OHLC, Sessions & Key Levels [Orderflowing]Multi-Timeframe (+) OHLC, Sessions & Key Levels | Custom-Timeframe OHLC | Sessions Analysis | Market Key Levels
Built using Pine Script V5.
Introduction
The OHLC, Sessions & Key Levels Indicator is a tool designed for traders who want to integrate Multi-Timeframe (MTF) OHLC Data, Sessions Analysis, and Key Market Levels into their trading system.
This Indicator can help traders by automatically marking the OHLC, Sessions & Key Levels directly on the price chart, saving time furthermore potentially allowing for better judgement in their trading and risk management process.
Innovation and Inspiration
The Indicator draws from multiple concepts;
The OHLC levels across different timeframes, session-based analysis, and plotting potentially important and pivotal market levels.
Concept Inspiration from ICT-Traders / Market Maker Model Traders.
Use of Open-Source Code
Specific parts of this Indicator's code have been inspired by & further developed from publicly available code originally developed for the MetaTrader platform.
All such integrations have been wired to work within the TradingView environment, specifically using Pine Script Version 5.
Elements have been made to benefit the overall functionality, the code logic, to make sure it offers unique value to TradingView's users.
Core Features
OHLC MTF Analysis
Foundation
This component allows traders to track the Open, High, Low, and Close levels across different timeframes, ranging from intraday periods to yearly data.
Customization
Traders can adjust the bar offset, width, and colors of the OHLC bars, as well as display options. Option to highlight the Open/Close with labels and the High/Low with marks.
Application
The OHLC MTF component gives traders a clear view of important price levels, which can serve as support, resistance, or potential entry/exit points.
Main Trading Sessions & Custom Sessions
Starting Point
The Sessions component relies on the user-inputted key market sessions, defaults include New York, London, Asia, and optionally Sydney. Session Defaults to UTC.
Please Note: Adjust Time Zone in TradingView's Desktop App or Web Interface to use the sessions in correct local time.
Customization
Traders can adjust session names, session times, time zone, visibility, session colors, and session-specific high and low markers.
This allows us to visualize price movements during these selected periods.
Application
By highlighting different trading sessions, traders can potentially better time their trades, understanding when significant price movements usually occur. This can potentially be used to try and find patterns in a time-based method.
Key Levels
Customization
Traders can choose which key levels to display and adjust the visual style of these levels, including line width, style, and color.
Application
The Key Levels feature can help traders identify support and resistance levels that can serve as potential entry or exit points. Can be useful in market structure analysis by marking significant price levels based on different timeframes.
Designed for multi-timeframe analysis, allowing traders to track OHLC levels, session ranges, and key market levels.
It’s highly customizable, making it suitable across trading styles and charting setups, whether scalping, day trading, swing trading or longer term investing.
Multi-Timeframe (MTF) OHLC
Can be plotted as a Candlestick or Bar-Chart or Both
These can help traders keep an eye on price levels across multiple timeframes while allowing the actual chart to be on another timeframe than the displayed OHLC.
Example - OHLC on the Weekly Candle/Bar - Chart 4 Hourly Candles
While being on lower timeframes, the trader can keep an eye on how the OHLC candle is developing. ICT-Traders find the Daily (Default Setting) OHLC useful in analysis.
It can be customized to any timeframe the trader wishes to use.
Inspired by ICT-Traders / Market Maker Model Traders and Top-Down Analysis Style.
Combined with Session Analysis to view into the price behavior during specific trading sessions, could potentially be very useful for finding trading setups.
OHLC Levels
Creates lines based on user input - Can potentially be important reference points for trade setups / invalidation / confirmation, levels could be used as the HTF Origin.
Conclusion
The OHLC MTF, Sessions & Key Levels Indicator is a tool that combines multiple market analysis concepts into a single unique script. It offers another view of the market's behavior by combining OHLC data from a different timeframe, main trading sessions, and key levels.
Why Invite-Only?
The OHLC, Sessions & Key Levels Indicator is offered as invite-only because you receive a quality and customizable tool that combines multiple functions into one convenient script.
This Indicator stands out by being a complete and optimized trading tool based on three desirable components.
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Multi-Timeframe OHLC Analysis, Sessions Tracking & Key Levels
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Into One Customizable Indicator.
Disclaimer
While the Indicator offers a view of the OHLC price action on multiple timeframes, key levels & trading sessions, traders should not solely rely on it for trading decisions. As with all trading tools, it should be used as part of a complete trading strategy.
Cerca negli script per "swing trading"
HTF Multi Candles DisplayHTF Multi Candles Display
Description
The HTF Multi Candles Display is a powerful and versatile indicator that overlays higher timeframe (HTF) candles on your current chart, providing traders with a comprehensive multi-timeframe analysis tool in a single view. This indicator is particularly valuable for traders who employ strategies that rely on higher timeframe context, such as the Power of Three strategy, Turtle Soup, Candle Range Theory (CRT), and Inner Circle Trader (ICT) concepts like Price Delivery (PD) arrays.
> **Notice**: If you find this indicator beneficial for your trading, I would greatly appreciate any contribution in the form of TradingView Coins. Thank you for your support!
Key Features
1. Displays up to 5 higher timeframe candles
2. Customizable higher timeframe selection (5m to Monthly)
3. Adjustable candle appearance (colors, wicks, width)
4. Time labels for easy reference
5. Optional vertical lines to separate HTF candles
6. Offset adjustment to position candles away from the chart edge
7. Customizable wick and border colors
8. Flexible vertical line styles (solid, dashed, dotted)
9. Adjustable time label font sizes
How it Helps Traders
### 1. Multi-timeframe Analysis
By overlaying higher timeframe candles on your current chart, this indicator allows you to easily identify key levels, trends, and potential reversal points across different timeframes without switching between multiple charts.
### 2. Power of Three Strategy
This indicator is invaluable for traders using the Inner Circle Trader (ICT) Power of Three strategy, which focuses on accumulation, manipulation, and distribution phases. The higher timeframe candles help identify these phases more accurately, allowing for better trade entries and exits:
- Accumulation: Identify periods of sideways price action on higher timeframes.
- Manipulation: Spot false breakouts or breakdowns on lower timeframes that are contained within higher timeframe ranges.
- Distribution: Recognize when price is approaching significant higher timeframe levels where smart money may begin to distribute.
### 3. Turtle Soup
Traders can use this indicator to spot potential Turtle Soup setups by identifying key breakout levels on higher timeframes and comparing them to current price action. This helps in:
- Identifying false breakouts that may lead to Turtle Soup trade opportunities.
- Confirming the validity of breakouts by comparing lower timeframe momentum to higher timeframe structure.
### 4. Candle Range Theory (CRT)
This indicator is extremely useful for traders applying Candle Range Theory. CRT focuses on the relationship between the current candle's range and the previous candle's range. By displaying higher timeframe candles, traders can:
- Easily compare candle ranges across multiple timeframes.
- Identify potential breakout or breakdown levels based on the previous HTF candle's range.
- Spot instances where the current lower timeframe price action is testing or breaking significant HTF candle ranges.
- Recognize potential reversal points where price reaches the extremes of higher timeframe candle ranges.
### 5. Support and Resistance
Higher timeframe candles often represent significant support and resistance levels. This indicator makes it easy to spot these levels and incorporate them into your trading decisions, allowing you to:
- Identify key support and resistance levels from higher timeframes.
- Anticipate potential price reactions at these levels on your current timeframe.
- Plan entries, exits, and stop-loss placement with greater precision.
### 6. Trend Identification
By displaying multiple HTF candles, traders can quickly assess the overall trend direction on higher timeframes, helping to align trades with the broader market direction:
- Easily visualize the trend on higher timeframes without changing your chart.
- Identify potential trend changes or continuations based on HTF candle patterns.
- Align your trades with the higher timeframe trend for potentially higher probability setups.
### 7. Enhanced Decision Making
The combination of current timeframe price action and higher timeframe context allows for more informed decision-making, potentially improving trade quality and risk management:
- Validate trade setups by ensuring they align with higher timeframe structure.
- Avoid low-probability trades that conflict with higher timeframe trends or key levels.
- Adjust position sizing based on the proximity to significant HTF levels.
### 8. Time Efficiency
Instead of constantly switching between timeframes, traders can view all necessary information on a single chart, streamlining their analysis process:
- Reduce the time spent switching between multiple charts.
- Quickly assess market conditions across various timeframes.
- Improve focus by having all relevant information in one view.
### 9. ICT Price Delivery (PD) Arrays
The HTF Multi Candles Display is particularly useful for traders familiar with Inner Circle Trader (ICT) concepts, especially in identifying Price Delivery (PD) arrays:
- Visualize potential PD arrays across multiple timeframes without switching charts.
- Identify key swing highs and lows that form PD array structures.
- Recognize patterns such as Breaker Blocks, Inefficient Price Points, and Fair Value Gaps more easily on higher timeframes.
