Fractal & Entropy Market Dynamics with Mexican Hat WaveletThis indicator combines fractal analysis, entropy, and wavelet theory to model market dynamics using a customized approach. It integrates advanced mathematical techniques to assess the complexity and structure of price action, while also incorporating volume and price volatility.
Key Concepts and Features:
Volume-Weighted Price:
The script calculates a volume-adjusted price using a moving average of volume to give more weight to periods with higher volume. This allows the indicator to account for the impact of trading volume on price movements, enhancing its sensitivity to significant price shifts.
Mexican Hat Wavelet Approximation:
The script employs the Mexican Hat Wavelet, a mathematical tool that approximates price movements based on the Laplacian of the price series. This helps capture localized oscillations in price, acting as a filter to highlight certain price dynamics over the specified length. This wavelet is commonly used to identify key inflection points and trends in financial data.
Fractal Dimension Calculation:
The fractal dimension is calculated to quantify the market's complexity. It measures how price moves between intervals, with higher values indicating chaotic or more volatile market behavior. This dimension captures the self-similarity in price movements across different time frames, a key feature of fractals.
Shannon Entropy Calculation:
Shannon Entropy is used to measure the randomness or uncertainty in the price action. It calculates the degree of unpredictability based on the price changes, providing insight into the market's informational efficiency. Higher entropy indicates more randomness, while lower entropy suggests more predictable trends.
Custom Normalization:
The script includes a custom normalization function that processes the composite score (derived from fractal dimension and entropy). This normalization helps scale the values into a consistent range, making it easier to interpret the output. The smoothing factor and RSI-based approach ensure that the normalized value reacts smoothly to the changes in market dynamics.
Composite Score:
The composite score is a weighted combination of the fractal dimension and entropy. This score aims to provide a holistic view of the market by combining the structural complexity (fractal) and randomness (entropy) into one unified metric.
Plotting and Visuals:
The indicator plots the normalized composite score on a scale where a baseline of 50 is provided for reference. The resulting plot helps traders visualize market dynamics, with the score fluctuating based on changes in the market's fractal dimension and entropy. A score above or below the baseline of 50 indicates potential market shifts.
Use Case:
The "Enhanced Fractal and Entropy Market Dynamics with Mexican Hat Wavelet" is useful for traders looking to identify market conditions where there is a balance between price structure and randomness. By integrating wavelets, fractals, and entropy, the indicator can provide insights into market complexity, helping traders recognize potential trend reversals, periods of consolidation, or increased volatility. This can be particularly effective for those employing swing trading or trend-following strategies
Pesquisar nos scripts por "swing trading"
RSI Fakeout Filter with SMA Confirmation [CHE] Introducing: RSI Fakeout Detection
Are you tired of being caught in fakeouts that can lead to frustrating losses? The RSI Fakeout Detection is here to enhance your trading strategy by filtering out false signals and providing you with more reliable entries. This innovative indicator is designed to help traders identify when market momentum, as indicated by the RSI, does not align with price movement – a key indicator of potential fakeouts!
What Does It Do?
The RSI Fakeout Detection focuses on one key goal: avoiding false signals. By monitoring when the RSI exceeds a customizable threshold (indicating strength) but the price remains below a moving average like the SMA, this indicator highlights situations where the market may seem strong, but the price action doesn't support that momentum. In other words, it saves you from those tricky fake breakouts.
Key Benefits:
1. Reduce Risk, Increase Confidence: Get an extra layer of protection against fakeouts by receiving signals only when both RSI and price confirm the market's true direction. Avoid entering false breakouts and trade with more confidence.
2. Dynamic Analysis of SMA Lengths: It doesn’t just rely on one SMA. The indicator automatically analyzes and sorts through different SMA lengths to find the most reliable one for your specific market condition, ensuring that you get the best possible signal.
3. Tailored for You: With customizable RSI thresholds, a choice of multiple moving average types (SMA, EMA, Bollinger Bands, and more), and vibrant color-coded visuals, this tool is built to fit your unique trading style and preferences.
4. Spot Fakeouts with Ease: Visual cues make it easy to see when the market might be tricking you. Labels, plotted lines, and a toggleable disclaimer keep everything transparent and easy to understand.
5. Friendly and Intuitive: Whether you’re new to trading or a seasoned pro, the RSI Fakeout Detection is designed to be simple and effective. The labels and plots are clear, the alerts are timely, and it seamlessly integrates into your chart without cluttering it.
Why Choose RSI Fakeout Detection?
- Accuracy and Precision: By combining RSI and SMA analysis, this indicator minimizes the risk of following false trends and entering trades too early.
- Save Time and Reduce Guesswork: No more spending hours trying to figure out which SMA length works best – the RSI Fakeout Detection does it for you!
- Peace of Mind: Avoiding fakeouts means fewer bad trades, which can lead to more consistent performance and less stress.
Transform the way you trade, and step into a more confident trading future with RSI Fakeout Detection . Whether you’re day trading or swing trading, this tool will give you an edge by helping you filter out the noise and make more informed decisions.
Best regards,
Chervolino
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Fx_Shepherd Lot Size Calculator [ALLDYN]This "Fx_Shepherd Lot Size Calculator" script is a basic yet essential tool designed for traders to calculate the appropriate lot size based on account balance, risk percentage, and stop-loss pips. It promotes disciplined risk management by ensuring that the user only risks a defined percentage of their account on each trade. The script also features a toggleable table that displays the account size, risk percentage, and calculated lot size, offering clear, real-time visualization for the user. This helps traders maintain consistency and avoid over-leveraging.
This "Fx_Shepherd Lot Size Calculator" script stands out as a unique utility for traders in several ways:
### 1. **Real-Time Lot Size Calculation**:
- The script provides an automatic, real-time calculation of the optimal lot size based on the account balance, risk percentage, and stop loss (SL) in pips. This offers traders immediate guidance on how much risk they are exposing their account to in each trade, streamlining risk management decisions.
### 2. **Dynamic Table Display**:
- The toggle-able table feature allows users to show or hide the lot size table on the chart. This makes the script non-intrusive for traders who may not want constant table overlays, providing more flexibility for chart space management.
### 3. **Customizable Inputs**:
- Inputs such as **balance**, **risk percentage**, and **stop loss** are easily configurable, allowing users to adjust the calculations to suit different trading strategies, account sizes, and risk tolerances.
- The `truncate()` function ensures the lot size is presented in a simple, rounded format, which is crucial for precise order placement and reduces the chance of errors.
### 4. **Responsive and Clean UI**:
- The table is color-coded for easy reading, with a sleek design that places key information — account size, risk percentage, and calculated lot size — in a clear, organized structure. The black background with white text for the data points improves readability, while the border and table cell colors (green and black) provide a professional look.
### 5. **Risk Management Focus**:
- The primary purpose of this script is to ensure that traders maintain consistent risk management by aligning their lot size with their defined risk per trade and stop loss distance. This automated approach to risk ensures that traders stay disciplined with risk exposure.
### 6. **Efficiency for All Trading Styles**:
- Whether a trader is scalping, day trading, or swing trading, this calculator adjusts dynamically, allowing it to be used across various timeframes and asset classes. It helps traders avoid manual calculations for each trade, thus improving efficiency and reducing human error.
### 7. **Non-Intrusive Clean-Up**:
- The feature to **clear** the table when not needed ensures the chart remains clean and decluttered when the table is hidden. This improves the user experience, especially for traders who switch between different strategies or charts.
Overall, this script combines simplicity and efficiency while being flexible enough to fit the needs of a broad spectrum of traders. Its focus on user customization, clean interface, and emphasis on risk management makes it a valuable tool for both novice and experienced traders.
True Strength Index with Buy/Sell Signals and AlertsThe True Strength Index (TSI) is a momentum oscillator that helps traders identify trends and potential reversal points in the market. Here’s how it works:
1. **Price Change Calculation**:
- **`pc = ta.change(price)`**: This calculates the change in price (current price minus the previous price).
2. **Double Smoothing**:
- **`double_smooth(src, long, short)`**: This function smooths the price change data twice using two Exponential Moving Averages (EMAs):
- The first EMA smooths the raw data.
- The second EMA smooths the result of the first EMA.
- **`double_smoothed_pc`**: The double-smoothed price change.
- **`double_smoothed_abs_pc`**: The double-smoothed absolute price change, which helps normalize the TSI value.
3. **TSI Calculation**:
- **`tsi_value = 100 * (double_smoothed_pc / double_smoothed_abs_pc)`**: This calculates the TSI by dividing the double-smoothed price change by the double-smoothed absolute price change, then multiplying by 100 to scale the value.
- The TSI oscillates around the zero line, indicating momentum. Positive values suggest bullish momentum, while negative values suggest bearish momentum.
