RexDog AverageYes, simple—the RexDog Average is a bias moving average indicator. The purpose is to provide the overall momentum bias you should have when trading an instrument. It works across all markets and all timeframes.
Usage:
Price above the RexDog AVG = long momentum bias
Price below the RexDog AVG = short momentum bias
*Note: we have banned the word “trend” in the RexDog Trading Method.
Additional Usage Advice:
If price rips through the average your momentum bias should probably change. 80% of the time when price moves through the RexDog Average it will come back and test the area around average within 1-2 bars. 20% of the time it does not. The momentum is so strong in that direction so look for a 50-70% tests of the bar that impulse through the RexDog Average.
If you are using the RexDog Trading Method by default if the price is above the average and you are short you are in a fade trade. The momentum trade would be long. Of course reverse if price is below.
On multiple time frames. Of course, one timeframe can be long bias and a lower timeframe can be short bias. Which one do you use? Both—if your in a short trade using lower timeframe and with the bias of the average your in a momentum trade—but on the higher timeframe your aware you are essential fading the overall momentum.
Background:
Rex and I searched high and low for one simple thing. A moving average (or combination of some) that we could use to form our momentum bias that worked for all timeframes and all markets we trade.
We tried and tested them all. Even went down the path of ribbons and various other types of hybrid EMA/MA derivatives. Nothing had a high enough accuracy or mathematically was reliable that we could say with a high probability that it was on the right side of the momentum.
We almost stopped and landed on using the true and tested 200 MA—but we found through extensive tests that using the 200MA or EMA you’re often late to the party. Look you don’t need to be the first one in the trade but having a heads up sure helps.
To quote one of the best financial movies of the modern era—Margin Call:
“There are three ways to make a living in this business: be first, be smarter, or cheat… it sure is a hell of a lot easier to be first”. The RexDog Average used properly enables you to be first or damn near close.
Under the Hood:
This is so simple most reading this will discount it. You might even scoff and berate Rex for wasting your time. But you would be wrong. The RexDog Average has been tested across all markets—FOREX, Crypto, Equities, Futures (even tick charts), and even the Penguin population in Antarctica.
The RexDog Average is an average of 6 simple moving averages: 200, 100, 50, 24, 9, 5.
Yes, that’s it.
The RexDog Average Plus will be released soon with additional parameters and most likely upper and lower bounds. In addition, we are working on a hybrid RexDog Exponential Average.
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CT Reverse True Strength Indicator On ChartIntroducing the Caretakers “On Chart” Reverse True Strength Index.
According to Wikipedia….
“The True Strength Index (TSI) is a technical indicator used in the analysis of financial markets that attempts to show both trend direction and overbought/oversold conditions. It was first published William Blau in 1991.
The indicator uses moving averages of the underlying momentum of a financial instrument.
Momentum is considered a leading indicator of price movements, and a moving average characteristically lags behind price.
The TSI combines these characteristics to create an indication of price and direction more in sync with market turns than either momentum or moving average.”
The TSI has a normal range of values between +100 and -100.
Traditionally traders and analysts will consider:
Positives values above 25 to indicate an “overbought” condition
Negative values below -25 to indicate an “oversold” condition
I have reverse engineered the True Strength Index formula to derive 2 new functions.
1) The reverse TSI function is dual purpose which can be used to calculate….
The chart price at which the TSI will reach a particular TSI scale value.
The chart price at which the TSI will equal its previous value.
2) The reverse TSI signal cross function can be used to calculate the chart price at which the TSI will cross its signal line.
I have employed these functions here to return the price levels where the True Strength Index would equal :
Upper alert level ( default 25 )
Zero-Line
Lower alert level ( default -25 )
Previous TSI (eq) value
TSI signal line
In this “On Chart” version of the reverse True Strength Index the crossover levels are displayed both as lines on the chart and via an optional info-box with choice of user selected info.
Chart Line Colors
Upper alert level... ( Fuchsia )
Zero-Line............ ( White )
Lower alert level... ( Aqua )
TSI (eq)...............( TSI (eq) > close..Orange, TSI (eq) < close..Lime )
TSI signal line........( Signal Cross Line > Close..Aqua, Signal Cross Line < Close..Fuchsia )
How to interpret the displayed prices returned from the TSI scale zero line and upper and lower alert levels.
Closing exactly at the given price will cause the True Strength Index value to equal the scale value.
Closing above the given price will cause the True Strength Index to cross above the scale value.
Closing below the given price will cause the True Strength Index to cross below the scale value.
How to interpret the displayed price returned from the TSI (eq)
Closing exactly at the price will cause the True Strength Index value to equal the previous TSI value.
Closing above the price will cause the True Strength Index value to increase.
Closing below the price will cause the True Strength Index value to decrease.
How to interpret the displayed price returned from the TSI signal line crossover.
Closing exactly at the given price will cause the True Strength Index value to equal the signal line.
Closing above the given price will cause the True Strength Index to cross above the signal line.
Closing below the given price will cause the True Strength Index to cross below the signal line.
Common methods to derive signals from the TSI :
Zero-line crossovers
When the CMO crosses above the zero-line, a buy signal is generated.
When the CMO crosses below the zero-line, a sell signal is generated.
“Overbought” and “Oversold” crossovers
When the SMI crosses below -25 and then moves back above it, a buy signal is generated.
When the SMI crosses above +25 and then moves back below it, a sell signal is generated.
What Does the True Strength Index (TSI) Tell You?
