Lsma | viResearchLsma | viResearch
Certainly! Here's the revised text:
Conceptual Foundation and Innovation
The "Lsma" (Least Squares Moving Average) indicator, developed by viResearch, offers a refined approach to trend detection by using linear regression to smooth price data. Unlike traditional moving averages, the Lsma reduces lag by fitting a linear regression line through the data points, providing a more responsive and accurate representation of price trends. This dynamic approach enables traders to capture market movements with greater precision, especially in fast-moving markets.
Technical Composition and Calculation
The "Lsma" indicator is based on the least squares method, a statistical analysis technique that minimizes the difference between observed and predicted values. By applying this method to price data, the Lsma indicator calculates a trend line that reduces the impact of random fluctuations.
Linear Regression Calculation:
Length (len_lsma): The Lsma is computed over a user-defined period, allowing traders to adjust the sensitivity of the indicator to market conditions. A longer period provides a smoother trend, while a shorter period makes the indicator more responsive to recent price changes.
Offset (off): The script includes an optional offset parameter, which shifts the trend line forward or backward, providing additional flexibility in visualizing market trends.
Source (src): The input source (default: close price) determines which price data the Lsma is applied to. This can be customized to suit various trading strategies.
Trend Identification:
Lsma Direction: The script compares the current Lsma value to its previous value to detect trend direction. If the Lsma is increasing and the price is above it, this signals an uptrend (L). Conversely, if the Lsma is decreasing and the price is below it, this signals a downtrend (S).
Entry Confirmation (en): The user can select an entry confirmation source to further validate potential trade signals. This ensures that traders are not solely reliant on the Lsma's trend direction but can also confirm signals with additional data points.
Features and User Inputs
The "Lsma" script offers several customizable options, making it adaptable to various trading styles and market conditions:
Lsma Length: Controls the period over which the Lsma is calculated. Traders can increase this value to smooth out short-term fluctuations or reduce it for faster trend detection.
Offset: Allows users to shift the Lsma plot, which can help in analyzing trends or refining entry and exit points.
Source and Entry Confirmation: The indicator can be applied to different data sources, and users can select a secondary confirmation source for more accurate signal generation.
Practical Applications
The "Lsma" indicator is a versatile tool, especially well-suited for traders seeking to capture trends with minimal lag. It is particularly effective in volatile markets where traditional moving averages may lag behind price action, leading to delayed signals.
Key Uses:
Trend Following: The Lsma provides a clear view of the market's direction, allowing traders to align their positions with the prevailing trend.
Signal Confirmation: The entry confirmation feature enhances the reliability of trend signals, reducing the likelihood of false entries in choppy markets.
Trade Timing: The customizable length and offset settings give traders flexibility in determining the optimal timing for entering and exiting trades.
Advantages and Strategic Value
The "Lsma" indicator offers several advantages over traditional moving averages:
Reduced Lag: By applying linear regression, the Lsma minimizes lag, providing more timely trend signals.
Customizability: The adjustable length, offset, and source inputs give traders the ability to fine-tune the indicator to their specific needs.
Trend Clarity: The indicator's design ensures that only significant trends are captured, filtering out short-term noise that can obscure the bigger picture.
Summary and Usage Tips
The "Lsma" indicator is an excellent tool for trend-following traders, offering a powerful blend of precision and adaptability. By using linear regression, it provides a more accurate and responsive measure of price trends, helping traders stay aligned with market direction. For best results, traders should experiment with different Lsma lengths and entry confirmation sources to tailor the indicator to their strategy. Whether used for identifying trend reversals or confirming trend strength, the "Lsma" indicator is a reliable and versatile solution for modern trading.
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Tomorrow Floor Pivots with CPR By Nifty ZThe colors for resistance and support levels have been updated to gradient reds and greens for clearer distinction.
The CPR band uses light blue and purple to stand out more effectively.
Here's a detailed explanation of the user inputs and the typical use of **Floor Pivots for Tomorrow’s Market Range** in a trading context, focusing on support, resistance, and breakout scenarios:
The script allows traders to customize key parameters for their analysis:
1. Pivot Timeframe:
- Users can select different timeframes for calculating floor pivots, such as 1 hour, 4 hours, daily, weekly, monthly, etc.
- This is crucial because the timeframe selection influences the granularity of the support and resistance levels for the next trading day.
- For instance, selecting a **Daily** timeframe will calculate floor pivots for the next trading day, while selecting **Weekly** will give levels for the upcoming week.
2. Show Floor Pivots:
- Users can toggle the visibility of the calculated **Floor Pivots**, which include resistance levels (R1, R2, R3, R4) and support levels (S1, S2, S3, S4).
3. Show CPR (Central Pivot Range):
- CPR (Central Pivot Range) is a key area where the price tends to consolidate.
- The script allows users to enable or disable the visibility of CPR, which consists of the BC (Bottom Central Pivot) and TC (Top Central Pivot).
4. Show Labels:
- Users can choose whether or not to display labels indicating the **Pivot**, **Support**, and Resistance levels on the chart. This can be helpful for visual analysis when day trading.
Understanding Floor Pivots
The Floor Pivots (Pivot, Resistance, and Support levels) for tomorrow's market range are calculated based on today’s high, low, and close. These levels help traders anticipate how the market may behave in the upcoming session.
1. Pivot:
- The Pivot Point is a central level, calculated as the average of the high, low, and close. It’s considered a reference point that determines the market’s overall bias.
- If the price is trading **above the pivot**, it generally suggests a **bullish** sentiment for the day.
- If the price is trading **below the pivot**, it suggests a **bearish** sentiment.
2. Resistance Levels (R1, R2, R3, R4):
- R1 is often the first area where price may stall in an uptrend. It represents the first major resistance level.
- **R2**, **R3**, and **R4** mark additional levels of resistance, progressively further away from the current price. These are used to project potential upward targets.
- These resistance levels are areas where the price might encounter selling pressure, especially during day trading.
3. **Support Levels (S1, S2, S3, S4):**
- Similarly, **S1** is the first area where the price might find support in a downtrend.
- **S2**, **S3**, and **S4** provide deeper support levels where the price may bounce from.
- These support zones are used by day traders to anticipate where the price might reverse upward.
### **Role of Resistance and Support in Day Trading**
- **Resistance Levels (R1, R2, R3, R4)** indicate potential areas where price could **stall** during an uptrend. These levels are useful for **short-term traders** looking to set exit points or identify reversal zones.
- **Support Levels (S1, S2, S3, S4)** highlight areas where the price could **find support** and potentially **bounce** higher. These levels are particularly helpful for identifying buy zones in a downtrend.
- If a price **breaks out** above the resistance levels or **breaks down** below the support levels, it often signals a strong trend continuation.
### **Understanding the Central Pivot Range (CPR)**
The **CPR** is formed by two key levels:
- **BC (Bottom Central Pivot):** The midpoint of the day’s high and low.
- **TC (Top Central Pivot):** The difference between the pivot and BC.
The CPR acts as a region of **consolidation** or **indecision** where the market is likely to stay within a narrow range. The width of the CPR gives traders a sense of volatility:
- A **narrow CPR** often signals that a **breakout** is imminent.
- A **wider CPR** suggests that the market could remain range-bound.
### **Market Sentiment Based on Floor Pivots**
The relationship between **today’s** and **tomorrow’s pivots** is crucial in determining the market sentiment for the next day.
1. **Bullish Case (Higher Highs):**
- If **tomorrow's pivot** is higher than **today's pivot**, it indicates a **bullish sentiment**. This suggests that the market is likely to trend upward in the next session.
- In a **bullish overlapping pivot range**, if **Day 1 (today)** is higher than **Day 2 (tomorrow)**, traders expect continued upward momentum.
