EulerMethod: DeltaEN
Shows the Integral Volume Delta (IVD)
It is a detailed OBV. Each bar sums up the volume for bars of a shorter timeframe.
For example, inside a 1M bar, every 12h bar is added up, and inside a 1h bar, every 1min bar is added. Thus, a conditional volume delta inside the bar is obtained.
The indicator for each bar shows the volume of purchases (positive), sales (negative) and the difference — IVD
The delta histogram is thicker than the volume histograms
Settings detalisation
M — 6 hours, 12 hours and 1 day for the M timeframe (720 by default)
W — 4 hours, 6 hours and 12 hours for the W timeframe (240 by default)
D — 30 minutes, 1 hour and 2 hours for the D timeframe (60 by default)
H — 1 minute, 5 minutes and 15 minutes for timeframes [1h, D) (default is 1)
For timeframes of 15m and less, the calculation is carried out by minute bars
VSA mode
The classic OBV adds volume to the cumulative sum under the condition Сlose (n) > Close (n-1) and subtracts it under the condition Close (n) < Close (n-1)
When VSA mode is disabled, all volumes are summed up under these conditions.
When the VSA approximation is turned on, the volume per bar of detail is divided by the factor (Close - Low) / (High - Low)
That is, it takes into account the spread per bar and closing relative to the spread. VSA is enabled by default
A/D mode
Shows the cumulative Accumulation / Distribution Index
The delta of the detail bar is multiplied by (High + Low + Close) / 3 bars, the result is added to the cumulative sum
No additional price conversions required due to integral summation
Index line view is customizable
EM Delta does not receive intermediate values in real time.
To see the result, wait until the bar closes or switch to a smaller timeframe
RU
Показывает Интегральную Дельту Объёма (ИДО)
Представляет собой детализированный OBV. В каждом баре суммируется объём за бары меньшего таймфрейма.
Например, внутри 1М-бара суммируется каждый 12h-бар, а внутри 1h — каждый 1m-бар. Таким образом получается условная дельта объёма внутри бара
Индикатор на каждый бар показывает объём покупок (положительный), объём продаж (отрицательный) и разницу — ИДО
Гистограмма дельты толще гистограмм объёмов
Настройки детализации внутри бара
M — 6 часов, 12 часов и 1 день для таймфрейма M (по-умолчанию 720)
W — 4 часа, 6 часов и 12 часов для таймфрейма W (по-умолчанию 240)
D — 30 минут, 1 час и 2 часа для таймфрейма D (по-умолчанию 60)
H — 1 минута, 5 минут и 15 минут для таймфреймов [1h, D) (по-умолчанию 1)
Для таймфреймов 15m и меньше расчёт ведётся по минутным барам
Режим VSA
Классический OBV прибавляет объём к кумулятивной сумме при условии Сlose(n) > Close(n-1) и отнимает при условии Close(n) < Close(n-1)
При отключении режима VSA все объёмы суммируются по этим условиям
При включённой VSA-аппроксимации объём за бар детализации делится по фактору (Close - Low) / (High - Low)
То есть учитывает спред за бар и закрытие относительно спреда. По-умолчанию режим VSA включен
Режим A/D
Показывает кумулятивный индекс Накопления/Распределения
Дельта бара детализации умножается на (High + Low + Close) / 3 бара, результат прибавляется к кумулятивной сумме
Дополнительные преобразования цены не требуются ввиду интегрального суммирования
Вид линии индекса настраивается
EM Delta не получает промежуточные значения в реальном времени.
Чтобы увидеть результат, дождитесь закрытия бара или перейдите на меньший таймфрейм
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Reversal finderThis script is used to visually highlight candles which may signal a reversal following a false break of a support or resistance level.
Inputs are:
Lookback period: look for the highest high and the lowest low of the prior x bars.
SMA length: used for a simple moving average of the range (high minus low) of the prior x bars.
Range multiple: used to filter out signals for any bars with a range smaller than the average range of the preceding bars (determined by SMA length above) e.g. a range multiple of 2 will only show signals for bars with a range twice of that of the average range of the preceding bars.
Range threshold: used to filter signals for bars both the open and close of the bar are at the extreme end of the bar e.g. a threshold setting of 33% will only show buy signals for bars which open and close within the upper 1/3rd of the bar’s high/low range (vice versa for sell signals). This helps highlight, for example, bars with a high which exceeds resistance in a current range but which close back inside the range.
Highlight signal bars?: This will highlight bars with a buy signal in green, sell signal bars in red, and all other bars in grey. The script was designed for use with a dark background, so you will need to play around with the bar colours in the style settings to suit your preferences.
Settings used in the example chart are not the default – they are lookback: 5, SMA length: 20, range multiple: 1.2, range threshold: 33%.
Enjoy!
MFI v1.0 Normal and Dinamic (Totals)The normal MFI script use an RSI in the formula so the quantity of movments are not visible, this script allows you to see how much volume is being trade at the moment, so you can detect unusual levels, but you will no be allowed to see the RSI (0-100)* so I suggest to use this script with a normal MFI
Features:
+ Normal MFI length (14)
+ Green bars show the total of money trade of the bars that are going up
+ Red bars show the total of money trade when of the bars that are going down
+ Dinamic calculation (Optional)(Bellow)
Normal MFI use hlc3 ((high+low+close)/3) * (volume) to calculate each bar
The dinamic MFI: (This is an optional feature, if you dont active it you will use the normal MFI calculation)
(The information bellow is experimental and theorical only, you can use it or not in the script with the Dinamic option)
Dinamic MFI divides the bar and volume in three parts.
Volume is corresponding on each part ex. If the bar has not a top or lower wick the 100% of volume is in the middle... ex 2 If the 50% of the bar is a top wick, the 50% of volume is in the top wick
Top wick: Is calculated this way
If the bar is red (high-open)*volume of top wick
or
If the bar is green (high-close)*volume of top wick
Middle: Is calculated this way
If the bar is green (close-open)*volumemiddle
or
If the bar is red (open-close)*volumemiddle
Lower wick
If the bar is red (close-low)*volume of lower wick
or
If the bar is green (open- low)*volume of lower wick
MIDAS VWAP Jayy his is just a bash together of two MIDAS VWAP scripts particularly AkifTokuz and drshoe.
I added the ability to show more MIDAS curves from the same script.
The algorithm primarily uses the "n" number but the date can be used for the 8th VWAP
I have not converted the script to version 3.
To find bar number go into "Chart Properties" select " "background" then select Indicator Titles and "Indicator values". When you place your cursor over a bar the first number you see adjacent to the script title is the bar number. Put that in the dialogue box midline is MIDAS VWAP . The resistance is a MIDAS VWAP using bar highs. The resistance is MIDAS VWAP using bar lows.
In most case using N will suffice. However, if you are flipping around charts inputting a specific date can be handy. In this way, you can compare the same point in time across multiple instruments eg first trading day of the year or an election date.
Adding dates into the dialogue box is a bit cumbersome so in this version, it is enabled for only one curve. I have called it VWAP and it follows the typical VWAP algorithm. (Does that make a difference? Read below re my opinion on the Difference between MIDAS VWAP and VWAP ).
I have added the ability to start from the bottom or top of the initiating bar.
In theory in a probable uptrend pick a low of a bar for a low pivot and start the MIDAS VWAP there using the support.
For a downtrend use the high pivot bar and select resistance. The way to see is to play with these values.
Difference between MIDAS VWAP and the regular VWAP
MIDAS itself as described by Levine uses a time anchored On-Balance Volume (OBV) plotted on a graph where the horizontal (abscissa) arm of the graph is cumulative volume not time. He called his VWAP curves Support/Resistance VWAP or S/R curves. These S/R curves are often referred to as "MIDAS curves".
These are the main components of the MIDAS chart. A third algorithm called the Top-Bottom Finder was also described. (Separate script).
Additional tools have been described in "MIDAS_Technical_Analysis"
Midas Technical Analysis: A VWAP Approach to Trading and Investing in Today’s Markets by Andrew Coles, David G. Hawkins
Copyright © 2011 by Andrew Coles and David G. Hawkins.
Denoting the different way in which Levine approached the calculation.
The difference between "MIDAS" VWAP and VWAP is, in my opinion, much ado about nothing. The algorithms generate identical curves albeit the MIDAS algorithm launches the curve one bar later than the VWAP algorithm which can be a pain in the neck. All of the algorithms that I looked at on Tradingview step back one bar in time to initiate the MIDAS curve. As such the plotted curves are identical to traditional VWAP assuming the initiation is from the candle/bar midpoint.
How did Levine intend the curves to be drawn?
On a reversal, he suggested the initiation of the Support and Resistance VVWAP (S/R curve) to be started after a reversal.
It is clear in his examples this happens occasionally but in many cases he initiates the so-called MIDAS S/R VWAP right at the reversal point. In any case, the algorithm is problematic if you wish to start a curve on the first bar of an IPO .
You will get nothing. That is a pain. Also in Levine's writings, he describes simply clicking on the point where a
S/R VWAP is to be drawn from. As such, the generally accepted method of initiating the curve at N-1 is a practical and sensible method. The only issue is that you cannot draw the curve from the first bar on any security, as mentioned without resorting to the typical VWAP algorithm. There is another difference. VWAP is launched from the middle of the bar (as per AlphaTrends), You can also launch from the top of the bar or the bottom (or anywhere for that matter). The calculation proceeds using the top or bottom for each new bar.
The potential applications are discussed in the MIDAS Technical Analysis book.
RSI Signals Multi-Layer RSI System with Classical Divergence**DrFX RSI Signals Fixed** is an advanced RSI-based trading system that combines duration-filtered extreme conditions with classical divergence detection and momentum confirmation. This enhanced version addresses common RSI false signals through multi-layer filtering while adding proper divergence analysis for identifying high-probability reversal points.