The indicator is primarily used to identify overbought and oversold conditions in an asset's price, spot divergence, identify trend direction and changes via the zero-line, and highlight short-term price momentum with signal line crossovers.
Since the TSI is based on price movements, oversold and overbought levels will vary by the asset being traded. Some stocks may reach +30 and -30 before tending to see price reversals, while another stock may reverse near +20 and -20.
Mark extreme TSI levels, on the asset being traded, to see where overbought and oversold is. Being oversold doesn't necessarily mean it is time to buy, and when an asset is overbought it doesn't necessarily mean it is time to sell. Traders will typically watch for other signals to trigger a trade decision. For example, they may wait for the price or TSI to start dropping before selling in overbought territory. Alternatively, they may wait for a signal line crossover.
Signal Line Crossovers
The true strength index has a signal line, which is usually a seven- to 13-period EMA of the TSI line. A signal line crossover occurs when the TSI line crosses the signal line. When the TSI crosses above the signal line from below, that may warrant a long position. When the TSI crosses below the signal line from above, that may warrant selling or short selling.
Signal line crossovers occur frequently, so should be utilized only in conjunction with other signals from the TSI. For example, buy signals may be favoured when the TSI is above the zero-line. Or sell signals may be favoured when the TSI is in overbought territory.
Zero-line Crossovers
The zero-line crossover is another signal the TSI generates. Price momentum is positive when the indicator is above zero and negative when it is below zero. Some traders use the zero-line for a directional bias. For example, a trader may decide only to enter a long position if the indicator is above its zero-line. Conversely, the trader would be bearish and only consider short positions if the indicator's value is below zero.
Breakouts and Divergence
Traders can use support and resistance levels created by the true strength index to identify breakouts and price momentum shifts. For instance, if the indicator breaks below a trendline, the price may see continued selling.
Divergence is another tool the TSI provides. If the price of an asset is moving higher, while the TSI is dropping, that is called bearish divergence and could result in a downside price move. If the TSI is rising while the price is falling, that could signal higher prices to come. This is called bullish divergence.
Divergence is a poor timing signal, so it should only be used in conjunction with other signals generated by the TSI or other technical indicators.
The Difference Between the True Strength Index (TSI) and the Moving Average Convergence Divergence (MACD) Indicator.
The TSI is smoothing price changes to create a technical oscillator. The moving average convergence divergence (MACD) indicator is measuring the separation between two moving averages. Both indicators are used in similar ways for trading purposes, yet they are not calculated the same and will provide different signals at different times.
The Limitations of Using the True Strength Index (TSI)
Many of the signals provided by the TSI will be false signals. That means the price action will be different than expected following a trade signal. For example, during an uptrend, the TSI may cross below the zero-line several times, but then the price proceeds higher even though the TSI indicates momentum has shifted down.
Signal line crossovers also occur so frequently that they may not provide a lot of trading benefit. Such signals need to be heavily filtered based on other elements of the indicator or through other forms of analysis. The TSI will also sometimes change direction without price changing direction, resulting in trade signals that look good on the TSI but continue to lose money based on price.
Divergence also tends to unreliable on the indicator. Divergence can last so long that it provides little insight into when a reversal will actually occur. Also, divergence isn't always present when price reversals actually do occur.
The TSI should only be used in conjunction with other forms of analysis, such as price action analysis and other technical indicators.
This is not financial advice, use at your own risk.
CT Reverse True Strength IndicatorIntroducing the Caretakers Reverse True Strength Index.
According to Wikipedia….
“The True Strength Index (TSI) is a technical indicator used in the analysis of financial markets that attempts to show both trend direction and overbought/oversold conditions. It was first published William Blau in 1991.
The indicator uses moving averages of the underlying momentum of a financial instrument.
Momentum is considered a leading indicator of price movements, and a moving average characteristically lags behind price.
The TSI combines these characteristics to create an indication of price and direction more in sync with market turns than either momentum or moving average.”
The TSI has a normal range of values between +100 and -100.
Traditionally traders and analysts will consider:
Positives values above 25 to indicate an “overbought” condition
Negative values below -25 to indicate an “oversold” condition
I have reverse engineered the True Strength Index formula to derive 2 new functions.
The reverse TSI function is dual purpose which can be used to calculate….
The chart price at which the TSI will reach a particular TSI scale value.
The chart price at which the TSI will equal its previous value.
The reverse TSI signal cross function can be used to calculate the chart price at which the TSI will cross its signal line.
I have employed these functions here to return the price levels where the True Strength Index would equal :
Upper alert level ( default 25 )
Zero-Line
Lower alert level ( default -25 )
Previous TSI (eq) value.
TSI signal line
These crossover levels are displayed via an optional info-box with choice of user selected info.
How to interpret the displayed prices returned from the TSI scale zero line and upper and lower alert levels.
Closing exactly at the given price will cause the True Strength Index value to equal the scale value.
Closing above the given price will cause the True Strength Index to cross above the scale value.
Closing below the given price will cause the True Strength Index to cross below the scale value.
How to interpret the displayed price returned from the TSI (eq)
Closing exactly at the price will cause the True Strength Index value to equal the previous TSI value.
Closing above the price will cause the True Strength Index value to increase.
Closing below the price will cause the True Strength Index value to decrease.
How to interpret the displayed price returned from the TSI signal line crossover.
Closing exactly at the given price will cause the True Strength Index value to equal the signal line.
Closing above the given price will cause the True Strength Index to cross above the signal line.