4. **Signal Line**:
- **`signal_line = ta.ema(tsi_value, signal)`**: This creates a signal line by applying another EMA to the TSI value. The signal line is typically used to identify entry and exit points.
5. **Buy and Sell Signals**:
- **Buy Signal**: Occurs when the TSI crosses above the signal line (`ta.crossover(tsi_value, signal_line)`), indicating that bullish momentum is strengthening, which might suggest a buying opportunity.
- **Sell Signal**: Occurs when the TSI crosses below the signal line (`ta.crossunder(tsi_value, signal_line)`), indicating that bearish momentum is strengthening, which might suggest a selling opportunity.
6. **Visual Representation**:
- The TSI line and the signal line are plotted on the chart.
- Buy signals are marked with green "BUY" labels below the bars, and sell signals are marked with red "SELL" labels above the bars.
**How to Use It**:
- **Trend Identification**: When the TSI is above zero, it suggests an uptrend; when it's below zero, it suggests a downtrend.
- **Buy/Sell Signals**: Traders often enter a buy trade when the TSI crosses above the signal line and enter a sell trade when the TSI crosses below the signal line.
- **Divergences**: TSI can also be used to spot divergences between the indicator and price action, which can signal potential reversals.
The TSI is particularly useful in identifying the strength of a trend and the potential turning points, making it valuable for trend-following and swing trading strategies.
Landry Light with Moving AverageLandry Light with Moving Average
Overview:
This Pine Script, titled "Landry Light with Moving Average", visualizes the relationship between price action and a chosen moving average (MA) over time. It helps users easily identify periods where the price stays consistently above or below the moving average, which can be a useful indicator of bullish or bearish trends.
Key Features:
Moving Average Type Selection:
The script allows users to choose between two types of moving averages:
Exponential Moving Average (EMA)
Simple Moving Average (SMA)
This is done via a user input option, enabling traders to tailor the indicator to their preferred analysis method.
Moving Average Length:
Users can set the length of the moving average (default is 21 periods). This allows customization based on the trader's time frame, whether short-term or long-term analysis.
Dynamic Moving Average Color:
The moving average line changes color based on the relationship between the price and the MA:
Green: Price is consistently above the MA (bullish condition).
Red: Price is consistently below the MA (bearish condition).
Blue: Price is crossing or close to the MA (neutral or indecisive condition).
Cumulative Days Above/Below MA:
The script tracks and displays the number of consecutive days the price remains above or below the moving average:
Cumulative Days Above: Shown as a green histogram above the zero line.
Cumulative Days Below: Shown as a red histogram below the zero line.
This feature helps users identify sustained trends or potential reversals.
Real-time Labels:
The script generates dynamic labels that display the count of cumulative days the price has stayed above or below the moving average.
These labels are positioned near the moving average on the chart, providing an easy reference for traders.
How Users Can Benefit:
Trend Identification:
By visually representing how long the price stays above or below a key moving average, traders can identify strong bullish or bearish trends. This can inform entry and exit points.
Visualizing Market Sentiment:
The colored moving average line and histogram help traders quickly assess market sentiment. A prolonged green MA line suggests a strong uptrend, while a prolonged red line indicates a downtrend.
Adaptability:
With customizable moving average types and lengths, the indicator can be tailored to fit various trading strategies, whether for day trading, swing trading, or long-term investing.
Reversal Signals:
A shift from cumulative days above to cumulative days below (or vice versa) can serve as an early signal of a potential market reversal, allowing traders to adjust their positions accordingly.
Simplified Decision-Making:
The combination of visual cues (colors, histograms, and labels) simplifies decision-making, allowing traders to focus on trend strength rather than complex calculations.
Usage:
To use this script:
Add the Indicator to Your Chart:
Select the desired moving average type and length.
The script will plot the moving average, colored by the trend, and display cumulative days above or below it.
Interpret the Signals:
Use the histogram and labels to gauge the strength of the trend.
Monitor color changes in the moving average for potential trend reversals.
Incorporate into Your Strategy:
Combine this indicator with other tools (e.g., volume analysis, RSI) to confirm signals and refine your trading strategy.
This indicator is particularly useful for traders who follow the "Landry Light" concept, emphasizing the importance of price staying above or below a moving average to determine trend strength.
Ceres Trader MTF Triple EMA with SmoothingDescription:
The "Ceres Trader MTF EMA with Smoothing" indicator is a versatile tool designed for traders who rely on Exponential Moving Averages (EMAs) for their technical analysis. This indicator uniquely blends the concept of EMAs with customizable smoothing techniques, enhancing the clarity and interpretability of moving average lines on your charts.
Features:
Triple EMA Visualization: Visualize three distinct EMAs on your chart, each customizable in terms of length, timeframe, and color. This triple-layer approach allows for a comprehensive view of price trends across different time periods.
User-defined EMA Lengths: Set the lengths of all three EMAs according to your trading strategy. The default length is set at 20 bars, but this can be easily adjusted to suit different trading styles and timeframes.
Flexible Timeframes: Each EMA can be plotted based on different timeframes, providing a multi-timeframe analysis within a single chart view.
Smoothing Techniques: Choose from five different smoothing methods (SMA, EMA, SMMA, WMA, VWMA) to refine the EMA lines. This feature reduces market “noise” and helps in identifying the true underlying trends.
Enhanced Smoothing for Longer Timeframes: The indicator applies an advanced double smoothing technique to the EMA of the longest timeframe, offering an even smoother line that is beneficial for long-term trend analysis.
Customizable Aesthetics: Personalize the appearance of each EMA line with a selection of colors, enhancing visual differentiation and readability.
Benefits:
Versatility: Suitable for various trading styles, including swing trading, day trading, and long-term trend following.
Clarity in Trend Analysis: The smoothing techniques help in filtering out market noise, making it easier to identify meaningful trends.
Multi-Timeframe Analysis: The ability to view EMAs from different timeframes simultaneously offers a comprehensive analysis, saving time and enhancing decision-making.
Ideal for: Traders looking for a customizable and insightful way to use EMAs in their market analysis. Whether you are a beginner or an experienced trader, this indicator's flexibility and depth can add significant value to your technical analysis toolkit.
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.
Panoramic VWAP### Panoramic VWAP Indicator Overview
The Panoramic VWAP indicator provides a way to display up to four Volume Weighted Average Price (VWAP) lines on a chart, each anchored to different timeframes. This indicator also includes options for displaying standard deviation bands and close lines, offering a comprehensive view of price action across multiple time horizons.
### Key Features
Quad VWAPs : The indicator allows for the display of four VWAP lines simultaneously. Each line can be set to a different timeframe, enabling traders to analyze market conditions across various periods on a single chart.
Standard Deviation Bands : Users can enable bands around each VWAP line, which represent standard deviations or percentage levels from the VWAP. These bands help in assessing volatility and identifying potential overbought or oversold conditions.
Close Lines : The indicator includes an option to show close lines, marking the price's closing level relative to the VWAP. This feature is useful for examining how the market closes in relation to VWAP, which can be important for understanding trend strength or potential reversals.
### How It Looks
VWAP Lines : Multiple VWAP lines are displayed, each reflecting different timeframes. The lines change color depending on whether the price is above or below the VWAP, indicating bullish or bearish momentum.
Bands : Optional bands around the VWAP lines provide a visual indication of volatility, with the potential to identify overbought or oversold areas.
Close Lines : These lines represent the price's closing level relative to the VWAP and can be displayed to add further context to the analysis.
### How to Use It
Trend Analysis :
- Price above a VWAP line indicates bullish momentum .
- Price below a VWAP line suggests bearish momentum .
Support and Resistance :
- VWAP lines often act as dynamic support and resistance. Price approaching a VWAP line from above may find support, while approaching from below may encounter resistance.
Volatility Assessment :
- Bands around the VWAP lines can signal areas of potential reversal. Upper bands may indicate overbought conditions, while lower bands may indicate oversold conditions.
Multiple Timeframe Analysis :
- The ability to display VWAPs from different timeframes simultaneously allows for the identification of confluence zones, where multiple VWAP levels align, indicating potentially significant support or resistance levels.
Customization :
- The indicator settings are customizable, allowing users to choose which VWAP lines, bands, and close lines to display, along with adjustments for visual preferences like line thickness and colors.
### Practical Application
Intraday Trading : Traders can use the VWAPs and bands to identify potential entry and exit points during the trading day based on price interactions with these levels.
Swing Trading : Monitoring VWAP lines across different timeframes can help identify key levels where price might reverse or gain momentum, aiding in decisions about holding or exiting positions.
Long-Term Analysis : VWAP lines on higher timeframes can serve as dynamic support or resistance levels, providing context for long-term trend analysis and investment decisions.
