Overbought & Oversold Oscillator - By CryptoEasonThis is an overbought/oversold indicator that combines EMA / ATR / RSI and Bollinger Bands.
Overbought Definition:
When the RSI is greater than 70, and the price is above EMA20 + 2.5 * ATR.
When the price meets the overbought condition, the oscillator value will exceed 40, and a red bar will be displayed on the chart.
Oversold Definition:
When the RSI is less than 30, and the price is below EMA20 - 2.5 * ATR.
When the price meets the oversold condition, the oscillator value will drop below -40, and a green bar will be displayed on the chart.
The default average price used is EMA20, but you can modify it to SMA20 or adjust the length in the settings.
The default RSI length is set to 14, but this can also be customized. You can also adjust the ATR overbought/oversold multiplier in the settings, for example, setting it to 3.
Bollinger Bands:
The Bollinger Bands are used as a supplementary tool.
When the price is overbought and above the upper Bollinger Band, a red dot will be displayed.
When the price is oversold and below the lower Bollinger Band, a green dot will be displayed.
Buy and Sell Signals:
When the price moves from an overbought condition to a non-overbought condition, a sell signal is generated.
When the price moves from an oversold condition to a non-oversold condition, a buy signal is generated.
Altcoin Buy/Sell Signals:
In crypto markets, we usually view the bitcoin chart, so for the reason of convenience, I have also included altcoins buy and sell signals for 15 different altcoins. The default list includes: ETH / SOL / AVAX / DOT / APT / NEAR / ADA / SUI / MATIC / OP / PEPE / BLUR / GLMR / ASTR / APE.
You can customize these 15 altcoin pairs in the settings to any altcoins you prefer. When a buy or sell signal appears for one of these altcoins, you can quickly switch to its chart to view the signal. This is for convenience, so you don't need to check each chart's overbought/oversold status one by one; you only need to view the charts when a signal appears.
Reminder:
The overbought/oversold indicator works best in ranging markets. Use carefully when applying this indicator in a trending market. During trends, the price can keep remaining at overbought / oversold level.
Note:
If you think this indicator should have additional features that are currently not available, feel free to leave a comment and let me know.
=============== 中文說明（Chinese Introduction）===============
這是一個超買超賣指標，該指標結合了 EMA / ATR / RSI 與 Bollinger Bands。
我將超買定義為：
當RSI大於70，且價格大於 EMA20 + 2.5*ATR
當價格符合超買定義時，此時振盪器的值會大於40，並在圖表上顯示紅柱。
我將超賣定義為：
RSI < 30 且價格小於 EMA20 - 2.5 * ATR
當價格符合超賣定義時，此時振盪器的值為低於-40，並在圖表上顯示綠柱。
平均價格使用的是EMA20，但你可以在設定中修改成SMA20，或是其它長度。
預設RSI長度為14，你可以在設定中修改成其它參數。
你也可以在設定中將 ATR 超買超賣乘數改成其他倍數，例如3。
Bollinger Bands 在這個指標中的作用為輔助，當價格位於超買且在布林帶上邊界之外，會顯示紅點，當價格位於超賣且價格低於布林帶下邊界之外，會顯示綠點。
超指標還提供了買入與賣出信號：
當價格從超買狀態變為非超買狀態時，顯示賣出信號。
當價格從超賣狀態變為非超賣狀態時，顯示買入信號。
我還再這個指標上加入了山寨幣的買入賣出信號，一共十五組，預設為：
ETH / SOL / AVAX / DOT / APT /NEAR / ADA / SUI / MATIC / OP / PEPE / BLUR / GLMR / ASTR / APE
你可以客製化這十五組山寨幣的標的，在設定中修改成你喜歡的山寨幣。
當你在圖表上發現了某個山寨幣出現買入賣出信號，你可以迅速切換圖表到該山寨幣圖表上，提供這個山寨幣買入賣出信號，僅僅是為了方便性，讓你不用逐一檢查每個圖表的超買超賣狀態，僅在出現信號再查看即可。
提醒：
超買超賣指標比較適合用在震盪行情，當趨勢行情來臨時，需要謹慎使用這個超買超賣指標。
因為當趨勢來臨時，價格可以一直處在超買狀態或超賣狀態。
註：
如果你認為這個指標應該多增加什麼功能，但是目前沒有，歡迎留言告訴我。
M-oscillator
Elliott Wave Oscillator with Peak DetectionThe Elliott Wave Oscillator with Derivative Peak Detection and Breakout Bands is a technical indicator that blends traditional Elliott Wave theory with modern derivative-based peak detection and breakout bands for a clearer view of market trends.
Key Components:
Elliott Wave Oscillator (EWO):
The core of the indicator is based on the difference between two simple moving averages (SMA): a short-term SMA (default length: 5) and a long-term SMA (default length: 35).
This difference is expressed either as an absolute value or a percentage of the current price, depending on the user’s input.
Smoothing:
The EWO is smoothed using an Exponential Moving Average (EMA) to filter out noise and provide a clearer trend direction.
The smoothing length is adaptive based on the current chart's timeframe (e.g., longer smoothing for daily charts).
Derivative Peak Detection:
The smoothed EWO is analyzed for peaks (positive) and troughs (negative) by calculating the derivative (rate of change) between consecutive values.
Peaks are detected when the derivative transitions from positive to negative, while troughs are identified when the derivative switches from negative to positive.
Tolerance levels are adjustable and vary by timeframe to avoid false signals.
Breakout Bands:
Upper and lower breakout bands are dynamically generated based on the smoothed EWO.
The bands help to filter significant peaks and troughs, only highlighting those that occur beyond the breakout levels.
Users can choose to display these bands and use them to filter out less significant peaks and troughs.
Visualization:
The original, unsmoothed EWO is plotted as a histogram, with positive values in green and negative values in red.
The smoothed EWO is plotted as a blue line, providing a clearer view of the underlying trend.
The breakout bands, if enabled, are plotted as white lines to visualize the upper and lower bounds of the oscillator's movement.
Positive peaks and negative troughs that meet the filtering criteria are marked with purple triangles (for peaks) and red triangles (for troughs) on the chart.
Customization Options:
Timeframe-based Smoothing and Tolerance: Different smoothing lengths and tolerance levels can be set for daily, hourly, and 5-minute charts.
Breakout Bands: Users can toggle the display of breakout bands and adjust their visual properties.
Peak Filtering: Peaks and troughs can be filtered based on whether they break out beyond the bands, or all peaks can be shown.
This indicator provides a unique blend of trend detection through the Elliott Wave Oscillator and derivative analysis to highlight significant market reversals while offering breakout bands as a filtering mechanism for false signals.
Tandem Oscillator | viResearchTandem Oscillator | viResearch
Conceptual Foundation and Innovation
The "Tandem Oscillator" script provides an enhanced way to analyze market momentum by utilizing both the Relative Strength Index (RSI) and standard deviation to detect shifts in price movement. The oscillator creates dynamic upper and lower boundaries around the RSI, helping traders identify potential overbought and oversold conditions more effectively. By applying a tandem approach—combining RSI and standard deviation—the script offers a more refined and sensitive momentum indicator, ideal for spotting trend reversals and market entries.
This approach allows traders to capture moments of extreme market behavior, giving them an edge in timing trades.
Technical Composition and Calculation
The script is structured around several key technical components that make it an efficient tool for momentum detection:
RSI Calculation: The RSI is calculated using a user-defined lookback period to assess the strength of recent price movements. This forms the core of the oscillator and helps determine overbought or oversold conditions.
Tandem Bands: The standard deviation is applied to the RSI to create dynamic upper and lower bands, providing a more adaptive boundary to track market extremes.
Dual Scoring Systems: Two separate systems are used to score the RSI and its lower band. These systems evaluate the RSI against thresholds and calculate scores to detect potential momentum shifts.
Threshold-Based Trend Detection: The script compares the scores against user-defined thresholds to trigger long or short signals. Crossovers of these thresholds help identify potential trend reversals or confirmations.
Features and User Inputs
The "Tandem Oscillator" offers various input parameters that traders can adjust to fine-tune the indicator for their strategies:
Lookback Period: Defines the number of bars used in the RSI calculation, allowing traders to adjust how responsive the indicator is to price movements.
Tandem Length: Controls the length of the standard deviation applied to the RSI, which determines the sensitivity of the tandem bands.
Thresholds: User-defined thresholds that determine when the oscillator identifies potential uptrends or downtrends, triggering buy or sell signals.
Bar Coloring: Optional settings to color bars based on detected trends, offering traders visual cues for easier identification of trading opportunities.
Alerts: The script includes alert conditions for both long and short signals, ensuring traders are notified of key market events even when they're not actively monitoring the charts.
Practical Applications
The "Tandem Oscillator" script is an adaptable tool suited for traders looking to capture momentum shifts and improve the timing of their trades. This indicator is particularly effective in:
Identifying Overbought and Oversold Conditions: The tandem bands provide dynamic thresholds, helping traders detect when the market is stretched in either direction, signaling potential reversal points.
Spotting Trend Reversals: The dual scoring system and threshold detection help traders identify moments when market momentum is about to shift, offering a more precise entry or exit point.
Improving Trade Timing: By tracking the RSI and its deviation, traders can gain a clearer picture of when the market is reaching an extreme, allowing them to enter or exit trades at optimal times.
