator has crossed its centerline.
- Alternate timeframe feature allows you to configure the oscillator to use data from a different timeframe than the chart it is loaded on.
- 2x MTF triple-timeframe Stochastic RSI overbought and oversold confluence signals painted at the top of the panel for use as a confluence for reversal entry trades.
The core calculations of the UFO+ combine the factory settings of the Ultimate Oscillator and Money Flow Index, taking an average of their combined values for its output eg:
UO_Value + MFI_Value / 2
The result is a powerful oscillator capable of detecting high quality divergences, including on very low timeframes and highly volatile markets, it benefits from the higher weighting of the most recent price action provided by the Ultimate Oscillators calculations, as well as the calculation of the MFI, which incorporates volume data. The UFO and its incorporated 2x triple-timeframe MTF Stoch RSI overbought and oversold signals makes it well adapted for low timeframe scalping and regular divergence trades in particular.
The Ultimate Oscillator (UO)
Tradingview describes the Ultimate Oscillator as follows:
“The Ultimate Oscillator indicator (UO) is a technical analysis tool used to measure momentum across three varying timeframes. The problem with many momentum oscillators is that after a rapid advance or decline in price, they can form false divergence trading signals. For example, after a rapid rise in price, a bearish divergence signal may present itself, however price continues to rise. The Ultimate Oscillator attempts to correct this by using multiple timeframes in its calculation as opposed to just one timeframe which is what is used in most other momentum oscillators.”
You can read more about the UO and its calculations here
The Money Flow Index ( MFI )
Investopedia describes the True Strength Indicator as follows:
“The Money Flow Index ( MFI ) is a technical oscillator that uses price and volume data for identifying overbought or oversold signals in an asset. It can also be used to spot divergences which warn of a trend change in price. The oscillator moves between 0 and 100. Unlike conventional oscillators such as the Relative Strength Index ( RSI ), the Money Flow Index incorporates both price and volume data, as opposed to just price. For this reason, some analysts call MFI the volume-weighted RSI .”
You can read more about the MFI and its calculations here
The Stochastic RSI (relating to the built-in MTF Stoch RSI feature)
The popular oscillator has been described as follows:
“The Stochastic RSI is an indicator used in technical analysis that ranges between zero and one (or zero and 100 on some charting platforms) and is created by applying the Stochastic oscillator formula to a set of relative strength index ( RSI ) values rather than to standard price data. Using RSI values within the Stochastic formula gives traders an idea of whether the current RSI value is overbought or oversold. The Stochastic RSI oscillator was developed to take advantage of both momentum indicators in order to create a more sensitive indicator that is attuned to a specific security's historical performance rather than a generalized analysis of price change.”
You can read more about the Stochastic RSI and its calculations here
How do traders use overbought and oversold levels in their trading?
The oversold level, that is when the Stochastic RSI is above the 80 level is typically interpreted as being 'overbought', and below the 20 level is typically considered 'oversold'. Traders will often use the Stochastic RSI at an overbought level as a confluence for entry into a short position, and the Stochastic RSI at an oversold level as a confluence for an entry into a long position. These levels do not mean that price will necessarily reverse at those levels in a reliable way, however. This is why this version of the Stoch RSI employs the triple timeframe overbought and oversold confluence, in an attempt to add a more confluence and reliability to this usage of the Stoch RSI .
What are divergences?
Divergence is when the price of an asset is moving in the opposite direction of a technical indicator, such as an oscillator, or is moving contrary to other data. Divergence warns that the current price trend may be weakening, and in some cases may lead to the price changing direction.
There are 4 main types of divergence, which are split into 2 categories;
regular divergences and hidden divergences. Regular divergences indicate possible trend reversals, and hidden divergences indicate possible trend continuation.
Regular bullish divergence: An indication of a potential trend reversal, from the current downtrend, to an uptrend.
Regular bearish divergence: An indication of a potential trend reversal, from the current uptrend, to a downtrend.
Hidden bullish divergence: An indication of a potential uptrend continuation.
Hidden bearish divergence: An indication of a potential downtrend continuation.
How do traders use divergences in their trading?
A divergence is considered a leading indicator in technical analysis , meaning it has the ability to indicate a potential price move in the short term future.
Hidden bullish and hidden bearish divergences, which indicate a potential continuation of the current trend are sometimes considered a good place for traders to begin, since trend continuation occurs more frequently than reversals, or trend changes.
When trading regular bullish divergences and regular bearish divergences, which are indications of a trend reversal, the probability of it doing so may increase when these occur at a strong support or resistance level . A common mistake new traders make is to get into a regular divergence trade too early, assuming it will immediately reverse, but these can continue to form for some time before the trend eventually changes, by using forms of support or resistance as an added confluence, such as when price reaches a moving average, the success rate when trading these patterns may increase.