- Spot potential areas where smart money might be accumulating or distributing by analyzing the relationship between HTF candles.
- Use the series of HTF candles to identify potential Order Blocks, which are often key components of PD arrays.
- Recognize Mitigation Points and Liquidity Voids more effectively by analyzing the structure of multiple HTF candles.
By displaying a series of HTF candles, this indicator allows traders to more easily identify and validate ICT concepts like PD arrays, enhancing their ability to spot high-probability trading opportunities and potential market turning points.
Conclusion
The HTF Multi Candles Display indicator is suitable for traders of all levels, from beginners looking to understand market structure across timeframes to experienced traders refining their multi-timeframe analysis techniques. Whether you're day trading, swing trading, or looking for longer-term positions, this indicator provides valuable insights to enhance your trading strategy.
By incorporating higher timeframe context into your analysis, you can make more informed trading decisions, identify high-probability setups, and potentially improve your overall trading performance. The HTF Multi Candles Display is a versatile tool that adapts to various trading strategies and helps traders gain a deeper understanding of market dynamics across multiple timeframes, including advanced concepts like ICT Price Delivery arrays.
Swing [SMRT Algo]The SMRT Algo Swing indicator is a tool tailored for swing trading, designed to provide traders with insights and entry points on higher timeframes, such as the 1-hour (1H) chart and above. This indicator incorporates a range of features to enhance both trend identification and risk management.
Features:
Bar Colors: The indicator employs a straightforward color-coding system to denote market trends: red bars indicate a bearish trend, and green bars indicate a bullish trend. This immediate visual representation aids traders in quickly discerning the prevailing market direction, facilitating swift decision-making.
Buy & Sell Signals: SMRT Algo Swing generates distinct buy and sell signals categorized into two levels, weak and strong.
- Weak Signals: These signals are generated when the basic entry criteria are met. They serve as early alerts to potential trading opportunities, suitable for traders willing to take on more risk or those employing a more aggressive trading strategy.
- Strong Signals: Generated when additional, more stringent conditions are satisfied, these signals indicate higher-probability trade setups.
EMA Filter: The Exponential Moving Average (EMA) filter is a feature that facilitates trend trading. When turned on, the filter ensures that only signals that align with the prevailing trend are displayed. This helps in avoiding counter-trend trades, which can be riskier and less reliable. The EMA length is customizable, allowing traders to adjust the sensitivity of trend detection based on their trading style and market conditions.
Take Profit & Stop Loss Levels: TP & SL levels are pre-calculated based on a risk-reward ratio:
- TP1: Indicates a conservative 1:1 risk-reward ratio, suitable for quick profit-taking. Goes up to TP3. This approach to TP and SL can help traders define their risk exposure clearly and set realistic profit targets.
Strong signals are designed to provide highly accurate entry points, often referred to as "sniper entries," due to their precision in aligning with market trends. The option to display weak, strong, or both types of signals allows traders to tailor the indicator to their specific trading preferences and risk profiles.
Input Settings:
Bar Color: Bar colors can be turned on/off. Green candles show a bullish market/trend, while red candles show bearish.
Signal: Choose to show either only Strong/Weak/Both buy & sell signals.
Lookback Period: The higher the lookback period, the less frequent the signals. Adjusting this value affects the frequency of the buy sell signals.
EMA Filter: Trend filter can be turned on/off. If on, it will only show buy signals that are above the EMA, and sell signals that are below the EMA.
Timeframe: EMA timeframe can be adjusted, i.e. to view higher timeframe trends.
Length: Used to adjust EMA length. A smaller value means that EMA is more susceptible to market movements.
TP/SL: The take profit & stop loss zones can be turned on/off. The size of TP/SL can also be adjusted by increasing or decreasing the multiplier and length values.
EMA Filter Off:
EMA Filter On:
We recommend traders use this indicator on timeframes 1H and above, with the goal of holding trades over a longer period of time (days, weeks, months) to maximize the market moves.
The integration of these features ensures that the SMRT Algo Swing indicator functions as a cohesive and robust tool for swing traders. The color-coded bars provide an at-a-glance trend overview, which is crucial for context. The buy/sell signals, especially the strong signals, offer entry points that are carefully vetted by the indicator's algorithms. The EMA filter adds a layer of trend confirmation, ensuring that trades are not only timely but also in line with the broader market trend, thereby enhancing the likelihood of success. The TP and SL levels serve as a built-in risk management system, guiding traders on optimal exit points and helping to protect against significant losses.
The SMRT Algo Suite, which the Swing indicator is a part of, offers a comprehensive set of tools and features that extend beyond the capabilities of standard or open-source indicators, providing significant additional value to users.
What you also get with the SMRT Algo Suite:
Advanced Customization: Users can customize various aspects of the indicator, such as toggling the confirmation signals on or off and adjusting the parameters of the MA Filter. This customization enhances the adaptability of the tool to different trading styles and market conditions.
Enhanced Market Understanding: The combination of pullback logic, dynamic S/R zones, and MA filtering offers traders a nuanced understanding of market dynamics, helping them make more informed trading decisions.
Unique Features: The specific combination of pullback logic, dynamic S/R, and multi-level TP/SL management is unique to SMRT Algo, offering features that are not readily available in standard or open-source indicators.
Educational and Support Resources: As with other tools in the SMRT Algo suite, this indicator comes with comprehensive educational resources and access to a supportive trading community, as well as 24/7 Discord support.
The educational resources and community support included with SMRT Algo ensure that users can maximize the indicators’ potential, offering guidance on best practices and advanced usage.
SMRT Algo believe that there is no magic indicator that is able to print money. Indicator toolkits provide value via their convenience, adaptability and uniqueness. Combining these items can help a trader make more educated; less messy, more planned trades and in turn hopefully help them succeed.
RISK DISCLAIMER
Trading involves significant risk, and most day traders lose money. All content, tools, scripts, articles, and educational materials provided by SMRT Algo are intended solely for informational and educational purposes. Past performance is not indicative of future results. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
TrendScope:TrendScope Indicator Description with First-Time User Tutorial
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Overview:
The TrendScope indicator is designed to give traders a comprehensive view of the market by combining multiple filter sets that analyze different aspects of price action. The filter sets allow you to switch between different views effortlessly and avoid indicator clutter. Whether you're scalping, swing trading, or identifying breakout opportunities, TrendScope helps you make informed decisions by assessing momentum, volatility, trade timing, and trend direction. It also includes a scalp setup you can use to execute trades and manage risk.
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TrendScope Filter Sets with First-Time User Setup & Tutorial
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Filter Set A: Short-Term Momentum
Goal:
This filter focuses on the immediate market sentiment without any additional indicators. It reveals where retail traders might enter the market, potentially highlighting areas where they could be stopped out. The goal is to identify these weak spots and anticipate likely price movements that could follow.
No Additional Indicators Required:
This filter set uses moving averages (SMA 20, SMA 50, SMA 100) to determine the short-term trend.
Tutorial:
- To Confirm an Uptrend: Ensure all moving averages are aligned in sequence: SMA 20 above SMA 50, and SMA 50 above SMA 100, all trending upwards.
Action: Consider going long using the scalper in Filter Set D.
- To Confirm a Downtrend: Ensure all moving averages are aligned in sequence: SMA 20 below SMA 50, and SMA 50 below SMA 100, all trending downwards.
Action: Consider going short using the scalper in Filter Set D.
- To Confirm Consolidation: If the moving averages are not aligned or are intertwined, the market is either about to or already trending sideways. The market is in a consolidation phase.
Action: Switch to Filter Set C for further analysis.
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Filter Set B: Long-Term Momentum
Goal:
Similar to the short-term filter, but with a broader perspective. It helps in understanding the bigger picture, providing insights into longer-term trends and potential reversals for swing trade entries.
No Additional Indicators Required:
This filter set uses moving averages (SMA 20, SMA 100, SMA 200) to determine the long-term trend.
Tutorial:
- To Confirm an Uptrend: Ensure all moving averages are aligned in sequence: SMA 20 above SMA 100, and SMA 100 above SMA 200, all trending upwards.
Action: Consider going long using the scalper in Filter Set D.
- To Confirm a Downtrend: Ensure all moving averages are aligned in sequence: SMA 20 below SMA 100, and SMA 100 below SMA 200, all trending downwards.
Action: Consider going short using the scalper in Filter Set D.
- To Confirm Consolidation: If the moving averages are not aligned or are intertwined, the market is either about to or already trending sideways. The market is in a consolidation phase.
Action: Switch to Filter Set C for further analysis.
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Filter Set C: Trading Range
This filter uses Bollinger Bands, Volume, and Volume-Weighted Relative Volume Profile (VRVP) to identify trading ranges and predict breakouts and trade timing. In short, when Bollinger Bands contract and volume is below average, the VRVP highlights low-volume areas that can serve as breakout targets, offering a timing edge.
Goal:
Anticipate breakouts in a sideways market.
Additional Indicators Required:
- VRVP: For visualizing volume at specific price levels.
