Patrick [TFO]This Patrick indicator was made for the 1 year anniversary of my Spongebob indicator, which was an experiment in using the polyline features of Pine Script to draw complex subjects. This indicator was made with the same methodology, with some helper functions to make things a bit easier on myself. It's sole purpose is to display a picture of Patrick Star on your chart, particularly the "I have $3" meme.
The initial Spongebob indicator included more than 1300 lines of code, as there were several more shapes to account for compared to Patrick, however it was done rather inefficiently. I essentially used an anchor point for each "layer" or shape (eye, nose, mouth, etc.), and drew from that point. This resulted in a ton of trial and error as I had to be very careful about the anchor points for each and every layer, and then draw around that point. In this indicator, however, I gave myself a frame to work with by specifying fixed bounds that you'll see in the code: LEFT, RIGHT, TOP, and BOTTOM.
var y_size = 4
atr = ta.atr(50)
LEFT = bar_index + 10
RIGHT = LEFT + 200
TOP = open + atr * y_size
BOTTOM = open - atr * y_size
You may notice that the top and bottom scale with the atr, or Average True Range to account for varying price fluctuations on different assets.
With these limits established, I could write some simple functions to translate my coordinates, using a range of 0-100 to describe how far the X coordinates should be from left to right, where left is 0 and right is 100; and likewise how far the Y coordinates should be from bottom to top, where bottom is 0 and top is 100.
X(float P) =>
result = LEFT + math.floor((RIGHT - LEFT)*P/100)
Y(float P) =>
result = BOTTOM + (TOP - BOTTOM)*P/100
With these functions, I could then start drawing points much simpler, with respect to the overall frame of the picture. If I wanted a point in the dead center of the frame, I would choose X(50), Y(50) for example.
At this point, the process just became tediously drawing each layer of my reference picture, including but not limited to Patrick's body, arm, mouth, eyes, eyebrows, etc. I've attached the reference picture here (left), without the text enabled.
As tedious as this was to create, it was done much more efficiently than Spongebob, and the ideas used here will make it much easier to draw more complex subjects in the future.
Cari dalam skrip untuk "马斯克+100万"
[ AlgoChart ] - Pearson Index CorrelationCorrelation Indicator (Pearson Index)
The correlation indicator measures the strength and direction of the relationship between two financial assets using the Pearson Index.
Correlation values range from +100 to -100, where:
+100 indicates perfect positive correlation, meaning the two assets tend to move in the same direction.
-100 indicates perfect negative correlation, where the two assets move in opposite directions.
The neutral zone ranges from +25% to -25%, suggesting that the asset movements are independent, with no clear correlation between them.
Interpreting Correlation Levels:
Correlation above +75%: The two assets tend to move similarly and in the same direction. This may indicate a risk of overexposure if both assets are traded in the same direction, as their movements will be very similar, increasing the likelihood of double losses or gains.
Correlation below -75%: The two assets tend to move similarly but in opposite directions. This correlation level can be useful for strategies that benefit from opposing movements between assets, such as trading pairs with inverse dynamics.
Practical Use of the Indicator:
Risk management: Use the indicator to monitor asset correlations before opening positions. High correlation may indicate you are duplicating exposure, as two highly correlated assets tend to move similarly. This helps avoid excessive risk and improves portfolio diversification.
Statistical Arbitrage: During moments of temporary decorrelation between two assets, the indicator can be used for statistical arbitrage strategies. In such cases, you can take advantage of the divergence by opening positions and closing them when the correlation returns to higher or positive levels, thus potentially profiting from the reconvergence of movements.
While the correlation indicator provides valuable insights into asset relationships, it is most effective when used in conjunction with other concepts and tools. On its own, it may offer limited relevance in trading decisions.
Uptrick: RSI Histogram
1. **Introduction to the RSI and Moving Averages**
2. **Detailed Breakdown of the Uptrick: RSI Histogram**
3. **Calculation and Formula**
4. **Visual Representation**
5. **Customization and User Settings**
6. **Trading Strategies and Applications**
7. **Risk Management**
8. **Case Studies and Examples**
9. **Comparison with Other Indicators**
10. **Advanced Usage and Tips**
---
## 1. Introduction to the RSI and Moving Averages
### **1.1 Relative Strength Index (RSI)**
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder and introduced in his 1978 book "New Concepts in Technical Trading Systems." It is widely used in technical analysis to measure the speed and change of price movements.
**Purpose of RSI:**
- **Identify Overbought/Oversold Conditions:** RSI values range from 0 to 100. Traditionally, values above 70 are considered overbought, while values below 30 are considered oversold. These thresholds help traders identify potential reversal points in the market.
- **Trend Strength Measurement:** RSI also indicates the strength of a trend. High RSI values suggest strong bullish momentum, while low values indicate bearish momentum.
**Calculation of RSI:**
1. **Calculate the Average Gain and Loss:** Over a specified period (e.g., 14 days), calculate the average gain and loss.
2. **Compute the Relative Strength (RS):** RS is the ratio of average gain to average loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS))
### **1.2 Moving Averages (MA)**
Moving Averages are used to smooth out price data and identify trends by filtering out short-term fluctuations. Two common types are:
**Simple Moving Average (SMA):** The average of prices over a specified number of periods.
**Exponential Moving Average (EMA):** A type of moving average that gives more weight to recent prices, making it more responsive to recent price changes.
**Smoothed Moving Average (SMA):** Used to reduce the impact of volatility and provide a clearer view of the underlying trend. The RMA, or Running Moving Average, used in the USH script is similar to an EMA but based on the average of RSI values.
## 2. Detailed Breakdown of the Uptrick: RSI Histogram
### **2.1 Indicator Overview**
The Uptrick: RSI Histogram (USH) is a technical analysis tool that combines the RSI with a moving average to create a histogram that reflects momentum and trend strength.
**Key Components:**
- **RSI Calculation:** Determines the relative strength of price movements.
- **Moving Average Application:** Smooths the RSI values to provide a clearer trend indication.
- **Histogram Plotting:** Visualizes the deviation of the smoothed RSI from a neutral level.
### **2.2 Indicator Purpose**
The primary purpose of the USH is to provide a clear visual representation of the market's momentum and trend strength. It helps traders identify:
- **Bullish and Bearish Trends:** By showing how far the smoothed RSI is from the neutral 50 level.
- **Potential Reversal Points:** By highlighting changes in momentum.
### **2.3 Indicator Design**
**RSI Moving Average (RSI MA):** The RSI MA is a smoothed version of the RSI, calculated using a running moving average. This smooths out short-term fluctuations and provides a clearer indication of the underlying trend.
**Histogram Calculation:**
- **Neutral Level:** The histogram is plotted relative to the neutral level of 50. This level represents a balanced market where neither bulls nor bears have dominance.
- **Histogram Values:** The histogram bars show the difference between the RSI MA and the neutral level. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
## 3. Calculation and Formula
### **3.1 RSI Calculation**
The RSI calculation involves:
1. **Average Gain and Loss:** Calculated over the specified length (e.g., 14 periods).
2. **Relative Strength (RS):** RS = Average Gain / Average Loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS)).
### **3.2 Moving Average Calculation**
For the USH indicator, the RSI is smoothed using a running moving average (RMA). The RMA formula is similar to that of the EMA but is based on averaging RSI values over the specified length.
### **3.3 Histogram Calculation**
The histogram value is calculated as:
- **Histogram Value = RSI MA - 50**
**Plotting the Histogram:**
- **Positive Histogram Values:** Indicate that the RSI MA is above the neutral level, suggesting bullish momentum.
- **Negative Histogram Values:** Indicate that the RSI MA is below the neutral level, suggesting bearish momentum.
## 4. Visual Representation
### **4.1 Histogram Bars**
The histogram is plotted as bars on the chart:
- **Bullish Bars:** Colored green when the RSI MA is above 50.
- **Bearish Bars:** Colored red when the RSI MA is below 50.
### **4.2 Customization Options**
Traders can customize:
- **RSI Length:** Adjust the length of the RSI calculation to match their trading style.
- **Bull and Bear Colors:** Choose colors for histogram bars to enhance visual clarity.
### **4.3 Interpretation**
**Bullish Signal:** A histogram bar that moves from red to green indicates a potential shift to a bullish trend.
**Bearish Signal:** A histogram bar that moves from green to red indicates a potential shift to a bearish trend.
## 5. Customization and User Settings
### **5.1 Adjusting RSI Length**
The length parameter determines the number of periods over which the RSI is calculated and smoothed. Shorter lengths make the RSI more sensitive to price changes, while longer lengths provide a smoother view of trends.
### **5.2 Color Settings**
Traders can adjust:
- **Bull Color:** Color of histogram bars indicating bullish momentum.
- **Bear Color:** Color of histogram bars indicating bearish momentum.
**Customization Benefits:**
- **Visual Clarity:** Traders can choose colors that stand out against their chart’s background.
- **Personal Preference:** Adjust settings to match individual trading styles and preferences.
## 6. Trading Strategies and Applications
### **6.1 Trend Following**
**Identifying Entry Points:**
- **Bullish Entry:** When the histogram changes from red to green, it signals a potential entry point for long positions.
- **Bearish Entry:** When the histogram changes from green to red, it signals a potential entry point for short positions.
**Trend Confirmation:** The histogram helps confirm the strength of a trend. Strong, consistent green bars indicate robust bullish momentum, while strong, consistent red bars indicate robust bearish momentum.
### **6.2 Swing Trading**
**Momentum Analysis:**
- **Entry Signals:** Look for significant shifts in the histogram to time entries. A shift from bearish to bullish (red to green) indicates potential for upward movement.
- **Exit Signals:** A shift from bullish to bearish (green to red) suggests a potential weakening of the trend, signaling an exit or reversal point.
### **6.3 Range Trading**
**Market Conditions:**
- **Consolidation:** The histogram close to zero suggests a range-bound market. Traders can use this information to identify support and resistance levels.
- **Breakout Potential:** A significant move away from the neutral level may indicate a potential breakout from the range.
### **6.4 Risk Management**
**Stop-Loss Placement:**
- **Bullish Positions:** Place stop-loss orders below recent support levels when the histogram is green.
- **Bearish Positions:** Place stop-loss orders above recent resistance levels when the histogram is red.
**Position Sizing:** Adjust position sizes based on the strength of the histogram signals. Strong trends (indicated by larger histogram bars) may warrant larger positions, while weaker signals suggest smaller positions.
## 7. Risk Management
### **7.1 Importance of Risk Management**
Effective risk management is crucial for long-term trading success. It involves protecting capital, managing losses, and optimizing trade setups.
### **7.2 Using USH for Risk Management**
**Stop-Loss and Take-Profit Levels:**
- **Stop-Loss Orders:** Use the histogram to set stop-loss levels based on trend strength. For instance, place stops below support levels in bullish trends and above resistance levels in bearish trends.
- **Take-Profit Targets:** Adjust take-profit levels based on histogram changes. For example, lock in profits as the histogram starts to shift from green to red.
**Position Sizing:**
- **Trend Strength:** Scale position sizes based on the strength of histogram signals. Larger histogram bars indicate stronger trends, which may justify larger positions.
- **Volatility:** Consider market volatility and adjust position sizes to mitigate risk.
## 8. Case Studies and Examples
### **8.1 Example 1: Bullish Trend**
**Scenario:** A trader notices a transition from red to green histogram bars.
**Analysis:**
- **Entry Point:** The transition indicates a potential bullish trend. The trader decides to enter a long position.
- **Stop-Loss:** Set stop-loss below recent support levels.
- **Take-Profit:** Consider taking profits as the histogram moves back towards zero or turns red.
**Outcome:** The bullish trend continues, and the histogram remains green, providing a profitable trade setup.
### **8.2 Example 2: Bearish Trend**
**Scenario:** A trader observes a transition from green to red histogram bars.
**Analysis:**
- **Entry Point:** The transition suggests a potential
bearish trend. The trader decides to enter a short position.
- **Stop-Loss:** Set stop-loss above recent resistance levels.
- **Take-Profit:** Consider taking profits as the histogram approaches zero or shifts to green.
**Outcome:** The bearish trend continues, and the histogram remains red, resulting in a successful trade.
## 9. Comparison with Other Indicators
### **9.1 RSI vs. USH**
**RSI:** Measures momentum and identifies overbought/oversold conditions.
**USH:** Builds on RSI by incorporating a moving average and histogram to provide a clearer view of trend strength and momentum.
### **9.2 RSI vs. MACD**
**MACD (Moving Average Convergence Divergence):** A trend-following momentum indicator that uses moving averages to identify changes in trend direction.
**Comparison:**
- **USH:** Provides a smoothed RSI perspective and visual histogram for trend strength.
- **MACD:** Offers signals based on the convergence and divergence of moving averages.
### **9.3 RSI vs. Stochastic Oscillator**
**Stochastic Oscillator:** Measures the level of the closing price relative to the high-low range over a specified period.
**Comparison:**
- **USH:** Focuses on smoothed RSI values and histogram representation.
- **Stochastic Oscillator:** Provides overbought/oversold signals and potential reversals based on price levels.
## 10. Advanced Usage and Tips
### **10.1 Combining Indicators**
**Multi-Indicator Strategies:** Combine the USH with other technical indicators (e.g., Moving Averages, Bollinger Bands) for a comprehensive trading strategy.
**Confirmation Signals:** Use the USH to confirm signals from other indicators. For instance, a bullish histogram combined with a moving average crossover may provide a stronger buy signal.
### **10.2 Customization Tips**
**Adjust RSI Length:** Experiment with different RSI lengths to match various market conditions and trading styles.
**Color Preferences:** Choose histogram colors that enhance visibility and align with personal preferences.
### **10.3 Continuous Learning**
**Backtesting:** Regularly backtest the USH with historical data to refine strategies and improve accuracy.
**Education:** Stay updated with trading education and adapt strategies based on market changes and personal experiences.
Advanced Keltner Channel/Oscillator [MyTradingCoder]This indicator combines a traditional Keltner Channel overlay with an oscillator, providing a comprehensive view of price action, trend, and momentum. The core of this indicator is its advanced ATR calculation, which uses statistical methods to provide a more robust measure of volatility.
Starting with the overlay component, the center line is created using a biquad low-pass filter applied to the chosen price source. This provides a smoother representation of price than a simple moving average. The upper and lower channel lines are then calculated using the statistically derived ATR, with an additional set of mid-lines between the center and outer lines. This creates a more nuanced view of price action within the channel.
The color coding of the center line provides an immediate visual cue of the current price momentum. As the price moves up relative to the ATR, the line shifts towards the bullish color, and vice versa for downward moves. This color gradient allows for quick assessment of the current market sentiment.
The oscillator component transforms the channel into a different perspective. It takes the price's position within the channel and maps it to either a normalized -100 to +100 scale or displays it in price units, depending on your settings. This oscillator essentially shows where the current price is in relation to the channel boundaries.
The oscillator includes two key lines: the main oscillator line and a signal line. The main line represents the current position within the channel, smoothed by an exponential moving average (EMA). The signal line is a further smoothed version of the oscillator line. The interaction between these two lines can provide trading signals, similar to how MACD is often used.