Advantages and Strategic Value
The "Tandem Oscillator" script stands out due to its ability to dynamically adjust to market conditions using both RSI and ATR. This reduces the likelihood of false signals and provides a more nuanced understanding of market momentum. The customizable inputs make the indicator versatile, enabling traders to adapt it to different assets and timeframes based on their specific trading goals.
Summary and Usage Tips
The "Tandem Oscillator" script is a powerful tool for detecting market momentum and trend shifts by combining RSI with standard deviation bands. Its customizable parameters and dual scoring system make it a valuable addition to any trader's toolkit. By incorporating this script into your strategy, you can enhance your ability to identify overbought or oversold conditions and time your trades more effectively.
Be sure to adjust the lookback period and tandem length according to the asset you are trading, and use the alert system to stay informed of potential opportunities without needing constant chart monitoring.
As always, backtesting and forward-testing are important to understand how the script performs under different market conditions. Past performance is not indicative of future results.
Adaptive Gaussian MA For Loop [BackQuant]Adaptive Gaussian MA For Loop
PLEASE Read the following carefully before applying this indicator to your trading system. Knowing the core logic behind the tools you're using allows you to integrate them into your strategy with confidence and precision.
Introducing BackQuant's Adaptive Gaussian Moving Average For Loop (AGMA FL) — a sophisticated trading indicator that merges the Gaussian Moving Average (GMA) with adaptive volatility to provide dynamic trend analysis. This unique indicator further enhances its effectiveness by utilizing a for-loop scoring mechanism to detect potential shifts in market direction. Let's dive into the components, the rationale behind them, and how this indicator can be practically applied to your trading strategies.
Understanding the Gaussian Moving Average (GMA)
The Gaussian Moving Average (GMA) is a smoothed moving average that applies Gaussian weighting to price data. Gaussian weighting gives more significance to data points near the center of the lookback window, making the GMA particularly effective at reducing noise while maintaining sensitivity to changes in price direction. In contrast to simpler moving averages like the SMA or EMA, GMA provides a more refined smoothing function, which can help traders follow the true trend in volatile markets.
In this script, the GMA is calculated over a defined Calculation Period (default 14), applying a Gaussian filter to smooth out market fluctuations and provide a clearer view of underlying trends.
Adaptive Volatility: A Dynamic Edge
The Adaptive feature in this indicator gives it the ability to adjust its sensitivity based on current market volatility. If the Adaptive option is enabled, the GMA uses a standard deviation-based volatility measure (with a default period of 20) to dynamically adjust the width of the Gaussian filter, allowing the GMA to react faster in volatile markets and more slowly in calm conditions. This dynamic nature ensures that the GMA stays relevant across different market environments.
When the Adaptive setting is disabled, the script defaults to a constant standard deviation value (default 1.0), providing a more stable but less responsive smoothing function.
Why Use Adaptive Gaussian Moving Average?
The Gaussian Moving Average already provides smoother results than standard moving averages, but by adding an adaptive component, the indicator becomes even more responsive to real-time price changes. In fast-moving or highly volatile markets, this adaptation allows traders to react quicker to emerging trends. Conversely, in quieter markets, it reduces over-sensitivity to minor fluctuations, thus lowering the risk of false signals.
For-Loop Scoring Mechanism
The heart of this indicator lies in its for-loop scoring system, which evaluates the smoothed price data (the GMA) over a specified range, comparing it to previous values. This scoring system assigns a numerical value based on whether the current GMA is higher or lower than previous values, creating a trend score.
Long Signals: These are generated when the for-loop score surpasses the Long Threshold (default set at 40), signaling that the GMA is gaining upward momentum, potentially identifying a favorable buying opportunity.
Short Signals: These are triggered when the score crosses below the Short Threshold (default set at -10), indicating that the market may be losing strength and that a selling or shorting opportunity could be emerging.
Thresholds & Customization Options
This indicator offers a high degree of flexibility, allowing you to fine-tune the settings according to your trading style and risk preferences:
Calculation Period: Adjust the lookback period for the Gaussian filter, affecting how smooth or responsive the indicator is to price changes.
Adaptive Mode: Toggle the adaptive feature on or off, allowing the GMA to dynamically adjust based on market volatility or remain consistent with a fixed standard deviation.
Volatility Settings: Control the standard deviation period for adaptive mode, fine-tuning how quickly the GMA responds to shifts in volatility.
For-Loop Settings: Modify the start and end points for the for-loop score calculation, adjusting the depth of analysis for trend signals.
Thresholds for Signals: Set custom long and short thresholds to determine when buy or sell signals should be generated.
Visualization Options: Choose to color bars based on trend direction, plot signal lines, or adjust the background color to reflect current market sentiment visually.
Trading Applications
The Adaptive Gaussian MA For Loop can be applied to a variety of trading styles and markets. Here are some key ways you can use this indicator in practice:
Trend Following: The combination of Gaussian smoothing and adaptive volatility helps traders stay on top of market trends, identifying significant momentum shifts while filtering out noise. The for-loop scoring system enhances this by providing a numerical representation of trend strength, making it easier to spot when a new trend is emerging or when an existing one is gaining strength.
Mean Reversion: For traders looking to capitalize on short-term market corrections, the adaptive nature of this indicator makes it easier to identify when price action is deviating too far from its smoothed trend, allowing for strategic entries and exits based on overbought or oversold conditions.
Swing Trading: With its ability to capture medium-term price movements while avoiding the noise of short-term fluctuations, this indicator is well-suited for swing traders who aim to profit from market reversals or short-to-mid-term trends.
Volatility Management: The adaptive feature allows the indicator to adjust dynamically in volatile markets, ensuring that it remains responsive in times of increased uncertainty while avoiding unnecessary noise in calmer periods. This makes it an effective tool for traders who want to manage risk by staying in tune with changing market conditions.
Final Thoughts
The Adaptive Gaussian MA For Loop is a powerful and flexible indicator that merges the elegance of Gaussian smoothing with the adaptability of volatility-based adjustments. By incorporating a for-loop scoring mechanism, this indicator provides traders with a comprehensive view of market trends and potential trade opportunities.
It’s important to test the settings on historical data and adapt them to your specific trading style, timeframe, and market conditions. As with any technical tool, the AGMA For Loop should be used in conjunction with other indicators and solid risk management practices for the best results.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Two Pole Butterworth For Loop [BackQuant]Two Pole Butterworth For Loop
PLEASE read the following carefully, as understanding the underlying concepts and logic behind the indicator is key to incorporating it into your trading system in a sound and methodical manner.
Introducing BackQuant's Two Pole Butterworth For Loop (2P BW FL) — an advanced indicator that fuses the power of the Two Pole Butterworth filter with a dynamic for-loop scoring mechanism. This unique approach is designed to extract actionable trading signals by smoothing out price data and then analyzing it using a comparative scoring method. Let's delve into how this indicator works, why it was created, and how it can be used in various trading scenarios.
Understanding the Two Pole Butterworth Filter
The Butterworth filter is a signal processing tool known for its smooth response and minimal distortion. It's often used in electronic and communication systems to filter out unwanted noise. In trading, the Butterworth filter can be applied to price data to smooth out the volatility, providing traders with a clearer view of underlying trends without the whipsaws often associated with market noise.
The Two Pole Butterworth variant further enhances this effect by applying the filter with two poles, effectively creating a sharper transition between the passband and stopband. In simple terms, this allows the filter to follow the price action more closely, reacting to changes while maintaining smoothness.
In this script, the Two Pole Butterworth filter is applied to the Calculation Source (default is set to the closing price), creating a smoothed price series that serves as the foundation for further analysis.
Why Use a Two Pole Butterworth Filter?
The Two Pole Butterworth filter is chosen for its ability to reduce lag while maintaining a smooth output. This makes it an ideal choice for traders who want to capture trends without being misled by short-term volatility or market noise. By filtering the price data, the Two Pole Butterworth enables traders to focus on the broader market movements and avoid false signals.
The For-Loop Scoring Mechanism
In addition to the Butterworth filter, this script uses a for-loop scoring system to evaluate the smoothed price data. The for-loop compares the current value of the filtered price (referred to as "subject") to previous values over a defined range (set by the start and end input). The score is calculated based on whether the subject is higher or lower than the previous points, and the cumulative score is used to determine the strength of the trend.
Long and Short Signal Logic
Long Signals: A long signal is triggered when the score surpasses the Long Threshold (default set at 40). This suggests that the price has built sufficient upward momentum, indicating a potential buying opportunity.
Short Signals: A short signal is triggered when the score crosses under the Short Threshold (default set at -10). This indicates weakening price action or a potential downtrend, signaling a possible selling or shorting opportunity.
By utilizing this scoring system, the indicator identifies moments when the price momentum is shifting, helping traders enter positions at opportune times.
Customization and Visualization Options
One of the strengths of this indicator is its flexibility. Traders can customize various settings to fit their personal trading style or adapt it to different markets and timeframes:
Calculation Periods: Adjust the lookback period for the Butterworth filter, allowing for shorter or longer smoothing depending on the desired sensitivity.
Threshold Levels: Set the long and short thresholds to define when signals should be triggered, giving you control over the balance between sensitivity and specificity.
Signal Line Width and Colors: Customize the visual presentation of the indicator on the chart, including the width of the signal line and the colors used for long and short conditions.
Candlestick and Background Colors: If desired, the indicator can color the candlesticks or the background according to the detected trend, offering additional clarity at a glance.