- Volume Indicator: With a 100-period moving average for anticipating low market participation.
Tutorial:
1. Setup Screen: Zoom out to see the entire consolidation phase.
2. Identify Support & Resistance:
- Use VRVP to determine VAH (upper range) and VAL (lower range) support or resistance levels.
- Identify the POC (Point of Control) as the area with the highest support or resistance.
3. Wait for Setup:
- Wait for Bollinger Bands to contract and volume to dip below the average.
- Go short if the price is at VAH, go long if the price is at VAL.
4. Action: Switch to Filter Set D for precise entry, target, and risk management.
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Filter Set D: Scalper
After determining the market condition using the previous filter sets, you can use this filter set to hunt for trades. Designed for use with Heikin Ashi candles, this filter allows you to enter when there’s high momentum and provides a trailing stop along the way.
Goal:
Execute trades in harmony with the established trend.
Setup Rules:
1. Condition 1: You know the current trend direction as per filter set guidance (A, B, & C), and the trend is up, and you are going long.
2. Condition 2: Wait for the price to close 3 consecutive flat-bottom Heikin Ashi candles above the 7 MA. Then Enter on the open of the fourth Candle.
3. Condition 3: The 3x candles have to be above the 7 MA (red line), and the 7 MA has to be above the 50 EMA (yellow line).
Trade Management:
Use the 50 EMA (Yellow Line) as a trailing stop and hold the position until a candle opens and closes below the 7 SMA (Red Line).
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Additional Filter Sets
These filter sets are designed to accommodate various trading strategies, allowing for flexibility depending on the trader's approach.
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Filter Set E: VWAP
When using the VWAP filter, load the On-Balance Volume (OBV) indicator to complement your analysis. This combination can help confirm volume trends and potential price movements.
Tips:
Look for instances where the VWAP aligns with OBV divergences to confirm or negate potential trade setups.
Tutorial:
- Complement with OBV: Look for volume confirmations.
- Usage: Switch the candles to a line chart. Wait for both the line to close above the VWAP and OBV above the Smoothing Line. Then, switch to Filter Set D and hunt for a long entry as per the strategy. Do the opposite for hunting short entries.
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Filter Set F: Super Trend
This filter is most effective when paired with the Ichimoku Cloud (using custom settings) along with the MACD and ADX indicators.
Goal:
Gauge trend strength, momentum, and support and resistance levels.
Tutorial:
- Load Ichimoku, MACD, and ADX: To gauge trend strength and momentum.
- Usage Tips:
I use the cloud to look for long periods where the clouds print horizontal levels and use them for support and resistance levels. Alternatively, use the ADX. When the price breaks up through the super trend downtrend line and retraces back to the top of the Ichimoku cloud, switch to Filter Set D and hunt for a long scalp entry. For a short entry, wait for the price to break through the Up Trend Line and retrace back up to the cloud. Then, switch to Filter Set D and use the setup to hunt for a short.
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Filter Set G: Keltner Channels
Combine this filter with Donchian Channels and the Average True Range (ATR) for enhanced volatility analysis. This filter set works similarly to Filter Set C.
Goal:
Measure volatility and predict breakouts.
Tutorial:
- Load Donchian Channels or ATR: To measure volatility and breakouts.
- Usage Tips:
Look for the price to fall through the Keltner lower line and the ATR making a higher low. Then, use the scalper for entries, with Donchian boundaries as take-profit estimates.
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Filter Set H: Pivot Points
This filter works with the RSI to spot divergences that could signal a trend change or reversal.
Goal:
Identify divergences and trend reversals.
Tutorial:
- Load RSI: For identifying divergences.
- Usage Tips:
Use RSI in conjunction with pivot points to identify divergences. Then, switch to Filter Set D and use the scalper to hunt for swing entries in the divergence direction.
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Filter Set I: Opening Range Breakout
This filter uses the Seasonality indicator to gauge investor sentiment and prediction sentiment.
Goal:
Assess market sentiment and predict breakout directions.
Tutorial:
- Load Seasonality Indicator: To assess market sentiment.
- Usage Tips:
Use seasonal trends to gauge potential breakout directions. Use on the daily timeframe only. Risk on investment zones are when the price is close to the ORB low level. Realize investment profit when the price is nearing the ORB high level, considering that there has to be divergence as determined using Filter Set H.
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By following this structured approach, traders can learn to navigate different market conditions, using TrendScope to make informed decisions based on a comprehensive analysis of momentum, trend, and volatility. The goal is to go through all the filter sets and combine them with the scalp setup in Filter Set D, using the additional filters to adapt to various strategies and market conditions.
Three Anchored Moving Averages (VWAP / SMA / EMA)
This indicator allows users to anchor three types of moving averages (Simple Moving Average (SMA), Exponential Moving Average (EMA), and Volume Weighted Average Price (VWAP)) to specific points in time (anchor points)
Key Features:
Select from three Moving Average Types:
Simple Moving Average (SMA): Averages the closing prices over a specified period.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to new information.
Volume Weighted Average Price (VWAP): Averages the price weighted by volume, useful for understanding the average price at which the asset has traded over a period.
Up to Three Anchor Points:
Users can set up to three different anchor points to calculate the moving averages from specific dates and times. This allows for analysis of price action starting from significant points or specific events. For example, you can anchor to the low and high of a move to identify key levels or to points where the price takes off from a previous anchored MA.
Customisable Sentiment Options:
Each anchor point can be associated with a sentiment input (Auto, Bull, Bear, None), which influences if the MAs are displayed as lines or zones/bands:
Auto: Automatically determines the sentiment based on whether anchor points are on pivot highs and lows. If anchored to a pivot high, the system will assume a bearish sentiment and display a red band or zone between the MA OHLC4 and High. Anchoring to a pivot low will display a green band (OHLC4 - Low).
Bull: Forces a bullish sentiment (Green Band - OHLC4 to Low)
Bear: Forces a bearish sentiment (Red Band - OHLC4 to High)
None: Ignores sentiment and displays a single line (OHLC4)
Chart Matching:
The indicator includes an option to display the moving averages only if the chart symbol matches a specified ticker. This feature ensures that the indicator is relevant to the specific asset being analysed.
How to Use the Indicator:
1. Set Anchor Points: When added to your chart, select three anchor points by point and click. If you only wish to anchor to a single point, click on that point three times and disable the other two in settings once the indicator is applied.
2. Select Moving Average Type: Choose between SMA, EMA, or VWAP using the dropdown menu. EMAs are the most responsive.
3. Enable/Disable Anchor Points: Use the checkboxes to enable or disable each anchor point.
4. Select Sentiment Type: Choose between Auto, Bull, Bear, or None.
5. Chart Matching: Optionally, specify a chart symbol to restrict the indicator's display to that particular asset.
6. Interpret the Plots: The indicator plots the high, mid, and low values of the selected moving average type from each anchor point. The fills between these plots help identify potential support and resistance zones. These should be used as points of interest for pullback reversals or potential continuation if the price breaks through.
Practical Applications:
Trend Analysis: Identify the overall trend direction from specific historical points.
Support and Resistance: Determine key dynamic support and resistance levels based on anchored moving averages.
Event-Based Analysis: Anchor the moving averages to significant events (e.g., earnings releases, economic data) to study their impact on price trends.
Multi Timeframe Analysis: Higher Timeframe Anchors can be used to identify longer term trend analysis. Switching to a lower timeframe for execution triggers at these points wont distort the MA levels as they are anchored to a specific point in time
Intraday or Swing Trading: trend analysis using anchor points can be used for any style of trading (Intraday / Swing / Invest). Use anchored levels as points of interest and wait for hints in price action to try and catch the next move.
MTF-Colored EMA Difference and Stochastic indicatorThis indicator combines two popular technical analysis tools: the Exponential Moving Average (EMA) and the Stochastic Oscillator, with the added flexibility of analyzing them across multiple time frames. It visually represents the difference between two EMAs and the crossover signals from the Stochastic Oscillator, providing a comprehensive view of the market conditions.
Components:
EMA Difference Histogram :
EMA Calculation : The indicator calculates two EMAs (EMA1 and EMA2) for the selected time frame.
EMA Difference : The difference between EMA1 and EMA2 is plotted as a 4 coloured histogram.
Stochastic Oscillato r:
Calculation : The %K and %D lines of the Stochastic Oscillator are calculated for the selected time frame.
Additional Confirmation via Colors :
Green: %K is above %D, indicating a bullish signal.
Red: %K is below %D, indicating a bearish signal.
Entry and Exit Strategies
Entry Strategy :
Bullish Entry :
Condition 1: The histogram is Dark green (indicating a strong upward trend).
Condition 2: The Stochastic colour is green (%K is above %D).
Bearish Entry :
Condition 1: The histogram is Dark Red (indicating a strong downward trend).
Condition 2: The Stochastic colour is red (%K is below %D).
