Any RibbonThis indicator displays a ribbon of two individually configured Fast and Slow and Moving Averages for a fixed time frame. It also displays the last close price of the configured time frame, colored green when above the band, red below and blue when interacting. A label shows the percentage distance of the current price from the band, (again red below, green above, blue interacting), when the price is within the band it will show the percentage distance from median of the band.
The Fast and Slow Moving Averages can be set to:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Volume-Weighted Moving Average (VWMA)
Hull Moving Average (HMA)
Exponentially Weighted Moving Average (RMA) (SMMA)
Linear regression curve Moving Average (LSMA)
Double EMA (DEMA)
Double SMA (DSMA)
Double WMA (DWMA)
Double RMA (DRMA)
Triple EMA (TEMA)
Triple SMA (TSMA)
Triple WMA (TWMA)
Triple RMA (TRMA)
Symmetrically Weighted Moving Average (SWMA) ** length does not apply **
Arnaud Legoux Moving Average (ALMA)
Variable Index Dynamic Average (VIDYA)
Fractal Adaptive Moving Average (FRAMA)
I wrote this script after identifying some interesting moving average bands with my AMACD indicator and wanting to see them on the price chart. As an example look at the interactions between ETHBUSD 4hr and the band of VIDYA 32 Open and VIDYA 39 Open. Or start from the good old BTC Bull market support band, Weekly EMA 21 and SMA 20 and see if you can get a better fit. I find the Double RMA 22 a better fast option than the standard EMA 21.
在腳本中搜尋"Exponential Moving Average"
[SS]_TrendAVGZones_and_GoldenRatioMAThe _TrendAVGZones_and_GoldenRatioMA is an indicator that is composed first of a channel made of three price averages ( base average, middle lower and middle upper ) in red is the previous corrections average and in green the previous rises average. So that way we the setting of stop loss targets and price targets can be set up at first glance. It adjusts to any timeframe so no worries 'bout that.
Also I added two exponential moving averages ( white and silver lines ) on the chart which I modified their equations by multiplying as it follows :
is the simple modification I added to fine tune it's precision and after some trials and errors I finally found a perfect spot. Now I tried it with historical data of Bitcoin and when the two Golden Ratio EMA crosses there's a big move coming imminently : if the white one is on top of the silver one the trend is bullish inversely the white one finds itself under the silver line then it needs to cross to expect a reversal.
rphi = 0.6180339887498948 = is the conjugate root of the golden ratio also called the silver ratio
phi = 1.6180339887498948 = golden ratio
It should be used to find short to mid term price targets selling as well as buying ones. If you're a long term trader I suggest using trend lines analysis in combination with it.
I hope to make this indicator a community owned indicator so don't hesitate to perfect it so we can build the best tool traders can hope for ! Together we will no longer ask wen lambo? we will get it!
IF you've got any question you can always DM me
take care of yourselves you future millionaires :D
-SS
Exponentially Deviating Moving Average (MZ EDMA)Exponentially Deviating Moving Average (MZ EDMA) is derived from Exponential Moving Average to predict better exit in top reversal case.
EDMA Philosophy
EDMA is calculated in following steps:
In first step, Exponentially expanding moving line is calculated with same code as of EMA but with different smoothness (1 instead of 2).
In 2nd step, Exponentially contracting moving line is calculated using 1st calculated line as source input and also using same code as of EMA but with different smoothness (1 instead of 2).
In 3rd step, Hull Moving Average with 3/2 of EDMA length is calculated using final line as source input. This final HMA will be equal to Exponentially Deviating Moving Average.
EDMA Advantages
EDMA's main advantage is that in case of top price reversal it deviates from conventional EMA of 2*Length. This benefits in using EDMA for EMA cross with quick signals avoiding unnecessary crossovers. EDMA's deviation in case of top reversal can be seen as below:
EDMA presents better smoothened curve which acts as better Support and resistance. EDMA coparison with conventional EMA of 2*length of EDMA is as follows.
Additional Features
EMA Band: EMA band is shown on chart to better visualize EMA cross with EDMA.
Dynamic Coloring: Chikou Filter library is used for derivation of dynamic coloring of EDMA and its band.
Alerts: Alerts are provided of all trade signals. Weak buy/sell would trigger if EMA of 2*EDMA_length crosses EDMA. Strong buy/sell would trigger if EMA of same length as of EDMA crosses EDMA.
Trade Confirmation with Chikou Filter: Trend filteration from Chikou filter library is used as an option to enhance trades signals accuracy.
Defaults
Currently default EDMA and EMA1 length is set to 20 period which I've found better for higher timeframes but this can be adjusted according to user's timeframe. I would soon add Multi Timeframe option in script too. Chikou filter's period is set to 25.
SuperTrended Moving AveragesA different approach to SuperTrend:
adding 100 periods Exponential Moving Average in calculation of SuperTrend and also 0.5 ATR Multiplier to have a clear view of the ongoing trend and also provides significant Supports and Resistances.
Default Moving Average type set as EMA (Exponential Moving Average) but users can choose from 11 different Moving Average types as:
SMA : Simple Moving Average
EMA : Exponential Moving Average
WMA : Weighted Moving Average
DEMA : Double Exponential Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average a.k.a. VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
HULL : Hull Moving Average
TILL : Tillson T3 Moving Average
Credits going to @CryptoErge for sharing his development to public.
Multi-X by HamidBoxHello to All, introducing Multi Types Crossover strategy,
simply the best way of trading with Crossover and Crossunder Strategy, How it Works???
I added 5 types of Moving Averages,
1: Simple Moving Average ( SMA )
2: Exponential Moving Average ( EMA )
3: Weighted Moving Average ( WMA )
4: Volume Weighted Moving Average ( VWMA )
5: Relative Moving Average (RMA)
With this indicator, you can do scalping, You can trade not only with similar types of Moving Average indicators but also with different types of Moving Average indicators.
what is mean? like: Normal Condition is:
( Simple Moving Average ) Crossover to ( Simple Moving Average ), SMA x SMA
( Exponential Moving Average ) Crossover to ( Exponential Moving Average ), EMA x EMA
But we can Crossover with:
( Exponential Moving Average ) Crossover to ( Simple Moving Average ), EMA x SMA
( Simple Moving Average ) Crossover to ( Weighted Moving Average ), SMA x WMA
( Weighted Moving Average ) Crossover to ( Weighted Moving Average ), WMA x WMA
( Simple Moving Average ) Crossover to (Relative Moving Average), WMA x RMA
and also I added Moving Average ZONE in this tool, What does it work???
The zone will tell us what type of direction the market has, if the market is above the zone, it's mean we have a Bullish Trend, and if the market is below the zone, it means the market has a Bearish Trend,
so if you want to play on the safe side, never trade when the market is in Bearish Trend, and if you want to play on aggressive mood, you can skip Moving Average Zone section.
CPR, Camarilla & Moving AverageThis script is created primarily for Intraday trading but can also be used for short and long term trading. This is a combination of Central Pivot Range (CPR), Moving Averages and Camarilla Pivot levels (with inner levels). This helps you to combine the strategies of CPR and Moving Averages to identify the best trading opportunities with greater edge. Central Pivot Range and Camarilla pivots are taken from PivotBoss by Franc Ochoa.
