Average Daily Range (ADR)This indicator just shows a simple text box with average daily range (in ticks) for the past 20, 40, and 60 days. It also includes the range of the current day, and the % of the different ADR values. Other indicators all plotted lines or had sub-charts and I just wanted a simple text box with the values. Hence, this indicator.
インジケーターとストラテジー
3 Candle AlertThis is a test for integration using a webhook. I am publishing it so I can share it. Ultimately, this is what we want to do:
1. Trade Entry Rules:
Wait until at least the 3rd bar of the day (15 minutes after market open) before entering the first trade.
Order of Priority for Entry:
Look for two consecutive volume bars of the same color (the second bar must have higher volume than the first).
Look for a “price push” beyond the high or low of the day (as determined in the first 15 minutes).
2. Trading Direction:
If the volume bars are RED, I take a Long Position.
If the volume bars are GREEN, I take a Short Position.
BTMM EMA'sThis script is written in Pine Script version 5 for TradingView and is designed to display multiple Exponential Moving Averages (EMAs) on a price chart. Here's a breakdown of its components:
1. Indicator Declaration
indicator(title="Moving Averages", shorttitle="BFX BTMM EMA", overlay=true):
Declares an indicator named "Moving Averages" with a short title "BFX BTMM EMA".
overlay=true means the indicator will be plotted directly on the price chart, not in a separate window.
2. EMA Calculation
The script calculates EMAs for the lengths of 5, 13, 50, 200, and 800 using the ta.ema() function, which applies the exponential moving average to the closing price (close).
pinescript
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ema5 = ta.ema(close, 5)
ema13 = ta.ema(close, 13)
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)
ema800 = ta.ema(close, 800)
3. Plotting EMAs
Each EMA is plotted on the chart using the plot() function with specific colors for visual distinction:
EMA5: Yellow (color.rgb(255, 213, 0))
EMA13: Red (color.rgb(255, 0, 0))
EMA50: Light Blue (color.rgb(111, 183, 242))
EMA200: White (color.rgb(255, 255, 255))
EMA800: Purple (color.rgb(60, 0, 255))
4. Custom Smoothing Function
ma(source, length, type) is a custom function that allows users to select different types of moving averages, such as SMA, EMA, SMMA (RMA), WMA, and VWMA.
pinescript
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ma(source, length, type) =>
switch type
"SMA" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
5. User Inputs
typeMA and smoothingLength are user inputs for selecting the smoothing method and the length of the moving average. These inputs allow customization of the indicator:
typeMA provides options for the smoothing method.
smoothingLength sets the length of the smoothing.
pinescript
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typeMA = input.string(title = "Method", defval = "SMA", options= , group="Smoothing")
smoothingLength = input.int(title = "Length", defval = 5, minval = 1, maxval = 100, group="Smoothing")
Summary:
This script calculates and plots five EMAs on the price chart, providing a visual representation of different time-frame trends. Additionally, it includes a custom function to allow the user to apply other smoothing techniques to the data, offering flexibility in analysis.
Indicateur VIDYA + HULL [Pine v5]Comment utiliser cet indicateur
Ajuster les paramètres selon vos préférences :
1 - Longueur VIDYA : contrôle la période pour le lissage (plus la longueur est grande, plus la courbe sera douce mais réagira moins vite).
2 - Longueur CMO : détermine sur combien de barres le CMO est calculé (influence la réactivité de l’alpha).
3 - Facteur d’amplification : contrôle la sensibilité de la VIDYA au CMO.
4 - Longueur HMA : période pour la Hull Moving Average.
Les signaux d’achat/vente (flèches vertes et rouges) se basent sur le croisement de la HMA et de la VIDYA.
Pensez toujours à tester et valider vos signaux avant de trader en réel.
NG pattern detector - UdayThis pattern detects mostly used candle patterns
bullish engulfing bearish engulfing hammer inverted hammer dragonfly doji and gravestone doji.
also make sure to add alert
Williams %R IntensityOverview
"Williams %R Intensity" is a unique indicator that combines the classic Williams %R with a dynamic intensity-based visualization. This indicator helps traders identify overbought and oversold conditions with enhanced clarity while also predicting potential future crossovers using smoothed slope calculations. It is tailored for traders seeking a more nuanced approach to trend detection and momentum analysis.
Features and How It Works
Core Calculation:
Williams %R : Measures the current closing price relative to the highest high and lowest low over a user-defined length (default: 14).