2. **Bearish Case (Lower Lows):**
- Conversely, if **tomorrow's pivot** is lower than **today's pivot**, it suggests a **bearish sentiment** and that the market could trend downward in the next session.
- In a **bearish overlapping pivot range**, if **Day 1 (today)** is lower than **Day 2 (tomorrow)**, traders expect continued downward pressure.
### **Breakout Scenarios**
A breakout occurs when the price **violates either the support or resistance levels** significantly, indicating that the price is moving in the direction of the breakout.
1. **Bullish Breakout:**
- If the price consistently stays **above the CPR** and **resistance levels (R1, R2)**, it indicates a strong **bullish breakout**.
- This is especially true when the **CPR is narrow** for both days, signaling a buildup in price action and a potential breakout to the upside.
2. **Bearish Breakout:**
- If the price breaks **below the CPR** and **support levels (S1, S2)**, it indicates a **bearish breakout**.
- A narrow CPR on **both days** suggests that a breakout to the downside could be imminent.
3. **Neutral or Ranging Days:**
- Sometimes, the CPR stays **unchanged** for 4-5 days, indicating a period of **consolidation** where the price is moving within a tight range. This often leads to a significant breakout once the consolidation ends.
Strategic Application of Floor Pivots for Tomorrow
Traders use floor pivots to plan their next-day trades by:
- **Aligning with Market Sentiment:** Based on whether tomorrow’s pivot is higher or lower than today’s, traders can align their trades in the direction of the market’s overall bias.
- **Identifying Entry and Exit Points:** Resistance and support levels provide well-defined areas to enter or exit trades, making pivots essential for day trading strategies.
- **Anticipating Breakouts:** Monitoring the width of the CPR and the relation between pivots helps traders anticipate potential breakouts, allowing them to react quickly to sudden price movements.
By effectively using these pivots and understanding their significance, traders can improve their decision-making for short-term trades in the stock or futures markets.
HMA Smoothed RSI [Pinescriptlabs]This indicator uses a modified version of the RSI (Relative Strength Index) weighted by volume. This means it not only takes into account the price but also the amount of volume supporting those price movements, making the indicator more sensitive to real market fluctuations.
Hull Moving Average (HMA) Applied to RSI: To smooth the volume-weighted RSI, a Hull Moving Average (HMA) is applied. The HMA is known for its ability to reduce market "noise" and quickly react to trend changes. This process helps better identify when an asset is overbought or oversold.
Overbought and Oversold Regions: The indicator sets clear overbought and oversold levels, which are adjustable. By default, the overbought level is set at 20 and the oversold level at -20, but you can customize these values. Additionally, there are extreme overbought and oversold levels to help identify more extreme market conditions where a price reversal is more likely.
Buy and Sell Signals:
Buy Signal: This is generated when the modified RSI crosses above the oversold level. This indicates that the price has dropped enough and may be about to rise.
Sell Signal: This occurs when the RSI crosses below the overbought level. This suggests that the price has risen too much and could be about to fall.
Dynamic Visualization and Colors: The indicator is displayed with different colors based on its behavior:
When the RSI is within normal levels, the color is neutral.
If it is above the overbought level, the color turns red (sell alert).
If it is below the oversold level, the color turns green (buy alert).
Alerts: This indicator also allows you to set up alerts. You will receive automatic notifications when buy or sell signals are generated, helping you make decisions without constantly monitoring the chart.
Español:
Este indicador utiliza una versión modificada del RSI (Índice de Fuerza Relativa), ponderado por volumen. Esto significa que no solo tiene en cuenta el precio, sino también la cantidad de volumen que respalda esos movimientos de precios, haciendo que el indicador sea más sensible a las fluctuaciones reales del mercado.
Media Móvil Hull (HMA) aplicada al RSI: Para suavizar el RSI ponderado por volumen, se le aplica una Media Móvil Hull (HMA). La HMA es conocida por su capacidad para reducir el "ruido" del mercado y reaccionar rápidamente a los cambios de tendencia. Este proceso ayuda a identificar mejor cuándo un activo está sobrecomprado o sobrevendido.
Regiones de sobrecompra y sobreventa: El indicador establece niveles claros de sobrecompra y sobreventa que son ajustables. Por defecto, el nivel de sobrecompra está en 20 y el de sobreventa en -20, pero puedes personalizar estos valores. Además, hay niveles extremos de sobrecompra y sobreventa que te ayudan a identificar condiciones más extremas del mercado, donde una reversión de precio es más probable.
Señales de compra y venta:
Señal de compra: Se genera cuando el RSI modificado cruza hacia arriba el nivel de sobreventa. Esto indica que el precio ha bajado lo suficiente y puede estar a punto de subir.
Señal de venta: Se produce cuando el RSI cruza hacia abajo el nivel de sobrecompra. Esto indica que el precio ha subido demasiado y podría estar a punto de bajar.
Visualización y colores dinámicos: El indicador se muestra con diferentes colores según su comportamiento:
Cuando el RSI está dentro de los niveles normales, el color es neutro.
Si está por encima del nivel de sobrecompra, el color se vuelve rojo (señal de alerta de venta).
Si está por debajo del nivel de sobreventa, el color se vuelve verde (señal de alerta de compra).
Alertas: Este indicador también te permite configurar alertas. Así, recibirás notificaciones automáticas cuando se generen señales de compra o venta, ayudándote a tomar decisiones sin estar constantemente monitoreando el gráfico.
Inverted SD Dema RSI | viResearchInverted SD Dema RSI | viResearch
The "Inverted SD Dema RSI" developed by viResearch introduces a new approach to trend analysis by combining the Double Exponential Moving Average (DEMA), Standard Deviation (SD), and Relative Strength Index (RSI). This unique indicator provides traders with a tool to capture market trends by integrating volatility-based thresholds. By using the smoothed DEMA along with standard deviation, the indicator offers improved responsiveness to price fluctuations, while RSI thresholds offer insight into overbought and oversold market conditions.
At the core of the "Inverted SD Dema RSI" is the combination of DEMA and standard deviation for a more nuanced view of market volatility. The use of RSI further aids in detecting price extremes and potential trend reversals.
DEMA Calculation (sublen): The Double Exponential Moving Average (DEMA) smoothes out price data over a user-defined period, reducing lag compared to traditional moving averages. This provides a clearer representation of the market's overall direction.
Standard Deviation Calculation (sublen_2): The standard deviation of the DEMA is used to define the upper (u) and lower (d) bands, highlighting areas where price volatility may signal a change in trend. These dynamic bands help traders gauge price volatility and potential breakouts or breakdowns.
RSI Calculation (len): The script applies the Relative Strength Index (RSI) to the smoothed DEMA values, allowing traders to detect momentum shifts based on a modified data set. This provides a more accurate reflection of market strength when combined with the DEMA.
Thresholds: The RSI is compared to user-defined thresholds (70 for overbought and 55 for oversold conditions). These thresholds help in identifying potential market reversals, especially when the price breaks outside of the calculated standard deviation bands.
Uptrend (L): An uptrend signal is generated when the RSI exceeds the upper threshold (70) and the price is not above the upper standard deviation band, indicating that there may be room for further price appreciation.
Downtrend (S): A downtrend signal occurs when the RSI falls below the lower threshold (55), indicating that the price may continue to decline.
The "Inverted SD Dema RSI" offers a wide range of customizable settings, allowing traders to adjust the indicator based on their trading style or market conditions.
DEMA Length (sublen): Controls the period used to smooth the price data, impacting the sensitivity of the DEMA to recent price movements.
Standard Deviation Length (sublen_2): Defines the length over which the standard deviation is calculated, helping traders control the width of the upper and lower bands.
RSI Length (len): Adjusts the period used for the RSI calculation, providing flexibility in determining overbought and oversold conditions.
RSI Thresholds: Traders can define their own levels for detecting trend reversals, with default values of 70 for an uptrend and 55 for a downtrend.