Key features:
# Daily CPR levels
# Weekly CPR levels
# Monthly CPR levels
# Previous Day High and Lows
# Previous Week Highs and Lows
# Previous Month Highs and Lows
# Camarilla Pivots with inner Levels
# CPR Levels for the next Day, Week and Month
# 5 Simple moving averages and 5 Exponential Moving Averages
What separates this script from other scripts with CPR and Moving averages?
# One of the few indicators (if not the only one) which combines the 2 types of Moving Averages, CPR and also Camarilla Pivots.
# CPR Levels for not just the next Day, but for next Week(Weekly CPR) and Month(Monthly CPR) also.
# Hide the previous day's levels according to your wish. This is the most unique feature of this indicator. You can set the number of Daily CPR levels you want to load in the chart. This is not just for the Daily CPR but also for the Weekly and Monthly CPR also. This makes the chart less cluttered and prevents the candles from getting buried in the indicators. Please notice how the previous day's CPR levels are hidden in the displayed demo chart on the script page. In the chart, only one trading day's data is shown(by default).
# This script is OPEN SOURCE.
Strategies :
For CPR & Camarilla Strategies for intraday trading and swing trading refer to the book 'Secrets of a Pivot Boss: Revealing Proven Methods for Profiting in the Market' by Franklin O. Ochoa.
Moving averages strategies :
Moving averages can be combined and also used individually for several strategies
* 9 EMA can be used as trailing stop loss for strong moving trends that helps you to catch big moves.
* 20sma can be used not just trailing stop loss but also for taking re-entry to the trend.
* Golden cross - The golden cross occurs when a short-term moving average crosses over a major long-term moving average to the upside. This indicates a bullish turn in the market. Eg: 50 SMA cuts 200 SMA from below.
* Death Cross - The death cross occurs when the short term moving average crosses the long-term average from above. This indicates a bearish turn in the market. Eg: 50 SMA cuts 200 SMA from above.
* When 20 SMA is above 50 SMA and 20 SMA and 50 SMA are angling up like parallel lines, then it denotes bullish strength. If this happens right after Golden Cross, big moves to the upside can be expected.
* When 20 SMA is below 50 SMA and 20 SMA and 50 SMA are angling down like parallel lines, then it denotes bearish strength. If this happens right after Death Cross, big moves to the downside can be expected.
* When 20SMA and 50 SMA are going flat and crossing each other, then it denotes sideways sentiment.
Moving average strategies are taken from the book 'How to Make Money in Intraday Trading' by Ashwani Gujral. For learning more about how to combine CPR and Moving averages in your trading please refer to this book.
Pinescript v4 - The Holy Grail (Trailing Stop)After studying several other scripts, I believe I have found the Holy Grail! (Or perhaps I've just found a bug with Tradingview's Pinescript v4 language) Anyhow, I'm publishing this script in the hope that someone smarter than myself could shed some light on the fact that adding a trailing stop to any strategy seems to make it miraculously...no that's an understatement...incredulously, stupendously, mind-bendingly profitable. I'm talking about INSANE profit factors, higher than 200x, with drawdowns of <10%. Sounds too good to be true? Maybe it is...or you could hook it up to your LIVE broker, and pray it doesn't explode. This is an upgraded version of my original Pin Bar Strategy.
Recommended Chart Settings:
Asset Class: Forex
Time Frame: H1
Long Entry Conditions:
a) Exponential Moving Average Fan up trend
b) Presence of a Bullish Pin Bar
c) Pin Bar pierces the Exponential Moving Average Fan
Short Entry Conditions:
a) Exponential Moving Average down trend
b) Presence of a Bearish Pin Bar
c) Pin Bar pierces the Exponential Moving Average Fan
Exit Conditions:
a) Trailing stop is hit
b) Moving Averages cross-back (optional)
c) It's the weekend
Default Robot Settings:
Equity Risk (%): 3 //how much account balance to risk per trade
Stop Loss (x*ATR, Float): 0.5 //stoploss = x * ATR, you can change x
Stop Loss Trail Points (Pips): 1 //the magic sauce, not sure how this works
Stop Loss Trail Offset (Pips): 1 //the magic sauce, not sure how this works
Slow SMA (Period): 50 //slow moving average period
Medium EMA (Period): 18 //medium exponential moving average period
Fast EMA (Period): 6 //fast exponential moving average period
ATR (Period): 14 // average true range period
Cancel Entry After X Bars (Period): 3 //cancel the order after x bars not triggered, you can change x
Backtest Results (2019 to 2020, H1, Default Settings):
AUDUSD - 1604% profit, 239.6 profit factor, 4.9% drawdown (INSANE)
NZDUSD - 1688.7% profit, 100.3 profit factor, 2.5% drawdown
GBPUSD - 1168.8% profit, 98.7 profit factor, 0% drawdown
USDJPY - 900.7% profit, 93.7 profit factor, 4.9% drawdown
USDCAD - 819% profit, 31.7 profit factor, 8.1% drawdown
EURUSD - 685.6% profit, 26.8 profit factor, 5.9% drawdown
USDCHF - 1008% profit, 18.7 profit factor, 8.6% drawdown
GBPJPY - 1173.4% profit, 16.1 profit factor, 7.9% drawdown
EURAUD - 613.3% profit, 14.4 profit factor, 9.8% drawdown
AUDJPY - 1619% profit, 11.26 profit factor, 9.1% drawdown
EURJPY - 897.2% profit, 6 profit factor, 13.8% drawdown
EURGBP - 608.9% profit, 5.3 profit factor, 9.8% drawdown (NOT TOO SHABBY)
As you can clearly see above, this forex robot is projected by the Tradingview backtester to be INSANELY profitable for all common forex pairs. So what was the difference between this strategy and my previous strategies? Check my code and look for "trail_points" and "trail_offset"; you can even look them up in the PineScript v4 documentation. They specify a trailing stop as the exit condition, which automatically closes the trade if price reverses against you.
I however suspect that the backtester is not properly calculating intra-bar price movement, and is using a simplified model. With this simplfied approach, the trailing stop code becomes some sort of "holy grail" generator, making every trade entered profitable.
Risk Warning:
This is a forex trading strategy that involves high risk of equity loss, and backtest performance will not equal future results. You agree to use this script at your own risk.
Hint:
To get more realistic results, and *maybe* overcome the intrabar simulation error, change the settings to: "Stop Loss Trail Points (pips)": 100
I am not sure if this eradicates the bug, but the entries and exits look more proper, and the profit factors are more believable.
Maguila Strategy by Rodrigo CohenREAD BEFORE USE!!!
!!!ALERT!!!! THIS CODE ONLY WORKS WITH WDO AND WIN , BOTH WITH TIMEFRAMES 1 MINUTE AND 5 MINUTE.
This is a test to the Maguila strategy created by Rodrigo Cohen.
This code MUST be validaded by Rodrigo Cohen, use ONLY for tests.
Some results are different from Cohen's videos, so the McGuinley indicator needs some ajustments.
FUTURES: WIN , WDO
TIME FRAME: 1 Minute (also works in 5 minutes)
INDICATORS: McGinley Dynamic accompanied by the Exponential Moving Average coloring rule of 21 and 42 periods
MARKET TYPE: In trend (up or down)
INPUT:
1. When buying (long) = Market in an upward trend, the average of 21 crosses that of 42 upwards. When the price returns to the average of 21, wait for a positive candle in the Maguila's color and buy a break from the maximum of this signal candle.