Typically, traders will manually draw lines across the swing highs and swing lows of both the price chart and the oscillator to see whether they appear to present a divergence, this indicator will draw them for you, quickly and clearly, and can notify you when they occur.
Setting alerts.
With this indicator you can set alerts to notify you when any/all of the above types of divergences occur, on any chart timeframe you choose.
Configurable pivot period.
You can adjust the default pivot lookback values to suit your prefered trading style and timeframe. If you like to trade a shorter time frame, lowering the default lookback values will make the divergences drawn more sensitive to short term price action.
Disclaimer: This script includes code from the stock UO and MFI by Tradingview as well as the Divergence for Many Indicators v4 by LonesomeTheBlue. Indicator
MFI + Realtime DivergencesMoney Flow Index (MFI) + Realtime Divergences + Alerts
This version of the MFI indicator adds the following 5 additional features to the stock MFI:
- Optional divergence lines drawn directly onto the oscillator in realtime.
- Configurable alerts to notify you when divergences occur.
- Configurable lookback periods to fine tune the divergences drawn in order to suit different trading styles and timeframes, including the ability to enable automatic adjustment of pivot period per chart timeframe.
- Background colouring option to indicate when the MFI oscillator has crossed above or below its centerline, or optionally when both the MFI has crossed its centerline and an external oscillator, which can be linked via the settings, has also crossed its centerline.
- Alternate timeframe feature allows you to configure the oscillator to use data from a different timeframe than the chart it is loaded on.
This indicator adds additional features onto the standard MFI , whose core calculations remain unchanged. Namely the configurable option to automatically, quickly and clearly draw divergence lines onto the oscillator for you as they occur in realtime. It also has the addition of unique alerts, so you can be notified when divergences occur without spending all day watching the charts. Furthermore, this version of the TSI comes with configurable lookback periods, which can be configured in order to adjust the sensitivity of the divergences, in order to suit shorter or higher timeframe trading approaches.
What is the Money Flow Index ( MFI )?
Investopedia describes the True Strength Indicator as follows:
“The Money Flow Index ( MFI ) is a technical oscillator that uses price and volume data for identifying overbought or oversold signals in an asset. It can also be used to spot divergences which warn of a trend change in price. The oscillator moves between 0 and 100.
Unlike conventional oscillators such as the Relative Strength Index ( RSI ), the Money Flow Index incorporates both price and volume data, as opposed to just price. For this reason, some analysts call MFI the volume-weighted RSI .”
What are divergences?
Divergence is when the price of an asset is moving in the opposite direction of a technical indicator, such as an oscillator, or is moving contrary to other data. Divergence warns that the current price trend may be weakening, and in some cases may lead to the price changing direction.
There are 4 main types of divergence, which are split into 2 categories;
regular divergences and hidden divergences. Regular divergences indicate possible trend reversals, and hidden divergences indicate possible trend continuation.
Regular bullish divergence: An indication of a potential trend reversal, from the current downtrend, to an uptrend.
Regular bearish divergence: An indication of a potential trend reversal, from the current uptrend, to a downtrend.
Hidden bullish divergence: An indication of a potential uptrend continuation.
Hidden bearish divergence: An indication of a potential downtrend continuation.
Setting alerts.
With this indicator you can set alerts to notify you when any/all of the above types of divergences occur, on any chart timeframe you choose.
Configurable pivot periods.
You can adjust the default pivot periods to suit your prefered trading style and timeframe. If you like to trade a shorter time frame, lowering the default lookback values will make the divergences drawn more sensitive to short term price action.
How do traders use divergences in their trading?
A divergence is considered a leading indicator in technical analysis , meaning it has the ability to indicate a potential price move in the short term future.
Hidden bullish and hidden bearish divergences, which indicate a potential continuation of the current trend are sometimes considered a good place for traders to begin, since trend continuation occurs more frequently than reversals, or trend changes.
When trading regular bullish divergences and regular bearish divergences, which are indications of a trend reversal, the probability of it doing so may increase when these occur at a strong support or resistance level . A common mistake new traders make is to get into a regular divergence trade too early, assuming it will immediately reverse, but these can continue to form for some time before the trend eventually changes, by using forms of support or resistance as an added confluence, such as when price reaches a moving average, the success rate when trading these patterns may increase.
Typically, traders will manually draw lines across the swing highs and swing lows of both the price chart and the oscillator to see whether they appear to present a divergence, this indicator will draw them for you, quickly and clearly, and can notify you when they occur.
Disclaimer: This script includes code from the stock MFI by Tradingview as well as the Divergence for Many Indicators v4 by LonesomeTheBlue. Indicator
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