The "Inverted SD Dema RSI" is particularly well-suited for traders looking to capture trends while accounting for volatility and momentum. By using a smoothed DEMA as the foundation, it effectively filters out noise, making it ideal for detecting reliable trends in volatile markets.
Key Uses:
Trend Following: The indicator’s combination of DEMA, standard deviation, and RSI helps traders follow trends more effectively by reducing noise and identifying key momentum shifts.
Volatility Filtering: The use of standard deviation bands provides a dynamic measure of volatility, ensuring that traders are aware of potential breakouts or breakdowns in the market.
Momentum Detection: The inclusion of RSI ensures that the indicator is not only focused on trend direction but also on the strength of the underlying momentum, helping traders avoid entering trades during weak trends.
The "Inverted SD Dema RSI" provides several key advantages over traditional trend-following indicators:
Reduced Lag: The use of DEMA ensures faster trend detection, reducing the lag associated with simple moving averages.
Noise Reduction: The integration of standard deviation helps filter out irrelevant price movements, making it easier to identify significant trends.
Momentum Awareness: The addition of RSI provides valuable insight into the strength of trends, helping traders avoid false signals during periods of weak momentum.
The "Inverted SD Dema RSI" offers a powerful blend of trend-following and momentum detection, making it a versatile tool for modern traders. By integrating DEMA, standard deviation, and RSI, the indicator provides a comprehensive view of market trends and volatility. Traders are encouraged to experiment with different settings for the DEMA length, standard deviation, and RSI thresholds to fine-tune the indicator for their specific trading strategies. Whether used for trend confirmation, volatility assessment, or momentum analysis, the "Inverted SD Dema RSI" offers a valuable tool for traders seeking a comprehensive approach to market analysis.
Median Standard Deviation | viResearchMedian Standard Deviation | viResearch
The "Median Standard Deviation" indicator, developed by viResearch, introduces a unique combination of median smoothing and standard deviation to detect trends and volatility in market data. This tool provides traders with a stable and accurate measure of price trends by integrating median smoothing with a customized calculation of the standard deviation. This innovative approach allows for enhanced sensitivity to market fluctuations while filtering out short-term price noise.
Technical Composition and Calculation:
The "Median Standard Deviation" indicator incorporates median smoothing and dynamic standard deviation calculations to build upon traditional volatility measures.
Median Smoothing:
DEMA Calculation (len_dema): The script applies a Double Exponential Moving Average (DEMA) to smooth the price data over a user-defined period, reducing noise and helping traders focus on broader market trends.
Median Calculation (median_len): The smoothed DEMA data is further refined by calculating the 50th percentile (median) over a specified length, ensuring that the central tendency of price data is captured more accurately than with a simple moving average.
Volatility Measurement:
ATR Calculation (atr_len, atr_mul): The script incorporates the Average True Range (ATR) to measure market volatility. The user-defined ATR multiplier is applied to this value to calculate upper and lower trend bands around the median, providing a dynamic measure of potential price movement based on recent volatility.
Standard Deviation Analysis:
Standard Deviation Calculation (len_sd): The script calculates the standard deviation of the median over a user-defined length, providing another layer of volatility measurement. The upper and lower standard deviation bands (sdd, sdl) act as additional indicators of price extremes.
Trend Detection:
Trend Logic: The indicator uses the calculated bands to identify whether the price is moving within or outside the standard deviation and ATR bands. Crosses above or below these bands are used to signal potential uptrends or downtrends, offering traders a clear view of market direction.
Features and User Inputs:
The "Median Standard Deviation" script offers a variety of user inputs to customize the indicator to suit traders' styles and market conditions:
DEMA Length: Allows traders to adjust the sensitivity of the DEMA smoothing to control the amount of noise filtered from the price data.
Median Length: Users can define the length over which the median price is calculated, providing flexibility in capturing short-term or long-term trends.
ATR Length and Multiplier: These inputs let traders fine-tune the ATR calculation, affecting the size of the dynamic upper and lower bands.
Standard Deviation Length: Controls how the standard deviation is calculated, allowing for further customization in detecting price volatility.
Practical Applications:
The "Median Standard Deviation" indicator is particularly effective in volatile markets where price swings can lead to false signals using traditional methods. By combining median smoothing and standard deviation, this tool provides a more robust analysis of trends and price movements.
Key Uses:
Trend Following: The upper and lower bands provide clear signals for entering and exiting trades based on whether the price is moving outside the calculated ranges.
Volatility Detection: The integration of ATR and standard deviation bands allows traders to assess market volatility in real time, enabling more informed trading decisions.
Noise Reduction: The use of median smoothing ensures that short-term price fluctuations do not interfere with broader trend analysis, making this indicator ideal for traders looking to avoid whipsaws in volatile markets.
Advantages and Strategic Value:
The "Median Standard Deviation" indicator offers several key advantages:
Precision in Trend Detection: The combination of median smoothing and standard deviation allows traders to detect trends with greater accuracy, reducing the risk of false signals.
Customization: With several adjustable parameters, traders can fine-tune the indicator to suit different timeframes and trading strategies.
Volatility Sensitivity: By incorporating ATR and standard deviation, this indicator provides an adaptive measure of market volatility, ensuring that traders are always aware of potential price swings.
Summary and Usage Tips:
The "Median Standard Deviation" indicator is a powerful tool for traders looking to refine their analysis of market trends and volatility. Its combination of median smoothing and standard deviation provides a nuanced view of market movements, helping traders make better-informed decisions. It's recommended to experiment with the various input parameters to optimize the indicator for specific needs, whether used for trend detection, volatility analysis, or noise reduction. The "Median Standard Deviation" offers a reliable and adaptable solution for modern trading strategies.
Please keep in mind the following text: Backtests are based on past results and are not indicative of future performance.
Rainbow Histogram v1.01Sure! Here’s a compelling English version of the article for your TradingView post:
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### 🌈 **Introducing Rainbow Histogram: A Fusion of EMA and MA for Enhanced Trading Analysis**
**Hello Traders,**
I’m excited to introduce a fresh concept that combines technical analysis techniques into a new indicator called **Rainbow Histogram**. This innovative tool blends Exponential Moving Averages (EMA) and Moving Averages (MA) to provide you with a powerful and accurate tool for making trading decisions.
#### **🎨 What is Rainbow Histogram?**
The Rainbow Histogram is designed to help you identify market trends and signal precise entry and exit points by blending EMA and MA into a colorful "Rainbow" display. This visual approach enhances your ability to spot trend strength and direction with clarity.
#### **📈 How Does Rainbow Histogram Work?**
1. **Exponential Moving Average (EMA):** Captures short-term trends and reacts quickly to price changes.
2. **Moving Average (MA):** Tracks long-term trends and provides a broader view of the market direction.
**Rainbow Histogram** uses the combination of EMA and MA to create a histogram that shows the difference between these two averages in distinct colors. This makes it easy to visualize trend changes and market momentum.
#### **🔧 Setting It Up**
1. **EMA:** Adjust the EMA settings based on your trading timeframe and strategy (e.g., EMA 9, EMA 21).
2. **MA:** Set the MA parameters to capture long-term trends (e.g., MA 50, MA 200).
#### **🌟 Why Use Rainbow Histogram?**
- **Simplified Analysis:** Quickly identify trends and their strength with a clear visual representation.
- **Distinct Colors:** Differentiate between EMA and MA with vibrant colors for easy interpretation.
- **Precise Signals:** Get clear buy and sell signals based on histogram changes.
#### **📥 Get Started**
Add **Rainbow Histogram** to your TradingView charts by searching for the script in TradingView’s library or set it up manually using the recommended settings.
#### **📝 In Summary**
**Rainbow Histogram** is a unique tool that simplifies trend analysis and enhances accuracy by merging EMA and MA into a single, colorful indicator. Use this tool to refine your trading strategy and make more informed financial decisions.
