GM-8 and ADX Strategy with Second EMADescription:
This TradingView script implements a trading strategy based on the Moving Average (GM-8), the Average Directional Index (ADX), and the second Exponential Moving Average (EMA). The strategy utilizes these indicators to identify potential buy and sell signals on the chart.
Indicators:
GM-8 (Moving Average 8): This indicator calculates the average price of the last 8 periods and is used to identify trends.
ADX (Average Directional Index): The ADX measures the strength of a trend and is used to determine whether the market is moving in a particular direction or not.
Second EMA (Exponential Moving Average): This is an additional EMA line with a period of 59, which is used to provide additional confirmation signals for the trend.
Trading Conditions:
Buy Condition: A buy signal is generated when the closing price is above the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Sell Condition: A sell signal is generated when the closing price is below the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Trading Logic:
If a buy condition is met, a long position is opened with a user-defined lot size.
If a sell condition is met, a short position is opened with the same user-defined lot size.
Positions are closed when the opposite conditions are met.
User Parameters:
Users can adjust the periods for the GM-8, the second EMA, and the ADX, as well as the threshold for the ADX and the lot size according to their preferences.
Note:
This script has been developed for use on a $100,000 account with FTMO, therefore the account size is set to $100,000. Please ensure that the strategy parameters and settings meet the requirements of your trading strategy and carefully review the results before committing real capital.
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Beschreibung:
Dieses TradingView-Skript implementiert eine Handelsstrategie, die auf dem gleitenden Mittelwert (GM-8), dem Average Directional Index (ADX) und der zweiten exponentiellen gleitenden Durchschnittslinie (EMA) basiert. Die Strategie verwendet diese Indikatoren, um potenzielle Kauf- und Verkaufssignale auf dem Chart zu identifizieren.
Indikatoren:
GM-8 (Gleitender Mittelwert 8): Dieser Indikator berechnet den Durchschnittspreis der letzten 8 Perioden und wird verwendet, um Trends zu identifizieren.
ADX (Average Directional Index): Der ADX misst die Stärke eines Trends und wird verwendet, um festzustellen, ob sich der Markt in eine bestimmte Richtung bewegt oder nicht.
Zweite EMA (Exponential Moving Average): Dies ist eine zusätzliche EMA-Linie mit einer Periode von 59, die verwendet wird, um zusätzliche Bestätigungssignale für den Trend zu liefern.
Handelsbedingungen:
Kaufbedingung: Es wird ein Kaufsignal generiert, wenn der Schlusskurs über dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Verkaufsbedingung: Es wird ein Verkaufssignal generiert, wenn der Schlusskurs unter dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Handelslogik:
Wenn eine Kaufbedingung erfüllt ist, wird eine Long-Position mit einer benutzerdefinierten Losgröße eröffnet.
Wenn eine Verkaufsbedingung erfüllt ist, wird eine Short-Position mit derselben benutzerdefinierten Losgröße eröffnet.
Positionen werden geschlossen, wenn die Gegenbedingungen erfüllt sind.
Benutzerparameter:
Benutzer können die Perioden für den GM-8, die zweite EMA und den ADX sowie den Schwellenwert für den ADX und die Losgröße nach ihren eigenen Präferenzen anpassen.
Hinweis:
Dieses Skript wurde für die Verwendung auf einem $100.000-Konto bei FTMO entwickelt, daher ist die Kontogröße auf $100.000 festgelegt. Bitte stellen Sie sicher, dass die Strategieparameter und -einstellungen den Anforderungen Ihrer Handelsstrategie entsprechen und dass Sie die Ergebnisse sorgfältig überprüfen, bevor Sie echtes Kapital einsetzen.
Скользящие средние
Steinkopff SteigungThe "Steinkopff Slope" indicator is a custom tool for TradingView designed to measure and visually represent the percentage slope of a moving average. This indicator is particularly useful for analyzing the momentum of a financial instrument by highlighting changes in the slope of the moving average.