Exponential Moving Average (EMA) : Smoothens the %R values for better trend tracking (default length: 14).
Overbought/Oversold Zones :
Upper and lower threshold levels are set at -20 (overbought) and -80 (oversold), making it easier to identify extreme conditions.
Intensity Visualization:
The intensity is calculated based on the absolute distance between Williams %R and its EMA.
The closer the value is to extreme levels, the more pronounced the visual intensity, capping at 90% transparency.
Overbought conditions are highlighted in red; oversold conditions in teal.
Crossover Signals:
Bullish Cross: When Williams %R crosses above its EMA in the oversold zone.
Bearish Cross: When Williams %R crosses below its EMA in the overbought zone.
The background color changes (lime for bullish, red for bearish) to highlight these critical moments when enabled via the "Show Cross & Predicted Cross Signal" option.
Future Cross Prediction:
Uses the smoothed slope of %R to estimate future values over a customizable number of steps.
Predicts potential bullish or bearish crosses based on the interaction between the predicted Williams %R and EMA.
Light green and light red background colors indicate predicted bullish and bearish crosses, respectively.
How to Use
Trend Detection: Use the Williams %R and its EMA to identify ongoing trends and confirm their strength.
Overbought/Oversold Analysis: Pay attention to crosses in extreme zones (-20 and -80) for potential reversals.
Intensity-Based Filtering: The intensity visualization helps to focus on the most significant conditions, reducing noise.
Cross Prediction: Enable "Show Cross & Predicted Cross Signal" to anticipate future turning points and plan trades proactively.
Example Applications
Scalping: Monitor rapid crossovers in lower timeframes for quick entries and exits.
Swing Trading: Use the overbought/oversold zones and cross predictions to identify longer-term reversal opportunities.
Risk Management: The intensity visualization can be used to filter out weak signals, ensuring higher-quality trade setups.
Chart Information
For clarity and compliance with publishing standards:
The chart should display the full symbol, timeframe, and the script name ("Williams %R Intensity").
Ensure the indicator is visible and properly configured for the chart.
TEMA Cross StrategyDisclaimer Work in Progress:
This Indicator calculates three emas. Default Value 8,13 & 21
Under certain circumstances the indicator will generate a buy or sell signal. If a given signal matches with your analysis u can turn on the EST ATR Range.
This will calulate the ART from a given timeperiodand display the double on the chart to identify potential tps
JJ Psychological Levels (125 Increments)Psychological Levels Indicator
Description:
The Psychological Levels Indicator is a versatile tool designed for traders to identify key price levels that often act as support or resistance zones in the market. These levels are plotted at regular intervals, customizable by the user, starting from a base price level. This is particularly useful for spotting psychological price points that traders and investors frequently monitor.
Key Features:
1.Dynamic Psychological Levels:
- The script calculates and displays horizontal lines at price levels separated by customizable increments (default: 125 points).
- These levels are dynamically adjusted to the visible range of the chart.
2. Customizable Inputs:
- Starting Level: Set the base level from which increments are calculated (e.g., 0 or 1000).
- Step Size: Define the interval between levels (e.g., 125 for indices like Bank NIFTY).
3. Visual Representation:
- Horizontal lines are drawn at each psychological level, helping traders quickly identify key zones.
- Labels are placed next to each level, displaying the corresponding price for easy reference.
4. Application Across Instruments:
- This indicator works seamlessly with various asset classes, including stocks, indices, forex, and cryptocurrencies.
How to Use:
1.Identify Key Price Zones:
- Use the plotted psychological levels to spot areas where price action is likely to react.
- Levels such as 1125, 1250, and 1375 (for a step size of 125) are visually highlighted.
2. Plan Trades Around Key Levels:
- These levels can act as support/resistance or breakout points, providing opportunities for entry, exit, and stop-loss placement.
3. Customizable Settings:
- Adjust the starting level and step size to tailor the indicator to your trading instrument or strategy.
Why Psychological Levels Matter:
Psychological levels are widely followed by traders and often coincide with key market turning points due to their significance in human behavior and market psychology. They are frequently used by institutional traders, making them valuable reference points for intraday and swing trading.
Custom Settings:
- **Starting Level:** Default: `0`
- **Step Size:** Default: `125`
Disclaimer:
This indicator is a technical analysis tool and is not intended to provide financial advice. Always combine it with other indicators and perform your due diligence before making trading decisions.