Exit Strategy:
Bullish Exit:
Condition: The Stochastic colour turns red (%K crosses below %D).
Bearish Exit:
Condition: The Stochastic colour turns green (%K crosses above %D).
Additional Considerations:
Time Frame Selection : The chosen time frame for both the EMA and Stochastic calculations should align with the trader’s strategy (e.g., daily for swing trading, hourly for intraday trading).
Risk Management : Implement stop-loss orders to manage risk effectively. The stop-loss can be placed below the recent swing low for long positions and above the recent swing high for short positions.
Confirmation : Consider using this indicator in conjunction with other technical analysis tools to confirm signals and reduce the likelihood of false entries and exits.
Groupings [SS]Hey everyone,
Releasing this indicator called groupings.
If you watch/read my analyses on Tradingview, you will have heard me talk about groups. Groups is something I invented. What it is, is just taking the Euclidean Distance (ED) of the previous 5 candles in a specified period (i.e. daily timeframe, weekly, 1 minute, 5 minute, etc.) and rounding the ED up to a whole number.
I have had great success in this approach because the information provided is broad enough to give leniency in interpretation but narrow enough to hone in on potential moves and target prices.
This indicator is a simplified version of how I do groupings in other software, however it is no less powerful!
What do groups tell us?
A "group" takes into account the previous 5 candles, using the ED. This gives Pinescript a general idea of what the short term trend looks like mathematically. From there, Pinescript can look for other groups that looked similar to how this current trend looks. From there, it can offer us insights into what tends to happen in candles subsequent to this group. For example, the ATR range, the close range and whether it is bearish or bullish.
And that is precisely how this indicator operates, Pinescript will calculate the group of the previous 5 canndles in the timeframe period you are looking at. It will then lookback over the designated "train" length and identify previous groups, and what happened in those groups. It looks specifically at:
- What is that average High ATR associated with that group,
- What is the average Low ATR associated with that group,
- What is the average close range associated with that group,
- What is the sentiment associated with that group.
How to use the indicator?
In terms of use, the indicator is relatively simple to use. It will plot three lines, a red for the anticipated low range, a green for the anticipated high range and purple for the opening range (where the current candle opened at).
In addition, it will plot a dot for the anticipated close area. When the dot is green, it expects a bullish close. When the dot is red, it expects a bearish close.
The indicator is going to give you a heads up as to whether we are in a bullish group, what you can anticipate the high and low range to be and where you can anticipate the close.
Of course, its not always exact, as in the image above you can see it underestimated the high range and over-estimated the low range; however, we did close within the anticipate range.
The indicator is meant to help you with your bias. I will reference this indicator on the daily timeframe at open to see what the expectations are for the day.
However, you can use it on any timeframe you wish.
Other functions:
The indicator can plot the EMA 9, 21 and 5. These are the 3 indicators I like and I find them helpful for both intraday and swing trading. However, they can be toggled off if you do not wish to view them.
In addition, the EMAs will be green if the ticker is trending above the EMA 21 (which is a critical EMA for me to determine the immediate sentiment). If the ticker is below, they will turn red.
There is also the ability to adjust the train time. The default is 1,000 candles back, but I usually have it on 1500. If you have a lot of indicators and a lot going on, on your chart, you may find that 1500 is too much and it will lag/error. That’s okay, 500 candles is sufficient and will not put a lot of stress on Pinescript.
Concluding remarks
Its overall a fairly simple concept and indicator, but it has been a neat and helpful / insightful invention. I originally developed this using R and happy to have now brought it into Pinescript.
I hope you enjoy!
Safe trades everyone!
Ripster MTF CloudsDescription:
MTF EMA Cloud By Ripster
EMA Cloud System is a Trading System Invented by Ripster where areas are shaded between two desired EMAs. The concept implies the EMA cloud area serves as support or resistance for Intraday & Swing Trading. This can be utilized effectively on 10 Min for day trading and 1Hr/Daily for Swings. Ripster himself utilizes various combinations of the 5-12, 34-50, 8-9, 20-21 EMA clouds but the possibilities are endless to find what works best for you.
“Ideally, 5-12 or 5-13 EMA cloud acts as a fluid trendline for day trades. 8-9 EMA Clouds can be used as pullback Levels –(optional). Additionally, a high level price over or under 34-50 EMA clouds confirms either bullish or bearish bias on the price action for any timeframe” – Ripster
This indicator is an extension of the Ripster EMA Clouds. It allows you to visualize Exponential Moving Average (EMA) clouds from any time frame on your current chart, regardless of the chart's own time frame. This functionality is especially useful for traders who want to monitor higher time frame trends and support/resistance levels while trading on lower time frames.
What does this code do?
The Ripster MTF Clouds indicator displays two sets of EMA clouds. Each set consists of a short EMA and a long EMA. By default, the indicator uses Daily 20/21 and 50/55 EMAs, but you can customize these settings to fit your trading strategy. The EMAs are plotted on your chart along with their corresponding clouds, colored for easy differentiation:
EMA 1 (default 50/55): Plotted in blue.
EMA 2 (default 20/21): Plotted in teal.
The indicator uses the security function to fetch EMA values from higher time frames and plots them on your current chart, allowing you to see how these higher time frame EMAs interact with your current time frame's price action.
How to use this indicator:
Adjust Resolution:
Set the "Resolution" input to the time frame from which you want to fetch EMA values. For example, set it to "1H" if you want to see 1-hour EMAs on your current chart.
Customize EMAs:
Modify the "EMA 1 Short Length" and "EMA 1 Long Length" inputs to change the default 50/55 EMAs.
Adjust the "EMA 2 Short Length" and "EMA 2 Long Length" inputs to change the default 20/21 EMAs.
Monitor Clouds:
The indicator fills the area between the short and long EMAs, creating a cloud that helps visualize the trend. A blue cloud indicates the area between the EMA 1 pair, while a teal cloud indicates the area between the EMA 2 pair.
Use Multiple Instances:
You can add multiple instances of this indicator to your chart to monitor multiple higher time frames simultaneously. For instance, one instance can show daily clouds while another shows hourly clouds.
Integration with Trading Strategy:
Use this indicator to identify higher time frame trends and support/resistance levels, which can help improve your trading decisions on lower time frames.
For example, you can go long when the stock is above the 50-55 EMA clouds and 20-21 EMA clouds with daily resolution on a 10-minute chart and short when it is below it.
Similarly, you can short a stock under the 1-hour 34/50 EMA clouds while still trading on a 10-minute chart.
Dynamic Support & Resistance Tracker with MTFDynamic Support & Resistance Tracker with Weekly, Monthly & Daily Levels
The Dynamic Support & Resistance Tracker is designed to help traders identify key support and resistance levels across multiple timeframes, enhancing market analysis and decision-making. This indicator calculates and plots support and resistance levels for daily, weekly, and monthly periods, along with extension lines that provide insights into potential price targets.
Key Features:
Multi-Timeframe Analysis:
Daily Levels: Identifies the high, low, and midpoint for each trading day. These levels help traders recognize important price points for short-term trading strategies.
Weekly Levels: Plots the high, low, and midpoint for each week. This feature is valuable for swing traders who need to understand broader market trends.
Monthly Levels: Displays the high, low, and midpoint for each month, which is essential for long-term investors.
Extension Lines:
Calculates extension lines beyond the standard support and resistance levels to help anticipate potential price targets and reversals. These extensions are based on the distance between the high/low and midpoint levels.
Real-Time Updates:
Automatically updates the levels based on the most recent market data, ensuring traders have the most current information for their analysis.
Clear Visuals:
The indicator provides clearly labeled and color-coded lines for easy identification of key levels, improving the visual clarity of market analysis.
How It Works:
Daily, Weekly, and Monthly Levels: The indicator calculates the high, low, and midpoint levels for daily, weekly, and monthly timeframes and plots them on the chart. These levels serve as potential areas of support and resistance where price action may react.
Extension Lines: The extension lines are calculated based on the distance between the high/low and midpoint levels, projecting potential areas where price may find support or resistance beyond the standard levels.
Automatic Updates: The indicator continuously updates the plotted levels based on the latest market data, providing real-time insights.
Benefits:
Improved Market Analysis: By providing a clear view of support and resistance levels across multiple timeframes, this indicator helps traders understand market trends and price movements more effectively.
Informed Trading Decisions: The detailed plotting of levels and extensions allows traders to make more informed decisions, enhancing their trading strategies.
Versatility: Suitable for various trading styles, including intraday trading, swing trading, and long-term investing.
Instructions for Use:
Analyze the Levels: Observe the plotted high, low, and mid-levels for daily, weekly, and monthly timeframes.
Plan Your Trades: Use the identified support and resistance levels to set your entry and exit points, stop-losses, and profit targets.
Monitor the Market: Stay updated with real-time adjustments of the levels, ensuring you always have the latest market information.
Note: This indicator is designed to enhance your trading analysis by providing clear and reliable support and resistance levels. However, it should be used as part of a comprehensive trading strategy and not as the sole basis for trading decisions.