Closing below the given price will cause the True Strength Index to cross below the signal line.
Common methods to derive signals from the TSI :
Zero-line crossovers
When the CMO crosses above the zero-line, a buy signal is generated.
When the CMO crosses below the zero-line, a sell signal is generated.
“Overbought” and “Oversold” crossover
When the SMI crosses below -25 and then moves back above it, a buy signal is generated.
When the SMI crosses above +25 and then moves back below it, a sell signal is generated.
What Does the True Strength Index (TSI) Tell You?
The indicator is primarily used to identify overbought and oversold conditions in an asset's price, spot divergence, identify trend direction and changes via the zero-line, and highlight short-term price momentum with signal line crossovers.
Since the TSI is based on price movements, oversold and overbought levels will vary by the asset being traded. Some stocks may reach +30 and -30 before tending to see price reversals, while another stock may reverse near +20 and -20.
Mark extreme TSI levels, on the asset being traded, to see where overbought and oversold is. Being oversold doesn't necessarily mean it is time to buy, and when an asset is overbought it doesn't necessarily mean it is time to sell. Traders will typically watch for other signals to trigger a trade decision. For example, they may wait for the price or TSI to start dropping before selling in overbought territory. Alternatively, they may wait for a signal line crossover.
Signal Line Crossovers
The true strength index has a signal line, which is usually a seven- to 13-period EMA of the TSI line. A signal line crossover occurs when the TSI line crosses the signal line. When the TSI crosses above the signal line from below, that may warrant a long position. When the TSI crosses below the signal line from above, that may warrant selling or short selling.
Signal line crossovers occur frequently, so should be utilized only in conjunction with other signals from the TSI. For example, buy signals may be favoured when the TSI is above the zero-line. Or sell signals may be favoured when the TSI is in overbought territory.
Zero-line Crossovers
The zero-line crossover is another signal the TSI generates. Price momentum is positive when the indicator is above zero and negative when it is below zero. Some traders use the zero-line for a directional bias. For example, a trader may decide only to enter a long position if the indicator is above its zero-line. Conversely, the trader would be bearish and only consider short positions if the indicator's value is below zero.
Breakouts and Divergence
Traders can use support and resistance levels created by the true strength index to identify breakouts and price momentum shifts. For instance, if the indicator breaks below a trendline, the price may see continued selling.
Divergence is another tool the TSI provides. If the price of an asset is moving higher, while the TSI is dropping, that is called bearish divergence and could result in a downside price move. If the TSI is rising while the price is falling, that could signal higher prices to come. This is called bullish divergence.
Divergence is a poor timing signal, so it should only be used in conjunction with other signals generated by the TSI or other technical indicators.
The Difference Between the True Strength Index (TSI) and the Moving Average Convergence Divergence (MACD) Indicator.
The TSI is smoothing price changes to create a technical oscillator. The moving average convergence divergence (MACD) indicator is measuring the separation between two moving averages. Both indicators are used in similar ways for trading purposes, yet they are not calculated the same and will provide different signals at different times.
The Limitations of Using the True Strength Index (TSI)
Many of the signals provided by the TSI will be false signals. That means the price action will be different than expected following a trade signal. For example, during an uptrend, the TSI may cross below the zero-line several times, but then the price proceeds higher even though the TSI indicates momentum has shifted down.
Signal line crossovers also occur so frequently that they may not provide a lot of trading benefit. Such signals need to be heavily filtered based on other elements of the indicator or through other forms of analysis. The TSI will also sometimes change direction without price changing direction, resulting in trade signals that look good on the TSI but continue to lose money based on price.
Divergence also tends to unreliable on the indicator. Divergence can last so long that it provides little insight into when a reversal will actually occur. Also, divergence isn't always present when price reversals actually do occur.
The TSI should only be used in conjunction with other forms of analysis, such as price action analysis and other technical indicators.
This is not financial advice, use at your own risk.
Phoenix085-Strategies==>MTF - Average True Range + MovAvgFIRSTLY, Here are a few who have influenced my pinescripting immensely recently:
@JustUncleL
@BigBitsIO
@TheArtofTrading
@QuantNomad
@SquigglesNiggles and many many many more.
Overview:
> This indicator is a simple crossover of Moving Averages.
> In addition I am using ATR rising as an indication for Trending Price.
> The entry is made once the smaller moving average crosses the bigger moving average, and also the Closes above the Smaller moving average.
> but the only twist here is,
- the ATR source is One timeframe Higher(In this case same as the session).whereas the source for the Moving averages is one Timeframe Lower.
>i.e., if the Session is 1D, the Indicator checks if the ATR is rising in the DAILY TIMEFRAME,
*_* the trade entry is made once the MOVING AVERAGE crossover happens on ONE TIME FRAME lower, as per example, ATR --> 1D = MA -->4H.
> Moving Average ->
- Thick -> Bigger MA,
- Thin and Transparent -> Smaller MA,
> Also, the Color of the Thicker MOVING AVERAGE Changes as Below:
- When LongCondition is satisfied --> Color=Lime
- When ShortCondition is satisfied --> Color=Red
- When neither condition is satisfied --> Color=Gray
NOTE:
1) There is a limitation in using the Securities function for FREE USERS --> Only 500 bars are allowed. So to use the indicators with more data, you need an upgraded TV account.
2) Strategy still needs Fine tuning, but for now, use the Thicker moving average color LIME FOR LONG ENTRIES and RED FOR SHORT ENTRIES.