When the oscillator line crosses above the signal line, it might indicate bullish momentum, especially if this occurs in the lower half of the oscillator range. Conversely, the oscillator line crossing below the signal line could signal bearish momentum, particularly if it happens in the upper half of the range.
The oscillator's position relative to its own range is also informative. Values near the top of the range (close to 100 if normalized) suggest that price is near the upper Keltner Channel band, indicating potential overbought conditions. Values near the bottom of the range (close to -100 if normalized) suggest proximity to the lower band, potentially indicating oversold conditions.
One of the strengths of this indicator is how the overlay and oscillator work together. For example, if the price is touching the upper band on the overlay, you'd see the oscillator at or near its maximum value. This confluence of signals can provide stronger evidence of overbought conditions. Similarly, the oscillator hitting extremes can draw your attention to price action at the channel boundaries on the overlay.
The mid-lines on both the overlay and oscillator provide additional nuance. On the overlay, price action between the mid-line and outer line might suggest strong but not extreme momentum. On the oscillator, this would correspond to readings in the outer quartiles of the range.
The customizable visual settings allow you to adjust the indicator to your preferences. The glow effects and color coding can make it easier to quickly interpret the current market conditions at a glance.
Overlay Component:
The overlay displays Keltner Channel bands dynamically adapting to market conditions, providing clear visual cues for potential trend reversals, breakouts, and overbought/oversold zones.
The center line is a biquad low-pass filter applied to the chosen price source.
Upper and lower channel lines are calculated using a statistically derived ATR.
Includes mid-lines between the center and outer channel lines.
Color-coded based on price movement relative to the ATR.
Oscillator Component:
The oscillator component complements the overlay, highlighting momentum and potential turning points.
Normalized values make it easy to compare across different assets and timeframes.
Signal line crossovers generate potential buy/sell signals.
Advanced ATR Calculation:
Uses a unique method to compute ATR, incorporating concepts like root mean square (RMS) and z-score clamping.
Provides both an average and mode-based ATR value.
Customizable Visual Settings:
Adjustable colors for bullish and bearish moves, oscillator lines, and channel components.
Options for line width, transparency, and glow effects.
Ability to display overlay, oscillator, or both simultaneously.
Flexible Parameters:
Customizable inputs for channel width multiplier, ATR period, smoothing factors, and oscillator settings.
Adjustable Q factor for the biquad filter.
Key Advantages:
Advanced ATR Calculation: Utilizes a statistical method to generate ATR, ensuring greater responsiveness and accuracy in volatile markets.
Overlay and Oscillator: Provides a comprehensive view of price action, combining trend and momentum analysis.
Customizable: Adjust settings to fine-tune the indicator to your specific needs and trading style.
Visually Appealing: Clear and concise design for easy interpretation.
The ATR (Average True Range) in this indicator is derived using a sophisticated statistical method that differs from the traditional ATR calculation. It begins by calculating the True Range (TR) as the difference between the high and low of each bar. Instead of a simple moving average, it computes the Root Mean Square (RMS) of the TR over the specified period, giving more weight to larger price movements. The indicator then calculates a Z-score by dividing the TR by the RMS, which standardizes the TR relative to recent volatility. This Z-score is clamped to a maximum value (10 in this case) to prevent extreme outliers from skewing the results, and then rounded to a specified number of decimal places (2 in this script).
These rounded Z-scores are collected in an array, keeping track of how many times each value occurs. From this array, two key values are derived: the mode, which is the most frequently occurring Z-score, and the average, which is the weighted average of all Z-scores. These values are then scaled back to price units by multiplying by the RMS.
Now, let's examine how these values are used in the indicator. For the Keltner Channel lines, the mid lines (top and bottom) use the mode of the ATR, representing the most common volatility state. The max lines (top and bottom) use the average of the ATR, incorporating all volatility states, including less common but larger moves. By using the mode for the mid lines and the average for the max lines, the indicator provides a nuanced view of volatility. The mid lines represent the "typical" market state, while the max lines account for less frequent but significant price movements.
For the color coding of the center line, the mode of the ATR is used to normalize the price movement. The script calculates the difference between the current price and the price 'degree' bars ago (default is 2), and then divides this difference by the mode of the ATR. The resulting value is passed through an arctangent function and scaled to a 0-1 range. This scaled value is used to create a color gradient between the bearish and bullish colors.
Using the mode of the ATR for this color coding ensures that the color changes are based on the most typical volatility state of the market. This means that the color will change more quickly in low volatility environments and more slowly in high volatility environments, providing a consistent visual representation of price momentum relative to current market conditions.
Using a good IIR (Infinite Impulse Response) low-pass filter, such as the biquad filter implemented in this indicator, offers significant advantages over simpler moving averages like the EMA (Exponential Moving Average) or other basic moving averages.
At its core, an EMA is indeed a simple, single-pole IIR filter, but it has limitations in terms of its frequency response and phase delay characteristics. The biquad filter, on the other hand, is a two-pole, two-zero filter that provides superior control over the frequency response curve. This allows for a much sharper cutoff between the passband and stopband, meaning it can more effectively separate the signal (in this case, the underlying price trend) from the noise (short-term price fluctuations).
The improved frequency response of a well-designed biquad filter means it can achieve a better balance between smoothness and responsiveness. While an EMA might need a longer period to sufficiently smooth out price noise, potentially leading to more lag, a biquad filter can achieve similar or better smoothing with less lag. This is crucial in financial markets where timely information is vital for making trading decisions.
Moreover, the biquad filter allows for independent control of the cutoff frequency and the Q factor. The Q factor, in particular, is a powerful parameter that affects the filter's resonance at the cutoff frequency. By adjusting the Q factor, users can fine-tune the filter's behavior to suit different market conditions or trading styles. This level of control is simply not available with basic moving averages.
Another advantage of the biquad filter is its superior phase response. In the context of financial data, this translates to more consistent lag across different frequency components of the price action. This can lead to more reliable signals, especially when it comes to identifying trend changes or price reversals.
The computational efficiency of biquad filters is also worth noting. Despite their more complex mathematical foundation, biquad filters can be implemented very efficiently, often requiring only a few operations per sample. This makes them suitable for real-time applications and high-frequency trading scenarios.
Furthermore, the use of a more sophisticated filter like the biquad can help in reducing false signals. The improved noise rejection capabilities mean that minor price fluctuations are less likely to cause unnecessary crossovers or indicator movements, potentially leading to fewer false breakouts or reversal signals.
In the specific context of a Keltner Channel, using a biquad filter for the center line can provide a more stable and reliable basis for the entire indicator. It can help in better defining the overall trend, which is crucial since the Keltner Channel is often used for trend-following strategies. The smoother, yet more responsive center line can lead to more accurate channel boundaries, potentially improving the reliability of overbought/oversold signals and breakout indications.
In conclusion, this advanced Keltner Channel indicator represents a significant evolution in technical analysis tools, combining the power of traditional Keltner Channels with modern statistical methods and signal processing techniques. By integrating a sophisticated ATR calculation, a biquad low-pass filter, and a complementary oscillator component, this indicator offers traders a comprehensive and nuanced view of market dynamics.
The indicator's strength lies in its ability to adapt to varying market conditions, providing clear visual cues for trend identification, momentum assessment, and potential reversal points. The use of statistically derived ATR values for channel construction and the implementation of a biquad filter for the center line result in a more responsive and accurate representation of price action compared to traditional methods.
Furthermore, the dual nature of this indicator – functioning as both an overlay and an oscillator – allows traders to simultaneously analyze price trends and momentum from different perspectives. This multifaceted approach can lead to more informed decision-making and potentially more reliable trading signals.
The high degree of customization available in the indicator's settings enables traders to fine-tune its performance to suit their specific trading styles and market preferences. From adjustable visual elements to flexible parameter inputs, users can optimize the indicator for various trading scenarios and time frames.
Ultimately, while no indicator can predict market movements with certainty, this advanced Keltner Channel provides traders with a powerful tool for market analysis. By offering a more sophisticated approach to measuring volatility, trend, and momentum, it equips traders with valuable insights to navigate the complex world of financial markets. As with any trading tool, it should be used in conjunction with other forms of analysis and within a well-defined risk management framework to maximize its potential benefits.
Trading Channel Index (TCI)Overview:
The Trading Channel Index (TCI) is a technical analysis tool designed to identify cyclical trends in financial markets by smoothing out price movements and reducing volatility compared to traditional oscillators, like the Commodity Channel Index (CCI). The TCI helps traders pinpoint overbought and oversold conditions, as well as gauge the strength and direction of market trends.
Calculation:
The TCI is calculated through a multi-step process:
Typical Price (Xt): The typical price is computed as the average of the high, low, and close prices for each bar:
Xt = (High + Low + Close) / 3
Exponential Average (Et): This step smooths the typical price over a specified number of bars (TCI Channel Length) using an exponential moving average (EMA). The smoothing factor alpha is derived from the channel length:
Et = alpha * Xt + (1 - alpha) * Et
Where alpha = 2 / (TCI Channel Length + 1).
Average Deviation (Dt): The average deviation measures how much the typical price deviates from the exponential average over time. This is also smoothed using the EMA:
Dt = alpha * abs(Et - Xt) + (1 - alpha) * Dt
Channel Index (CI): The Channel Index is calculated by normalizing the difference between the typical price and the exponential average by the average deviation:
CI = (Xt - Et) / (0.15 * Dt)
Trading Channel Index (TCI): Finally, the TCI is generated by applying additional smoothing to the Channel Index using another EMA over the specified number of bars (TCI Average Length). The smoothing factor beta is derived from the average length:
TCI = beta * CI + (1 - beta) * TCI
Indicator Variables:
TCI Channel Length:
- Description: This variable sets the number of historical bars used to calculate the Channel Index (CI). A shorter length results in a more sensitive CI that responds quickly to price changes, while a longer length produces a smoother and less volatile CI.
- Default Value: 21
TCI Average Length:
-Description: This variable determines the number of bars over which the Channel Index (CI) is smoothed to produce the TCI. A shorter length makes the TCI more responsive to recent price changes, whereas a longer length further smooths the TCI, reducing its sensitivity to short-term fluctuations.
-Default Value: 10
Usage:
Overbought and Oversold Conditions: The TCI often uses levels such as +100 and -100 to identify potential reversal points. When the TCI crosses above +100, it might indicate an overbought condition, signaling a potential sell. Conversely, when it crosses below -100, it could indicate an oversold condition, suggesting a potential buy.
Trend Identification: Sustained values above 0 typically indicate a bullish trend, while values below 0 suggest a bearish trend. The TCI's smoothness helps traders stay in trends longer by reducing the impact of short-term market noise.
Conclusion:
The Trading Channel Index (TCI) is a versatile and powerful tool for traders who wish to capture cyclical price movements with a reduced level of noise. By adjusting the TCI Channel Length and TCI Average Length, traders can tailor the indicator to suit different market conditions, making it applicable across various timeframes and asset classes.
Double Bottom and Top Hunter### Türkçe Açıklama:
Bu strateji, grafikte ikili dip ve ikili tepe formasyonlarını tespit ederek otomatik alım ve satım işlemleri gerçekleştirir. İkili dip, fiyatın belirli bir dönem içinde iki kez en düşük seviyeye ulaşması ile oluşur ve bu durumda strateji long (alım) işlemi açar. İkili tepe ise fiyatın belirli bir dönem içinde iki kez en yüksek seviyeye ulaşması ile oluşur ve bu durumda strateji short (satış) işlemi açar.
- **Dönem Uzunluğu ve Geriye Dönük Kontrol:** Strateji, varsayılan olarak 100 periyotluk bir zaman dilimini temel alır ve bu süre boyunca en düşük ve en yüksek fiyat seviyelerini belirler. Geriye dönük kontrol süresi de 100 periyot olarak ayarlanmıştır.
- **İşlem Açma Koşulları:** İkili dip tespit edildiğinde long pozisyon, ikili tepe tespit edildiğinde short pozisyon açılır.
- **İşlem Kapatma Koşulları:** İkili dipte, en yüksek seviyeye (HH) ulaşıldıktan sonra fiyatın daha düşük bir seviye (LL) yapması durumunda pozisyon kapanır. İkili tepede ise tam tersi bir durumda, pozisyon kapanır.
- **Zigzag Çizimi:** İkili dip ve tepe formasyonları, grafik üzerinde yeşil (dipler) ve kırmızı (tepeler) zigzag çizgileri ile gösterilir.
Bu strateji, özellikle 1, 3 ve 5 dakikalık kısa zaman dilimlerinde yüksek başarı oranına sahiptir ve piyasadaki kısa vadeli trend dönüşlerini yakalamada etkili bir araçtır.
### English Explanation:
This strategy automatically executes buy and sell orders by detecting double bottom and double top formations on the chart. A double bottom occurs when the price reaches a low level twice within a specific period, prompting the strategy to open a long (buy) position. Conversely, a double top forms when the price reaches a high level twice, leading the strategy to open a short (sell) position.
- **Period Length and Lookback Control:** By default, the strategy is based on a 100-period length, during which it identifies the lowest and highest price levels. The lookback control period is also set to 100 periods.
- **Entry Conditions:** A long position is opened when a double bottom is detected, while a short position is opened when a double top is identified.
- **Exit Conditions:** In the case of a double bottom, the position is closed after the price reaches a higher high (HH) and then makes a lower low (LL). For a double top, the opposite occurs before closing the position.
- **Zigzag Plotting:** The double bottom and top formations are visually represented on the chart with green (bottoms) and red (tops) zigzag lines.
This strategy is particularly successful in short timeframes such as 1, 3, and 5 minutes and is an effective tool for capturing short-term trend reversals in the market.
Prometheus Black-Scholes Option PricesThe Black-Scholes Model is an option pricing model developed my Fischer Black and Myron Scholes in 1973 at MIT. This is regarded as the most accurate pricing model and is still used today all over the world. This script is a simulated Black-Scholes model pricing model, I will get into why I say simulated.
What is an option?
An option is the right, but not the obligation, to buy or sell 100 shares of a certain stock, for calls or puts respective, at a certain price, on a certain date (assuming European style options, American options can be exercised early). The reason these agreements, these contracts exist is to provide traders with leverage. Buying 1 contract to represent 100 shares of the underlying, more often than not, at a cheaper price. That is why the price of the option, the premium , is a small number. If an option costs $1.00 we pay $100.00 for it because 100 shares * 1 dollar per share = 100 dollars for all the shares. When a trader purchases a call on stock XYZ with a strike of $105 while XYZ stock is trading at $100, if XYZ stock moves up to $110 dollars before expiration the option has $5 of intrinsic value. You have the right to buy something at $105 when it is trading at $110. That agreement is way more valuable now, as a result the options premium would increase. That is a quick overview about how options are traded, let's get into calculating them.
Inputs for the Black-Scholes model
To calculate the price of an option we need to know 5 things:
Current Price of the asset
Strike Price of the option
Time Till Expiration
Risk-Free Interest rate
Volatility
The price of a European call option 𝐶 is given by:
𝐶 = 𝑆0 * Φ(𝑑1) − 𝐾 * 𝑒^(−𝑟 * 𝑇) * Φ(𝑑2)
where:
𝑆0 is the current price of the underlying asset.
𝐾 is the strike price of the option.
