Twin Range Filter VisualizedVisulaized version of @colinmck's Twin Range Filter version on TradingView.
On @colinmck's Twin Range Filter version, you can only see Long and Short signals on the chart.
But in this version of TRF, users can visually see the BUY and SELL signals on the chart with an added line of TRF.
TRF is an average of two smoothed Exponential Moving Averages, fast one has 27 bars of length and the slow one has 55 bars.
The purpose is to obtain two ranges that price fluctuates between (upper and lower range) and have LONG AND SHORT SIGNALS when close price crosses above the upper range and conversely crosses below lower range.
I personally combine the upper and lower ranges on one line to see the long and short signals with my own eyes so,
-BUY when price is higher or equal to the upper range level and the indicator line turns to draw the lower range to follow the price just under the bars as a trailing stop loss indicator like SuperTrend.
-SELL when price is lower or equal to the lower range levelline under the bars and then the indicator line turns to draw the upper range to follow the price just over the bars in that same trailing stop loss logic.
There are also two coefficients that adjusts the trailing line distance levels from the price multiplying the effect of the faster and slower moving averages.
The default values of the multipliers:
Fast range multiplier of Fast Moving Average(27): 1.6
Slow range multiplier of fSlow Moving Average(55): 2
Remember that if you enlarge these multipliers you will enlarge the ranges and have less but lagging signals. Conversely, decreasing the multipliers will have small ranges (line will get closer to the price and more signals will occur)
Cerca negli script per "supertrend"
Moving Average SARHello Traders,
Today, I have brought to you an indicator that utilizes the Parabolic SAR.
To begin with, the Parabolic SAR is an indicator that trails the price in the form of a parabola, seeking out Stop And Reverse points.
The indicator I present merges the calculation formula of the Parabolic SAR with the Moving Average.
One aspect I pondered over was how to determine the starting point of this SAR. Trailing the price flow with the logic set by the moving average was fine, but the question was where to begin.
My approach involves a variable I call 'sensitiveness,' which automatically adjusts the length according to the timeframe you are observing. Using pinescript's math.ceil, I formulated:
interval_to_len = timeframe.multiplier * (timeframe.isdaily ? 1440 : timeframe.isweekly ? 1440 * 7 : timeframe.ismonthly ? 1440 * 30 : 1)
main_len = math.ceil(sensitiveness / interval_to_len)
This formula represents the length, and through variables like:
_highest = math.min(ta.highest(high, main_len), close + ta.atr(46)*4)
_lowest = math.max(ta.lowest(low, main_len), close - ta.atr(46)*4)
I have managed to set the risk at a level that does not impose too great a burden.
Moreover, the 'Trend Strength Parameter' allows you to choose how strongly to trail the current price.
Lastly, think of the Band Width as a margin for accepting changes in the trend. As the value increases, the Band Width expands, measured through the ATR.
This indicator is particularly useful for holding positions and implementing trailing stops. It will be especially beneficial for those interested in price tracking of trends, like with Parabolic SAR or Supertrend.
I hope you find this tool useful.
AI-Bank-Nifty Tech AnalysisThis code is a TradingView indicator that analyzes the Bank Nifty index of the Indian stock market. It uses various inputs to customize the indicator's appearance and analysis, such as enabling analysis based on the chart's timeframe, detecting bullish and bearish engulfing candles, and setting the table position and style.
The code imports an external script called BankNifty_CSM, which likely contains functions that calculate technical indicators such as the RSI, MACD, VWAP, and more. The code then defines several table cell colors and other styling parameters.
Next, the code defines a table to display the technical analysis of eight bank stocks in the Bank Nifty index. It then defines a function called get_BankComponent_Details that takes a stock symbol as input, requests the stock's OHLCV data, and calculates several technical indicators using the imported CSM_BankNifty functions.
The code also defines two functions called get_EngulfingBullish_Detection and get_EngulfingBearish_Detection to detect bullish and bearish engulfing candles.
Finally, the code calculates the technical analysis for each bank stock using the get_BankComponent_Details function and displays the results in the table. If the engulfing input is enabled, the code also checks for bullish and bearish engulfing candles and displays buy/sell signals accordingly.