Gap Finder with Horizontal LinesBecause I was tired of manually marking gaps, I coded a simple script to automatically mark all candle gaps.
To ensure that all gaps are displayed even when only the wicks of the next candles touch the previous candle, the condition for identifying gaps was adjusted. Now this indicator tracks all gaps live and highlights high-volume price changes, which is important for swing trading or day trading. The code checks if the previous candle is completely below or above the current candle, considering both the bodies and the wicks.
There are a few scenarios where I use this indicator:
Scenario 1:
When the price increases with gaps, there is a high chance the price will come down to fill the gap.
Scenario 2:
When you see a cluster of many gaps and indicator lines, there is a high chance that there was a lot of volume and possible support.
Settings:
Update: You can change the transparency of the Lines to keep your Chart clean.
In the picture above, I marked some gaps that were closed shortly after they appeared. I use this indicator in the 1M timeframe, where gaps are closed very quickly. Some gaps created by the next candle are closed right away.
The code can be used for your private use and benefit, but please don’t forget to like it if you find it useful.
Pivot Points with MID LevelsThis indicator shows the Standard Pivot Points level based on daily values that can act as support and resistance. It is used by a variety of traders around the world. You can select which time frame Pivot Point Levels you'd like. Daily, weekly etc... Perfect for swing trading or day trading.
Pivot Points- Shows 3 levels of resistance, the Pivot Point and 3 levels of support
(R3, R2, R1, PIVOT POINT, S1, S2, S3
MID Levels- The MID levels are 50% retracement from the pivot point level above it and below
Example- R3, MID, R2, MID, R1, MID, PIVOT POINT, MID, S1, MID, S2, MID, S3
With this indicator you will also have the option to show the Previous days High and Low that are also important levels. On gap up/down days it is always interesting to see if price will close the gap, hence the important level to note.
PDH= Previous Days High
PDL= Previous Days Low
I have added a feature that you can now select specific color to each level and the line style for each level to help understand which levels are being show by personal needs.
Happy Trading
Ratio Chart with GMMA■About this indicator
This indicator divides the selected stocks by any stocks you specify and plots the result in a new pane.
At the same time, it plots the GMMA against the result of the division.
This allows you to see the relative chart and trend of the selected stock and the arbitrary stock.
Quote Symbol: Specify the denominator of the division. The default is TOPIX. Feel free to change it.
EMA Days: 5 to 30 days are indicated in green, and 75 to 200 days in red. Change the number of days and color freely.
Explanation of Effective Usage
It is recommended to enter an index for stocks specified in the Quote Symbol.
By entering the index, you can check the superiority of the selected issue and the index at a glance.
Example: By dividing AAPL by SP500, you can see on the chart whether AAPL is stronger or weaker relative to SP500.
(Similar concept to the Relative Strength Comparison RSC.)
At the same time, by plotting GMMA, you can confirm the trend of strength or weakness of the selected issue divided by the index. This is useful for swing trading and mid- to long-term trading.
The greater the distance between the short-term and long-term EMAs of the GMMA, the more the selected stocks outperform the index, and when the short-term and long-term EMAs cross, the trend ends and the stock underperforms the index.
■About the Chart
The screen below shows a chart plotted using this indicator.
For comparison with the regular chart, the upper screen shows only the GMMA plotted for the selected stocks.
From the red circle in the lower screen, a trend begins where the selected stocks outperform the index, and the trend ends at the blue circle.
When the trend ends, the selected stocks will underperform the index and it can be determined that it is more efficient to invest in another stock.
■このインジケーターについて
このインジケーターは選択している銘柄を、指定した任意の銘柄で割り算し、その結果を新規ペインにプロットします。
同時に、割り算の結果に対してGMMAをプロットします。
これにより選択した銘柄と、任意の銘柄の相対チャートとトレンドを把握することが出来ます。
Quote Symbol：割り算の分母を指定します。デフォルトはTOPIXです。自由に変更して下さい。
EMA日数：5～30日が緑、75～200日を赤で表記しています。日数と色は自由に変更して下さい。
■有効な使い方の説明
Quote Symbolで指定する銘柄は、指数を入力することを推奨します。
指数を入力することによって、選択した銘柄と指数の優位性を一目で確認出来ます。
例）AAPLをSP500で割ることで、SP500に比べてAAPLが相対的に強いのか、弱いのかをチャートで把握できます。
（相対力比較RSCと似たような考え方です。）
同時にGMMAをプロットすることで、選択した銘柄÷指数の強弱のトレンドを確認できます。これはスイングトレードや中長期トレードに役立ちます。
GMMAの短期EMAと長期EMAの距離が開いていくほど、指数より選択した銘柄がアウトパフォームしていると考えられ、短期EMAと長期EMAが交わるとトレンドは終了し、指数をアンダーパフォームします。
■チャートについて
下の画面がこのインジケーターを使用してプロットしたチャートです。
通常のチャートとの比較のため、上画面には選択した銘柄にGMMAだけをプロットしたものを表示しています。
下の画面の赤い丸から、選択した銘柄が指数をアウトパフォームするトレンドが始まり、青い〇でトレンドは終了します。
トレンドが終了した場合、選択した銘柄は指数をアンダーパフォームするので、別の銘柄に投資する方が効率的と判断できます。
Linear Regression Oscillator [ChartPrime]Linear Regression Oscillator Indicator
Overview:
The Linear Regression Oscillator is a custom TradingView indicator designed to provide insights into potential mean reversion and trend conditions. By calculating a linear regression on the closing prices over a user-defined period, this oscillator helps identify overbought and oversold levels and highlights trend changes. The indicator also offers visual cues and color-coded price bars to aid in quick decision-making.
Key Features:
◆ Customizable Look-Back Period:
Input: Length
Default: 20
Description: Determines the period over which the linear regression is calculated. A longer period smooths the oscillator but may lag, while a shorter period is more responsive but may be noisier.
◆ Overbought and Oversold Thresholds:
Inputs: Upper Threshold and Lower Threshold
Default: 1.5 and -1.5 respectively
Description: Define the upper and lower bounds for identifying overbought and oversold conditions. Values outside these thresholds suggest potential reversals.
◆ Candlestick Color Plotting:
Input: Plot Bar Color
Default: false
Description: Option to color the price bars based on the oscillator's value, providing a visual representation of market conditions. Bars turn cyan for positive oscillator values and blue for negative.
◆ Mean Reversion and Trend Signals:
Visual markers and labels indicate when the oscillator suggests mean reversion or trend changes, aiding in identifying key market turning points.
◆ Invalidation Levels:
Tracks the highest and lowest prices over a recent period to set levels where the current trend signal would be considered invalidated.
◆ Gradient Color Coding:
Utilizes gradient color coding to enhance the visualization of oscillator values, making it easier to interpret overbought and oversold conditions.
◆ Usage Notes:
Setting the Look-Back Period:
Adjust the "Length" input based on the timeframe and the type of trading you are conducting. Shorter periods are more suited for intraday trading, while longer periods can be used for swing trading.
Interpreting Thresholds:
Use the upper and lower threshold inputs to fine-tune the sensitivity of the overbought and oversold signals. Higher absolute values reduce the number of signals but increase their reliability.
Candlestick Coloring:
Enabling the "Plot Bar Color" option can help quickly identify the current state of the oscillator in relation to the zero line. This visual aid can be particularly useful in fast-moving markets.
Mean Reversion and Trend Signals:
Pay attention to the symbols and labels on the chart indicating mean reversion and trend changes. These signals are designed to highlight potential entry and exit points.
Invalidation Levels:
Use the plotted invalidation levels as stop-loss or signal invalidation points. If the price moves beyond these levels, the current trend signal is likely invalid.
This indicator helps traders identify overbought and oversold conditions, potential mean reversions, and trend changes based on the linear regression of the closing prices over a specified look-back period.
Liquidity Hour by Ibramiho v2Liquidity Hour by Ibramiho (Version 2) - Identify High-Potential Reversal Zones
Understanding the pre-New York session hour is crucial for institutional traders. This period is often characterized by increased liquidity and price volatility as major financial players prepare for the upcoming trading day. The Liquidity Hour indicator capitalizes on this phenomenon, automatically pinpointing the candle (by default, in orange) immediately before the New York session opens.
Why Focus on This Candle?
Liquidity Magnet: Institutional traders often use this hour to establish or adjust positions, creating pockets of liquidity.
Breakout and Retracement Potential: The indicator helps you spot potential areas where price might retrace after a breakout, offering high-probability trading opportunities.
Visual Clarity: The highlighted candle acts as a visual anchor, making it easy to identify these key levels on your chart.
How It Works
1. Automatic Detection: The indicator intelligently detects the pre-New York session candle, regardless of your chart's timeframe.
2. Colour Coding: The candle is highlighted in orange (customizable), instantly drawing your attention.
3. Trade Insights: Watch for price breakouts above or below the highlighted candle. When price retraces back to this level, it signals a potential entry or exit point.