Initially, the indicator allows the user to define the length of the moving average to be used as the basis for the calculation. This input is set to 220 periods by default but can be adjusted according to the user's preference. The moving average itself is calculated based on the closing prices.
The core functionality of the indicator is to calculate the percentage slope of the moving average. This is achieved by determining the change in the moving average between the current period and the previous period and expressing this change relative to the value of the previous period. The result is then scaled by a factor of 10,000 to derive a percentage slope.
To refine the results and smooth out potential outliers, the indicator additionally performs a smoothing of the calculated slope. The user can adjust the length of this smoothing through another input parameter, which is set to 3 periods by default. The smoothed slope is finally displayed as a histogram in blue, with the line thickness set to 1.
A horizontal line at zero (displayed in gray) serves as a reference point to visually distinguish between positive and negative slopes. This helps traders and analysts identify trends: a slope above the zero line indicates a positive trend, while a slope below the zero line signals a negative trend.
In summary, the "Steinkopff Slope" indicator provides a simple yet effective way to understand the momentum and direction of a trend by analyzing and visualizing changes in the slope of a moving average over a definable period.
Advanced Trend Strategy [BITsPIP]The BITsPIP team is super excited to share our latest trading gem with you all. We're all about diving deep and ensuring our strategies can stand the test of time. So, we invite you to join us in exploring the awesome potential of this new strategy and really put it through its pace with some deep backtesting. This isn't just another strategy; it boasts a profit factor hovering around 1.5 across over 1000 trades, which is quite an achievement. Consider integrating it with your trading bots to further enhance your trading efficiency and profit generation. Curious? Ask for trial access or drop by our website for more details.
I. Deep Backtesting
We're all in on transparency and solid results, which is why we didn't stop at 100... or even 500 trades. We went over 1000, making sure this strategy is as robust as they come. No flimsy forecasts or sneaky repainting here. Just good, solid strategy that's ready for the real deal. Curious about the details? Check out our detailed backtesting screenshot for the BINANCE:BTCUSDT in a 5-minute timeframe. It's all about giving you the clear picture.
#No Overfitting
#No Repainting
Backtesting Screenshot
II. Algorithmic Trading
Thinking of trading as a manual game? Think again! Manual trading is a bit like rolling the dice - fun, but kind of risky if you're aiming for consistent wins. Instead, why not lean into the future with algorithmic trading? It's all about trusting the market's rhythm over the long term. By integrating your strategy with a trading bot, you can enjoy peace of mind, rest easy, and keep those emotional trades at bay.
III) Applications
Dive into the Advanced Trend Strategy, your versatile tool for navigating the market's waters. This strategy shines in under an hour timeframes, offering adaptability across stocks, commodities, forex, and cryptocurrencies. Initially fine-tuned for low-volatility cryptos like BINANCE:BTCUSDT , its default settings are a solid starting point.
But here's where your expertise comes into play. Each market beats to its own drum, necessitating nuanced adjustments to stop loss and take profit settings. This customization is key to maximizing the strategy's effectiveness in your chosen arena.
IV) Strategy's Logic
The Advanced Trend Strategy is a powerhouse, blending the precision of Hull Suite, RSI, and our unique trend detector technique. At its core, it’s designed for savvy risk management, aiming to lock in substantial profits while steering clear of minor market ripples. It utilizes stop-loss and take-profit thresholds to form a profit channel, providing a safety net for each trade. This is a trend-following strategy at heart, where these profit channels play a critical role in maximizing returns by securing positions within these "warranty channels."
1. Trend-Following
The market's complexity, influenced by countless factors, makes small movements seem almost chaotic. Yet, the principle of #Trend-Following shines in less volatile markets in long term. The strategy excels by pinpointing the ideal moments to enter the market, coupled with refined risk management to secure profits. It’s tailored for you, the individual trader, enabling you to ride the waves of market trends upwards or downwards.
2. Risk Management
A key facet of the strategy is its emphasis on pragmatic risk management. Traders are empowered to establish practical stop-loss and take-profit levels, tailoring these crucial parameters to the specific market they are engaging in. This customization is instrumental in optimizing long-term profitability, ensuring that the strategy adapts fluidly to the unique characteristics and volatility patterns of different trading environments.