If you have any questions or feedback about **Rainbow Histogram**, feel free to comment below or send me a message!
**Happy Trading!** 🌟
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I hope this version effectively captures attention and engages your audience!
Fractal Proximity MA Aligment Scalping StrategyFractal Analysis
Fractals in trading help identify potential reversal points by marking significant price changes. Our strategy calculates a "fractal value" by comparing the current price to recent high and low fractal points. This is done by evaluating the sum of distances from the current closing price to the recent highs and lows. A positive fractal value suggests proximity to recent lows, hinting at upward momentum. Conversely, a negative value indicates closeness to recent highs, signaling potential downward movement.
Moving Averages for Confirmation
We use a series of 20 moving averages ranging from 5 to 100 to confirm trend directions indicated by fractal analysis. An entry signal is considered bullish when shorter-term moving averages are all above a long-term moving average, aligning with a positive fractal value.
Exit Strategy
The strategy employs dynamic stop-loss levels set at various moving averages, allowing for partial exits when the price crosses below specific thresholds. This helps manage the trade by locking in profits gradually. A full exit might be triggered by strong reversal signals suggested by both fractal values and moving average trends.
This open-source strategy is available for the community to test, adapt, and utilize. Your feedback and modifications are welcome as we refine the approach based on collective user experiences.
Composite Momentum█ Introduction
The Composite Momentum Indicator is a tool we came across that we found to be useful at detecting implied tops and bottoms within quick market cycles. Its approach to analyzing momentum through a combination of moving averages and summation techniques makes it a useful addition to the range of available indicators on TradingView.
█ How It Works
This indicator operates by calculating the difference between two moving averages—one fast and one slow, which can be customized by the user. The difference between these two averages is then expressed as a percentage of the fast moving average, forming the core momentum value which is then smoothed with an Exponential Moving Average is applied. The smoothed momentum is then compared across periods to identify directional changes in direction
Furthermore, the script calculates the absolute differences between consecutive momentum values. These differences are used to determine periods of momentum acceleration or deceleration, aiming to establish potential reversals.
In addition to tracking momentum changes, the indicator sums positive and negative momentum changes separately over a user-defined period. This summation is intended to provide a clearer picture of the prevailing market bias—whether it’s leaning towards strength or weakness.
Finally, the summed-up values are normalized to a percentage scale. This normalization helps in identifying potential tops and bottoms by comparing the relative strength of the momentum within a given cycle.
█ Usage
This indicator is primarily useful for traders who focus on detecting quick cycle tops and bottoms. It provides a view of momentum shifts that can signal these extremes, though it’s important to use it in conjunction with other tools and market analysis techniques. Given its ability to highlight potential reversals, it may be of interest to those who seek to understand short-term market dynamics.
█ Disclaimer
This script was discovered without any information about its author or original intent but was nonetheless ported from its original format that is available publicly. It’s provided here for educational purposes and should not be considered a guaranteed method for market analysis. Users are encouraged to test and understand the indicator thoroughly before applying it in real trading scenarios.
Median Supertrend | viResearchMedian Supertrend | viResearch
Conceptual Foundation and Innovation
The "Median Supertrend" indicator, developed by viResearch, offers a unique approach to identifying trends by combining a median-based smoothing mechanism with a modified Supertrend calculation. Unlike the traditional Supertrend, which relies solely on price data, this version calculates a median percentile of the closing price over a specified length, resulting in a more accurate representation of underlying trends.
Technical Composition and Calculation
The "Median Supertrend" enhances the conventional Supertrend formula by introducing improvements to minimize lag and improve responsiveness to market volatility.
Median Smoothing:
The script uses the 50th percentile of the closing price over a user-defined period to provide a smoother representation of price movements, reducing the influence of short-term price spikes or dips for more stable trend analysis.
Supertrend Calculation:
The indicator applies the Average True Range (ATR) to determine the upper and lower trend bands, which are then shifted above or below the smoothed price (median) by a multiple of the ATR, customizable by users to adjust sensitivity.
Trend Logic:
The script uses the upper and lower bands to detect whether the price is trending upwards or downwards and introduces persistence logic to prevent excessive shifting of the bands during consolidating market phases. This mechanism ensures that once the trend changes, the bands adjust smoothly rather than oscillating with each price movement.
Directional Analysis:
Based on price action relative to the trend bands, a directional variable (d) is computed to track whether the price crosses above or below these bands, signaling uptrends or downtrends. The script also includes events to detect transitions from bullish to bearish trends and vice versa, with the option to set alerts for timely decision-making.
Features and User Inputs
The "Median Supertrend" offers several customizable parameters to suit different trading styles:
Supertrend Length: Defines the period used to calculate the smoothing, allowing users to adjust the indicator's sensitivity based on market conditions.
Multiplier: Controls how far the trend bands are placed from the median price. Traders can increase the multiplier for less frequent trend changes or decrease it for more sensitive detection.
Median Length: Governs the length over which the median price is calculated, providing further customization to balance responsiveness and stability.
Practical Applications
The "Median Supertrend" is particularly useful in markets with rapid trend reversals and high volatility, offering an effective way to filter out noise and capture significant trend changes promptly.
Key Uses:
Trend Following: The indicator's primary function is to identify prevailing trends and guide traders in aligning with the market's direction, with its smoothing mechanism helping to ensure reliable trend signals.
Trend Reversal Detection: By tracking crossovers and crossunders relative to the Supertrend bands, the indicator helps traders detect potential reversals early, making it valuable in fast-moving markets.
Strategic Positioning: With adjustable sensitivity and real-time alerts, the "Median Supertrend" can adapt to a variety of trading strategies, from scalping to longer-term trend-following.
Advantages and Strategic Value
The "Median Supertrend" offers advantages over traditional trend indicators:
Reduced Noise: Median smoothing reduces noise from extreme price movements, ensuring more reliable trend signals.
Customizability: With adjustable length and multiplier settings, the indicator allows traders to fine-tune its sensitivity for different market conditions.
Responsiveness: Median-based smoothing, coupled with the ATR, provides a more responsive and adaptive measure of trend direction, particularly valuable in volatile markets.
Summary and Usage Tips
The "Median Supertrend" indicator is a potent tool for capturing market trends with increased precision and reduced lag. It combines the best features of traditional Supertrend indicators with the added stability of median-based smoothing, making it highly effective in volatile markets. Traders are encouraged to experiment with the length and multiplier settings to optimize the indicator for their specific trading strategies, while alerts and visual cues further enhance its utility.
Please keep in mind the following text: Backtests are based on past results and are not indicative of future performance.
VWAP and MA Crossover SignalsDescription: The VWAP and 20 MA Crossover Indicator is a powerful trading tool designed to capitalize on trend reversals and momentum shifts. This indicator overlays two key technical analysis tools on the price chart: the Volume Weighted Average Price (VWAP) and the 20-period Moving Average (MA).
Functionality:
VWAP: Represents the average price a security has traded at throughout the day, based on volume and price. It is a measure of the market's trend and trading volume.
20 MA: Offers a smoothed average of the closing prices over the last 20 periods, providing a glimpse of the underlying trend.
Signals:
Buy Signal: Generated when the VWAP crosses above the 20-period MA, suggesting an upward momentum and a potential bullish trend reversal.
Sell Signal: This occurs when the VWAP crosses below the 20-period MA, indicating a downward momentum and a potential bearish trend reversal.
Usage: This indicator is ideal for traders focusing on intraday and swing trading strategies, providing clear visual cues for entry and exit points based on the interaction between VWAP and the 20 MA. By identifying key crossover points, traders can make informed decisions about potential bullish or bearish movements in the market.