Key Features
Customizable Colour: Change the highlight colour to suit your chart preferences.
Working Timeframes: Works on timeframes, from minutes up to 2 hours timeframe.
Versatile Trading: Suitable for both intraday and swing trading strategies.
Unlock the Power of Institutional Liquidity
Don't miss out on the opportunities that arise in the hour before the New York session. With the Liquidity Hour indicator, you'll gain a valuable edge by identifying key levels where price action is most likely to reverse.
SMC Community [algoat] — Smart Money ConceptsEmpower your trading with the core principles of the Smart Money Concepts through interactive features and highly customizable settings.
The indicator's strength lies in the unique SMC Core algorithm, a calculation based on real price action data, capturing every tick from small intraday fluctuations to significant high timeframe movements.
algoat SMC Core is our continually evolving, specialized structure mapping algorithm, serving as the backbone of our price action related publications.
⭐ Key Features
Swing Market Structure: Change of Character, Break of Structure
Recognize and visualize real-time market structures with swing elements. Identify and mark key structural changes in the market to visually highlight shifts in market trends and patterns. This feature is designed to alert you to significant changes in the market's behavior, signaling a potential shift from accumulation to distribution phases, or vice versa. It helps traders adapt their strategies based on evolving market dynamics.
Order Flow: Structure Fractal
Connect the successive structural high and low levels, visualizing the intricate flow of market movements. This feature highlights fractal structures within the market, enabling traders to detect significant price action patterns.
Structure Range: Determine Discount, Premium, and Equilibrium Zones
This feature provides a unique way of visualizing price areas where a security could be overbought or oversold (premium or discount zones) and where the price is expected to be fair and balanced (equilibrium zone). Distance from the current price is displayed in percentage terms, which can assist traders with crucial data for risk management and strategic planning. The Range function helps you identify the most favorable price zones for entries and set your stop-loss and take-profit levels more accurately.
Liquidity Grabs: Reveal Hidden Manipulation Attempts
Identify uncovered market areas where high liquidity trading may take place. Liquidity Grabs help track "smart money" footprints by identifying levels where large institutional traders may have induced liquidity traps. Understanding these traps can aid in avoiding false market moves and optimizing trade entries.
Institutional Interest Zones: Order Blocks and Fair Value Gaps
Uncover areas where bigger orders may be lined up. Reveal zones of interest ordered by volume strength. Receive warnings about market price imbalances.
▸ Order Blocks pinpoint crucial zones where large institutional investors ("smart money") have shown strong buying or selling interest recently. These blocks can serve as a tool for identifying key areas for potential trade entries or exits.
▸ Fair Value Gaps detect discrepancies between the perceived market value and the actual market price, revealing potential areas for price correction. With its mitigation settings, you can fine-tune the FVG detection according to the magnitude of value misalignment you consider significant.
Mitigation types dictate how price interacts with a zone, with order blocks requiring a close through (indicating stronger price movement) and fair value gaps requiring a wick through (hinting at weak rejection).
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⭐ Why SMC?
In the ever-evolving trading landscape, mainstream methods and strategies can quickly become outdated as they are widely adopted. Liquidity is constantly sought after, and the best source for this is exploring and exploiting trading strategies that are widely accepted and applied. Currently, one of these strategies is the SMC (Supply, Demand, and Price Action).
It's no coincidence that our educational materials incorporate concepts such as liquidity grabs (LG) and Smart Money Traps (SMT). As the application of SMC gains popularity among retail traders, trading with this approach becomes more challenging. Therefore, the recent focus has been on reforming the SMC methodology, as it is the only method that relies on real price movements and will always work when applied correctly.
The indicator reflects our personal use and deep comprehension of Smart Money Concepts. It provides streamlined tools for tracking algorithmic trends with modern visualizations, without unnecessary clutter.
▸ What does the proper application of SMC entail?
Many SMC traders associate their key areas of interest with the market structure, which is generally considered acceptable. However, depending solely on a single foundation can lead to significant deviations, which may cause notable impacts on trading results. Moreover, if the basis for the market structure calculation is inaccurate, the consequences can be even more severe. It's akin to risking money on a lottery ticket, believing it will be a winner.
Our methodology is different, and it may ensure longevity in the financial markets. The structure remains crucial, but it is not the sole foundation of everything; instead, it serves as a validation tool. Each calculation, such as order blocks (OB), Fair Value Gaps (FVG), liquidity grabs (LG), range analysis, and more, is independent and unique, separate from the structure. However, validation must ultimately come from the structure itself.
We employ individual and high-quality filters: before a function calculation is validated by the structure, it must undergo rigorous testing based on its own set of validation conditions. This approach aims to enhance robustness and accuracy, providing traders with a reliable framework for making informed trading decisions.
▸ An example of structure validation: Order Block with "Swing Sensitivity"
These order blocks will only be displayed and utilized by the script if there is a swing structure validation with a valid break. In other words, the presence of a confirmed swing Change of Character (ChoCh) or Break of Structure (BoS) is essential for the Order Block to be considered valid and relevant.
This approach ensures that the order blocks are aligned with the overall market structure and are not based on isolated or unreliable price movements. Whether it's Fair Value Gaps (FVG), Liquidity Grabs (LG), Range calculations, or other functionalities, the same underlying principle holds true. The background structure calculation serves as a validation mechanism for the data and insights generated by these functions, ensuring they adhere to the specific criteria and rules established within our methodology. By incorporating this robust validation process, traders can have confidence in the reliability and accuracy of the information provided by the indicator, allowing them to make informed trading decisions based on validated data and analysis.
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👉 Usage - the general approach
Determine your trading style and build your basic strategy:
The indicator helps you understand your trading style, whether it's swing trading, scalping or another approach. By analyzing the SMC indicator, you gain valuable information about potential market trends, entry and exit points, and overall market sentiment.
Steps:
Identify Trading Style: Determine whether you are a swing trader, scalper, or long-term investor. This will influence how you use the indicator.
Analyze Market Trends: Use the SMC indicator to observe market trends and identify potential entry and exit points.
Adapt Strategies: Adjust your strategies based on the market dynamics revealed by the SMC indicator, such as changes in order flow or market structure.
👉 Example of usage
In the following chart, you'll notice how we've utilized the indicator to formulate a strategic trading approach. We've employed Order Blocks equipped with volume parameters to identify crucial market zones. Simultaneously, we've leveraged swing/internal market structures to gain insights into potential long- and short-term market turnarounds. Lastly, we've examined trend line liquidity zones to pinpoint probable impulses and breakouts within ongoing trends.
Now we can see how the price descended to the order block with the highest volume, which we had previously marked as our point of interest for an entry. As the price closed below the median Order Block, we noted its mitigation. After an internal CHoCH, it's directing us towards the main Order Block as a target.
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🧠 General advice
Trading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. By integrating multiple analytical approaches, traders can tailor their strategies to fit their unique trading styles and objectives.
Confirming signals with other indicators
As with all technical indicators, it is important to confirm potential signals with other analytical tools, such as support and resistance levels, as well as indicators like RSI, MACD, and volume. This helps increase the probability of a successful trade.
Use proper risk management
When using this or any other indicator, it is crucial to have proper risk management in place. Consider implementing stop-loss levels and thoughtful position sizing.
Combining with other technical indicators
Integrate this indicator with other technical indicators to develop a comprehensive trading strategy and provide additional confirmation.
Conduct Thorough Research and Backtesting
Ensure a solid understanding of the indicator and its behavior through thorough research and backtesting before making trading decisions. Consider incorporating fundamental analysis and market sentiment into your trading approach.
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⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. A word to the wise is enough: developed by traders, for traders — pioneering innovations for the modern era.
Risk Notice
Everything provided by algoat — from scripts, tools, and articles to educational materials — is intended solely for educational and informational purposes. Past performance does not assure future returns.
TS & AO This is Best Intraday and Swing Trading Indicator
Certainly! Let’s explore some intraday and swing trading indicators that can help traders make informed decisions
SuperTrend:
The Supertrend indicator is commonly used for intraday trading.
It is plotted on the price chart and helps determine the current trend.
Parameters: It uses the Average True Range (ATR) with default values of 10 for the period and 3 for the multiplier.
Interpretation:
Upward trend: When Supertrend is below the bars and changes color to green, it indicates a buy signal.
Downward trend: When Supertrend is above the bars and turns red, it signals a sell opportunity1.
VWAP (Volume Weighted Average Price):
VWAP is a volume-based indicator.
It compares the value of a stock traded at a specific time to the total volume traded for that stock.
Interpretation:
Bullish trend: When the stock price is above VWAP, it suggests an uptrend.
Traders can consider buying on retracements toward VWAP in the direction of the trend1.
Moving Averages (MAs):
MAs are versatile indicators suitable for intraday, swing, and longer-term trading.
Common MAs include:
9-day MA: Short-term trend indicator.
50-day MA: Intermediate trend indicator.