**Core Innovation & Originality**
This indicator uniquely integrates five analytical layers:
1. **Duration-Validated Extreme Zones** - Confirms RSI has remained overbought/oversold for minimum bars within lookback period
2. **Classical Divergence Detection** - Proper implementation comparing swing highs/lows in both price and RSI
3. **Momentum Confirmation Signals** - RSI crossing 50-line after extreme conditions for trend confirmation
4. **Multi-Signal Classification** - Four distinct signal types (Buy, Sell, Strong Buy, Strong Sell, Momentum)
5. **Visual Zone Highlighting** - Background coloring for instant extreme zone identification
**Technical Implementation & Improvements**
**Enhanced Duration Filter:**
Unlike the previous version, this system uses a refined approach:
```
for i = 0 to lookback_bars - 1
if rsi > overbought
barsInOverbought := barsInOverbought + 1
```
This counts actual bars within the lookback period (default 20 bars) where RSI was extreme, requiring minimum duration (default 4 bars) for signal validation.
**Classical Divergence Detection:**
The system implements proper divergence analysis, a significant improvement over simple delta comparison:
**Bullish Divergence Logic:**
- Price makes lower low: `low < prevPriceLow`
- RSI makes higher low: `rsi > prevRsiLow`
- Indicates weakening downward momentum despite lower prices
**Bearish Divergence Logic:**
- Price makes higher high: `high > prevPriceHigh`
- RSI makes lower high: `rsi < prevRsiHigh`
- Indicates weakening upward momentum despite higher prices
**Signal Generation Framework:**
**Primary Signals:**
- **Buy Signal**: RSI crosses above oversold (30) after meeting duration requirements
- **Sell Signal**: RSI crosses below overbought (70) after meeting duration requirements
**Strong Signals:**
- **Strong Buy**: Buy signal + bullish divergence confirmation
- **Strong Sell**: Sell signal + bearish divergence confirmation
**Momentum Signals:**
- **Momentum Buy (M+)**: RSI crosses above 50 after recent oversold conditions
- **Momentum Sell (M-)**: RSI crosses below 50 after recent overbought conditions
**What Makes This Version Superior**
**Compared to Standard RSI:**
1. **Duration Requirement**: Prevents signals on brief RSI spikes
2. **Lookback Validation**: Ensures extreme conditions actually occurred recently
3. **Proper Divergence**: Uses swing high/low comparison, not just bar-to-bar deltas
4. **Momentum Layer**: Adds trend confirmation via 50-line crosses
**Compared to Previous Version:**
1. **Pine Script v5**: Modern syntax with improved performance
2. **Configurable Parameters**: All values adjustable via inputs
3. **Better Divergence**: Classical divergence logic replaces simplified delta method
4. **Additional Signals**: Momentum confirmations for trend following
5. **Visual Enhancements**: Background coloring and improved signal differentiation
6. **Alert System**: Built-in alert conditions for all signal types
**Parameter Configuration**
**Customizable Inputs:**
- **Overbought Level** (70): Upper threshold, range 50-90
- **Oversold Level** (30): Lower threshold, range 10-50
- **RSI Period** (14): Calculation period, range 2-50
- **Minimum Duration** (4): Required bars in extreme zone, range 1-20
- **Lookback Bars** (20): Period to check for extreme conditions, range 5-100
- **Divergence Lookback** (5): Period for divergence swing comparison, range 2-20
**Optimization Guidelines:**
- **Shorter Duration** (2-3): More frequent signals, higher noise
- **Longer Duration** (5-7): Fewer signals, better quality
- **Smaller Lookback** (10-15): Faster response, may miss context
- **Larger Lookback** (30-50): More context, potentially delayed signals
**Signal Interpretation Guide**
**Visual Signal Hierarchy:**
**Light Green Triangle (Buy):**
- RSI recovered from oversold
- Duration requirements met
- Entry on reversal from oversold territory
**Light Red Triangle (Sell):**
- RSI declined from overbought
- Duration requirements met
- Entry on reversal from overbought territory
**Blue Triangle (Strong Buy):**
- Buy signal with bullish divergence
- Highest probability long setup
- Price made lower low, RSI made higher low
**Magenta Triangle (Strong Sell):**
- Sell signal with bearish divergence
- Highest probability short setup
- Price made higher high, RSI made lower high
**Tiny Green Circle (M+):**
- RSI crossed above 50 after oversold
- Momentum confirmation for uptrend
- Secondary entry or trend confirmation
**Tiny Red Circle (M-):**
- RSI crossed below 50 after overbought
- Momentum confirmation for downtrend
- Secondary entry or trend confirmation
**Background Coloring:**
- **Light Red Background**: RSI > 70 (overbought zone)
- **Light Green Background**: RSI < 30 (oversold zone)
**Trading Strategy Application**
**Conservative Approach (Strong Signals Only):**
1. Wait for blue/magenta triangles (divergence confirmed)
2. Enter on signal bar close or next bar open
3. Stop loss beyond recent swing high/low
4. Target minimum 2:1 risk/reward ratio
**Aggressive Approach (All Signals):**
1. Take light green/red triangles for earlier entries
2. Use momentum circles as confirmation
3. Tighter stops with partial profit taking
4. Scale positions based on signal strength
**Momentum Trading:**
1. Use momentum signals (M+/M-) as trend filters
2. Take primary signals aligned with momentum direction
3. Avoid counter-momentum signals in strong trends
4. Exit when opposing momentum signal appears
**Multi-Timeframe Strategy:**
1. Check higher timeframe for strong signals
2. Execute on lower timeframe primary signals
3. Use momentum signals for position management
4. Align all timeframe signals for best probability
**Optimal Market Conditions**
**Best Performance:**
- Mean-reverting markets with clear RSI extremes
- Range-bound or consolidating conditions
- Markets respecting support/resistance levels
- Timeframes: 15min to 4H for active trading
**Strong Signal Advantages:**
- Divergence signals often mark major turning points
- Work well at market structure levels
- Effective in both trending and ranging markets
- Higher success rate justifies waiting for setup
**Momentum Signal Benefits:**
- Confirms trend direction after extreme readings
- Useful for adding to positions
- Helps avoid counter-trend trades
- Works well in trending markets where reversals fail
**Technical Advantages**
**Divergence Accuracy:**
The improved divergence detection uses proper swing analysis rather than simple bar-to-bar comparison. This identifies genuine momentum shifts where price action diverges from oscillator movement over a meaningful period.
**Duration Logic:**
The for-loop counting method ensures the system checks actual RSI values within the lookback period, not just whether RSI touched levels. This distinguishes between sustained conditions and brief spikes.
**Momentum Filter:**
The 50-line crosses after extreme conditions provide an additional confirmation layer, helping traders distinguish between failed reversals (no momentum follow-through) and sustained moves (momentum confirmation).
**Risk Management Integration**
**Signal Priority:**
1. **Highest**: Strong signals with divergence (blue/magenta triangles)
2. **Medium**: Primary signals without divergence (light green/red triangles)
3. **Confirmation**: Momentum signals (tiny circles)
**Position Sizing:**
- Larger positions on strong signals (divergence present)
- Standard positions on primary signals
- Smaller positions or adds on momentum signals
**Stop Placement:**
- Beyond recent swing structure
- Below/above divergence swing low/high for strong signals
- Trail stops when momentum signals align with position
**Alert System**
Built-in alert conditions for:
- Buy Signal: RSI buy without divergence
- Sell Signal: RSI sell without divergence
- Strong Buy Alert: Buy with bullish divergence
- Strong Sell Alert: Sell with bearish divergence
Configure alerts via TradingView's alert system to receive notifications for chosen signal types.
**Important Considerations**
**Strengths:**
- Multiple confirmation layers reduce false signals
- Classical divergence improves reversal detection
- Momentum signals add trend-following capability
- Highly customizable for different trading styles
- No repainting - all signals fixed at bar close
**Limitations:**
- Duration requirements may cause missed quick reversals
- Divergence lookback period affects sensitivity
- Not suitable as standalone system
- Requires understanding of RSI principles and divergence concepts
**Best Practices:**
- Combine with price action and support/resistance
- Use higher timeframe context for directional bias
- Respect overall market trend and structure
- Implement proper position sizing based on signal type
- Test parameters on your specific instrument and timeframe
**Comparison Summary**
This enhanced version represents a significant upgrade:
- Upgraded to Pine Script v5 modern standards
- Proper classical divergence detection (not simplified)
- Added momentum confirmation signals
- Fully customizable parameters via inputs
- Visual background zone highlighting
- Comprehensive alert system
- Better signal differentiation through color coding
The system transforms basic RSI analysis into a multi-dimensional trading tool suitable for various market conditions and trading styles.
**Disclaimer**: This indicator is designed for educational and analytical purposes. While the multi-layer filtering and classical divergence detection improve upon standard RSI implementations, no indicator guarantees profitable trades. The duration filtering reduces false signals but may delay entries. Divergence signals, while statistically favorable, can fail in strong trending conditions. Always use proper risk management, position sizing, and stop-loss orders. Consider multiple confirmation methods and market context before making trading decisions. Past performance does not guarantee future results.
STRAT 3-2-2 (30m) • Upcoming / Approach / Entry + AlertsThis indicator is built for The STRAT trading method, specifically the 3-2-2 reversal pattern. It monitors price action on the 30-minute timeframe (HTF = 30m) and visually/alert-wise highlights where a 3-2-2 setup, approach, or entry trigger occurs.
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⚙️ How it works
1. Detects bar types:
3 (Outside Bar) = range breaks both high & low of the previous bar
2u (Up bar) = higher high, not outside
2d (Down bar) = lower low, not outside
1 (Inside bar) = fully contained within prior bar
2. Looks for 3-2-2 setups:
Bullish 3-2-2 = 3 → 2d → 2u (expect reversal UP)
Bearish 3-2-2 = 3 → 2u → 2d (expect reversal DOWN)
3. Defines trigger levels:
Bullish trigger = high of the first “2d” bar
Bearish trigger = low of the first “2u” bar
4. Signals 3 phases:
Upcoming: pattern is forming, second “2” hasn’t triggered yet
Approach: price comes within 50% (adjustable) of the trigger level
Entry: price breaks the trigger (actual reversal confirmation)
5. Visualization:
Labels above/below candles show “Approach” and “Entry”
Background or bar colors (toggle in settings) highlight Setup / Approach / Entry
Optional dotted line marks the trigger level for clarity
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🔔 Alerts
Two alert systems are built in:
1. Safe static conditions (for normal TradingView alert setup):
APPROACH: Bullish 3-2-2 (30m)
APPROACH: Bearish 3-2-2 (30m)
ENTRY: Bullish 3-2-2 (30m)
ENTRY: Bearish 3-2-2 (30m)
2. Dynamic messages (using alert() calls with price info):
If you create an alert with “Any alert() function call”, the pop-up will include the trigger price.