Application: To use this indicator, simply add it to your TradingView chart setup. The buy and sell signals will be displayed directly on the chart, allowing for easy interpretation and quick action. Adjust the settings to fit your specific trading strategy or market conditions.
Combo 2/20 EMA & CCI
This is another part of my research work, where I test a combination of two strategies, receiving a combined signal. In order to understand which indicator combinations work better, which work worse, as filters for trades. This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
The Commodity Channel Index (CCI) is best used with markets that display cyclical or seasonal characteristics, and is formulated to detect the beginning and ending of the cycles by incorporating a moving average together with a divisor that reflects both possible and actual trading ranges. The final index measures the deviation from normal, which indicates major changes in market trend.
Strategy tester settings:
Initial capital: 1000
Order size: 0.5
Commission: 0.1%
Other as default.
Indicator settings:
EMA Length: 50
CCI Length: 10
Fast MA Length: 15
Slow MA Length: 20
Other as default.
WARNING:
- For purpose educate only
- This script to change bars colors.
RSI based MAGot it! Here’s some information in English specifically about the **RSI-based Moving Average (RSI-based MA)** that we wrote the Pine Script code for:
### RSI-Based Moving Average (RSI-based MA)
An **RSI-based Moving Average (RSI-based MA)** is a technical analysis tool that combines the Relative Strength Index (RSI) with moving averages to provide more insight into market trends and potential reversals. This indicator can be particularly useful for identifying the beginning and end of trends, allowing traders to make more informed decisions.
### How RSI-based MA Works
The RSI-based MA indicator calculates the moving average of the RSI values rather than the asset's price itself. In the script you asked for, we implemented two RSI-based moving averages: one for a 1-minute timeframe and another for a 5-minute timeframe. This dual timeframe approach can help traders spot trends more accurately and identify shifts in momentum across different time periods.
#### Key Features of RSI-based MA:
1. **Dual Timeframe Analysis**:
- The script plots two RSI-based moving averages on the same chart:
- **1-minute RSI-based MA**: A moving average calculated based on RSI values over a 1-minute interval.
- **5-minute RSI-based MA**: A moving average calculated based on RSI values over a 5-minute interval.
- Using different timeframes helps traders see both short-term and longer-term trends simultaneously.
2. **RSI Levels**:
- The RSI-based MA plots values between 0 and 100, similar to the RSI itself. Traders can use typical RSI levels, such as 70 (overbought) and 30 (oversold), to identify potential entry and exit points.
- **Overbought condition**: When the RSI-based MA moves above 70, it indicates the asset might be overbought, suggesting a potential for price to drop.
- **Oversold condition**: When the RSI-based MA drops below 30, it signals that the asset might be oversold, indicating a potential price increase.
3. **Crossovers**:
- **Bullish signal**: If the shorter 1-minute RSI-based MA crosses above the longer 5-minute RSI-based MA, this could indicate a new upward trend beginning.
- **Bearish signal**: Conversely, if the 1-minute RSI-based MA crosses below the 5-minute RSI-based MA, it could suggest the beginning of a downward trend.
### Potential Advantages
- **Smoother Trend Identification**: By applying moving averages to RSI, you can smooth out the short-term fluctuations in RSI values, making it easier to identify the underlying trend.
- **Versatility**: The indicator can be customized for different timeframes and settings, allowing it to be tailored to various trading strategies and asset classes.
- **Enhanced Signals**: Combining RSI and moving averages helps filter out noise, providing more reliable signals for potential trend changes or continuations.
### Potential Limitations
- **Lagging Indicator**: Like most moving averages, RSI-based MAs are lagging indicators. They tend to react after price movements have already begun, which could result in delayed signals.
- **False Signals**: In ranging or highly volatile markets, RSI-based MA may give false signals, indicating a trend reversal or continuation that does not occur.
- **Should Not Be Used Alone**: It's often recommended to use RSI-based MA alongside other technical indicators (like MACD, Bollinger Bands, or moving average crossovers) to confirm signals and reduce the risk of false readings.
### Conclusion
The RSI-based MA can be a powerful tool for traders looking to enhance their understanding of market trends and momentum. By combining RSI with moving averages, traders can smooth out RSI readings and gain a clearer view of the market’s direction. However, as with any indicator, it should be used in conjunction with other tools and strategies to maximize its effectiveness and reduce risk.
True Strength Index with Buy/Sell Signals and AlertsThe True Strength Index (TSI) is a momentum oscillator that helps traders identify trends and potential reversal points in the market. Here’s how it works:
1. **Price Change Calculation**:
- **`pc = ta.change(price)`**: This calculates the change in price (current price minus the previous price).
2. **Double Smoothing**:
- **`double_smooth(src, long, short)`**: This function smooths the price change data twice using two Exponential Moving Averages (EMAs):
- The first EMA smooths the raw data.
- The second EMA smooths the result of the first EMA.
- **`double_smoothed_pc`**: The double-smoothed price change.
- **`double_smoothed_abs_pc`**: The double-smoothed absolute price change, which helps normalize the TSI value.
3. **TSI Calculation**:
- **`tsi_value = 100 * (double_smoothed_pc / double_smoothed_abs_pc)`**: This calculates the TSI by dividing the double-smoothed price change by the double-smoothed absolute price change, then multiplying by 100 to scale the value.
- The TSI oscillates around the zero line, indicating momentum. Positive values suggest bullish momentum, while negative values suggest bearish momentum.
4. **Signal Line**:
- **`signal_line = ta.ema(tsi_value, signal)`**: This creates a signal line by applying another EMA to the TSI value. The signal line is typically used to identify entry and exit points.
5. **Buy and Sell Signals**:
- **Buy Signal**: Occurs when the TSI crosses above the signal line (`ta.crossover(tsi_value, signal_line)`), indicating that bullish momentum is strengthening, which might suggest a buying opportunity.
- **Sell Signal**: Occurs when the TSI crosses below the signal line (`ta.crossunder(tsi_value, signal_line)`), indicating that bearish momentum is strengthening, which might suggest a selling opportunity.
6. **Visual Representation**:
- The TSI line and the signal line are plotted on the chart.
- Buy signals are marked with green "BUY" labels below the bars, and sell signals are marked with red "SELL" labels above the bars.
**How to Use It**:
- **Trend Identification**: When the TSI is above zero, it suggests an uptrend; when it's below zero, it suggests a downtrend.
- **Buy/Sell Signals**: Traders often enter a buy trade when the TSI crosses above the signal line and enter a sell trade when the TSI crosses below the signal line.
- **Divergences**: TSI can also be used to spot divergences between the indicator and price action, which can signal potential reversals.
The TSI is particularly useful in identifying the strength of a trend and the potential turning points, making it valuable for trend-following and swing trading strategies.
[MACC] Moving Average Candle ColorThe simplest trading framework is using moving average. This indicator is harnessing that very method.
What It Does:
This indicator helps you see market trends at a glance by changing the color of the candlesticks based on the relationship between two Exponential Moving Averages (EMAs). When the 9-period EMA is above the 21-period EMA, candlesticks turn green, suggesting a bullish trend. When the 9 EMA is below the 21 EMA, candlesticks turn red, indicating a bearish trend.
Why You'll Love It:
Easy Trend Visualization: Quickly spot trends and potential reversals with color-coded candlesticks.
Customizable Settings: Adjust the lengths of the EMAs to fit your trading style. Just change the values in the settings panel and watch the indicator update in real-time.
Optional EMA Lines: See the EMA lines plotted on your chart for added context and trend confirmation.
How to Use It:
Green Candlesticks: It’s a sign that the trend is likely upward.
Red Candlesticks: signaling a potential downward trend.
Customization:
EMA Lengths: You can set the lengths for the 9 EMA and 21 EMA to whatever fits your trading strategy best.
Colors: Adjust the colors if you want to match your chart’s theme.
Get Started: Add this indicator to your TradingView chart and tweak the settings to see how it helps you track market trends more effectively.