𝑟 is the risk-free interest rate.
𝑇 is the time to expiration.
Φ is the cumulative distribution function of the standard normal distribution.
𝑑1 and 𝑑2 are calculated as:
𝑑1 = (ln(𝑆0 / 𝐾) + (𝑟 + (𝜎^2 / 2)) * 𝑇) / (𝜎 * sqrt(𝑇))
𝑑2= 𝑑1 - (𝜎 * sqrt(𝑇))
𝜎 is the volatility of the underlying asset.
The price of a European put option 𝑃 is given by:
𝑃 = 𝐾 * 𝑒^(−𝑟 * 𝑇) * Φ(−𝑑2) − 𝑆0 * Φ(−𝑑1)
where 𝑑1 and 𝑑2 are as defined above.
Key Assumptions of the Black-Scholes Model
The price of the underlying asset follows a lognormal distribution.
There are no transaction costs or taxes.
The risk-free interest rate and volatility of the underlying asset are constant.
The underlying asset does not pay dividends during the life of the option.
The markets are efficient, meaning that all known information is already reflected in the prices.
Options can only be exercised at expiration (European-style options).
Understanding the Script
Here I have arrows pointing to specific spots on the table. They point to Historical Volatility and Inputted DTE . Inputted DTE is a value the user may input to calculate premium for options that expire in that many days. Historical Volatility , is the value calculated by this code.
length = 252 // One year of trading days
hv = ta.stdev(math.log(close / close ), length) * math.sqrt(365)
And then made daily like the Black-Scholes model needs from this step in the code.
hv_daily = request.security(syminfo.tickerid, "1D", hv)
The user has the option to input their own volatility to the Script. I will get into why that may be advantageous in a moment. If the user chooses to do so the Script will change which value it is using as so.
hv_in_use = which_sig == false ? hv_daily : sig
There is a lot going on in this image but bare with me, it will all make sense by the end. The column to the far left of both the green and maroon colored columns represent the strike price of the contract, if the numbers are white that means the contract is out of the money, gray means in the money. If you remember from the calculation this represents the price to buy or sell shares at, for calls or puts respective. The column second from the left shows a value for Simulated Market Price . This is a necessary part of this script so we can show changes in implied volatility. See, when we go to our brokerages and look at options prices, sure the price was calculated by a pricing model, but that is rarely the true price of the model. Market participant sentiment affects this value as their estimates for future volatility, Implied Volatility changes.
For example, if a call option is supposed to be worth $1.00 from the pricing model, however everyone is bullish on the stock and wants to buy calls, the premium may go to $1.20 from $1.00 because participants juice up the Implied Volatility . Higher Implied Volatility generally means higher premium, given enough time to expiration. Buying an option at $0.80 when it should be worth $1.00 due to changes in sentiment is a big part of the Quant Trading industry.
Of course I don't have access to an actual exchange so get prices, so I modeled participant decisions by adding or subtracting a small random value on the "perfect premium" from the Black-Scholes model, and solving for implied volatility using the Newton-Raphson method.
It is like when we have speed = distance / time if we know speed and time , we can solve for distance .
This is what models the changing Implied Volatility in the table. The other column in the table, 3rd from the left, is the Black-Scholes model price without the changes of a random number. Finally, the 4th column from the left is that Implied Volatility value we calculated with the modified option price.
More on Implied Volatility
Implied Volatility represents the future expected volatility of an asset. As it is the value in the future it is not know like Historical Volatility, only projected. We provide the user with the option to enter their own Implied Volatility to start with for better modeling of options close to expiration. If you want to model options 1 day from expiration you will probably have to enter a higher Implied Volatility so that way the prices will be higher. Since the underlying is so close to expiration they are traded so much and traders manipulate their Implied Volatility , increasing their value. Be safe while trading these!
Thank you all for clicking on my indicator and reading this description! Happy coding, Happy trading, Be safe!
Good reference: www.investopedia.com
Smart Money Concepts by WeloTradesThe "Smart Money Concepts by WeloTrades" indicator is designed to offer traders a comprehensive tool that integrates multiple advanced features to aid in market analysis. By combining order blocks, liquidity levels, fair value gaps, trendlines, and market structure analysis, the indicator provides a holistic approach to understanding market dynamics and making informed trading decisions.
Components and Their Integration:
Order Blocks and Breaker Blocks Detection
Functionality: Order blocks represent areas where significant buying or selling occurred, creating potential support or resistance zones. Breaker blocks signal potential reversals.
Integration: By detecting and visualizing these blocks, the indicator helps traders identify key levels where price might react, aiding in entry and exit decisions. The customizable settings allow traders to adjust the visibility and parameters to suit their specific trading strategy.
Liquidity Levels Analysis
Functionality: Liquidity levels indicate zones where significant price movements can occur due to the presence of large orders. These are areas where smart money might be executing trades.
Integration: By tracking these high-probability liquidity areas, traders can anticipate potential price movements. Customizable display limits and mitigation strategies ensure that the information is tailored to the trader’s needs, providing precise and actionable insights.
Fair Value Gaps (FVG)
Functionality: Fair value gaps highlight areas where there is an imbalance between buyers and sellers. These gaps often represent potential trading opportunities.
Integration: The ability to identify and analyze FVGs helps traders spot potential entries based on market inefficiencies. The touch and break detection functionalities provide further refinement, enhancing the precision of trading signals.
Trendlines
Functionality: Trendlines help in identifying the direction of the market and potential reversal points. The additional trendline adds a layer of confirmation for breaks or retests.
Integration: Automatically drawn trendlines assist traders in visualizing market trends and making decisions about potential entries and exits. The additional trendline for stronger confirmation reduces the risk of false signals, providing more reliable trading opportunities.
Market Structure Analysis
Functionality: Understanding market structure is crucial for identifying key support and resistance levels and overall market dynamics. This component displays internal, external, and composite market structures.
Integration: By automatically highlighting shifts in market structure, the indicator helps traders recognize important levels and potential changes in market direction. This analysis is critical for strategic planning and execution in trading.
Customizable Alerts
Functionality: Alerts ensure that traders do not miss significant market events, such as the formation or breach of order blocks, liquidity levels, and trendline interactions.
Integration: Customizable alerts enhance the user experience by providing timely notifications of key events. This feature ensures that traders can act quickly and efficiently, leveraging the insights provided by the indicator.
Interactive Visualization
Functionality: Customizable visual aspects of the indicator allow traders to tailor the display to their preferences and trading style.
Integration: This feature enhances user engagement and usability, making it easier for traders to interpret the data and make informed decisions. Personalization options like colors, styles, and display formats improve the overall effectiveness of the indicator.
How Components Work Together
Comprehensive Market Analysis
Each component of the indicator addresses a different aspect of market analysis. Order blocks and liquidity levels highlight potential support and resistance zones, while fair value gaps and trendlines provide additional context for potential entries and exits. Market structure analysis ties everything together by offering a broad view of market dynamics.
Synergistic Insights
The integration of multiple features allows for cross-validation of trading signals. For instance, an order block coinciding with a high-probability liquidity level and a fair value gap can provide a stronger signal than any of these features alone. This synergy enhances the reliability of the insights and trading signals generated by the indicator.
Enhanced Decision Making
By combining these advanced features into a single tool, traders are equipped with a powerful resource for making informed decisions. The customizable alerts and interactive visualization further support this by ensuring that traders can act quickly on the insights provided.
Order Blocks ( OB) & Breaker Blocks (BB) Visuals:
📝 OB Input Settings
📊 Timeframe #1
TF #1🕑: Enable or disable Timeframe 1.
What it is: A boolean input to toggle the use of the first timeframe.
What it does: Enables or disables Timeframe 1 for the OB settings.
How to use it: Check or uncheck the box to enable or disable.
📊 Timeframe 1 Selection
Timeframe #1🕑: Select the timeframe for Timeframe 1.
What it is: A dropdown to select the desired timeframe.
What it does: Sets the timeframe for Timeframe 1.
How to use it: Choose a timeframe from the dropdown list.
📊 Timeframe #2
TF #2🕑: Enable or disable Timeframe 2.
What it is: A boolean input to toggle the use of the second timeframe.
What it does: Enables or disables Timeframe 2 for the OB settings.
How to use it: Check or uncheck the box to enable or disable.
📊 Timeframe 2 Selection
Timeframe #2🕑: Select the timeframe for Timeframe 2.
What it is: A dropdown to select the desired timeframe.
What it does: Sets the timeframe for Timeframe 2.
How to use it: Choose a timeframe from the dropdown list.
Additional Info: Higher TF Chart & Lower TF Setting / Lower TF Chart & Higher TF Setting.
📏 Show OBs
OB (Length)📏: Toggle the display of Order Blocks.
What it is: A boolean input to enable or disable the display of Order Blocks.
What it does: Shows or hides Order Blocks based on the selected swing length.
How to use it: Check or uncheck the box to enable or disable.
📏 Swing Length Option
Swing Length Option: Select the swing length option.
What it is: A dropdown to choose between SHORT, MID, LONG, or CUSTOM.
What it does: Sets the length of swings for Order Blocks.
How to use it: Choose an option from the dropdown.
Additional Info: Default lengths are SHORT=10, MID=28, LONG=50.
🔧 Custom Swing Length
🔧custom: Specify a custom swing length.
What it is: An integer input for setting a custom swing length.
What it does: Overrides the default swing lengths if set to CUSTOM.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
📛 Show BBs
BB (Method)📛: Toggle the display of Breaker Blocks.
What it is: A boolean input to enable or disable the display of Breaker Blocks.
What it does: Shows or hides Breaker Blocks.
How to use it: Check or uncheck the box to enable or disable.
📛 OB End Method
OB End Method: Select the method for determining the end of a Breaker Block.
What it is: A dropdown to choose between Wick and Close.
What it does: Sets the criteria for when a Breaker Block is considered mitigated.
How to use it: Choose an option from the dropdown.
Additional Info: Wicks: OB is mitigated when the price wicks through the OB Level. Close: OB is mitigated when the closing price is within the OB Level.
🔍 Max Bullish Zones
🔍Max Bullish: Set the maximum number of Bullish Order Blocks to display.
What it is: A dropdown to select the maximum number of Bullish Order Blocks.
What it does: Limits the number of Bullish Order Blocks shown on the chart.
How to use it: Choose a value from the dropdown (1-10).
🔍 Max Bearish Zones
🔍Max Bearish: Set the maximum number of Bearish Order Blocks to display.
What it is: A dropdown to select the maximum number of Bearish Order Blocks.
What it does: Limits the number of Bearish Order Blocks shown on the chart.
How to use it: Choose a value from the dropdown (1-10).
🟩 Bullish OB Color
Bullish OB Color: Set the color for Bullish Order Blocks.
What it is: A color picker to set the color of Bullish Order Blocks.
What it does: Changes the color of Bullish Order Blocks on the chart.
How to use it: Select a color from the color picker.
🟥 Bearish OB Color
Bearish OB Color: Set the color for Bearish Order Blocks.
What it is: A color picker to set the color of Bearish Order Blocks.
What it does: Changes the color of Bearish Order Blocks on the chart.
How to use it: Select a color from the color picker.
🔧 OB & BB Range
↔ OB & BB Range: Select the range option for OB and BB.
What it is: A dropdown to choose between RANGE and CUSTOM.
What it does: Sets how far the OB or BB should extend.
How to use it: Choose an option from the dropdown.
Additional Info: RANGE = Current price, CUSTOM = Adjustable Range.
🔧 Custom OB & BB Range
🔧Custom: Specify a custom range for OB and BB.
What it is: An integer input for setting a custom range.
What it does: Defines how far the OB or BB should go, based on a custom value.
How to use it: Enter a custom integer value (range: 1000-500000).
💬 Text Options
💬Text Options: Set text size and color for OB and BB.
What it is: A dropdown to select text size and a color picker to choose text color.
What it does: Changes the size and color of the text displayed for OB and BB.
How to use it: Select a size from the dropdown and a color from the color picker.
💬 Show Timeframe OB
Text: Toggle to display the timeframe of OB.
What it is: A boolean input to show or hide the timeframe text for OB.
What it does: Displays the timeframe information for Order Blocks on the chart.
How to use it: Check or uncheck the box to enable or disable.
💬 Show Volume
Volume: Toggle to display the volume of OB.
What it is: A boolean input to show or hide the volume information for Order Blocks.
What it does: Displays the volume information for Order Blocks on the chart.
How to use it: Check or uncheck the box to enable or disable.
Additional Info:
What it represents: The volume displayed represents the total trading volume that occurred during the formation of the Order Block. This can indicate the level of participation or interest in that price level.
How it's calculated: The volume is the sum of all traded volumes within the candles that form the Order Block.
What it means: Higher volume at an Order Block level may suggest stronger support or resistance. It shows the amount of trading activity and can be an indicator of the potential strength or validity of the Order Block.
Why it's shown: To give traders an idea of the market participation and to help assess the strength of the Order Block.
💬 Show Percentage
%: Toggle to display the percentage of OB.
What it is: A boolean input to show or hide the percentage information for Order Blocks.
What it does: Displays the percentage information for Order Blocks on the chart.
How to use it: Check or uncheck the box to enable or disable.
Additional Info:
What it represents: The percentage displayed usually represents the proportion of price movement relative to the Order Block.
How it's calculated: This can be the percentage move from the start to the end of the Order Block or the retracement level that price has reached relative to the Order Block's range.
What it means: It helps traders understand the extent of price movement within the Order Block and can indicate the significance of the price level.
Why it's shown: To provide a clearer understanding of the price dynamics and the importance of the Order Block within the overall price movement.
Additional Information
Volume Example: If an Order Block forms over three candles with volumes of 100, 150, and 200, the total volume displayed for that Order Block would be 450.
Percentage Example: If the price moves from 100 to 110 within an Order Block, and the total range of the Order Block is from 100 to 120, the percentage shown might be 50% (since the price has moved halfway through the Order Block's range).
Liquidity Levels visuals:
📊 Liquidity Levels Input Settings
📊 Current Timeframe
TF #1🕑: Enable or disable the current timeframe.
What it is: A boolean input to toggle the use of the current timeframe.
What it does: Enables or disables the display of liquidity levels for the current timeframe.
How to use it: Check or uncheck the box to enable or disable.
📊 Higher Timeframe
Higher Timeframe: Select the higher timeframe for liquidity levels.
What it is: A dropdown to select the desired higher timeframe.
What it does: Sets the higher timeframe for liquidity levels.
How to use it: Choose a timeframe from the dropdown list.
📏 Liquidity Length Option
📏Liquidity Length: Select the length for liquidity levels.
What it is: A dropdown to choose between SHORT, MID, LONG, or CUSTOM.
What it does: Sets the length of swings for liquidity levels.
How to use it: Choose an option from the dropdown.
Additional Info: Default lengths are SHORT=10, MID=28, LONG=50.
🔧 Custom Liquidity Length
🔧custom: Specify a custom length for liquidity levels.
What it is: An integer input for setting a custom swing length.
What it does: Overrides the default liquidity lengths if set to CUSTOM.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
📛 Mitigation Method
📛Mitigation (Method): Select the method for determining the mitigation of liquidity levels.
What it is: A dropdown to choose between Close and Wick.