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📋 Inputs (Settings)
Signal timeframe (HTF) → default 30m
Confirm signals at HTF bar close → waits for bar close (non-repainting)
Approach = % of first '2' bar range → default 50%
Show labels → On/Off
Color candles instead of background → toggle between candle color vs. chart background
FlowScape PredictorFlowScape Predictor is a non-repainting, regime-aware entry qualifier that turns complex market context into two readiness scores (Long & Short, each 0/25/50/75/100) and clean, confirmed-bar signals. It blends three orthogonal pillars so you act only when trend energy, momentum, and location agree:
Regime (energy): ATR-normalized linear-regression slope of a smooth HMA → EMA baseline, gated by ADX to confirm when pressure is meaningful.
Momentum (push): RSI slope alignment so price has directional follow-through, not just drift.
Structure (location): proximity to pivot-confirmed swings, scaled by ATR, so “ready” appears near constructive pullbacks—not mid-trend chases.
A soft ATR cloud wraps the baseline for context. A yellow Predictive Baseline extends beyond the last bar to visualize near-term trajectory. It is visual-only: scores/alerts never use it.
What you see
Baseline line that turns green/red when regime is strong in that direction; gray when weak.
ATR cloud around the baseline (context for stretch and pullbacks).
Scores (Long & Short, 0–100 in steps of 25) and optional “L/S” icons on bar close.
Yellow Predictive Baseline that extends to the right for a few bars (visual trajectory of the smoothed baseline).
The scoring system (simple and transparent)
Each side (Long/Short) sums four binary checks, 25 points each:
Regime aligned: trendStrong is true and LR slope sign favors that side.
Momentum aligned: RSI side (>50 for Long, <50 for Short) and RSI slope confirms direction.
Baseline side: price is above (Long) / below (Short) the baseline.
Location constructive: distance from the last confirmed pivot is healthy (ATR-scaled; not overstretched).
Valid totals are 0, 25, 50, 75, 100.
Best-quality signal: 100/0 (your side/opposite) on bar close.
Good, still valid: 75/0, especially when the missing block is only “location” right as price re-engages the cloud/baseline.
Avoid: 75/25 or any opposition > 0 in a weak (gray) regime.
The Predictive (Kalman) line — what it is and isn’t
The yellow line is a visual forward extension of the smoothed baseline to help you see the current trajectory and time pullback resumptions. It does not predict price and is excluded from scores and alerts.
How it’s built (plain English):
We maintain a one-dimensional Kalman state x as a smoothed estimate of the baseline. Each bar we observe the current baseline z.
The filter adjusts its trust using the Kalman gain K = P / (P + R) and updates:
x := x + K*(z − x), then P := (1 − K)*P + Q.
Q (process noise): Higher Q → expects faster change → tracks turns quicker (less smoothing).
R (measurement noise): Higher R → trusts raw baseline less → smoother, steadier projection.
What you control:
Lead (how many bars forward to draw).
Kalman Q/R (visual smoothness vs. responsiveness).
Toggle the line on/off if you prefer a minimal chart.
Important: The predictive line extends the baseline, not price. It’s a visual timing aid—don’t automate off it.
How to use (step-by-step)
Keep the chart clean and use a standard OHLC/candlestick chart.
Read the regime: Prefer trades with green/red baseline (trendStrong = true).
Check scores on bar close:
Take Long 100 / Short 0 or Long 75 / Short 0 when the chart shows a tidy pullback re-engaging the cloud/baseline.
Mirror the logic for shorts.
Confirm location: If price is > ~1.5 ATR from its reference pivot, let it come back—avoid chasing.
Set alerts: Add an alert on Long Ready or Short Ready; these fire on closed bars only.
Risk management: Use ATR-buffered stops beyond the recent pivot; target fixed-R multiples (e.g., 1.5–3.0R). Manage the trade with the baseline/cloud if you trail.
Best-practice playbook (quick rules)
Green light: 100/0 (best) or 75/0 (good) on bar close in a colored (non-gray) regime.
Location first: Prefer entries near the baseline/cloud right after a pullback, not far above/below it.
Avoid mixed signals: Skip 75/25 and anything with opposition while the baseline is gray.
Use the yellow line with discretion: It helps you see rhythm; it’s not a signal source.
Timeframes & tuning (practical defaults)
Intraday indices/FX (5m–15m): Demand 100/0 in chop; allow 75/0 when ADX is awake and pullback is clean.
Crypto intraday (15m–1h): Prefer 100/0; 75/0 on the first pullback after a regime turn.
Swing (1h–4h/D1): 75/0 is often sufficient; 100/0 is excellent (fewer but cleaner signals).
If choppy: raise ADX threshold, raise the readiness bar (insist on 100/0), or lengthen the RSI slope window.
What makes FlowScape different
Energy-first regime filter: ATR-normalized LR slope + ADX gate yields a consistent read of trend quality across symbols and timeframes.
Location-aware entries: ATR-scaled pivot proximity discourages mid-air chases, encouraging pullback timing.
Separation of concerns: The predictive line is visual-only, while scores/alerts are confirmed on close for non-repainting behavior.
One simple score per side: A single 0–100 readiness figure is easier to tune than juggling multiple indicators.
Transparency & limitations
Scores are coarse by design (25-point blocks). They’re a gatekeeper, not a promise of outcomes.
Pivots confirm after right-side bars, so structure signals appear after swings form (non-repainting by design).
Avoid using non-standard chart types (Heikin Ashi, Renko, Range, etc.) for signals; use a clean, standard chart.
No lookahead, no higher-timeframe requests; alerts fire on closed bars only.
ds-Volume with Flags & Alerts v1.2ds-Volume with Flags & Alerts: User & Training Guide
1. Summary of Features
This indicator is a powerful, all-in-one tool designed to give you a deep and customizable view of market volume. By analyzing volume in multiple ways, it helps you spot unusual activity, confirm trends, and identify potential reversals.
How It Helps a Trader:
Spotting Institutional Activity: The core purpose of the Volume Flags (using either the Multiplier or Standard Deviation method) is to highlight bars with exceptionally high volume. These spikes often signal the entry or exit of large institutional players. A high-volume up-bar can confirm bullish conviction, while a high-volume down-bar can signal significant selling pressure.
Identifying Climactic Events: The HVE (Highest Volume Ever) and HV1 (Highest Volume - 1 Year) labels automatically pinpoint the most significant volume events on the chart. A "blow-off top" at the end of a long uptrend or a "capitulation" event at a market bottom is almost always accompanied by an HVE or HV1 bar. These are critical moments to watch for potential trend reversals.
Gauging Buying vs. Selling Pressure: The Up/Down Volume Ratio gives you a more nuanced view than volume alone. A ratio consistently above 1.2 suggests that buyers are more aggressive, while a ratio below 0.8 suggests sellers are in control. Watching this ratio can help you confirm the strength of a trend or spot divergences where price is rising but the ratio is falling (a potential warning sign).
Visual Confirmation & Customization: With options to color both the volume bars and the main price bars, you can get instant visual confirmation of these events without having to look away from the price action. The ability to toggle features on and off keeps your chart clean and focused on what matters most to you.
Actionable Alerts: The comprehensive alert system ensures you don't miss a key event. You can be notified of everything from a new all-time high volume bar to a subtle shift in the Up/Down Volume Ratio, allowing you to react to market changes in real-time.
2. User-Changeable Options
This indicator is highly customizable. Here is a breakdown of every setting available in the "Inputs" tab.
General Settings
MA Length: The lookback period for the simple moving average (the gray area plot) of the volume.
Volume Flags
Color Price Bars with Flags: If checked, the main price bars on your chart will be colored when a high or low volume flag condition is met.
Color Volume Bars with Flags: If checked, the volume bars in the indicator pane will be colored for flag conditions.
Flag Calculation Method: This is a crucial setting.
Multiplier (Default): Identifies high volume based on a simple multiple of the average volume (e.g., volume is 1.4x its average). It's simple and intuitive.
Standard Deviation: Identifies high volume based on how statistically unusual it is compared to its recent behavior. This method is more adaptive to changing market volatility.
Daily/Weekly Lookback (Multiplier): Sets the lookback period for calculating the average volume when using the "Multiplier" method.
Daily/Weekly High-Vol Multiplier: Sets the multiplier for a high volume event (e.g., 1.4).
STDEV Length (Daily/Weekly): Sets the lookback period for calculating the average and standard deviation when using the "Standard Deviation" method.
STDEV Threshold (Daily/Weekly): Sets the number of standard deviations above the average required to trigger a high volume flag (e.g., 2.0).
Daily/Weekly Low-Vol Multiplier: Sets the threshold for a low volume event (e.g., 0.5 means volume is less than 50% of its average). This is always based on the multiplier method.
Ratios & Stats
Up/Down Ratio Daily/Weekly Lookback: Sets the lookback period for calculating the sum of up volume and down volume for the ratio.
Ratio Calculation Method:
Close vs. Open: Defines an "up volume" bar as one where the close is higher than the open.
Close vs. Previous Close (Default): Defines an "up volume" bar as one where the close is higher than the previous bar's close. This is a common standard.
Up Ratio Arrow Threshold: If the U/D Ratio exceeds this value, a green "up" arrow will appear.
Show Up Ratio Arrow: Toggles the visibility of the green "up" arrow.
Down Ratio Arrow Threshold: If the U/D Ratio falls below this value, a red "down" arrow will appear.
Show Down Ratio Arrow: Toggles the visibility of the red "down" arrow.