Cherio...
Dynamic Trailing Stop with Trend ChangeKey features of this script:
Trend Identification: Uses previous day's high/low breaks to identify trend changes.
Uptrend starts when price closes above the previous day's high.
Downtrend starts when price closes below the previous day's low.
Dynamic Trailing Stop:
In an uptrend, the stop is set to the previous day's low and trails higher.
In a downtrend, the stop is set to the previous day's high and trails lower.
Visual Indicators:
Green triangle for uptrend start, red triangle for downtrend start.
Green/red line for the trailing stop.
Background color changes to light green in uptrends, light red in downtrends.
Alerts:
Trend change alerts when a new trend is identified.
Stop hit alerts when price crosses the trailing stop, suggesting a potential exit.
This implementation allows you to:
Identify trend changes based on previous day's high/low breaks.
Trail your stop loss dynamically as the trend progresses.
Get visual and alert-based signals for trend changes and potential exit points.
For swing trading, you could:
Enter long when an uptrend starts (green triangle).
Set your initial stop loss to the trailing stop (green line).
Exit if the price closes below the trailing stop or a downtrend starts (red triangle).
(Reverse for short trades)
Remember, while this strategy can be effective, it's important to combine it with other forms of analysis and proper risk management. The effectiveness can vary depending on the volatility of the asset and overall market conditions. Always test thoroughly before using in live trading.
Sniper Signal- Description
The Sniper Signal is a sophisticated technical indicator designed for traders seeking to maximize accuracy in identifying key turning points within a market. This indicator is built on a dual approach, combining the power of the Wave Trend Momentum Oscillator (WTMO) with the robustness of a long-term Simple Moving Average (SMA), making it an ideal tool for trading in dynamic and trending market environments.
The WTMO is known for its ability to capture momentum and underlying price direction, providing early signals of trend changes. By smoothing price movements using an exponential moving average (EMA), the WTMO accurately identifies when price is overextending in one direction, which may precede a reversal.
The 100-period SMA acts as a critical trend filter, ensuring that trades are only made in the direction of the prevailing market flow. This approach ensures that signals generated by the WTMO align with the long-term trend, filtering out false signals that can appear in sideways or low volatility markets.
The Sniper Signal is not just an indicator that marks entries and exits; it is a complete strategy in itself, designed for traders who understand the importance of trading in the direction of the prevailing trend. Buy signals are generated only when momentum is at its lowest point (WT1 < -5) and the price is supported by a confirmed uptrend (price above the SMA). Conversely, sell signals are only triggered when momentum is at extremely high levels (WT1 > 5) and the market shows clear signs of weakness (price below the SMA).
This combination of momentum and trend analysis creates a balanced approach that allows traders to capture significant moves in the market, while minimizing exposure to unnecessary risk. The Sniper Signal is particularly effective in markets with well-defined trends, where the key to success lies in entering the market at optimal points and exiting before a significant reversal occurs.
In summary, the Sniper Signal is an advanced tool designed for serious traders looking to take advantage of the combination of momentum and trend to execute high probability trades in moving markets.
- How to use the script?
The Sniper Signal indicator code is written in Pine Script, the native programming language of TradingView. To use this indicator, users must copy the code and paste it into the Pine Script editor within the TradingView platform. Once they have done this, they can save and add the script to their chart to begin displaying buy and sell signals directly on their price charts.
When using the Sniper Signal, traders should pay attention to the signals represented by the triangles on the chart: an upward-facing blue triangle indicates a possible buying opportunity, while a downward-facing red triangle suggests a possible selling opportunity. It is crucial that users also watch the 100-period Simple Moving Average (SMA), shown as a gray line on the chart, to ensure that trades align with the overall market trend. This helps filter out less reliable signals and improves the accuracy of trading decisions.
- Open-source reuse
The indicator code is based on common and widely used concepts in technical analysis, such as the Wave Trend Momentum Oscillator (WTMO) and the Simple Moving Average (SMA). These components are not proprietary and are part of the general knowledge in the trading community, which means that many developers can create their own versions based on these same principles.
Liquidity weighted SupertrendOverview
The Liquidity Weighted Supertrend Indicator (LWST) is an advanced iteration of the traditional Supertrend indicator, meticulously crafted to improve trend detection by incorporating liquidity into its calculations. By weighting price movements according to trading volume, the LWST becomes more responsive to significant market activities, offering traders a more accurate depiction of market trends.
Indicator Description
The Liquidity Weighted Supertrend Indicator is a versatile and adaptive tool designed to assist traders in recognizing trends and potential reversal points within the market. This indicator features two operational modes: Aggressive and Smoothed, allowing traders to tailor trend detection to their specific trading style and market conditions.
Key Features
Two Supertrend Modes:
Aggressive Mode: This mode offers more responsive signals, ideal for short-term trading. It utilizes an Exponential Moving Average (EMA) to smooth the price data, resulting in quicker reactions to market changes.
Smoothed Mode: This mode provides more stable signals, suitable for longer-term trading, by employing a Simple Moving Average (SMA). Note that when "Smoothed" mode is selected, the "Fast MA length" input is not utilized, focusing instead on producing smoother trend lines.
LWMA Calculation:
The Liquidity Weighted Moving Average (LWMA) is a distinctive feature of the LWST, blending volume and price action to filter out market noise and pinpoint significant price movements. This calculation begins with the liquidity factor, determined by multiplying volume with the price change, which is then smoothed using an EMA for accuracy.
Customizable Parameters:
Factor: Adjusts the Supertrend line's sensitivity to price movements.
Supertrend Length: Defines the lookback period for the Average True Range (ATR) calculation, which affects the width of the Supertrend channel.
Fast and Slow MA Lengths: Allows customization of the fast and slow moving averages used in the LWMA calculation, offering further control over the indicator's responsiveness.
How the Indicator Works
LWMA Smoothing:
The LWST calculates liquidity by multiplying volume with the absolute difference between the close and open prices. This liquidity value is smoothed using an EMA and compared to its standard deviation, identifying significant price movements. Depending on the selected mode, the price data (hl2) is smoothed either with an EMA (in Aggressive Mode) or an SMA (in Smoothed Mode). It’s important to note that when Smoothed mode is active, the "Fast MA length" input does not affect the output.
Visual Signals:
The Supertrend line is visually represented on the chart, with different colors indicating bullish (lime) and bearish (red) trends.
Buy and sell signals are clearly marked with arrows: green triangles indicate potential buying opportunities (when the price crosses above the Supertrend line), and red triangles suggest selling opportunities (when the price crosses below the Supertrend line).
Additional arrows may appear, signaling potential trend reversals, providing further confirmation for traders.
How to Use the Indicator
Configuring the Indicator:
Supertrend Type: Choose between Aggressive and Smoothed modes depending on your trading strategy and the current market conditions. Aggressive mode is better suited for shorter timeframes, while Smoothed mode provides more consistent signals for longer-term analysis.
Factor and Length Settings: Customize the Factor, Supertrend Length, and Moving Average lengths to fine-tune the sensitivity and responsiveness of the Supertrend line, adapting the indicator to various market environments.
Interpreting the Signals:
Trend Identification: The Supertrend line offers a clear visualization of the current market trend. A green line indicates a bullish trend, suggesting upward price movement, while a red line indicates a bearish trend, signaling potential downward price movement.
Entry and Exit Points: The arrows plotted by the LWST provide straightforward entry and exit signals. Green arrows signal potential buy opportunities, indicating that the price may continue to rise, while red arrows signal potential sell opportunities, suggesting that the price may decline. These visual cues help traders make informed decisions based on the current market trend.
Break of High/Low with Volume, MACD, and MAsHow It Works:
Sessions:
The London session is defined between 8:00 and 16:00 UTC.