The Panoramic VWAP indicator allows for a detailed analysis of price trends and levels across multiple timeframes, combining VWAPs, standard deviation bands, and close lines in a single, customizable tool.
Oster's Fair Economy (OFE)Overview:
Oster's Fair Economy (OFE) is a powerful tool designed to give traders and investors a comprehensive assessment of the fair value of major stock indices . Unlike conventional indicators that focus solely on technical analysis, OFE emphasizes economic metrics to offer a deeper understanding of the market's intrinsic value. By applying Oster's method (explained below), OFE determines the fundamental fair price of key indices, making it an invaluable tool for top-down analysis and market confirmation. It is particularly useful for swing trading on indices and as a top-down confirmation for individual stock trades.
Important Note:
OFE is designed for use with indices, not individual stocks : Stocks are often driven by their own fundamental factors, such as earnings, revenue, and dividend yields, which may not align with broad economic metrics. While OFE can sometimes provide insights into individual stocks, particularly those highly correlated with broader market trends, it is specifically intended for index analysis.
OFE is optimized for Weekly Candles (W ): OFE is most effective when used with weekly data, as it aligns with the longer-term outlook of economic analyses. While it can be used with smaller timeframes, weekly data is recommended for the most accurate insights.
Innovative Approach to Economic Analysis:
OFE integrates a unique combination of key economic metrics , including:
Gross National Product (GNP)
Consumer Price Index (CPI)
Unemployment Rate (UR)
Interest Rate (e.g., FED)
Nonfarm Payrolls (NFP)
Retail Sales (RS)
Industrial Production (IP)
Balance Of Trade (BOT)
Money Supply M2 (M2)
Consumer Confidence Index (CCI)
These metrics are tailored for 20 different markets : United States (US), Canada (CA), European Union (EU), Germany (DE), United Kingdom (GB), France (FR), Italy (IT), Switzerland (CH), Spain (ES), Australia (AU), New Zealand (NZ), Japan (JP), China (CN), Hong Kong (HK), South Korea (KR), India (IN), Russia (RU), Brazil (BR), Mexico (MX), and Saudi Arabia (SA).
This comprehensive set of data allows traders to gauge the potential for growth, inflation, and overall market conditions . OFE's weighting system reflects the importance of these metrics in determining the fair value of indices according to Oster's methodology .
How OFE Works:
OFE's calculation methodology is designed to provide insights into whether an index is fundamentally overvalued, undervalued, or trading at fair value by comparing its price dynamics with economic data. Here’s a step-by-step breakdown of how OFE works:
Economic Data Collection : OFE retrieves relevant economic data from the selected region, such as GDP, CPI, and interest rates. If specific market data is unavailable, OFE defaults to the US market as a fallback.
Normalization and Weighting : The collected economic metrics are normalized against historical trends to ensure that the data reflects both current levels and long-term averages. For example, GDP growth rates are normalized based on historical data, allowing for a comparison across different economic periods. Similarly, CPI and unemployment rates are adjusted to account for historical context, ensuring that high inflation or unemployment is appropriately weighed relative to past conditions. However, all other macroeconomic key figures are also processed in the same way.
Relating Economic Metrics to Price Dynamics : OFE calculates specific ratios by comparing the selected index’s price with the normalized economic data. These ratios, such as the GNP ratio, are then analyzed within the context of historical performance. The goal is to establish a relationship between the economic indicators and the index’s historical price behavior. For instance, if the GNP ratio is currently higher than historical norms, it could suggest that the index is overvalued relative to the economy’s actual productivity.
Fair Value Calculation : Based on the derived ratios and their historical correlations with index prices, OFE computes a fair value for the index. This calculation integrates multiple economic indicators, each weighted according to its perceived importance in influencing the index. For example, in a high-growth environment, GDP and industrial production might carry more weight, whereas in a recession, unemployment and interest rates could become more influential. The resulting fair value reflects the index's price adjusted for the current economic environment.
Price Comparison : The calculated fair value is then compared to the current market price of the index. If the market price significantly deviates from the fair value, it suggests that the index is either overvalued or undervalued. For example, if the fair value of the S&P 500 is calculated to be 10% lower than its current market price, OFE would indicate that the index might be overvalued, potentially signaling a market correction. The fair price line basically acts as a kind of magnet that keeps attracting the index price. This is because, in the longer term, the broad market is always guided by the economic health of the country in concerned.
Market Dynamics Consideration : By adjusting the "Strictness" level in OFE, users can control how sensitive the fair value calculation is to economic fundamentals. A higher strictness level would highlight discrepancies between the fair value and the market price more aggressively, suggesting a higher likelihood of market mispricing. Conversely, a lower strictness level allows for greater flexibility, acknowledging that markets can sometimes deviate from fundamental values without immediate correction.
Customizable Parameters for Tailored Analysis:
OFE offers extensive customization options to align with your specific investment strategy. Users can:
Select or deselect economic metrics for inclusion.
Adjust the weighting of each metric to reflect its importance in their analysis.
Fine-tune the strictness of the valuation process (as explained above).
Additionally, users can compare different indices with various macroeconomic data sets . For example, you might select the DAX index and apply US economic data to see how the index would perform if driven by US market fundamentals. This feature enables a highly tailored and region-specific analysis, empowering traders to align OFE with their individual perspectives and market outlooks.
Interpretation:
If the calculated fair price is above the current index value, the index is considered fundamentally undervalued, indicating potential for price increases. Conversely, if the fair price is below the current index value, the index is seen as overvalued, suggesting potential risks or a possible correction. The fair price acts as a gravitational force, pulling the index toward its true economic value over time.
This over- or undervaluation can also serve as an overarching economic confirmation for stock trading . For example, it might be advantageous to buy individual stocks when the broader market is fundamentally undervalued, as the general upward potential of the market could support stock price increases. Conversely, selling or avoiding stocks when the broader market is overvalued could help mitigate potential risks, as the market may be primed for a correction.
Conclusion:
Oster's Fair Economy (OFE) bridges the gap between technical simplicity and the depth of macroeconomic analysis . By integrating complex economic metrics with user-friendly customization, OFE empowers traders and investors to assess the fair valuation of indices confidently . This tool is ideal for confirming market trends and gaining a broader understanding of the economic landscape, making it a valuable asset in any investment toolkit.
Money Flow Profile [Angel Algo]Money Flow Profile
Overview
This indicator is designed to analyze trading activity and identify key supply and demand zones using volume and money flow data. It is an advanced tool for traders who want to incorporate volume profile analysis into their trading strategy, enhancing their ability to spot potential reversal zones and understand market sentiment.
Features
1. Customizable Lookback Period
Description: Users can specify the number of bars to consider in the volume profile calculation, allowing for flexible analysis over different periods.
Functionality: This setting adjusts the depth of historical data analyzed, enabling traders to tailor the indicator to various trading styles and timeframes.
2. Row Size Configuration
Description: This input determines the number of rows (or price levels) displayed in the volume profile.
Functionality: By adjusting the row size, traders can get a more granular or more generalized view of trading activity at different price levels.
3. Data Source Selection
Options: Volume, Money Flow
Description: Traders can choose between using traditional volume data or money flow for the volume profile calculation.
Functionality: Money flow incorporates both price and volume to give a more comprehensive view of market buying and selling pressure, while volume focuses solely on trading activity.
Volume:
Money Flow:
4. Color Gradient for Volume Intensity
Description: The script allows setting maximum and minimum colors to create a gradient that visually represents the intensity of trading activity.
Functionality: This visual aid helps traders quickly identify areas of high and low trading activity, enhancing the interpretability of the volume profile.
Advanced Analysis: Supply and Demand Zones
1. Sentiment Analysis-Based Zoning
Description: The script analyzes the volume profile bars above and below the current close price to detect zones with significant buying or selling pressure.
Methodology:
Supply Zones: Identified by analyzing bars above the current close and finding the area with the highest selling pressure, indicated by volume delta.
Demand Zones: Identified by analyzing bars below the current close and finding the area with the highest buying pressure.
2. Volume Delta Calculation
Description: Volume delta, the difference between buy and sell volumes, is used to gauge the strength of buying or selling pressure at each price level.
Functionality: This calculation helps pinpoint the most significant supply and demand zones, providing traders with potential entry and exit points based on market sentiment.
Usage Scenario
This indicator is particularly useful for traders who focus on intraday trading, swing trading, or any strategy that benefits from understanding volume dynamics and sentiment at specific price levels. It allows traders to visually assess which levels are likely to act as resistance or support, based on historical trading activity and current market sentiment.
Conclusion
By integrating both traditional and innovative analytical methods, this Indicator offers a powerful tool for market analysis. Its flexibility and depth provide traders with valuable insights into market dynamics.