V) Strategy's Input Settings and Default Values
1. Alerts
The strategy comes equipped with a flexible alert system designed to keep you informed and ready to act. Within the settings, you’ll find options to configure order/exit and comment/alert messages to your preference. This feature is particularly useful for staying on top of the strategy’s activities without constant manual oversight.
2. Hull Suite
i. Hull Suite Length: Designed for capturing long-term trends, the Hull Suite Length is configured at 1000. Functioning comparably to moving averages, the Hull Suite features upper and lower bands. Currently, it is set to 1000.
ii. Length Multiplier: It's advisable to maintain a minimal value for the Length Multiplier, prioritizing the optimization of the Hull Suite Length. Presently, it is set to 1.
3. RSI Indicator
i. The RSI is a widely recognized tool in trading. Adapt the oversold and overbought thresholds to better match the specifics of your market for optimal results.
4. StopLoss and TakeProfit
i. StopLoss and TakeProfit Settings: Two distinct approaches are available. Semi-Automatic StopLoss/TakeProfit Setting and Manual StopLoss/TakeProfit Setting. The Semi-Automatic mode streamlines the process by allowing you to input values for a 5-minute timeframe, subsequently auto-adjusting these values across various timeframes, both lower and higher. Conversely, the Manual mode offers full control, enabling you to meticulously define TakeProfit values for each individual timeframe.
ii. TakeProfit Threshold # and TakeProfit Value #: Imagine this mechanism as an ascending staircase. Each step represents a range, with the lower boundary (TakeProfit Value) designed to close the trade upon being reached, and the upper boundary (TakeProfit Threshold) upon being hit, propelling the trade to the next level, and forming a new range. This stair-stepping approach enhances risk management and increases profitability. The pre-set configurations are tailored for $BINANCE:BTCUSDT. It's advisable to devote time to tailoring these settings to your specific market, aiming to achieve optimal results based on backtesting.
iii. StopLoss Value: In line with its name, this value marks the limit of loss you're prepared to accept should the market trend go against your expectations. It's crucial to note that once your asset reaches the first TakeProfit range, the initial StopLoss value becomes obsolete, supplanted by the first TakeProfit Value. The default StopLoss value is pegged at 1.6(%), a figure worth considering in your trading strategy.
VI) Entry Conditions
The primary signal for entry is generated by our custom trend detection mechanism and hull suite values (ascending/descending). This is supported by additional indicators acting as confirmation.
VII) Exit Conditions
The strategy stipulates exit conditions primarily governed by stop loss and take profit parameters. On infrequent occasions, if the trend lacks confirmation post-entry, the strategy mandates an exit upon the issuance of a reverse signal (whether confirmed or unconfirmed) by the strategy itself.
BITsPIP
Gaussian Price Filter [BackQuant]Gaussian Price Filter
Overview and History of the Gaussian Transformation
The Gaussian transformation, often associated with the Gaussian (normal) distribution, is a mathematical function characteristically prominent in statistics and probability theory. The bell-shaped curve of the Gaussian function, expressing the normal distribution, is ubiquitously employed in various scientific and engineering disciplines, including financial market analysis. This transformation's core utility in trading and economic forecasting is derived from its efficacy in smoothing data series and highlighting underlying trends, which are pivotal for making strategic trading decisions.
The Gaussian filter, specifically, is a type of data-smoothing algorithm that mitigates the random "noise" of market price data, thus enhancing the visibility of crucial trend changes and patterns. Historically, this concept was adapted from fields such as signal processing and image editing, where precise extraction of useful information from noisy environments is critical.
1. What is a Gaussian Transformation?
A Gaussian transformation involves the application of a Gaussian function to a set of data points. The function is applied as a filter in the context of trading algorithms to smooth time series data, which helps in identifying the intrinsic trends obscured by market volatility. The transformation is characterized by its parameter, sigma (σ), representing the standard deviation, which determines the width of the Gaussian bell curve. The breadth of this curve impacts the degree of smoothing: a wider curve (higher sigma value) results in more smoothing, beneficial for longer-term trend analysis.