2. On sale (short) = Downtrend market, the average of 21 crosses that of 42 downwards. When the price returns to the average of 21, wait for a negative candle in the Maguila's color and sell when the minimum of this signal candle breaks.
GAIN and LOSS are technical.
DEFAULT VALUES:
Averages:
- 1 minute - EMA 21 and EMA 42
- 5 minute - EMA 17 and EMA 34
Gains and Loss:
- WDO - 10 points
- WIN - 200 points
Tabajara simple versionIndicator Tabajara from the brazilian trader André Machado.
Simple version with moving averages SMA 20 and SMA 200.
If fast moving average (20) is ascending, positive candles will receive green color.
Descending fast moving average (20) makes negative candles receive red color.
In other cases the candles will be gray (positive) and black (negative).
The slow moving average (SMA 200) shows the primary trend.
It´s also possible using the indicator with exponential moving averages.
Well Rounded Moving AverageIntroduction
There are tons of filters, way to many, and some of them are redundant in the sense they produce the same results as others. The task to find an optimal filter is still a big challenge among technical analysis and engineering, a good filter is the Kalman filter who is one of the more precise filters out there. The optimal filter theorem state that : The optimal estimator has the form of a linear observer , this in short mean that an optimal filter must use measurements of the inputs and outputs, and this is what does the Kalman filter. I have tried myself to Kalman filters with more or less success as well as understanding optimality by studying Linear–quadratic–Gaussian control, i failed to get a complete understanding of those subjects but today i present a moving average filter (WRMA) constructed with all the knowledge i have in control theory and who aim to provide a very well response to market price, this mean low lag for fast decision timing and low overshoots for better precision.
Construction
An good filter must use information about its output, this is what exponential smoothing is about, simple exponential smoothing (EMA) is close to a simple moving average and can be defined as :
output = output(1) + α(input - output(1))
where α (alpha) is a smoothing constant, typically equal to 2/(Period+1) for the EMA.
This approach can be further developed by introducing more smoothing constants and output control (See double/triple exponential smoothing - alpha-beta filter) .
The moving average i propose will use only one smoothing constant, and is described as follow :
a = nz(a ) + alpha*nz(A )
b = nz(b ) + alpha*nz(B )
y = ema(a + b,p1)
A = src - y
B = src - ema(y,p2)
The filter is divided into two components a and b (more terms can add more control/effects if chosen well) , a adjust itself to the output error and is responsive while b is independent of the output and is mainly smoother, adding those components together create an output y , A is the output error and B is the error of an exponential moving average.
Comparison
There are a lot of low-lag filters out there, but the overshoots they induce in order to reduce lag is not a great effect. The first comparison is with a least square moving average, a moving average who fit a line in a price window of period length .
Lsma in blue and WRMA in red with both length = 100 . The lsma is a bit smoother but induce terrible overshoots
ZLMA in blue and WRMA in red with both length = 100 . The lag difference between each moving average is really low while VWRMA is way more precise.
Hull MA in blue and WRMA in red with both length = 100 . The Hull MA have similar overshoots than the LSMA.
Reduced overshoots moving average (ROMA) in blue and WRMA in red with both length = 100 . ROMA is an indicator i have made to reduce the overshoots of a LSMA, but at the end WRMA still reduce way more the overshoots while being smoother and having similar lag.
I have added a smoother version, just activate the extra smooth option in the indicator settings window. Here the result with length = 200 :
This result is a little bit similar to a 2 order Butterworth filter. Our filter have more overshoots which in this case could be useful to reduce the error with edges since other low pass filters tend to smooth their amplitude thus reducing edge estimation precision.
Conclusions
I have presented a well rounded filter in term of smoothness/stability and reactivity. Try to add more terms to have different results, you could maybe end up with interesting results, if its the case share them with the community :)
As for control theory i have seen neural networks integrated to Kalman flters which leaded to great accuracy, AI is everywhere and promise to be a game a changer in real time data smoothing. So i asked myself if it was possible for a neural networks to develop pinescript indicators, if yes then i could be replaced by AI ? Brrr how frightening.
Thanks for reading :)
Moving Average RibbonThis is an extension of the Madrid Moving Average Ribbon public script to allow for different kinds of moving averages (the original allows only exponential and simple). Possible entries in the MA Type argument field are:
sma (simple moving average)
ema (exponential moving average)
wma (weighted moving average)
trima (triangular moving average)
zlema (zero-lag exponential moving average)
dema (double exponential moving average)
tema (triple exponential moving average)
hma (hull moving average)
If the argument given by the user does not match anything from the above list, it will default to ema.
Daily Delta TrendDaily Delta Trend is a useful exponential moving average of the 50 day and 200 day simple moving average. In the first Daily Delta Trend I realized that the simple moving averages were pretty choppy as they were buy then sell over short period of times. So I thought taking an average of another average would smooth my results and give it buy and sell signals more clearly. In chart 1, you can see that it is choppy, and in chart 2 is much smoother.
The way I've been interpreting the chart is to trade it only when the 50-day average (GREEN) Trades with 200-day average (RED). For example, when red and green are both >0 = Buy and both <0 = Sell.
Just from a little of pretesting, I was able to find solid trades from multiple pairs.
DISCLAIMER, I have not actually traded this indicator as I just wrote it for the past few hours, But I thought it was interesting and maybe I might trade it. Feel free to play with it and comment back :P
ZLEMA Trend Index 2.0ZTI — ZLEMA Trend Index 2.0 (0–1000)
Overview
Price Mapped ZTI v2.0 - Enhanced Zero-Lag Trend Index.
This indicator is a significant upgrade to the original ZTI v1.0, featuring enhanced resolution from 0-100 to 0-1000 levels for dramatically improved price action accuracy. The Price Mapped ZTI uses direct price-to-level mapping to eliminate statistical noise and provide true proportional representation of market movements.
Key Innovation: Instead of statistical normalization, this version maps current price position within a user-defined lookback period directly to the ZTI scale, ensuring perfect correlation with actual price movements. I believe this is the best way to capture trends instead of directly on the charts using a plethora of indicators which introduces bad signals resulting in drawdowns. The RSI-like ZTI overbought and oversold lines filter valid trends by slicing through the current trading zone. Unlike RSI that can introduce false signals, the ZTI levels 1 to 1000 is faithfully mapped to the lowest to highest price in the current trading zone (lookback period in days) which can be changed in the settings. The ZTI line will never go off the beyond the ZTI levels in case of extreme trend continuation as the trading zone is constantly updated to reflect only the most recent bars based on lookback days.