Outside Bar ProbabilityOutside Bar Percentage by Hour Indicator
Description:
The "Outside Bar Percentage by Hour" indicator is a powerful tool designed to analyze the occurrence of outside bars within each hour of the trading day. This indicator not only tracks the frequency of these key market events but also provides a detailed breakdown of their distribution, allowing traders to identify potential patterns and key trading hours.
What It Does:
Outside Bar Detection: The indicator identifies "outside bars," which occur when the high of a bar is higher than the previous bar's high, and the low is lower than the previous bar's low. These bars often signal significant market moves and potential reversals.
Hourly Analysis: The script tracks the total number of bars and outside bars for each hour (0 to 23) of the trading day. This granular analysis helps traders pinpoint specific hours when outside bars are more likely to occur.
Percentage Calculation: It calculates the percentage chance of an outside bar occurring for each hour, based on the total bars observed. This percentage provides a clear view of the likelihood of encountering an outside bar within a given hour, which can be critical for timing entries and exits.
Visual Representation: The data is displayed in a table format directly on the chart, showing:
Hour: The specific hour of the day.
Total Bars: The total number of bars observed during each hour.
Outside Bar Count: The number of outside bars detected in that hour.
Percentage: The calculated percentage chance of an outside bar occurring in each hour.
How It Works:
The indicator uses a loop to analyze each bar in real-time, checking if it qualifies as an outside bar. It then records the occurrence in arrays that track data for each hour.
At the start of each new day, the counts are reset to ensure the data remains relevant and accurate.
The percentage chance of an outside bar occurring is computed using the formula: (Outside Bar Count / Total Bar Count) * 100.
The results are neatly organized in a table that updates dynamically, providing traders with real-time insights.
How to Use It:
Identify Key Trading Hours: Use the table to observe the distribution of outside bars across different hours. This can help you identify when significant market moves are more likely to occur.
Time Your Entries and Exits: Understanding the likelihood of outside bars can assist in timing your trades, particularly if you use strategies that rely on volatility or market reversals.
Market Analysis: The percentage data can provide insights into the market's behavior during specific times, helping you refine your trading strategy based on historical patterns.
Concepts Underlying the Calculations:
The script leverages the concept of "outside bars," which are often considered indicators of potential reversals or significant market movements. By analyzing these bars across different hours, the indicator provides a temporal dimension to market analysis, helping traders understand when these pivotal events are most likely to occur.
The detailed hourly breakdown and percentage calculations offer a nuanced view of market activity, making it a valuable tool for traders looking to enhance their timing and strategic decision-making.
This indicator is suitable for all types of traders, including those focused on day trading, swing trading, or even longer-term analysis. It provides a unique perspective on market activity that can complement other technical indicators and analyses.
Comprehensive Market Overview1. What is this indicator about?
The "Comprehensive Market Overview" indicator provides a holistic view of the market by incorporating several key metrics:
Close Price: Displays the current close price below each candle.
Percent from All-Time High: Calculates how far the current close price is from the highest high observed over a specified period.
RSI (Relative Strength Index): Measures the momentum of price movements to assess whether a stock is overbought or oversold.
Volume Gain: Computes the current volume relative to its 20-period simple moving average (SMA), indicating volume strength or weakness.
Volatility: Quantifies market volatility by calculating the ratio of the Bollinger Bands' width (difference between upper and lower bands) to the SMA.
2. How it works?
Close Price Label: This label is displayed below each bar, showing the current close price.
Percent from All-Time High: Calculates the percentage difference between the highest high observed (all-time high) and the current close price.
RSI Calculation: Computes the RSI using a 14-period setting, providing insight into whether a stock is potentially overbought or oversold.
Volume Strength: Computes the current volume divided by its 20-period SMA, indicating whether volume is above or below average.
Volatility Calculation: Calculates the width of the Bollinger Bands (based on a 20-period SMA and 2 standard deviations) and expresses it as a percentage of the SMA, providing a measure of market volatility
3.Correct Trend Identification with Indicators
All-Time High (ATH) Levels:
Low Value (Near ATH): When the percent from ATH is low (close to 0%), it indicates that the current price is near the all-time high zone. This suggests strong bullish momentum and potential resistance levels.
High Value (Below ATH): A high percentage from ATH indicates how much the current price is below the all-time high. This could signal potential support levels or opportunities for price recovery towards previous highs.
RSI (Relative Strength Index):
Overbought (High RSI): RSI values above 70 typically indicate that the asset is overbought, suggesting a potential reversal or correction in price.
Oversold (Low RSI): RSI values below 30 indicate oversold conditions, suggesting a potential rebound or price increase.
Swing Trading Strategies
Confirmation with Visual Analysis: Visualizing the chart to confirm ATH levels and RSI readings can provide strong indications of market sentiment and potential trading opportunities:
Bullish Signals: Look for prices near ATH with RSI confirming strength (not yet overbought), indicating potential continuation or breakout.
Bearish Signals: Prices significantly below ATH with RSI showing weakness (not yet oversold), indicating potential for a bounce or reversal.
Volume Confirmation: Comparing current volume to its SMA helps confirm the strength of price movements. Higher current volume relative to the SMA suggests strong price action.
Volatility Assessment: Monitoring volatility through the Bollinger Bands' width ratio helps assess potential price swings. Narrow bands suggest low volatility, while wide bands indicate higher volatility and potential trading opportunities.
4.Entry and Exit Points:
Entry: Consider entering long positions near support levels when prices are below ATH and RSI is oversold. Conversely, enter short positions near resistance levels when prices are near ATH and RSI is overbought.
Exit: Exit long positions near resistance or ATH levels when prices show signs of resistance or RSI becomes overbought. Exit short positions near support levels or when prices rebound from oversold conditions.
Risk Management: Always incorporate risk management techniques such as setting stop-loss orders based on support and resistance levels identified through ATH and RSI analysis.
Implementation Example
Significant Volume with Price Changes HighlightedSignificant Volume with Price Changes Highlighted
The "Significant Volume with Price Changes Highlighted" indicator by PappyTrading is a powerful tool designed to help traders identify significant volume spikes and price changes in the market. This indicator overlays the volume bars on the price chart and highlights them based on specific volume and price change conditions, providing a clear visual representation of market activity.
What It Does
This indicator calculates the moving average of the volume over a specified period and compares the current volume to this average. It also calculates the daily percentage change relative to the previous day's close and compares this to its moving average. The volume bars are then color-coded based on the following conditions:
Bright Green (#089981): Indicates a significant volume spike with an above-average price increase.
Bright Red (#f23645): Indicates a significant volume spike with an above-average price decrease.
Green with 60% transparency: Indicates a normal up day with a price increase but not a significant volume spike.
Red with 60% transparency: Indicates a normal down day with a price decrease but not a significant volume spike.
Additionally, the indicator plots a 20-period simple moving average (SMA) of the volume, providing a reference point to understand the general volume trend.
How It Works
Volume Calculation:
The indicator calculates the 20-period SMA of the volume and compares the current volume to this average to determine if there is a significant volume spike.
Price Change Calculation:
The indicator calculates the daily percentage change in price relative to the previous day's close and compares this to the 20-period SMA of the percentage change to identify significant price movements.
Color Coding:
The volume bars are color-coded based on the combination of the volume and price change conditions. This visual representation allows traders to quickly identify significant market activities.
How to Use It
Overlay on Chart:
Add the "Significant Volume with Price Changes Highlighted" indicator to your chart. The volume bars will be displayed at the bottom of the chart, color-coded based on the conditions described above.
Identify Market Activity:
Use the color-coded volume bars to identify significant market activities. Bright green bars indicate strong buying pressure, while bright red bars indicate strong selling pressure. Transparent green and red bars indicate normal market activity without significant volume spikes.
Volume Moving Average:
The blue line represents the 20-period SMA of the volume. Use this as a reference to understand the general volume trend and identify deviations from the average.
Concepts Underlying the Calculations
Volume Spikes: Significant volume spikes often precede or accompany major market moves. By highlighting these spikes, traders can gain insights into potential market turning points or continuation patterns.
Price Changes: Large price changes relative to the previous day's close indicate strong market momentum. By comparing these changes to their moving average, the indicator helps traders identify unusually strong buying or selling pressure.
This indicator is ideal for traders who want to gain a deeper understanding of market dynamics by analyzing volume and price changes together. It is suitable for various trading styles, including trend following, swing trading, and scalping.
RSI DeviationAn oscillator which de-trends the Relative Strength Index. Rather, it takes a moving average of RSI and plots it's standard deviation from the MA, similar to a Bollinger %B oscillator. This seams to highlight short term peaks and troughs, Indicating oversold and overbought conditions respectively. It is intended to be used with a Dollar Cost Averaging strategy, but may also be useful for Swing Trading, or Scalping on lower timeframes.