This is Free for Use and share
MAMA by EHLERSMESA Adaptive Moving Average aka: Mother of Adaptive Moving Averages:
The MESA Adaptive Moving Average ( MAMA ) adapts to price movement in an
entirely new and unique way. The adapation is based on the rate change of phase as
measured by the Hilbert Transform Discriminator I have previously described.1
The advantage of this method of adaptation is that it features a fast attack average and a
slow decay average so that composite average rapidly ratchets behind price changes
and holds the average value until the next ratchet occurs. The action of MAMA is
shown in Figure 1. Since the average fallback is slow I can build trading systems that
are virtually free of whipsaw trades.
For detailed information of MAMA: (creators' PDF document)
www.mesasoftware.com
Long condition: when MAMA Crosses over FAMA (Following Adaptive Moving Average )
Short condition: when FAMA Crosses over MAMA
(Personally modified LazyBear's version which was originally calculated in degrees instead of radian by applying explanations in the MESA pdf document.http://www.mesasoftware.com/papers/MAMA.pdf)
Creator: John EHLERS
MR.Z Strategy Reversal Signal Nadaraya SMA)Nadaraya-Watson Envelope (NW Envelope):
A smoothed, non-linear dynamic envelope that adapts to price structure. It visually identifies price extremes using kernel regression. The upper and lower bands move with the chart and provide reliable dynamic support and resistance.
EMA Levels:
Includes three key exponential moving averages:
EMA 50 (short-term trend)
EMA 100 (medium-term)
EMA 200 (long-term, institutional level)
Fully Scrollable and Responsive:
All lines and envelopes are plotted using plot() so they move with the chart and respond to zoom and pan actions naturally.
🧠 Ideal Use:
Identify reversal zones, dynamic support/resistance, and trend momentum exhaustion.
Combine WTB and NW Envelope for confluence-based entries.
Use EMA structure for trend confirmation or breakout anticipation.
Let me know if you'd like to add:
Divergence detection
Buy/Sell signals
Alerts or signal filtering options
I’ll be happy to extend the description or the script accordingly!
Moving Average Candles**Moving Average Candles — MA-Based Smoothed Candlestick Overlay**
This script replaces traditional price candles with smoothed versions calculated using various types of moving averages. Instead of plotting raw price data, each OHLC component (Open, High, Low, Close) is independently smoothed using your selected moving average method.
---
### 📌 Features:
- Choose from 13 MA types: `SMA`, `EMA`, `RMA`, `WMA`, `VWMA`, `HMA`, `T3`, `DEMA`, `TEMA`, `KAMA`, `ZLEMA`, `McGinley`, `EPMA`
- Fully configurable moving average length (1–1000)
- Color-coded candles based on smoothed Open vs Close
- Works directly on price charts as an overlay
---
### 🎯 Use Cases:
- Visualize smoothed market structure more clearly
- Reduce noise in price action for better trend analysis
- Combine with other indicators or strategies for confluence
---
> ⚠️ **Note:** Since all OHLC values are based on moving averages, these candles do **not** represent actual market trades. Use them for trend and structure analysis, not trade entries based on precise levels.
---
*Created to support traders seeking a cleaner visual representation of price dynamics.*
[blackcat] L2 FiboKAMA Adaptive TrendOVERVIEW
The L2 FiboKAMA Adaptive Trend indicator leverages advanced technical analysis techniques by integrating Fibonacci principles with the Kaufman Adaptive Moving Average (KAMA). This combination creates a dynamic and responsive tool designed to adapt seamlessly to changing market conditions. By providing clear buy and sell signals based on adaptive momentum, this indicator helps traders identify potential entry and exit points effectively. Its intuitive design and robust features make it a valuable addition to any trader’s arsenal 📊💹.
According to the principle of Kaufman's Adaptive Moving Average (KAMA), it is a type of moving average line specifically designed for markets with high volatility. Unlike traditional moving averages, KAMA can automatically adjust its period based on market conditions to improve accuracy and responsiveness. This makes it particularly useful for capturing market trends and reducing false signals in varying market environments.
The use of Fibonacci magic numbers (3, 8, 13) enhances the performance and accuracy of KAMA. These numbers have special mathematical properties that align well with the changing trends of KAMA moving averages. Combining them with KAMA can significantly boost its effectiveness, making it a popular choice among traders seeking reliable signals.
This fusion not only smoothens price fluctuations but also ensures quick responses to market changes, offering dependable entry and exit points. Thanks to the flexibility and precision of KAMA combined with Fibonacci magic numbers, traders can better manage risks and aim for higher returns.
FEATURES
Enhanced Kaufman Adaptive Moving Average (KAMA): Incorporates Fibonacci principles for improved adaptability:
Source Price: Allows customization of the price series used for calculation (default: HLCC4).
Fast Length: Determines the period for quicker adjustments to recent price changes.
Slow Length: Sets the period for smoother transitions over longer-term trends.
Dynamic Lines:
KAMA Line: A yellow line representing the primary adaptive moving average, which adapts quickly to new trends.
Trigger Line: A fuchsia line serving as a reference point for detecting crossovers and generating signals.
Visual Cues:
Buy Signals: Green 'B' labels indicating potential buying opportunities.
Sell Signals: Red 'S' labels signaling possible selling points.
Fill Areas: Colored regions between the KAMA and Trigger lines to visually represent trend directions and strength.