Core Features
✅ 10x Higher Resolution - 0-1000 scale provides granular movement detection
✅ Adjustable Trading Zone - Customizable lookback period from 1-50 days
✅ Price-Proportional Mapping - Direct correlation between price position and ZTI level
✅ Zero Statistical Lag - No rolling averages or standard deviation calculations
✅ Multi-Strategy Adaptability - Single parameter adjustment for different trading styles
Trading Zone Optimization
📊 Lookback Period Strategies
Short-term (1-3 days):
Ultra-responsive to recent price action
Perfect for scalping and day trading
Tight range produces more sensitive signals
Medium-term (7-14 days):
Balanced view of recent trading range
Ideal for swing trading
Captures meaningful support/resistance levels
Long-term (21-30 days):
Broader market context
Excellent for position trading
Smooths out short-term market noise
⚡ Market Condition Adaptation
Volatile Markets: Use shorter lookback (3-5 days) for tighter ranges
Trending Markets: Use longer lookback (14-21 days) for broader context
Ranging Markets: Use medium lookback (7-10 days) for clear boundaries
🎯 Timeframe Optimization
1-minute charts: 1-2 day lookback
5-minute charts: 2-5 day lookback
Hourly charts: 7-14 day lookback
Daily charts: 21-50 day lookback
Trading Applications
Scalping Setup (2-day lookback):
Super tight range for quick reversals
ZTI 800+ = immediate short opportunity
ZTI 200- = immediate long opportunity
Swing Trading Setup (10-day lookback):
Meaningful swing levels captured
ZTI extremes = high-probability reversal zones
More stable signals, reduced whipsaws
Advanced Usage
🔧 Real-Time Adaptability
Trending days: Increase to 14+ days for broader perspective
Range-bound days: Decrease to 3 days for tighter signals
High volatility: Shorter lookback for responsiveness
Low volatility: Longer lookback to avoid false signals
💡 Multi-Timeframe Approach
Entry signals: Use 7-day ZTI on main timeframe
Trend confirmation: Use 21-day ZTI on higher timeframe
Exit timing: Use 3-day ZTI for precise exits
🌐 Session Optimization
Asian session: Shorter lookback (3-5 days) for range-bound conditions
London/NY session: Longer lookback (7-14 days) for trending conditions
How It Works
The indicator maps the current price position within the specified lookback period directly to a 0-1000 scale and plots it using ZLEMA (Zero Lag Exponential Moving Average) which has the least lag of the available popular moving averages:
Price at recent high = ZTI at 1000
Price at recent low = ZTI at 1
Price at mid-range = ZTI at 500
This creates perfect proportional representation where every price movement translates directly to corresponding ZTI movement, eliminating the false signals common in traditional oscillators.
This single, versatile indicator adapts to any market condition, timeframe, or trading style through one simple parameter adjustment, making it an essential tool for traders at every level.
Credits
ZLEMA techniques widely attributed to John Ehlers.
Disclaimer
This tool is for educational purposes only and is not financial advice. Backtest and forward‑test before live use, and always manage risk.
Please note that I set this as closed source to prevent source code cloning by others, repackaging and republishing which results in multiple confusing choices of the same indicator.
Volume Momentum [BackQuant]Volume Momentum
The Volume Momentum indicator is designed to help traders identify shifts in market momentum based on volume data. By analyzing the relative volume momentum, this indicator provides insights into whether the market is gaining strength (uptrend) or losing momentum (downtrend). The strategy uses a combination of percentile-based volume normalization, weighted moving averages (WMA), and exponential moving averages (EMA) to assess volume trends.
The system focuses on the relationship between price and volume, utilizing normalized volume data to highlight key market changes. This approach allows traders to focus on volume-driven price movements, helping them to capture momentum shifts early.
Key Features
1. Volume Normalization and Percentile Calculation:
The signed volume (positive when the close is higher than the open, negative when the close is lower) is normalized against the rolling average volume. This normalized volume is then subjected to a percentile interpolation, allowing for a robust statistical measure of how the current volume compares to historical data. The percentile level is customizable, with 50 representing the median.
2. Weighted and Smoothed Moving Averages for Trend Detection:
The normalized volume is smoothed using weighted moving averages (WMA) and exponential moving averages (EMA). These smoothing techniques help eliminate noise, providing a clearer view of the underlying momentum. The WMA filters out short-term fluctuations, while the EMA ensures that the most recent data points have a higher weight, making the system more responsive to current market conditions.
3. Trend Reversal Detection:
The indicator detects momentum shifts by evaluating whether the volume momentum crosses above or below zero. A positive volume momentum indicates a potential uptrend, while a negative momentum suggests a possible downtrend. These trend reversals are identified through crossover and crossunder conditions, triggering alerts when significant changes occur.
4. Dynamic Trend Background and Bar Coloring:
The script offers customizable background coloring based on the trend direction. When volume momentum is positive, the background is colored green, indicating a bullish trend. When volume momentum is negative, the background is colored red, signaling a bearish trend. Additionally, the bars themselves can be colored based on the trend, further helping traders quickly visualize market momentum.
5. Alerts for Momentum Shifts:
The system provides real-time alerts for traders to monitor when volume momentum crosses a critical threshold (zero), signaling a trend reversal. The alerts notify traders when the market momentum turns bullish or bearish, assisting them in making timely decisions.
6. Customizable Parameters for Flexible Usage:
Users can fine-tune the behavior of the indicator by adjusting various parameters:
Volume Rolling Mean: The period used to calculate the average volume for normalization.
Percentile Interpolation Length: Defines the range over which the percentile is calculated.
Percentile Level: Determines the percentile threshold (e.g., 50 for the median).
WMA and Smoothing Periods: Control the smoothing and response time of the indicator.
7. Trend Background Visualization and Trend-Based Bar Coloring:
The background fill is shaded according to whether the volume momentum is positive or negative, providing a visual cue to indicate market strength. Additionally, bars can be color-coded to highlight the trend, making it easier to see the trend’s direction without needing to analyze numerical data manually.
8. Note on Mean-Reversion Strategy:
If you take the inverse of the signals, this indicator can be adapted for a mean-reversion strategy. Instead of following the trend, the strategy would involve buying assets that are underperforming and selling assets that are overperforming, based on volume momentum. However, it’s important to note that this approach may not work effectively on highly correlated assets, as their price movements may be too similar, reducing the effectiveness of the mean-reversion strategy.
Final Thoughts
The Volume Momentum indicator offers a comprehensive approach to analyzing volume-based momentum shifts in the market. By using volume normalization, percentile interpolation, and smoothed moving averages, this system helps identify the strength and direction of market trends. Whether used for trend-following or adapted for mean-reversion, this tool provides traders with actionable insights into the market’s volume-driven movements, improving decision-making and portfolio management.
TrendTwisterV1.5 (Forex Ready + Indicators)A Precision Trend-Following TradingView Strategy for Forex**
HullShiftFX is a Pine Script strategy for TradingView that combines the power of the **Hull Moving Average (HMA)** and a **shifted Exponential Moving Average (EMA)** with multi-layered momentum filters including **RSI** and **dual Stochastic Oscillators**.
It’s designed for traders looking to catch high-probability breakouts with tight risk management and visual clarity.
Chart settings:
1. Select "Auto - Fits data to screen"
2. Please Select "Scale Price Chart Only" (To make the chart not squished)
### ✅ Entry Conditions
**Long Position:**
- Price closes above the 12-period Hull Moving Average.
- Price closes above the 5-period EMA shifted forward by 2 bars.
- RSI is above 50.
- Stochastic Oscillator (12,3,3) %K is above 50.
- Stochastic Oscillator (5,3,3) %K is above 50.
- Hull MA crosses above the shifted EMA.
**Short Position:**
- Price closes below the 12-period Hull Moving Average.
- Price closes below the 5-period EMA shifted forward by 2 bars.
- RSI is below 50.
- Stochastic Oscillator (12,3,3) %K is below 50.
- Stochastic Oscillator (5,3,3) %K is below 50.
- Hull MA crosses below the shifted EMA.
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## 📉 Risk Management
- **Stop Loss:** Set at the low (for long) or high (for short) of the previous 2 candles.
- **Take Profit:** Calculated at a risk/reward ratio of **1.65x** the stop loss distance.