Trading Applications
This Two Pole Butterworth For Loop indicator is versatile and can be adapted to various market conditions and trading strategies. Here are a few use cases where this indicator shines:
Trend Following: The Butterworth filter smooths the price data, making it easier to follow trends and identify when they are gaining or losing strength. The for-loop scoring system enhances this by providing a clear indication of how strong the current trend is compared to recent history.
Mean Reversion: For traders looking to identify potential reversals, the indicator’s ability to compare the filtered price to previous values over a range of periods allows it to spot moments when the trend may be losing steam, potentially signaling a reversal.
Swing Trading: The combination of smoothing and scoring allows swing traders to capture short to medium-term price movements by filtering out the noise and focusing on significant shifts in momentum.
Risk Management: By providing clear long and short signals, this indicator helps traders manage their risk by offering well-defined entry and exit points. The smooth nature of the Butterworth filter also reduces the risk of getting caught in false signals due to market noise.
Final Thoughts
The Two Pole Butterworth For Loop indicator offers traders a powerful combination of smoothing and scoring to detect meaningful trends and shifts in price momentum. Whether you are a trend follower, swing trader, or someone looking to refine your entry and exit points, this indicator provides the tools to make more informed trading decisions.
As always, it's essential to backtest the indicator on historical data and tailor the settings to your specific trading style and market. While the Butterworth filter helps reduce noise and smooth trends, no indicator can predict the future with absolute certainty, so it should be used in conjunction with other tools and sound risk management practices.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Adaptive SuperTrend Oscillator [AlgoAlpha]Adaptive SuperTrend Oscillator 🤖📈
Introducing the Adaptive SuperTrend Oscillator , an innovative blend of volatility clustering and SuperTrend logic designed to identify market trends with precision! 🚀 This indicator uses K-Means clustering to dynamically adjust volatility levels, helping traders spot bullish and bearish trends. The oscillator smoothly tracks price movements, adapting to market conditions for reliable signals. Whether you're scalping or riding long-term trends, this tool has got you covered! 💹✨
🔑 Key Features:
📊 Volatility Clustering with K-Means: Segments volatility into three levels (high, medium, low) using a K-Means algorithm for precise trend detection.
📈 Normalized Oscillator : Allows for customizable smoothing and normalization, ensuring the oscillator remains within a fixed range for easy interpretation.
🔄 Heiken Ashi Candles : Optionally visualize smoothed trends with Heiken Ashi-style candlesticks to better capture market momentum.
🔔 Alert System : Get notified when key conditions like trend shifts or volatility changes occur.
🎨 Customizable Appearance : Fully customizable colors for bullish/bearish signals, along with adjustable smoothing methods and lengths.
📚 How to Use:
⭐ Add the indicator to favorites by pressing the star icon. Customize settings to your preference:
👀 Watch the chart for trend signals and reversals. The oscillator will change color when trends shift, offering visual confirmation.
🔔 Enable alerts to be notified of critical trend changes or volatility conditions
⚙️ How It Works:
This script integrates SuperTrend with volatility clustering by analyzing ATR (Average True Range) to dynamically identify high, medium, and low volatility clusters using a K-Means algorithm . The SuperTrend logic adjusts based on the assigned volatility level, creating adaptive trend signals. These signals are then smoothed and optionally normalized for clearer visual interpretation. The Heiken Ashi transformation adds an additional layer of smoothing, helping traders better identify the market's true momentum. Alerts are set to notify users of key trend shifts and volatility changes, allowing traders to react promptly.
ATR with Donchian Channels and SMAsThis script combines the Average True Range (ATR), Donchian Channels, and Simple Moving Averages (SMAs) to provide a comprehensive tool for volatility and trend analysis.
Key Components:
ATR Calculation: The ATR is used to measure market volatility. It is calculated as a moving average of the true range over a specified length, which you can customize using different smoothing methods: RMA, SMA, EMA, or WMA. ATR helps identify periods of high and low volatility, giving insights into potential breakout or consolidation phases in the market.
Donchian Channels on ATR: The Donchian Channels are calculated based on the highest and lowest values of the ATR over a user-defined period. The upper and lower bands provide a volatility range, and the middle line represents the average of the two. This can help visualize the range of market volatility and detect possible trend reversals or continuations.
SMAs on ATR: Two Simple Moving Averages (SMA) are applied to the ATR values. These SMAs act as a smoothed version of the ATR, providing additional insight into volatility trends. By adjusting the length of these SMAs, you can track short-term and long-term volatility movements, helping in decision-making for potential entries and exits.
Inputs:
ATR Length: Set the length for calculating the ATR.
Smoothing Method: Choose from RMA, SMA, EMA, or WMA for smoothing the ATR calculation.
Donchian Channel Length: Set the length for calculating the highest and lowest ATR values for Donchian Channels.
SMA Lengths: Two adjustable lengths for applying SMAs to the ATR.
Visualization:
ATR Plot: The ATR is plotted in red, allowing you to see the market's volatility at a glance.
Donchian Channels: Blue lines represent the upper and lower bands, while the green line represents the middle line of the Donchian Channels, helping you visualize the volatility range.
SMAs: Two SMAs (green and orange) are plotted to smooth out the ATR and identify trends in volatility.
Use Cases:
Breakout Detection: High ATR values breaking out of the Donchian Channels may signal increased volatility and a potential breakout.
Trend Analysis: SMAs on ATR help smooth volatility trends, aiding in determining if the market is entering a more volatile or stable period.
Stop-Loss Placement: ATR and Donchian Channels can be used to set dynamic stop-loss levels based on market volatility.
This script is versatile and can be used across different asset classes, such as stocks, forex, crypto, and commodities. It is especially useful for traders who want to incorporate volatility into their trading strategies for better risk management and trend detection.
RSI 30-50-70 moving averageDescription:
The RSI 30-50-70 Moving Average indicator plots three distinct moving averages based on different RSI ranges (30%, 50%, and 70%). Each moving average corresponds to different market conditions and provides potential entry and exit signals. Here's how it works:
• RSI_30 Range (25%-35%): The moving average of closing prices when the RSI is between 25% and 35%, representing potential oversold conditions.
• RSI_50 Range (45%-55%): The moving average of closing prices when the RSI is between 45% and 55%, providing a balanced perspective for trend-following strategies.
• RSI_70 Range (65%-75%): The moving average of closing prices when the RSI is between 65% and 75%, representing potential overbought conditions.
This indicator offers flexibility, as users can adjust key parameters such as RSI ranges, periods, and time frames to fine-tune the signals for their trading strategies.
How it Works:
Like traditional moving averages, the RSI 30-50-70 Moving Averages can highlight dynamic levels of support and resistance. They offer additional insight by focusing on specific RSI ranges, providing early signals for trend reversals or continuation. The default settings can be used across various assets but should be optimized via backtesting.
Default Settings:
• RSI_30: 25% to 35% (Oversold Zone, yellow line)
• RSI_50: 45% to 55% (Neutral/Trend Zone, green line)
• RSI_70: 65% to 75% (Overbought Zone, red line)
• RSI Period: 14
Buy Conditions:
• Use the 5- or 15-minute time frame.
• Wait for the price to move below the RSI_30 line, indicating potential oversold conditions.
• Enter a buy order when the price closes above the RSI_30 line, signaling a recovery from the oversold zone.
• For a more conservative approach, use the RSI_50 line as the buy signal to confirm a trend reversal.
• Important: Before entering, ensure that the RSI_30 moving average has flattened or started to level off, signaling that the oversold momentum has slowed.
Sell Conditions:
• Use the 5- or 15-minute time frame.
• Wait for the price to close above the RSI_70 line, indicating potential overbought conditions.
• Enter a sell order when the price closes below the RSI_70 line, signaling a decline from the overbought zone.
• Important: Similar to buying, wait for the RSI_70 moving average to flatten or level off before selling, indicating the overbought conditions are stalling.
Key Features:
1. Dynamic Range Customization: The indicator allows users to modify the RSI ranges and periods, tailoring the moving averages to fit different market conditions or asset classes.
2. Trend-Following and Reversal Signals: The RSI 30-50-70 moving averages provide both reversal and trend-following signals, making it a versatile tool for short-term traders.
3. Visual Representation of Market Strength: By plotting moving averages based on RSI levels, traders can visually interpret the market’s strength and potential turning points.
4. Risk Management: The built-in flexibility allows traders to choose lower-risk entries by adjusting which RSI level (e.g., RSI_30 vs. RSI_50) they rely on for signals.
Practical Use:
Different assets respond uniquely to RSI-based moving averages, so it's recommended to backtest and adjust ranges for specific instruments. For example, volatile assets may require wider RSI ranges, while more stable assets could benefit from tighter ranges.
Checking for Buy conditions:
1st: Wait for current price to go below the RSI_30 (yellow line)
2nd: Wait and observe for bullish divergence
3rd: RSI_30 has flattened indicating potential gain of momentum after a bullish divergence.
4th: Enter a buy order when the price closed above the RSI_30, preferably when a green candle appeared.
All In One Divergences Indicator - By CryptoEasonThis indicator displays divergences for multiple indicators on the chart. It includes divergences for volume, CCI, MACD, OBV, CMF, RSI, MFI, and maybe more in the future.
Below is an explanation of how divergences for these indicators are displayed:
1. Volume
I use volume to assess the strength of demand and supply. The way Volume divergences are calculated is similar to OBV.
Bearish Divergence: The price reaches a new high, but demand starts to weaken.
Bullish Divergence: The price reaches a new low, but supply starts to weaken.
2. CCI
Bearish Divergence: The price reaches a new high, but CCI forms a lower high, and the previous CCI peak is > 200.