The New York session is defined between 13:00 and 21:00 UTC.
Previous High/Low:
The script identifies the highest high and lowest low from the previous bar using ta.highest(high, 1) and ta.lowest(low, 1) .
Candle Body Size:
The script calculates the size of the current candle's body and checks if it is at least double the size of the previous candle's body.
Volume Check:
A high volume threshold is set as 1.5 times the 50-period SMA of the volume.
MACD Crossover:
The script calculates the MACD and its signal line and checks for bullish (buy) or bearish (sell) crossovers.
Signals:
A long signal (buy) is generated if the price breaks the previous high with a large body candle, high volume, and a bullish MACD crossover during the specified sessions.
A short signal (sell) is generated if the price breaks the previous low with a large body candle, high volume, and a bearish MACD crossover during the specified sessions.
Plotting:
The 50-period and 200-period moving averages, previous high, and previous low are plotted on the chart.
If a long condition is met, a "BUY" label is displayed below the bar. If a short condition is met, a "SELL" label is displayed above the bar.
Alerts:
Alerts are triggered whenever the conditions for a long or short trade are met.
Customization:
Feel free to adjust the session times, volume threshold, MACD settings, or moving averages based on your trading strategy or the specific asset you are trading.
Multi Adaptive Moving Average (MAMA)The Multi Adaptive Moving Average (MAMA) indicator is an advanced tool for technical analysis, designed to provide traders with a detailed understanding of market trends and potential future price movements. This indicator utilizes multiple Simple Moving Averages (SMAs) and forecasting techniques to enhance decision-making processes.
Simple Moving Averages (SMAs):
Short MA (20-period): This moving average is highly responsive to price changes, making it ideal for capturing short-term trends. It helps traders identify quick market shifts and potential entry or exit points.
Mid MA (50-period): This average strikes a balance between short- and long-term trends, offering insights into the market's intermediate direction. It aids in confirming the sustainability of short-term trends.
Long MA (100-period): By smoothing out price data over a longer period, this moving average is useful for identifying long-term trends and filtering out short-term volatility.
Very Long MA (200-period): Often considered a critical indicator for determining the overall market trend, this average helps confirm the direction and strength of long-term movements.
Forecasting:
Flat Forecast: This approach assumes that prices will remain constant in the near future, which is particularly useful in markets trading sideways without a clear trend direction.
Linear Regression Forecast: This method uses historical data to project future price movements, offering a dynamic forecast based on existing trends. It helps traders anticipate potential price changes and plan their strategies accordingly.
Advantages:
Comprehensive Trend Analysis: By incorporating four different SMAs, the indicator provides a layered view of market trends across various timeframes. This enables traders to identify potential trend reversals and continuations with greater accuracy.
Predictive Insights: The forecasting feature offers traders a forward-looking perspective, enabling them to anticipate market movements and adjust their trading strategies proactively. This can be especially advantageous in volatile markets.
Customization: The MAMA indicator is highly customizable, allowing traders to adjust parameters such as the source of price data and the inclusion of the current unclosed candle. This flexibility ensures that the indicator can be tailored to fit different trading styles and market conditions.
Visual Clarity: The use of distinct colors for each SMA and their forecasts enhances visual interpretation, making it easier for traders to quickly assess market conditions and make informed decisions. The inclusion of a legend further aids in distinguishing between the different moving averages and their respective forecasts.
How to Use:
Trend Confirmation: Use the alignment of the SMAs to confirm market trends. For example, when the Short MA crosses above the Mid and Long MAs, it may indicate a bullish trend, while the opposite could suggest a bearish trend.
Entry and Exit Points: Look for crossovers between the SMAs as potential signals for entering or exiting trades. The forecasts can help in timing these decisions by providing an expectation of future price movements.
Risk Management: Utilize the Very Long MA to set stop-loss and take-profit levels, as it reflects the long-term trend and can help in avoiding trades against the prevailing market direction.
The MAMA indicator is intended to support technical analysis and should not be used as the sole basis for making trading decisions. Financial markets are inherently uncertain, and past performance does not guarantee future results. Traders should use this tool in conjunction with other analytical methods and consider their risk tolerance and investment objectives. It is advisable to conduct thorough research and consult with a financial advisor before making significant trading decisions. Always be aware of the risks involved in trading and invest only what you can afford to lose.
BTC Top Indicator - Extension from 20 Week SMA (Normalized)This Indicator calculates the logarithmic deviation of the BTCUSD price from its 20-week SMA and dynamically normalizes it between a lower signal line (-0.57) and an upper trendline defined by two historical points (May 30, 2011, at 1.75 and March 4, 2024, at 0.45).
The indicator line color changes dynamically:
green below 0
blue at 0.5
red above 1
Ideal for analyzing BTCUSD on the Index chart to identify potential overbought or oversold levels. It's better suited for identifying tops, than bottoms.
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
TrendFusion [CrypTolqa]This code colors the SMA line red when the RSI is below 50 and the CCI is below 0, and green when the RSI is above 50 and the CCI is above 0. For cases that do not meet the specified details, the line is displayed in gray.
Uptrick: DPO Signal & Zone Indicator
## **Uptrick: DPO Signal & Zone Indicator**
### **Introduction:**
The **Uptrick: DPO Signal & Zone Indicator** is a sophisticated technical analysis tool tailored to provide insights into market momentum, identify potential trading signals, and recognize extreme market conditions. It leverages the Detrended Price Oscillator (DPO) to strip out long-term trends from price movements, allowing traders to focus on short-term fluctuations and cyclical behavior. The indicator integrates multiple components, including a Detrended Price Oscillator, a Signal Line, a Histogram, and customizable alert levels, to deliver a robust framework for market analysis and trading decision-making.
### **Detailed Breakdown:**
#### **1. Detrended Price Oscillator (DPO):**
- **Purpose and Functionality:**
- The DPO is designed to filter out long-term trends from the price data, isolating short-term price movements. This helps in understanding the cyclical patterns and momentum of an asset, allowing traders to detect periods of acceleration or deceleration that might be overlooked when focusing solely on long-term trends.
- **Calculation:**
- **Formula:** `dpo = close - ta.sma(close, smaLength)`
- **`close`:** The asset’s closing price for each period in the dataset.
- **`ta.sma(close, smaLength)`:** The Simple Moving Average (SMA) of the closing prices over a period defined by `smaLength`.
- The DPO is derived by subtracting the SMA value from the current closing price. This calculation reveals how much the current price deviates from the moving average, effectively detrending the price data.
- **Interpretation:**
- **Positive DPO Values:** Indicate that the current price is higher than the moving average, suggesting bullish market conditions and a potential upward trend.
- **Negative DPO Values:** Indicate that the current price is lower than the moving average, suggesting bearish market conditions and a potential downward trend.
- **Magnitude of DPO:** Reflects the strength of momentum. Larger positive or negative values suggest stronger momentum in the respective direction.
#### **2. Signal Line:**
- **Purpose and Functionality:**
- The Signal Line is a smoothed average of the DPO, intended to act as a reference point for generating trading signals. It helps to filter out short-term fluctuations and provides a clearer perspective on the prevailing trend.
- **Calculation:**
- **Formula:** `signalLine = ta.sma(dpo, signalLength)`
- **`ta.sma(dpo, signalLength)`:** The SMA of the DPO values over a period defined by `signalLength`.
- The Signal Line is calculated by applying a moving average to the DPO values. This smoothing process reduces noise and highlights the underlying trend direction.
- **Interpretation:**
- **DPO Crossing Above Signal Line:** Generates a buy signal, suggesting that short-term momentum is turning bullish relative to the longer-term trend.
- **DPO Crossing Below Signal Line:** Generates a sell signal, suggesting that short-term momentum is turning bearish relative to the longer-term trend.