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## 📊 Indicators Used
- **Hull Moving Average (12)**
- **Exponential Moving Average (5) **
- **Relative Strength Index (14)**
- **Stochastic Oscillators:**
- %K (12,3,3)
- %K (5,3,3)
EMA 21 and SMA 50 Low ConditionsDescription:
This indicator highlights trend zones on a daily chart using the 21-day Exponential Moving Average (EMA) and 50-day Simple Moving Average (SMA). It’s designed to identify bullish conditions with two distinct background colors:
• Green Background: Signals a strong bullish trend. Appears when the low of the candle stays above the 21 EMA for 3 or more consecutive days, with either the 3rd or 4th day closing higher than its open (an “up” day). The green zone persists until a candle closes below the 21 EMA.
• Yellow Background: Indicates a potential support zone. Triggers when the low of the candle remains above the 50 SMA after the green condition ends, suggesting the price is still holding above a longer-term average. The yellow zone lasts until a candle closes below the 50 SMA.
Features:
• Plots the 21 EMA (blue line) and 50 SMA (orange line) for visual reference.
• Uses background colors to mark trend zones, making it easy to spot bullish phases and support levels.
• Optimized for daily timeframes, ideal for swing traders or long-term trend followers.
How to Use:
1. Apply the indicator to a daily chart.
2. Watch for the green background to identify strong bullish momentum (lows holding above the 21 EMA with an up close confirmation).
3. Look for the yellow background as a sign of potential support after the short-term trend weakens (lows above the 50 SMA).
4. Exit zones are triggered by closes below the respective averages (21 EMA for green, 50 SMA for yellow).
Notes:
• Best used on symbols with sufficient historical data to ensure accurate EMA and SMA calculations.
• The indicator prioritizes the green condition over yellow—green will override if both could apply.
Author’s Intent:
Created to help traders visualize sustained bullish trends and key support levels using simple moving average rules. Perfect for confirming uptrends and monitoring pullbacks within a broader bullish context.
Volume Flow with Bollinger Bands and EMA Cross SignalsThe Volume Flow with Bollinger Bands and EMA Cross Signals indicator is a custom technical analysis tool designed to identify potential buy and sell signals based on several key components:
Volume Flow: This component combines price movement and trading volume to create a signal that indicates the strength or weakness of price movements. When the price is rising with increasing volume, it suggests strong buying activity, whereas falling prices with increasing volume indicate strong selling pressure.
Bollinger Bands: Bollinger Bands consist of three lines:
The Basis (middle line), which is a Simple Moving Average (SMA) of the price over a set period.
The Upper Band, which is the Basis plus a multiple of the standard deviation (typically 2).
The Lower Band, which is the Basis minus a multiple of the standard deviation. Bollinger Bands help identify periods of high volatility and potential overbought/oversold conditions. When the price touches the upper band, it might indicate that the market is overbought, while touching the lower band might indicate oversold conditions.
EMA Crossovers: The script includes two Exponential Moving Averages (EMAs):
Fast EMA: A shorter-term EMA, typically more sensitive to price changes.
Slow EMA: A longer-term EMA, responding slower to price changes. The crossover of the Fast EMA crossing above the Slow EMA (bullish crossover) signals a potential buy opportunity, while the Fast EMA crossing below the Slow EMA (bearish crossover) signals a potential sell opportunity.
Background Color and Candle Color: The indicator highlights the chart's background with specific colors based on the signals:
Green background for buy signals.
Yellow background for sell signals. Additionally, the candles are colored green for buy signals and yellow for sell signals to visually reinforce the trade opportunities.
Buy/Sell Labels: Small labels are placed on the chart:
"BUY" label in green is placed below the bar when a buy signal is generated.
"SELL" label in yellow is placed above the bar when a sell signal is generated.
Working of the Indicator:
Volume Flow Calculation: The Volume Flow is calculated by multiplying the price change (current close minus the previous close) with the volume. This product is then smoothed with a Simple Moving Average (SMA) over a user-defined period (length). The result is then multiplied by a multiplier to adjust its sensitivity.
Price Change = close - close
Volume Flow = Price Change * Volume
Smoothed Volume Flow = SMA(Volume Flow, length)
The Volume Flow Signal is then: Smooth Volume Flow * Multiplier
This calculation represents the buying or selling pressure in the market.
Bollinger Bands: Bollinger Bands are calculated using the Simple Moving Average (SMA) of the closing price (basis) and the Standard Deviation (stdev) of the price over a period defined by the user (bb_length).
Basis (Middle Band) = SMA(close, bb_length)
Upper Band = Basis + (bb_std_dev * Stdev)
Lower Band = Basis - (bb_std_dev * Stdev)
The upper and lower bands are plotted alongside the price to identify the price's volatility. When the price is near the upper band, it could be overbought, and near the lower band, it could be oversold.
EMA Crossovers: The Fast EMA and Slow EMA are calculated using the Exponential Moving Average (EMA) function. The crossovers are detected by checking:
Buy Signal (Bullish Crossover): When the Fast EMA crosses above the Slow EMA.
Sell Signal (Bearish Crossover): When the Fast EMA crosses below the Slow EMA.
The long_condition variable checks if the Fast EMA crosses above the Slow EMA, and the short_condition checks if it crosses below.
Visual Signals:
Background Color: The background is colored green for a buy signal and yellow for a sell signal. This gives an immediate visual cue to the trader.
Bar Color: The candles are colored green for buy signals and yellow for sell signals.
Labels:
A "BUY" label in green appears below the bar when the Fast EMA crosses above the Slow EMA.
A "SELL" label in yellow appears above the bar when the Fast EMA crosses below the Slow EMA.
Summary of Buy/Sell Logic:
Buy Signal:
The Fast EMA crosses above the Slow EMA (bullish crossover).
Volume flow is positive, indicating buying pressure.
Background turns green and candles are colored green.
A "BUY" label appears below the bar.
Sell Signal:
The Fast EMA crosses below the Slow EMA (bearish crossover).
Volume flow is negative, indicating selling pressure.
Background turns yellow and candles are colored yellow.
A "SELL" label appears above the bar.
Usage of the Indicator:
This indicator is designed to help traders identify potential entry (buy) and exit (sell) points based on:
The interaction of Exponential Moving Averages (EMAs).
The strength and direction of Volume Flow.
Price volatility using Bollinger Bands.
By combining these components, the indicator provides a comprehensive view of market conditions, helping traders make informed decisions on when to enter and exit trades.
NasyI## NasyI - Multi-Timeframe Technical Analysis Toolkit
### English Description
**NasyI** is a comprehensive technical analysis indicator designed to provide traders with a complete view of market dynamics across multiple timeframes. This indicator combines the power of Exponential Moving Averages (EMAs), Simple Moving Averages (MAs), Volume Weighted Average Price (VWAP), and key support/resistance levels to help traders identify trend direction, potential reversal points, and optimal entry/exit opportunities.