The FRAMA stands for "Fractal Adaptive Moving Average," which is a type of moving average that adjusts its smoothing factor based on the fractal dimension of the price data. The fractal dimension reflects self-similarity at different scales. The FRAMA uses this property to adapt to the scale of price movements, capturing short-term and long-term trends while minimizing lag. The FRAMA was developed by John F. Ehlers and is commonly used by traders and analysts in technical analysis to identify trends and generate buy and sell signals. I tried to create this indicator in Pine.
In this context, "RS" stands for "Relative Strength," which is a technical indicator that compares the performance of a particular stock or market sector against a benchmark index.
The "Alligator" is a technical analysis tool that consists of three smoothed moving averages. Introduced by Bill Williams in his book "Trading Chaos," the three lines are called the Jaw, Teeth, and Lips of the Alligator. The Alligator indicator helps traders identify the trend direction and its strength, as well as potential entry and exit points. When the three lines are intertwined or close to each other, it indicates a range-bound market, while a divergence between them indicates a trending market. The position of the price in relation to the Alligator lines can also provide signals, such as a buy signal when the price crosses above the Alligator lines and a sell signal when the price crosses below them.
In addition to these, we have several other commonly used technical indicators, such as MACD, RSI, MFI (Money Flow Index), VWAP, EMA, and Supertrend. I used all the built-in functions for these indicators from TradingView. Thanks to the developer of this TradingView Indicator.
I also created a BankNifty Components Table and checked it on the dashboard.
Open Interest Delta with MAs[Binance Perpetuals]!!!!! This indicator only shows Binance Perpetuals Open Interest Delta !!!!!
!!!!! When Binance Spot pair charts is selected, It still shows the perpetual contract Open Interest, if the pair on the chart is tradeble on perpetual contracts. I assume you know what Open Interest is. !!!!!
ZLEMA , Tillson, VAR MAs codes are coming from @KivancOzbilgic => SuperTrended Moving Averages
KAMA code is coming from @HPOTTER => Kaufman Moving Average Adaptive ( KAMA )
Open Interest with Bollinger Bands and some moving averages!!! This indicator only shows Binance Perpetuals Open Interest !!!
!!!!! When Binance Spot pair charts is selected, It still shows the perpetual contract Open Interest, if the pair on the chart is tradeble on perpetual contracts. I assume you know what Open Interest is. !!!!!
ZLEMA, Tillson, VAR MAs codes are coming from @KivancOzbilgic => SuperTrended Moving Averages
Indicators OverviewThis Indicator help you to see whether the price is above or below vwap, supertrend. Also you can see realtime RSI value.
You can add upto 15 stock of your choice.
HiLo IndicatorNYSE:SPCE
This is an old and simple concept of mine that I am revisiting. It looks similar to the Vortex Indicator but the formulation is different. I was sick and tired of buying late at the top of the peaks, so I wanted to relate the current price to historic highs and lows (you can change how far you want to go back Time Length = tl). The functions are incredible simple:
lo = close -lowest(close,tl)
hi = highest(close,tl) -close
This generates a weaving pattern that shows bullish (lo>hi) and bearish (lo<hi) zones. WMA's (Fast and Long which can be changed and I have the defaults set kind or high) are used to smooth the functions. Only the long is shown for the "hi" function to keep the plot cleaner. I used crossover points of the "lo" WMA curves to specify places of possible bearish "turn around" points and bullish "entry" points. Alerts can set set for these along with the main crossovers where the plots cross bullish (green) and bearish (red). It seems to be a really good companion to popular buy/sell indicators like the Supertrend.
Hope you like it and let me know if there are any questions.
Niki Super1.2This is a completely super trend indicator. Changed only the ATR period and the multifactor default values. This setup shows more profit on the 5 minute chart, making it ideal for scalping and day trading. This indicator is suitable for any type of stock. The 'Buy' symbol represents the long entry and the 'Sell' symbol represents the short entry. Modified the bar color based on the SuperTrend. Signals or highlighted colors can be omitted from the Signal Settings window
Contact us using the links below to get access to this indicator
Bot Study v7 OverlayShowing the direction of price, based on candlestick patterns. Working similarly as PSAR or Supertrend.
Mixed TrendsTwo green dots in a row means it's good time to start long position.
Likewise, two red dots in a row means to start short.
Better performance used together with SuperTrend.
50EMA + 52RSI Day TradeBased on the great day trading video by @TrueCrypto28 ( www.youtube.com ), this indicator is perfect for trading on Binance. Have tweaked it so it is based on the 50EMA instead of SuperTrend.