What it does: Sets the criteria for when a liquidity level is considered mitigated.
How to use it: Choose an option from the dropdown.
Additional Info:
Wick: Level is mitigated when the price wicks through the level.
Close: Level is mitigated when the closing price is within the level.
📛 Display Mitigated Levels
-: Select to display or hide mitigated levels.
What it is: A dropdown to choose between Remove and Show.
What it does: Displays or hides mitigated liquidity levels.
How to use it: Choose an option from the dropdown.
Additional Info:
Remove: Hide mitigated levels.
Show: Display mitigated levels.
🔍 Max Buy Side Liquidity
🔍Max Buy Side Liquidity: Set the maximum number of Buy Side Liquidity Levels to display.
What it is: An integer input to set the maximum number of Buy Side Liquidity Levels.
What it does: Limits the number of Buy Side Liquidity Levels shown on the chart.
How to use it: Enter a value between 0 and 50.
🟦 Buy Side Liquidity Color
Buy Side Liquidity Color: Set the color for Buy Side Liquidity Levels.
What it is: A color picker to set the color of Buy Side Liquidity Levels.
What it does: Changes the color of Buy Side Liquidity Levels on the chart.
How to use it: Select a color from the color picker.
Additional Info:
Tooltip: Set the maximum number of Buy Side Liquidity Levels to display. Default: 5, Min: 1, Max: 50.
If liquidity levels are not displayed as expected, try increasing the max count.
🔍 Max Sell Side Liquidity
🔍Max Sell Side Liquidity: Set the maximum number of Sell Side Liquidity Levels to display.
What it is: An integer input to set the maximum number of Sell Side Liquidity Levels.
What it does: Limits the number of Sell Side Liquidity Levels shown on the chart.
How to use it: Enter a value between 0 and 50.
🟥 Sell Side Liquidity Color
Sell Side Liquidity Color: Set the color for Sell Side Liquidity Levels.
What it is: A color picker to set the color of Sell Side Liquidity Levels.
What it does: Changes the color of Sell Side Liquidity Levels on the chart.
How to use it: Select a color from the color picker.
Additional Info:
Tooltip: Set the maximum number of Sell Side Liquidity Levels to display. Default: 5, Min: 1, Max: 50.
If liquidity levels are not displayed as expected, try increasing the max count.
✂ Box Style (Height)
✂ Box Style (↕): Set the box height style for liquidity levels.
What it is: A float input to set the height of the boxes.
What it does: Adjusts the height of the boxes displaying liquidity levels.
How to use it: Enter a value between -50 and 50.
Additional Info: Default value is -5.
📏 Box Length
b: Set the box length of liquidity levels.
What it is: An integer input to set the length of the boxes.
What it does: Adjusts the length of the boxes displaying liquidity levels.
How to use it: Enter a value between 0 and 500.
Additional Info: Default value is 20.
⏭ Extend Liquidity Levels
Extend ⏭: Toggle to extend liquidity levels beyond the current range.
What it is: A boolean input to enable or disable the extension of liquidity levels.
What it does: Extends liquidity levels beyond their default range.
How to use it: Check or uncheck the box to enable or disable.
Additional Info: Extend liquidity levels beyond the current range.
💬 Text Options
💬 Text Options: Set text size and color for liquidity levels.
What it is: A dropdown to select text size and a color picker to choose text color.
What it does: Changes the size and color of the text displayed for liquidity levels.
How to use it: Select a size from the dropdown and a color from the color picker.
💬 Show Text
Text: Toggle to display text for liquidity levels.
What it is: A boolean input to show or hide the text for liquidity levels.
What it does: Displays the text information for liquidity levels on the chart.
How to use it: Check or uncheck the box to enable or disable.
💬 Show Volume
Volume: Toggle to display the volume of liquidity levels.
What it is: A boolean input to show or hide the volume information for liquidity levels.
What it does: Displays the volume information for liquidity levels on the chart.
How to use it: Check or uncheck the box to enable or disable.
Additional Info:
What it represents: The volume displayed represents the total trading volume that occurred during the formation of the liquidity level. This can indicate the level of participation or interest in that price level.
How it's calculated: The volume is the sum of all traded volumes within the candles that form the liquidity level.
What it means: Higher volume at a liquidity level may suggest stronger support or resistance. It shows the amount of trading activity and can be an indicator of the potential strength or validity of the liquidity level.
Why it's shown: To give traders an idea of the market participation and to help assess the strength of the liquidity level.
💬 Show Percentage
%: Toggle to display the percentage of liquidity levels.
What it is: A boolean input to show or hide the percentage information for liquidity levels.
What it does: Displays the percentage information for liquidity levels on the chart.
How to use it: Check or uncheck the box to enable or disable.
Additional Info:
What it represents: The percentage displayed usually represents the proportion of price movement relative to the liquidity level.
How it's calculated: This can be the percentage move from the start to the end of the liquidity level or the retracement level that price has reached relative to the liquidity level's range.
What it means: It helps traders understand the extent of price movement within the liquidity level and can indicate the significance of the price level.
Why it's shown: To provide a clearer understanding of the price dynamics and the importance of the liquidity level within the overall price movement.
Fair Value Gaps visuals:
📊 Fair Value Gaps Input Settings
📊 Show FVG
TF #1🕑: Enable or disable Fair Value Gaps for Timeframe 1.
What it is: A boolean input to toggle the display of Fair Value Gaps.
What it does: Shows or hides Fair Value Gaps on the chart.
How to use it: Check or uncheck the box to enable or disable.
📊 Select Timeframe
Timeframe: Select the timeframe for Fair Value Gaps.
What it is: A dropdown to select the desired timeframe.
What it does: Sets the timeframe for Fair Value Gaps.
How to use it: Choose a timeframe from the dropdown list.
Additional Info: Higher TF Chart & Lower TF Setting or Lower TF Chart & Higher TF Setting.
📛 FVG Break Method
📛FVG Break (Method): Select the method for determining when an FVG is mitigated.
What it is: A dropdown to choose between Touch, Wicks, Close, or Average.
What it does: Sets the criteria for when a Fair Value Gap is considered mitigated.
How to use it: Choose an option from the dropdown.
Additional Info:
Touch: FVG is mitigated when the price touches the gap.
Wicks: FVG is mitigated when the price wicks through the gap.
Close: FVG is mitigated when the closing price is within the gap.
Average: FVG is mitigated when the average price (average of high and low) is within the gap.
📛 Show Mitigated FVG
show: Toggle to display mitigated FVGs.
What it is: A boolean input to show or hide mitigated Fair Value Gaps.
What it does: Displays or hides mitigated Fair Value Gaps.
How to use it: Check or uncheck the box to enable or disable.
📛 Fill FVG
Fill: Toggle to fill Fair Value Gaps.
What it is: A boolean input to fill the Fair Value Gaps with color.
What it does: Adds a color fill to the Fair Value Gaps.
How to use it: Check or uncheck the box to enable or disable.
📛 Shade FVG
Shade: Toggle to shade Fair Value Gaps.
What it is: A boolean input to shade the Fair Value Gaps.
What it does: Adds a shade effect to the Fair Value Gaps.
How to use it: Check or uncheck the box to enable or disable.
Additional Info: Select the method to break FVGs and toggle the visibility of FVG Breaks (fill FVG and/or shade FVG).
🔍 Max Bullish FVG
🔍Max Bullish FVG: Set the maximum number of Bullish Fair Value Gaps to display.
What it is: An integer input to set the maximum number of Bullish Fair Value Gaps.
What it does: Limits the number of Bullish Fair Value Gaps shown on the chart.
How to use it: Enter a value between 0 and 50.
🔍 Max Bearish FVG
🔍Max Bearish FVG: Set the maximum number of Bearish Fair Value Gaps to display.
What it is: An integer input to set the maximum number of Bearish Fair Value Gaps.
What it does: Limits the number of Bearish Fair Value Gaps shown on the chart.
How to use it: Enter a value between 0 and 50.
🟥 Bearish FVG Color
Bearish FVG Color: Set the color for Bearish Fair Value Gaps.
What it is: A color picker to set the color of Bearish Fair Value Gaps.
What it does: Changes the color of Bearish Fair Value Gaps on the chart.
How to use it: Select a color from the color picker.
Additional Info:
Tooltip: Set the maximum number of Bearish Fair Value Gaps to display. Default: 5, Min: 1, Max: 50.
If Fair Value Gaps are not displayed as expected, try increasing the max count.
🟦 Bullish FVG Color
Bullish FVG Color: Set the color for Bullish Fair Value Gaps.
What it is: A color picker to set the color of Bullish Fair Value Gaps.
What it does: Changes the color of Bullish Fair Value Gaps on the chart.
How to use it: Select a color from the color picker.
Additional Info:
Tooltip: Set the maximum number of Bullish Fair Value Gaps to display. Default: 5, Min: 1, Max: 50.
If Fair Value Gaps are not displayed as expected, try increasing the max count.
📏 FVG Range
↔ FVG Range: Set the range for Fair Value Gaps.
What it is: An integer input to set the range of the Fair Value Gaps.
What it does: Adjusts the range of the Fair Value Gaps displayed.
How to use it: Enter a value between 0 and 100.
Additional Info: Adjustable length only works when both RANGE & EXTEND display OFF. Range=current price, Extend=Full Range.
⏭ Extend FVG
Extend⏭: Toggle to extend Fair Value Gaps beyond the current range.
What it is: A boolean input to enable or disable the extension of Fair Value Gaps.
What it does: Extends Fair Value Gaps beyond their default range.
How to use it: Check or uncheck the box to enable or disable.
⏯ FVG Range
Range⏯: Toggle the range of Fair Value Gaps.
What it is: A boolean input to enable or disable the range display for Fair Value Gaps.
What it does: Sets the range of Fair Value Gaps displayed.
How to use it: Check or uncheck the box to enable or disable.
↕ Max Width
↕ Max Width: Set the maximum width of Fair Value Gaps.
What it is: A float input to set the maximum width of Fair Value Gaps.
What it does: Limits the width of Fair Value Gaps as a percentage of the price range.
How to use it: Enter a value between 0 and 5.0.
Additional Info: FVGs wider than this value will be ignored.
♻ Filter FVG
Filter FVG ♻: Toggle to filter out small Fair Value Gaps.
What it is: A boolean input to filter out small Fair Value Gaps.
What it does: Ignores Fair Value Gaps smaller than the specified max width.
How to use it: Check or uncheck the box to enable or disable.
➖ Mid Line Style
➖Mid Line Style: Select the style of the mid line for Fair Value Gaps.
What it is: A dropdown to choose between Solid, Dashed, or Dotted.
What it does: Sets the style of the mid line within Fair Value Gaps.
How to use it: Choose an option from the dropdown.
🎨 Mid Line Color
Mid Line Color: Set the color for the mid line within Fair Value Gaps.
What it is: A color picker to set the color of the mid line.
What it does: Changes the color of the mid line within Fair Value Gaps.
How to use it: Select a color from the color picker.
Additional Information
Mitigation Methods: Each method (Touch, Wicks, Close, Average) provides different criteria for when a Fair Value Gap is considered mitigated, helping traders to understand the dynamics of price movements within gaps.
Volume and Percentage: Displaying volume and percentage information for Fair Value Gaps helps traders gauge the strength and significance of these gaps in relation to trading activity and price movements.
Trendlines visuals:
📊 Trendlines Input Settings
📊 Show Trendlines
Trendlines & Trendlines Difference(%) ↕: Enable or disable trendlines and set the percentage difference from the first trendline.
What it is: A boolean input to toggle the display of trendlines.
What it does: Shows or hides trendlines on the chart and allows setting a percentage difference from the first trendline.
How to use it: Check or uncheck the box to enable or disable.
Additional Info: The percentage difference determines the distance of the second trendline from the first one.
📏 Trendline Length Option
📏Trendline Length: Select the length for trendlines.
What it is: A dropdown to choose between SHORT, MID, LONG, or CUSTOM.
What it does: Sets the length of trendlines.
How to use it: Choose an option from the dropdown.
Additional Info: Default lengths are SHORT=50, MID=100, LONG=200.
🔧 Custom Trendline Length
🔧custom: Specify a custom length for trendlines.
What it is: An integer input for setting a custom trendline length.
What it does: Overrides the default trendline lengths if set to CUSTOM.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
🔍 Max Bearish Trendlines
🔍Max Trendlines Bearish: Set the maximum number of bearish trendlines to display.
What it is: A dropdown to select the maximum number of bearish trendlines.
What it does: Limits the number of bearish trendlines shown on the chart.
How to use it: Choose a value from the dropdown (2-20).
🟩 Bearish Trendline Color
Bearish Trendline Color: Set the color for bearish trendlines.
What it is: A color picker to set the color of bearish trendlines.
What it does: Changes the color of bearish trendlines on the chart.
How to use it: Select a color from the color picker.
Additional Info: Adjust to control how many bearish trendlines are displayed.
🔍 Max Bullish Trendlines
🔍Max Trendlines Bullish: Set the maximum number of bullish trendlines to display.
What it is: A dropdown to select the maximum number of bullish trendlines.
What it does: Limits the number of bullish trendlines shown on the chart.
How to use it: Choose a value from the dropdown (2-20).
🟥 Bullish Trendline Color
Bullish Trendline Color: Set the color for bullish trendlines.
What it is: A color picker to set the color of bullish trendlines.
What it does: Changes the color of bullish trendlines on the chart.
How to use it: Select a color from the color picker.
Additional Info: Adjust to control how many bullish trendlines are displayed.
📐 Degrees Text
📐Degrees ° (💬 Size): Enable or disable degrees text and set its size and color.
What it is: A boolean input to show or hide the degrees text for trendlines.
What it does: Displays the degrees text for trendlines.
How to use it: Check or uncheck the box to enable or disable.
📏 Text Size for Degrees
Text Size: Set the text size for degrees on trendlines.
What it is: A dropdown to select the size of the degrees text.
What it does: Changes the size of the degrees text displayed for trendlines.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🎨 Degrees Text Color
Degrees Text Color: Set the color for the degrees text on trendlines.
What it is: A color picker to set the color of the degrees text.
What it does: Changes the color of the degrees text on the chart.
How to use it: Select a color from the color picker.
♻ Filter Degrees
♻ Filter Degrees °: Enable or disable angle filtering and set the angle range.
What it is: A boolean input to filter trendlines by their angle.
What it does: Shows only trendlines within a specified angle range.
How to use it: Check or uncheck the box to enable or disable.
Additional Info: Angles outside this range will be filtered out.
🔢 Angle Range
Angle Range: Set the angle range for filtering trendlines.
What it is: Two float inputs to set the minimum and maximum angle for trendlines.
What it does: Defines the range of angles for which trendlines will be shown.
How to use it: Enter values for the minimum and maximum angles.
➖ Line Style
➖Style #1 & #2: Select the style of the primary and secondary trendlines.
What it is: Two dropdowns to choose between Solid, Dashed, or Dotted for the trendlines.
What it does: Sets the style of the primary and secondary trendlines.
How to use it: Choose a style from each dropdown.
📏 Line Thickness
: Set the thickness for the trendlines.
What it is: An integer input to set the thickness of the trendlines.