#### Key Features
1. **Multi-Timeframe Analysis System**
- 2-minute EMAs (13, 48) for ultra-short-term trend identification
- 5-minute EMAs (9, 13, 21, 48, 200) for short-term trend confirmation
- Daily EMAs (5, 13, 21, 48, 100, 200) and MAs (20, 50, 100, 200) for longer-term perspective
- Color-coded bands between key EMAs to visually identify trend strength and direction
2. **Advanced VWAP Integration**
- Daily VWAP for intraday support/resistance
- Weekly VWAP for medium-term price reference
- Monthly VWAP for long-term institutional price levels
- All VWAPs properly reset at their respective time period boundaries
3. **Critical Price Level Identification**
- Previous day high/low lines for identifying key breakout and breakdown levels
- Pre-market high/low tracking to identify potential intraday support/resistance zones
- All levels displayed with distinct line styles for easy identification
4. **Dynamic Trend Analysis**
- Color-coded bands between EMAs display trend strength and direction:
- Green bands indicate uptrend conditions (9 EMA > 21 EMA > 48 EMA)
- Red bands indicate downtrend conditions (9 EMA < 21 EMA < 48 EMA)
- Yellow bands indicate neutral/confused market conditions
- Visual representation makes trend changes immediately apparent
5. **Comprehensive Customization Options**
- Fully customizable colors for all indicators and bands
- Adjustable transparency settings for visual clarity
- Optional price labels with customizable placement and appearance
- Ability to show/hide specific components based on trading preferences
#### Trading Applications
This indicator is particularly valuable for:
1. **Day Trading & Scalping**: The 2-minute and 5-minute EMAs with color bands provide clear short-term trend direction and potential reversal signals.
2. **Swing Trading**: Daily EMAs and MAs offer perspective on the larger trend, helping to align short-term trades with the broader market direction.
3. **Gap Trading**: Previous day and pre-market levels help identify potential gap fill scenarios and breakout/breakdown opportunities.
4. **VWAP Trading Strategies**: Multiple timeframe VWAPs allow for identifying institutional participation levels and potential reversal zones.
5. **EMA Cross Systems**: The various EMAs can be used to identify golden crosses and death crosses across multiple timeframes.
#### How the Components Work Together
The power of NasyI comes from the integration of these different technical elements:
1. The short-timeframe EMAs (2m, 5m) provide immediate trend information, while the daily EMAs/MAs provide context about the larger market structure.
2. The color bands between EMAs offer instant visual confirmation of trend alignment or divergence across timeframes.
3. Previous day and pre-market levels add horizontal support/resistance zones to complement the dynamic moving averages.
4. Multiple timeframe VWAPs provide additional confirmation of institutional activity levels and potential reversal points.
By combining these elements, traders can develop a comprehensive market view that integrates price action, trend direction, and key support/resistance levels all in one indicator.
#### Usage Instructions
1. Apply the NasyI indicator to your chart (works best on intraday timeframes from 1-minute to 30-minute).
2. Observe the relationship between price and the various EMAs:
- Price above the 2m/5m EMAs with green bands indicates bullish short-term conditions
- Price below the 2m/5m EMAs with red bands indicates bearish short-term conditions
3. Use the daily EMAs/MAs and VWAPs as targets for potential price movements and reversal zones.
4. Previous day and pre-market high/low lines provide key levels to watch for breakouts or breakdowns.
5. Customize the appearance according to your preferences using the extensive settings options.
This indicator represents a unique approach to technical analysis by combining multiple timeframe perspectives into a single, visually intuitive display that helps traders make more informed decisions based on a comprehensive view of market conditions.
### 中文描述
**NasyI** 是一个全面的技术分析指标，旨在为交易者提供跨多个时间周期的完整市场动态视图。该指标结合了指数移动平均线（EMA）、简单移动平均线（MA）、成交量加权平均价格（VWAP）和关键支撑/阻力水平的力量，帮助交易者识别趋势方向、潜在反转点和最佳进出场机会。
#### 主要特点
1. **多时间周期分析系统**
- 2分钟EMAs（13，48）用于超短期趋势识别
- 5分钟EMAs（9，13，21，48，200）用于短期趋势确认
- 日线EMAs（5，13，21，48，100，200）和MAs（20，50，100，200）用于更长期的视角
- 关键EMAs之间的彩色带状区域直观显示趋势强度和方向
2. **高级VWAP整合**
- 日内VWAP作为日内支撑/阻力
- 周内VWAP作为中期价格参考
- 月内VWAP作为长期机构价格水平
- 所有VWAP在各自的时间周期边界正确重置
3. **关键价格水平识别**
- 前一交易日高点/低点线用于识别关键突破和跌破水平
- 盘前高点/低点跟踪用于识别潜在的日内支撑/阻力区域
- 所有水平以不同的线条样式显示，便于识别
4. **动态趋势分析**
- EMAs之间的彩色带状区域显示趋势强度和方向：
- 绿色带状区域表示上升趋势（9 EMA > 21 EMA > 48 EMA）
- 红色带状区域表示下降趋势（9 EMA < 21 EMA < 48 EMA）
- 黄色带状区域表示中性/混乱市场条件
- 视觉表示使趋势变化立即显现
5. **全面的自定义选项**
- 所有指标和带状区域的颜色完全可定制
- 可调节的透明度设置，提高视觉清晰度
- 可选的价格标签，带有可定制的位置和外观
- 能够根据交易偏好显示/隐藏特定组件
#### 交易应用
此指标对以下方面特别有价值：
1. **日内交易和短线交易**：2分钟和5分钟EMAs与色带提供清晰的短期趋势方向和潜在反转信号。
2. **摇摆交易**：日线EMAs和MAs提供对更大趋势的视角，帮助将短期交易与更广泛的市场方向对齐。
3. **缺口交易**：前一日和盘前水平帮助识别潜在的缺口填充情况和突破/跌破机会。
4. **VWAP交易策略**：多时间周期VWAP允许识别机构参与水平和潜在反转区域。
5. **EMA交叉系统**：各种EMAs可用于识别跨多个时间周期的黄金交叉和死亡交叉。
#### 组件如何协同工作
NasyI的强大之处在于这些不同技术元素的集成：
1. 短时间周期EMAs（2m，5m）提供即时趋势信息，而日线EMAs/MAs提供关于更大市场结构的背景。
2. EMAs之间的色带提供趋势对齐或跨时间周期分歧的即时视觉确认。
3. 前一日和盘前水平添加水平支撑/阻力区域，补充动态移动平均线。
4. 多时间周期VWAP提供机构活动水平和潜在反转点的额外确认。
通过结合这些元素，交易者可以发展出全面的市场视图，整合价格行动、趋势方向和关键支撑/阻力水平于一个指标中。
#### 使用说明
1. 将NasyI指标应用到您的图表上（最适合1分钟至30分钟的日内时间周期）。
2. 观察价格与各种EMAs之间的关系：
- 价格位于2m/5m EMAs之上，带有绿色带状区域，表示看涨的短期条件
- 价格位于2m/5m EMAs之下，带有红色带状区域，表示看跌的短期条件
3. 使用日线EMAs/MAs和VWAPs作为潜在价格移动和反转区域的目标。
4. 前一日和盘前高点/低点线提供需要关注的突破或跌破的关键水平。
5. 使用广泛的设置选项根据您的偏好自定义外观。
这个指标代表了一种独特的技术分析方法，将多个时间周期的视角结合到一个单一的、视觉直观的显示中，帮助交易者基于对市场条件的全面视图做出更明智的决策。
Mile Runner - Swing Trade LONGMile Runner - Swing Trade LONG Indicator - By @jerolourenco
Overview
The Mile Runner - Swing Trade LONG indicator is designed for swing traders who focus on LONG positions in stocks, BDRs (Brazilian Depositary Receipts), and ETFs. It provides clear entry signals, stop loss, and take profit levels, helping traders identify optimal buying opportunities with a robust set of technical filters. The indicator is optimized for daily candlestick charts and combines multiple technical analysis tools to ensure high-probability trades.