Bullish Divergence: The price reaches a new low, but CCI forms a higher low, and the previous CCI low is < -200.
3. MACD
Bearish Divergence: The price reaches a new high, but the MACD lines cross at a lower point.
Bullish Divergence: The price reaches a new low, but the MACD lines cross at a higher point.
4. OBV
Bearish Divergence: The price reaches a new high, but OBV forms a lower high.
Bullish Divergence: The price reaches a new low, but OBV forms a higher low.
5. CMF
Bearish Divergence: The price reaches a new high, but CMF forms a lower high.
Bullish Divergence: The price reaches a new low, but CMF forms a higher low.
6. RSI
Bearish Divergence: The price reaches a new high, but RSI forms a lower high, and the previous RSI peak is > 70.
Bullish Divergence: The price reaches a new low, but RSI forms a higher low, and the previous RSI low is < 30.
7. MFI
Bearish Divergence: The price reaches a new high, but MFI forms a lower high, and the previous MFI peak is > 80.
Bullish Divergence: The price reaches a new low, but MFI forms a higher low, and the previous MFI low is < 20.
This indicator provides a sub-chart that displays seven indicators: Volume, CCI, MACD, OBV, CMF, RSI, and MFI.
When you find a divergence in the chart, I recommend using the sub-chart to check the real-time status of each indicator. This is important and is the way I use this indicator. Whenever a divergence signal appears, check the actual status of all the indicators with divergences.
Reminders:
1.Having too many divergence signals is not always better. Personally, I typically use divergences from four indicators: Volume, CCI, MACD, and OBV, and sometimes I add RSI. I recommend that you use divergence signals only from the indicators you are familiar with. If you're not familiar with a particular indicator, you can disable its divergence signals in the settings.
2.Some indicators are volume-related, such as OBV, Volume, MFI, and CMF. Therefore, the chart you're using should reflect the main trading volume of the market. For example, in the Bitcoin market, I recommend using the COINBASE:BTCUSD chart.
3.The divergence signals for MACD are displayed separately in this indicator. This is because the way MACD divergences are calculated is more complex. It requires the identification of the highs and lows of two MACD line crossovers, which is different from simply identifying the highs and lows of other indicators. Hence, MACD divergences are displayed separately in this indicator.
Note:
Although this indicator currently only shows divergences for seven indicators, I may add more divergence indicators in the future. If you would like to see divergence signals for a particular indicator included, or if you have any feature requests that are not currently offered, feel free to leave a comment and let me know.
============== 中文說明 (Chinese Introduction) ==============
這個指標是一個能在圖表上顯示多個指標背離的指標。
包括：成交量、CCI、MACD、OBV、CMF、RSI、MFI 等多個指標的背離。
以下說明這幾個指標背離的顯示方式：
1、成交量
我用成交量來判斷需求與供應強弱，它的背離判斷方式與OBV類似。
頂背離：價格創新高、但需求卻開始衰竭
底背離：價格創新低，但供應卻開始衰竭
2、CCI
頂背離：價格創新高、但CCI卻更低，且前一個高點 CCI > 200
底背離：價格創新低，但CCI卻更高，且前一個低點 CCI < -200
3、MACD
頂背離：價格創新高、但MACD快慢線交叉創下低點
底背離：價格創新低，但MACD 快慢線交叉雙下高點
4、OBV
頂背離：價格創新高、但OBV卻更低
底背離：價格創新低，但OBV卻更高
5、CMF
頂背離：價格創新高、但CMF卻更低
底背離：價格創新低，但CMF卻更高
6、RSI
頂背離：價格創新高、但RSI卻更低，且前一個高點 RSI > 70
底背離：價格創新低，但RSI卻更高，且前一個低點 RSI < 30
7、MFI
頂背離：價格創新高、但MFI卻更低，且前一個高點 MFI > 80
底背離：價格創新低，但MFI卻更高，且前一個低點 MFI < 20
該指標提供了副圖表，副圖表一共可顯示七個指標：成交量、CCI、MACD、OBV、CMF、RSI、MFI 。
當你發現當前價格出現背離時，我建議使用副圖表來一一檢查指標的真實情況，這很重要，這也是我使用這指標的方式，每當背離訊號出現時，檢查所有背離指標的真實情況。
提醒：
1、背離顯示並不是越多越好，我個人通常只使用 成交量、CCI、MACD、OBV 等四個指標的背離，偶爾會加上 RSI。我也建議你應該只使用自己熟悉的指標的背離，如果你不是很熟悉某個指標，那麼你可以在設定中取消顯示該指標的背離。
2、某些指標與成交量有關，例如OBV、Volume、MFI、CMF 等等，所以你使用的圖表應該要能反應市場的主要成交量，例如在比特幣市場裡，建議以 COINBASE:BTCUSD 圖表為主。
3、MACD 的背離訊號在這個指標裡是個別顯示的，因為MACD的背離判斷方式比較複雜，它需要判斷兩次快慢線交叉的高低點，跟其他指標只需要判斷高低點出現的值不太一樣，所以MACD背離在這個指標裡是單獨顯示的。
註：
雖然目前這個指標只有顯示七個指標的背離，但是未來我可能會加入更多指標的背離。如果你希望某個指標的背離訊號出現在這隻指標中，或是你想要某個功能但是目前這指標沒有提供，歡迎留言讓我知道。
Commitment of Trader %R StrategyThis Pine Script strategy utilizes the Commitment of Traders (COT) data to inform trading decisions based on the Williams %R indicator. The script operates in TradingView and includes various functionalities that allow users to customize their trading parameters.
Here’s a breakdown of its key components:
COT Data Import:
The script imports the COT library from TradingView to access historical COT data related to different trader groups (commercial hedgers, large traders, and small traders).
User Inputs:
COT data selection mode (e.g., Auto, Root, Base currency).
Whether to include futures, options, or both.
The trader group to analyze.
The lookback period for calculating the Williams %R.
Upper and lower thresholds for triggering trades.
An option to enable or disable a Simple Moving Average (SMA) filter.
Williams %R Calculation: The script calculates the Williams %R value, which is a momentum indicator that measures overbought or oversold levels based on the highest and lowest prices over a specified period.
SMA Filter: An optional SMA filter allows users to limit trades to conditions where the price is above or below the SMA, depending on the configuration.
Trade Logic: The strategy enters long positions when the Williams %R value exceeds the upper threshold and exits when the value falls below it. Conversely, it enters short positions when the Williams %R value is below the lower threshold and exits when the value rises above it.
Visual Elements: The script visually indicates the Williams %R values and thresholds on the chart, with the option to plot the SMA if enabled.
Commitment of Traders (COT) Data
The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides a breakdown of open interest positions held by different types of traders in the U.S. futures markets. It is widely used by traders and analysts to gauge market sentiment and potential price movements.
Data Collection: The COT data is collected from futures commission merchants and is published every Friday, reflecting positions as of the previous Tuesday. The report categorizes traders into three main groups:
Commercial Traders: These are typically hedgers (like producers and processors) who use futures to mitigate risk.
Non-Commercial Traders: Often referred to as speculators, these traders do not have a commercial interest in the underlying commodity but seek to profit from price changes.
Non-reportable Positions: Small traders who do not meet the reporting threshold set by the CFTC.
Interpretation:
Market Sentiment: By analyzing the positions of different trader groups, market participants can gauge sentiment. For instance, if commercial traders are heavily short, it may suggest they expect prices to decline.
Extreme Positions: Some traders look for extreme positions among non-commercial traders as potential reversal signals. For example, if speculators are overwhelmingly long, it might indicate an overbought condition.
Statistical Insights: COT data is often used in conjunction with technical analysis to inform trading decisions. Studies have shown that analyzing COT data can provide valuable insights into future price movements (Lund, 2018; Hurst et al., 2017).
Scientific References
Lund, J. (2018). Understanding the COT Report: An Analysis of Speculative Trading Strategies.
Journal of Derivatives and Hedge Funds, 24(1), 41-52. DOI:10.1057/s41260-018-00107-3
Hurst, B., O'Neill, R., & Roulston, M. (2017). The Impact of COT Reports on Futures Market Prices: An Empirical Analysis. Journal of Futures Markets, 37(8), 763-785.
DOI:10.1002/fut.21849
Commodity Futures Trading Commission (CFTC). (2024). Commitment of Traders. Retrieved from CFTC Official Website.
Momentum-Based Buy/Sell SignalsBuy Signal:
Triggered when ROC > threshold and the MACD line crosses above the Signal line.
Sell Signal:
Triggered when ROC < threshold and the MACD line crosses below the Signal line.
Visual Elements:
Green labels with "Buy" are displayed below the bars for buy signals.
Red labels with "Sell" are displayed above the bars for sell signals.
The background turns green during a buy signal and red during a sell signal for better visual clarity.
Open-Close Absolute Difference with Threshold CountsThe Open-Close Absolute Difference with Threshold Counts indicator is a versatile tool designed to help traders analyze the volatility and price movements within any given timeframe on their charts. This indicator calculates the absolute difference between the open and close prices for each bar, providing a clear visualization through a color-coded histogram.
Key features include:
• Timeframe Flexibility: Utilizes the current chart’s timeframe, whether it’s a 5-minute, hourly, or daily chart.
• Custom Thresholds: Allows you to set up to four custom threshold levels (Thresholds A, B, C, and D) with default values of 10, 15, 25, and 35, respectively.
• Period Customization: Enables you to define the number of bars (N) over which the indicator calculates the counts, with a default of 100 bars.