Default settings
Long signal will be given when RSI is above 52 on the hourly chart to confirm a higher timeframe bullish bias as well as price closing above the 50EMA on the 5 minute chart. High + Low + Close / 3 has been used to smooth signals.
Trade will be closed when price either closes below the 50EMA on the 5 minute or RSI drops above 52 on the hourly.
Colour coded candles included for ease of trading. Green = all signals met to buy. Red = sell.
Can change inputs to suite your style.
SY_Quant_AI_Trend📌 SY_Quant_AI Trend Visualization Indicator
🔍 This script is a trend visualization tool designed to assist traders in identifying market direction. It integrates multiple classic technical indicators (Supertrend, EMA/SMA, MACD) for multi-factor trend analysis and is ideal for use on 5-minute to 15-minute timeframes, particularly for digital assets such as BTC or ETH.
📐 Logic Overview:
✅ Supertrend determines the overall trend direction: green for uptrend, red for downtrend.
✅ EMA10 and MA80 alignment confirms trend strength.
✅ MACD crossovers (golden/dead) complement trend signals and trigger floating profit take-profit reminders (not entry signals).
✅ Bar colors indicate trend strength: dark green = strong long, light green = moderate long; dark red = strong short, light red = moderate short.
✅ Take-profit labels display current floating profit percentage as a manual reference — not a trading signal.
⚠️ Disclaimer:
This script does not execute any trades. It is solely for visual analysis of market trends. Users should independently assess whether to act on the analysis provided. The author bears no responsibility for any trading decisions based on this script.
Exponential Trend [AlgoAlpha]OVERVIEW
This script plots an adaptive exponential trend system that initiates from a dynamic anchor and accelerates based on time and direction. Unlike standard moving averages or trailing stops, the trend line here doesn't follow price directly—it expands exponentially from a pivot determined by a modified Supertrend logic. The result is a non-linear trend curve that starts at a specific price level and accelerates outward, allowing traders to visually assess trend strength, persistence, and early-stage reversal points through both base and volatility-adjusted extensions.
CONCEPTS
This indicator builds on the idea that trend-following tools often need dynamic, non-static expansion to reflect real market behavior. It uses a simplified Supertrend mechanism to define directional context and anchor levels, then applies an exponential growth function to simulate trend acceleration over time. The exponential growth is unidirectional and resets only when the direction flips, preserving trend memory. This method helps avoid whipsaws and adds time-weighted confirmation to trends. A volatility buffer—derived from ATR and modifiable by a width multiplier—adds a second layer to indicate zones of risk around the main trend path.
FEATURES
Exponential Trend Logic : Once a directional anchor is set, the base trend line accelerates using an exponential formula tied to elapsed bars, making the trend stronger the longer it persists.
Volatility-Adjusted Extension : A secondary band is plotted above or below the base trend line, widened by ATR to visualize volatility zones, act as soft stop regions or as a better entry point (Dynamic Support/Resistance).
Color-Coded Visualization : Clear green/red base and extension lines with shaded fills indicate trend direction and confidence levels.
Signal Markers & Alerts : Triangle markers indicate confirmed trend reversals. Built-in alerts notify users of bullish or bearish direction changes in real-time.
USAGE
Use this script to identify strong trends early, visually measure their momentum over time, and determine safe areas for entries or exits. Start by adjusting the *Exponential Rate* to control how quickly the trend expands—the higher the rate, the more aggressive the curve. The *Initial Distance* sets how far the anchor band is placed from price initially, helping filter out noise. Increase the *Width Multiplier* to widen the volatility zone for more conservative entries or exits. When the price crosses above or below the base line, a new trend is assumed and the exponential projection restarts from the new anchor. The base trend and its extension both shift over time, but only reset on a confirmed reversal. This makes the tool especially useful for momentum continuation setups or trailing stop logic in trending markets.
AI Trend Momentum SniperThe AI Trend Momentum Sniper is a powerful technical analysis tool designed for day trading. This strategy combines multiple momentum and trend indicators to identify high-probability entry and exit points. The indicator utilizes a combination of Supertrend, MACD, RSI, ATR (Average True Range), and On-Balance Volume (OBV) to generate real-time signals for buy and sell opportunities.
Key Features:
Supertrend for detecting market direction (bullish or bearish).
MACD for momentum confirmation, highlighting changes in market momentum.
RSI to filter out overbought/oversold conditions and ensure high-quality trades.
ATR as a volatility filter to adjust for changing market conditions.