Key Features
Entry Signals: Visualized as green triangles below the price bars, indicating a potential LONG entry.
Stop Loss and Take Profit Levels: Automatically plotted on the chart for easy reference.
Stop Loss: Based on the most recent pivot low (support level).
Take Profit: Calculated using a Fibonacci-based projection from the entry price to the stop loss.
Trend and Momentum Filters: Ensures trades align with the prevailing trend and have sufficient momentum.
Volume and Volatility Confirmation: Verifies market interest and price movement potential.
How It Works
The indicator uses a combination of technical tools to filter and confirm trade setups:
Exponential Moving Averages (EMAs):
A short EMA (default: 9 periods) and a long EMA (default: 21 periods) identify the trend.
A bullish crossover (EMA9 crosses above EMA21) signals a potential upward trend.
Money Flow Index (MFI):
Confirms buying pressure when MFI > 50.
Average True Range (ATR):
Ensures sufficient volatility by checking if ATR exceeds its 20-period moving average.
Volume:
Confirms market interest when volume exceeds its 20-period moving average.
Pivot Lows:
Identifies recent support levels (pivot lows) to set the stop loss.
Ensures the pivot low is recent (within the last 10 bars by default).
Additional Trend Filter:
Confirms the long EMA is rising, reinforcing the bullish trend.
Inputs and Customization
The indicator is highly customizable, allowing traders to tailor it to their strategies:
EMA Periods: Adjust the short and long EMA lengths.
ATR and MFI Periods: Modify lookback periods for volatility and momentum.
Pivot Lookback: Control the sensitivity of pivot low detection.
Fibonacci Level: Adjust the Fibonacci retracement level for take profit.
Take Profit Multiplier: Fine-tune the aggressiveness of the take profit target.
Max Pivot Age: Set the maximum bars since the last pivot low for relevance.
Usage Instructions
Apply the Indicator:
Add the "Mile Runner - Swing Trade LONG" indicator to your TradingView chart.
Best used on daily charts for swing trading.
Look for Entry Signals:
A green triangle below the price bar signals a potential LONG entry.
Set Stop Loss and Take Profit:
Stop Loss: Red dashed line indicating the stop loss level.
Take Profit: Purple dashed line showing the take profit level.
Monitor the Trade:
The entry price is marked with a green dashed line for reference.
Adjust trade management based on the plotted levels.
Set Alerts:
Use the built-in alert condition to get notified of new LONG entry signals.
Important Notes
For LONG Positions Only : Designed exclusively for swing trading LONG positions.
Timeframe: Optimized for daily charts but can be tested on other timeframes.
Asset Types: Works best with stocks, BDRs, and ETFs.
Risk Management: Always align stop loss and take profit levels with your risk tolerance.
Why Use Mile Runner?
The Mile Runner indicator simplifies swing trading by integrating trend, momentum, volume, and volatility filters into one user-friendly tool. It helps traders:
Identify high-probability entry points.
Establish clear stop loss and take profit levels.
Avoid low-volatility or low-volume markets.
Focus on assets with strong buying pressure and recent support.
By following its signals and levels, traders can make informed decisions and enhance their swing trading performance. Customize the inputs and test it on your favorite assets—happy trading!
Cometreon_Public📚 Cometreon Public Library – Advanced Functions for Pine Script
This library contains advanced functions used in my public indicators on TradingView. The goal is to make the code more modular and efficient, allowing users to call pre-built functions for complex calculations without rewriting them from scratch.
🔹 Currently Available Functions:
1️⃣ Moving Average Function – Provides multiple types of moving averages to choose from, including:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
2️⃣ Custom RSI – Uses the Moving Average function to modify the calculation method, with an additional option for a dynamic version.
3️⃣ Custom MACD – Uses the Moving Average function to modify the calculation method, with an additional option for a dynamic version.
4️⃣ Custom Alligator – Uses the Moving Average function to modify generic calculations, allowing users to change the calculation method.
[blackcat] L2 Enhanced MACD Trend█ OVERVIEW
The Enhanced MACD Trend script combines traditional Moving Average Convergence Divergence (MACD) analysis with On-Balance Volume (OBV) insights to provide traders with a comprehensive understanding of market trends. By examining both price momentum and volume fluctuations, this tool aids in identifying potential upward or downward market transitions.
█ LOGICAL FRAMEWORK
Initially, the script prompts users to configure fundamental parameters such as the speed of moving averages. It subsequently utilizes a specialized auxiliary function named calculate_macd_obv_signals to perform intricate computations. This function calculates the discrepancy between two distinct types of moving averages (captured via MACD analysis), evaluates the direction of capital inflows and outflows within securities (using OBV), and applies smoothing techniques to mitigate undue influence from minor fluctuations. Ultimately, visual representations of these calculations are rendered on an additional chart pane for enhanced interpretability.
█ CUSTOM FUNCTIONS
Function: calculate_macd_obv_signals
• Purpose: Determines critical aspects associated with MACD and OBV.
• Parameters:
• fastLength (int): Dictates the responsiveness of the shorter Exponential Moving Average (EMA) to price variations.
• slowLength (int): Specifies the reactivity of the longer EMA.
• signalSmoothing (int): Defines the degree of smoothness applied to the divergence between EMAs.
• Functionality:
• macd_diff: Illustrates whether price increases have accelerated relative to previous levels or decelerated, providing insight into existing momentum.
• macd_signal_line: Smoothens macd_diff values, serving akin to a trailing indicator for macd_diff.
• macd_histogram: Visually accentuates disparities between macd_diff and macd_signal_line employing color-coded bars, facilitating identification of significant divergences.
• obv_signal: Represents a refined variant of short-term OBV concentrating solely on periods characterized by elevated buying interest, aiding in reduction of extraneous signals.
• moving_average_short: Analyzes recent closing prices across several sessions to corroborate burgeoning bullish or bearish tendencies.
• Returns: An array encompassing .
█ KEY POINTS AND TECHNIQUES
Advanced Features: Employs sophisticated functions including ta.ema() and ta.sma(), enabling accurate calculation of EMAs and SMAs respectively, thus enhancing precision in trend detection.
Optimization Techniques: Incorporates customizable inputs (input.int) permitting strategic adjustments alongside scrutiny of escalating or declining volumes to accurately gauge genuine sentiment shifts while discounting insignificant anomalies.
Best Practices: Maintains separation between algorithmic processes and graphical outputs, preserving organizational clarity; hence simplifying debugging efforts and future enhancements.
Unique Approaches: Integrates multifaceted assessments simultaneously – amalgamating candlestick formations and volumetric activities – offering a holistic perspective instead of reliance on singular indicators. Consequently, delivers astute recommendations grounded in diverse analytical underpinnings rather than speculative forecasts.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
Potential Modifications:
1 — Implement automated alert mechanisms signaling crossover events pinpointing optimal buy/sell junctures to fine-tune timing preemptively minimizing losses proactively.
2 — Enable user customization of sensitivity criteria governing trigger intensity thereby eliminating trivial aberrations and emphasizing substantial patterns exclusively.