Alert Functionality: Generates real-time alerts for both buy and sell signals, ensuring timely notifications for actionable insights 🔔.
Customizable Parameters: Offers flexibility through adjustable inputs, allowing users to tailor the indicator to their specific trading strategies and preferences.
HOW TO USE
Adding the Indicator:
Open your TradingView chart and navigate to the indicators list.
Select L2 FiboKAMA Adaptive Trend and add it to your chart.
Configuring Parameters:
Adjust the Source Price to choose the desired price series (e.g., close, open, high, low).
Set the Fast Length to define how quickly the indicator responds to recent price movements.
Configure the Slow Length to determine the smoothness of long-term trend adaptations.
Interpreting Signals:
Monitor the chart for green 'B' labels indicating buy signals and red 'S' labels for sell signals.
Observe the colored fill areas between the KAMA and Trigger lines to gauge trend strength and direction.
Setting Up Alerts:
Enable alerts within the indicator settings to receive notifications whenever buy or sell signals are triggered.
Customize alert messages and frequencies according to your trading plan.
Combining with Other Tools:
Integrate this indicator with additional technical analysis tools and fundamental research for comprehensive decision-making.
Confirm signals using other indicators like RSI, MACD, or Bollinger Bands for increased reliability.
Optimizing Performance:
Backtest the indicator across various assets and timeframes to understand its behavior under different market conditions.
Fine-tune parameters based on historical performance and current market dynamics.
Integrating Magic Numbers:
Understand the basic principles of KAMA to find suitable entry points for Fibonacci magic numbers.
Utilize the efficiency ratio to measure market volatility and adjust moving average parameters accordingly.
Apply Fibonacci magic numbers (3, 8, 13) to enhance the responsiveness and accuracy of KAMA.
LIMITATIONS
Market Volatility: May produce false signals during periods of extreme volatility or sideways movement.
Parameter Sensitivity: Requires careful tuning of fast and slow lengths to balance responsiveness and stability.
Asset-Specific Behavior: Effectiveness can vary significantly across different financial instruments and time horizons.
Complementary Analysis: Should be used alongside other analytical methods to enhance accuracy and reduce risk.
NOTES
Historical Data: Ensure adequate historical data availability for precise calculations and backtesting.
Demo Testing: Thoroughly test the indicator on demo accounts before deploying it in live trading environments.
Continuous Learning: Stay updated with market trends and continuously refine your strategy incorporating feedback from the indicator's performance.
Risk Management: Always implement proper risk management practices regardless of the signals provided by the indicator.
ADVANCED USAGE TIPS
Multi-Timeframe Analysis: Apply the indicator across multiple timeframes to gain deeper insights into underlying trends.
Divergence Strategy: Look for divergences between price action and the KAMA line to spot potential reversals early.
Volume Integration: Combine volume analysis with the indicator to confirm the strength of identified trends.
Custom Scripting: Modify the script to include additional filters or conditions tailored to your unique trading approach.
IMPROVING KAMA PERFORMANCE
Increase Length: Extend the KAMA length to consider more historical data, reducing the impact of short-term price fluctuations.
Adjust Fast and Slow Lengths: Make KAMA smoother by increasing the fast length and decreasing the slow length.
Use Smoothing Factor: Apply a smoothing factor to control the level of smoothness; typical values range from 0 to 1.
Combine with Other Indicators: Pair KAMA with other smoothing indicators like EMA or SMA for more reliable signals.
Filter Noise: Use filters or other technical analysis tools to eliminate price noise, enhancing KAMA's effectiveness.
IWMA - DolphinTradeBot1️⃣ WHAT IS IT ?
▪️ The Inverted Weighted Moving Average (IWMA) is the reversed version of WMA, where older prices receive higher weights, while recent prices receive lower weights. As a result, IWMA focuses more on past price movements while reducing sensitivity to new prices.
2️⃣ HOW IS IT WORK ?
🔍 To understand the IWMA(Inverted Weighted Moving Average) indicator, let's first look at how WMA (Weighted Moving Average) is calculated.
LET’S SAY WE SELECTED A LENGTH OF 5, AND OUR CURRENT CLOSING VALUES ARE .
▪️ WMA Calculation Method
When calculating WMA, the most recent price gets the highest weight, while the oldest price gets the lowest weight.
The Calculation is ;
( 10 ×1)+( 12 ×2)+( 21 ×3)+( 24 ×4)+( 38 ×5) = 10+24+63+96+190 = 383
1+2+3+4+5 = 15
WMA = 383/15 ≈ 25.53
WMA = ta.wma(close,5) = 25.53
▪️ IWMA Calculation Method
The Inverted Weighted Moving Average (IWMA) is the reversed version of WMA, where older prices receive higher weights, while recent prices receive lower weights. As a result, IWMA focuses more on past price movements while reducing sensitivity to new prices.
The Calculation is ;
( 10 ×5)+( 12 ×4)+( 21 ×3)+( 24 ×2)+( 38 ×1) = 50+48+63+48+38 = 247
1+2+3+4+5 = 15
IWMA = 247/15 ≈ 16.46
IWMA = iwma(close,5) = 16.46
3️⃣ SETTINGS
in the indicator's settings, you can change the length and source used for calculation.
With the default settings, when you first add the indicator, only the iwma will be visible. However, to observe how much it differs from the normal wma calculation, you can enable the "show wma" option to see both indicators with the same settings or you can enable the Show Signals to see IWMA and WMA crossover signals .