When the line on the oscillator line crosses back into the channel, it signals a trade opportunity.
~ Crossing into the band from the bottom, indicates the end of an oversold condition, signaling a potential reversal. This would be a BUY signal.
~ Crossing into the band from the top, indicates the end of an overbought condition, signaling a potential reversal. This would be a SELL signal.
For ease of use, I've made the oscillator highlight the main chart when Overbought/Oversold conditions are occurring, and place fractals upon reversion to the Band. These repaint as they are calculated at close. The earliest trade would occur upon open of the following day.
I have set the default St. Deviation to be 2, but in my testing I have found 1.5 to be quite reliable. By decreasing the St. Deviation you will increase trade frequency, to a point, at the expense of efficiency.
Cheers
DJSnoWMan06
Ichimoku LuqThis custom indicator enhances the traditional Ichimoku Cloud by allowing users to specify a custom timeframe for its calculation. The Ichimoku Cloud, also known as Ichimoku Kinko Hyo, is a versatile and comprehensive indicator that defines support and resistance, identifies trend direction, gauges momentum, and provides trading signals.
Key Features:
Custom Timeframe: Unlike the standard Ichimoku Cloud, which operates on the chart's default timeframe, this indicator allows you to select a custom timeframe for its calculations. This flexibility enables you to analyze market trends and signals from different time perspectives without changing your chart's timeframe.
Comprehensive Market Analysis:
Tenkan-sen (Conversion Line): A moving average of the highest high and the lowest low over the last 9 periods.
Kijun-sen (Base Line): A moving average of the highest high and the lowest low over the last 26 periods.
Senkou Span A (Leading Span A): The average of the Tenkan-sen and Kijun-sen, plotted 26 periods ahead.
Senkou Span B (Leading Span B): A moving average of the highest high and the lowest low over the past 52 periods, plotted 26 periods ahead.
Chikou Span (Lagging Span): The closing price plotted 26 periods back.
Visual Cloud: The area between Senkou Span A and Senkou Span B creates the cloud (Kumo), which is used to identify future support and resistance levels. The cloud changes color based on whether Senkou Span A is above or below Senkou Span B.
Trend Identification:
Bullish Signals: Occur when the price is above the cloud, and the cloud is green.
Bearish Signals: Occur when the price is below the cloud, and the cloud is red.
Neutral Signals: Occur when the price is within the cloud.
Momentum and Signal Confirmation: The interactions between the Tenkan-sen and Kijun-sen, as well as the position of the Chikou Span relative to past prices, provide additional confirmation for trading signals.
How to Use:
Setting the Custom Timeframe: In the indicator settings, select your desired custom timeframe. This allows you to adapt the Ichimoku Cloud analysis to different market conditions and trading strategies.
Interpreting Signals: Use the traditional Ichimoku signals (e.g., crosses of the Tenkan-sen and Kijun-sen, cloud breakouts, etc.) while considering the custom timeframe for a broader market perspective.
Combining with Other Analysis: This indicator can be used alongside other technical analysis tools to enhance your trading strategy and gain more comprehensive market insights.
Benefits:
Flexibility: Analyze market trends from multiple time perspectives without altering your main chart timeframe.
Enhanced Decision Making: Gain deeper insights into market trends, support, and resistance levels.
Versatility: Suitable for various trading strategies, including day trading, swing trading, and long-term investing.
Chirant Orderblocks and LiquidityIntroduction
Our Pivot-Based Order Block Indicator is a cutting-edge trading tool designed to offer traders an unparalleled edge in the markets. This unique indicator combines pivot-based order blocks, fair value gaps, exponential moving averages (EMAs), and vector candles into a cohesive strategy. Unlike traditional indicators, this tool leverages the synergistic effects of these components to identify high-probability trading setups.
How It Works
Pivot-Based Order Blocks: At the heart of our indicator are pivot-based order blocks. These are price levels or ranges that are significant due to past market activity. Our algorithm identifies these blocks based on historical pivot points, considering both the price's reaction to these levels and their recurrence over time. This method helps in pinpointing areas where institutional orders are likely to be placed.
Fair Value Gaps: Alongside, our indicator detects fair value gaps - regions where price has moved too swiftly, leaving a gap in the market's valuation. By identifying these gaps, the tool helps traders anticipate areas where price might return to fill the gap, offering strategic entry and exit points.
EMAs and Vector Candles: To refine our signals, the indicator utilizes a combination of exponential moving averages and vector candles. EMAs help in determining the market's trend direction, while vector candles offer insights into the momentum and strength of price movements. The integration of these elements enables our tool to filter out lower probability setups, focusing on those with higher chances of success.
Originality and Usefulness
Our Pivot-Based Order Block Indicator is not merely a combination of existing tools. It represents a novel approach to market analysis, integrating various components into a single, comprehensive trading strategy. The methodology behind combining pivot-based order blocks with fair value gaps and EMAs, supplemented by the unique use of vector candles, is proprietary and designed to offer original insights into market dynamics.
This tool is invaluable for traders looking to enhance their market analysis, providing a deeper understanding of price movements and potential reversal points. Whether for scalping, day trading, or swing trading, our indicator offers versatile applications, helping traders to navigate the complexities of various market conditions with greater confidence.
How to Use
To make the most of our Pivot-Based Order Block Indicator:
Setup: Apply the indicator to any chart or time frame, tailoring the EMA settings according to your trading style.
Interpretation: Look for confluences between pivot-based order blocks and fair value gaps as high-probability entry points. EMAs will guide you on the trend's direction, while vector candles highlight momentum strength.
Application: Use the indicator to identify potential reversal zones, entry, and exit points. Combine it with your risk management strategy to optimize your trading performance.
Conclusion
Our Pivot-Based Order Block Indicator is crafted for traders who demand depth, precision, and originality in their tools. It stands out by providing a multifaceted approach to market analysis, backed by a proprietary integration of critical trading concepts. This tool is not just an indicator; it's a comprehensive strategy designed to elevate your trading journey.
Neural Network Synthesis: Trend and Valuation [QuantraSystems]Neural Network Synthesis - Trend and Valuation
Introduction
The Neural Network Synthesis (𝓝𝓝𝒮𝔂𝓷𝓽𝓱) indicator is an innovative technical analysis tool which leverages neural network concepts to synthesize market trend and valuation insights.
This indicator uses a bespoke neural network model to process various technical indicator inputs, providing an improved view of market momentum and perceived value.
Legend
The main visual component of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is the Neural Synthesis Line , which dynamically oscillates within the valuation chart, categorizing market conditions as both under or overvalued and trending up or down.
The synthesis line coloring can be set to trend analysis or valuation modes , which can be reflected in the bar coloring.
The sine wave valuation chart oscillates around a central, volatility normalized ‘fair value’ line, visually conveying the natural rhythm and cyclical nature of asset markets.
The positioning of the sine wave in relation to the central line can help traders to visualize transitions from one market phase to another - such as from an undervalued phase to fair value or an overvalued phase.
Case Study 1
The asset in question experiences a sharp, inefficient move upwards. Such movements suggest an overextension of price, and mean reversion is typically expected.
Here, a short position was initiated, but only after the Neural Synthesis line confirmed a negative trend - to mitigate the risk of shorting into a continuing uptrend.
Two take-profit levels were set:
The midline or ‘fair value’ line.
The lower boundary of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicators valuation chart.
Although mean-reversion trades are typically closed when price returns to the mean, under circumstances of extreme overextension price often overcorrects from an overbought condition to an oversold condition.
Case Study 2
In the above study, the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is applied to the 1 Week Bitcoin chart in order to inform long term investment decisions.
Accumulation Zones - Investors can choose to dollar cost average (DCA) into long term positions when the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicates undervaluation
Distribution Zones - Conversely, when overvalued conditions are indicated, investors are able to incrementally sell holdings expecting the market peak to form around the distribution phase.
Note - It is prudent to pay close attention to any change in trend conditions when the market is in an accumulation/distribution phase, as this can increase the likelihood of a full-cycle market peak forming.
In summary, the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is also an effective tool for long term investing, especially for assets like Bitcoin which exhibit prolonged bull and bear cycles.
Special Note
It is prudent to note that because markets often undergo phases of extreme speculation, an asset's price can remain over or undervalued for long periods of time, defying mean-reversion expectations. In these scenarios it is important to use other forms of analysis in confluence, such as the trending component of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator to help inform trading decisions.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
Example Settings
As used above.
Swing Trading
Smooth Length = 150
Timeframe = 12h
Long Term Investing
Smooth Length = 30
Timeframe = 1W
Methodology
The 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator draws upon the foundational principles of Neural Networks, particularly the concept of using a network of ‘neurons’ (in this case, various technical indicators). It uses their outputs as features, preprocesses this input data, runs an activation function and in the following creates a dynamic output.