100-day MA: Longer-term trend indicator.
Interpretation:
Uptrend: When the stock price is above the MA, it signals a bullish trend.
Downtrend: When the price is below the MA, it suggests a bearish trend2.
[MAD] Entrytool / Bybit-LinearThis indicator, "Entry Tool," was coded at request for Sandmann .
It is designed to provide traders with real-time feedback for strategizing entries, exits, and liquidation levels for trades initiated at that given moment.
The tool visualizes average entry prices, stop-loss levels, multiple take-profit targets, and potential liquidation prices, offering a comprehensive overview of possible trade outcomes. It aids traders in pre-planning their trades by visually simulating the impact of different trading decisions directly on the live chart. Each setting and parameter can be customized to align with individual trading strategies and risk tolerances, making this tool versatile for various trading styles, including day trading, swing trading, and position trading.
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Steps to Use the Indicator:
1. Basic Setup:
Setup Type: Choose between "Long" or "Short" to set the direction of the trade.
Leverage: Adjust the leverage to understand its impact on your potential returns and liquidation price.
Tracking follows the close price, alternative you can enter a specific price.
2. Position Setup:
Initial Entry Amount: Set the starting amount for the trade.
Distance: First Increment Percentage from Entry price
Amount: Define the increase for the first incremental addition to the position and specify the amount to be added.
Distance: Second Increment Percentage from Entry
Amount: Set the increase for the second incremental addition and the corresponding amount.
3. Risk Management:
Stop-Loss (SL) Percentage: Set the percentage below or above the average entry price at which the position should be closed to minimize losses.
Take-Profit (TP) Percentages: Define up to four different profit target levels by specifying the percentage above or below the average entry price.
4. Visual Settings:
Box Colors: Customize the colors of the boxes that represent long and short positions to differentiate easily on the chart.
Box Extension: Determine the length by which the box extends beyond the current bar, which helps in visualizing the potential price movement.
Line Colors and Extensions: Select colors for various lines such as the Average Entry Line, Stop-Loss Line, Take-Profit Lines, and Liquidations Line. Adjust the length of these lines for better visibility.
Label Settings: Configure the distance of labels from their corresponding lines and set the font size for better readability.
5. Additional Features:
Liquidation Price Visualization: This new feature calculates and displays the liquidation price based on the current leverage and margin settings, giving traders a critical insight into their risk exposure.
Interactive Drag Point: Adjust the start price manually by dragging the point on the chart, which dynamically updates entry and exit levels as well as risk metrics.
Detailed Leverage Data Array: Input different scenarios with specific leverage, initial margin, and maintenance rates to see how these factors impact potential liquidation points.
6. Informations about leverage calculation
The data used are fetched from Bybit for Linear pairs to calculate the liquidations like in their documentation.
Keep in mind that other exchanges may calulate based on another formular.
Enhanced Forex IndicatorDescription of the "Enhanced Forex Indicator"
The "Enhanced Forex Indicator" is designed for traders who want a comprehensive technical analysis tool on the TradingView platform. This script integrates Exponential Moving Averages (EMAs), support and resistance zones, and candlestick pattern recognition to provide actionable trading signals, particularly useful for Forex and other financial markets. The script is suitable for intraday trading and swing trading.
Components of the Indicator
Exponential Moving Averages (EMAs):
Short EMA (Blue Line): Faster responding average, good for identifying recent trend changes.
Long EMA (Red Line): Slower moving average, helps in confirming longer-term trends.
Support and Resistance Zones:
Resistance Zone (Red): Area where potential selling pressure could overcome buying pressure, halting price increases temporarily or reversing them.
Support Zone (Green): Area where potential buying pressure could overcome selling pressure, supporting prices and preventing them from falling further.
Candlestick Patterns:
Bullish Engulfing Pattern (Green Triangle Up 'BE'): Suggests a potential upward reversal or start of a bullish trend.
Bearish Engulfing Pattern (Red Triangle Down 'BE'): Indicates a potential downward reversal or start of a bearish trend.
Buy/Sell Signals:
Buy Signal (Green Label 'BUY'): Triggered when the price is above both EMAs and a bullish engulfing pattern is detected.
Sell Signal (Red Label 'SELL'): Triggered when the price is below both EMAs and a bearish engulfing pattern is detected.
Trading Setup:
Entry: Consider entering a buy position when the 'BUY' signal appears, indicating bullish conditions. Enter a sell position when the 'SELL' signal appears, indicating bearish conditions.
Exit: Look for closing signals opposite your entry or use predefined take profit and stop loss levels. For instance, exit a buy position on a 'SELL' signal or when the price drops below the support zone.
Risk Management:
Set stop losses just below the support zone for buy orders and above the resistance zone for sell orders to protect against significant losses.
Adjust position sizes according to your risk tolerance and account balance.
Considerations:
Use this indicator in conjunction with other analysis tools and fundamental data to confirm signals and strengthen your trading strategy.
Periodically backtest the strategy based on this indicator to ensure its effectiveness in current market conditions.
Optimization:
Adjust the lengths of the EMAs and the buffer size of the support and resistance zones to better fit the asset's volatility and your trading timeframe.
Multi-Timeframe Trend TableThe "Multi-Timeframe Trend Table" indicator is a tool that consolidates a variety of critical trading metrics into a single, easy-to-read table format. This indicator is especially useful for traders who need to analyze multiple timeframes and indicators simultaneously to make informed trading decisions. By displaying a broad spectrum of data including trend information, rangebound status, volatility levels, VWAP (Volume Weighted Average Price), and specific candlestick patterns, the indicator provides a comprehensive overview of market conditions across different timeframes.
Functionality and Components
At its core, the indicator provides real-time insights into market trends by showing whether each timeframe is experiencing an upward, downward, or neutral trend based on simple moving averages. This is complemented by the "Rangebound" status, which indicates whether the price is trading within a defined range, giving insights into market consolidation periods. This can be critical for identifying breakouts or breakdowns from established ranges.
Volatility Measurement
Another key feature of the indicator is the "Volatility" column, which rates the market's volatility on a scale from 1 to 10. This feature uses the Average True Range (ATR) to assess how drastically prices are changing within a given timeframe, providing a numerical value that helps traders understand the intensity of price movements. High volatility levels (scores above 6) are highlighted, which can be crucial for strategies that prefer high volatility.
VWAP and Candlestick Patterns
The indicator also displays the VWAP, which is essential for traders who focus on volume as it shows the average price a security has traded at throughout the day, based on both volume and price. It is especially useful for traders looking to confirm trend directions or catch potential reversals. Additionally, the "Candle" column enhances the indicator's utility by identifying specific candlestick patterns like Doji, Hammer, Inverted Hammer, Bullish Engulfing, and Bearish Engulfing, which are pivotal for pinpointing momentum changes and potential entry or exit points.
Usage Strategy
Traders can utilize this indicator by setting up specific rules based on the information provided. For instance, a possible strategy could involve entering a trade when a Bullish Engulfing pattern appears in a low-volatility environment as indicated by a volatility score under 6, suggesting a potential uptrend start with limited downside risk. Similarly, a trader might consider exiting a position or taking a short position when a Bearish Engulfing pattern is identified during high volatility periods, signaling possible sharp price declines.
Adaptability and Customization
An added advantage is the indicator’s adaptability; traders can customize which columns to display based on their trading preferences and strategies. Whether focusing on trends, volatility, or candlestick patterns, users can configure the table to match their specific needs. This makes it a versatile tool suited for various trading styles and objectives, from day trading to swing trading.
Overall Utility
Overall, the "Multi-Timeframe Trend Table" indicator is an invaluable asset for traders who manage multiple instruments across different timeframes, offering a bird's-eye view of the markets in one concise table. It aids in quick decision-making by providing all necessary data points at a glance, reducing the need to switch between multiple charts and potentially missing critical market movements. By integrating trend analysis with volatility and candlestick patterns, it equips traders with a powerful synthesis of technical analysis tools to enhance their trading strategies and improve market timing.
Master Candle Breakout Trading Strategy - Omkar BanneDiscover the Power of Master Candle Trading with Our Indicator! 📈
What does it do?
This indicator scans price action to identify 'Master Candle' formations, a powerful signal indicating potential trend continuations.
A Master Candle occurs when the high and low of the next 4 candles are within the range of the previous candle, suggesting a period of consolidation followed by a breakout.
How can it be used?
Swing Trading
Capture significant price movements by entering trades at the breakout of Master Candle formations.
It can also be used for Intraday trading.
Trend Reversals
Identify potential trend reversals early by recognizing Master Candle patterns.
Entry
The indicator displays the entry price depending on the high of the master candle.
Risk Management
Set stop-loss levels and take-profit targets based on the size of the Master Candle, enhancing risk management.
Customizable Threshold
Adjust tolerance levels for high and low prices to suit your trading style.
Background
It highlights the master candle using a different background colour.
Box
It draws a box around the pattern formation.