EvoluteTrading - Candle Patterns Pro【CANDLE PATTERNS PRO】
This indicator helps identify multiple Japanese candlestick patterns in real-time, highlighting potential reversal and continuation signals through color-coded bars.
Key Features:
- Detects 13 major candlestick patterns
- Easy-to-read color highlighting system
- Customizable trend period and sensitivity
- Non-repainting signals
Patterns Detected:
✓ Engulfing Patterns (Bullish/Bearish)
✓ Harami Patterns (Bullish/Bearish)
✓ Morning & Evening Stars
✓ Hammer & Inverted Hammer
✓ Shooting Star
✓ Piercing Line & Dark Cloud Cover
✓ Kicker Patterns (Bullish/Bearish)
✓ Hanging Man
Settings:
- Pattern Trend Length: Adjusts the lookback period for trend confirmation
- Doji Size: Controls the sensitivity of pattern detection
This indicator is ideal for both beginners and experienced traders looking to enhance their technical analysis with classical candlestick patterns.
Note: Always use this indicator in conjunction with other forms of analysis and proper risk management.
─────────────────
By EvolueTrading
3_EMA50 with FB M&W by tamer nabilThis indicator combines a 50-period Exponential Moving Average (EMA) with dynamic Fibonacci retracements for both weekly and monthly timeframes. It is designed to provide traders with an insightful visual tool for market analysis. Below is a detailed breakdown of its features:
Key Features:
Dynamic EMA50 with Color Coding:
Plots the 50-period EMA on the chart.
The EMA line changes color based on the price's position relative to it:
Green: Price is above the EMA.
Red: Price is below the EMA.
Blue: Price is equal to the EMA.
Fibonacci Levels:
Calculates and displays Fibonacci retracement levels for both weekly and monthly timeframes.
Levels include 0%, 12.5%, 25%, 37.5%, 50%, 62.5%, 75%, 87.5%, and 100%.
Custom color-coding highlights critical levels:
50%: Blue.
0%: Red.
100%: Green.
Other levels: Gray.
Timeframe Status Monitoring:
Monitors the EMA50 status across multiple timeframes:
30-minute.
45-minute.
1-hour.
Displays the status as "Above," "Below," or "Cross" relative to the EMA50 for each timeframe.
Labels dynamically adjust based on the last bar.
Customizable Display:
Users can toggle the visibility of weekly and monthly Fibonacci levels.
Fibonacci levels dynamically adjust to historical weekly and monthly high/low values for greater relevance.
Enhanced Visualization:
Labels and lines are plotted with precise positioning for better clarity.
Fibonacci levels are extended across the chart for a comprehensive view of key retracement areas.
Use Cases:
Trend Analysis: Use the color-coded EMA50 to quickly identify market trends and potential reversal points.
Support and Resistance Identification: Leverage the weekly and monthly Fibonacci levels to find significant areas for price reaction.
Multi-Timeframe Confirmation: The indicator’s status labels help traders align their strategy across multiple timeframes.
This indicator provides a comprehensive tool for traders who seek to combine moving averages with Fibonacci retracements for enhanced technical analysis.
ADX and DI with HistogramThe "ADX and DI with Histogram" indicator is designed to help traders analyze market trends using the Average Directional Index (ADX) and Directional Indicators (DI+ and DI-). It provides a visual representation of trend strength and direction, along with a histogram to illustrate the difference between the DI+ and DI- values.
Features:
Inputs:
Length (len): Sets the period for the ADX and DI calculations (default: 14).
Threshold Level (th): Defines the ADX threshold for trend strength (default: 20).
Shape Color: Customizes the color of the shape markers plotted on the chart.
Shape Size: Adjusts the size of the shape markers (default: 10).
Shape Type: Selects the type of shape to display (Circle or Square).
Calculations:
Computes the True Range, Directional Movement (both plus and minus), and applies Exponential Moving Averages to these values to derive DI+ and DI-.
The ADX is calculated using the smoothed directional movement indicators.
Visual Outputs:
Plots DI+ (green line), DI- (red line), and ADX (navy line) on the main chart.
Includes a horizontal line representing the threshold level for easy trend assessment.
Displays a histogram that reflects the difference between DI+ and DI- with color coding to indicate directional strength (green for DI+ > DI- and red for DI+ < DI-).