The following features/inputs are used as ‘neurons’:
Relative Strength Index (RSI)
Moving Average Convergence-Divergence (MACD)
Bollinger Bands
Stochastic Momentum
Average True Range (ATR)
These base indicators were chosen for their diverse methodologies for capturing market momentum, volatility and trend strength - mirroring how neurons in a Neural Network capture and process varied aspects of the input data.
Preprocessing:
Each technical indicator’s output is normalized to remove bias. Normalization is a standard practice to preprocess data for Neural Networks, to scale input data and allow the model to train more effectively.
Activation Function:
The hyperbolic tangent function serves as the activation function for the neurons. In general, for complete neural networks, activation functions introduce non-linear properties to the models and enable them to learn complex patterns. The tanh() function specifically maps the inputs to a range between -1 and 1.
Dynamic Smoothing:
The composite signal is dynamically smoothed using the Arnaud Legoux Moving Average, which adjusts faster to recent price changes - enhancing the indicator's responsiveness. It mimics the learning rate in neural networks - in this case for the output in a single layer approach - which controls how much new information influences the model, or in this case, our output.
Signal Processing:
The signal line also undergoes processing to adapt to the selected assets volatility. This step ensures the indicator’s flexibility across assets which exhibit different behaviors - similar to how a Neural Network adjusts to various data distributions.
Notes:
While the indicator synthesizes complex market information using methods inspired by neural networks, it is important to note that it does not engage in predictive modeling through the use of backpropagation. Instead, it applies methodologies of neural networks for real-time market analysis that is both dynamic and adaptable to changing market conditions.
Pulse Profiler [QuantraSystems]Pulse Profiler
Introduction
The Pulse Profiler ( ℙℙ ) is specifically designed to unambiguously indicate weakening momentum after a strong impulse. The upper and lower standard deviation bands also allow the user to assess the strength of an impulse and differentiate it from general noise.
Due to the ℙℙ ’s rapid responsiveness to exhaustion in price movement it is ideally used for the trader to recognize when to start taking profit when combined with other indicators.
The novum is that by dynamically balancing its sensitivity to recent movements the ℙℙ considers the asset’s inherent volatility. By reducing noise without sacrificing signal, and by visualizing it in our typical modern QuantraAI style, the ℙℙ enhances the traders’ ability to distinguish impulses with weakening momentum from strong trending movements.
Legend
Impulse: The ℙℙ showing strength based on momentum and volume.
Dynamic standard deviation bands: Rolling probability based bands based on a rolling normal distribution. Adjustable, recommended are σ = 1.5 to σ = 2.5.
Neutral lines: Dynamic thresholds which get often respected as support or resistance.
Case Study
To properly employ the ℙℙ , the trader should use it to identify out-of-the-ordinary 𝓲𝓶𝓹𝓾𝓵𝓼𝓮𝓼 which cause a following exhaustion.
The rolling standard deviation bands incorporate the asset’s historical behavior in regards to its inherent volatility on a rolling basis. If the asset shows strong 𝓲𝓶𝓹𝓾𝓵𝓼𝓮𝓼 that go beyond the rolling standard deviation, the event has been highly improbable. The trader then needs to determine if the price change was caused by critical external factors. If not, it is highly probable that the momentum exhausts and that price movement plateaus to enter a range.
These signals indicate that it is highly probable that closing a position upon these conditions is the correct choice.
If the 𝓲𝓶𝓹𝓾𝓵𝓼𝓮 reverses and retraces into the opposite direction, while moving more than 1.5σ across just 3 bars on the 4H chart, the signal indicates that a reversal is pushing the price down – in both momentum and volume.
A sharp reversal thus becomes more probable than not.
The ℙℙ can also be calibrated to find possible trend exhaustions on a longer timeframe (1D).
Please always use multiple Quantra indicators to add confirmations to your signals.
Recommended Settings
Swing Trading (4H chart)
Standard Deviation Lookback: 150
Standard Deviation Multiplier (σ): 2.5
Display Variant: Classic
Choose Mode for Bar Coloring: Signal
Trend exhaustion (1D chart)
Standard Deviation Lookback: 200
Standard Deviation Multiplier (σ): 2.0
Display Variant: Classic
Choose Mode for Bar Coloring: Extremes
Notes
Quantra Standard Value Contents:
The Heikin-Ashi (HA) candle visualization smoothes out the signal line to provide more informative insights into momentum and trends. This allows earlier entries and exits by observing the indicator values transformed by the HA.
Various visualization options are available to adjust the indicator to the user’s preference: Aside from HA, a classic line, or a hybrid of both.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
To add to Quantra's indicators’ utility we have added the option to change the price bars colors based on different signals:
Choose Mode for Coloring
Trend Following (Indicator above mid line counts as uptrend, below is downtrend)
Extremes (Everything beyond the SD bands is highlighted to signal mean reversion)
Candles (Color of HA candles as barcolor)
Reversions (Only for HA) (Reversion Signals via the triangles if HA candles change trend while beyond the SD bands, high probability entries/exits)
The ℙℙ is also sensitive to divergences for those interested in utilizing this feature.
Through a special combination of price, volume and momentum you get a holistic overview on the impulse strengths of movements.
The two neutral lines in the center act as dynamic, volume and volatility adjusted thresholds. Often the signal line respects them as support and resistance.
The upper and lower standard deviation lines express the rarity of an impulse based on the asset’s inherent volatility.
The indicator needs a long enough timespan to build up its probability estimation, therefore the asset needs sufficient price history.
The indicator requires thorough volume data. If the source of an asset pair does not forward it, try to find another source or exchange for the same pair.
Signal Mode on the 4H chart is a relevant part of this indicator when used in isolation and helps to analyze momentum adjusted by volatility.
Methodology
The ℙℙ combines the Arnaud Legoux Moving Average (ALMA) with a bespoke volume and momentum calculation, with a classical Exponential Moving Average (EMA) on price data.
The ℙℙ itself integrates ALMA for volume and momentum with an EMA calculation on price, creating a unique blend that expresses impulses using their three raw main components.
The indicator calculates dynamic standard deviation bands based on an adjustable lookback period and the adjustable sigma (σ), to signal when the impulse strength is just uncommon or even extraordinary when compared to the usual price movements:
σ = 1.5 the probability of similar impulse strength occuring is 13.37% / 2, hence ~ 6.69%
σ = 2.0 the probability of similar impulse strength occuring is ~ 2.28%
σ = 2.5 the probability of similar impulse strength occuring is ~ 0.62%
By detecting extremely improbable conditions the indicator can create an inversely highly probable signal to its user.
Neutral bands are calculated based on the ℙℙ alongside a rolling, dynamic multiplier. This effectively provides dynamic thresholds for approximating common volatility.
Heikin Ashi method: The indicator uses a custom function to calculate Heikin Ashi values, useful for smoothing impulse data and identifying trends.
Reversion Signals: Specifically for Heikin Ashi displays, we plot triangles as signals, useful to easily spot potential reversals.
The Signal Mode uses these different thresholds to highlight significant market moves.
Tangent Angle Trend Lines by Mustafa KAPUZThis custom indicator dynamically draws trend lines based on the tangent angle calculated from the current price level, offering a unique perspective on market momentum and potential reversal points. Designed for traders who appreciate the integration of geometry in technical analysis, this tool provides an innovative approach to identifying trend strength and direction.
Features:
Dynamic Angle Adjustment: The indicator automatically adjusts the angle of the trend lines according to the current price magnitude, ensuring relevance across various price levels and market conditions.
Period Customization: Users can set the period over which the highest and lowest prices are considered, allowing for flexibility in analysis over different time frames.
High and Low Price Labels: Clearly labeled highest and lowest prices within the selected period provide quick insights into critical levels.
Angle-Based Trend Lines: Utilizes the tangent of specified angles to project future price paths, helping to visualize potential trend continuations or reversals.
How It Works:
The indicator first calculates the highest and lowest prices over a user-defined period.
It then determines the angles for the trend lines based on the current price, ensuring the angles are dynamically adjusted to reflect recent market activity.
Trend lines are drawn from the highest and lowest points, projecting outwards at the calculated angles to indicate potential future price movements.
Usage:
Trend Confirmation: Use the angle trend lines to confirm the direction of the current trend. Steeper angles may indicate stronger trends.
Reversal Points: Monitor where price action intersects with the trend lines as potential reversal points or areas of support and resistance.
Strategic Entry/Exit Points: Identify strategic entry and exit points based on the proximity and angle of the trend lines relative to current price action.