• Visual Threshold Lines: Plots horizontal dashed lines on the histogram representing each threshold for easy visual reference.
• Dynamic Counting: Counts and displays the number of times the absolute difference is less than or greater than each threshold within the specified period.
• Customizable Table Position: Offers the flexibility to position the results table anywhere on the chart (e.g., Top Right, Bottom Left).
How It Works:
1. Absolute Difference Calculation:
• For each bar on the chart, the indicator calculates the absolute difference between the open and close prices.
• This difference is plotted as a histogram:
• Green Bars: Close price is higher than the open price.
• Red Bars: Close price is lower than the open price.
2. Threshold Comparison and Counting:
• Compares the absolute difference to each of the four thresholds.
• Determines whether the difference is less than or greater than each threshold.
• Utilizes the ta.sum() function to count occurrences over the specified number of bars (N).
3. Results Table:
• Displays a table with three columns:
• Left Column: Counts where the absolute difference is less than the threshold.
• Middle Column: The threshold value.
• Right Column: Counts where the absolute difference is greater than the threshold.
• The table updates dynamically and can be positioned anywhere on the chart according to your preference.
4. Threshold Lines on Histogram:
• Plots horizontal dashed lines at each threshold level.
• Each line is color-coded for distinction:
• Threshold A: Yellow
• Threshold B: Orange
• Threshold C: Purple
• Threshold D: Blue
How to Use:
1. Add the Indicator to Your Chart:
• Open the Pine Editor on TradingView.
• Copy and paste the provided code into the editor.
• Click “Add to Chart.”
2. Configure Settings:
• Number of Bars (N):
• Set the period over which you want to calculate the counts (default is 100).
• Thresholds A, B, C, D:
• Input your desired threshold values (defaults are 10, 15, 25, 35).
• Table Position:
• Choose where you want the results table to appear on the chart:
• Options include “Top Left,” “Top Center,” “Top Right,” “Bottom Left,” “Bottom Center,” “Bottom Right.”
3. Interpret the Histogram:
• Observe the absolute differences plotted as a histogram.
• Use the color-coded bars to quickly assess whether the close price was higher or lower than the open price.
4. Analyze the Counts Table:
• Review the counts of occurrences where the absolute difference was less than or greater than each threshold.
• Use this data to gauge volatility and price movement intensity over the specified period.
5. Visual Reference with Threshold Lines:
• Refer to the horizontal dashed lines on the histogram to see how the absolute differences align with your thresholds.
Example Use Case:
Suppose you’re analyzing a 5-minute chart for a particular stock and want to understand its short-term volatility:
• Set the Number of Bars (N) to 50 to analyze the recent 50 bars.
• Adjust Thresholds based on the typical price movements of the stock, e.g., Threshold A: 0.5, Threshold B: 1.0, Threshold C: 1.5, Threshold D: 2.0.
• Position the Table at the “Top Right” for easy viewing.
By doing so, you can:
• Quickly see how often the stock experiences significant price movements within 5-minute intervals.
• Make informed decisions about entry and exit points based on the volatility patterns.
• Customize the thresholds and periods as market conditions change.
Benefits:
• Customizable Analysis: Tailor the indicator to fit various trading styles and timeframes.
• Quick Visualization: Instantly assess market volatility and price movement direction.
• Enhanced Decision-Making: Use the counts and visual cues to make more informed trading decisions.
• User-Friendly Interface: Simple configuration and clear display of information.
Note: Always test the indicator with different settings to find the configuration that best suits your trading strategy. This indicator should be used as part of a comprehensive analysis and not as the sole basis for trading decisions.
Volume-Weighted Trend Strength indexVolume-Weighted Trend Strength index (VWTSI)
Introduction
The VWTSI is a custom indicator designed to combine trend strength, volume, and volatility to give traders a comprehensive view of market dynamics. It provides flexibility by allowing you to visualize the indicator as either an oscillator or a moving average.
Features
Dual Visualization: Can be displayed either as an oscillator or as a moving average on the chart.
Volume-Weighted: Adjusts trend strength based on current volume compared to its average.
Volatility-Adjusted: Incorporates market volatility into the trend strength calculation.
Customizable: Various parameters can be fine-tuned to suit different trading environments.
How It Works
1. Trend Strength Calculation
The difference between the fast (10-period) and slow (30-period) EMAs is used to calculate trend strength, which gives a percentage-based indication of the trend's strength
2. Volatility Adjustment
The ATR-based volatility is calculated and used to amplify or reduce the trend strength based on the current market conditions
3. Volume Adjustment
The ratio of current volume to the volume SMA adds another layer of adjustment to the final VWTSI value
4. Final VWTSI Calculation
The VWTSI value is the product of trend strength, volatility factor, and volume ratio
5. Normalization
The final VWTSI is normalized to fit within a range of -100 to 100 for better visualization in oscillator mode
Customization Inputs
Fast EMA Length: Default is 10.
Slow EMA Length: Default is 30.
Volume Length: Default is 14.
Volatility Length (ATR): Default is 20.
Oscillator or MA Mode: Toggle between displaying the indicator as an oscillator or moving average.
Order Book Pressure Index (OBPI)Overview
The Order Book Pressure Index (OBPI) is a custom technical indicator designed to provide traders with a real-time approximation of market pressure by analyzing buying and selling volumes. Unlike traditional indicators that rely heavily on historical price data, the OBPI focuses on current price movements and volume dynamics to offer a more responsive tool for detecting potential market shifts.
Key Features
Approximation of Order Book Pressure : Estimates market pressure by calculating the cumulative delta volume based on price movements and corresponding volumes. False Signal Filtering : Incorporates threshold levels and moving averages to reduce market noise and minimize false trading signals. Multi-Timeframe Analysis : Allows selection of multiple higher timeframes for signal confirmation, enhancing signal reliability. Customizable Parameters : Offers adjustable settings for thresholds, moving average periods, and the number of bars used in calculations.
How It Works
Volume Direction Calculation : Determines the price direction for each bar: Bullish : Closing price > Opening price; volume attributed to buying pressure. Bearish : Closing price < Opening price; volume attributed to selling pressure. Delta Volume Calculation : Computes the difference between buying and selling volumes to obtain the delta volume for each bar. Cumulative Delta Volume : Calculates the cumulative sum of delta volumes over a specified number of bars (user-defined), focusing on recent market activity. Moving Average Application : Applies a moving average to the cumulative delta volume to smooth out short-term fluctuations and highlight underlying trends. Signal Generation with Thresholds : Threshold Levels : User-defined thresholds identify significant changes in market pressure. Buy Signal : Triggered when the cumulative delta volume crosses above the positive threshold and is above its moving average. Sell Signal : Triggered when the cumulative delta volume crosses below the negative threshold and is below its moving average. Multi-Timeframe Filtering : Timeframe Selection : Traders can select multiple higher timeframes (e.g., 15 min, 30 min, 1 hr, 4 hr) via checkboxes. Signal Aggregation : The indicator aggregates signals from the selected timeframes. Final Signal Generation : A buy or sell signal is generated only if it is present on the current timeframe and at least one of the selected higher timeframes.
How to Use
1. Indicator Settings
Max Bars : Sets the maximum number of bars for cumulative delta volume calculation. A smaller number increases responsiveness by focusing on recent activity. Moving Average Period : Adjusts the period for the moving average applied to the cumulative delta volume. A shorter period increases sensitivity; a longer period smooths out noise. Signal Threshold : Defines the minimum delta volume required to generate a signal. Higher thresholds filter out minor fluctuations. Timeframe Selection : Use the checkboxes to select higher timeframes for multi-timeframe analysis. Available timeframes include 15 min, 30 min, 1 hr, and 4 hr.
2. Interpreting the Signals
Buy Signal (Green Triangle Up) : Indicates potential bullish market pressure. Consider entering long positions when the signal appears. Sell Signal (Red Triangle Down) : Indicates potential bearish market pressure. Consider entering short positions or exiting long positions when the signal appears. Signal Confirmation : For higher reliability, ensure that the signal aligns across multiple timeframes. The signal is stronger when confirmed by selected higher timeframes.
3. Trading Strategies
Trend Following : Use the indicator to identify and follow prevailing market trends. Enter trades in the direction of the cumulative delta volume. Reversal Signals : Look for divergences between price movements and the OBPI to anticipate potential market reversals. Risk Management : Always implement appropriate stop-loss and take-profit levels. Combine the OBPI with sound risk management practices.
Best Practices
Combine with Other Indicators : Enhance signal reliability by using the OBPI alongside indicators like RSI, MACD, or support and resistance levels. Adjust Parameters : Test different settings in a demo account to find optimal parameters for your trading style and the specific asset. Market Conditions : Be mindful of market volatility and liquidity, as extreme conditions can affect indicator performance. Backtesting : Conduct thorough backtesting over historical data before applying the indicator to live trading.
Limitations
Approximation : The OBPI provides an approximation of market pressure and does not access actual order book data. Lag in Higher Timeframes : Signals from higher timeframes may lag, affecting the timeliness of combined signals. Complexity : Multi-timeframe features increase complexity and may impact performance on some platforms.
Conclusion
The Order Book Pressure Index (OBPI) offers traders a unique perspective by focusing on current price movements and volume. Its ability to filter false signals and incorporate multi-timeframe analysis makes it a valuable addition to any trading strategy. Remember to use it in conjunction with other analytical methods and always practice prudent risk management.