[Mad]Triple Bollinger Bands ForecastTriple Bollinger Bands Forecast (BBx3+F)
This open-source indicator is an advanced version of the classic Bollinger Bands, designed to provide a more comprehensive and forward-looking view of market volatility and potential price levels.
It plots three distinct sets of Bollinger Bands and projects them into the future based on statistical calculations.
How It Is Built and Key Features
Triple Bollinger Bands: Instead of a single set of bands, this indicator plots three. All three share the same central basis line (a Simple Moving Average), but each has a different standard deviation multiplier. This creates three distinct volatility zones for analyzing price deviation from its mean.
Multi-Timeframe (MTF) Capability: The indicator can calculate and display Bollinger Bands from a higher timeframe (e.g., showing daily bands on a 4-hour chart). This allows for contextualizing price action within the volatility structure of a more significant trend.
(Lower HTF selection will result in script-crash!)
Future Forecasting: This is the indicator's main feature. It projects the calculated Bollinger Bands up to 8 bars into the future. This forecast is a recalculation of the Simple Moving Average and Standard Deviation based on a projected future source price.
Selectable Forecast Methods: The mathematical model for estimating the future source price can be selected:
Flat: A model that uses the most recent closing price as the price for all future bars in the calculation window.
Linreg (Linear Regression): A model that calculates a linear regression trend on the last few bars and projects it forward to estimate the future source price.
Efficient Drawing with Polylines: The future projections are drawn on the chart using Pine Script's polyline object. This is an efficient method that draws the forecast data only on the last bar, which avoids repainting issues.
Differences from a Classical Bollinger Bands Indicator
Band Count: A classical indicator shows one set of bands. This indicator plots three sets for a multi-layered view of volatility.
Perspective: Classical Bollinger Bands are purely historical. This indicator is both historical and forward-looking .
Forecasting: The classic version has no forecasting capability. This indicator projects the bands into the future .
Timeframe: The classic version works only on the current timeframe. This indicator has full Multi-Timeframe (MTF) support .
The Mathematics Behind the Future Predictions
The core challenge in forecasting Bollinger Bands is that a future band value depends on future prices, which are unknown. This indicator solves this by simulating a future price series. Here is the step-by-step logic:
Forecast the Source Price for the Next Bar
First, the indicator estimates what the price will be on the next bar.
Flat Method: The forecasted price is the current bar's closing price.
Price_forecast = close
Linreg Method: A linear regression is calculated on the last few bars and extrapolated one step forward.
Price_forecast = ta.linreg(close, linreglen, 1)
Calculate the Future SMA (Basis)
To calculate the Simple Moving Average for the next bar, a new data window is simulated. This window includes the new forecasted price and drops the oldest historical price. For a 1-bar forecast, the calculation is:
SMA_future = (Price_forecast + close + close + ... + close ) / length
Calculate the Future Standard Deviation
Similarly, the standard deviation for the next bar is calculated over this same simulated window of prices, using the new SMA_future as its mean.
// 1. Calculate the sum of squared differences from the new mean
d_f = Price_forecast - SMA_future
d_0 = close - SMA_future
// ... and so on for the rest of the window's prices
SumOfSquares = (d_f)^2 + (d_0)^2 + ... + (d_length-2)^2
// 2. Calculate future variance and then the standard deviation
Var_future = SumOfSquares / length
StDev_future = sqrt(Var_future)
Extending the Forecast (2 to 8 Bars)
For forecasts further into the future (e.g., 2 bars), the script uses the same single Price_forecast for all future steps in the calculation. For a 2-bar forecast, the simulated window effectively contains the forecasted price twice, while dropping the two oldest historical prices. This provides a statistically-grounded projection of where the Bollinger Bands are likely to form.
Usage as a Forecast Extension
This indicator's functionality is designed to be modular. It can be used in conjunction with as example Mad Triple Bollinger Bands MTF script to separate the rendering of historical data from the forward-looking forecast.
Configuration for Combined Use:
Add both the Mad Triple Bollinger Bands MTF and this Triple Bollinger Bands Forecast indicator to your chart.
Open the Settings for this indicator (BBx3+F).
In the 'General Settings' tab, disable the Activate Plotting option.
To ensure data consistency, the Bollinger Length, Multipliers, and Higher Timeframe settings should be identical across both indicators.
This configuration prevents the rendering of duplicate historical bands. The Mad Triple Bollinger Bands MTF script will be responsible for visualizing the historical and current bands, while this script will overlay only the forward-projected polyline data.
MirPapa_Handler_HTFLibrary "MirPapa_Handler_HTF"
High Time Frame Handler Library:
Provides utilities for working with High Time Frame (HTF) and chart (LTF) conversions and data retrieval.
IsChartTFcomparisonHTF(_chartTf, _htfTf)
IsChartTFcomparisonHTF
@description
Determine whether the given High Time Frame (HTF) is greater than or equal to the current chart timeframe.
Parameters:
_chartTf (string) : The current chart’s timeframe string (examples: "5", "15", "1D").
_htfTf (string) : The High Time Frame string to compare (examples: "60", "1D").
@return
Returns true if HTF minutes ≥ chart minutes, false otherwise or na if conversion fails.
GetHTFrevised(_tf, _case)
GetHTFrevised
@description
Retrieve a specific bar value from a Higher Time Frame (HTF) series.
Supports current and historical OHLC values, based on a case identifier.
Parameters:
_tf (string) : The target HTF string (examples: "60", "1D").
_case (string) : A case string determining which OHLC value and bar offset to request:
"b" → HTF bar_index
"o" → HTF open
"h" → HTF high
"l" → HTF low
"c" → HTF close
"o1" → HTF open one bar ago
"h1" → HTF high one bar ago
"l1" → HTF low one bar ago
"c1" → HTF close one bar ago
… up to "o5", "h5", "l5", "c5" for five bars ago.
@return
Returns the requested HTF value or na if _case does not match any condition.
GetHTFfromLabel(_label)
GetHTFfromLabel
@description
Convert a Korean HTF label into a Pine Script-recognizable timeframe string.
Examples:
"5분" → "5"
"1시간" → "60"
"일봉" → "1D"
"주봉" → "1W"
"월봉" → "1M"
"연봉" → "12M"
Parameters:
_label (string) : The Korean HTF label string (examples: "5분", "1시간", "일봉").
@return
Returns the Pine Script timeframe string corresponding to the label, or "1W" if no match is found.
GetHTFoffsetToLTFoffset(_offset, _chartTf, _htfTf)
GetHTFoffsetToLTFoffset
@description
Adjust an HTF bar index and offset so that it aligns with the current chart’s bar index.
Useful for retrieving historical HTF data on an LTF chart.
Parameters:
_offset (int) : The HTF bar offset (0 means current HTF bar, 1 means one bar ago, etc.).
_chartTf (string) : The current chart’s timeframe string (examples: "5", "15", "1D").
_htfTf (string) : The High Time Frame string to align (examples: "60", "1D").
@return
Returns the corresponding LTF bar index after applying HTF offset. If result is negative, returns 0.
volume profile ranking indicator📌 Introduction
This script implements a volume profile ranking indicato for TradingView. It is designed to visualize the distribution of traded volume over price levels within a defined historical window. Unlike TradingView’s built-in Volume Profile, this script gives full customization of the profile drawing logic, binning, color gradient, and the ability to anchor the profile to a specific date.
⚙️ How It Works (Logic)
1. Inputs
➤POC Lookback Days (lookback): Defines how many bars (days) to look back from a selected point to calculate the volume distribution.
➤Bin Count (bin_count): Determines how many price bins (horizontal levels) the price range will be divided into.
➤Use Custom Lookback Date (useCustomDate): Enables/disables manually selecting a backtest start date.
➤Custom Lookback Date (customDate): When enabled, the profile will calculate volume based on this date instead of the most recent bar.
2. Target Bar Determination
➤If a custom date is selected, the script searches for the bar closest to that date within 1000 bars.
➤If not, it defaults to the latest bar (bar_index).
➤The profile is drawn only when the current bar is close to the target bar (within ±2 bars), to avoid unnecessary recalculations and performance issues.
3. Volume Binning
➤The price range over the lookback window is divided into bin_count segments.
➤For each bar within the lookback window, its volume is added to the appropriate bin based on price.
➤If the price falls outside the expected range, it is clamped to the first or last bin.
4. Ranking and Sorting
➤A bubble sort ranks each bin by total volume.
➤The most active bin (POC, or Point of Control) is highlighted with a thicker bar.
5. Rendering
➤Horizontal bars (line.new) represent volume intensity in each price bin.
➤Each bar is color-coded by volume heat: more volume = more intense color.
➤Labels (label.new) show:
➤Total volume
➤Rank
➤Percentage of total volume
➤Price range of the bin
🧑💻 How to Use
1. Add the Script to Your Chart
➤Copy the code into TradingView’s Pine Script editor and add it to your chart.
2. Set Lookback Period
➤Default is 252 bars (about one year for daily charts), but can be changed via the input.
3. (Optional) Use Custom Date
●Toggle "Use Custom Lookback Date" to true.
➤Pick a date in the "Custom Lookback Date" input to anchor the profile.
4. Analyze the Volume Distribution
➤The longest (thickest) red/orange bar represents the Point of Control (POC) — the price with the most volume traded.
➤Other bars show volume distribution across price.
➤Labels display useful metrics to evaluate areas of high/low interest.
✅ Features
🔶 Customizable anchor point (custom date).
🔶Adjustable bin count and lookback length.
🔶 Clear visualization with heatmap coloring.
🔶 Lightweight and performance-optimized (especially with the shouldDrawProfile filter)
Enhanced Volume Profile█ OVERVIEW
The Enhanced Volume Profile (EVP) is an indicator designed to plot a volume profile on the chart based on either the visible chart range or a fixed lookback period. The script helps analyze the distribution of volume at different price levels over time, providing insights into areas of high trading activity and potential support/resistance zones.