4️⃣ 💡 SOME IDEAS
You can use the indicator for support and resistance level analysis or trend analysis and reversal detection with short and long moving averages like regular moving averages.
Another option is to consider whether the iwma is above or below the normal wma or to evaluate the crossovers between wma and iwma.
Algorithmic Signal AnalyzerMeet Algorithmic Signal Analyzer (ASA) v1: A revolutionary tool that ushers in a new era of clarity and precision for both short-term and long-term market analysis, elevating your strategies to the next level.
ASA is an advanced TradingView indicator designed to filter out noise and enhance signal detection using mathematical models. By processing price movements within defined standard deviation ranges, ASA produces a smoothed analysis based on a Weighted Moving Average (WMA). The Volatility Filter ensures that only relevant price data is retained, removing outliers and improving analytical accuracy.
While ASA provides significant analytical advantages, it’s essential to understand its capabilities in both short-term and long-term use cases. For short-term trading, ASA excels at capturing swift opportunities by highlighting immediate trend changes. Conversely, in long-term trading, it reveals the overall direction of market trends, enabling traders to align their strategies with prevailing conditions.
Despite these benefits, traders must remember that ASA is not designed for precise trade execution systems where accuracy in timing and price levels is critical. Its focus is on analysis rather than order management. The distinction is crucial: ASA helps interpret price action effectively but may not account for real-time market factors such as slippage or execution delays.
Features and Functionality
ASA integrates multiple tools to enhance its analytical capabilities:
Customizable Moving Averages: SMA, EMA, and WMA options allow users to tailor the indicator to their trading style.
Signal Detection: Identifies bullish and bearish trends using the Relative Exponential Moving Average (REMA) and marks potential buy/sell opportunities.
Visual Aids: Color-coded trend lines (green for upward, red for downward) simplify interpretation.
Alert System: Notifications for trend swings and reversals enable timely decision-making.
Notes on Usage
ASA’s effectiveness depends on the context in which it is applied. Traders should carefully consider the trade-offs between analysis and execution.
Results may vary depending on market conditions and chart types. Backtesting with ASA on standard charts provides more reliable insights compared to non-standard chart types.
Short-term use focuses on rapid trend recognition, while long-term application emphasizes understanding broader market movements.
Takeaways
ASA is not a tool for precise trade execution but a powerful aid for interpreting price trends.
For short-term trading, ASA identifies quick opportunities, while for long-term strategies, it highlights trend directions.
Understanding ASA’s limitations and strengths is key to maximizing its utility.
ASA is a robust solution for traders seeking to filter noise, enhance analytical clarity, and align their strategies with market movements, whether for short bursts of activity or sustained trading goals.
Trend Condition [TradersPro]
OVERVIEW
The Trend Condition Indicator measures the strength of the bullish or bearish trend by using a ribbon pattern of exponential moving averages and scoring system. Trend cycles naturally expand and contract as a normal part of the cycle. It is the rhythm of the market. Perpetual expansion and contraction of trend.
As trend cycles develop the indicator shows a compression of the averages. These compression zones are key locations as trends typically expand from there. The expansion of trend can be up or down.
As the trend advances the ribbon effect of the indicator can be seen as each average expands with the price action. Once they have “fanned” the probability of the current trend slowing is high.
This can be used to recognize a powerful trend may be concluding. Traders can tighten stops, exit positions or utilize other prudent strategies.
CONCEPTS
Each line will display green if it is higher than the prior period and red if it is lower than the prior period. If the average is green it is considered bullish and will score one point in the bullish display. Red lines are considered bearish and will score one point in the bearish display.
The indicator can then be used at a quick glance to see the number of averages that are bullish and the number that are bearish.
A trader may use these on any tradable instrument. They can be helpful in stock portfolio management when used with an index like the S&P 500 to determine the strength of the current market trend. This may affect trade decisions like possession size, stop location and other risk factors.
Adaptive DEMA Momentum Oscillator (ADMO)Overview:
The Adaptive DEMA Momentum Oscillator (ADMO) is an open-source technical analysis tool developed to measure market momentum using a Double Exponential Moving Average (DEMA) and adaptive standard deviation. By dynamically combining price deviation from the moving average with normalized standard deviation, ADMO provides traders with a powerful way to interpret market conditions.
Key Features:
Double Exponential Moving Average (DEMA):
The core calculation of the indicator is based on DEMA, which is known for being more responsive to price changes compared to traditional moving averages. This makes the ADMO capable of capturing trend momentum effectively.
Standard Deviation Integration:
A normalized standard deviation is used to adaptively weight the oscillator. This makes the indicator more sensitive to market volatility, enhancing responsiveness during high volatility and reducing sensitivity during calmer periods.
Oscillator Representation:
The final oscillator value is derived from the combination of the DEMA-based Z-score and the normalized standard deviation. This final value is visualized as a color-coded histogram, reflecting bullish or bearish momentum.
Color-Coded Histogram:
Bullish Momentum: Values above zero are colored using a customizable bullish color (default: light green).
Bearish Momentum: Values below zero are colored using a customizable bearish color (default: red).
How It Works:
Inputs:
DEMA Length: Defines the period used for calculating the Double Exponential Moving Average. It can be adjusted from 1 to 200 to suit different trading styles.
Standard Deviation Length: Sets the lookback period for standard deviation calculations, which influences the responsiveness of the oscillator.
Standard Deviation Weight (StdDev Weight): Controls the weight given to the normalized standard deviation, allowing customization of the oscillator's sensitivity to volatility.