Shape Markers:
When the ADX crosses above the specified threshold, a shape marker (Circle or Square) appears on the chart indicating a potential trend initiation.
Conversely, when the ADX crosses below the threshold, a shape marker is also plotted, signaling potential trend weakening.
Here is the description translated into Arabic:
---
مؤشر ADX و DI مع الهيستوجرام
نظرة عامة:
يُصمم مؤشر "ADX و DI مع الهيستوجرام" لمساعدة المتداولين في تحليل اتجاهات السوق باستخدام مؤشر الاتجاه المتوسط (ADX) ومؤشرات الاتجاه (DI+ و DI-). يوفر تمثيلًا بصريًا لقوة الاتجاه والاتجاه، بالإضافة إلى هيستوجرام لتوضيح الفرق بين قيم DI+ و DI-.
الميزات:
- **المدخلات:**
- **الطول (len):** يحدد الفترة لحسابات ADX و DI (افتراضي: 14).
- **مستوى العتبة (th):** يحدد عتبة ADX لقوة الاتجاه (افتراضي: 20).
- **لون الشكل:** يخصص لون علامات الشكل المرسومة على المخطط.
- **حجم الشكل:** يضبط حجم علامات الشكل (افتراضي: 10).
- **نوع الشكل:** يحدد نوع الشكل الذي يتم عرضه (دائرة أو مربع).
- **الحسابات:**
- يحسب النطاق الحقيقي، الحركة الاتجاهية (كلاهما زائد وناقص)، ويطبق المتوسطات المتحركة الأسية على هذه القيم للحصول على DI+ و DI-.
- يتم حساب ADX باستخدام مؤشرات الحركة الاتجاهية.
- **المخرجات :**
- يرسم DI+ (خط أخضر) و DI- (خط أحمر) و ADX (خط بحري) على المخطط الرئيسي.
- يتضمن خط أفقي يمثل مستوى العتبة لتقييم الاتجاه بسهولة.
- يعرض هيستوجرام يعكس الفرق بين DI+ و DI- مع ترميز لوني للإشارة إلى القوة الاتجاهية (أخضر عندما يكون DI+ أكبر من DI- وأحمر عندما يكون DI+ أقل من DI-).
- **علامات الشكل:**
- عندما يتجاوز ADX العتبة المحددة، تظهر علامة شكل (دائرة أو مربع) على المخطط تشير إلى احتمال بدء اتجاه جديد.
- على العكس، عندما يتجاوز ADX العتبة إلى الأسفل، يتم رسم علامة شكل أيضًا، مما يدل على احتمال ضعف الاتجاه.
### حالات الاستخدام:
هذا المؤشر مناسب للمتداولين الذين يتطلعون إلى تحديد الاتجاهات وتأكيدها، وتقييم قوة السوق، واتخاذ قرارات تداول مستنيرة بناءً على إشارات ADX و DI.
---
Enhanced Retail vs Institutional ActivityThis script highlights market activity in real-time, making it easier to infer the type of market participants driving price and volume changes.
Here’s a list of what the script analyzes:
Volume:
Current volume of the candle.
Moving average of volume over a specified number of periods.
Volume spikes: Current volume compared to a threshold multiple of the moving average.
Price Movement:
Percentage change in price between the current and previous candle.
Identifies significant price changes based on a user-defined threshold.
Institutional Activity:
High volume spikes combined with significant price movements.
Retail Activity:
Periods without volume spikes or significant price changes.
VWAP (Volume-Weighted Average Price):
The average traded price over a specified lookback period, weighted by volume, used as a benchmark.
Market Context Visualization:
Background colors to differentiate institutional (red) and retail (green) activity.
Overlays for:
-Volume bars.
-Average volume line.
-VWAP line.
In summary:
Red = Institutional activity: High volume + significant price change.
Green = Retail activity: Low volume or insignificant price change.
---------------------------------------------------------------------------------------------------------------------
Analysis Explanation:
I’m forecasting that Bitcoin will retest its November 12th low (~$85,098.75) around January 20th, 2025, where the horizontal support line intersects with the downtrend line. This conclusion is based on the following:
Trend Analysis:
The chart shows a clear downtrend with price respecting the descending trendline.
The intersection of the horizontal support and the downtrend line on January 20th indicates a confluence point where price action may gravitate.
Volume and Activity Insights:
Using the Retail vs Institutional Activity indicator, the chart highlights periods dominated by institutional (red background) or retail (green background) activity.