█ KEY FEATURES
1. Visible Chart Range vs. Fixed Lookback Depth
Visible Chart Range
- Default analysis mode
- Calculates profile based on visible portion of the chart
- Dynamically updates with chart view changes
Fixed Lookback Depth
- Optional alternative to visible range
- Uses specified number of bars (10-3000)
- Provides consistent analysis depth
- Independent of chart view
2. Custom Resolution
Auto-Resolution Mode
Automatically selects timeframes based on chart's current timeframe:
≤ 1 minute: Uses 1-minute resolution
≤ 5 minutes: Uses 1-minute resolution
≤ 15 minutes: Uses 5-minute resolution
≤ 1 hour: Uses 5-minute resolution
≤ 4 hours: Uses 15-minute resolution
≤ 12 hours: Uses 15-minute resolution
≤ 1 day: Uses 1-hour resolution
≤ 3 days: Uses 2-hours resolution
≤ 1 week: Uses 4-hours resolution
Custom Resolution Override
Optional override of auto-resolution system
Provides control over data granularity
Must be lower than or equal to chart's timeframe
Falls back to auto-resolution if validation fails
3. Volume Profile Resolution
Adjustable number of points (10-400)
Controls profile granularity
Higher resolution provides more detail
Balance between precision and performance
4. Point of Control (PoC)
Identifies price level with highest traded volume
Optional display with customizable appearance
Adjustable line thickness (1-30)
Configurable color
5. Value Area (VA)
Shows price range of majority trading volume
Adjustable coverage (5-95%), default is 68%
Customizable boundary lines
Configurable lines color and thickness (1-20)
█ INPUT PARAMETERS
Lookback Settings
Use Visible Chart Range
- Default: true
- Calculates profile based on visible bars
- Ideal for focused analysis
Fixed Lookback Bars
- Range: 10-3000
- Default: 200
- Used when visible range is disabled
Resolution Settings
Enable Custom Resolution
- Default: false
- Overrides auto-resolution
Custom Resolution
- Default: 1-minute
- Changes automatically when "Enable Custom Resolution" is disabled
Volume Profile Appearance
Profile Resolution
- Range: 10-400
- Default: 200
- Controls detail level
Profile Width Scale
- Range: 1-50
- Default: 15
- Adjusts profile width
Right Offset
- Range: 0-500
- Default: 20
- Controls spacing from price bars
Profile Fill Color
- Default: #5D606B (70% transparency)
Point of Control Settings
Show Point of Control
- Default: true
- Toggles PoC visibility
PoC Line Thickness
- Range: 1-30
- Default: 1
PoC Line Color
- Default: Red
Value Area Settings
Show Value Area
- Default: true
- Toggles VA lines
Value Area Coverage
- Range: 5-95%
- Default: 68%
Value Area Line Color
- Default: Blue
Value Area Line Thickness
- Range: 1-20
- Default: 1
█ TECHNICAL IMPLEMENTATION DETAILS
Exceeding Bars Management
The script dynamically adjusts the number of bars used in the volume profile calculation based on the selected timeframe and the maximum allowed bars (max_bars_back).
If the total number of bars exceeds the predefined threshold (6000 bars), the script reduces the lookback period (lookback_bars) by trimming some of the historical data, ensuring the chart does not become overloaded with data.
The adjustment is made based on the ratio of bars per candle (bars_per_candle), ensuring that the volume profile remains computationally efficient while maintaining its relevance.
█ EXAMPLE USE CASES
1. Visible Range Mode
For analyzing a recent trend and focusing on only the visible part of the chart, enabling the "Use Visible Chart Range" option calculates the profile based on the current view, without considering historical data outside the visible area.
2. Fixed Lookback Depth
For analyzing a specific period in the past (e.g., the last 200 bars), disabling the visible range and setting a fixed lookback depth of 200 bars ensures the profile always considers the last 200 bars, regardless of the visible range.
3. Custom Resolution
If there’s a need for greater control over the timeframe used for volume profile calculations (e.g., using a 5-minute resolution on a 15-minute chart), enabling custom resolution and setting the desired timeframe provides this control.
HAPPY TRADING ✌️
Price Imbalance as Consecutive Levels of AveragesOverview
The Price Imbalance as Consecutive Levels of Averages indicator is an advanced technical analysis tool designed to identify and visualize price imbalances in financial markets. Unlike traditional moving average (MA) indicators that update continuously with each new price bar, this indicator employs moving averages calculated over consecutive, non-overlapping historical windows. This unique approach leverages comparative historical data to provide deeper insights into trend strength and potential reversals, offering traders a more nuanced understanding of market dynamics and reducing the likelihood of false signals or fakeouts.
Key Features
Consecutive Rolling Moving Averages: Utilizes three distinct simple moving averages (SMAs) calculated over consecutive, non-overlapping windows to capture different historical segments of price data.
Dynamic Color-Coded Visualization: SMA lines change color and style based on the relationship between the averages, highlighting both extreme and normal market conditions.
Median and Secondary Median Lines: Provides additional layers of price distribution insight during normal trend conditions through the plotting of primary and secondary median lines.
Fakeout Prevention: Filters out short-term volatility and sharp price movements by requiring consistent historical alignment of multiple moving averages.
Customizable Parameters: Offers flexibility to adjust SMA window lengths and line extensions to align with various trading strategies and timeframes.
Real-Time Updates with Historical Context: Continuously recalculates and updates SMA lines based on comparative historical windows, ensuring that the indicator reflects both current and past market conditions.
Inputs & Settings
Rolling Window Lengths:
Window 1 Length (Most Recent) Bars: Number of bars used to calculate the most recent SMA. (Default: 5, Range: 2–300)
Window 2 Length (Preceding) Bars: Number of bars for the second SMA, shifted by Window 1. (Default: 8, Range: 2–300)
Window 3 Length (Third Rolling) Bars: Number of bars for the third SMA, shifted by the combined lengths of Window 1 and Window 2. (Default: 13, Range: 2–300)
Horizontal Line Extension:
Horizontal Line Extension (Bars): Determines how far each SMA line extends horizontally on the chart. (Default: 10 bars, Range: 1–100)
Functionality and Theory
1. Calculating Consecutive Simple Moving Averages (SMAs):
The indicator calculates three SMAs, each based on distinct and consecutive historical windows of price data. This approach contrasts with traditional MAs that continuously update with each new price bar, offering a static view of past trends rather than an ongoing one.
Mean1 (SMA1): Calculated over the most recent Window 1 Length bars. Represents the short-term trend.
Mean1=∑i=1N1CloseiN1
Mean1=N1∑i=1N1Closei
Where N1N1 is the length of Window 1.
Mean2 (SMA2): Calculated over the preceding Window 2 Length bars, shifted back by Window 1 Length bars. Represents the medium-term trend.
\text{Mean2} = \frac{\sum_{i=1}^{N_2} \text{Close}_{i + N_1}}}{N_2}
Where N2N2 is the length of Window 2.
Mean3 (SMA3): Calculated over the third rolling Window 3 Length bars, shifted back by the combined lengths of Window 1 and Window 2 bars. Represents the long-term trend.
\text{Mean3} = \frac{\sum_{i=1}^{N_3} \text{Close}_{i + N_1 + N_2}}}{N_3}
Where N3N3 is the length of Window 3.
2. Determining Market Conditions:
The relationship between the three SMAs categorizes the market condition into either extreme or normal states, enabling traders to quickly assess trend strength and potential reversals.
Extreme Bullish:
Mean3Mean2>Mean1
Mean3>Mean2>Mean1
Indicates a strong and sustained downward trend. SMA lines are colored purple and styled as dashed lines.
Normal Bullish:
Mean1>Mean2andnot in extreme bullish condition
Mean1>Mean2andnot in extreme bullish condition
Indicates a standard upward trend. SMA lines are colored green and styled as solid lines.
Normal Bearish:
Mean1Mean2>Mean1
Mean3>Mean2>Mean1
Normal Bullish:
Mean1>Mean2andnot in Extreme Bullish
Mean1>Mean2andnot in Extreme Bullish
Normal Bearish:
Mean1 Mean2 > Mean3
Visualization: All three SMAs are displayed as gold dashed lines.
Median Lines: Not displayed to maintain chart clarity.
Interpretation: Indicates a strong and sustained upward trend. Traders may consider entering long positions, confident in the trend's strength without the distraction of additional lines.
2. Normal Bullish Condition:
SMAs Alignment: Mean1 > Mean2 (not in extreme condition)
Visualization: Mean1 and Mean2 are green solid lines; Mean3 is gray.
Median Lines: A thin blue dotted median line is plotted between Mean1 and Mean2, with two additional thin blue dashed lines as secondary medians.
Interpretation: Confirms an upward trend while providing deeper insights into price distribution. Traders can use the median and secondary median lines to identify optimal entry points and manage risk more effectively.
3. Extreme Bearish Condition:
SMAs Alignment: Mean3 > Mean2 > Mean1
Visualization: All three SMAs are displayed as purple dashed lines.
Median Lines: Not displayed to maintain chart clarity.
Interpretation: Indicates a strong and sustained downward trend. Traders may consider entering short positions, confident in the trend's strength without the distraction of additional lines.
4. Normal Bearish Condition:
SMAs Alignment: Mean1 < Mean2 (not in extreme condition)
Visualization: Mean1 and Mean2 are red solid lines; Mean3 is gray.
Median Lines: A thin blue dotted median line is plotted between Mean1 and Mean2, with two additional thin blue dashed lines as secondary medians.
Interpretation: Confirms a downward trend while providing deeper insights into price distribution. Traders can use the median and secondary median lines to identify optimal entry points and manage risk more effectively.
Customization and Flexibility
The Price Imbalance as Consecutive Levels of Averages indicator is highly adaptable, allowing traders to tailor it to their specific trading styles and market conditions through adjustable parameters:
SMA Window Lengths: Modify the lengths of Window 1, Window 2, and Window 3 to capture different historical trend segments, whether focusing on short-term fluctuations or long-term movements.
Line Extension: Adjust the horizontal extension of SMA and median lines to align with different trading horizons and chart preferences.
Color and Style Preferences: While default colors and styles are optimized for clarity, traders can customize these elements to match their personal chart aesthetics and enhance visual differentiation.