2. Filtering Price with Gaussian Transformation and its Benefits
In the provided Script, the Gaussian transformation is utilized to filter price data. The filtering process involves convolving the price data with Gaussian weights, which are calculated based on the chosen length (the number of data points considered) and sigma. This convolution process smooths out short-term fluctuations and highlights longer-term movements, facilitating a clearer analysis of market trends.
Benefits:
Reduces noise: It filters out minor price movements and random fluctuations, which are often misleading.
Enhances trend recognition: By smoothing the data, it becomes easier to identify significant trends and reversals.
Improves decision-making: Traders can make more informed decisions by focusing on substantive, smoothed data rather than reacting to random noise.
3. Potential Limitations and Issues
While Gaussian filters are highly effective in smoothing data, they are not without limitations:
Lag introduction: Like all moving averages, the Gaussian filter introduces a lag between the actual price movements and the output signal, which can delay decision-making.
Feature blurring: Over-smoothing might obscure significant price movements, especially if a large sigma is used.
Parameter sensitivity: The choice of length and sigma significantly affects the output, requiring optimization and backtesting to determine the best settings for specific market conditions.
4. Extending Gaussian Filters to Other Indicators
The methodology used to filter price data with a Gaussian filter can similarly be applied to other technical indicators, such as RSI (Relative Strength Index) or MACD (Moving Average Convergence Divergence). By smoothing these indicators, traders can reduce false signals and enhance the reliability of the indicators' outputs, leading to potentially more accurate signals and better timing for entering or exiting trades.
5. Application in Trading
In trading, the Gaussian Price Filter can be strategically used to:
Spot trend reversals: Smoothed price data can more clearly indicate when a trend is starting to change, which is crucial for catching reversals early.
Define entry and exit points: The filtered data points can help in setting more precise entry and exit thresholds, minimizing the risk and maximizing the potential return.
Filter other data streams: Apply the Gaussian filter on volume or open interest data to identify significant changes in market dynamics.
6. Functionality of the Script
The script is designed to:
Calculate Gaussian weights (f_gaussianWeights function): Generates the weights used for the Gaussian kernel based on the provided length and sigma.
Apply the Gaussian filter (f_applyGaussianFilter function): Uses the weights to compute the smoothed price data.
Conditional Trend Detection and Coloring: Determines the trend direction based on the filtered price and colors the price bars on the chart to visually represent the trend.
7. Specific Actions of This Code
The Pine Script provided by BackQuant executes several specific actions:
Input Handling: It allows users to specify the source data (src), kernel length, and sigma directly in the chart settings.
Weight Calculation and Normalization: Computes the Gaussian weights and normalizes them to ensure their sum equals one, which maintains the original data scale.
Filter Application: Applies the normalized Gaussian kernel to the price data to produce a smoothed output.
Trend Identification and Visualization: Identifies whether the market is trending upwards or downwards based on the smoothed data and colors the bars green (up) or red (down) to indicate the trend direction.
Money Flow DashboardThe Money Flow Dashboard is my take on trying to replicate the great and mighty Market Cipher's Money Flow and pack it into a comprehensive dashboard format with access to various timeframes.
If Money Flow is king 👑, then follow the Money 💸
How to Use Money Flow Dashboard:
1. Timeframe Selection: Choose the relevant timeframes based on your trading style and preferences. Enable or disable timeframes in the settings to focus on the most relevant ones for your strategy.
2. Dashboard Interpretation: The Money Flow Dashboard displays green (🟢) and red (🔴) symbols to indicate when the Money Flow is in green or in red zone. You can also leverage the Money Flow values on the dashboard to better interpret sentiment and its changes.
3. Dashboard Placement: To maximize effectiveness, consider placing the Money Flow Dashboard alongside your Market Cipher indicator, allowing for seamless analysis of market dynamics on multiple timeframes at the same time.