Current price action is in a green zone, suggesting predominantly retail participation with lower volume and insignificant price movements.
Retail vs Institutional Dynamics:
Institutional activity (red zones) aligns with significant price movements and volume spikes, often marking key turning points or trends.
The recent green retail-dominated periods suggest a lack of strong momentum, which may lead to continued price decline until institutions re-enter around the confluence area.
Volume Observations:
Volume remains relatively low during the current retail phase, indicating weak buying pressure.
A potential surge in institutional activity (red zones) near the support level could trigger a rebound or breakdown.
I expect Bitcoin’s price to drop further and test the November 12th low near $85,098.75 on January 20th, 2025. This projection is supported by the convergence of the downtrend line and horizontal support, low retail-driven volume, and historical institutional activity patterns observed using the "Retail vs Institutional Activity" indicator.
Pivot Bsquad (Traditional and Fibonacci)Pivot Bsquad (Traditional & Fibonacci) - XAUUSD Scalping Indicator
The Pivot Bsquad Indicator is designed to provide high-precision support and resistance levels for scalping on XAUUSD (Gold). This tool combines Traditional Pivot Points and Fibonacci-based Pivot Points to help traders identify key price levels where reversals or breakouts are likely to occur.
Key Features:
1. Dual Pivot Calculation Modes:
Traditional Pivots: Calculated using classic formulas based on high, low, and close values, ideal for broader support and resistance zones.
Fibonacci Pivots: Incorporates Fibonacci ratios for more dynamic and nuanced levels, perfect for intraday scalping.
2. Color-Coded Zones:
Clear visual representation of support (S1, S2, S3) and resistance (R1, R2, R3) levels.
Enhanced with key pivot lines for quick decision-making.
3. Scalping-Friendly Design:
Optimized for short timeframes (e.g., 1-minute to 15-minute charts).
Highlights high-probability zones for reversals or continuation patterns.
4. Customizable Settings:
Toggle between Traditional and Fibonacci pivots to suit your trading style.
Adjustable timeframes for pivot calculation (Daily, Weekly, Monthly).
Ideal For
Scalpers looking to capitalize on XAUUSD's volatility.
Intraday traders who rely on precise support and resistance levels.
Technical traders seeking a reliable confluence of pivot strategies.
How to Use:
Select your preferred pivot mode (Traditional or Fibonacci) in the settings.
Observe price action around pivot levels for potential entry and exit points.
Use in conjunction with momentum oscillators or candlestick patterns for confirmation.
Note: While this indicator provides a solid framework for scalping, always consider risk management practices and market conditions.
Trade Checklist RSI BollingerBands UP/DOWN Daysupdated 30WSMA in the table this is a good indicator for a stock to be bullish or bearish above 30WSMA is bullish and below is bearish
Index Option TradingThis indicator helps identify potential entry and exit points for trading by combining three key technical indicators: Moving Average (MA), Relative Strength Index (RSI), and Bollinger Bands (BB). Here's how it works and how you can use it to initiate trades:
Trend Filter Finder Trend Filter Finder
趋势过滤器
This indicator combines Bollinger Bands and Keltner Channels to identify market trends and volatility conditions.
该指标结合了布林带和肯特纳通道来识别市场趋势和波动条件。
Usage 使用方法:
- Black bar color indicates not recommended for buy signals
K线呈黑色表示当前不建议释放买入信号
30-Min Trend + 1-Min EMA Cross AlertHow It Works:
30-Minute Trend Analysis:
Calculates the trend based on a fast and slow moving average.
The background color indicates the trend (green for bullish, red for bearish).
1-Minute EMA Crossover:
Calculates the 9-period and 18-period EMAs on the 1-minute timeframe.
Detects bullish and bearish crossovers.
Adds labels for crossovers (e.g., "Buy" for bullish and "Sell" for bearish).
Alerts:
Triggers alerts when a bullish or bearish crossover occurs.
You can configure alerts in TradingView using these signals.
Accurate Bollinger Bands mcbw_ [True Volatility Distribution]The Bollinger Bands have become a very important technical tool for discretionary and algorithmic traders alike over the last decades. It was designed to give traders an edge on the markets by setting probabilistic values to different levels of volatility. However, some of the assumptions that go into its calculations make it unusable for traders who want to get a correct understanding of the volatility that the bands are trying to be used for. Let's go through what the Bollinger Bands are said to show, how their calculations work, the problems in the calculations, and how the current indicator I am presenting today fixes these.