This flexibility ensures that the indicator remains versatile and applicable across various markets, asset classes, and trading strategies, providing valuable insights tailored to individual trading needs.
Conclusion
The Price Imbalance as Consecutive Levels of Averages indicator offers a comprehensive and innovative approach to analyzing price trends and imbalances within financial markets. By utilizing three consecutive, non-overlapping SMAs and incorporating median lines during normal trend conditions, the indicator provides clear and actionable insights into trend strength and price distribution. Its unique design leverages comparative historical data, distinguishing it from traditional moving averages and enhancing its utility in identifying genuine market movements while minimizing false signals. This dynamic and customizable tool empowers traders to refine their technical analysis, optimize their trading strategies, and navigate the markets with greater confidence and precision.
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
Dix$on's Weighted Volume FlowDixson's Weighted Volume Flow
Dixson's Weighted Volume Flow is a technical indicator designed to analyze and visualize the distribution of buy and sell volume within a given timeframe. It dynamically calculates the proportional allocation of volume based on price action within each bar, providing insights into market sentiment and activity. This indicator displays horizontal volume bars in a separate pane and annotates them with precise volume values.
How It Works
1. Volume Allocation:
- The indicator calculates buy and sell volume using the following formulas:
- Buy Volume = (Close - Low) / (High - Low) Total Volume
- Sell Volume = (High - Close) / (High - Low) Total Volume
- These formulas allocate volume proportionally based on the bar's price range, attributing more volume to buying or selling depending on the relationship between the close, high, and low prices.
2. Dynamic Scaling:
- The buy and sell volumes are scaled relative to their combined total for the period.
- The resulting values determine the length of the horizontal bars, providing a comparative view of buy and sell activity.
3. Bar Visualization:
- Buy Volume Bars: Displayed as green horizontal bars.
- Sell Volume Bars: Displayed as red horizontal bars.
- The lengths of the bars represent the dominance of buy or sell volume, scaled dynamically within the pane.
4. Labels:
- Each bar is annotated with a label showing its calculated buy or sell volume value.
5. Timeframe Adjustment:
- The indicator uses the request.security() function to fetch data from the selected timeframe, allowing users to customize their analysis for intraday, daily, or longer-term trends.
6. Customization Options:
- Enable or disable the indicator using a toggle.
- Adjust colors for the buy/sell bars and text labels to suit your chart theme.
How to Use It
1. Enable the Indicator:
- Activate the indicator using the "Enable/Disable" toggle in the settings.
2. Select a Timeframe:
- Choose the timeframe for analysis (e.g., 1-minute, 1-hour, daily). The indicator fetches volume data specific to the selected timeframe.
3. Interpret the Visualization:
- Compare Bar Lengths:
- Longer buy volume bars (green) indicate stronger buying activity.
- Longer sell volume bars (red) suggest dominant selling pressure.
- Labels:
- Use the labels to view the exact buy and sell volume values for precise analysis.
4. Combine with Other Tools:
- Use the indicator alongside price action analysis, support/resistance levels, or trend indicators to confirm market sentiment and detect potential reversals.
5. Monitor Imbalances:
- Significant disparities between buy and sell volume can signal shifts in market sentiment, such as the end of a trend or the start of a breakout.
Practical Applications
- Trend Confirmation:
- Align the dominance of buy or sell volume with price trends to confirm market direction.
- Reversal Signals:
- Watch for volume imbalances or a sudden shift in the dominance of buy or sell volume to identify potential reversals.
- High-Activity Zones:
- Identify areas with increased volume to anticipate significant price movements or key support/resistance interactions.
Dixson's Weighted Volume Flow provides a clear and systematic way to analyze market activity by visualizing the dynamics of buy and sell volume. It is particularly useful for traders looking to enhance their understanding of volume-based sentiment and its impact on price movements.
Wick/Tail Candle MeasurementsThis indicator runs on trading view. It was programmed with pine script v5.
Once the indicator is running you can scroll your chart to any year or date on the chart, then for the input select the date your interested in knowing the length of the tails and wicks from a bar and their lengths are measured in points.
To move the measurement, you can select the vertical bar built into the indicator AFTER clicking the green label and moving it around using the vertical bar *only*. You must click the vertical bar in the middle of the label to move the indicator calculation to another bar. You can also just select the date using the input as mentioned. This indicator calculates just one bar at a time.
measurements are from bar OPEN to bar HIGH for measured WICKS regardless of the bar being long or short and from bar OPEN to bar LOW for measured TAILS also regardless of the bar being long or short.
This indicator calculates tails and wicks including the bar body in the calculations. Basically showing you how much the market moved in a certain direction for the entire duration of that Doji candle.
Its designed to measure completed bars on the daily futures charts. (Dow Jones, ES&P500, Nasdaq, Russell 2000, etc) Although it may work well on other markets. The indicator could easily be tweaked in order to work well with other markets. It is not designed for forex markets currently.
Bull Bear Power With EMA FilterDescription of Indicator:
This Pine Script indicator colors price bars based on the open price in relation to custom moving averages (EMA/SMA), Bull/Bear Power (BBPower), and an optional VWAP filter. The bar colors help identify bullish and bearish conditions with added visual cues for price positioning relative to VWAP.
Key Features:
Customizable Moving Averages (EMA/SMA):
The user can select between EMA or SMA for both short-term and long-term moving averages.
Default moving averages are set to 5 (short-term) and 9 (long-term) but can be adjusted by the user.
Bullish Condition (Blue or Purple Bars):
A bar is colored blue if the following conditions are met:
The open price is above both the short-term and long-term moving averages.
The short-term moving average (MA 1) is above the long-term moving average (MA 2).
BBPower (open price minus the 13-period EMA) is positive, indicating bullish strength.
If the VWAP filter is enabled and the price opens below VWAP, the bullish bars will turn purple.
Bearish Condition (Yellow or Orange Bars):
A bar is colored yellow if the following conditions are met:
The open price is below both the short-term and long-term moving averages.
The short-term moving average (MA 1) is below the long-term moving average (MA 2).
BBPower is negative or zero, indicating bearish market conditions.
If the VWAP filter is enabled and the price opens above VWAP, the bearish bars will turn orange.
VWAP Filter (Optional):
An optional filter allows the user to add VWAP (Volume-Weighted Average Price) to the bar coloring logic.
When the VWAP filter is enabled, it provides additional information about price positioning relative to VWAP, turning bullish bars purple and bearish bars orange depending on whether the price opens above or below VWAP.
Usage:
Bullish Trend: Look for blue or purple bars to identify potential bullish momentum.
Bearish Trend: Look for yellow or orange bars to spot bearish conditions in the market.
The indicator allows users to customize the length and type of moving averages (EMA or SMA), as well as decide whether to apply the VWAP filter.
This indicator provides traders with clear visual signals to quickly assess the strength of bullish or bearish conditions based on the price's position relative to custom moving averages, BBPower, and VWAP, helping with trend identification and potential trade setups.
Trend and RSI Bias FusionTrend and RSI Bias Fusion Indicator
This is my first ever indicator. I created this indicator for myself. I was inspired by the indicators created by Bjorgum, Duyck and QuantTherapy and decided to create multiple indicators that either work well combined with their indicators or something new that applies some of their indicator concepts. I decided to share this because I believe in learning and earing together as a community. I will later share the rest of the indicators I have created. This is my first time ever sharing any indicator so if you guys have any questions or suggestions write them.
Overview
The "Trend and RSI Bias Fusion" indicator is a versatile tool designed to help traders identify key market trends, potential reversals, momentum shifts, and RSI-based pullbacks. This indicator fuses trend analysis and RSI bias into a single, comprehensive visual, making it easier to make informed trading decisions across various timeframes and market conditions.
Features
Dual Timeframe Analysis: Combines trend analysis on a higher timeframe (e.g., Daily) with RSI analysis on a lower timeframe (e.g., 4-Hour), providing a more granular view of market conditions. You can, however, choose any timeframe you want for instance 12hr with trend and 2hr RSI analysis.
Trend and Momentum Visualization: The indicator uses Exponential Moving Averages (EMAs) to determine trend direction and colors the chart background to reflect bullish or bearish trends, along with momentum strength.
RSI Bias Detection: Automatically identifies overbought and oversold conditions using the RSI, providing a clear indication of potential market reversals or continuations.
Color-Coded Bars: Optionally color codes bars based on either trend direction or RSI bias, giving you a quick visual cue of the market's state.
Reversal Markers: Displays trend reversal markers on the chart when the short-term EMA crosses over or under the long-term EMA.
Calculation Details
Exponential Moving Averages (EMAs): The indicator calculates short-term and long-term EMAs using the closing prices.
The crossover between these EMAs is used to determine the trend direction:
Short-Term EMA: Typically a 14-period EMA.
Long-Term EMA: Typically a 50-period EMA.
Momentum: Calculated using the RSI and then centered around zero by subtracting 50. This allows the indicator to distinguish between positive and negative momentum.
RSI Bias: The RSI is calculated on a lower timeframe to detect overbought (above 60) and oversold (below 40) conditions, which are used to determine the bias:
RSI Above 60: Indicates potential overbought conditions (bearish bias).
RSI Below 40: Indicates potential oversold conditions (bullish bias).
How to Use the Indicator
Select Your Timeframes: Choose your preferred trend timeframe (e.g., Daily) and RSI timeframe (e.g., 4-2 Hour) in the indicator settings. These should match your trading strategy and the asset class you're analyzing.
Interpret Trend and Momentum
Background Color: The background color reflects the current trend direction:
Green/Lime: Uptrend, with lime indicating positive momentum.
Red/Maroon: Downtrend, with maroon indicating positive momentum within a downtrend.
Momentum Histogram: The histogram plot shows momentum, color-coded by the trend. A histogram above zero with green/lime indicates bullish momentum, while below zero with red/maroon indicates bearish momentum.
Image above: Both RSI and Trend are set to daily, uses RSI bar color
Read RSI Bias:
The RSI bias line helps identify the current market state relative to overbought or oversold levels. The RSI value is plotted on the chart, with lines at 60 and 40 to mark these levels.