What it does: Adjusts the thickness of the trendlines displayed on the chart.
How to use it: Enter a value between 1 and 5.
Additional Information
Trendline Percentage Difference: Setting a percentage difference helps in analyzing the relative position and angle of trendlines.
Filtering by Angle: This feature allows focusing on trendlines within a specific angle range, enhancing the clarity of trend analysis.
BOS & CHOCH Market Structure visuals:
📊 BOS & CHOCH Market Structure Input Settings
📏 Market Structure Length Option
📏Market Structure: Select the market structure length option.
What it is: A dropdown to choose between INTERNAL, EXTERNAL, ALL, CUSTOM, or NONE.
What it does: Sets the type of market structure to be displayed.
How to use it: Choose an option from the dropdown.
Additional Info:
INTERNAL: Only internal structure.
EXTERNAL: Only external structure.
ALL: Both internal and external structures.
CUSTOM: Custom lengths.
NONE: No structure.
🔧 Custom Internal Length
🔧Custom Internal: Specify a custom length for internal market structure.
What it is: An integer input for setting a custom internal length.
What it does: Defines the length of internal market structures if CUSTOM is selected.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
💬 Internal Label Size
💬Internal Label Size: Set the label size for internal market structures.
What it is: A dropdown to select the size of the labels.
What it does: Changes the size of the labels for internal market structures.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🟩 Internal Bullish Color
Internal Bullish Color: Set the color for bullish internal market structures.
What it is: A color picker to set the color of bullish internal market structures.
What it does: Changes the color of bullish internal market structures on the chart.
How to use it: Select a color from the color picker.
🟥 Internal Bearish Color
Internal Bearish Color: Set the color for bearish internal market structures.
What it is: A color picker to set the color of bearish internal market structures.
What it does: Changes the color of bearish internal market structures on the chart.
How to use it: Select a color from the color picker.
🔧 Custom External Length
🔧Custom External: Specify a custom length for external market structure.
What it is: An integer input for setting a custom external length.
What it does: Defines the length of external market structures if CUSTOM is selected.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
💬 External Label Size
💬External Label Size: Set the label size for external market structures.
What it is: A dropdown to select the size of the labels.
What it does: Changes the size of the labels for external market structures.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🟩 External Bullish Color
External Bullish Color: Set the color for bullish external market structures.
What it is: A color picker to set the color of bullish external market structures.
What it does: Changes the color of bullish external market structures on the chart.
How to use it: Select a color from the color picker.
🟥 External Bearish Color
External Bearish Color: Set the color for bearish external market structures.
What it is: A color picker to set the color of bearish external market structures.
What it does: Changes the color of bearish external market structures on the chart.
How to use it: Select a color from the color picker.
📐 Show Equal Highs and Lows
EQL & EQH📐: Toggle visibility for equal highs and lows.
What it is: A boolean input to show or hide equal highs and lows.
What it does: Displays or hides equal highs and lows on the chart.
How to use it: Check or uncheck the box to enable or disable.
📏 Equal Highs and Lows Threshold
Equal Highs and Lows Threshold: Set the threshold for equal highs and lows.
What it is: A float input to set the threshold for equal highs and lows.
What it does: Defines the range within which highs and lows are considered equal.
How to use it: Enter a value between 0 and 10.
💬 Label Size for Equal Highs and Lows
💬Label Size for Equal Highs and Lows: Set the label size for equal highs and lows.
What it is: A dropdown to select the size of the labels.
What it does: Changes the size of the labels for equal highs and lows.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🟩 Bullish Color for Equal Highs and Lows
Bullish Color for Equal Highs and Lows: Set the color for bullish equal highs and lows.
What it is: A color picker to set the color of bullish equal highs and lows.
What it does: Changes the color of bullish equal highs and lows on the chart.
How to use it: Select a color from the color picker.
🟥 Bearish Color for Equal Highs and Lows
Bearish Color for Equal Highs and Lows: Set the color for bearish equal highs and lows.
What it is: A color picker to set the color of bearish equal highs and lows.
What it does: Changes the color of bearish equal highs and lows on the chart.
How to use it: Select a color from the color picker.
📏 Show Swing Points
Swing Points📏: Toggle visibility for swing points.
What it is: A boolean input to show or hide swing points.
What it does: Displays or hides swing points on the chart.
How to use it: Check or uncheck the box to enable or disable.
📏 Swing Points Length Option
Swing Points Length Option: Select the length for swing points.
What it is: A dropdown to choose between SHORT, MID, LONG, or CUSTOM.
What it does: Sets the length of swing points.
How to use it: Choose an option from the dropdown.
Additional Info: Default lengths are SHORT=10, MID=28, LONG=50.
💬 Swing Points Label Size
💬Swing Points Label Size: Set the label size for swing points.
What it is: A dropdown to select the size of the labels.
What it does: Changes the size of the labels for swing points.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🎨 Swing Points Color
Swing Points Color: Set the color for swing points.
What it is: A color picker to set the color of swing points.
What it does: Changes the color of swing points on the chart.
How to use it: Select a color from the color picker.
🔧 Custom Swing Points Length
🔧Custom Swings: Specify a custom length for swing points.
What it is: An integer input for setting a custom length for swing points.
What it does: Defines the length of swing points if CUSTOM is selected.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
Additional Information
Market Structure Types: Understanding internal and external structures helps in analyzing different market behaviors.
Equal Highs and Lows: This feature identifies areas where price action is balanced, which can be significant for trading strategies.
Swing Points: Highlighting swing points aids in recognizing significant market reversals or continuations.
Benefits
Enhance your trading strategy by visualizing smart money's influence on price movements.
Make informed decisions with real-time data on significant market structures.
Reduce manual analysis with automated detection of key trading signals.
Ideal For
Traders looking for an edge in forex, equities, and cryptocurrency markets by understanding the underlying forces driving market dynamics.
Acknowledgements
Special thanks to these amazing creators for inspiration and their creations:
I want to thank these amazing creators for creating there amazing indicators , that inspired me and also gave me a head start by making this indicator! Without their amazing indicators it wouldn't be possible!
Flux Charts: Volumized Order Blocks
LuxAlgo: Trend Lines
UAlgo: Fair Value Gaps (FVG)
By Leviathan: Market Structure
Sonarlab: Liquidity Levels
Note
Remember to always backtest the indicator first before integrating it into your strategy! For any questions about the indicator, please feel free to ask for assistance.
Weighted Volume Profile Pivot Points | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Weighted Volume Profile Pivot Points (WVPPP) Indicator! This indicator renders a volume profile using the latest pivot points, automatically adjusting itself when new pivots occur. The pivoting mode can be switched between default pivot points and order blocks mode. It can be adjusted to give more weight to recent or past candlesticks, or can be used as a normal volume profile. For more information, please read the full write-up.
Features of the new Weighted Volume Profile Pivot Points (WVPPP) Indicator :
Renders Volume Profile Of The Range Between Latest Pivots
Two Pivoting Modes Including Order Blocks Mode
Adjustable Weighthing Towards Past or Recent
Customizable Row Count & Maximum Distance
Left or Right Alignment
More Styling Options
🚩UNIQUENESS
This indicator stands out with two key features. One is it's ability to weight volumes based on their distance to the current time. Giving weight to volumes may offer new trading opportunities to traders as they can now see the most recent Point Of Control (POC) or a more powerful but past POC based on their choice. Another key feature the indicator has is that it automatically finds latest valid pivot points, and uses that range for the volume profile. The range changes dynamically as new pivots points emerge. You can select between normal pivot points and order blocks mode. The indicator also has a variety of useful styling settings such as aligning the volume profile to the right or the left of the chart, POC Line styling and color settings for bullish & bearish volumes.
📌 HOW DOES IT WORK ?
A volume profile provides an in-depth look at trading activity over a period of time by plotting a histogram on the price axis. This indicator can also give weight to volumes based on their distance to the current time, essentially determining their importance for the profile. The range which the volume profile will cover is determined by the latest pivot points. Here is how it works step-by-step :
1. Determine how much candlesticks the volume profile will cover (Analyze Bars setting)
2. Find the latest pivot points. If the mode is set to "Pivots", the pivot points are the candlesticks which has the highest / lowest wick in X amount of bars (Swing Length setting). If the mode is set to "Order Blocks", the volume profile range is the area between the latest buyside order block and the sellside order block. Order blocks occur when there is a high amount of market orders exist on a price range. It is possible to find order blocks using specific candlestick formations on the chart. For more information about the order block detection, I suggest you checking the write-up of our "Volumized Order Blocks" script. Increasing the "Swing Length" setting is recommended when the mode is set to "Pivots", as this will help in finding stronger pivot points.
3. Make a range using the latest pivot points, then divide it into rows (Row Count setting)
4. Then for each candlestick, add it's volume to the corresponding row in the range. Note that the volume can be added into several rows if it overlaps with them all.
5. If the candlestick is a bullish candlestick, we add it's volume into the bullish volume of the row, if it's a bearish candlestick, we add it to the bearish volume of the row.
With the weighted volume mode, which is activated if "Volume Weighthing" setting is set to "Recent" or "Past", all volumes get a penalty based on their distance to the latest candletstick. For example, if the setting is set to "Recent", the latest candlestick contributes it's volume by 100% to the corresponding row, but the candlestick which is 50 candlesticks far from the current candlestick only contributes it's volume by ~17% to the row. The same applies to the "Past" setting, but in the reversed order, where past candlesticks have more priority than the current ones.
Volume contribution percent for "Recent" setting : ((100 * 0.85) / (i + 1)) + (100 * (1.0 - 0.85))
Volume contribution percent for "Past" setting : ((100 * 0.85) * ((i + 1) / N)) + (100 * (1.0 - 0.85))
Where i = candlestick index from right to left, N = total number of candlesticks analyzed by the volume profile.
The Point Of Control (POC) line is drawn from the row with the most total volume, and is generally considered as a strong level because a lot of trading volume happened on that particular row. Traders may use this line as a support & resistance level.
We believe that automatically ranging the volume profile to important pivot points will help traders see crucial volume information easier without unnecessary hassle. Traders can use this indicator to have an insight of areas which price moves quickly without much volume, or see areas that holds the price still for much longer and plan their trades accordingly.
⚙️SETTINGS
1. General Configuration
Mode -> The pivoting mode that is switchable between "Pivots" and "Order Blocks" as described in the write-up. Please read the upper section to understand how this setting works.
Analyze Bars -> Total amount of bars that will be analyzed by the indicator from right to left.
Row Count -> The amount of rows that will the vertical range between pivot points will be divided into.
Volume Weighting -> The volume weighting mode as explained in the write-up.
2. Style
Highlight Sessions -> The volume profile sessions will be highlighted with a blue tint. To prevent confusion, highlighting will not work if the alignment is set to "Right".
Align To -> The alignment of the volume profile.
Weighted Volume Profile | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Weighted Volume Profile Indicator! This indicator renders a volume profile based on the volume of latest candlesticks. It can be adjusted to give more weight to recent or past candlesticks, or can be used as a normal volume profile. For more information, please read the full write-up.
Features of the new Weighted Volume Profile indicator :
Renders Volume Profile Of Current Ticker
Adjustable Weighthing Towards Past or Recent
Customizable Row Count & Maximum Distance
Left or Right Alignment
More Styling Options
🚩UNIQUENESS
This indicator differs from a normal volume profile indicator by it's ability to weight volumes based on their distance to the current time. Giving weight to volumes may offer new trading opportunities to traders as they can now see the most recent Point Of Control (POC) or a more powerful but past POC based on their choice. The indicator also has a variety of useful styling settings such as aligning the volume profile to the right or the left of the chart, POC Line styling and color settings for bullish & bearish volumes.
📌 HOW DOES IT WORK ?
A volume profile provides an in-depth look at trading activity over a period of time by plotting a histogram on the price axis. This indicator can also give weight to volumes based on their distance to the current time, essentially determining their importance for the profile. Here is how it works step-by-step :
1. Determine how much candlesticks the volume profile will cover (Analyze Bars setting)
2. Make a range from the highest point of chart to the lowest point of chart, then divide it into rows (Row Count setting)
3. For each candlestick, add it's volume to the corresponding row in the range. Note that the volume can be added into several rows if it overlaps with them.
4. If the candlestick is a bullish candlestick, we add it's volume into the bullish volume of the row, if it's a bearish candlestick, we add it to the bearish volume of the row.
With the weighted volume mode, which is activated if "Volume Weighthing" setting is set to "Recent" or "Past", all volumes get a penalty based on their distance to the latest candletstick. For example, if the setting is set to "Recent", the latest candlestick contributes it's volume by 100% to the corresponding row, but the candlestick which is 50 candlesticks far from the current candlestick only contributes it's volume by ~17% to the row. The same applies to the "Past" setting, but in the reversed order, where past candlesticks have more priority than the current ones.
Volume contribution percent for "Recent" setting : ((100 * 0.85) / (i + 1)) + (100 * (1.0 - 0.85))
Volume contribution percent for "Past" setting : ((100 * 0.85) * ((i + 1) / N)) + (100 * (1.0 - 0.85))
Where i = candlestick index from right to left, N = total number of candlesticks analyzed by the volume profile.
The Point Of Control (POC) line is drawn from the row with the most total volume, and is generally considered as a strong level because a lot of trading volume happened on that particular row. Traders may use this line as a support & resistance level.
Traders can use this indicator to have an insight of areas which price moves quickly without much volume, or see areas that holds the price still for much longer and plan their trades accordingly.
⚙️SETTINGS
1. General Configuration
Analyze Bars -> Total amount of bars that will be analyzed by the indicator from right to left.
Row Count -> The amount of rows that will the vertical range of chart will be divided into.
Volume Weighting -> The volume weighting mode as explained in the write-up.
2. Style
Align To -> The alignment of the volume profile.
Asset Drawdown & Drawdown HeatMap [InvestorUnknown]Overview
The "Asset Drawdown & Drawdown HeatMap" indicator is designed for educational purposes to help users visualize and analyze the drawdowns of various assets. It highlights both recent and historical drawdowns, offering valuable insights into the performance and risk of different investments. Additionally, it can serve as a complementary analysis tool for trading and investing decisions.
Features
Drawdown Calculation:
Computes the drawdown from the highest value (ATH) to the current value, showing the percentage decline.
Displays both the current drawdown and the maximum historical drawdown for the selected assets.
HeatMap Visualization:
Uses a gradient color scheme to represent the magnitude of drawdowns over a specified lookback period.
Helps identify periods of significant decline and recovery visually.
Multiple Assets:
Supports up to 10 different assets (adding more would make it harder to see the drawdowns of different assets), allowing users to compare drawdowns across various symbols.
Each asset can be individually plotted and color-coded for clarity.
Customizable Settings:
User inputs for high and low value calculations, color preferences, and lookback periods.
Option to color bars based on the drawdown heatmap.
Detailed Functionality
Drawdown Calculation:
The DD() function calculates the current drawdown and the maximum historical drawdown based on the high and low values.
The drawdown is calculated as 100 - (lowvalue / ATH * 100), where ATH is the highest value observed so far.