OBV (On-Balance Volume) to confirm volume strength and trend validity.
Dynamic Stop-Loss & Take-Profit based on ATR to manage risk and lock profits.
This indicator is tailored for intraday traders looking for quick market moves, especially in volatile and high liquidity assets like Bitcoin (BTC) and Ethereum (ETH). It helps traders capture short-term trends with efficient risk management tools.
How to Apply:
Set Your Chart: Apply the AI Trend Momentum Sniper to a 5-minute (M5) or 15-minute (M15) chart for optimal performance.
Buy Signal: When the indicator generates a green arrow below the bar, it indicates a buy signal based on positive trend and momentum alignment.
Sell Signal: A red arrow above the bar signals a sell condition when the trend and momentum shift bearish.
Stop-Loss and Take-Profit: The indicator automatically calculates dynamic stop-loss and take-profit levels based on the ATR value for each trade, ensuring proper risk management.
Alerts: Set up custom alerts for buy or sell signals, and get notified instantly when opportunities arise.
Best Markets for Use:
BTC/USDT, ETH/USDT – High liquidity and volatility.
Major altcoins with sufficient volume.
Avoid using it on low-liquidity assets where price action may become erratic.
Timeframes:
This indicator is best suited for lower timeframes (5-minute to 15-minute charts) to capture quick price movements in trending markets.
Machine Learning Moving Average [LuxAlgo]The Machine Learning Moving Average (MLMA) is a responsive moving average making use of the weighting function obtained Gaussian Process Regression method. Characteristic such as responsiveness and smoothness can be adjusted by the user from the settings.
The moving average also includes bands, used to highlight possible reversals.
🔶 USAGE
The Machine Learning Moving Average smooths out noisy variations from the price, directly estimating the underlying trend in the price.
A higher "Window" setting will return a longer-term moving average while increasing the "Forecast" setting will affect the responsiveness and smoothness of the moving average, with higher positive values returning a more responsive moving average and negative values returning a smoother but less responsive moving average.
Do note that an excessively high "Forecast" setting will result in overshoots, with the moving average having a poor fit with the price.
The moving average color is determined according to the estimated trend direction based on the bands described below, shifting to blue (default) in an uptrend and fushia (default) in downtrends.
The upper and lower extremities represent the range within which price movements likely fluctuate.
Signals are generated when the price crosses above or below the band extremities, with turning points being highlighted by colored circles on the chart.
🔶 SETTINGS
Window: Calculation period of the moving average. Higher values yield a smoother average, emphasizing long-term trends and filtering out short-term fluctuations.
Forecast: Sets the projection horizon for Gaussian Process Regression. Higher values create a more responsive moving average but will result in more overshoots, potentially worsening the fit with the price. Negative values will result in a smoother moving average.
Sigma: Controls the standard deviation of the Gaussian kernel, influencing weight distribution. Higher Sigma values return a longer-term moving average.
Multiplicative Factor: Adjusts the upper and lower extremity bounds, with higher values widening the bands and lowering the amount of returned turning points.
🔶 RELATED SCRIPTS
Machine-Learning-Gaussian-Process-Regression
SuperTrend-AI-Clustering
AadTrend [InvestorUnknown]The AadTrend indicator is an experimental trading tool that combines a user-selected moving average with the Average Absolute Deviation (AAD) from this moving average. This combination works similarly to the Supertrend indicator but offers additional flexibility and insights. In addition to generating Long and Short signals, the AadTrend indicator identifies RISK-ON and RISK-OFF states for each trade direction, highlighting areas where taking on more risk may be considered.
Core Concepts and Features
Moving Average (User-Selected Type)
The indicator allows users to select from various types of moving averages to suit different trading styles and market conditions:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Hull Moving Average (HMA)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Relative Moving Average (RMA)
Fractal Adaptive Moving Average (FRAMA)
Average Absolute Deviation (AAD)
The Average Absolute Deviation measures the average distance between each data point and the mean, providing a robust estimation of volatility.
aad(series float src, simple int length, simple string avg_type) =>
avg = // Moving average as selected by the user
abs_deviations = math.abs(src - avg)
ta.sma(abs_deviations, length)
This provides a volatility measure that adapts to recent market conditions.
Combining Moving Average and AAD
The indicator creates upper and lower bands around the moving average using the AAD, similar to how the Supertrend indicator uses Average True Range (ATR) for its bands.