When the RSI crosses above 60, it suggests a bearish bias; crossing below 40 suggests a bullish bias.
Use Reversal Markers: The indicator places small circles on the chart at points where the short-term EMA crosses the long-term EMA, signaling potential trend reversals.
Bar Color Customization:
You can choose to color the bars based on either the trend or the RSI bias in the indicator settings. In the Images below I have changed the colors to fit my personal style , Blue for uptrend and Pink for downtrend:
Trend-Based: Bars will reflect the trend direction (green for uptrend or in this case blue, red for downtrend or in this case pink).
RSI-Based: Bars will reflect RSI conditions (yellow for overbought, maroon for oversold).
Image above: RSI is set to 4hr and Trend is set to daily, uses RSI bar color
Image above: RSI is set to 4hr and Trend is set to daily, uses Trend bar color
Image above: Both RSI and Trend are set to daily, uses RSI bar color
Image above: Both RSI and Trend are set to daily, uses Trend bar color
Image above: Both RSI and Trend are set to daily, without bar color
Image above: Both RSI and Trend are set to daily, how it looks on a clean chart
Example Use Case Swing Traders:
For instance, if you're trading a 4-hour chart of USDCHF:
Set the trend timeframe to Daily and the RSI timeframe to 4-Hour.
Watch for background color shifts and reversal markers to determine trend direction.
Use RSI bias to time your entries and exits, especially around overbought/oversold levels.
Enable bar coloring to quickly see when conditions favor either trend continuation or reversal.
This indicator is particularly effective for swing traders and those who want to align their trades with higher timeframe trends while using momentum and RSI for entry and exit signals.
For Day Traders
Timeframe Selection:
Trend Timeframe: Set to a higher intraday timeframe such as the 1 or 2 Hour chart.
RSI Timeframe: Set to a shorter timeframe like 15-10 Minutes or 5-Minutes to capture finer details of intraday momentum shifts.
Using the Indicator:
Trend Identification: Day traders can use the background color to quickly identify whether the market is in a bullish or bearish trend on the 1-Hour chart. A green background suggests looking for long opportunities, while a red background suggests short opportunities.
Momentum Analysis: The histogram can help day traders gauge the strength of the current trend. For example, if the histogram is green and above zero, the trader may consider buying pullbacks within the trend.
RSI Bias: Monitor RSI levels on the lower timeframe (e.g., 15-Minutes). If the RSI crosses below 40, it indicates an oversold condition, potentially signaling a buying opportunity, especially if it aligns with a bullish trend on the higher timeframe.
Trade Execution:
Look for entries when the RSI shows a reversal or pullback in the direction of the higher timeframe trend.
Use the trend reversal markers to confirm potential intraday reversals, adding extra confidence to trade setups.
For Scalpers
Timeframe Selection:
Trend Timeframe: Set to a short intraday timeframe like 15-Minutes or 5-Minutes.
RSI Timeframe: Use an even shorter timeframe, such as 1-Minute, to capture rapid price movements.
Final Notes:
The "Trend and RSI Bias Fusion" indicator is a powerful tool that combines trend analysis, momentum assessment, and RSI insights into one cohesive package. By integrating these different aspects, the indicator helps traders navigate complex market environments with greater clarity and confidence. Customize the settings to fit your specific trading style and market and use it to stay ahead of market trends and potential reversals.
My Scripts/Indicators/Ideas /Systems that I share are only for educational purposes!
Brooks Always In [KintsugiTrading]Brooks Always In
Overview:
The "Brooks Always In Indicator" by KintsugiTrading is a tool designed for traders who follow price action methodologies inspired by Al Brooks. This indicator identifies key bar patterns and breakouts, plots an Exponential Moving Average (EMA), and highlights consecutive bullish and bearish bars. It is intended to assist traders in making informed decisions based on price action dynamics.
Features:
Consecutive Bar Patterns:
Identifies and highlights consecutive bullish and bearish bars.
Differentiates between bars that are above/below the EMA and those that are not.
Customizable EMA:
Option to display an Exponential Moving Average (EMA) with user-defined length and offset.
The EMA can be smoothed using various methods such as SMA, EMA, SMMA (RMA), WMA, and VWMA.
Breakout Patterns:
Recognizes bullish and bearish breakout bars and outside bars.
Tracks inside bars and prior bar conditions to better understand the market context.
Customizable Display:
Users can display or hide the EMA, consecutive bar patterns, and consecutive bars relative to the moving average.
How to Use:
Customize Settings:
First, I like to navigate to the top right corner of the chart (bolt icon), and change both the bull and bear body color to match the background (white/black) - this helps the user visualize the indicator far better.
Next, Toggle to display EMA, consecutive bar patterns, and consecutive bars relative to the moving average using the provided input options.
Adjust the EMA length, source, and offset as per your trading strategy.
Select the smoothing method and length for the EMA if desired.
Analyze Key Patterns:
Observe the highlighted bars on the chart to identify consecutive bullish and bearish patterns.
Use the plotted EMA to gauge the general trend and analyze the relationship between price bars and the moving average.
Informed Decision Making:
Utilize the identified bar patterns and breakouts to make informed trading decisions, such as identifying potential entry and exit points based on price action dynamics.
Good luck with your trading!
HTF Descending TriangleHTF Descending Triangle aims at detecting descending triangles using higher time frame data, without repainting nor misalignment issues.
Descending triangles are defined by a falling upper trend line and an horizontal lower trend line. It is a chart pattern used in technical analysis to predict the continuation of a downtrend.
This indicator can be useful if you, like me, believe that higher time frames can offer a broader perspective and provide clearer signals, smoothing out market noise and showing longer-term trends.
You can change the indicator settings as you see fit to tighten or loosen the detection, and achieve the best results for your use case.
Features
It draws the detected descending triangle on the chart.
It supports alerting when a detection occurs.
It allows for setting the higher time frame to run the detection on.
It allows for setting the minimum number of consecutive valid higher time frame bars to fit the pattern criteria.
It allows for setting a low factor detection criteria to apply on higher time frame bars low as a proportion of the distance between the reference bar low and open/close.
It allows for turning on an adjustment of the triangle using highest/lowest values within valid higher time frame bars.
Settings
Higher Time Frame dropdown: Selects higher time frame to run the detection on. It must be higher than, and a multiple of, the chart's timeframe.
Valid Bars Minimum field: Sets minimum number of consecutive valid higher time frame bars to fit the pattern criteria.
Low Factor checkbox: Turns on/off low factor detection criteria.
Low Factor field: Sets low factor to apply on higher time frame bars low as a proportion of the distance between the reference bar low and open/close.
Adjust Triangle checkbox: Turns on/off triangle adjustment using highest/lowest values within valid higher time frame bars.
Detection Algorithm Notes
The detection algorithm recursively selects a higher time frame bar as reference. Then it looks at the consecutive higher time frame bars (as per the requested number of minimum valid bars) as follows:
High must be lower than previous bar.
Open/close min value must be higher than reference bar low.
When low factor criteria is turned on, low must be lower than reference bar open/close min value minus low factor proportion of the distance between reference bar low and open/close min value.
HTF Ascending TriangleHTF Ascending Triangle aims at detecting ascending triangles using higher time frame data, without repainting nor misalignment issues.
Ascending triangles are defined by an horizontal upper trend line and a rising lower trend line. It is a chart pattern used in technical analysis to predict the continuation of an uptrend.
This indicator can be useful if you, like me, believe that higher time frames can offer a broader perspective and provide clearer signals, smoothing out market noise and showing longer-term trends.
You can change the indicator settings as you see fit to tighten or loosen the detection, and achieve the best results for your use case.
Features
It draws the detected ascending triangle on the chart.
It supports alerting when a detection occurs.
It allows for setting the higher time frame to run the detection on.
It allows for setting the minimum number of consecutive valid higher time frame bars to fit the pattern criteria.
It allows for setting a high factor detection criteria to apply on higher time frame bars high as a proportion of the distance between the reference bar high and open/close.
It allows for turning on an adjustment of the triangle using highest/lowest values within valid higher time frame bars.
Settings
Higher Time Frame dropdown: Selects higher time frame to run the detection on. It must be higher than, and a multiple of, the chart's timeframe.
Valid Bars Minimum field: Sets minimum number of consecutive valid higher time frame bars to fit the pattern criteria.
High Factor checkbox: Turns on/off high factor detection criteria.
High Factor field: Sets high factor to apply on higher time frame bars high as a proportion of the distance between the reference bar high and close/open.
Adjust Triangle checkbox: Turns on/off triangle adjustment using highest/lowest values within valid higher time frame bars.
Detection Algorithm Notes
The detection algorithm recursively selects a higher time frame bar as reference. Then it looks at the consecutive higher time frame bars (as per the requested number of minimum valid bars) as follows:
Low must be higher than previous bar.
Open/close max value must be lower than reference bar high.
When high factor criteria is turned on, high must be higher than reference bar open/close max value plus high factor proportion of the distance between reference bar high and open/close max value.
regressionsLibrary "regressions"
This library computes least square regression models for polynomials of any form for a given data set of x and y values.
fit(X, y, reg_type, degrees)
Takes a list of X and y values and the degrees of the polynomial and returns a least square regression for the given polynomial on the dataset.
Parameters:
X (array) : (float ) X inputs for regression fit.
y (array) : (float ) y outputs for regression fit.
reg_type (string) : (string) The type of regression. If passing value for degrees use reg.type_custom
degrees (array) : (int ) The degrees of the polynomial which will be fit to the data. ex: passing array.from(0, 3) would be a polynomial of form c1x^0 + c2x^3 where c2 and c1 will be coefficients of the best fitting polynomial.
Returns: (regression) returns a regression with the best fitting coefficients for the selecected polynomial
regress(reg, x)
Regress one x input.
Parameters:
reg (regression) : (regression) The fitted regression which the y_pred will be calulated with.
x (float) : (float) The input value cooresponding to the y_pred.
Returns: (float) The best fit y value for the given x input and regression.
predict(reg, X)
Predict a new set of X values with a fitted regression. -1 is one bar ahead of the realtime
Parameters:
reg (regression) : (regression) The fitted regression which the y_pred will be calulated with.