// - - - - - Custom Function - - - - - //{
DD() =>
ATH = highvalue
ATH := na(ATH ) ? highvalue : math.max(highvalue, ATH )
Drawdown = 100 - lowvalue / ATH * 100
MaxDrawdown = Drawdown
MaxDrawdown := na(MaxDrawdown ) ? Drawdown : math.max(Drawdown, MaxDrawdown )
//}
Security Request:
Uses the request.security() function to fetch drawdown data for each specified asset on a daily timeframe.
Computes both current drawdown (TnDD) and maximum drawdown (TnMDD) for each asset.
// - - - - - Create Variables - - - - - //{
= request.security("", "1D", DD()) // Chart
= request.security(t1, "1D", DD())
= request.security(t2, "1D", DD())
= request.security(t3, "1D", DD())
= request.security(t4, "1D", DD())
= request.security(t5, "1D", DD())
= request.security(t6, "1D", DD())
= request.security(t7, "1D", DD())
= request.security(t8, "1D", DD())
= request.security(t9, "1D", DD())
= request.security(t10, "1D", DD())
//}
Plotting:
Plots the drawdown values for each asset on the chart, with the option to enable or disable plotting for individual assets.
Colors the plotted lines and labels based on user-specified preferences.
HeatMap:
Creates a heatmap color gradient based on the drawdown values over the lookback period.
Colors the bars on the chart according to the heatmap to visualize drawdown severity over time.
// - - - - - HeatMap - - - - - //{
heatcol = color.from_gradient(T0DD, ta.lowest(T0DD,lookback), ta.highest(T0DD,lookback), topcol, botcol)
barcolor(colbars ? heatcol : na)
//}
Labels:
Displays labels for each asset's drawdown value at the end of the chart for quick reference.
This indicator is an excellent tool for educational purposes, helping users understand drawdown dynamics and their implications on asset performance. It also provides a visual aid for monitoring and comparing drawdowns across multiple assets, which can be beneficial for making informed trading and investment decisions.
Directional Movement Index DEThis script uses the existing built-in DMI indicator but adds two lines indicating strength of the ADX trend. The original author J. Welles Wilder, indicated a ADX trending strongly above 25 (yellow by default), and ADX trending weaker at a threshold of 20 or below (dashed yellow by default).
The default colours have been changed so that ADX is yellow, +DI is green, and -DI is red.
Calculation
Calculating the DMI can actually be broken down into two parts. First, calculating the +DI and -DI, and second, calculating the ADX. To calculate the +DI and -DI you need to find the +DM and -DM (Directional Movement). +DM and -DM are calculated using the High, Low and Close for each period. You can then calculate the following:
Current High - Previous High = UpMove
Previous Low - Current Low = DownMove
If UpMove > DownMove and UpMove > 0, then +DM = UpMove, else +DM = 0
If DownMove > Upmove and Downmove > 0, then -DM = DownMove, else -DM = 0
Once you have the current +DM and -DM calculated, the +DM and -DM lines can be calculated and plotted based on the number of user defined periods.
+DI = 100 times Exponential Moving Average of (+DM / Average True Range)
-DI = 100 times Exponential Moving Average of (-DM / Average True Range)
Now that -+DX and -DX have been calculated, the last step is calculating the ADX.
ADX = 100 times the Exponential Moving Average of the Absolute Value of (+DI - -DI) / (+DI + -DI)
The basics
DMI has a value between 0 and 100 and is used to measure the strength of the current trend. +DI and -DI are then used to measure direction. When combined, the indicator can provide some valuable insight. A general interpretation would be that during a strong trend (ADX above 25 but dependent on the analyst's interpretation), when the +DI is above the -DI, then a Bullish Market is defined. When -DI is above +DI, then a Bearish Market is at hand.
One thing to be considered is that what DMI values determine, strength or a potential signal, is up to the trader's interpretation. Acceptable values may change depending on the financial instrument being examined, therefore some historical analysis of the instrument in question would be prudent. A technical analyst can make better decisions based on what has occurred in historical examples.
All credit goes to the original script .
Strategic Multi-Step Supertrend - Strategy [presentTrading]The code is mainly developed for me to stimulate the multi-step taking profit function for strategies. The result shows the drawdown can be reduced but at the same time reduced the profit as well. It can be a heuristic for futures leverage traders.
█ Introduction and How it is Different
The "Strategic Multi-Step Supertrend" is a trading strategy designed to leverage the power of multiple steps to optimize trade entries and exits across the Supertrend indicator. Unlike traditional strategies that rely on single entry and exit points, this strategy employs a multi-step approach to take profit, allowing traders to lock in gains incrementally. Additionally, the strategy is adaptable to both long and short trades, providing a comprehensive solution for dynamic market conditions.
This template strategy lies in its dual Supertrend calculation, which enhances the accuracy of trend detection and provides more reliable signals for trade entries and exits. This approach minimizes false signals and increases the overall profitability of trades by ensuring that positions are entered and exited at optimal points.
BTC 6h L/S Performance
█ Strategy, How It Works: Detailed Explanation
The "Strategic Multi-Step Supertrend Trader" strategy utilizes two Supertrend indicators calculated with different parameters to determine the direction and strength of the market trend. This dual approach increases the robustness of the signals, reducing the likelihood of entering trades based on false signals. Here is a detailed breakdown of how the strategy operates:
🔶 Supertrend Indicator Calculation
The Supertrend indicator is a trend-following overlay on the price chart, typically used to identify the direction of the trend. It is calculated using the Average True Range (ATR) to ensure that the indicator adapts to market volatility. The formula for the Supertrend indicator is:
Upper Band = (High + Low) / 2 + (Factor * ATR)
Lower Band = (High + Low) / 2 - (Factor * ATR)
Where:
- High and Low are the highest and lowest prices of the period.
- Factor is a user-defined multiplier.
- ATR is the Average True Range over a specified period.
The Supertrend changes its direction based on the closing price in relation to these bands.
🔶 Entry-Exit Conditions
The strategy enters long positions when both Supertrend indicators signal an uptrend, and short positions when both indicate a downtrend. Specifically:
- Long Condition: Supertrend1 < 0 and Supertrend2 < 0
- Short Condition: Supertrend1 > 0 and Supertrend2 > 0
- Long Exit Condition: Supertrend1 > 0 and Supertrend2 > 0
- Short Exit Condition: Supertrend1 < 0 and Supertrend2 < 0
🔶 Multi-Step Take Profit Mechanism
The strategy features a multi-step take profit mechanism, which allows traders to lock in profits incrementally. This is achieved through four user-configurable take profit levels. For each level, the strategy specifies a percentage increase (for long trades) or decrease (for short trades) in the entry price at which a portion of the position is exited:
- Step 1: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent1 / 100)
- Step 2: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent2 / 100)
- Step 3: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent3 / 100)
- Step 4: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent4 / 100)
This staggered exit strategy helps in locking profits at multiple levels, thereby reducing risk and increasing the likelihood of capturing the maximum possible profit from a trend.
BTC Local
█ Trade Direction
The strategy is highly flexible, allowing users to specify the trade direction. There are three options available:
- Long Only: The strategy will only enter long trades.
- Short Only: The strategy will only enter short trades.
- Both: The strategy will enter both long and short trades based on the Supertrend signals.
This flexibility allows traders to adapt the strategy to various market conditions and their own trading preferences.
█ Usage
1. Add the strategy to your trading platform and apply it to the desired chart.
2. Configure the take profit settings under the "Take Profit Settings" group.
3. Set the trade direction under the "Trade Direction" group.
4. Adjust the Supertrend settings in the "Supertrend Settings" group to fine-tune the indicator calculations.
5. Monitor the chart for entry and exit signals as indicated by the strategy.
█ Default Settings
- Use Take Profit: True
- Take Profit Percentages: Step 1 - 6%, Step 2 - 12%, Step 3 - 18%, Step 4 - 50%
- Take Profit Amounts: Step 1 - 12%, Step 2 - 8%, Step 3 - 4%, Step 4 - 0%
- Number of Take Profit Steps: 3
- Trade Direction: Both
- Supertrend Settings: ATR Length 1 - 10, Factor 1 - 3.0, ATR Length 2 - 11, Factor 2 - 4.0
These settings provide a balanced starting point, which can be customized further based on individual trading preferences and market conditions.
Fusion MFI RSIHello fellas,
This superb indicator summons two monsters called Relative Strength Index (RSI) and Money Flow Index (MFI) and plays the Yu-Gi-Oh! card "Polymerization" to combine them.
Overview
The Fusion MFI RSI Indicator is an advanced analytical tool designed to provide a nuanced understanding of market dynamics by combining the Relative Strength Index (RSI) and the Money Flow Index (MFI). Enhanced with sophisticated smoothing techniques and the Inverse Fisher Transform (IFT), this indicator excels in identifying key market conditions such as overbought and oversold states, trends, and potential reversal points.
Key Features (Brief Overview)
Fusion of RSI and MFI: Integrates momentum and volume for a comprehensive market analysis.
Advanced Smoothing Techniques: Employs Hann Window, Jurik Moving Average (JMA), T3 Smoothing, and Super Smoother to refine signals.
Inverse Fisher Transform (IFT) Enhances the clarity and distinctiveness of indicator outputs.
Detailed Feature Analysis
Fusion of RSI and MFI
RSI (Relative Strength Index): Developed by J. Welles Wilder Jr., the RSI measures the speed and magnitude of directional price movements. Wilder recommended using a 14-day period and identified overbought conditions above 70 and oversold conditions below 30.
MFI (Money Flow Index): Created by Gene Quong and Avrum Soudack, the MFI combines price and volume to measure trading pressure. It is typically calculated using a 14-day period, with over 80 considered overbought and under 20 as oversold.
Application in Fusion: By combining RSI and MFI, the indicator leverages RSI's sensitivity to price changes with MFI's volume-weighted confirmation, providing a robust analysis tool. This combination is particularly effective in confirming the strength behind price movements, making the signals more reliable.
Advanced Smoothing Techniques
Hann Window: Traditionally used to reduce the abrupt data discontinuities at the edges of a sample, it is applied here to smooth the price data.
Jurik Moving Average (JMA): Known for preserving the timing and smoothness of the data, JMA reduces market noise effectively without significant lag.
T3 Smoothing: Developed to respond quickly to market changes, T3 provides a smoother response to price fluctuations.
Super Smoother: Filters out high-frequency noise while retaining important trends.
Application in Fusion: These techniques are chosen to refine the output of the combined RSI and MFI values, ensuring the indicator remains responsive yet stable, providing clearer and more actionable signals.
Inverse Fisher Transform (IFT):
Developed by John Ehlers, the IFT transforms oscillator outputs to enhance the clarity of extreme values. This is particularly useful in this fusion indicator to make critical turning points more distinct and actionable.
Mathematical Calculations for the Fusion MFI RSI Indicator
RSI (Relative Strength Index)
The RSI is calculated using the following steps:
Average Gain and Average Loss: First, determine the average gain and average loss over the specified period (typically 14 days). This is done by summing all the gains and losses over the period and then dividing each by the period.
Average Gain = (Sum of Gains over the past 14 periods) / 14
Average Loss = (Sum of Losses over the past 14 periods) / 14
Relative Strength (RS): This is the ratio of average gain to average loss.
RS = Average Gain / Average Loss
RSI: Finally, the RSI is calculated using the RS value:
RSI = 100 - (100 / (1 + RS))
MFI (Money Flow Index)
The MFI is calculated using several steps that incorporate both price and volume:
Typical Price: Calculate the typical price for each period.
Typical Price = (High + Low + Close) / 3
Raw Money Flow: Multiply the typical price by the volume for the period.
Raw Money Flow = Typical Price * Volume
Positive and Negative Money Flow: Compare the typical price of the current period to the previous period to determine if the money flow is positive or negative.
If today's Typical Price > Yesterday's Typical Price, then Positive Money Flow = Raw Money Flow; Negative Money Flow = 0
If today's Typical Price < Yesterday's Typical Price, then Negative Money Flow = Raw Money Flow; Positive Money Flow = 0
Money Flow Ratio: Calculate the ratio of the sum of Positive Money Flows to the sum of Negative Money Flows over the past 14 periods.
Money Flow Ratio = (Sum of Positive Money Flows over 14 periods) / (Sum of Negative Money Flows over 14 periods)
MFI: Finally, calculate the MFI using the Money Flow Ratio.
MFI = 100 - (100 / (1 + Money Flow Ratio))
Fusion of RSI and MFI
The final Fusion MFI RSI value could be calculated by averaging the IFT-transformed values of RSI and MFI, providing a single oscillator value that reflects both momentum and volume-weighted price action:
Fusion MFI RSI = (MFI weight * MFI) + (RSI weight * RSI)
Suggested Settings and Trading Rules
Original Usage
RSI: Wilder suggested buying when the RSI moves above 30 from below (enter long) and selling when the RSI moves below 70 from above (enter short). He recommended exiting long positions when the RSI reaches 70 or higher and exiting short positions when the RSI falls below 30.
MFI: Quong and Soudack recommended buying when the MFI is below 20 and starts rising (enter long), and selling when it is above 80 and starts declining (enter short). They suggested exiting long positions when the MFI reaches 80 or higher and exiting short positions when the MFI falls below 20.
Fusion Application
Settings: Use a 14-day period for this indicator's calculations to maintain consistency with the original settings suggested by the inventors.
Trading Rules:
Enter Long Signal: Consider entering a long position when both RSI and MFI are below their respective oversold levels and begin to rise. This indicates strong buying pressure supported by both price momentum and volume.
Exit Long Signal: Exit the long position when either RSI or MFI reaches its respective overbought threshold, suggesting a potential reversal or decrease in buying pressure.
Enter Short Signal: Consider entering a short position when both indicators are above their respective overbought levels and begin to decline, suggesting that selling pressure is mounting.
Exit Short Signal: Exit the short position when either RSI or MFI falls below its respective oversold threshold, indicating diminishing selling pressure and a potential upward reversal.
How to Use the Indicator
Select Source and Timeframe: Choose the data source and the timeframe for analysis.
Configure Fusion Settings: Adjust the weights for RSI and MFI.
Choose Smoothing Technique: Select and configure the desired smoothing method to suit the market conditions and personal preference.
Enable Fisherization: Optionally apply the Inverse Fisher Transform to enhance signal clarity.
Customize Visualization: Set up gradient coloring, background plots, and bands according to your preferences.
Interpret the Indicator: Use the Fusion value and visual cues to identify market conditions and potential trading opportunities.
Conclusion
The Fusion MFI RSI Indicator integrates classical and modern technical analysis concepts to provide a comprehensive tool for market analysis. By combining RSI and MFI with advanced smoothing techniques and the Inverse Fisher Transform, this indicator offers enhanced insights, aiding traders in making more informed and timely trading decisions. Customize the settings to align with your trading strategy and leverage this powerful tool to navigate financial markets effectively.
Best regards,
simwai
---
Credits to:
@loxx – T3
@everget – JMA
@cheatcountry – Hann Window
CPR by MTThe CPR indicator, or Central Pivot Range indicator, is a technical analysis tool used in trading to identify potential support and resistance levels based on the price action of a security. Developed by pivot point theory, it is particularly popular among day traders and swing traders. The CPR indicator consists of three lines:
1. **Pivot Point (PP):** This is the central line and is calculated as the average of the high, low, and closing prices from the previous trading period.