AadTrend(series float src, simple int length, simple float aad_mult, simple string avg_type) =>
// Calculate AAD (volatility measure)
aad_value = aad(src, length, avg_type)
// Calculate the AAD-based moving average by scaling the price data with AAD
avg = switch avg_type
"SMA" => ta.sma(src, length)
"EMA" => ta.ema(src, length)
"HMA" => ta.hma(src, length)
"DEMA" => ta.dema(src, length)
"TEMA" => ta.tema(src, length)
"RMA" => ta.rma(src, length)
"FRAMA" => ta.frama(src, length)
avg_p = avg + (aad_value * aad_mult)
avg_m = avg - (aad_value * aad_mult)
var direction = 0
if ta.crossover(src, avg_p)
direction := 1
else if ta.crossunder(src, avg_m)
direction := -1
A chart displaying the moving average with upper and lower AAD bands enveloping the price action.
Signals and Trade States
1. Long and Short Signals
Long Signal: Generated when the price crosses above the upper AAD band,
Short Signal: Generated when the price crosses below the lower AAD band.
2. RISK-ON and RISK-OFF States
These states provide additional insight into the strength of the current trend and potential opportunities for taking on more risk.
RISK-ON Long: When the price moves significantly above the upper AAD band after a Long signal.
RISK-OFF Long: When the price moves back below the upper AAD band, suggesting caution.
RISK-ON Short: When the price moves significantly below the lower AAD band after a Short signal.
RISK-OFF Short: When the price moves back above the lower AAD band.
Highlighted areas on the chart representing RISK-ON and RISK-OFF zones for both Long and Short positions.
A chart showing the filled areas corresponding to trend directions and RISK-ON zones
Backtesting and Performance Metrics
While the AadTrend indicator focuses on generating signals and highlighting risk areas, it can be integrated with backtesting frameworks to evaluate performance over historical data.
Integration with Backtest Library:
import InvestorUnknown/BacktestLibrary/1 as backtestlib
Customization and Calibration
1. Importance of Calibration
Default Settings Are Experimental: The default parameters are not optimized for any specific market condition or asset.
User Calibration: Traders should adjust the length, aad_mult, and avg_type parameters to align the indicator with their trading strategy and the characteristics of the asset being analyzed.
2. Factors to Consider
Market Volatility: Higher volatility may require adjustments to the aad_mult to avoid false signals.
Trading Style: Short-term traders might prefer faster-moving averages like EMA or HMA, while long-term traders might opt for SMA or FRAMA.
Alerts and Notifications
The AadTrend indicator includes built-in alert conditions to notify traders of significant market events:
Long and Short Alerts:
alertcondition(long_alert, "LONG (AadTrend)", "AadTrend flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (AadTrend)", "AadTrend flipped ⬇Short⬇")
RISK-ON and RISK-OFF Alerts:
alertcondition(risk_on_long, "RISK-ON LONG (AadTrend)", "RISK-ON LONG (AadTrend)")
alertcondition(risk_off_long, "RISK-OFF LONG (AadTrend)", "RISK-OFF LONG (AadTrend)")
alertcondition(risk_on_short, "RISK-ON SHORT (AadTrend)", "RISK-ON SHORT (AadTrend)")
alertcondition(risk_off_short, "RISK-OFF SHORT (AadTrend)", "RISK-OFF SHORT (AadTrend)")
Important Notes and Disclaimer
Experimental Nature: The AadTrend indicator is experimental and should be used with caution.
No Guaranteed Performance: Past performance is not indicative of future results. Backtesting results may not reflect real trading conditions.
User Responsibility: Traders and investors should thoroughly test and calibrate the indicator settings before applying it to live trading.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Universal Trend and Valuation System [QuantAlgo]Universal Trend and Valuation System 📊🧬
The Universal Trend and Valuation System by QuantAlgo is an advanced indicator designed to assess asset valuation and trends across various timeframes and asset classes. This system integrates multiple advanced statistical indicators and techniques with Z-score calculations to help traders and investors identify overbought/sell and oversold/buy signals. By evaluating valuation and trend strength together, this tool empowers users to make data-driven decisions, whether they aim to follow trends, accumulate long-term positions, or identify turning points in mean-reverting markets.