- **Signal Line’s Role:** Provides a benchmark for assessing the strength of the DPO. The interaction between the DPO and the Signal Line offers actionable insights into potential entry or exit points.
#### **3. Histogram:**
- **Purpose and Functionality:**
- The Histogram visualizes the difference between the DPO and the Signal Line. It provides a graphical representation of momentum strength and direction, allowing traders to quickly gauge market conditions.
- **Calculation:**
- **Formula:** `histogram = dpo - signalLine`
- The Histogram is computed by subtracting the Signal Line value from the DPO value. Positive values indicate that the DPO is above the Signal Line, while negative values indicate that the DPO is below the Signal Line.
- **Interpretation:**
- **Color Coding:**
- **Green Bars:** Represent positive values, indicating bullish momentum.
- **Red Bars:** Represent negative values, indicating bearish momentum.
- **Width of Bars:** Indicates the strength of momentum. Wider bars signify stronger momentum, while narrower bars suggest weaker momentum.
- **Zero Line:** A horizontal gray line that separates positive and negative histogram values. Crosses of the histogram through this zero line can signal shifts in momentum direction.
#### **4. Alert Levels:**
- **Purpose and Functionality:**
- Alert levels define specific thresholds to identify extreme market conditions, such as overbought and oversold states. These levels help traders recognize potential reversal points and extreme market conditions.
- **Inputs:**
- **`alertLevel1`:** Defines the upper threshold for identifying overbought conditions.
- **Default Value:** 0.5
- **`alertLevel2`:** Defines the lower threshold for identifying oversold conditions.
- **Default Value:** -0.5
- **Interpretation:**
- **Overbought Condition:** When the DPO exceeds `alertLevel1`, indicating that the market may be overbought. This condition suggests that the asset could be due for a correction or reversal.
- **Oversold Condition:** When the DPO falls below `alertLevel2`, indicating that the market may be oversold. This condition suggests that the asset could be poised for a rebound or reversal.
#### **5. Visual Elements:**
- **DPO and Signal Line Plots:**
- **DPO Plot:**
- **Color:** Blue
- **Width:** 2 pixels
- **Purpose:** To visually represent the deviation of the current price from the moving average.
- **Signal Line Plot:**
- **Color:** Red
- **Width:** 1 pixel
- **Purpose:** To provide a smoothed reference for the DPO and generate trading signals.
- **Histogram Plot:**
- **Color Coding:**
- **Green:** For positive values, signaling bullish momentum.
- **Red:** For negative values, signaling bearish momentum.
- **Style:** Histogram bars are displayed with varying width to represent the strength of momentum.
- **Zero Line:** A gray horizontal line separating positive and negative histogram values.
- **Overbought/Oversold Zones:**
- **Background Colors:**
- **Green Shading:** Applied when the DPO exceeds `alertLevel1`, indicating an overbought condition.
- **Red Shading:** Applied when the DPO falls below `alertLevel2`, indicating an oversold condition.
- **Horizontal Lines:**
- **Dotted Green Line:** At `alertLevel1`, marking the upper alert threshold.
- **Dotted Red Line:** At `alertLevel2`, marking the lower alert threshold.
- **Purpose:** To provide clear visual cues for extreme market conditions, aiding in the identification of potential reversal points.
#### **6. Trading Signals and Alerts:**
- **Buy Signal:**
- **Trigger:** When the DPO crosses above the Signal Line.
- **Visual Representation:** A "BUY" label appears below the price bar in the specified buy color.
- **Purpose:** Indicates a potential buying opportunity as short-term momentum turns bullish.
- **Sell Signal:**
- **Trigger:** When the DPO crosses below the Signal Line.
- **Visual Representation:** A "SELL" label appears above the price bar in the specified sell color.
- **Purpose:** Indicates a potential selling opportunity as short-term momentum turns bearish.
- **Overbought/Oversold Alerts:**
- **Overbought Alert:** Triggered when the DPO crosses below `alertLevel1`.
- **Oversold Alert:** Triggered when the DPO crosses above `alertLevel2`.
- **Visual Representation:** Labels "OVERBOUGHT" and "OVERSOLD" appear with distinctive colors and sizes to highlight extreme conditions.
- **Purpose:** To signal potential reversal points and extreme market conditions that may lead to price corrections or trend reversals.
- **Alert Conditions:**
- **DPO Cross Above Signal Line:** Alerts traders when the DPO crosses above the Signal Line, generating a buy signal.
- **DPO Cross Below Signal Line:** Alerts traders when the DPO crosses below the Signal Line, generating a sell signal.
- **DPO Above Upper Alert Level:** Alerts when the DPO is above `alertLevel1`, indicating an overbought condition.
- **DPO Below Lower Alert Level:** Alerts when the DPO is below `alertLevel2`, indicating an oversold condition.
- **Purpose:** To provide real-time notifications of significant market events, enabling traders to make informed decisions promptly.
### **Practical Applications:**
#### **1. Trend Following Strategies:**
- **Objective:**
- To capture and ride the prevailing market trends by entering trades that align with the direction of the momentum.
- **How to Use:**
- Monitor buy and sell signals generated by the DPO crossing the Signal Line. A buy signal suggests a bullish trend and a potential long trade, while a sell signal suggests a bearish trend and a potential short trade.
- Use the Histogram to confirm the strength of the trend. Expanding green bars indicate strong bullish momentum, while expanding red bars indicate strong bearish momentum.
- **Advantages:**
- Helps traders stay aligned with the market trend, increasing the likelihood of capturing substantial price moves.
#### **2. Reversal Trading:**
- **Objective:**
- To identify potential market reversals
by detecting overbought and oversold conditions.
- **How to Use:**
- Look for overbought and oversold signals based on the DPO crossing `alertLevel1` and `alertLevel2`. These conditions suggest that the market may be due for a reversal.
- Confirm reversal signals with the Histogram. A decrease in histogram bars (from green to red or vice versa) may support the reversal hypothesis.
- **Advantages:**
- Provides early warnings of potential market reversals, allowing traders to position themselves before significant price changes occur.
#### **3. Momentum Analysis:**
- **Objective:**
- To gauge the strength and direction of market momentum for making informed trading decisions.
- **How to Use:**
- Analyze the Histogram to assess momentum strength. Positive and expanding histogram bars indicate increasing bullish momentum, while negative and expanding bars suggest increasing bearish momentum.
- Use momentum insights to validate or question existing trading positions and strategies.
- **Advantages:**
- Offers valuable information about the market's momentum, helping traders confirm the validity of trends and trading signals.
### **Customization and Flexibility:**
The **Uptrick: DPO Signal & Zone Indicator** offers extensive customization options to accommodate diverse trading preferences and market conditions:
- **SMA Length and Signal Line Length:**
- Adjust the `smaLength` and `signalLength` parameters to control the sensitivity and responsiveness of the DPO and Signal Line. Shorter lengths make the indicator more responsive to price changes, while longer lengths provide smoother, less volatile signals.
- **Alert Levels:**
- Modify `alertLevel1` and `alertLevel2` to fit varying market conditions and volatility. Setting these levels appropriately helps tailor the indicator to different asset classes and trading strategies.
- **Color and Shape Customization:**
- Customize the colors and sizes of buy/sell signals, histogram bars, and alert levels to enhance visual clarity and align with personal preferences. This customization helps ensure that the indicator integrates seamlessly with a trader's charting setup.
### **Conclusion:**
The **Uptrick: DPO Signal & Zone Indicator** is a multifaceted analytical tool that combines the power of the Detrended Price Oscillator with customizable visual elements and alert levels to deliver a comprehensive approach to market analysis. By offering insights into momentum strength, trend direction, and potential reversal points, this indicator equips traders with valuable information to make informed decisions and enhance their trading strategies. Its flexibility and customization options ensure that it can be adapted to various trading styles and market conditions, making it a versatile addition to any trader's toolkit.