\
2. **Top Central Pivot (TC):** This is calculated by subtracting the low from the PP and then adding the result to the PP.
\
3. **Bottom Central Pivot (BC):** This is calculated by subtracting the high from the PP and then adding the result to the PP.
\
### How to Use the CPR Indicator
- **Trend Identification:** A wide CPR range indicates low volatility and a potential sideways or consolidation phase. A narrow CPR range indicates high volatility and a potential strong trending move.
- **Support and Resistance:** The top and bottom central pivots act as immediate resistance and support levels. If the price is above the TC, it indicates a bullish sentiment, while if it is below the BC, it indicates a bearish sentiment.
- **Entry and Exit Points:** Traders use the CPR lines to determine optimal entry and exit points. For example, if the price breaks above the TC and sustains, it may signal a buy opportunity, whereas a drop below the BC may signal a sell opportunity.
### Practical Example
Suppose a stock had a high of $105, a low of $95, and a closing price of $100 on the previous day. The CPR levels for the next day would be calculated as follows:
1. **Pivot Point (PP):**
\
2. **Top Central Pivot (TC):**
\
3. **Bottom Central Pivot (BC):**
\
The levels for the next day would be PP = $100, TC = $110, and BC = $90. Traders would then use these levels to assess potential trading strategies based on where the price moves relative to these levels.
### Conclusion
The CPR indicator is a useful tool for traders looking to understand market conditions and make informed decisions about entry and exit points. Its effectiveness comes from its ability to highlight key price levels derived from historical price data, helping traders predict potential market movements.
Statistics • Chi Square • P-value • SignificanceThe Statistics • Chi Square • P-value • Significance publication aims to provide a tool for combining different conditions and checking whether the outcome is significant using the Chi-Square Test and P-value.
🔶 USAGE
The basic principle is to compare two or more groups and check the results of a query test, such as asking men and women whether they want to see a romantic or non-romantic movie.
–––––––––––––––––––––––––––––––––––––––––––––
| | ROMANTIC | NON-ROMANTIC | ⬅︎ MOVIE |
–––––––––––––––––––––––––––––––––––––––––––––
| MEN | 2 | 8 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
| WOMEN | 7 | 3 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
|⬆︎ SEX | 10 | 10 | 20 |
–––––––––––––––––––––––––––––––––––––––––––––
We calculate the Chi-Square Formula, which is:
Χ² = Σ ( (Observed Value − Expected Value)² / Expected Value )
In this publication, this is:
chiSquare = 0.
for i = 0 to rows -1
for j = 0 to colums -1
observedValue = aBin.get(i).aFloat.get(j)
expectedValue = math.max(1e-12, aBin.get(i).aFloat.get(colums) * aBin.get(rows).aFloat.get(j) / sumT) //Division by 0 protection
chiSquare += math.pow(observedValue - expectedValue, 2) / expectedValue
Together with the 'Degree of Freedom', which is (rows − 1) × (columns − 1) , the P-value can be calculated.
In this case it is P-value: 0.02462
A P-value lower than 0.05 is considered to be significant. Statistically, women tend to choose a romantic movie more, while men prefer a non-romantic one.
Users have the option to choose a P-value, calculated from a standard table or through a math.ucla.edu - Javascript-based function (see references below).
Note that the population (10 men + 10 women = 20) is small, something to consider.
Either way, this principle is applied in the script, where conditions can be chosen like rsi, close, high, ...
🔹 CONDITION
Conditions are added to the left column ('CONDITION')
For example, previous rsi values (rsi ) between 0-100, divided in separate groups
🔹 CLOSE
Then, the movement of the last close is evaluated
UP when close is higher then previous close (close )
DOWN when close is lower then previous close
EQUAL when close is equal then previous close
It is also possible to use only 2 columns by adding EQUAL to UP or DOWN
UP
DOWN/EQUAL
or
UP/EQUAL
DOWN
In other words, when previous rsi value was between 80 and 90, this resulted in:
19 times a current close higher than previous close
14 times a current close lower than previous close
0 times a current close equal than previous close
However, the P-value tells us it is not statistical significant.
NOTE: Always keep in mind that past behaviour gives no certainty about future behaviour.
A vertical line is drawn at the beginning of the chosen population (max 4990)
Here, the results seem significant.
🔹 GROUPS
It is important to ensure that the groups are formed correctly. All possibilities should be present, and conditions should only be part of 1 group.
In the example above, the two top situations are acceptable; close against close can only be higher, lower or equal.
The two examples at the bottom, however, are very poorly constructed.
Several conditions can be placed in more than 1 group, and some conditions are not integrated into a group. Even if the results are significant, they are useless because of the group formation.
A population count is added as an aid to spot errors in group formation.
In this example, there is a discrepancy between the population and total count due to the absence of a condition.
The results when rsi was between 5-25 are not included, resulting in unreliable results.
🔹 PRACTICAL EXAMPLES
In this example, we have specific groups where the condition only applies to that group.
For example, the condition rsi > 55 and rsi <= 65 isn't true in another group.
Also, every possible rsi value (0 - 100) is present in 1 of the groups.
rsi > 15 and rsi <= 25 28 times UP, 19 times DOWN and 2 times EQUAL. P-value: 0.01171
When looking in detail and examining the area 15-25 RSI, we see this:
The population is now not representative (only checking for RSI between 15-25; all other RSI values are not included), so we can ignore the P-value in this case. It is merely to check in detail. In this case, the RSI values 23 and 24 seem promising.
NOTE: We should check what the close price did without any condition.
If, for example, the close price had risen 100 times out of 100, this would make things very relative.
In this case (at least two conditions need to be present), we set 1 condition at 'always true' and another at 'always false' so we'll get only the close values without any condition:
Changing the population or the conditions will change the P-value.
In the following example, the outcome is evaluated when:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is lower/equal than the close value from 2 bars back
Or:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is equal than the close value from 2 bars back
close value from 1 bar back is lower than the close value from 2 bars back
In both examples, all possibilities of close against close are included in the calculations. close can only by higher, equal or lower than close
Both examples have the results without a condition included (5 = 5 and 5 < 5) so one can compare the direction of current close.
🔶 NOTES
• Always keep in mind that:
Past behaviour gives no certainty about future behaviour.
Everything depends on time, cycles, events, fundamentals, technicals, ...
• This test only works for categorical data (data in categories), such as Gender {Men, Women} or color {Red, Yellow, Green, Blue} etc., but not numerical data such as height or weight. One might argue that such tests shouldn't use rsi, close, ... values.
• Consider what you're measuring
For example rsi of the current bar will always lead to a close higher than the previous close, since this is inherent to the rsi calculations.
• Be careful; often, there are na -values at the beginning of the series, which are not included in the calculations!
• Always keep in mind considering what the close price did without any condition
• The numbers must be large enough. Each entry must be five or more. In other words, it is vital to make the 'population' large enough.
• The code can be developed further, for example, by splitting UP, DOWN in close UP 1-2%, close UP 2-3%, close UP 3-4%, ...
• rsi can be supplemented with stochRSI, MFI, sma, ema, ...
🔶 SETTINGS
🔹 Population
• Choose the population size; in other words, how many bars you want to go back to. If fewer bars are available than set, this will be automatically adjusted.
🔹 Inputs
At least two conditions need to be chosen.
• Users can add up to 11 conditions, where each condition can contain two different conditions.
🔹 RSI
• Length
🔹 Levels
• Set the used levels as desired.
🔹 Levels
• P-value: P-value retrieved using a standard table method or a function.
• Used function, derived from Chi-Square Distribution Function; JavaScript
LogGamma(Z) =>
S = 1
+ 76.18009173 / Z
- 86.50532033 / (Z+1)
+ 24.01409822 / (Z+2)
- 1.231739516 / (Z+3)
+ 0.00120858003 / (Z+4)
- 0.00000536382 / (Z+5)
(Z-.5) * math.log(Z+4.5) - (Z+4.5) + math.log(S * 2.50662827465)
Gcf(float X, A) => // Good for X > A +1
A0=0., B0=1., A1=1., B1=X, AOLD=0., N=0
while (math.abs((A1-AOLD)/A1) > .00001)
AOLD := A1
N += 1
A0 := A1+(N-A)*A0
B0 := B1+(N-A)*B0
A1 := X*A0+N*A1
B1 := X*B0+N*B1
A0 := A0/B1
B0 := B0/B1
A1 := A1/B1
B1 := 1
Prob = math.exp(A * math.log(X) - X - LogGamma(A)) * A1
1 - Prob
Gser(X, A) => // Good for X < A +1
T9 = 1. / A
G = T9
I = 1
while (T9 > G* 0.00001)
T9 := T9 * X / (A + I)
G := G + T9
I += 1
G *= math.exp(A * math.log(X) - X - LogGamma(A))
Gammacdf(x, a) =>
GI = 0.
if (x<=0)
GI := 0
else if (x
Chisqcdf = Gammacdf(Z/2, DF/2)
Chisqcdf := math.round(Chisqcdf * 100000) / 100000
pValue = 1 - Chisqcdf
🔶 REFERENCES
mathsisfun.com, Chi-Square Test
Chi-Square Distribution Function
Wick Percentages TableThis script is designed to calculate and display the percentage representation of wick lengths in relation to the total candle range for the last 100 candles on a trading chart. Here's a breakdown of its functionality:
Indicator Initialization: It sets up an indicator named "Wick Percentages Table" (WPT) that overlays on the trading chart.
Variables Initialization: The script initializes variables to store the total lengths of top wicks, bottom wicks, and the total ranges for the last 100 candles.
Wick and Range Calculations: For the past 100 candles, it calculates:
The length of the top wick (the distance between the high and the higher of the open or close).
The length of the bottom wick (the distance between the low and the lower of the open or close).
The total range of each candle (the distance between the high and the low).
Percentage Calculations: It computes the top and bottom wick lengths as percentages of the total candle range across the last 100 candles.
Table Display: It creates or updates a table displayed on the top right of the chart showing these percentages. The table has two rows: one for the "Top Wick %" and another for the "Bottom Wick %", with the corresponding percentages calculated and displayed.
Visibility Maintenance: It plots a dummy variable to ensure the indicator's visibility on the chart.
The purpose of this script is to provide traders with a visual representation of the wick lengths as percentages, offering insights into market behavior and potential price movements based on recent candlestick patterns. It aids in assessing market volatility and trader sentiment through the analysis of wick lengths relative to the total candle sizes.
...
Any improvements to this code would be more then welcome.
I was getting an error in line 30, the only thing I could find was to comment it out.
Price and Volume Stochastic Divergence [MW]Introduction
This indicator creates signals of interest for entering and exiting long and short positions on equities. It primarily uses up and down trends defined by the change in cumulative volume with some filtering provided by a short period exponential moving average (9 EMA by default).
Settings
Moving Average Period : The moving average over which the cumulative volume delta is calculated. Default: 14
Short Period EMA : The EMA used to represent price action, and is used to generate the EMA Delta line. Default: 27 (3*3*3)
Long Period EMA : The second EMA used to calculate the EMA Delta line. Default: 108 (2*2*3*3*3)
Stochastic K Value : The value used for stochastic curve smoothing. Default: 3
Dot Size : The diameter of the larger indicator. Default: 10
Dot Transparency : The transparency level of the outer ring of the primary BUY/SELL signal. Default: 50 (0 is opaque, 100 is transparent)
Band Distance from 0 to 100 : The upper and lower band distance. Default: 20
Calculations
The cumulative volume delta (CVD) is calculated using candle bodies and wicks. For a red candle, buying volume is calculated by multiplying the volume by the spread percentage of the average of the top and bottom wicks, while Selling Volume is calculated multiplying the volume by the spread percentage of the average of the top and bottom wicks - in addition to the spread percentage of the candle body.
For a green candle, buying volume is calculated by multiplying the volume by the spread percentage of the average of the top and bottom wicks - plus the spread percentage of the candle body - while Selling Volume is calculated using only the spread percentage average of the top and bottom wicks.
Once we have the CVD, we can then perform a stochastic calculation of the CVD value.
stochastic calculation = (current value - lowest value in period) / (highest value in period - lowest value in period)
We’ll do the same stochastic calculation for the short term EMA (27 EMA default) as well as for the difference between the short term and long term EMA.
When the stochastic CVD value is rising from zero and the short term EMA stochastic value equals 100, then it’s a major bullish signal. When the stochastic CVD value is falling from 100 and the short term EMA stochastic value equals 0, then it’s a major bearish signal.
Sometimes, after a bullish or bearish signal, the stochastic CVD will reverse direction triggering a new opposing signal.
How to Interpret
The CVD indicates when there is either more buying than selling or vice versa. A value over 50 for the stochastic CVD curve represents more buying taking place. A value below 50 represents more selling. One might intuitively believe that when there is more buying volume than selling volume that the price would follow suit. This is not always the case.
Most of the time buying volume will precede consistent price movement upwards, and selling volume will precede consistent price movement downwards. When this divergence occurs, the indicator generates a signal. When this divergence begins to fail, and buying or selling volume reverses, then another signal is generated indicating that the buying/selling impulse is headed back into the direction of price action.
These interactions are visually represented on the chart with the coral line that represents CVD, and the yellow line that represents the EMA, or the average price. When the coral line goes up and the yellow line stays down, that’s the BUY signal. When the coral line goes down and the yellow line stays up, that’s the sell signal. When the coral line switches direction, the chart generates another signal showing that volume is moving in a direction that supports the price.
The orange line represents the stochastic representation of the difference between the short EMA (27 by default) and the long EMA (108 by default). EMA differences is a method that can be used to define a trend. When a short term EMA is above a longer term EMA, that may represent a bullish trend. When it is below, that may represent a bearish trend. When all 3 lines are rising or falling in the same direction at the same time, it tends to indicate a movement that has the potential to continue.
Other Usage Notes and Limitations
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
This indicator can be paired with the MW Volume Impulse indicator if it is desired to see the actual buying and selling cumulative volume deltas. Also, in many cases, the BUY and SELL signals tend to correspond with Keltner Bands (ATR Bands) becoming extended. Lastly, volume weighted average price (VWAP) along with other macro events can impact price and negate signals. To view VWAP lines, you may choose to use the Multi VWAP or Multi VWAP for Gaps indicator to help ensure that the signals you see in this indicator are not being affected by VWAP lines.
Awesome Oscillator + Bars count lines + EMA LineThe indicator includes an Awesome Oscillator with 2 vertical lines at a distance of 100 and 140 bars from the last bar to determine the third Elliott wave by the maximum peak of AO in the interval from 100 to 140 bars according to Bill Williams' Profitunity strategy. Additionally, a faster EMA line is displayed that calculates the difference between 5 Period and 34 Period Exponential Moving Averages (EMA 5 - EMA 34) based on the midpoints of the bars, just like AO calculates the difference between Simple Moving Averages (SMA 5 - SMA 34).
In the indicator settings, you can change the number of bars for vertical lines and any parameters for AO and EMA - method (SMA, Smoothed SMA, EMA and others), length, source (open, high, low, close, hl2 and others).