--> If you just want to know how the settings work then skip straight to the end or click on the little (i) symbol next to the values in the indicator settings window when its on your chart <--
--------------------------- What Are Bollinger Bands ---------------------------
The Bollinger Bands were formed in the 1980's, a time when many retail traders interacted with their symbols via physically printed charts and computer memory for personal computer memory was measured in Kb (about a factor of 1 million smaller than today). Bollinger Bands are designed to help a trader or algorithm see the likelihood of price expanding outside of its typical range, the further the lines are from the current price implies the less often they will get hit. With a hands on understanding many strategies use these levels for designated levels of breakout trades or to assist in defining price ranges.
--------------------------- How Bollinger Bands Work ---------------------------
The calculations that go into Bollinger Bands are rather simple. There is a moving average that centers the indicator and an equidistant top band and bottom band are drawn at a fixed width away. The moving average is just a typical moving average (or common variant) that tracks the price action, while the distance to the top and bottom bands is a direct function of recent price volatility. The way that the distance to the bands is calculated is inspired by formulas from statistics. The standard deviation is taken from the candles that go into the moving average and then this is multiplied by a user defined value to set the bands position, I will call this value 'the multiple'. When discussing Bollinger Bands, that trading community at large normally discusses 'the multiple' as a multiplier of the standard deviation as it applies to a normal distribution (gaußian probability). On a normal distribution the number of standard deviations away (which trades directly use as 'the multiple') you are directly corresponds to how likely/unlikely something is to happen:
1 standard deviation equals 68.3%, meaning that the price should stay inside the 1 standard deviation 68.3% of the time and be outside of it 31.7% of the time;
2 standard deviation equals 95.5%, meaning that the price should stay inside the 2 standard deviation 95.5% of the time and be outside of it 4.5% of the time;
3 standard deviation equals 99.7%, meaning that the price should stay inside the 3 standard deviation 99.7% of the time and be outside of it 0.3% of the time.
Therefore when traders set 'the multiple' to 2, they interpret this as meaning that price will not reach there 95.5% of the time.
---------------- The Problem With The Math of Bollinger Bands ----------------
In and of themselves the Bollinger Bands are a great tool, but they have become misconstrued with some incorrect sense of statistical meaning, when they should really just be taken at face value without any further interpretation or implication.
In order to explain this it is going to get a bit technical so I will give a little math background and try to simplify things. First let's review some statistics topics (distributions, percentiles, standard deviations) and then with that understanding explore the incorrect logic of how Bollinger Bands have been interpreted/employed.
---------------- Quick Stats Review ----------------
.
(If you are comfortable with statistics feel free to skip ahead to the next section)
.
-------- I: Probability distributions --------
When you have a lot of data it is helpful to see how many times different results appear in your dataset. To visualize this people use "histograms", which just shows how many times each element appears in the dataset by stacking each of the same elements on top of each other to form a graph. You may be familiar with the bell curve (also called the "normal distribution", which we will be calling it by). The normal distribution histogram looks like a big hump around zero and then drops off super quickly the further you get from it. This shape (the bell curve) is very nice because it has a lot of very nifty mathematical properties and seems to show up in nature all the time. Since it pops up in so many places, society has developed many different shortcuts related to it that speed up all kinds of calculations, including the shortcut that 1 standard deviation = 68.3%, 2 standard deviations = 95.5%, and 3 standard deviations = 99.7% (these only apply to the normal distribution). Despite how handy the normal distribution is and all the shortcuts we have for it are, and how much it shows up in the natural world, there is nothing that forces your specific dataset to look like it. In fact, your data can actually have any possible shape. As we will explore later, economic and financial datasets *rarely* follow the normal distribution.