💫 Conceptual Foundation and Innovation
The Universal Trend and Valuation System by QuantAlgo provides a unique framework for assessing market valuation and trend dynamics through a blend of Z-score analysis and trend-following algorithm. Unlike traditional indicators that only reflect price direction, this system incorporates multi-layered data to reveal the relative value of an asset, helping users determine whether it’s overvalued, undervalued, or approaching a trend reversal. By combining high quality trend-following tools, such as Dynamic Score Supertrend, DEMA RSI, and EWMA, it evaluates trend stability and momentum quality, while Z-scores of performance ratios like Sharpe, Sortino, and Omega standardize deviations from historical trends, enabling traders and investors to spot extreme conditions. This dual approach allows users to better identify accumulation (undervaluation) and distribution (overvaluation) phases, enhancing strategies like Dollar Cost Averaging (DCA) and overall timing for entries and exits.
📊 Technical Composition and Calculation
The Universal Trend-Following Valuation System is composed of several trend-following and valuation indicators that create a dynamic dual scoring model:
Risk-Adjusted Ratios (Sharpe, Sortino, Omega): These ratios assess trend quality by analyzing an asset’s risk-adjusted performance. Sharpe and Sortino provide insight into trend consistency and risk/reward, while Omega evaluates profitability potential, helping traders and investors assess how favorable a trend or an asset is relative to its associated risk.
Dynamic Z-Scores: Z-scores are applied to various metrics like Price, RSI, and RoC, helping to identify statistical deviations from the mean, which indicate potential extremes in valuation. By combining these Z-scores, the system produces a cumulative score that highlights when an asset may be overbought or oversold.
Aggregated Trend-Following Indicators: The model consolidates multiple high quality indicators to highlight probable trend shifts. This helps confirm the direction and strength of market moves, allowing users to spot reversals or entry points with greater clarity.
📈 Key Indicators and Features
The Universal Trend and Valuation System combines various technical and statistical tools to deliver a well-rounded analysis of market trends and valuation:
The indicator utilizes trend-following indicators like RSI with DEMA smoothing and Dynamic Score Supertrend to minimize market noise, providing clearer and more stable trend signals. Sharpe, Sortino, and Omega ratios are calculated to assess risk-adjusted performance and volatility, adding a layer of analysis for evaluating trend quality. Z-scores are applied to these ratios, as well as Price and Rate of Change (RoC), to detect deviations from historical trends, highlighting extreme valuation levels.
The system also incorporates multi-layered visualization with gradient color coding to signal valuation states across different market conditions. These adaptive visual cues, combined with threshold-based alerts for overbought and oversold zones, help traders and investors track probable trend reversals or continuations and identify accumulation or distribution zones, adding reliability to both trend-following and mean-reversion strategies.
⚡️ Practical Applications and Examples
✅ Add the Indicator: Add the Universal Trend-Following Valuation System to your favourites and to your chart.
👀 Monitor Trend Shifts and Valuation Levels: Watch the average Z score, trend probability state and gradient colors to identify overbought and oversold conditions. During undervaluation, consider using a DCA strategy to gradually accumulate positions (buy), while overvaluation may signal distribution or profit-taking phases (sell).
🔔 Set Alerts: Configure alerts for significant trend or valuation changes, ensuring you can act on market movements promptly, even when you’re not actively monitoring the charts.
🌟 Summary and Usage Tips
The Universal Trend and Valuation System by QuantAlgo is a highly adaptable tool, designed to support both trend-following and valuation analysis across different market environments. By combining valuation metrics with high quality trend-following indicators, it helps traders and investors identify the relative value of an asset based on historical norms, providing more reliable overbought/sell and oversold/buy signals. The tool’s flexibility across asset types and timeframes makes it ideal for both short-term trading and long-term investment strategies like DCA, allowing users to capture meaningful trends while minimizing noise.
FMS Suite [KFB Quant]FMS Suite
Overview
The FMS Suite is a powerful and adaptive trend and momentum analysis tool that leverages multiple technical indicators to deliver a comprehensive signal for market direction. This suite combines the strengths of the Aroon, DMI, RSI, Supertrend, and Trix indicators, offering traders a well-rounded perspective on market trends.
How It Works
The FMS Suite integrates five essential components to assess market behavior:
Aroon Indicator : Detects trend strength and direction by analyzing the frequency of recent highs and lows over multiple timeframes. Directional Movement Index (DMI) : Measures the direction and strength of trends, with an ADX component for better trend assessment. Relative Strength Index (RSI) : Evaluates market momentum by indicating overbought or oversold conditions, with signals derived from the 50-line. Supertrend : Utilizes ATR-based volatility measures to establish dynamic support and resistance levels, signaling potential trend changes. Trix : A triple-smoothed EMA oscillator that highlights trend reversals using rate-of-change dynamics.