Disclaimer : Trading involves significant risk. The OBPI indicator is a tool to aid decision-making and does not guarantee profitable trades. Perform your own analysis and consider consulting a financial advisor before making trading decisions.
Distance From moving averageDistance From Moving Average is designed to help traders visualize the deviation of the current price from a specified moving average. Users can select from four different types of moving averages: Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), and Hull Moving Average (HMA).
Key Features:
User-Friendly Input Options:
Choose the type of moving average from a dropdown menu.
Set the length of the moving average, with a default value of 200.
Custom Moving Average Calculations:
The script computes the selected moving average using the appropriate mathematical formula, allowing for versatile analysis based on individual trading strategies.
Distance Calculation:
The indicator calculates the distance between the current price and the chosen moving average, providing insight into market momentum. A positive value indicates that the price is above the moving average, while a negative value shows it is below.
Visual Representation:
The distance is plotted on the chart, with color coding:
Lime: Indicates that the price is above the moving average (bullish sentiment).
Red: Indicates that the price is below the moving average (bearish sentiment).
Customization:
Users can further customize the appearance of the plotted line, enhancing clarity and visibility on the chart.
This indicator is particularly useful for traders looking to gauge market conditions and make informed decisions based on the relationship between current prices and key moving averages.
RTI For Loop | viResearchRTI For Loop | viResearch
Conceptual Foundation and Innovation
The "RTI For Loop" script introduces a unique approach to analyzing market trends by leveraging the concept of Relative Trend Index (RTI) within a loop-based scoring system. The RTI measures the price's relative position between an upper and lower trend boundary, dynamically calculated using standard deviations. This provides a clearer picture of market momentum and trend strength. The scoring mechanism, which iterates through a specified range of values, offers a robust framework for detecting trend shifts and potential reversals with heightened accuracy. By incorporating trend sensitivity and length parameters, the script allows users to fine-tune the analysis according to market conditions, making it adaptable for various trading strategies.
Technical Composition and Calculation
The "RTI For Loop" script consists of several technical components designed to offer precise trend analysis. The upper and lower trends are calculated using the price's standard deviation, which creates dynamic boundaries for evaluating price movements. Users can adjust the sensitivity of the trend boundaries with a percentage input, allowing the script to respond to different market volatility levels. At the core of the script is a for-loop scoring system that evaluates whether the RTI is above or below a specified range of values. The score adjusts accordingly, helping to identify trend strength and momentum. Additionally, the script includes an Exponential Moving Average (EMA) applied to the score to smooth out fluctuations, providing a clearer trend signal.
Features and User Inputs
The script offers a variety of user inputs that can be adjusted to suit different trading environments. Trend Length defines the number of data points used to calculate the upper and lower trends, influencing the indicator's sensitivity to trend changes. Trend Sensitivity adjusts the percentage of price data used to define the upper and lower trend boundaries. Thresholds allow for customizable levels to detect uptrends and downtrends, enabling traders to control when signals are triggered. The EMA Length provides control over smoothing the RTI score, reducing noise and clarifying trends. Bar Color Settings offer optional visual cues that highlight trend direction by changing bar colors based on trend signals.
Practical Applications
The "RTI For Loop" script is ideal for traders who seek a more nuanced and dynamic analysis of market trends. It is particularly effective in detecting trend reversals, as the loop-based scoring system offers early identification of shifts in momentum. By evaluating the RTI across a range of values and applying EMA smoothing, the script helps confirm the strength and direction of trends. Its customizable inputs allow traders to adapt the indicator to various market conditions, making it suitable for both short-term and long-term strategies.
Advantages and Strategic Value
This script enhances traditional trend analysis by incorporating a loop-based scoring mechanism, reducing the likelihood of false signals and providing more reliable trend identification. The ability to dynamically adjust trend sensitivity based on market conditions makes it a versatile tool for traders aiming to improve their trend-following strategies. The RTI-based approach also provides deeper insights into market behavior, offering a more detailed view of price dynamics compared to simple moving averages or momentum indicators.
Summary and Usage Tips
The "RTI For Loop" script is a powerful tool that combines trend analysis, a for-loop scoring mechanism, and EMA smoothing to provide traders with a reliable method for detecting and confirming trends. By incorporating this indicator into your trading strategy, you can gain greater confidence in identifying trend shifts and managing trades more effectively. Traders can adjust the sensitivity and length parameters to adapt to different market conditions, ensuring that the indicator remains responsive to changing volatility and trends.
Note: Backtests are based on past results and are not indicative of future performance.
Mongoose multi time frame RSI quick glance w/alertsThis Pine Script helps you identify overbought and oversold conditions for any stock, index, or cryptocurrency you're monitoring, across three different time frames (daily, weekly, and monthly). It uses the Relative Strength Index (RSI) as the indicator for these conditions. Here’s a breakdown of what the script does and what it tells you:
Key Features:
RSI Indicator:
The script calculates the RSI for three different timeframes: daily, weekly, and monthly.
RSI is a momentum oscillator that measures the speed and change of price movements, typically on a scale from 0 to 100:
Overbought: RSI > 70 (This could indicate the asset is overvalued and may see a price correction).
Oversold: RSI < 30 (This could indicate the asset is undervalued and may see a price rebound).
Color-Coded Background:
The script visually highlights overbought and oversold conditions by coloring the chart background:
Blue for Daily overbought/oversold.
Green for Weekly overbought/oversold.
Red for Monthly overbought/oversold.
Overbought areas will have the colored background whenever the RSI is above 70.
Oversold areas will have the colored background when the RSI drops below 30.
Multiple Timeframes:
The script checks these overbought and oversold levels on three timeframes (daily, weekly, and monthly) simultaneously, giving you a broad view of the market’s momentum.
This helps you determine whether a price movement is part of a short-term fluctuation (daily), a mid-term trend (weekly), or a long-term cycle (monthly).
Alerts:
If the RSI crosses the overbought or oversold threshold for any of these timeframes, the script will trigger an alert.
The alert message includes the name of the stock or cryptocurrency and the timeframe in which the condition occurred (e.g., "Daily Overbought").
How to Use This Information:
Trading Decisions: You can use this script to help decide when to enter or exit trades based on whether an asset is overbought or oversold in different timeframes.
Buy Signal: When RSI is oversold (below 30) and you expect a price rebound.
Sell Signal: When RSI is overbought (above 70) and you expect a price correction.
Long-Term vs Short-Term: By analyzing the three timeframes, you can tailor your strategy to short-term trades (daily RSI) or longer-term investments (weekly or monthly RSI).
In essence, this script gives you a multi-timeframe RSI-based view of potential reversal points in the market, visually coded for clarity, and alerts you when those levels are hit across different timeframes.
Pi Cycle Top & Bottom Indicator [InvestorUnknown]The Pi Cycle Top & Bottom Indicator is designed for long-term cycle analysis, particularly useful for detecting significant market tops and bottoms in assets like Bitcoin. By comparing the behavior of two moving averages, one with a shorter period (default 111) and the other with a longer period (default 350), the indicator helps investors identify potential turning points in the market.
Key Features:
Dual Moving Average System:
The indicator uses two moving averages (MA) to create a cyclic oscillator. The shorter moving average (Short Length MA) is more reactive to recent price changes, while the longer moving average (Long Length MA) smooths out long-term trends. Users can select between:
Simple Moving Average (SMA): A straightforward average of closing prices.
Exponential Moving Average (EMA): Places more weight on recent prices, making it more responsive to market changes.
Oscillator Mode Options:
The Pi Cycle Indicator offers two modes of oscillation to better suit different analysis styles:
RAW Mode: This mode calculates the raw ratio of the Short MA to the Long MA, offering a simple comparison of the two averages.
LOG(X) Mode: In this mode, the oscillator takes the natural logarithm of the Short MA to Long MA ratio. This transformation compresses extreme values and highlights relative changes more effectively, making it particularly useful for spotting shifts in long-term trends.
Cyclical Analysis:
The core of the Pi Cycle Indicator is its ability to visualize the relationship between the two moving averages. The ratio of the Short MA to the Long MA is plotted as an oscillator. When the oscillator crosses above or below a baseline (which is 1 for RAW mode and 0 for LOG(X) mode), it signals potential market turning points.
Visual Representation:
The indicator provides a clear visual display of market conditions:
Orange Line: Represents the Pi Cycle Oscillator, which shows the relationship between the short and long moving averages.
Gray Baseline: A reference line that dynamically adjusts based on the oscillator mode. Crosses above or below this line help indicate possible trend reversals.
Shaded Areas: Color-filled areas between the oscillator and the baseline, which are shaded green when the market is bullish (oscillator above baseline) and red when bearish (oscillator below baseline). This provides a visual cue to assist in identifying potential market tops and bottoms.
Use Cases:
The Pi Cycle Top & Bottom Indicator is primarily used in long-term market analysis, such as Bitcoin cycles, to identify significant tops and bottoms. These moments often coincide with large cyclical shifts, making it valuable for those aiming to enter or exit positions at key moments in the market cycle.
By analyzing the interaction between short-term and long-term trends, investors can gain insight into broader market dynamics and make more informed decisions regarding entry and exit points. The ability to switch between moving average types (SMA/EMA) and oscillator modes (RAW/LOG) adds flexibility for adapting to different market environments.