Calculation Steps:
Double Exponential Moving Average Calculation:
The DEMA is calculated using two exponential moving averages, which helps in reducing lag compared to a simple moving average.
Z-score Calculation:
The Z-score is derived by comparing the difference between the DEMA and its smoothed average (LSMA) to the standard deviation. This indicates how far the current value is from the mean in units of standard deviation.
Normalized Standard Deviation:
The standard deviation is normalized by subtracting the mean standard deviation and dividing by the standard deviation of the values. This helps to make the oscillator adaptive to recent changes in volatility.
Final Oscillator Value:
The final value is calculated by multiplying the Z-score with a factor based on the normalized standard deviation, resulting in a momentum indicator that adapts to different market conditions.
Visualization:
Histogram: The oscillator is plotted as a histogram, with color-coded bars showing the strength and direction of market momentum.
Positive (bullish) values are shown in green, indicating upward momentum.
Negative (bearish) values are shown in red, indicating downward momentum.
Zero Line: A zero line is plotted to provide a reference point, helping users quickly determine whether the current momentum is bullish or bearish.
Example Use Cases:
Momentum Identification:
ADMO helps identify the current market momentum by dynamically adapting to changes in market volatility. When the histogram is above zero and green, it indicates bullish conditions, whereas values below zero and red suggest bearish momentum.
Volatility-Adjusted Signals:
The normalized standard deviation weighting allows the ADMO to provide more reliable signals during different market conditions. This makes it particularly useful for traders who want to be responsive to market volatility while avoiding false signals.
Trend Confirmation and Divergence:
ADMO can be used to confirm the strength of a trend or identify potential divergences between price and momentum. This helps traders spot potential reversal points or continuation signals.
Summary:
The Adaptive DEMA Momentum Oscillator (ADMO) offers a unique approach by combining momentum analysis with adaptive standard deviation. The integration of DEMA makes it responsive to price changes, while the standard deviation adjustment helps it stay relevant in both high and low volatility environments. It's a versatile tool for traders who need an adaptive, momentum-based approach to technical analysis.
Feel free to explore the code and adapt it to your trading strategy. The open-source nature of this tool allows you to adjust the settings and visualize the output to fit your personal trading preferences.
Normalised T3 Oscillator [BackQuant]Normalised T3 Oscillator
The Normalised T3 Oscillator is an technical indicator designed to provide traders with a refined measure of market momentum by normalizing the T3 Moving Average. This tool was developed to enhance trading decisions by smoothing price data and reducing market noise, allowing for clearer trend recognition and potential signal generation. Below is a detailed breakdown of the Normalised T3 Oscillator, its methodology, and its application in trading scenarios.
1. Conceptual Foundation and Definition of T3
The T3 Moving Average, originally proposed by Tim Tillson, is renowned for its smoothness and responsiveness, achieved through a combination of multiple Exponential Moving Averages and a volume factor. The Normalised T3 Oscillator extends this concept by normalizing these values to oscillate around a central zero line, which aids in highlighting overbought and oversold conditions.
2. Normalization Process
Normalization in this context refers to the adjustment of the T3 values to ensure that the oscillator provides a standard range of output. This is accomplished by calculating the lowest and highest values of the T3 over a user-defined period and scaling the output between -0.5 to +0.5. This process not only aids in standardizing the indicator across different securities and time frames but also enhances comparative analysis.
3. Integration of the Oscillator and Moving Average
A unique feature of the Normalised T3 Oscillator is the inclusion of a secondary smoothing mechanism via a moving average of the oscillator itself, selectable from various types such as SMA, EMA, and more. This moving average acts as a signal line, providing potential buy or sell triggers when the oscillator crosses this line, thus offering dual layers of analysis—momentum and trend confirmation.
4. Visualization and User Interaction
The indicator is designed with user interaction in mind, featuring customizable parameters such as the length of the T3, normalization period, and type of moving average used for signals. Additionally, the oscillator is plotted with a color-coded scheme that visually represents different strength levels of the market conditions, enhancing readability and quick decision-making.
5. Practical Applications and Strategy Integration
Traders can leverage the Normalised T3 Oscillator in various trading strategies, including trend following, counter-trend plays, and as a component of a broader trading system. It is particularly useful in identifying turning points in the market or confirming ongoing trends. The clear visualization and customizable nature of the oscillator facilitate its adaptation to different trading styles and market environments.
6. Advanced Features and Customization
Further enhancing its utility, the indicator includes options such as painting candles according to the trend, showing static levels for quick reference, and alerts for crossover and crossunder events, which can be integrated into automated trading systems. These features allow for a high degree of personalization, enabling traders to mold the tool according to their specific trading preferences and risk management requirements.
7. Theoretical Justification and Empirical Usage
The use of the T3 smoothing mechanism combined with normalization is theoretically sound, aiming to reduce lag and false signals often associated with traditional moving averages. The practical effectiveness of the Normalised T3 Oscillator should be validated through rigorous backtesting and adjustment of parameters to match historical market conditions and volatility.
8. Conclusion and Utility in Market Analysis
Overall, the Normalised T3 Oscillator by BackQuant stands as a sophisticated tool for market analysis, providing traders with a dynamic and adaptable approach to gauging market momentum. Its development is rooted in the understanding of technical nuances and the demand for a more stable, responsive, and customizable trading indicator.
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
Uptrick: Bullish/Bearish Highlight -DEMO 1 Indicator Purpose:
• The indicator serves as a technical analysis tool for traders to identify potential bullish
and bearish trends in the market.