This indicator is suited for traders looking for an edge in their technical analysis by incorporating geometric principles into the analysis of market trends. Whether you are day trading, swing trading, or analyzing long-term movements, the Tangent Angle Trend Lines indicator offers a fresh perspective on price dynamics.
Enjoy exploring the markets with this innovative tool and may it enhance your trading strategy!
Unbounded RSIIntroducing the concept of "Unbounded RSI".
Instead of indexing the average gain and average loss, over the time period of interest, we leave the average gain and loss unbounded. Instead we "bound" them by difference of each and smoothen out this difference in an envelope using exponential average. See code.
What this does to traditional RSI concept?
No concept of "overbought", "oversold"
No concept of "60-40", "70-30" bands and arguments over it
No concept of "Range Shifts"
...
How to use it?
I am generally a positional long trader. So I present my version. Of course, I expect each individual who decide to use this concept, to come up with their ideas, based on their style and temperament.
The points below, I apply on a Weekly Timeframe Chart.
Once, we see a long consolidation and price breakout, we should be able to see "Green" histogram bars. These appear, once we have the stock at least 20% up from the 52WL and the "Unbounded RSI" has turned positive. This can be a good time to "enter" into the scrip.
The height of the bars are significant, since they essentially show, that the "gap" between the avg. gain and avg. loss is widening, indicating momentum. Swing trading can thrive in these environments I guess.
Falling heights indicate that gaps to close, though, the "gap can still be green". This means, momentum is now falling. Swing traders and "quick buck makers", would ideally book profits here. If the color of the bars still remain "Green" it indicates that momentum has reduced but still the gains are "more" than loss on the timeperiod selected.
Once the histogram turns red, it means that the gain is now lower than loss. An increasing height underground, means this loss is widening. Generally, this will corelate with price action (not necessarily volume).
At this time, exits should be looked for, may be also check other factors/indicators to decide, but surely the momentum and the gain% over the timeperiod selected has now gone.
Note for Pine Coders:
The source code can easily be modified to develop this concept further.
For example:
Use different smoothing algorithms
Remove 52WL condition and introduce new additional conditions
Instead of price change of the stock for gain/loss calculations, we use the concept of Relative Strength (RS, not RSI) and measuere the gain/loss based on a benchmark index . I intend to work on this concept, soon.
You shall see a variable "unboundedRSI" which is actually a ratio of the Avg. Gain / Avg. Loss. This ratio is not plotted. It is kept there, for future use.
Many more
Triple Confirmation Kernel Regression Overlay [QuantraSystems]Kernel Regression Oscillator - Overlay
Introduction
The Kernel Regression Oscillator (ᏦᏒᎧ) represents an advanced tool for traders looking to capitalize on market trends.
This Indicator is valuable in identifying and confirming trend directions, as well as probabilistic and dynamic oversold and overbought zones.
It achieves this through a unique composite approach using three distinct Kernel Regressions combined in an Oscillator.
The additional Chart Overlay Indicator adds confidence to the signal.
Which is this Indicator.
This methodology helps the trader to significantly reduce false signals and offers a more reliable indication of market movements than more widely used indicators can.
Legend
The upper section is the Overlay. It features the Signal Wave to display the current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 3), which can indicate extremely rare situations which can lead to either a softening momentum in the trend or even a mean reversion situation.
The lower one is the Base Chart.
The Indicator is linked here
It features the Kernel Regression Oscillator to display a composite of three distinct regressions, also displaying current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 2), which can indicate extremely rare situations.
Case Study
To effectively utilize the ᏦᏒᎧ, traders should use both the additional Overlay and the Base
Chart at the same time. Then focus on capturing the confluence in signals, for example:
If the 𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮 on the Overlay and the ᏦᏒᎧ on the Base Chart both reside near the extreme of an Oversold zone the probability is higher than normal that momentum in trend may soften or the token may even experience a reversion soon.
If a bar is characterized by an Oversold Shading in both the Overlay and the Base Chart, then the probability is very high to experience a reversion soon.
In this case the trader may want to look for appropriate entries into a long position, as displayed here.
If a bar is characterized by an Overbought Shading in either Overlay or Base Chart, then the probability is high for momentum weakening or a mean reversion.
In this case the trade may have taken profit and closed his long position, as displayed here.
Please note that we always advise to find more confluence by additional indicators.
Recommended Settings
Swing Trading (1D chart)
Overlay
Bandwith: 45
Width: 2
SD Lookback: 150
SD Multiplier: 2
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Fast-paced, Scalping (4min chart)
Overlay
Bandwith: 75
Width: 2
SD Lookback: 150
SD Multiplier: 3
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Notes
The Kernel Regression Oscillator on the Base Chart is also sensitive to divergences if that is something you are keen on using.
For maximum confluence, it is recommended to use the indicator both as a chart overlay and in its Base Chart.
Please pay attention to shaded areas with Standard Deviation settings of 2 or 3 at their outer borders, and consider action only with high confidence when both parts of the indicator align on the same signal.
This tool shows its best performance on timeframes lower than 4 hours.
Traders are encouraged to test and determine the most suitable settings for their specific trading strategies and timeframes.
The trend following functionality is indicated through the "𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮" Line, with optional "Up" and "Down" arrows to denote trend directions only (toggle “Show Trend Signals”).
Methodology
The Kernel Regression Oscillator takes three distinct kernel regression functions,
used at similar weight, in order to calculate a balanced and smooth composite of the regressions. Part of it are:
The Epanechnikov Kernel Regression: Known for its efficiency in smoothing data by assigning less weight to data points further away from the target point than closer data points, effectively reducing variance.
The Wave Kernel Regression: Similarly assigning weight to the data points based on distance, it captures repetitive and thus wave-like patterns within the data to smoothen out and reduce the effect of underlying cyclical trends.
The Logistic Kernel Regression: This uses the logistic function in order to assign weights by probability distribution on the distance between data points and target points. It thus avoids both bias and variance to a certain level.
kernel(source, bandwidth, kernel_type) =>
switch kernel_type
"Epanechnikov" => math.abs(source) <= 1 ? 0.75 * (1 - math.pow(source, 2)) : 0.0
"Logistic" => 1/math.exp(source + 2 + math.exp(-source))
"Wave" => math.abs(source) <= 1 ? (1 - math.abs(source)) * math.cos(math.pi * source) : 0.
kernelRegression(src, bandwidth, kernel_type) =>
sumWeightedY = 0.
sumKernels = 0.
for i = 0 to bandwidth - 1
base = i*i/math.pow(bandwidth, 2)
kernel = kernel(base, 1, kernel_type)
sumWeightedY += kernel * src
sumKernels += kernel
(src - sumWeightedY/sumKernels)/src
// Triple Confirmations
Ep = kernelRegression(source, bandwidth, 'Epanechnikov' )
Lo = kernelRegression(source, bandwidth, 'Logistic' )
Wa = kernelRegression(source, bandwidth, 'Wave' )
By combining these regressions in an unbiased average, we follow our principle of achieving confluence for a signal or a decision, by stacking several edges to increase the probability that we are correct.
// Average
AV = math.avg(Ep, Lo, Wa)
The Standard Deviation bands take defined parameters from the user, in this case sigma of ideally between 2 to 3,
to help the indicator detect extremely improbable conditions and thus take an inversely probable signal from it to forward to the user.
The parameter settings and also the visualizations allow for ample customizations by the trader. The indicator comes with default and recommended settings.
For questions or recommendations, please feel free to seek contact in the comments.
Triple Confirmation Kernel Regression Base [QuantraSystems]Kernel Regression Oscillator - BASE
Introduction
The Kernel Regression Oscillator (ᏦᏒᎧ) represents an advanced tool for traders looking to capitalize on market trends.
This Indicator is valuable in identifying and confirming trend directions, as well as probabilistic and dynamic oversold and overbought zones.
It achieves this through a unique composite approach using three distinct Kernel Regressions combined in an Oscillator. The additional Chart Overlay Indicator adds confidence to the signal.
This methodology helps the trader to significantly reduce false signals and offers a more reliable indication of market movements than more widely used indicators can.
Legend
The upper section is the Overlay. It features the Signal Wave to display the current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 3), which can indicate extremely rare situations which can lead to either a softening momentum in the trend or even a mean reversion situation.
The lower one is the Base Chart - This Indicator.
It features the Kernel Regression Oscillator to display a composite of three distinct regressions, also displaying current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 2), which can indicate extremely rare situations.
Case Study
To effectively utilize the ᏦᏒᎧ, traders should use both the additional Overlay and the Base
Chart at the same time. Then focus on capturing the confluence in signals, for example:
If the 𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮 on the Overlay and the ᏦᏒᎧ on the Base Chart both reside near the extreme of an Oversold zone the probability is higher than normal that momentum in trend may soften or the token may even experience a reversion soon.