Theme Options
Choose between light and dark themes for optimal visibility.
Whether you're a beginner or an experienced trader, our Master Candle Trading Strategy Indicator can enhance your trading arsenal and improve your profitability.
DEMA RSI Overlay [BackQuant]DEMA RSI Overlay
PLEASE Read the following, knowing what an indicator does at its core before adding it into a system is pivotal. The core concepts can allow you to include it in a logical and sound manner.
Anyways,
BackQuant's new trading indicator that blends the Double Exponential Moving Average (DEMA) with the Relative Strength Index (RSI) to create a unique overlay on the trading chart. This combination is not arbitrary; both the DEMA and RSI are revered for their distinct advantages in trading strategy development. Let's delve into the core components of this script, the rationale behind choosing DEMA and RSI, the logic of long and short signals, and its practical trading applications.
Understanding DEMA
DEMA is an enhanced version of the conventional exponential moving average that aims to reduce the lag inherent in traditional averages. It does this by applying more weight to recent prices. The reduction in lag makes DEMA an excellent tool for tracking price trends more closely. In the context of this script, DEMA serves as the foundation for the RSI calculation, offering a smoother and more responsive signal line that can provide clearer trend indications.
Why DEMA?
DEMA is chosen for its responsiveness to price changes. This characteristic is particularly beneficial in fast-moving markets where entering and exiting positions quickly is crucial. By using DEMA as the price source, the script ensures that the signals generated are timely and reflective of the current market conditions, reducing the risk of entering or exiting a trade based on outdated information.
Integrating RSI
The RSI, a momentum oscillator, measures the speed and change of price movements. It oscillates between zero and 100 and is typically used to identify overbought or oversold conditions. In this script, the RSI is calculated based on DEMA, which means it inherits the responsiveness of DEMA, allowing traders to spot potential reversals or continuation signals sooner.
Why RSI?
Incorporating RSI offers a measure of price momentum and market conditions relative to past performance. By setting thresholds for long (buy) and short (sell) signals, the script uses RSI to identify potential turning points in the market, providing traders with strategic entry and exit points.
Calculating Long and Short Signals
Long Signals : These are generated when the RSI of the DEMA crosses above the longThreshold (set at 70 by default) and the closing price is not above the upper volatility band. This suggests that the asset is gaining upward momentum while not being excessively overbought, presenting a potentially favorable buying opportunity.
Short Signals : Generated when the RSI of the DEMA falls below the shortThreshold (set at 55 by default). This indicates that the asset may be losing momentum or entering a downtrend, signaling a possible selling or shorting opportunity.
Logical Soundness
The logic of combining DEMA with RSI for generating trade signals is sound for several reasons:
Timeliness : The use of DEMA ensures that the price source for RSI calculation is up-to-date, making the momentum signals more relevant.
Balance : By setting distinct thresholds for long and short signals, the script balances sensitivity and specificity, aiming to minimize false signals while capturing genuine market movements.
Adaptability : The inclusion of user inputs for periods and thresholds allows traders to customize the indicator to fit various trading styles and timeframes.
Trading Use-Cases
This DEMA RSI Overlay indicator is versatile and can be applied across different markets and timeframes. Its primary use-cases include:
Trend Following: Traders can use it to identify the start of a new trend or the continuation of an existing trend.
Swing Trading: The indicator's sensitivity to price changes makes it ideal for swing traders looking to capitalize on short to medium-term price movements.
Risk Management: By providing clear long and short signals, it helps traders manage their positions more effectively, potentially reducing the risk of significant losses.
Final Note
We have also decided to add in the option of standard deviation bands, calculated on the DEMA, this can be used as a point of confluence rendering trading ranges. Expanding when volatility is high and compressing when it is low.
For example:
This provides the user with a 1, 2, 3 standard deviation band of the DEMA.
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
GKD-B Multi-Ticker Stepped Baseline [Loxx]Giga Kaleidoscope GKD-B Multi-Ticker Stepped Baseline is a Baseline module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
This version of the GKD-B Baseline is designed specifically to support traders who wish to conduct GKD-BT Multi-Ticker Backtests with multiple tickers. This functionality is exclusive to the GKD-BT Multi-Ticker Backtests.
Traders have the capability to apply a filter to the selected moving average, leveraging various volatility metrics to enhance trend identification. This feature is tailored for traders favoring a gradual and consistent approach, enabling them to discern more sustainable trends. The system permits filtering for both the input data and the moving average results, requiring price movements to exceed a specific threshold—defined as multiples of the volatility—before acknowledging a trend change. This mechanism effectively reduces false signals caused by market noise and lateral movements. A distinctive aspect of this tool is its ability to adjust both price and moving average data based on volatility indicators like VIX, EUVIX, BVIV, and EVIV, among others. Understanding the time frame over which a volatility index is measured is crucial; for instance, VIX is measured on an annual basis, whereas BVIV and EVIV are based on a 30-day period. To accurately convert these measurements to a daily scale, users must input the correct "days per year" value: 252 for VIX and 30 for BVIV and EVIV. Future updates will introduce additional functionality to extend analysis across various time frames, but currently, this feature is solely available for daily time frame analysis.
█ GKD-B Multi-Ticker Stepped Baseline includes 65+ different moving averages:
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Ehlers Optimal Tracking Filter - EOTF
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Geometric Mean Moving Average
Coral
Tether Lines
Range Filter
Triangle Moving Average Generalized
Ultinate Smoother
Adaptive Moving Average - AMA
The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Ehlers Optimal Tracking Filter - EOTF
The Elher's Optimum Tracking Filter quickly adjusts rapid shifts in the price and yet is relatively smooth when the price has a sideways action. The operation of this filter is similar to Kaufman’s Adaptive Moving
Average
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and its smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
One More Moving Average (OMA)
The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
█ Volatility Goldie Locks Zone
This volatility filter is the standard first pass filter that is used for all NNFX systems despite the additional volatility/volume filter used in step 5. For this filter, price must fall into a range of maximum and minimum values calculated using multiples of volatility. Unlike the standard NNFX systems, this version of volatility filtering is separated from the core Baseline and uses it's own moving average with Loxx's Exotic Source Types.
█ Volatility Types included
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. You can change the values of the multipliers in the settings as well.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Various volatility estimators and indicators that investors and traders can use to measure the dispersion or volatility of a financial instrument's price. Each estimator has its strengths and weaknesses, and the choice of estimator should depend on the specific needs and circumstances of the user.
Volatility Ticker Selection
Import volatility tickers like VIX, EUVIX, BVIV, and EVIV.
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
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, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, a manual recreation of the quantile function in Pine Script is used. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX).
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker CC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Advance Trend Pressure as shown on the chart above
Confirmation 2: uf2018
Continuation: Coppock Curve
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
ATR Bands (Keltner Channel), Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of ATR Bands, candle wicks crossing the ATR upper and lower bands, and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from the lower band when using phi * multiplier
B2 Signal - Potential pivot up from the lower band when using 1/2 * multiplier
B3 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the upper band when using
S2 Signal - Potential pivot down from the upper band when using 1/2 * multiplier
S3 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional B1, B2, and S1, and S2 signals can be displayed that use the bands based on a multiplier that is half that of the primary one, and phi (0.618) times the primary multiplier as a way to quickly check for signals occurring along different, but related, bands.
Calculations
ATR Bands, or Keltner Channels, are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. ATR Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of ATRs to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of ATRs from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Settings
CHANNEL SETTINGS
Baseline EMA Period (Default: 21): Period length of the moving average basis line.
ATR Period (Default: 21): The number of periods over which the Average True Range (ATR) is calculated.
Basis MA Type (Default: SMA): The moving average type for the basis line.
Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
ADDITIONAL CHANNELS
Half of Multiplier Offset (Default: True): Toggles the display of the ATR bands that are set a distance of half of the ATR multiplier.
Quarter of Multiplier Offset (Default: false): Toggles the display of the ATR bands that are set a distance of one quarter of the ATR multiplier.
Phi (Φ) Offset (Default: false): Toggles the display of the ATR bands that are set a distance of phi (Φ) times the ATR multiplier.
WICK SETTINGS FOR CANDLE FILTERS
Wick Ratio for Bands (Default: 0.4): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.4): The ratio of wick size to total candle size for use at baseline.
Use Candle Body (rather than full candle size) (Default: false): Determines whether wick calculations use the candle body or the entire candle size.
VISUAL PREFERENCES - SIGNALS
Show Signals (Default: true): Allows signal labels to be shown.
Show Signals from 1/2 Band Offset (Default: false): Toggle signals originating from 1/2 offset upper and lower bands.
Show Signals from Phi (Φ) Band Offset (Default: false): Toggle signals originating from phi (Φ) offset upper and lower bands.
Show Baseline Signals (Default: false): Toggle Baseline signals.
VISUAL PREFERENCES - BANDS
Show ATR (Keltner) Bands (Default: true): Use a background color inside the Bollinger Bands.
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