MTF Squeeze Analyzer - [tradeviZion]MTF Squeeze Analyzer
Multi-Timeframe Squeeze Pro Analyzer Tool
Overview:
The MTF Squeeze Analyzer is a comprehensive tool designed to help traders monitor the TTM Squeeze indicator across multiple timeframes in a streamlined and efficient manner. Built with Pine Script™ version 5, this indicator enhances your market analysis by providing detailed insights into squeeze conditions and momentum shifts, enabling you to make more informed trading decisions.
Key Features:
1. Multi-Timeframe Monitoring:
Comprehensive Coverage: Track squeeze conditions across multiple timeframes, including 1-minute, 5-minute, 15-minute, 30-minute, 1-hour, 2-hour, 4-hour, and daily charts.
Squeeze Counts: Keep count of the number of consecutive bars the price has been within each squeeze level (low, mid, high), helping you assess the strength and duration of consolidation periods.
2. Dynamic Table Display:
Customizable Appearance: Adjust table position, text size, and colors to suit your preferences.
Color-Coded Indicators: Easily identify squeeze levels and momentum shifts with intuitive color schemes.
Message Integration: Features rotating messages to keep you engaged and informed.
3. Alerts for Key Market Events:
Squeeze Start and Fire Alerts: Receive notifications when a squeeze starts or fires on your selected timeframes.
Custom Squeeze Count Alerts: Set thresholds for squeeze counts and get alerted when these levels are reached, allowing you to anticipate potential breakouts.
Fully Customizable: Choose which alerts you want to receive and tailor them to your trading strategy.
4. Momentum Analysis:
Momentum Oscillator: Visualize momentum using a histogram that changes color based on momentum shifts.
Detailed Insights: Determine whether momentum is increasing or decreasing to make more strategic trading decisions.
How It Works:
The indicator is based on the TTM Squeeze concept, which identifies periods of low volatility where the market is "squeezing" before a potential breakout. It analyzes the relationship between Bollinger Bands and Keltner Channels to determine squeeze conditions and uses linear regression to calculate momentum.
1. Squeeze Levels:
No Squeeze (Green): Market is not in a squeeze.
Low Compression Squeeze (Gray): Mild consolidation, potential for a breakout.
Mid Compression Squeeze (Red): Moderate consolidation, higher breakout potential.
High Compression Squeeze (Orange): Strong consolidation, significant breakout potential.
2. Squeeze Counts:
Tracks the number of consecutive bars in each squeeze condition.
Helps identify how long the market has been consolidating, providing clues about potential breakout timing.
3. Momentum Histogram:
Upward Momentum: Shown in aqua or blue, indicating increasing or decreasing upward momentum.
Downward Momentum: Displayed in red or yellow, representing increasing or decreasing downward momentum.
Using Alerts:
Stay ahead of market movements with customizable alerts:
1. Enable Alerts in Settings:
Squeeze Start Alert: Get notified when a new squeeze begins.
Squeeze Fire Alert: Be alerted when a squeeze ends, signaling a potential breakout.
Squeeze Count Alert: Set a specific number of bars for a squeeze condition, and receive an alert when this count is reached.
2. Set Up Alerts on Your Chart:
Click on the indicator name and select " Add Alert on MTF Squeeze Analyzer ".
Choose your desired alert conditions and customize the notification settings.
Click " Create " to activate the alerts.
How to Set It Up:
1. Add the Indicator to Your Chart:
Search for " MTF Squeeze Analyzer " in the TradingView Indicators library.
Add it to your chart.
2. Customize Your Settings:
Table Display:
Choose whether to show the table and select its position on the chart.
Adjust text size and colors to enhance readability.
Timeframe Selection:
Select the timeframes you want to monitor.
Enable or disable specific timeframes based on your trading strategy.
Colors & Styles:
Customize colors for different squeeze levels and momentum shifts.
Adjust header and text colors to match your chart theme.
Alert Settings:
Enable alerts for squeeze start, squeeze fire, and squeeze counts.
Set your preferred squeeze type and count threshold for alerts.
3. Interpret the Data:
Table Information:
The table displays the squeeze status and counts for each selected timeframe.
Colors indicate the type of squeeze, making it easy to assess market conditions at a glance.
Momentum Histogram:
Use the histogram to gauge the strength and direction of market momentum.
Observe color changes to identify shifts in momentum.
Why Use MTF Squeeze Analyzer ?
Enhanced Market Insight:
Gain a deeper understanding of market dynamics by monitoring multiple timeframes simultaneously.
Identify potential breakout opportunities by analyzing squeeze durations and momentum shifts.
Customizable and User-Friendly:
Tailor the indicator to fit your trading style and preferences.
Easily adjust settings without needing to delve into the code.
Time-Efficient:
Save time by viewing all relevant squeeze information in one place.
Reduce the need to switch between different charts and timeframes.
Stay Informed with Alerts:
Never miss a critical market movement with fully customizable alerts.
Focus on other tasks while the indicator monitors the market for you.
Acknowledgment:
This tool builds upon the foundational work of John Carter , who developed the TTM Squeeze concept. It also incorporates enhancements from LazyBear and Makit0 , providing a more versatile and powerful indicator. MTF Squeeze Analyzer extends these concepts by adding multi-timeframe analysis, squeeze counting, and advanced alerting features, offering traders a comprehensive solution for market analysis.
Note: Always practice proper risk management and test the indicator thoroughly to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
Trade smarter with TradeVizion—unlock your trading potential today!
COT INDEXING | OPEN INTEREST [DIGGERDOG]COT INDEXING | OPEN INTEREST
This Pine Script for TradingView, titled **"COT INDEXING | OPEN INTEREST "**, is designed to analyze and visualize the **Open Interest (OI)** in conjunction with **COT (Commitment of Traders) data**. It calculates and plots an Open Interest index across multiple timeframes and highlights extreme values to help identify overbought or oversold market conditions.
Key Features:
1. **COT Data Retrieval**:
- The script fetches Open Interest from the **Legacy COT Report**.
- Open Interest data is also retrieved, representing the number of active contracts on the market. This is a key indicator of market participation.
2. **Multi-Timeframe Open Interest Index Calculation**:
- The script calculates the **Open Interest Index** across multiple timeframes (e.g., 26, 52, 156 weeks). For each timeframe, it calculates:
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- The index values show where the current Open Interest stands relative to historical extremes (high and low) over each timeframe.
3. **Extreme Value Highlighting**:
- The script highlights extreme values by marking Open Interest values above a user-defined **extreme high threshold** and below an **extreme low threshold**.
- **Red background**: Indicates Open Interest is above the extreme high threshold (potentially overbought).
- **Green background**: Indicates Open Interest is below the extreme low threshold (potentially oversold).
4. **Visualizations**:
- The script plots the **Open Interest Index** for each timeframe as a line chart.
- It also includes horizontal reference lines at 80, 50, and 20, representing typical thresholds for overbought, neutral, and oversold conditions.
5. **Customizable Inputs**:
- **Timeframes**: Users can define the time periods for the Open Interest Index calculation (e.g., 26, 52, 156 weeks).
- **Extreme Thresholds**: The **high** and **low** thresholds can be adjusted to customize the extreme levels for overbought or oversold signals.
- **Color Settings**: Colors for the plot lines and background can be customized for better visualization.
How It Works:
1. **Open Interest Index Calculation**:
- The script calculates the Open Interest Index for three different timeframes (e.g., short-term, medium-term, long-term). Each index is plotted to show how the current Open Interest compares to historical values.
2. **Extreme Value Highlighting**:
- The background color of the chart changes based on whether the Open Interest Index crosses above or below the user-defined extreme thresholds. This helps visually identify potentially overbought or oversold conditions.
3. **Multi-Timeframe Analysis**:
- By calculating the index over multiple timeframes, traders can gain insights into both short-term and long-term trends in Open Interest. This helps identify whether recent Open Interest changes are part of a larger trend or just short-term fluctuations.
Usage:
- **Market Sentiment Analysis**: Open Interest is a measure of market participation, and changes in OI can indicate shifts in market sentiment. For example, rising Open Interest during a price increase suggests a strong trend, while falling Open Interest may signal weakening momentum.
- **Trend Confirmation**: When Open Interest is rising alongside price trends, it confirms that new participants are entering the market. Conversely, falling OI during price movements suggests that the trend might lack strength.
- **Overbought/Oversold Identification**: The extreme thresholds help identify when the Open Interest has reached levels that might signal an overbought or oversold market, indicating a potential reversal.
### Example Use Case:
- A trader could use this script to monitor whether the market is gaining or losing participation (via Open Interest) as the price of a commodity moves. If Open Interest is rising along with price, this suggests a strong trend. If Open Interest starts to fall while the price rises, it could signal that the trend is running out of steam.
### Customizable Features:
- **Timeframe Adjustments**: The user can set different timeframes (e.g., short, medium, long-term) for the Open Interest Index calculation.
- **Extreme Thresholds**: Define custom thresholds for overbought and oversold conditions to suit your trading strategy. (only timeframe 1)
- **Color and Visual Settings**: Adjust the colors of the plots and background to better fit your charting style. (only timeframe 1)
This script provides a clear visual representation of Open Interest trends across multiple timeframes and highlights potential market turning points based on extreme levels in Open Interest. By integrating this with price analysis, traders can get a better sense of market momentum and strength.
UNDERWATER EQUITY INDEX [DIGGERDOG]UNDERWATER EQUITY INDEX
This TradingView Pine Script titled **"UNDERWATER EQUITY INDEX "** displays the percentage drawdown of an equity curve and calculates an RSI-based oscillator based on the drawdown. The oscillator is smoothed and presented with optimized colors to visually highlight bullish, bearish, and potential reversal trends.