If a bar is characterized by an Oversold Shading in both the Overlay and the Base Chart, then the probability is very high to experience a reversion soon.
In this case the trader may want to look for appropriate entries into a long position, as displayed here.
If a bar is characterized by an Overbought Shading in either Overlay or Base Chart, then the probability is high for momentum weakening or a mean reversion.
In this case the trade may have taken profit and closed his long position, as displayed here.
Please note that we always advise to find more confluence by additional indicators.
Recommended Settings
Swing Trading (1D chart)
Overlay
Bandwith: 45
Width: 2
SD Lookback: 150
SD Multiplier: 2
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Fast-paced, Scalping (4min chart)
Overlay
Bandwith: 75
Width: 2
SD Lookback: 150
SD Multiplier: 3
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Notes
The Kernel Regression Oscillator on the Base Chart is also sensitive to divergences if that is something you are keen on using.
For maximum confluence, it is recommended to use the indicator both as a chart overlay and in its Base Chart.
Please pay attention to shaded areas with Standard Deviation settings of 2 or 3 at their outer borders, and consider action only with high confidence when both parts of the indicator align on the same signal.
This tool shows its best performance on timeframes lower than 4 hours.
Traders are encouraged to test and determine the most suitable settings for their specific trading strategies and timeframes.
The trend following functionality is indicated through the "𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮" Line, with optional "Up" and "Down" arrows to denote trend directions only (toggle “Show Trend Signals”).
Methodology
The Kernel Regression Oscillator takes three distinct kernel regression functions,
used at similar weight, in order to calculate a balanced and smooth composite of the regressions. Part of it are:
The Epanechnikov Kernel Regression: Known for its efficiency in smoothing data by assigning less weight to data points further away from the target point than closer data points, effectively reducing variance.
The Wave Kernel Regression: Similarly assigning weight to the data points based on distance, it captures repetitive and thus wave-like patterns within the data to smoothen out and reduce the effect of underlying cyclical trends.
The Logistic Kernel Regression: This uses the logistic function in order to assign weights by probability distribution on the distance between data points and target points. It thus avoids both bias and variance to a certain level.
kernel(source, bandwidth, kernel_type) =>
switch kernel_type
"Epanechnikov" => math.abs(source) <= 1 ? 0.75 * (1 - math.pow(source, 2)) : 0.0
"Logistic" => 1/math.exp(source + 2 + math.exp(-source))
"Wave" => math.abs(source) <= 1 ? (1 - math.abs(source)) * math.cos(math.pi * source) : 0.
kernelRegression(src, bandwidth, kernel_type) =>
sumWeightedY = 0.
sumKernels = 0.
for i = 0 to bandwidth - 1
base = i*i/math.pow(bandwidth, 2)
kernel = kernel(base, 1, kernel_type)
sumWeightedY += kernel * src
sumKernels += kernel
(src - sumWeightedY/sumKernels)/src
// Triple Confirmations
Ep = kernelRegression(source, bandwidth, 'Epanechnikov' )
Lo = kernelRegression(source, bandwidth, 'Logistic' )
Wa = kernelRegression(source, bandwidth, 'Wave' )
By combining these regressions in an unbiased average, we follow our principle of achieving confluence for a signal or a decision, by stacking several edges to increase the probability that we are correct.
// Average
AV = math.avg(Ep, Lo, Wa)
The Standard Deviation bands take defined parameters from the user, in this case sigma of ideally between 2 to 3,
to help the indicator detect extremely improbable conditions and thus take an inversely probable signal from it to forward to the user.
The parameter settings and also the visualizations allow for ample customizations by the trader. The indicator comes with default and recommended settings.
For questions or recommendations, please feel free to seek contact in the comments.
Fourier Smoothed Volume Zone Oscillator (FSVZO) [AlgoAlpha]Description
The Fourier Smoothed Volume Zone Oscillator (FSVZO) is an implementation of the Discrete Fourier Transform in a Volume Zone Oscillator. Its purpose is to smooth price data and reduce noise to provide a more clear and accurate indication of price movement. This indicator also includes additional EMA smoothing to accurately depict reversals.
Discrete Fourier Transform
The Discrete Fourier Transform (DFT) is a mathematical algorithm used to convert discrete time-domain data into its frequency-domain representation. By decomposing a signal into its constituent frequencies, it reveals the amplitude and phase information associated with each frequency component.
Volume Zone Oscillator
The Volume Zone Oscillator is an indicator that combines volume and price data to provide insights into market trends and momentum. It calculates the difference between the volume traded above and below a specified price level and represents it as a line plot on the chart. The Volume Zone Oscillator helps traders identify periods of high buying or selling pressure and can be used to confirm trends, spot divergences, and generate trading signals. By analyzing the relationship between volume and price, traders can gain a deeper understanding of market dynamics and make more informed trading decisions.
Features
This indicator incorporates Ehler's Universal Oscillator concept and presents a histogram to provide valuable insights into the market's noise levels. Ehler's Universal Oscillator represents the statistical model that characterizes random and unpredictable market behavior. By utilizing this concept, the histogram enhances traders' ability to identify periods of increased or decreased volatility in the market.
How to use it?
Green dots and lines represent bullish price movement, while red dots and lines indicate bearish price movement. These signals gain additional strength when considering our oversold and overbought zones. Traders and investors can leverage these signals to initiate long positions when green signals coincide with oversold conditions, and vice versa. By combining these signals in synergy with Ehler's Universal Oscillator, a more precise representation of market trends can be achieved. To optimize its effectiveness, it is advisable to integrate this indicator with complementary technical analysis tools and incorporate it into a comprehensive trading strategy. Traders are encouraged to explore diverse settings and timeframes to align the indicator with their individual trading preferences and adapt it to prevailing market conditions.
Utility
By combining the FSVZO indicator with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions. It empowers traders and investors to evaluate the intensity of buying or selling pressure, detect potential trend reversals or continuations, and ultimately make more informed trading decisions. This information can serve as confirmation or validation for other technical indicators, enabling traders to identify potential market turning points and enhance their comprehension of market dynamics.
The indicator offers several valuable applications, including the detection of divergence patterns between volume and price, identification of accumulation or distribution phases, and assessment of overall market trend strength. It accommodates various trading styles, such as swing trading, trend following, or mean reversion strategies. By leveraging these capabilities, traders can expand their toolkit and make more informed trading decisions.
Originality
The originality of the script lies in the combination of the Fourier analysis, white noise calculations, and the Volume Zone Oscillator. It provides a unique perspective on market dynamics and can be used to identify potential trading opportunities based on overbought and oversold conditions as well as trend reversals. Special thanks to @QuantiLuxe for their assistance in the development of this indicator
Re-Anchoring VWAP TripleThe Triple Re-Anchoring VWAP (Volume Weighted Average Price) indicator is a tool designed for traders seeking a deeper understanding of market trends and key price levels. This indicator dynamically recalibrates VWAP calculations based on significant market pivot points, offering a unique perspective on potential support and resistance levels.
Key Features:
Dynamic Re-anchoring at All-Time Highs (ATH) : The first layer of this indicator continuously tracks the all-time high and recalibrates the VWAP from each new ATH. This VWAP line, typically acting as a dynamic resistance level, offers insights into the overbought conditions and potential reversal zones.
Adaptive Re-anchoring to Post-ATH Lows : The second component of the indicator shifts focus to the market's reaction post-ATH. It identifies the lowest low following an ATH and re-anchors the VWAP calculation from this point. This VWAP line often serves as a dynamic support level, highlighting key areas where the market finds value after a significant high.
Re-anchoring to Highs After Post-ATH Lows : The third element of this tool takes adaptation one step further by tracking the highest high achieved after the lowest low post-ATH. This VWAP line can act as either support or resistance, providing a nuanced view of the market's valuation in the recovery phase or during consolidation after a significant low.
Applications:
Trend Confirmation and Reversal Signals : By comparing the price action relative to the dynamically anchored VWAP lines, traders can gauge the strength of the trend and anticipate potential reversals.
Entry and Exit Points : By highlighting significant support and resistance areas, it assists in determining optimal entry and exit points, particularly in swing trading and mean reversion strategies.
Enhanced Market Insight : The dynamic nature of the indicator, with its shifting anchor points, offers a refined understanding of market sentiment and valuation changes over time.
Why Triple Re-Anchoring VWAP?
Traditional VWAP tools offer a linear view, often missing out on the intricacies of market fluctuations. The Triple Re-Anchoring VWAP addresses this by providing a multi-faceted view of the market, adapting not just to daily price changes but pivoting around significant market events. Whether you're a day trader, swing trader, or long-term investor, this indicator adds depth to your market analysis, enabling more informed trading decisions.
Examples:
