MA - Plus / Connectable [Azullian]
The Moving Average Plus indicator enhances trend analysis by offering refined calculations and a variety of moving average types for sharper insights. As a component of the connectable indicator system on TradingView, it's designed to simplify strategy testing, visualization, and construction, all without requiring coding skills. In line with our suite of connectable indicators , it integrates through TradingView's input source, serving as a signal connector that links different indicators. Each connectable indicator, including the Moving Average Plus, plays a role in contributing signal weight to the system, culminating in an informed output for strategies or signal monitors.
█ DISTINCTIVE FEATURES
The Moving Average Plus indicator brings a set of features to enhance your market analysis:
• Variety of Moving Average Options: Select from multiple moving average types such as ALMA, EMA, HMA, RMA, and SMA, providing flexibility and precision in identifying market trends.
• Customizable Analysis Tools: Tailor the indicator settings to suit your specific analytical needs, enabling a more personalized approach to trend analysis.
• Enhanced Trend Visualization: Visual cues and detailed trend line plotting offer clear insights into market movements, aiding in decision-making processes.
• Integrated Signal Weighting: Utilize the signal weight mechanism for a comprehensive understanding of trend strength and market dynamics.
█ UNIFORM SETTINGS AND A WAY OF WORK
Although connectable indicators may have specific weight scoring conditions, they all aim to follow a standardized general approach to weight scoring settings, as outlined below.
■ Connectable indicators - Settings
• 🗲 Energy: Energy applies an ATR multiplier to the plotted shapes on the chart. A higher value plots shapes farther away from the candle, enhancing visibility.
• ☼ Brightness: Brightness determines the opacity of the shape plotted on the chart, aiding visibility. Indicator weight also influences opacity.
• → Input: Use the input setting to specify a data source for the indicator. Here you can connect the indicator to other indicators.
• ⌥ Flow: Determine where you want to receive signals from:
○ Both: Weights from this indicator and the connected indicator will apply
○ Indicator only: Only weights from this indicator will apply
○ Input only: Only weights from the connected indicator will apply
• ⥅ Weight multiplier: Multiply all weights in the entire indicator by a given factor, useful for quickly testing different indicators in a granular setup.
• ⥇ Threshold: Set a threshold to indicate the minimum amount of weight it should receive to pass it through to the next indicator.
• ⥱ Limiter: Set a hard limit to the maximum amount of weight that can be fed through the indicator.
■ Connectable indicators - Weight scoring settings
▢ Weight scoring conditions
• SM – Signal mode: Enable specific conditions for weight scoring
○ Start: A new trend starting will score
○ End: A trend ending will score
○ Zone: Continuous scoring for each candle between the start and the end.
• SP – Signal period: Defines a range of candles within which a signal can score.
• SC - Signal count: Specifies the number of bars to retrospectively examine and score.
○ Single: Score for a single occurrence
○ All occurrences: Score for all occurrences
○ Single + Threshold: Score for single occurrences within the signal period (SP)
○ Every + Threshold: Score for all occurrences within the signal period (SP)
▢ Weight scoring direction
• ES: Enter Short weight
• XL: Exit long weight
• EL: Enter Long weight
• XS: Exit Short weight
▢ Weight scoring values
• Weights can hold either positive or negative scores. Positive weights enhance a particular trading direction, while negative weights diminish it.
█ MA - Plus - INDICATOR SETTINGS
■ Main settings
• Enable/Disable Indicator: Toggle the entire indicator on or off.
• T - Type: Choose a type of moving average. (ALMA, EMA, HMA, RMA, SMA, SWMA, VWMA, WMA)
• L - Length: Set a period on which the moving average is calculated.
• F - Filter: Set a conditional filter for scoring:
○ Line position: Score bullish when the current trendline is above the next trendline, score bearish when the current trendline is below the next trendline
○ Line direction: Score bullish when the trend line is going up, score bearish when the trendline is going down.
○ Line candle position: Score bullish when the candles are above the current trendline, score bearish when the candles are below the current trendline
○ Any: Score if any of the previously mentioned conditions are true
○ All: Score if all of the previously mentioned conditions are true
• S - Source: Choose an alternative data source for the Moving average calculation.
• T - Timeframe: Select an alternative timeframe for the Moving average calculation.
• C - Candletype: Choose a candletype for the alternative source.
■ Scoring functionality
• For each moving average you'll be able to score Bullish, Bearish or Neutral for each of the conditions as mentioned in the filter above.
█ PLOTTING
• Standard: Symbols (EL, XS, ES, XL) Moving average lines are plotted with bearish, bullish and neutral zones, in the visuals section you can enable plotting by weight which will only show moving average lines to which weight is addressed.
• Conditional Settings: A larger icon appears if global conditions are met. For instance, with a Threshold(⥇) of 12, Signal Period (SP) of 3, and Scoring Condition (SC) set to "EVERY", a moving average signaling over two times in 3 candles (scoring 6 each) triggers a larger icon.
█ USAGE OF CONNECTABLE INDICATORS
■ Connectable chaining mechanism
Connectable indicators can be connected directly to the signal monitor, signal filter or strategy , or they can be daisy chained to each other while the last indicator in the chain connects to the signal monitor, signal filter or strategy. When using a signal filter you can chain the filter to the strategy input to make your chain complete.
• Direct chaining: Connect an indicator directly to the signal monitor, signal filter or strategy through the provided inputs (→).
• Daisy chaining: Connect indicators using the indicator input (→). The first in a daisy chain should have a flow (⌥) set to 'Indicator only'. Subsequent indicators use 'Both' to pass the previous weight. The final indicator connects to the signal monitor, signal filter, or strategy.
■ Set up this indicator with a signal filter and strategy
The indicator provides visual cues based on signal conditions. However, its weight system is best utilized when paired with a connectable signal filter, monitor, or strategy .
Let's connect the MA - Plus to a connectable signal filter and a strategy :
1. Load all relevant indicators
• Load MA - Plus / Connectable
• Load Signal filter / Connectable
• Load Strategy / Connectable
2. Signal Filter: Connect the MA - Plus to the Signal Filter
• Open the signal filter settings
• Choose one of the five input dropdowns (1→, 2→, 3→, 4→, 5→) and choose : MA - Plus / Connectable: Signal Connector
• Toggle the enable box before the connected input to enable the incoming signal
3. Signal Filter: Update the filter settings if needed
• The default filter mode for the trading direction is SWING, and is compatible with the default settings in the strategy and indicators.
4. Signal Filter: Update the weight threshold settings if needed
• All connectable indicators load by default with a score of 6 for each direction (EL, XL, ES, XS)
• By default, weight threshold is 'ABOVE' Threshold 1 (TH1) and Threshold 2 (TH2), both set at 5. This allows each occurrence to score, as the default score is 1 point above the threshold.
5. Strategy: Connect the strategy to the signal filter in the strategy settings
• Select a strategy input → and select the Signal filter: Signal connector
6. Strategy: Enable filter compatible directions
• As the default setting of the filter is SWING, we should also set the SM (Strategy mode) to SWING.
Now that everything is connected, you'll notice green spikes in the signal filter representing long signals, and red spikes indicating short signals. Trades will also appear on the chart, complemented by a performance overview. Your journey is just beginning: delve into different scoring mechanisms, merge diverse connectable indicators, and craft unique chains. Instantly test your results and discover the potential of your configurations. Dive deep and enjoy the process!
█ BENEFITS
• Adaptable Modular Design: Arrange indicators in diverse structures via direct or daisy chaining, allowing tailored configurations to align with your analysis approach.
• Streamlined Backtesting: Simplify the iterative process of testing and adjusting combinations, facilitating a smoother exploration of potential setups.
• Intuitive Interface: Navigate TradingView with added ease. Integrate desired indicators, adjust settings, and establish alerts without delving into complex code.
• Signal Weight Precision: Leverage granular weight allocation among signals, offering a deeper layer of customization in strategy formulation.
• Advanced Signal Filtering: Define entry and exit conditions with more clarity, granting an added layer of strategy precision.
• Clear Visual Feedback: Distinct visual signals and cues enhance the readability of charts, promoting informed decision-making.
• Standardized Defaults: Indicators are equipped with universally recognized preset settings, ensuring consistency in initial setups across different types like momentum or volatility.
• Reliability: Our indicators are meticulously developed to prevent repainting. We strictly adhere to TradingView's coding conventions, ensuring our code is both performant and clean.
█ COMPATIBLE INDICATORS
Each indicator that incorporates our open-source 'azLibConnector' library and adheres to our conventions can be effortlessly integrated and used as detailed above.
For clarity and recognition within the TradingView platform, we append the suffix ' / Connectable' to every compatible indicator.
█ COMMON MISTAKES, CLARIFICATIONS AND TIPS
• Removing an indicator from a chain: Deleting a linked indicator and confirming the "remove study tree" alert will also remove all underlying indicators in the object tree. Before removing one, disconnect the adjacent indicators and move it to the object stack's bottom.
• Point systems: The azLibConnector provides 500 points for each direction (EL: Enter long, XL: Exit long, ES: Enter short, XS: Exit short) Remember this cap when devising a point structure.
• Flow misconfiguration: In daisy chains the first indicator should always have a flow (⌥) setting of 'indicator only' while other indicator should have a flow (⌥) setting of 'both'.
• Hide attributes: As connectable indicators send through quite some information you'll notice all the arguments are taking up some screenwidth and cause some visual clutter. You can disable arguments in Chart Settings / Status line.
• Layout and abbreviations: To maintain a consistent structure, we use abbreviations for each input. While this may initially seem complex, you'll quickly become familiar with them. Each abbreviation is also explained in the inline tooltips.
• Inputs: Connecting a connectable indicator directly to the strategy delivers the raw signal without a weight threshold, meaning every signal will trigger a trade.
█ A NOTE OF GRATITUDE
Through years of exploring TradingView and Pine Script, we've drawn immense inspiration from the community's knowledge and innovation. Thank you for being a constant source of motivation and insight.
█ RISK DISCLAIMER
Azullian's content, tools, scripts, articles, and educational offerings are presented purely for educational and informational uses. Please be aware that past performance should not be considered a predictor of future results.
Скользящие средние
MBAND 200 4H BTC/USDT - By MGS-TradingMBAND 200 4H BTC/USDT with RSI and Volume by MGS-Trading: A Neural Network-Inspired Indicator
Introduction:
The MBAND 200 4H BTC/USDT with RSI and Volume represents a groundbreaking achievement in the integration of artificial intelligence (AI) into cryptocurrency market analysis. Developed by MGS-Trading, this indicator is the culmination of extensive research and development efforts aimed at leveraging AI's power to enhance trading strategies. By synthesizing neural network concepts with traditional technical analysis, the MBAND indicator offers a dynamic, multi-dimensional view of the market, providing traders with unparalleled insights and actionable signals.
Innovative Approach:
Our journey to create the MBAND indicator began with a simple question: How can we mimic the decision-making prowess of a neural network in a trading indicator? The answer lay in the weighted aggregation of Exponential Moving Averages (EMAs) from multiple timeframes, each serving as a unique input akin to a neuron in a neural network. These weights are not arbitrary; they were painstakingly optimized through backtesting across various market conditions to ensure they reflect the significance of each timeframe’s contribution to overall market dynamics.
Core Features:
Neural Network-Inspired Weights: The heart of the MBAND indicator lies in its AI-inspired weighting system, which treats each timeframe’s EMA as an input node in a neural network. This allows the indicator to process complex market data in a nuanced and sophisticated manner, leading to more refined and informed trading signals.
Multi-Timeframe EMA Analysis: By analyzing EMAs from 15 minutes to 3 days, the MBAND indicator captures a comprehensive snapshot of market trends, enabling traders to make informed decisions based on a broad spectrum of data.
RSI and Volume Integration: The inclusion of the Relative Strength Index (RSI) and volume data adds layers of confirmation to the signals generated by the EMA bands. This multi-indicator approach helps in identifying high-probability setups, reinforcing the neural network’s concept of leveraging multiple data points for decision-making.
Usage Guidelines:
Signal Interpretation: The MBAND bands provide a visual representation of the market’s momentum and direction. A price moving above the upper band signals strength and potential continuation of an uptrend, while a move below the lower band suggests weakness and a possible downtrend.
Overbought/Oversold Conditions: The RSI component identifies when the asset is potentially overbought (>70) or oversold (<30). Traders should watch for these conditions near the MBAND levels for potential reversal opportunities.
Volume Confirmation: An increase in volume accompanying a price move towards or beyond an MBAND level serves as confirmation of the strength behind the move. This can indicate whether a breakout is likely to sustain or if a reversal has substantial backing.
Strategic Entry and Exit Points: Combine the MBAND readings with RSI and volume indicators to pinpoint strategic entry and exit points. For example, consider entering a long position when the price is near the lower MBAND, RSI indicates oversold conditions, and there is a notable volume increase.
About MGS-Trading:
At MGS-Trading, we are passionate about harnessing the transformative power of AI to revolutionize cryptocurrency trading. Our indicators and tools are designed to provide traders with advanced analytics and insights, drawing on the latest AI techniques and methodologies. The MBAND 200 4H BTC/USDT with RSI and Volume indicator is a prime example of our commitment to innovation, offering traders a sophisticated, AI-enhanced tool for navigating the complexities of the cryptocurrency markets.
Disclaimer:
The MBAND indicator is provided for informational purposes only and does not constitute investment advice. Trading cryptocurrencies involves significant risk and can result in the loss of your investment. We recommend conducting your own research and consulting with a qualified financial advisor before making any trading decisions.
SMA Angular Trends [Yosiet]This indicator uses two specific SMA configurations conditioned by an angular slope that is always repeated in trend markets, which are usually beneficial in swing or long-term strategies.
SETTINGS
- Fast Angle Threshold: Is the value in degrees for the condition of the fast sma
- Slow Angle Threshold: Is the value in degrees for the condition of the slow sma
- Linear Mode: When is active, it shows the sma curves only when the condition is satisfied. When is inactive, it shows color of the trends
HOW TO USE
This indicator it helps to see clearly the trends and the oppotunities to entry/exit in breakouts and retests
WHY THOSE SMAs
The SMAs are sma(7, low) and sma(30, high), those setups came from analyze several others indicators with machine learning searching for convergence points in 2018.
THOUGHTS
This indicator only pretends to help traders to take decissions with extra data confirmation
IMPROVEMENTS
You can comment your ideas and sugestions to improve this indicator
Kalman Filtered RSI Oscillator [BackQuant]Kalman Filtered RSI Oscillator
The Kalman Filtered RSI Oscillator is BackQuants new free indicator designed for traders seeking an advanced, empirical approach to trend detection and momentum analysis. By integrating the robustness of a Kalman filter with the adaptability of the Relative Strength Index (RSI), this tool offers a sophisticated method to capture market dynamics. This indicator is crafted to provide a clearer, more responsive insight into price trends and momentum shifts, enabling traders to make informed decisions in fast-moving markets.
Core Principles
Kalman Filter Dynamics:
At its core, the Kalman Filtered RSI Oscillator leverages the Kalman filter, renowned for its efficiency in predicting the state of linear dynamic systems amidst uncertainties. By applying it to the RSI calculation, the tool adeptly filters out market noise, offering a smoothed price source that forms the basis for more accurate momentum analysis. The inclusion of customizable parameters like process noise, measurement noise, and filter order allows traders to fine-tune the filter’s sensitivity to market changes, making it a versatile tool for various trading environments.
RSI Adaptation:
The RSI is a widely used momentum oscillator that measures the speed and change of price movements. By integrating the RSI with the Kalman filter, the oscillator not only identifies the prevailing trend but also provides a smoothed representation of momentum. This synergy enhances the indicator's ability to signal potential reversals and trend continuations with a higher degree of reliability.
Advanced Smoothing Techniques:
The indicator further offers an optional smoothing feature for the RSI, employing a selection of moving averages (HMA, THMA, EHMA, SMA, EMA, WMA, TEMA, VWMA) for traders seeking to reduce volatility and refine signal clarity. This advanced smoothing mechanism is pivotal for traders looking to mitigate the effects of short-term price fluctuations on the RSI's accuracy.
Empirical Significance:
Empirically, the Kalman Filtered RSI Oscillator stands out for its dynamic adjustment to market conditions. Unlike static indicators, the Kalman filter continuously updates its estimates based on incoming price data, making it inherently more responsive to new market information. This dynamic adaptation, combined with the RSI's momentum analysis, offers a powerful approach to understanding market trends and momentum with a depth not available in traditional indicators.
Trend Identification and Momentum Analysis:
Traders can use the Kalman Filtered RSI Oscillator to identify strong trends and momentum shifts. The color-coded RSI columns provide immediate visual cues on the market's direction and strength, aiding in quick decision-making.
Optimal for Various Market Conditions:
The flexibility in tuning the Kalman filter parameters makes this indicator suitable for a wide range of assets and market conditions, from volatile to stable markets. Traders can adjust the settings based on empirical testing to find the optimal configuration for their trading strategy.
Complementary to Other Analytical Tools:
While powerful on its own, the Kalman Filtered RSI Oscillator is best used in conjunction with other analytical tools and indicators. Combining it with volume analysis, price action patterns, or other trend-following indicators can provide a comprehensive view of the market, allowing for more nuanced and informed trading decisions.
The Kalman Filtered RSI Oscillator is a groundbreaking tool that marries empirical precision with advanced trend analysis techniques. Its innovative use of the Kalman filter to enhance the RSI's performance offers traders an unparalleled ability to navigate the complexities of modern financial markets. Whether you're a novice looking to refine your trading approach or a seasoned professional seeking advanced analytical tools, the Kalman Filtered RSI Oscillator represents a significant step forward in technical analysis capabilities.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Kyrie Crossover ( @zaytradellc )Unlocking Market Dynamics: Kyrie Crossover Script by @zaytradellc
personalized trading success with the "Kyrie Crossover" script, meticulously crafted by @zaytrade. This innovative Pine Script, tailored to the birthdays of Kyrie and the script creator, combines the power of technical analysis with a touch of personalization to revolutionize your trading experience.
**Exponential Moving Average (EMA) Crossover Strategy:**
At the heart of the "Kyrie Crossover" script lies a sophisticated EMA crossover strategy. By utilizing a 10-period EMA and a 323-period EMA (symbolizing long term price action ), the strategy effectively captures market trends with precision and insight.
- **Short-Term EMA (10-period):** This EMA reacts swiftly to recent price changes, offering heightened sensitivity to short-term fluctuations. It excels in identifying immediate shifts in market sentiment, making it invaluable for pinpointing short-lived trends and potential reversal points.
- **Long-Term EMA (323-period):** In contrast, the long-term EMA provides a broader perspective by smoothing out short-term noise and focusing on longer-term trend direction. Its extended length filters out market noise effectively, providing a clear representation of the underlying trend's momentum and sustainability.
**Directional Movement Index (DMI) Metrics:**
The "Kyrie Crossover" script goes beyond traditional indicators by incorporating DMI metrics across multiple timeframes. By assessing trend strength and direction, traders gain valuable insights into market dynamics, allowing for informed decision-making.
**Simple Instructions to Profit:**
1. **Identify EMA Crossovers:** Look for instances where the short-term EMA (10-period) crosses above the long-term EMA (323-period) for a bullish signal, indicating a potential buying opportunity. Conversely, a crossover where the short-term EMA crosses below the long-term EMA signals a bearish trend and a potential selling opportunity.
2. **Confirm with DMI Metrics:** Validate EMA crossovers by checking DMI metrics across different timeframes (5 minutes, 15 minutes, 30 minutes, and 1 hour). Pay attention to color-coded indicators, with green indicating a bullish trend, red indicating a bearish trend, and white indicating no clear trend.
3. **Manage Risk:** Implement proper risk management techniques, such as setting stop-loss orders and position sizing based on your risk tolerance and trading objectives.
4. **Stay Informed:** Regularly monitor market conditions and adjust your trading strategy accordingly based on new signals and emerging trends.
Cauchy Distribution Trend AnalysisThis custom Pine Script indicator is designed to analyze assets, including cryptocurrencies, through a lens inspired by the Cauchy distribution's characteristics. It focuses on identifying potential long and short opportunities by evaluating the asset's price position relative to a dynamically calculated median price and a scale parameter. Here's a breakdown of its components and how to use it:
Components
Median Length: The period over which the median price is calculated. The median price acts as a proxy for the Cauchy distribution's location parameter, representing a central value around which the market price fluctuates.
MA Length: The length for calculating the moving average, which is used to determine the scale parameter. The scale parameter estimates the average volatility around the median price, adjusted for the selected averaging method.
Moving Average Type: Offers a choice between HMA (Hull Moving Average), SMA (Simple Moving Average), and EMA (Exponential Moving Average) to calculate the scale parameter. This flexibility allows users to tailor the sensitivity of the scale parameter to the asset's price volatility.
Median Price Calculation: Uses the close price (by default) to calculate the median price over the specified period.
Scale Parameter Calculation: A function that calculates the scale parameter based on the chosen average source. This parameter is used to identify the threshold for long and short conditions.
Strategy Logic
Long Condition: Triggered when the asset's close price is greater than the sum of the median price and the scale parameter. This indicates that the asset's price has moved significantly above the median price, suggesting bullish momentum.
Short Condition: Triggered when the asset's close price is less than the difference between the median price and the scale parameter. This indicates that the asset's price has moved significantly below the median price, suggesting bearish momentum.
Adaptive Fisher [BackQuant]Adaptive Fisher
What is it at its core:
Custom Kaufman Adaptive Moving Average Smoothed Price Data, Fisher Transformation.
Why did we choose to make an Adaptive Fisher ?
The Adaptive Fisher Transformation Indicator is an advanced technical tool designed to signal potential turning points in market prices by transforming asset price data into a nearly Gaussian normal distribution. This transformation, initially conceptualized by John F. Ehlers, aims to make extreme price behavior, which could indicate potential market reversals, more identifiable. Unlike the standard distribution of asset prices, the Gaussian normal distribution provides a clearer framework for identifying price extremes and trends.
With that being considered there are key things to take into consideration:
As the transformation seeks to normalize price data, it's crucial to remember that asset prices inherently do not follow a normal distribution. Thus, traders should use this tool in conjunction with other analyses to confirm potential trading signals. The effectiveness can vary across different assets and market conditions, underscoring the importance of customization and adaptation to specific trading strategies. As the same for all tools, all must be backtested. Past performance is not a guarantee for future results.
Now for the Key Features
Normalization of Prices: The Adaptive Fisher Transformation normalizes price data, enhancing the visibility of turning points. This normalization is critical for identifying moments when the price movement is statistically significant, thereby aiding in decision-making.
Adaptivity through Kaufman's Adaptive Moving Average (KAMA): Unlike traditional indicators, this version employs KAMA to dynamically adjust to market volatility. By doing so, it smoothens the price data more effectively, providing signals that are more responsive to current market conditions.
Divergence Detection: It includes the capability to detect divergences between the indicator and price movement, a powerful signal of potential trend reversals. Traders can specify the length over which divergences are calculated, allowing for customization based on their trading strategy.
Visual Enhancements: The indicator features color gradients to delineate strength levels and extreme values, improving readability and the quick assessment of market conditions.
Customizable Smoothing Mechanism: To accommodate different assets and timeframes, the indicator includes an option to select from various moving averages for smoothing, with an Exponential Moving Average (EMA) recommended for its effectiveness.
Application and Interpretation:
Traders can utilise this tool to identify potential reversal points by looking for extreme values in the transformed price data. Changes in the direction of the indicator can also signal shifts in market trends.
The inclusion of a normalized Relative Strength Index (RSI) provides additional confluence, aiding traders in recognizing overbought and oversold conditions through color-coded background hues in the chart.
Alert conditions are programmed for various scenarios, including trend shifts, Fisher Transform crossings over the midline, and both regular and hidden divergences, enabling traders to react promptly to potential market movements.
Empirical Soundness
Mathematical Foundation in Gaussian Distribution: At its core, the Fisher Transformation's application to financial markets is based on transforming prices to conform more closely to a Gaussian normal distribution, which is a fundamental concept in statistics. This transformation aims to make the identification of price extremes more reliable. Empirical studies have shown that while raw financial data may not follow a normal distribution, the application of transformations can facilitate the identification of critical turning points in market data (Ehlers, John F., "Cybernetic Analysis for Stocks and Futures", Wiley & Sons, 2004).
Adaptivity through KAMA: The use of Kaufman's Adaptive Moving Average introduces a dynamic element to the indicator, allowing it to adjust to market volatility automatically. This adaptivity is particularly relevant in today's financial markets, where volatility patterns can shift rapidly due to economic news, geopolitical events, and changes in market sentiment. The empirical strength of KAMA lies in its foundational logic, designed to account for market noise and smoothing price data more effectively than traditional moving averages (Kaufman, Perry J., "Trading Systems and Methods", Wiley & Sons, 2013).
Innovative Divergence Detection Mechanism: Divergence detection adds an empirical layer to the Adaptive Fisher Transformation by highlighting discrepancies between price action and the indicator's performance. This feature is grounded in the principle that divergences can often precede reversals, providing early warning signs of potential shifts in market direction. The ability to customize the calculation length for divergences enables the indicator to be fine-tuned to the characteristics of specific assets or market conditions, enhancing its practical application.
User Inputs Explained:
Calculation Source (price): This input determines the base price used for calculations, typically the closing price (close). Traders can adjust this to open, high, low, or another average, tailoring the indicator to focus on specific aspects of price action.
Fisher Lookback (ftPeriod): Defines the period over which the Fisher Transform is calculated. A shorter period makes the indicator more sensitive to price movements, while a longer period smoothens the output, reducing sensitivity.
Make Fisher Adaptive (adapt): A boolean input that enables the adaptation feature of the Fisher Transform using KAMA. When set to true, it dynamically adjusts the Fisher Transform according to market volatility, enhancing its responsiveness to recent price changes.
Adaptive Period (length), Fast Length (fast), Slow Length (slow): These inputs configure the KAMA calculation, affecting its sensitivity to price movements. The length determines the lookback period for volatility calculation, while fast and slow set the speed of adjustment to market conditions.
Smooth Fisher (smooth): Allows for additional smoothing of the Fisher Transform output to reduce noise. This is particularly useful in highly volatile markets or when the indicator is too reactive to price changes.
Smoothing Type (modeSwitch) and Smooth Period (smoothlen): Determine the method and period for smoothing. Options include various moving averages (EMA, SMA, etc.), providing flexibility in how the smoothing is applied.
Show Fisher, Show Fisher Moving Average, Moving Average Period (malen): These inputs control the visibility of the Fisher Transform and its moving average on the chart, as well as the period of the moving average. This helps in identifying trends and the direction of the market.
Show Detected Trend Shifts (trendshift): Enables the highlighting of moments when the indicator suggests a potential shift in market trend, providing early signals for traders.
Show Fisher Strength levels (showextreme): Displays predefined levels indicating extreme values of the Fisher Transform, which could suggest overbought or oversold conditions.
Show Confluence RSI (showrsi), RSI Period (rsiPeriod): These inputs add a normalized Relative Strength Index to the chart for additional analysis, offering a secondary measure of market conditions.
Show Overbought and Oversold Signals: When enabled, the background color changes to highlight overbought or oversold conditions based on the RSI, aiding in visual identification of potential trading opportunities.
Use Case of Midline Crossover Fisher:
Midline Crossover Fisher: The Fisher Transform's midline crossover is a critical signal for traders. A crossover above the midline indicates a bullish market sentiment, suggesting that it might be a good time to consider entering a long position. Conversely, a crossover below the midline suggests bearish sentiment, potentially signaling an opportunity to go short. This is based on the principle that the Fisher Transform makes turning points more evident, and crossing the midline reflects a change in momentum.
Overbought and Oversold Hues:
RSI Overbought and Oversold Background Color: The background color feature for RSI OB (overbought) and OS (oversold) conditions enhances visual cues for market extremes. When the RSI exceeds upper thresholds (Above 70), indicating overbought conditions, the background will turn to warn traders of potential price reversals. Similarly, when the RSI falls below lower thresholds (Below 30), suggesting oversold conditions, green can highlight potential opportunities for buying.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
This is using the Midline Crossover:
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
EHRHART Algo Premium (V.2)EHRHART Algo Premium is a indicator designed to help traders analyze market flow. It work with multiple EMA for identifying the sentiment of market. It's very simple calculation but it's a good help for people who use price action. I think the visual of the chart is very important and and I wanted to create an indicator very visual. I'm price action lover like lots of people and I personally think it's very important to identify the flow of market because buying when the flow of market is up give you better chance to win your trade. It's not BUY and SELL signal, this indicator don't tell u when u need buy or when u need sell, it's principally here for helping the visual of trading chart (have a good clear chart). I decided to post this indicator because people were asking me how it worked and were curious about these colors, so here we go !
This indicator show:
The main flow ( green candle=buy pressure /red candle=seller pressure ), it's based on two EMA cross over, this two EMA are editable so u can take the combination you want depending on your trading strategy. When the first EMA is above the second EMA candle becoming green and when the second EMA is above the first EMA candle becoming red.
The trend of two EMA crossover (blue=bullish and violet=bearish), it's based on two EMA (two different than main flow) cross over, this two EMA are editable so u can take the combination you want depending on your trading strategy. When the first EMA is above the second EMA the trend becoming blue and when the second EMA is above the first EMA the trend becoming violet.
Potential trend reversals (violet candle), it's calculate with the two EMA of the main flow, when these two EMA becoming closer, the candle becoming violet. It meaning that the trend may reversals. I added sensitivity parameter, so u can adjust it depending on your trading strategy, the more sensitive it is, the more candle will be colored violet.
A system of RSI print on the chart, when the RSI becoming overbought (more than 75) a red triangle will pop up on the chart, and when the RSI becoming oversold (less than 25) a green triangle will pop up on the chart. U can show or hidden these setting.
Bullish candles are represented by hollow candles.
Bearish candles are represented by full candles.
You can use this indicator with multiple strategy, I personally use it with price action (support/resistance) and I made it for that (but it's your choice).
This is an example of how I'll use it:
Here we can see that the price is coming testing our weakly support, however the main flow is bullish (red candle), so I'm waiting my first signal (violet candle). When the first candle passed violet I decided to enter the trade because violet candle after red candle means that the two EMA start closed to themselves meaning that's the flow may turn green. My second signal will be candle passed green, because it meaning the two EMA start deviate from themselves, buyer are taking advantage. In this situation a green triangle on the support will be my third signal.
CAPACE MARKETThis custom indicator combines the Moving Average Convergence Divergence (MACD) and the Relative Strength Index (RSI) into a single trading tool. It calculates the MACD and RSI values, then averages these two indicators to create a composite line. This average line is intended to capture the momentum and relative strength of the market simultaneously, potentially offering a more nuanced view of market conditions.
Key features of the indicator include:
Visualization of MACD and RSI Lines: It plots the MACD and RSI values as separate lines on the chart, allowing traders to see the behavior of each indicator clearly.
Average Line: A line representing the average of the MACD and RSI indicators is plotted, providing a synthesized view of both momentum and strength.
Entry Points Indication: The indicator uses red dots to mark the points where the average line crosses over or under the MACD or RSI lines. These intersections are meant to signal potential entry points for traders.
Market Condition Highlighting: The background color changes based on whether the average line is above or below zero. A green background suggests a positive market condition (bullish), while a red background indicates a negative market condition (bearish).
This tool aims to offer traders an integrated perspective by combining the insights of both MACD and RSI, potentially aiding in the identification of entry and exit points as well as the overall market sentiment.
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
Adaptive Moving Average (AMA) Signals (Zeiierman)█ Overview
The Adaptive Moving Average (AMA) Signals indicator, enhances the classic concept of moving averages by making them adaptive to the market's volatility. This adaptability makes the AMA particularly useful in identifying market trends with varying degrees of volatility.
The core of the AMA's adaptability lies in its Efficiency Ratio (ER), which measures the directionality of the market over a given period. The ER is calculated by dividing the absolute change in price over a period by the sum of the absolute differences in daily prices over the same period.
⚪ Why It's Useful
The AMA Signals indicator is particularly useful because of its adaptability to changing market conditions. Unlike static moving averages, it dynamically adjusts, providing more relevant signals that can help traders capture trends earlier or identify reversals with greater accuracy. Its configurability makes it suitable for various trading strategies and timeframes, from day trading to swing trading.
█ How It Works
The AMA Signals indicator operates on the principle of adapting to market efficiency through the calculation of the Efficiency Ratio (ER), which measures the directionality of the market over a specified period. By comparing the net price change to total price movements, the AMA adjusts its sensitivity, becoming faster during trending markets and slower during sideways markets. This adaptability is enhanced by a gamma parameter that filters signals for either trend continuation or reversal, making it versatile across different market conditions.
change = math.abs(close - close )
volatility = math.sum(math.abs(close - close ), n)
ER = change / volatility
Efficiency Ratio (ER) Calculation: The AMA begins with the computation of the Efficiency Ratio (ER), which measures the market's directionality over a specified period. The ER is a ratio of the net price change to the total price movements, serving as a measure of the efficiency of price movements.
Adaptive Smoothing: Based on the ER, the indicator calculates the smoothing constants for the fastest and slowest Exponential Moving Averages (EMAs). These constants are then used to compute a Scaled Smoothing Coefficient (SC) that adapts the moving average to the market's efficiency, making it faster during trending periods and slower in sideways markets.
Signal Generation: The AMA applies a filter, adjusted by a "gamma" parameter, to identify trading signals. This gamma influences the sensitivity towards trend or reversal signals, with options to adjust for focusing on either trend-following or counter-trend signals.
█ How to Use
Trend Identification: Use the AMA to identify the direction of the trend. An upward moving AMA indicates a bullish trend, while a downward moving AMA suggests a bearish trend.
Trend Trading: Look for buy signals when the AMA is trending upwards and sell signals during a downward trend. Adjust the fast and slow EMA lengths to match the desired sensitivity and timeframe.
Reversal Trading: Set the gamma to a positive value to focus on reversal signals, identifying potential market turnarounds.
█ Settings
Period for ER calculation: Defines the lookback period for calculating the Efficiency Ratio, affecting how quickly the AMA responds to changes in market efficiency.
Fast EMA Length and Slow EMA Length: Determine the responsiveness of the AMA to recent price changes, allowing traders to fine-tune the indicator to their trading style.
Signal Gamma: Adjusts the sensitivity of the filter applied to the AMA, with the ability to focus on trend signals or reversal signals based on its value.
AMA Candles: An innovative feature that plots candles based on the AMA calculation, providing visual cues about the market trend and potential reversals.
█ Alerts
The AMA Signals indicator includes configurable alerts for buy and sell signals, as well as positive and negative trend changes.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
LineBreak Exponential Moving AverageThere are two types of charts. Timed and timeless ones.
The classic (timed) trading chart is the one shown on the right.
After each period closes, a candle closes.
Time defines the progress of this chart.
Then there are timeless charts, as shown on the left.
A candle closes only after price reaches a target, based on rules.
Price defines the progress of this chart.
Japanese invented most timeless charts to filter volatility and improve the visibility of trend changes.
To achieve consistency between these two different worlds, a simple but very useful EMA was developed.
This indicator transforms the timeless linebreak chart into a timed one to calculate EMA.
In this way, we have consistent behavior as being in a timed chart. Identical MA crossings and support/resistance.
The use of EMA is well known. It is not some new concept that needs further explanation.
The interpretation of LineBreak EMA is the same as the interpretation of your daily EMA.
Tread lightly, for this is line-broken ground.
ziksfx Structure - LiteInspired by the 'mentfx Structure' indicator created by Anton (mentfx) on TradingView, I have developed my own unique version of the market structure indicator, enhancing it with features that resonate with my personal trading style and offer additional insights into market behaviour.
In the spirit of Anton's original concept, my indicator incorporates the fundamental idea of "sells before buys" for bullish ranges and "buys before sells" for bearish ranges. This methodological approach is designed to mirror the activities of large market participants who typically offload positions before accumulating again in a bullish context, and accumulate before offloading in a bearish context.
The "ranges" displayed on the chart represent historical and updated highs and lows, reflecting the structural delivery of price across any timeframe. This approach assumes that in a bullish range, the market is likely to sustain upward momentum until it reaches a new high or experiences a significant "sell before buy" scenario, and conversely in a bearish range.
Key Enhancements and Features:
Immediate Break of Structure (BOS) Recognition: This feature promptly updates the high/low to the candle that triggers a BOS, providing a more agile response compared to the original mentfx Structure's approach of waiting for a swing high/low to set the range. This adaptation allows me for quicker adaptation to the market's unfolding narrative.
Market Stage Visualization: By seamlessly integrating with the structure tracking, my indicator presents the current 'Market Stage,' offering a clear stage of the current market's phase, which is crucial for informed trading decisions. The core methodology for determining market stages is derived from the foundational concepts established by mentfx.
Moving Average Integration: The inclusion of a Moving Average (MA) within the indicator adds a layer of trend confirmation, reinforcing decisions based on market structure with established trend analysis techniques. You can use EMA or SMA.
Customizable Session Settings: Tailor the indicator to focus on specific market hours, enhancing its utility for session-based trading strategies and backtesting efficiency.
Triple M: The Triple-M feature is also included in this indicator, which provides a visual representation of the market's momentum and potential reverse.
ATR: Utilizes the Average True Range (ATR) to estimate stop loss levels, providing a data-driven method to manage risk in accordance with current market volatility.
Watermark: Displays the name of the ticker and the current timeframe directly on the chart for easy reference, ensuring clarity and orientation when analyzing multiple instruments or timeframes.
How It Works:
When a range is assigned as being bullish, it will continue updating the high until a new high is created after the bos (= the new high of the range) and will not update or change until a candle's body, open's or close's above it - which will re-update the high and update the low. The low will be updated based on the last time price had a candle (open or closure) below a previous candle low, and then will find the lowest low after the rule was met to assign a low (the idea here is to locate the last major "sell before buy" and showcase that range. And this will occur vice versa, where: when a range is assigned as bearish, it will continue updating the low until a true low is created (=low of the range) and will not update or change until a candle's body, open's or close's below it - which will reupdate the low and update the high. The high will be updated based on the last time price had a candle (open or closure) above a previous candle high, and then will find the highest high after the rule was met to assign a high (once again, the idea being to locate the last major "buy before sell" and showcase price as existing in that range.)
A high is considered as a high that has a lower high to its left and to its right. And a low is considered as a low that has a higher low to its left and to its right. These high and low are used to determine the final high or low of a Bullish or Bearish range (respectively).
Range Determination: The indicator assesses the market momentum and assigns a Bullish or Bearish state based on the most recent directional break.
High/Low Rules Adaptation: In a Bullish range, indicator updates the high if a candle's body, not just the wick, exceeds the current high. This subtle yet significant change allows for a more conservative and potentially more accurate portrayal of bullish sentiment.
Dynamic Updating: As the market evolves, the indicator recalibrates the high and low lines based on the latest price movements, ensuring that you always have the most current and relevant data.
The indicator is not merely a trend-following or scalping tool. It leverages a distinct interpretation of market behavior, focusing on the last major "sell before buy" in Bullish ranges and "buy before sell" in Bearish ranges. By doing so, it aims to pinpoint the true sentiment behind price movements, offering traders a more grounded basis for anticipating market trends.
Of course, a special acknowledgment is due to Anton for his foundational work and the insightful knowledge he's giving day-by-day. The principles of his structure tracking method and market approach have significantly influenced the creation of this indicator, which now carries those insights forward, adapted through the lens of my personal trading philosophy.
DEMA Adjusted Average True Range [BackQuant]The use of the Double Exponential Moving Average (DEMA) within your Adjusted Average True Range (ATR) calculation serves as a cornerstone for enhancing the indicator's responsiveness to market changes. To delve deeper into why DEMA is employed specifically in the context of your ATR calculation, let's explore the inherent qualities of DEMA and its impact on the ATR's performance.
DEMA and Its Advantages
As previously mentioned, DEMA was designed to offer a more responsive alternative to the traditional Exponential Moving Average (EMA). By giving more weight to recent price data, DEMA reduces the lag typically associated with moving averages. This reduction in lag is especially beneficial for short-term traders looking to capitalize on trend reversals and other market movements as swiftly as possible.
The calculation of DEMA involves the following steps:
Calculate EMA1: This is the Exponential Moving Average of the price.
Calculate EMA2: This is the Exponential Moving Average of EMA1, thus it is a smoothing of a smoothing, leading to a greater lag.
Formulate DEMA: The formula
EMA1 = EMA of price
EMA2 = EMA of EMA1
DEMA = (2 x EMA1) - EMA2
effectively doubles the weighting of the most recent data points by subtracting the lagged, double-smoothed EMA2 from twice the single-smoothed EMA1.
This process enhances the moving average's sensitivity to recent price movements, allowing the DEMA to adhere more closely to the price bars than either EMA1 or EMA2 alone.
Integration with ATR
In the context of your ATR calculation, the integration of DEMA plays a crucial role in defining the indicator's core functionality. Here's a detailed explanation of how DEMA affects the ATR calculation:
Initial Determination of DEMA : By applying the DEMA formula to the chosen source data (which can be adjusted to use Heikin Ashi candle close prices for an even smoother analysis), you set a foundation for a more reactive trend-following mechanism within the ATR framework.
Application to ATR Bands : The calculated DEMA serves as the central line from which the ATR bands are derived. The ATR value, multiplied by a user-defined factor, is added to and subtracted from the DEMA to form the upper and lower bands, respectively. This dynamic adjustment not only reflects the volatility based on the ATR but does so in a way that is closely aligned with the most recent price action, thanks to the utilization of DEMA.
Enhanced Signal Quality : The responsiveness of DEMA ensures that the ATR bands adjust more promptly to changes in market conditions. This quality is vital for traders who rely on the ATR bands to identify potential entry and exit points, trend reversals, or to assess market volatility.
By employing DEMA as the core component in calculating the Adjusted Average True Range, your indicator leverages DEMA's reduced lag and increased weight on recent data to provide a more timely and accurate measure of market volatility. This innovative approach enhances the utility of the ATR by making it not only a tool for assessing volatility but also a more reactive indicator for trend analysis and trading signal generation.
The main concept of combining these is to reduce lag, get a more robust signal and still capture clear trends over medium time horizons.
For me, this is best used in confluence with other indicators, it can be made faster in order to get fasters response time, or slower. This is all depending on the needs of you as a trader.
User Inputs:
The script offers several user-configurable inputs, such as the period lengths for DEMA and ATR calculations, the multiplication factor for the ATR, and options to use Heikin Ashi candles or standard price data. Additionally, it allows for the toggling of visual features, like the plotting of the DEMA ATR and its moving average, and the application of color-coded trends on price bars.
Additional Features:
Moving Average Confluence: Traders can opt to display a moving average of the DEMA ATR, choosing from various types (e.g., SMA, EMA, HMA). This feature provides a layer of confluence, aiding in the identification of trend direction and strength.
Trend Identification :
The script employs logical conditions to ascertain the trend direction based on the movement of the DEMA ATR. It assigns colors to represent bullish or bearish trends, which are reflected in the plotted lines and the coloring of price bars.
Alerts :
Customizable alert conditions for trend reversals enhance the utility of the indicator for active trading, notifying users of significant changes in trend direction.
1D Backtests
We include these backtests as a general proxy for how they work.
Please do your own calibrating to suit it to your own needs and backtest.
Past results don't = future results but they can help you understand how it functions.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Volume Based S/R with EMA Crossover SignalsThis Pine Script indicator, titled "Volume Based S/R with EMA Crossover Signals," is designed for use on the TradingView platform and overlays on price charts to help traders identify potential buy and sell opportunities based on volume changes and EMA (Exponential Moving Average) crossovers. Let's break down its components for a detailed understanding:
Inputs
length: The number of bars used to calculate the standard deviation of the volume change. This parameter helps in identifying significant changes in volume over a specified period.
threshold: A multiplier applied to the standard deviation of volume change to determine significant spikes in volume, which are then used to identify support and resistance levels.
smoothLength: The length of the EMA used to smooth the price data, providing a clearer view of the overall price trend and helping to confirm trade signals.
fastEMALength and slowEMALength: The lengths of the fast and slow EMAs, respectively. These are used to generate crossover signals, where the crossing of the fast EMA over the slow EMA may indicate a potential entry or exit point.
Calculations
Volume Change and Standard Deviation: The script calculates the percentage change in volume from one bar to the next and then computes the standard deviation of these changes over the specified length. This process helps identify unusual volume activity, which can precede significant price movements.
Signal Generation Based on Volume: When the absolute value of the volume change divided by its standard deviation exceeds the threshold, it signals significant volume activity, potentially indicating strong support or resistance levels at previous highs or lows.
Smoothed Price: An EMA applied to the closing prices over smoothLength bars helps to confirm the trend direction and filter out noise.
EMA Crossover Signals: The script calculates two EMAs based on the fastEMALength and slowEMALength inputs. A crossover of these two averages generates potential buy or sell signals.
Logic for Buy/Sell Signals
Buy Signal: Generated when the price is above the identified support level (determined by significant volume activity), the fast EMA crosses above the slow EMA, and the price is also above the smoothed price. This confluence of conditions suggests upward momentum and potential buying opportunity.
Sell Signal: The opposite conditions generate a sell signal — when the price is below the identified resistance level, the fast EMA crosses below the slow EMA, and the price is below the smoothed price, indicating downward momentum and a potential selling opportunity.
Plotting
Support and Resistance Levels: Plotted as circles on the chart, with resistance levels in red and support levels in green, based on significant volume activity.
Smoothed Price and EMAs: The smoothed price line and both EMAs are plotted on the chart to help visually assess the trend and the crossover signals.
Buy and Sell Signals: Represented by shapes plotted on the chart, indicating the recommended trading action (buy or sell) based on the combined indicator logic.
Filling Between Support and Resistance: For visual clarity, the area between the identified support and resistance levels is filled, highlighting the range within which the price is expected to fluctuate.
This indicator offers a multi-faceted approach to trading, combining volume analysis with trend following via EMA crossovers. By identifying significant volume-based support and resistance levels and confirming trend direction with EMA crossovers and smoothed price trends, traders can make more informed decisions regarding entry and exit points. However, it's important to use this indicator as part of a comprehensive trading strategy, considering other factors such as market conditions, news, and technical analysis from other indicators.
Hull Trend and CompareThis Pine Script is a TradingView indicator called "Hull Trend and Compare." Its main purpose is to provide a visual representation of price trends and a comparative analysis between the selected symbol and another symbol chosen for comparison.
The key components and functionalities:
Price Trend Visualization:
1.Mode Selection:
Offers three modes: "Normal," "Linear," and "Heikin-Ashi."
Allows users to choose between a standard chart, linear regression, or Heikin-Ashi candlesticks.
2.Hull Moving Average (HullMA):
Calculates the HullMA for the selected mode and length.
Plots the HullMA on the chart.
Colors the background based on the relationship between HullMA and the closing price.
Generates buy and sell signals when the price crosses over or under the HullMA.
Symbol Comparison:
1.Comparison with Another Symbol:
Allows users to compare the selected symbol with another symbol (specified in the sym input).
Provides options to choose the method of calculation for the compared symbol (open, high, low, close).
Users can choose whether to use a different method of calculation (usem), adjust the length (len), and enable or disable comparison (usecmp).
Table Display:
1.Table for Technical Indicators:
Optionally displays a table showing technical indicators for both symbols.
Includes Stochastic Momentum, RSI (Relative Strength Index), and MACD (Moving Average Convergence Divergence).
Colors the table cells based on the direction of the indicators.
Users can customize the table's position, text size, and visibility (shwtbl).
Technical Indicators:
1.Stochastic Momentum (StochMoM):
Calculates %K and %D using the Stochastic formula.
Displays StochMoM values and colors cells based on bullish or bearish conditions.
2.Relative Strength Index (RSI):
Computes the RSI values and colors cells based on the direction of the trend.
3.MACD (Moving Average Convergence Divergence):
Calculates MACD and Signal line values.
Displays MACD values and colors cells based on bullish or bearish conditions.
Summary:
This script provides traders with a versatile tool for analyzing price trends, comparing symbols, and viewing key technical indicators. The combination of visual elements on the chart and a detailed table enhances the ability to make informed trading decisions.
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
F2X IndexThis script is designed to analyze financial market data, particularly focusing on trends and volatility. It allows users to input parameters such as index length and signal length. The script calculates moving averages and differences between the source data and the moving averages. It also optionally adjusts for volatility using the Average True Range (ATR) and can color the signal based on trend direction. The output includes plots for the index and signal, with customizable colors based on trend and volatility. The script provides a visual representation of market dynamics to aid in decision-making for traders and investors.
Multi Time Frame Exponential Moving Average and dasboardThis Pine script, titled "Multi Time Frame Exponential Moving Average (MTF EMA)," provides an innovative approach for traders who wish to track trends across multiple timeframes without having to switch between different charts. It combines two main features: an indicator displaying exponential moving averages (EMA) on five different time periods, as well as a compact dashboard that synthesizes this information on a single chart window.
The originality of this script lies in its ability to provide a comprehensive analysis of EMA trends across different time intervals, allowing traders to quickly and clearly understand the market dynamics without having to navigate between multiple charts. Rather than switching from one chart to another to observe trends on different time scales, traders can now consult a single dashboard to obtain all the necessary information.
The script uses exponential moving averages (EMA) to identify trends over five time periods: 5 minutes, 15 minutes, 1 hour, 4 hours, and 1 day. The values of the EMAs are calculated based on the closing prices of candles. Bullish or bearish trends are indicated by upward or downward arrows respectively, making it easy to interpret the information on the dashboard.
To use this script, traders can simply add it to their chart on the TradingView platform. They can customize the parameters of the exponential moving averages according to their preferences and choose between a dark or light theme for the dashboard. Then, they can observe trends on different time scales directly on the dashboard, enabling them to make informed trading decisions.
In summary, this script offers a practical and innovative solution for tracking trends across multiple timeframes, combining the efficiency of exponential moving averages with the convenience of a dashboard centralized on a single chart. This allows traders to save time and stay informed about market movements effectively and efficiently.
Swing Trading Indicators (Improved)This "Swing Trading Indicators" script is a sophisticated trading tool designed for traders who wants to use technical analysis for identifying optimal entry points, safeguarding profits, and protect their capital. With foundations loosely based on the momentum burst strategy by Pradeep Bonde, Kristjan Kullamaggie's trading methodologies, and incorporating automatic stop-losses based on Average Daily Range (ADR) and Average True Range (ATR), this script offers a comprehensive solution if you want to capitalize on short-term market movements.
Key Features:
Indicators and Moving Averages: Includes EMA (5, 10, 20, 50 days), SMA (200 days), and the highest and lowest prices over 200 days to provide a multifaceted view of market trends and momentum.
Thrust Indicator: Central to the script, the thrust indicator signals a buy point when a candlestick bar closes above the highs of the last two days, indicating a momentum burst. This feature is particularly inspired by Pradeep Bonde's 4% breakout strategy, highlighting the script's capability to identify range expansion and upward thrusts as key entry moments.
Automatic Stop-Levels: Utilizes ADR and ATR to set dynamic stop-losses, helping traders to manage risk effectively by adapting to market volatility.
Comprehensive Market Analysis : Through volume analysis, RSI, closing range, and other parameters, the script offers a deep dive into market dynamics, aiding in decision-making.
Who Should Use It:
This tool is ideal for swing traders and momentum traders focused on short to medium-term gains. Its robust set of features makes it suitable for those who prefer a data-driven approach to identify buying opportunities and manage risk.
Trading Style Compatibility:
The thrust indicator shines in momentum trading strategies, providing clear signals for entering trades ahead of potential price jumps. The integration of moving averages and volume analysis supports a variety of trading styles, including day trading and swing trading, by offering insights into trend strength and potential reversals.
How the Thrust Indicator Works:
When you see a thrust indicator (green upwards arrow below a candle) when the price is moving out of a consolidation or low volatility price-range , that's the buy point.
The thrust indicator is NOT indended as an indicator for long term positions or trend reversals, but for entries at a good price while capturing the first day of a potential 5-20% move in the coming 3-5 days.
The thrust indicator pinpoints moments when a stock shows a strong upward momentum, characterized by a candlestick closing above the highs of the preceding two days. This identifies a momentum burst, signaling an optimal entry point for traders looking to profit from a short-term price movement, typically ranging from 5-20% over the following 3-5 days. Such precision in identifying entry points is invaluable for traders focusing on capturing quick gains from market volatility.
"Top / Watch out" Indicator:
In addition to the script's core functionality, the "WatchOut" indicator plays a crucial role in identifying potential reversals after significant price movements. By analyzing conditions such as recent price increases compared to the average daily range, RSI levels, and the opening price distance from the EMA, the "WatchOut" indicator alerts traders to exercise caution. This feature is pivotal for those looking to avoid entering trades that might be on the verge of a pullback or reversal, enhancing the script's utility in managing risk.
Adjustable SMA with Comparative AnalysisInputs for Customization:
SMA Period (smaPeriod): Defines the period over which the SMA is calculated. The default is set to 252 days, typically representing a trading year.
Comparison Symbol (comparisonSymbol): Specifies the ticker symbol of another instrument (e.g., SPY for the S&P 500 ETF) to compare against the current stock. This allows for a relative performance analysis.
Days Ago for Price Difference (daysAgo): Determines the number of days in the past from which to calculate the price difference, allowing for a historical comparison.
The label, displayed at the end of the chart, contains several pieces of information:
Symbol vs. SMA: Shows the percentage difference between the current stock's close price and its SMA, indicating whether the stock is currently trading above or below its average price over the specified period.