-------- II: Percentiles --------
After you have made the histogram of your dataset you have built the "probability distribution" of your own dataset that is specific to all the data you have collected. There is a whole complicated framework for how to accurately calculate percentiles but we will dramatically simplify it for our use. The 'percentile' in our case is just the number of data points we are away from the "middle" of the data set (normally just 0). Lets say I took the difference of the daily close of a symbol for the last two weeks, green candles would be positive and red would be negative. In this example my dataset of day by day closing price difference is:
week 1:
week 2:
sorting all of these value into a single dataset I have:
I can separate the positive and negative returns and explore their distributions separately:
negative return distribution =
positive return distribution =
Taking the 25th% percentile of these would just be taking the value that is 25% towards the end of the end of these returns. Or akin the 100%th percentile would just be taking the vale that is 100% at the end of those:
negative return distribution (50%) = -5
positive return distribution (50%) = +4
negative return distribution (100%) = -10
positive return distribution (100%) = +20
Or instead of separating the positive and negative returns we can also look at all of the differences in the daily close as just pure price movement and not account for the direction, in this case we would pool all of the data together by ignoring the negative signs of the negative reruns
combined return distribution =
In this case the 50%th and 100%th percentile of the combined return distribution would be:
combined return distribution (50%) = 4
combined return distribution (100%) = 10
Sometimes taking the positive and negative distributions separately is better than pooling them into a combined distribution for some purposes. Other times the combined distribution is better.
Most financial data has very different distributions for negative returns and positive returns. This is encapsulated in sayings like "Price takes the stairs up and the elevator down".
-------- III: Standard Deviation --------
The formula for the standard deviation (refereed to here by its shorthand 'STDEV') can be intimidating, but going through each of its elements will illuminate what it does. The formula for STDEV is equal to:
square root ( (sum ) / N )
Going back the the dataset that you might have, the variables in the formula above are:
'mean' is the average of your entire dataset
'x' is just representative of a single point in your dataset (one point at a time)
'N' is the total number of things in your dataset.
Going back to the STDEV formula above we can see how each part of it works. Starting with the '(x - mean)' part. What this does is it takes every single point of the dataset and measure how far away it is from the mean of the entire dataset. Taking this value to the power of two: '(x - mean) ^ 2', means that points that are very far away from the dataset mean get 'penalized' twice as much. Points that are very close to the dataset mean are not impacted as much. In practice, this would mean that if your dataset had a bunch of values that were in a wide range but always stayed in that range, this value ('(x - mean) ^ 2') would end up being small. On the other hand, if your dataset was full of the exact same number, but had a couple outliers very far away, this would have a much larger value since the square par of '(x - mean) ^ 2' make them grow massive. Now including the sum part of 'sum ', this just adds up all the of the squared distanced from the dataset mean. Then this is divided by the number of values in the dataset ('N'), and then the square root of that value is taken.
There is nothing inherently special or definitive about the STDEV formula, it is just a tool with extremely widespread use and adoption. As we saw here, all the STDEV formula is really doing is measuring the intensity of the outliers.
--------------------------- Flaws of Bollinger Bands ---------------------------
The largest problem with Bollinger Bands is the assumption that price has a normal distribution. This is assumption is massively incorrect for many reasons that I will try to encapsulate into two points:
Price return do not follow a normal distribution, every single symbol on every single timeframe has is own unique distribution that is specific to only itself. Therefore all the tools, shortcuts, and ideas that we use for normal distributions do not apply to price returns, and since they do not apply here they should not be used. A more general approach is needed that allows each specific symbol on every specific timeframe to be treated uniquely.
The distributions of price returns on the positive and negative side are almost never the same. A more general approach is needed that allows positive and negative returns to be calculated separately.
In addition to the issues of the normal distribution assumption, the standard deviation formula (as shown above in the quick stats review) is essentially just a tame measurement of outliers (a more aggressive form of outlier measurement might be taking the differences to the power of 3 rather than 2). Despite this being a bit of a philosophical question, does the measurement of outlier intensity as defined by the STDEV formula really measure what we want to know as traders when we're experiencing volatility? Or would adjustments to that formula better reflect what we *experience* as volatility when we are actively trading? This is an open ended question that I will leave here, but I wanted to pose this question because it is a key part of what how the Bollinger Bands work that we all assume as a given.
Circling back on the normal distribution assumption, the standard deviation formula used in the calculation of the bands only encompasses the deviation of the candles that go into the moving average and have no knowledge of the historical price action. Therefore the level of the bands may not really reflect how the price action behaves over a longer period of time.
------------ Delivering Factually Accurate Data That Traders Need------------
In light of the problems identified above, this indicator fixes all of these issue and delivers statistically correct information that discretionary and algorithmic traders can use, with truly accurate probabilities. It takes the price action of the last 2,000 candles and builds a huge dataset of distributions that you can directly select your percentiles from. It also allows you to have the positive and negative distributions calculated separately, or if you would like, you can pool all of them together in a combined distribution. In addition to this, there is a wide selection of moving averages directly available in the indicator to choose from.
Hedge funds, quant shops, algo prop firms, and advanced mechanical groups all employ the true return distributions in their work. Now you have access to the same type of data with this indicator, wherein it's doing all the lifting for you.
------------------------------ Indicator Settings ------------------------------
.
---- Moving average ----
Select the type of moving average you would like and its length
---- Bands ----
The percentiles that you enter here will be pulled directly from the return distribution of the last 2,000 candles. With the typical Bollinger Bands, traders would select 2 standard deviations and incorrectly think that the levels it highlights are the 95.5% levels. Now, if you want the true 95.5% level, you can just enter 95.5 into the percentile value here. Each of the three available bands takes the true percentile you enter here.
---- Separate Positive & Negative Distributions----
If this box is checked the positive and negative distributions are treated indecently, completely separate from each other. You will see that the width of the top and bottom bands will be different for each of the percentiles you enter.
If this box is unchecked then all the negative and positive distributions are pooled together. You will notice that the width of the top and bottom bands will be the exact same.
---- Distribution Size ----
This is the number of candles that the price return is calculated over. EG: to collect the price return over the last 33 candles, the difference of price from now to 33 candles ago is calculated for the last 2,000 candles, to build a return distribution of 2000 points of price differences over 33 candles.
NEGATIVE NUMBERS(<0) == exact number of candles to include;
EG: setting this value to -20 will always collect volatility distributions of 20 candles
POSITIVE NUMBERS(>0) == number of candles to include as a multiple of the Moving Average Length value set above;
EG: if the Moving Average Length value is set to 22, setting this value to 2 will use the last 22*2 = 44 candles for the collection of volatility distributions
MORE candles being include will generally make the bands WIDER and their size will change SLOWER over time.
I wish you focus, dedication, and earnest success on your journey.
Happy trading :)
Sessionsseparate the different operating sessions for a better visualizacion on the grafh, configure it as you want to separate and customize the colors.
Pivot Points High Low - JVersion**Indicator Name**: Pivot Points High Low (Without Price Labels)
**Overview**
The Pivot Points High Low indicator is designed to identify and mark local highs and lows (or “pivot” points) on a price chart. Unlike other pivot-based indicators that label each pivot with its exact price, this version displays only small circular markers—removing clutter and focusing attention on the pivot locations themselves.
**Key Features**
1. **Pivot Detection**
- The script uses TradingView’s built-in `ta.pivothigh()` and `ta.pivotlow()` functions to determine when the market has formed a pivot high or pivot low.
- You can define how many bars to the left and right are required to confirm a pivot, helping you tailor the indicator to different market conditions and timeframes.
2. **Clean Markers**
- Each confirmed pivot high or low is represented by a circle placed precisely on the candle where the pivot is detected.
- No numeric labels are shown, keeping your chart visually uncluttered while still highlighting important turning points in price.
3. **Customization**
- **Left/Right Pivot Length**: Choose how many bars to the left and right must be lower (for highs) or higher (for lows) to validate a pivot. Larger values mean fewer but more significant pivots; smaller values mean more frequent pivots.
- **Marker Colors**: Independently customize the colors of the high-marker circles and low-marker circles to easily distinguish between local tops and bottoms.
4. **Usage and Interpretation**
- **Identifying Reversals**: As soon as a circle appears at a local high or low, it may indicate a short-term trend reversal or the beginning of a new swing in price.
- **Combine with Other Tools**: Pivot points are more informative when used alongside broader trend analysis, support/resistance identification, or other momentum indicators.
- **Adjusting Sensitivity**: By increasing or decreasing the left/right pivot lengths, you can make the indicator more or less sensitive to small market fluctuations.
5. **Practical Tips**
- **Swing Trading**: Shorter lengths can be used by swing traders looking for quick reversals in lower timeframes.
- **Longer-Term Trends**: Larger lengths are better for position traders or those who prefer to see only major turning points in the market.
- **Clean Chart Layout**: Because text labels are removed, you can visually focus on the circles—especially helpful if you use multiple indicators and prefer a less cluttered chart.
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By pinpointing local highs and lows without price labels, the **Pivot Points High Low** indicator keeps charts neat yet informative, allowing traders to quickly recognize potential turning points in the market and make more informed decisions.
Alejandro IndicatorCopy 1, de prueba de estrategia tortuga, hace falta poderle agregar una alerta auditiva