• It highlights periods where the closing price is above or below a 50-period simple
moving average (SMA), indicating potential bullish or bearish sentiment, respectively.
2 Moving Averages:
• The indicator calculates a 50-period SMA (sma50) to smooth out price fluctuations
and identify the overall trend direction.
• It also computes an 8-period exponential moving average (EMA), which responds
more quickly to recent price changes compared to the SMA.
3 Bollinger Bands:
• Bollinger Bands are plotted around the SMA, indicating volatility in the price
movement.
• The bands are typically set at two standard deviations above and below the SMA,
representing approximately 95% of the price data within that range.
4 Bullish and Bearish Conditions:
• The indicator defines conditions for identifying bullish and bearish market sentiments.
• When the closing price is above the SMA50, it indicates a bullish condition, and when
it's below, it suggests a bearish condition.
5 Plotting:
• The indicator visualizes the bullish and bearish conditions by changing the
background color accordingly.
• It also plots the SMA50, EMA, and Bollinger Bands to provide a graphical
representation of the market dynamics.
6 User Interface:
• The indicator is designed to be used as an overlay on price charts, allowing traders to
easily incorporate it into their analysis.
Overall, the "Uptrick: Bullish/Bearish Highlight" indicator offers traders a comprehensive view of market trends and potential reversal points, helping them make informed trading decisions.
TIP: When the white line, which is the EMA , crosses above the SMA (the orange line), it is usually a good idea to buy, but when the EMA crosses below the SMA it is a good idea to sell.
Volatility Exponential Moving AverageVEMA is a custom indicator that enhances the traditional moving average by incorporating market volatility. Unlike standard moving averages that rely solely on price, VEMA integrates both the Simple Moving Average (SMA) and the Exponential Moving Average (EMA) of the closing price, alongside a measure of market volatility.
The unique aspect of VEMA is its approach. It calculates the standard deviation of the closing price and also computes the simple moving average of this volatility. This dual approach to understanding market fluctuations allows for a more nuanced understanding of market dynamics.
Key to VEMA's functionality is the dynamic weighting factor, which adjusts the influence of SMA and EMA based on current market volatility. This factor increases the weight of the EMA, which is more responsive to recent price changes, during periods of high volatility. Conversely, during periods of lower volatility, the SMA, which offers a smoother view of price trends, becomes more prominent.
The resultant is a hybrid moving average that responds adaptively to changes in market volatility. This adaptability makes VEMA particularly useful in dynamic markets, potentially offering more insightful trend analysis and reversal signals compared to traditional moving averages.
Bank Nifty ScalpingThis indicator is designed for scalping purposes.
Users have the option to input the desired source and enable or disable the following indicators:
Multiple EMA (Exponential moving average)
Simultaneously displays multiple moving averages to quickly identify shifts in momentum and obtain confirmation from slower-moving averages.
By default, the EMA display settings are configured to show the 20-day EMA and the 200-day EMA. However, users have the flexibility to modify the display settings according to their preferences. This means that users can customize the indicator to show the EMA values of their choice, such as EMA 50 and EMA 100.
VWAP ( Volume weighted average price )
Default value is set to ‘hl2’
A bullish trend is indicated when the price is above the Volume Weighted Average Price (VWAP), while a bearish trend is indicated when the price is below the VWAP.
VWMA ( Volume weighted moving average )
In the VWMA (Volume Weighted Moving Average) indicator, a default value of 20 is used. If the price is higher than the VWMA, it typically indicates a bullish trend. Conversely, if the price is lower than the VWMA, it suggests a bearish trend. The VWMA takes into account both price and volume, providing a weighted average that can help identify shifts in market sentiment.
Multiple SuperTrends
Default value is 10 and 2 / 10 and 3
A bullish trend is identified when the price is above the SuperTrend indicator, whereas a bearish trend is observed when the price is below the SuperTrend indicator.
Camarilla Pivot Points (Level 3 and 4 only)
Levels 3 and 4 serve as crucial support and resistance levels, acting as the final line of defense against strong trends. These levels are expected to generate reversals, where price often changes direction.
CPR ( Central Pivot Points)
The Daily Central Pivot Point Indicator is a popular tool used in technical analysis. It calculates several levels based on the previous day's high, low, and closing prices.
Strong Volume
The user has the ability to set the average volume for Nifty and BankNifty indices to calculate strong volume.
Elder Impulse System
The Impulse System, developed by Alexander Elder and discussed in his book "New Trading for a Living," is a censorship trading system designed to determine whether a trade should be allowed or prohibited. Additionally, it can be used to identify when a trend is starting to weaken. The Impulse System relies on the following factors:
1. Slope of a Fast Exponential Moving Average (EMA): The fast EMA's slope reflects the price's inertia or momentum.
2. Slope of the Moving Average Convergence Divergence (MACD): The MACD's slope indicates the strength or power of the price movement.
Based on these factors, the Impulse System categorizes candles or price bars into three colors:
* Green Candle: When both the fast EMA and MACD are rising, indicating upward momentum.
* Red Candle: When both the fast EMA and MACD are declining, suggesting downward momentum.
* Blue Candle: In all other cases where the conditions for green or red candles are not met, representing a neutral or uncertain market condition.
By applying the Impulse System, traders can gain insights into the market trend, its strength, and potential shifts in momentum, helping them make informed trading decisions.
Happy Trading