Application Scenarios:
Beneficial for high-frequency trading aiming to capitalize on fleeting price movements swiftly. Suitable for dynamic environments necessitating rapid responses due to frequent market volatility demanding prompt reactions. Perfect for individuals engaging in regular transactions seeking unparalleled accuracy navigating fluctuating circumstances ensuring consistent profitability amidst disturbances maintaining steady yields irrespective of upheavals.
Related Concepts:
Contemplate interactions among oscillators (such as MACD) and volume metrics detecting instances wherein they oppose each other (indicative of divergences) or concur (signaling crossovers). Profound comprehension of these interrelationships substantially refines trading strategies integrating broader economic factors, seasonal influences guiding overarching plans resulting in heightened predictive capabilities elevating trading effectiveness leveraging cumulative information transforming unprocessed statistics into actionable intelligence empowering informed decisions advancing confidently toward objectives effortlessly scaling achievements seamlessly realizing aspirations effortlessly.
Median Deviation Suite [InvestorUnknown]The Median Deviation Suite uses a median-based baseline derived from a Double Exponential Moving Average (DEMA) and layers multiple deviation measures around it. By comparing price to these deviation-based ranges, it attempts to identify trends and potential turning points in the market. The indicator also incorporates several deviation types—Average Absolute Deviation (AAD), Median Absolute Deviation (MAD), Standard Deviation (STDEV), and Average True Range (ATR)—allowing traders to visualize different forms of volatility and dispersion. Users should calibrate the settings to suit their specific trading approach, as the default values are not optimized.
Core Components
Median of a DEMA:
The foundation of the indicator is a Median applied to the 7-day DEMA (Double Exponential Moving Average). DEMA aims to reduce lag compared to simple or exponential moving averages. By then taking a median over median_len periods of the DEMA values, the indicator creates a robust and stable central tendency line.
float dema = ta.dema(src, 7)
float median = ta.median(dema, median_len)
Multiple Deviation Measures:
Around this median, the indicator calculates several measures of dispersion:
ATR (Average True Range): A popular volatility measure.
STDEV (Standard Deviation): Measures the spread of price data from its mean.
MAD (Median Absolute Deviation): A robust measure of variability less influenced by outliers.
AAD (Average Absolute Deviation): Similar to MAD, but uses the mean absolute deviation instead of median.
Average of Deviations (avg_dev): The average of the above four measures (ATR, STDEV, MAD, AAD), providing a combined sense of volatility.
Each measure is multiplied by a user-defined multiplier (dev_mul) to scale the width of the bands.
aad = f_aad(src, dev_len, median) * dev_mul
mad = f_mad(src, dev_len, median) * dev_mul
stdev = ta.stdev(src, dev_len) * dev_mul
atr = ta.atr(dev_len) * dev_mul
avg_dev = math.avg(aad, mad, stdev, atr)
Deviation-Based Bands:
The indicator creates multiple upper and lower lines based on each deviation type. For example, using MAD:
float mad_p = median + mad // already multiplied by dev_mul
float mad_m = median - mad
Similar calculations are done for AAD, STDEV, ATR, and the average of these deviations. The indicator then determines the overall upper and lower boundaries by combining these lines:
float upper = f_max4(aad_p, mad_p, stdev_p, atr_p)
float lower = f_min4(aad_m, mad_m, stdev_m, atr_m)
float upper2 = f_min4(aad_p, mad_p, stdev_p, atr_p)
float lower2 = f_max4(aad_m, mad_m, stdev_m, atr_m)
This creates a layered structure of volatility envelopes. Traders can observe which layers price interacts with to gauge trend strength.
Determining Trend
The indicator generates trend signals by assessing where price stands relative to these deviation-based lines. It assigns a trend score by summing individual signals from each deviation measure. For instance, if price crosses above the MAD-based upper line, it contributes a bullish point; crossing below an ATR-based lower line contributes a bearish point.
When the aggregated trend score crosses above zero, it suggests a shift towards a bullish environment; crossing below zero indicates a bearish bias.
// Define Trend scores
var int aad_t = 0
if ta.crossover(src, aad_p)
aad_t := 1
if ta.crossunder(src, aad_m)
aad_t := -1
var int mad_t = 0
if ta.crossover(src, mad_p)
mad_t := 1
if ta.crossunder(src, mad_m)
mad_t := -1
var int stdev_t = 0
if ta.crossover(src, stdev_p)
stdev_t := 1
if ta.crossunder(src, stdev_m)
stdev_t := -1
var int atr_t = 0
if ta.crossover(src, atr_p)
atr_t := 1
if ta.crossunder(src, atr_m)
atr_t := -1
var int adev_t = 0
if ta.crossover(src, adev_p)
adev_t := 1
if ta.crossunder(src, adev_m)
adev_t := -1
int upper_t = src > upper ? 3 : 0
int lower_t = src < lower ? 0 : -3
int upper2_t = src > upper2 ? 1 : 0
int lower2_t = src < lower2 ? 0 : -1
float trend = aad_t + mad_t + stdev_t + atr_t + adev_t + upper_t + lower_t + upper2_t + lower2_t
var float sig = 0
if ta.crossover(trend, 0)
sig := 1
else if ta.crossunder(trend, 0)
sig := -1
Practical Usage and Calibration
Default settings are not optimized: The given parameters serve as a starting point for demonstration. Users should adjust:
median_len: Affects how smooth and lagging the median of the DEMA is.
dev_len and dev_mul: Influence the sensitivity of the deviation measures. Larger multipliers widen the bands, potentially reducing false signals but introducing more lag. Smaller multipliers tighten the bands, producing quicker signals but potentially more whipsaws.
This flexibility allows the trader to tailor the indicator for various markets (stocks, forex, crypto) and time frames.
Backtesting and Performance Metrics
The code integrates with a backtesting library that allows traders to:
Evaluate the strategy historically
Compare the indicator’s signals with a simple buy-and-hold approach
Generate performance metrics (e.g., mean returns, Sharpe Ratio, Sortino Ratio) to assess historical effectiveness.
Disclaimer
No guaranteed results: Historical performance does not guarantee future outcomes. Market conditions can vary widely.
User responsibility: Traders should combine this indicator with other forms of analysis, appropriate risk management, and careful calibration of parameters.
Trend Condition [TradersPro]
OVERVIEW
The Trend Condition Indicator measures the strength of the bullish or bearish trend by using a ribbon pattern of exponential moving averages and scoring system. Trend cycles naturally expand and contract as a normal part of the cycle. It is the rhythm of the market. Perpetual expansion and contraction of trend.
As trend cycles develop the indicator shows a compression of the averages. These compression zones are key locations as trends typically expand from there. The expansion of trend can be up or down.
As the trend advances the ribbon effect of the indicator can be seen as each average expands with the price action. Once they have “fanned” the probability of the current trend slowing is high.
This can be used to recognize a powerful trend may be concluding. Traders can tighten stops, exit positions or utilize other prudent strategies.
CONCEPTS
Each line will display green if it is higher than the prior period and red if it is lower than the prior period. If the average is green it is considered bullish and will score one point in the bullish display. Red lines are considered bearish and will score one point in the bearish display.
The indicator can then be used at a quick glance to see the number of averages that are bullish and the number that are bearish.
A trader may use these on any tradable instrument. They can be helpful in stock portfolio management when used with an index like the S&P 500 to determine the strength of the current market trend. This may affect trade decisions like possession size, stop location and other risk factors.