***
Индикатор включает Awesome Oscillator с 2 вертикальными линиями на расстоянии 100 и 140 баров от последнего бара, чтобы определить третью волну Эллиота по максимальному пику AO в интервале от 100 до 140 баров по стратегии Profitunity Билла Вильямса. Дополнительно отображается более быстрая линия EMA, которая вычисляет разницу между 5 Периодной и 34 Периодной Экспоненциальными Скользящими Средними (EMA 5 - EMA 34) по средним точкам баров (hl2), точно так же, как AO вычисляет разницу между Простыми Скользящими Средними (SMA 5 - SMA 34).
В настройках индикатора вы можете изменить количество баров для вертикальных линий и любые параметры для AO и EMA – метод (SMA, Smoothed SMA, EMA и другие), длину, источник (open, high, low, close, hl2 и другие).
Candlestick Bias OscillatorCandlestick Bias Oscillator (CBO)
The Candlestick Bias Oscillator (CBO) with Signal Line is a pioneering indicator developed for the TradingView platform, designed to offer traders a nuanced analysis of market sentiment through the unique lens of candlestick patterns. This indicator stands out by merging traditional concepts of price action analysis with innovative mathematical computations, providing a fresh perspective on trend detection and potential market reversals.
Originality and Utility
At the core of the CBO's originality is its method of calculating the bias of candlesticks. Unlike conventional oscillators that may rely solely on closing prices or high-low ranges, the CBO incorporates both the body and wick of candlesticks into its analysis. This dual consideration allows for a more rounded understanding of market sentiment, capturing both the directional momentum and the strength of price rejections within a single oscillator.
Mathematical Foundations
1. Body Bias: The CBO calculates the body bias by assessing the relative position of the close to the open within the day's range, scaled to a -100 to 100 range. This calculation reflects the bullish or bearish sentiment of the market, based on the day's closing momentum.
Body Bias = (Close−Open)/(High−Low) x 100
Wick Bias: Similarly, the wick bias calculation takes into account the lengths of the upper and lower wicks, indicating rejection levels beyond the body's close. The balance between these wicks is scaled similarly to the body bias, offering insight into the market's indecision or rejection of certain price levels.
Wick Bias=(Lower Wick−Upper Wick)/(Total Wick Length) × 100
3. Overall Bias and Oscillator: By averaging the body and wick biases, the CBO yields an overall bias score, which is then smoothed over a user-defined period to create the oscillator. This oscillator provides a clear visual representation of the market's underlying sentiment, smoothed to filter out the noise.
4. Signal Line: A secondary smoothing of the oscillator creates the signal line, offering a trigger for potential trading signals when the oscillator crosses this line, indicative of a change in market momentum.
How to Use the CBO:
The CBO is versatile, suitable for various trading strategies, including scalping, swing trading, and long-term trend following. Traders can use the oscillator and signal line crossovers as indications for entry or exit points. The relative position of the oscillator to the zero line further provides insight into the prevailing market bias, enabling traders to align their strategies with the broader market sentiment.
Why It Adds Value:
The CBO's innovative approach to analyzing candlestick patterns fills a gap in the existing array of TradingView indicators. By providing a detailed analysis of both candle bodies and wicks, the CBO offers a more comprehensive view of market sentiment than traditional oscillators. This can be particularly useful for traders looking to gauge the strength of price movements and potential reversal points with greater precision.
Conclusion:
The Candle Bias Oscillator with Signal Line is not just another addition to the plethora of indicators on TradingView. It represents a significant advancement in the analysis of market sentiment, combining traditional concepts with a novel mathematical approach. By offering a deeper insight into the dynamics of candlestick patterns, the CBO equips traders with a powerful tool to navigate the complexities of the market with increased confidence.
Explore the unique insights provided by the CBO and integrate it into your trading strategy for a more informed and nuanced market analysis.
CARNAC Elasticity IndicatorThe CARNAC Elasticity Indicator (EI) is a technical analysis tool designed for traders and investors using TradingView. It calculates the percentage deviation of the current price from an Exponential Moving Average (EMA) and helps traders identify potential overbought and oversold conditions in a financial instrument.
Key Features:
EMA Length: Users can customize the length of the Exponential Moving Average (EMA) used in the calculations by adjusting the "EMA Length" parameter in the indicator settings.
Percentage Deviation: The indicator calculates the percentage deviation of the current price from the EMA. Positive values indicate prices above the EMA, while negative values indicate prices below the EMA.
Maximum Deviations: The indicator tracks the maximum positive (above EMA) and negative (below EMA) percentage deviations over time, allowing traders to monitor extreme price movements.
Bands: Upper and lower bands are displayed on the indicator chart at 100 and -100, respectively. Additionally, dashed middle bands at 50 and -50 provide reference points for moderate deviations.
Dynamic Color Coding: The indicator uses dynamic color coding to highlight the current percentage deviation. It turns red for values above 50 (indicating potential overbought conditions), green for values below -50 (indicating potential oversold conditions), and purple for values in between.
How to Use:
Overbought Conditions: Watch for the percentage deviation to cross above 50, indicating potential overbought conditions. This might be a signal to consider selling or taking profits.
Oversold Conditions: Look for the percentage deviation to cross below -50, signaling potential oversold conditions. This could be an opportunity to consider buying or entering a long position.
Historical Extremes: Keep an eye on the upper and lower bands (100 and -100) to identify historical extremes in percentage deviation.
The CARNAC Elasticity Indicator can be a valuable tool for traders seeking to identify potential trend reversals and assess the strength of price movements. However, it should be used in conjunction with other technical analysis tools and risk management strategies for comprehensive trading decisions.
Advanced Technical Range and Expectancy Estimator [SS]Hello everyone,
This indicator is a from of momentum based probability modelling. It is derived from my own approaches to probability modelling but just simplified a bit.
How it works:
The indicator looks at various technical, including stochastics, RSI, MFI and Z-Score, to determine the likely sentiment. All of these, with the exception of Z-Score, are momentum based indicators and can alert us to likely sentiment. However, instead of us making the subjective determination ourselves as to whether the RSI or MFI or Stochastics are bullish, the indicator will look at previous instances of these occurrences, and tally the bullish and bearish follow throughs that happened. It will also calculate the average target price that was hit, under similar conditions, on the same timeframe.
The Z-Score is your "tie breaker". It is not a momentum based indicator and measures something a little different (the standard deviation and over-extension of the stock). For this reason, it provides an alternative assessment and tends to be a bit more reliable in times of low momentum.
Back-test Results:
The indicator back-tests itself over the previous 100 candles. I have limited it to 100 candles for pragmatic considerations (it has to back-test each technical individually and increasing the BT length will slow and potentially error out the indicator) as well as accuracy considerations.
One thing I have noticed in my years of trying to crack the code and develop probability models for tickers, is historical accuracy doesn't always matter because sentiment is always changing. You need to see what it has done over the most recent 100 to 200 candles.
There are two back-test windows, one for the price targets and the other for the sentiment accuracy. The most effective/most accurate will highlight green, the least effective/least accurate will highlight red:
In the image above, you can see that the most accurate predictor of sentiment is Z-Score, with a 90.32% accuracy rate over the past 100 candles.
The most accurate predictor of price is MFI, with a 60% (for bull targets) and 42% (for bear targets)accuracy rate.
Anchoring Points:
The indicator permits you to anchor by two points. The default setting is anchoring by previous candle. If you plan to use this as an oscillator, to see the current prediction for the current candle you are viewing, then you will need to leave this default setting. It will pull the data from the previous candle and give you the data for the current candle you are on.
If you are assess the likely sentiment for the next day after the day has closed off, you will want to anchor by current candle. This will take the current technicals that the day has closed off with and run the assessment for you.
Customizability
You can customize the technicals by source and length of assessment.
They are all defaulted to the traditional settings of these indicators, but if you want to customize your model to try and improve or enhance accuracy in one way or another, you are free and able to do so!
I do suggest leaving the defaults as they seem to work particular well :-).
Thresholds
Thresholds are the tolerance levels that we permit for our technical search range. If you want them to be exactly identical, then you can set it to 0. If you want it to be extremely similar, you can set it to 0.01. This will hone in on the ranges you are interest in and you can see how it affects your accuracy by reviewing the results in the back-test tables.
Keep Static Colour Option
I want to make a quick note on the "Keep Static Colour" option that is in your settings menu.
The primary table that shows you the probability and price targets change colours based on the accuracy of the assessment. This is so, if you are using a mobile device or smaller screen and can't have the back-test results open at the same time, you can see still which are the most reliable results. However, if you have the back-test tables open and you find these colour changes too distracted, you can toggle on the "Keep Static Colour" and it will resort the colour of the table to a solid white:
Show Technicals
The indicator can show you the current technical values if you are using it in place of an oscillator. Its less pivotal as its making the assessment for you, but just for your reference if you want to see what the current MFI, Z-Score or Stochastics etc. are, you have that option as well.
All Timeframes Permitted
You can view Weekly, Monthly, Hourly, 5 minute, 1 minute, its all supported!
That's the indicator in a nutshell.
Hope you enjoy and leave your questions below.
Safe trades everyone!
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy
1. Introduction
Purpose of the Handbook:
The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios.
Overview of the Supertrend Advance Pullback Strategy:
At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals.
1. Basic Concept:
The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends.
2. Methodology:
Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise.
3. Benefits:
One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points.
4. Practical Applications:
The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies.
In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading.
As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors.
2. Getting Started
Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time.
Setting up on TradingView:
TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how:
1. Account Creation:
• Visit TradingView's official website.
• Click on the "Join for free" or "Sign up" button.
• Follow the registration process, providing the necessary details and setting up your login credentials.
2. Navigating the Dashboard:
• Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window.
• To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top.
3. Configuring Chart Settings:
• Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window.
• Adjust the chart type, time intervals, and other display settings to your preference.
Integrating the Strategy into a Chart:
Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy.
1. Accessing the Pine Script Editor:
• Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it.
• This is where custom strategies and indicators are scripted or imported.
2. Loading the Supertrend Advance Strategy Script:
• Depending on whether you have the script or need to find it, there are two paths:
• If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor.
• If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart.
3. Applying the Strategy:
• After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window.
4. Configuring Strategy Settings:
• Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings.
• Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing.
5. Interpreting Signals:
• With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions.
3. Strategy Overview
What is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals.
In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point.
Strategy Goals and Objectives:
1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor.
2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making.
3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability.
4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system.
Type of Assets/Markets to Apply the Strategy:
1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices.
2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders.
3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements.
4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters.
5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits.
It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades.
4. Input Settings
Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance.
Grouping Inputs:
Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator.
Strategy Choice:
This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available.
Supertrend Settings:
1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer.
2. Period: The number of bars used in the ATR calculation. A common default is 7.
EMA Settings (Exponential Moving Average):
1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200.
2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation.
RSI Settings (Relative Strength Index):
1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14.
2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70.
3. Oversold Level: The threshold at which the asset is considered oversold, often at 30.
MACD Settings (Moving Average Convergence Divergence):
1. Short Period: The shorter EMA, usually set to 12.
2. Long Period: The longer EMA, commonly set to 26.
3. Signal Period: Defines the EMA of the MACD line, typically set at 9.
CCI Settings (Commodity Channel Index):
1. Period: The number of bars used in the CCI calculation, often set to 20.
2. Overbought Level: Typically set at +100, denoting overbought conditions.
3. Oversold Level: Usually set at -100, indicating oversold conditions.
SL/TP Settings (Stop Loss/Take Profit):
1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss.
2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit.
Filtering Conditions:
This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions.
Trade Direction and Backtest Period:
1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both.
2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc.
It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy.
5. Understanding Strategy Conditions
Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point.
Basic Logic Behind Conditions:
Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future.
Buy and Sell Conditions:
1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum.
2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum.
Simple Strategy:
The simple strategy could involve using just the Supertrend indicator. Here:
• Buy: When price closes above the Supertrend line.
• Sell: When price closes below the Supertrend line.
Pullback Strategy:
This strategy capitalizes on price retracements:
• Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator.
• Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator.
Indicators Used:
EMA (Exponential Moving Average):
• Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish.
RSI (Relative Strength Index):
• Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold.
MACD (Moving Average Convergence Divergence):
• Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish.
CCI (Commodity Channel Index):
• Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition.
And others...
As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives.
Logic Behind Each Indicator:
1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels.
2. RSI: Indicates overbought and oversold conditions based on recent price changes.
3. MACD: Showcases momentum and direction of a trend by comparing two EMAs.
4. CCI: Measures the difference between a security's price change and its average price change.
Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets.
6. Trade Execution and Management
Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy.
Position Entry:
Effective trade entry revolves around:
1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators.
2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal.
3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover.
Position Exit Strategies:
A successful exit strategy will lock in profits and minimize losses. Here are some strategies:
1. Fixed Time Exit: Exiting after a predetermined period.
2. Percentage-based Profit Target: Exiting after a certain percentage gain.
3. Indicator-based Exit: Exiting when an indicator gives an opposing signal.
Percentage-based SL/TP:
• Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses.
• Example: A 2% SL on an entry at $100 would trigger a sell at $98.
• Take Profit (TP): Set a fixed percentage above the entry price to lock in gains.
• Example: A 5% TP on an entry at $100 would trigger a sell at $105.
Supertrend-based SL/TP:
• Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal.
• Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum.
Swing high/low-based SL/TP:
• Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high.
• Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support.
And other methods...
1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor.
2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages.
3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal.
Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance.
7. Visual Representations
Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance.
Understanding Plots on the Chart:
Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves.
1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day.
2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves.
Trend Lines:
Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance:
1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal.
2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend.
Filled Areas:
These represent a range between two values on a chart, usually shaded or colored. For instance:
1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility.
2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels.
Stop Loss and Take Profit Lines:
These are horizontal lines representing pre-determined exit points for trades.
1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance.
2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors.
Trailing Stop Lines:
A trailing stop is a dynamic form of stop loss that moves with the price. On a chart:
1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in.
2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises.
Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results.
8. Backtesting
Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of.
Setting Up Backtest Period:
1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years.
2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results.
3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments.
Analyzing Backtest Results:
1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency.
2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics.
3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss.
4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover.
9. Tips and Best Practices
Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy.
When to Use the Strategy:
1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets.
2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news.
3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume.
Adjusting Settings for Different Markets/Timeframes:
1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity.
2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes.
3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions.
10. Frequently Asked Questions (FAQs)
Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy.
1. What exactly is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals.
2. Can I use the Supertrend Advance Strategy for all asset types?
Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type.
3. Is this strategy suitable for day trading?
Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on.
4. How do I deal with false signals?
No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals.
5. Do I need any prior trading experience to use this strategy?
While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts.
6. How often should I review and adjust the strategy settings?
There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments.
7. Can the Supertrend Advance Strategy be automated?
Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended.
8. Are there any markets or conditions where the strategy shouldn't be used?
The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market.
9. How important is backtesting with this strategy?
Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades.
10. What if the strategy isn't working for me?
No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success.
Other comments
Value of combining several indicators in this script and how they work together
Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point.
Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced.
Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios.
Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market.
How do the different indicators in the Supertrend Advance Strategy work together?
Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends.
EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa.
RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend.
MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend.
CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points.
In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions.
Backtesting and Default Settings
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
• Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