Script Explanation:
1. **Variable Initialization:**
- `highestEquity`: This variable stores the highest value of the equity curve.
- `underwaterEquity`: This variable stores the current drawdown, calculated as a percentage relative to the highest equity value.
2. **Equity Curve:**
- The script uses the closing price (`close`) as a placeholder for the equity curve. In a real-world application, this could be replaced with an actual equity curve.
3. **Highest Equity Calculation:**
- The `highestEquity` is updated as the highest recorded equity value. If the variable is uninitialized (`na`), it is set to the current equity value.
4. **Drawdown Calculation:**
- The drawdown is calculated as the percentage difference between the current equity and the highest recorded equity value.
5. **RSI-Based Oscillator:**
- The oscillator (`osc`) is calculated using the RSI (Relative Strength Index) over a 13-period window based on the drawdown and is smoothed using a simple moving average (SMA) over 9 periods.
6. **Plot Colors:**
- **Green**: Bullish trend (equity increasing above the zero line).
- **Orange**: Warning signal (falling trend above the zero line).
- **Blue**: Potential bullish reversal (rising trend below the zero line).
- **Red**: Bearish trend (falling trend below the zero line).
7. **Plotting the Oscillator:**
- The smoothed oscillator is plotted as a line with the color codes mentioned above.
8. **Threshold Lines:**
- Three horizontal lines at 30, 50, and 70 indicate extreme points (30 and 70 signal oversold and overbought conditions, respectively).
9. **Marking Extremes:**
- When enabled, the script marks extreme values in the oscillator with a green background when the value exceeds 60 (potentially overbought) and a red background when it falls below 40 (potentially oversold).
Usage:
- **Drawdown Analysis**: Track drawdowns in the equity curve to assess risk performance.
- **Trend and Reversal Signals**: The smoothed RSI-based oscillator indicates potential bullish or bearish phases, including warning signals for possible reversals.
- **Visualization of Extremes**: Utilize the background highlighting of extreme oscillator values to immediately recognize overbought or oversold conditions.
This script is useful for monitoring risk and drawdowns while visually presenting key trend information. If you have further questions or need adjustments, feel free to let me know!
OBV OSCILLATOR [DIGGERDOG]OBV OSCILLATOR
This Pine Script for TradingView titled "OBV OSCILLATOR " is designed to plot the On-Balance Volume (OBV) Oscillator with both a smoothed and an unsmoothed version, allowing you to visualize trends in volume flow. It also highlights bullish and bearish zones with background colors and shows key levels on the chart.
Here’s a breakdown of the script’s functionality:
### **Inputs:**
- **OBV Normalization Period** (`obvLength`): Default is 14 periods for the calculation of the highest and lowest OBV values.
- **OBV Smoothing** (`obvSmoothing`): Default is 9 periods, applying a moving average to smooth the OBV values.
- **OBV Upper Limit** (`obvUpperLimit`): Default is 50, used to determine bullish zones.
- **OBV Lower Limit** (`obvLowerLimit`): Default is 50, used to determine bearish zones.
### **Calculations:**
- **OBV (On-Balance Volume):**
- The script calculates cumulative OBV using the formula `ta.cum(close > close ? volume : close < close ? -volume : 0)`.
- **OBV Oscillator:**
- The OBV is normalized by calculating its position between the highest and lowest OBV values over the given period (`obvLength`).
- Formula: `obvOscillator = 100 * (obv - obvMin) / (obvMax - obvMin)`, which scales the OBV between 0 and 100.
- **Smoothed OBV:**
- The OBV is further smoothed using a simple moving average (SMA) over the `obvSmoothing` period.
- A separate OBV Oscillator is then calculated for the smoothed OBV using the same normalization formula.
### **Visuals:**
- **OBV Oscillator and Smoothed OBV:**
- The unsmoothed OBV Oscillator is plotted in **blue**.
- The smoothed OBV Oscillator is plotted in **red** with some transparency for easier differentiation.
- **Background Color:**
- The background turns **light green** when the OBV Oscillator is above the upper limit (bullish).
- The background turns **light red** when the OBV Oscillator is below the lower limit (bearish).
- **Key Levels:**
- A **gray dotted line** represents the middle value (50).
- **Green and red dotted lines** represent the upper and lower OBV limits, respectively.
### **Usage:**
- Use the OBV Oscillator to identify strong trends based on volume flow.
- The smoothed OBV Oscillator helps filter out noise and offers a more stable trend signal.
- The background color changes provide quick visual cues for bullish and bearish conditions.
If you need further modifications or explanation, feel free to ask!
Trend CCITrend CCI (TCCI) Indicator
Description:
The Trend CCI (TCCI) indicator is a unique combination of the Commodity Channel Index (CCI) and the Average True Range (ATR), designed to identify trends and market reversals with a refined sensitivity to price volatility. The indicator plots the CCI, adjusted by an ATR filter, and color-codes the trendline to signal uptrends and downtrends.
How It Works:
This indicator uses the CCI to measure price momentum and an ATR-based filter to smooth out market noise, making it easier to detect significant shifts in the market trend. Key parameters such as the ATR Period, ATR Multiplier, and CCI Period have been carefully chosen to optimize the indicator's performance:
1. ATR Period (default: 18)
The ATR Period determines the number of periods used to calculate the **Average True Range**, which reflects market volatility. In this case, an **ATR Period of 18** has been selected for several reasons:
Balance between responsiveness and noise reduction : A period of 18 strikes a balance between being responsive to recent price movements and filtering out minor fluctuations. Shorter ATR periods might be too reactive, creating false signals, while longer periods might miss shorter-term trends.
Adaptable to various market conditions : An 18-period ATR is suitable for both intraday and swing trading strategies, making it versatile across different time frames.
Standard industry practice : Many traders use ATR settings between 14 and 20 periods as a convention for detecting reliable volatility levels.
2. ATR Multiplier (default: 1.5)
The ATR Multiplier is applied to the ATR value to define how sensitive the indicator is to volatility. In this case, a multiplier of 1.5 has been chosen:
Avoiding whipsaws in low volatility markets: By setting the multiplier to 1.5, the indicator filters out smaller, less significant price movements, reducing the likelihood of whipsaw signals (i.e., false trend reversals during periods of low volatility).
Optimizing signal accuracy: A moderate multiplier like 1.5 ensures that the indicator only generates signals when the price moves a significant distance from the average range. Higher multipliers (e.g., 2.0) may ignore valid opportunities, while lower multipliers (e.g., 1.0) might create too many signals.
Enhancing trend clarity : The multiplier’s role in widening the range allows the indicator to respond more clearly during periods of strong trends, reducing signal noise and false positives.
3. CCI Period (default: 63)
The CCI Period defines the number of periods used to calculate the Commodity Channel Index. A 63-period CCI is selected based on the following considerations:
Smoothing the momentum calculation: A longer period, such as 63, is used to smooth out the CCI and reduce the effects of short-term price fluctuations. This period captures longer-term momentum, making it ideal for identifying more significant market trends.
-Filtering out short-term noise: While shorter CCI periods (e.g., 14 or 20) may be more reactive, they tend to produce more signals, some of which may be false. A 63-period CCI focuses on stronger and more sustained price movements, providing fewer but higher-quality signals.
Adapted to intermediate trading: A 63-period CCI aligns well with traders looking for medium-term trend-following strategies, striking a balance between long-term trend identification and responsiveness to significant price shifts.
How to Use:
Green Area: When the trendline turns green, it signals that the CCI is positive, reflecting upward momentum. This can be interpreted as a buy signal, indicating the potential for long positions or continuing bullish trades.
Red Area: When the trendline turns red, it signals that the CCI is negative, reflecting downward momentum. This can be interpreted as a sell signal, indicating potential short positions or bearish trades.
ATR Filter: The ATR helps reduce false signals by ignoring minor price movements. Traders can adjust the ATR Multiplier to make the indicator more or less sensitive based on market conditions. A lower multiplier (e.g., 1.2) may increase signal frequency, while a higher multiplier (e.g., 2.0) reduces it.
Originality:
The Trend CCI (TCCI) stands out due to its combination of the CCI and ATR. While many indicators simply plot raw CCI values, this script enhances the CCI’s effectiveness by incorporating an ATR-based volatility filter. This ensures that only significant trends trigger signals, making it a more reliable tool in volatile markets. The choice of the ATR period, multiplier, and CCI period ensures a refined balance between trend detection and noise reduction, distinguishing it as a powerful trend-following indicator.
Additionally, the visual aspect—using color-coded trendlines that dynamically shift between green and red—simplifies the interpretation of market trends, offering traders a clear and immediate understanding of trend direction and momentum strength.
Final Recommendations:
Use in Trending Markets The TCCI is most effective in trending markets, where its signals align with broader market momentum. In sideways or low-volatility markets, consider adjusting the ATR multiplier or using other complementary indicators to confirm the signals.
Risk Management: Always integrate robust risk management practices, such as using stop-loss orders and position sizing, to protect against sudden market reversals or periods of heightened volatility.
Adjust for Volatility: Consider the volatility of the asset being traded. In highly volatile assets, a higher ATR multiplier (e.g., 2.0) may be necessary to filter out noise, while in more stable assets, a lower multiplier (e.g., 1.2) might generate earlier signals.
By using the Trend CCI (TCCI) indicator with a deeper understanding of its key parameters, traders can better identify trends, reduce noise, and improve their overall decision-making in the markets.
Good Profits!