Each component is calculated across three separate timeframes (fast, medium, and slow), which are then averaged to produce a final FMS Signal . Users can also apply signal smoothing to reduce noise and enhance clarity.
Key Features
Customizable Parameters : Adjust the lengths for each component (fast, medium, slow) to optimize the indicator's responsiveness to different markets. Signal Smoothing Options : Select from various smoothing methods, including SMA, EMA, DEMA, and WMA, to fine-tune the FMS signal. Visual Representation : The FMS Suite plots a histogram representing the raw signal and a smoother line for clearer trend visualization. The background color shifts dynamically to indicate long, short, or neutral conditions. Threshold-Based Alerts : Set your own long and short thresholds, tailoring the indicator to your trading strategy and market outlook. Informative Table Display : An integrated table provides an at-a-glance summary of the current FMS and smoothed FMS signals, along with their respective scores and market state.
How to Use
Trend Confirmation : Utilize the FMS histogram and smoothed signal to validate or challenge existing trend assumptions. Trade Entries and Exits : Identify potential buy (long) or sell (short) signals based on the relationship between the FMS signal and predefined thresholds. Strategy Customization : Fine-tune the indicator settings to align with your trading style, whether it’s short-term scalping or long-term trend following.
Important Considerations
Not Predictive : The FMS Suite does not predict future price movements and should be used in conjunction with other analysis methods. It is based on historical price data, and past performance is not indicative of future results. Settings and Backtesting : Experiment with different lengths and smoothing techniques to optimize performance for specific instruments and market conditions. Always backtest thoroughly.
Disclaimer: This tool is provided for informational and educational purposes only and should not be considered as financial advice. Always conduct your own research and consult with a licensed financial advisor before making any investment decisions.
Rolling ATR Bands | Flux Charts💎 GENERAL OVERVIEW
Introducing the Rolling ATR Bands indicator! This indicator overlays adaptive bands around the price, using the Average True Range (ATR) to define dynamic support and resistance levels. The Rolling ATR Bands are color-coded to visually indicate potential trend strength, shifting between bearish, neutral, and bullish colors. This tool can help traders interpret price volatility, as well as identify probable trend changes, continuations, or reversals. For more information about the process, check the "HOW DOES IT WORK ?" section.
Features of the new Rolling ATR Bands:
ATR Bands With Customizable ATR Length & Multiplier
Smooth Trend Strength With Adjustable Smoothing Options
Color-coded bands Representing Bearish, Neutral, or Bullish Trends
Alerts for Retests & Breaks
Customizable Visuals
📌 HOW DOES IT WORK?
The Rolling ATR Bands indicator calculates the ATR based on the specified length and multiplier to form upper and lower bands around the price. These bands adapt with market volatility, widening during high volatility and contracting during lower volatility periods.
In addition, the indicator calculates a "trend strength" score by combining an interpolated RSI, Supertrend, and EMA crossover. This score is smoothed with a customizable length, and a color gradient is applied to visually denote the strength of bearish, neutral, or bullish conditions.
Here's how to interpret the bands:
Upper Band: Acts as dynamic resistance; when price approaches or touches it, this often suggests potential overbought conditions.
Lower Band: Acts as dynamic support; touching or nearing this band might indicate potential oversold conditions.
Color Shifts: Color changes indicate shifts in trend direction. For example, a green color suggests a bullish trend, while red hints at bearish tendencies.
🚩 UNIQUENESS
What sets the Rolling ATR Bands apart is the combined use of interpolated RSI, Supertrend, and EMA cross values, creating a weighted trend strength score. This integration allows for nuanced, color-coded visual cues that respond quickly to trend changes without excessive noise, offering traders an intuitive view of both trend direction and potential momentum. You can also set up alerts for retest & alerts for upper and lower bands to get informed of potential movements.
⚙️ SETTINGS
1. General Configuration
ATR Length : Controls the ATR calculation length for the bands.
Smoothing: Adjusts the trend strength smoothing to control sensitivity to trend changes.
ATR Multiplier : Sets the width of the bands by multiplying the ATR value.
Trend Smoothing : Higher settings will result in longer periods of time required for trend to change direction from bullish to bearish and vice versa.