X (array)
Returns: (float ) The best fit y values for the given x input and regression.
generate_points(reg, x, y, left_index, right_index)
Takes a regression object and creates chart points which can be used for plotting visuals like lines and labels.
Parameters:
reg (regression) : (regression) Regression which has been fitted to a data set.
x (array) : (float ) x values which coorispond to passed y values
y (array) : (float ) y values which coorispond to passed x values
left_index (int) : (int) The offset of the bar farthest to the realtime bar should be larger than left_index value.
right_index (int) : (int) The offset of the bar closest to the realtime bar should be less than right_index value.
Returns: (chart.point ) Returns an array of chart points
plot_reg(reg, x, y, left_index, right_index, curved, close, line_color, line_width)
Simple plotting function for regression for more custom plotting use generate_points() to create points then create your own plotting function.
Parameters:
reg (regression) : (regression) Regression which has been fitted to a data set.
x (array)
y (array)
left_index (int) : (int) The offset of the bar farthest to the realtime bar should be larger than left_index value.
right_index (int) : (int) The offset of the bar closest to the realtime bar should be less than right_index value.
curved (bool) : (bool) If the polyline is curved or not.
close (bool) : (bool) If true the polyline will be closed.
line_color (color) : (color) The color of the line.
line_width (int) : (int) The width of the line.
Returns: (polyline) The polyline for the regression.
series_to_list(src, left_index, right_index)
Convert a series to a list. Creates a list of all the cooresponding source values
from left_index to right_index. This should be called at the highest scope for consistency.
Parameters:
src (float) : (float ) The source the list will be comprised of.
left_index (int) : (float ) The left most bar (farthest back historical bar) which the cooresponding source value will be taken for.
right_index (int) : (float ) The right most bar closest to the realtime bar which the cooresponding source value will be taken for.
Returns: (float ) An array of size left_index-right_index
range_list(start, stop, step)
Creates an from the start value to the stop value.
Parameters:
start (int) : (float ) The true y values.
stop (int) : (float ) The predicted y values.
step (int) : (int) Positive integer. The spacing between the values. ex: start=1, stop=6, step=2:
Returns: (float ) An array of size stop-start
regression
Fields:
coeffs (array__float)
degrees (array__float)
type_linear (series__string)
type_quadratic (series__string)
type_cubic (series__string)
type_custom (series__string)
_squared_error (series__float)
X (array__float)
Statistics • Chi Square • P-value • SignificanceThe Statistics • Chi Square • P-value • Significance publication aims to provide a tool for combining different conditions and checking whether the outcome is significant using the Chi-Square Test and P-value.
🔶 USAGE
The basic principle is to compare two or more groups and check the results of a query test, such as asking men and women whether they want to see a romantic or non-romantic movie.
–––––––––––––––––––––––––––––––––––––––––––––
| | ROMANTIC | NON-ROMANTIC | ⬅︎ MOVIE |
–––––––––––––––––––––––––––––––––––––––––––––
| MEN | 2 | 8 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
| WOMEN | 7 | 3 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
|⬆︎ SEX | 10 | 10 | 20 |
–––––––––––––––––––––––––––––––––––––––––––––
We calculate the Chi-Square Formula, which is:
Χ² = Σ ( (Observed Value − Expected Value)² / Expected Value )
In this publication, this is:
chiSquare = 0.
for i = 0 to rows -1
for j = 0 to colums -1
observedValue = aBin.get(i).aFloat.get(j)
expectedValue = math.max(1e-12, aBin.get(i).aFloat.get(colums) * aBin.get(rows).aFloat.get(j) / sumT) //Division by 0 protection
chiSquare += math.pow(observedValue - expectedValue, 2) / expectedValue
Together with the 'Degree of Freedom', which is (rows − 1) × (columns − 1) , the P-value can be calculated.
In this case it is P-value: 0.02462
A P-value lower than 0.05 is considered to be significant. Statistically, women tend to choose a romantic movie more, while men prefer a non-romantic one.
Users have the option to choose a P-value, calculated from a standard table or through a math.ucla.edu - Javascript-based function (see references below).
Note that the population (10 men + 10 women = 20) is small, something to consider.
Either way, this principle is applied in the script, where conditions can be chosen like rsi, close, high, ...
🔹 CONDITION
Conditions are added to the left column ('CONDITION')
For example, previous rsi values (rsi ) between 0-100, divided in separate groups
🔹 CLOSE
Then, the movement of the last close is evaluated
UP when close is higher then previous close (close )
DOWN when close is lower then previous close
EQUAL when close is equal then previous close
It is also possible to use only 2 columns by adding EQUAL to UP or DOWN
UP
DOWN/EQUAL
or
UP/EQUAL
DOWN
In other words, when previous rsi value was between 80 and 90, this resulted in:
19 times a current close higher than previous close
14 times a current close lower than previous close
0 times a current close equal than previous close
However, the P-value tells us it is not statistical significant.
NOTE: Always keep in mind that past behaviour gives no certainty about future behaviour.
A vertical line is drawn at the beginning of the chosen population (max 4990)
Here, the results seem significant.
🔹 GROUPS
It is important to ensure that the groups are formed correctly. All possibilities should be present, and conditions should only be part of 1 group.
In the example above, the two top situations are acceptable; close against close can only be higher, lower or equal.
The two examples at the bottom, however, are very poorly constructed.
Several conditions can be placed in more than 1 group, and some conditions are not integrated into a group. Even if the results are significant, they are useless because of the group formation.
A population count is added as an aid to spot errors in group formation.
In this example, there is a discrepancy between the population and total count due to the absence of a condition.
The results when rsi was between 5-25 are not included, resulting in unreliable results.
🔹 PRACTICAL EXAMPLES
In this example, we have specific groups where the condition only applies to that group.
For example, the condition rsi > 55 and rsi <= 65 isn't true in another group.
Also, every possible rsi value (0 - 100) is present in 1 of the groups.
rsi > 15 and rsi <= 25 28 times UP, 19 times DOWN and 2 times EQUAL. P-value: 0.01171
When looking in detail and examining the area 15-25 RSI, we see this:
The population is now not representative (only checking for RSI between 15-25; all other RSI values are not included), so we can ignore the P-value in this case. It is merely to check in detail. In this case, the RSI values 23 and 24 seem promising.
NOTE: We should check what the close price did without any condition.
If, for example, the close price had risen 100 times out of 100, this would make things very relative.
In this case (at least two conditions need to be present), we set 1 condition at 'always true' and another at 'always false' so we'll get only the close values without any condition:
Changing the population or the conditions will change the P-value.
In the following example, the outcome is evaluated when:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is lower/equal than the close value from 2 bars back
Or:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is equal than the close value from 2 bars back
close value from 1 bar back is lower than the close value from 2 bars back
In both examples, all possibilities of close against close are included in the calculations. close can only by higher, equal or lower than close
Both examples have the results without a condition included (5 = 5 and 5 < 5) so one can compare the direction of current close.
🔶 NOTES
• Always keep in mind that:
Past behaviour gives no certainty about future behaviour.
Everything depends on time, cycles, events, fundamentals, technicals, ...
• This test only works for categorical data (data in categories), such as Gender {Men, Women} or color {Red, Yellow, Green, Blue} etc., but not numerical data such as height or weight. One might argue that such tests shouldn't use rsi, close, ... values.
• Consider what you're measuring
For example rsi of the current bar will always lead to a close higher than the previous close, since this is inherent to the rsi calculations.
• Be careful; often, there are na -values at the beginning of the series, which are not included in the calculations!
• Always keep in mind considering what the close price did without any condition
• The numbers must be large enough. Each entry must be five or more. In other words, it is vital to make the 'population' large enough.
• The code can be developed further, for example, by splitting UP, DOWN in close UP 1-2%, close UP 2-3%, close UP 3-4%, ...
• rsi can be supplemented with stochRSI, MFI, sma, ema, ...
🔶 SETTINGS
🔹 Population
• Choose the population size; in other words, how many bars you want to go back to. If fewer bars are available than set, this will be automatically adjusted.
🔹 Inputs
At least two conditions need to be chosen.
• Users can add up to 11 conditions, where each condition can contain two different conditions.
🔹 RSI
• Length
🔹 Levels
• Set the used levels as desired.
🔹 Levels
• P-value: P-value retrieved using a standard table method or a function.
• Used function, derived from Chi-Square Distribution Function; JavaScript
LogGamma(Z) =>
S = 1
+ 76.18009173 / Z
- 86.50532033 / (Z+1)
+ 24.01409822 / (Z+2)
- 1.231739516 / (Z+3)
+ 0.00120858003 / (Z+4)
- 0.00000536382 / (Z+5)
(Z-.5) * math.log(Z+4.5) - (Z+4.5) + math.log(S * 2.50662827465)
Gcf(float X, A) => // Good for X > A +1
A0=0., B0=1., A1=1., B1=X, AOLD=0., N=0
while (math.abs((A1-AOLD)/A1) > .00001)
AOLD := A1
N += 1
A0 := A1+(N-A)*A0
B0 := B1+(N-A)*B0
A1 := X*A0+N*A1
B1 := X*B0+N*B1
A0 := A0/B1
B0 := B0/B1
A1 := A1/B1
B1 := 1
Prob = math.exp(A * math.log(X) - X - LogGamma(A)) * A1
1 - Prob
Gser(X, A) => // Good for X < A +1
T9 = 1. / A
G = T9
I = 1
while (T9 > G* 0.00001)
T9 := T9 * X / (A + I)
G := G + T9
I += 1
G *= math.exp(A * math.log(X) - X - LogGamma(A))
Gammacdf(x, a) =>
GI = 0.
if (x<=0)
GI := 0
else if (x
Chisqcdf = Gammacdf(Z/2, DF/2)
Chisqcdf := math.round(Chisqcdf * 100000) / 100000
pValue = 1 - Chisqcdf
🔶 REFERENCES
mathsisfun.com, Chi-Square Test
Chi-Square Distribution Function