Symbol vs. Days Ago: Displays the percentage difference between the current close price and the stock's open price from the specified daysAgo, offering insight into the stock's performance over that period.
Open Price X Days Ago: Presents the stock's open price from the specified number of days ago, providing a reference point for historical price analysis.
Minimum Price: Calculates a theoretical minimum price based on the stock's open price a specified number of days ago, adjusted by the percentage difference observed in the comparison symbol over the same period. This offers a unique insight into how the stock's price could have moved in parallel to the comparison symbol.
Comparison Symbol vs. SMA & Days Ago: Similar to the stock's analysis, these lines show the comparison symbol's performance relative to its SMA and its percentage difference from the specified days ago, aiding in a relative performance analysis.
Volatility Adjusted EMA - by CrunchsterApplies recent volatility adjustment to the exponential moving average, where the smoothing factor is 2/(N + 1) - N being the lookback period or span
Volatility of recent 30 days returns is calculated using standard deviation with a thirty day lookback.
Increased smoothing compared to a standard EMA, which also adjusts to market conditions, as first described by Chande in 1991.
Composite Trend Oscillator [ChartPrime]CODE DUELLO:
Have you ever stopped to wonder what the underlying filters contained within complex algorithms are actually providing for you? Wouldn't it be nice to actually visually inspect for that? Those would require some kind of wild west styled quick draw duel or some comparison method as a proper 'code duello'. Then it can be determined which filter can 'draw' the quickest from it's computational holster with the least amount of lag and smoothness.
In Pine we can do so, discovering how beneficial that would be. This can be accomplished by quickly switching from one filter to another by input() back and forth, requiring visual memory. A better way could be done by placing two indicators added to the chart and then eventually placed into one indicator pane on top of each other.
By adding a filter() helper function that calls other moving average functions chosen for comparison, it can put to the test which moving average is the best drawing filter suited to our expected needs. PhiSmoother was formerly debuted and now it is utilized in a more complex environment in a multitude of ways along side other commonly utilized filters. Now, you the reader, get to judge for yourself...
FILTER VERSATILITY:
Having the capability to adjust between various smoothing methods such as PhiSmoother, TEMA, DEMA, WMA, EMA, and SMA on historical market data within the code provides an advantage. Each of these filter methods offers distinct advantages and hinderances. PhiSmoother stands out often by having superb noise rejection, while also being able to manipulate the fine-tuning of the phase or lag of the indicator, enhancing responsiveness to price movements.
The following are more well-known classic filters. TEMA (Triple Exponential Moving Average) and DEMA (Double Exponential Moving Average) offer reduced transient response times to price changes fluctuations. WMA (Weighted Moving Average) assigns more weight to recent data points, making it particularly useful for reduced lag. EMA (Exponential Moving Average) strikes a balance between responsiveness and computational efficiency, making it a popular choice. SMA (Simple Moving Average) provides a straightforward calculation based on the arithmetic mean of the data. VWMA and RMA have both been excluded for varying reasons, both being unworthy of having explanation here.
By allowing for adjustment refinements between these filter methods, traders may garner the flexibility to adapt their analysis to different market dynamics, optimizing their algorithms for improved decision-making and performance on demand.
INDICATOR INTRODUCTION:
ChartPrime's Composite Trend Oscillator operates as an oscillator based on the concept of a moving average ribbon. It utilizes up to 32 filters with progressively longer periods to assess trend direction and strength. Embedded within this indicator is an alternative view that utilizes the separation of the ribbon filaments to assess volatility. Both versions are excellent candidates for trend and momentum, both offering visualization of polarity, directional coloring, and filter crossings. Anyone who has former experience using RSI or stochastics may have ease of understanding applying this to their chart.
COMPOSITE CLUSTER MODES EXPLAINED:
In Trend Strength mode, the oscillator behavior signifies market direction and movement strength. When the oscillator is rising and above zero, the market is within a bullish phase, and visa versa. If the signal filter crosses the composite trend, this indicates a potential dynamic shift signaling a possible reversal. When the oscillator is teetering on its extremities, the market is more inclined to reverse later.
With Volatility mode, the oscillator undergoes a transformation, displaying an unbounded oscillator driven by market volatility. While it still employs the same scoring mechanism, it is now scaled according to the strength of the market move. This can aid with identification of ranging scenarios. However, one side effect is that the oscillator no longer has minimum or maximum boundaries. This can still be advantageous when considering divergences.
NOTEWORTHY SETTINGS FEATURES:
The following input settings described offer comprehensive control over the indicator's behavior and visualization.
Common Controls:
Price Source Selection - The indicator offers flexibility in choosing the price source for analysis. Traders can select from multiple options.
Composite Cluster Mode - Choose between "Trend Strength" and "Volatility" modes, providing insights into trend directionality or volatility weighting.
Cluster Filter and Length - Selects a filter for the cluster composition. This includes a length parameter adjustment.
Cluster Options:
Cluster Dispersion - Users can adjust the separation between moving averages in the cluster, influencing the sensitivity of the analysis.
Cluster Trimming - By modifying upper and lower trim parameters, traders can adjust the sensitivity of the moving averages within the cluster, enhancing its adaptability.
PostSmooth Filter and Length - Choose a filter to refine the composite cluster's post-smoothing with a length parameter adjustment.
Signal Filter and Length - Users can select a filter for the lagging signal plot, also having a length parameter adjustment.
Transition Easing - Sensitivity adjustment to influence the transition between bullish and bearish colors.
Enjoy
Exponentially Weighted Moving Average Oscillator [BackQuant]Exponentially Weighted Moving Average (EWMA)
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
Applications of the EWMA
The EWMA is widely used in technical analysis. It may not be used directly, but it is used in conjunction with other indicators to generate trading signals. A well-known example is the Negative Volume Index (NVI), which is used in conjunction with its EWMA.
Why is it different from the In-Built TradingView EWMA
Adaptive Algorithms: If your strategy requires the alpha parameter to change adaptively based on certain conditions (for example, based on market volatility), a for loop can be used to adjust the weights dynamically within the loop as opposed to the fixed decay rate in the standard EWMA.
Customization: A for loop allows for more complex and nuanced calculations that may not be directly supported by built-in functions. For example, you might want to adjust the weights in a non-standard way that the typical EWMA calculation doesn't allow for.
Use of the Oscillator
This mainly comes from 3 main premises, this is something I like to do personally since it is easier to work with them in the context of my system. E.g. Using them to spot clear trends without noise on longer timeframes.
Clarity: Plotting the EWMA as an oscillator provides a clear visual representation of the momentum or trend strength. It allows traders to see overbought or oversold conditions relative to a normalized range.
Comparison: An oscillator can make it easier to compare different securities or timeframes on a similar scale, especially when normalized. This is because the oscillator values are typically bounded within a range (like -1 to 1 or 0 to 100), whereas the actual price series can vary significantly.
Focus on Change: When plotted as an oscillator, the focus is on the rate of change or the relative movement of the EWMA, not on the absolute price levels. This can help traders spot divergences or convergences that may not be as apparent when the EWMA is plotted directly on the price chart. This is also one reason there is a conditional plotting on the chart.
Trend Strength: When normalized, the distance of the oscillator from its midpoint can be interpreted as the strength of the trend, providing a quantitative measure that can be used to make systematic trading decisions.
Here are the backtests on the 1D Timeframe for
BITSTAMP:BTCUSD
BITSTAMP:ETHUSD
COINBASE:SOLUSD
When using this script the user is able to define a source and period, which by extension calculates the alpha. An option to colour the bars accord to trend.
This makes it super easy to use in a system.
I recommend using this as above the midline (0) for a positive trend and below the midline for negative trend.
Hence why I put a label on the last bar to ensure it is easier for traders to read.
Lastly, The decreasing colour relative to RoC, this also helps traders to understand the strength of the indicator and gain insight into when to potentially reduce position size.
This indicator is best used in the medium timeframe.