4. Confirmation and Strategy: Consider Money Flow Dashboard signals as confirmation for your trading strategy. For instance, in an uptrend, look for long opportunities when the dashboard displays consistent green symbols. Conversely, in a downtrend, focus on short opportunities when red symbols dominate.
5. Risk Management: As with any indicator, use Money Flow Dashboard in conjunction with proper risk management techniques. Avoid trading solely based on indicator signals; instead, integrate them into a comprehensive trading plan.
Coiled Moving AveragesThis indicator detects when 3 moving averages converge and become coiled. This indicates volatility contraction which often leads to volatility expansion, i.e. large price movements.
Moving averages are considered coiled when the percent difference from each moving average to the others is less than the Coil Tolerance % input value.
This indicator is unique in that it detects when moving averages converge within a specified percent range. This is in contrast to other indicators that only detect moving average crossovers, or the distance between price and a moving average.
This indicator includes options such as:
- % difference between the MAs to be considered coiled
- type and length of MAs
- background color to indicate when the MAs are coiled
- arrows to indicate if price is above or below the MAs when they become coiled
While coiling predicts an increased probability for volatility expansion, it does not necessarily predict the direction of expansion. However, the arrows which indicate whether price is above or below the moving average coil may increase the odds of a move in that direction. Bullish alignment of the moving averages (faster MAs above the slower MAs) may also increase the odds of a bullish break, while bearish alignment may increase the odds of a bearish break.
Note that mean reversion back to the MA coil is common after initial volatility expansion. This can present an entry opportunity for traders, as mean reversion may be followed by continuation in the direction of the initial break.
Experiment with different settings and timeframes to see how coiled MAs can help predict the onset of volatility.
BINANCE-BYBIT Cross Chart: Spot-Perpetual CorrelationName: "Binance-Bybit Cross Chart: Spot-Perpetual Correlation"
Category: Scalping, Trend Analysis
Timeframe: 1M, 5M, 30M, 1D (depending on the specific technique)
Technical analysis: This indicator facilitates a comparison between the price movements shown on the Binance spot chart and the Bybit perpetual chart, with the aim of discerning the correlation between the two charts and identifying the dominant market trends. It automatically generates the corresponding chart based on the ticker selected in the primary chart. When a Binance pair is selected in the main chart, the indicator replicates the Bybit perpetual chart for the same pair and timeframe, and vice versa, selecting the Bybit perpetual chart as the primary chart generates the Binance spot chart.
Suggested use: You can utilize this tool to conduct altcoin trading on Binance or Bybit, facilitating the comparison of price actions and real-time monitoring of trigger point sensitivity across both exchanges. We recommend prioritizing the Binance Spot chart in the main panel due to its typically longer historical data availability compared to Bybit.
The primary objective is to efficiently and automatically manage the following three aspects:
- Data history analysis for higher timeframes, leveraging the extensive historical data of the Binance spot market. Variations in indicators such as slow moving averages may arise due to differences in historical data between exchanges.
- Assessment of coin liquidity on both exchanges by observing candlestick consistency on smaller timeframes or the absence of gaps. In the crypto market, clean charts devoid of gaps indicate dominance and offer enhanced reliability.
- Identification of precise trigger point levels, including daily, previous day, or previous week highs and lows, which serve as sensitive areas for breakout or reversal operations.
All-Time High (ATH) and All-Time Low (ATL) levels may vary significantly across exchanges due to disparities in historical data series.
This tool empowers traders to make informed decisions by leveraging historical data, liquidity insights, and precise trigger point identification across Binance Spot and Bybit Perpetual market.
Configuration:
EMA length:
- EMA 1: Default 5, user configurable
- EMA 2: Default 10, user configurable
- EMA 3: Default 60, user configurable
- EMA 4: Default 223, user configurable
- Additional Average: Optional display of an additional average, such as a 20-period average.
Chart Elements:
- Session separator: Indicates the beginning of the current session (in blue)
- Background: Indicates an uptrend (60 > 223) with a green background and a downtrend (60 < 223) with a red background.
Instruments:
- EMA Daily: Shows daily averages on an intraday timeframe.
- EMA levels 1h - 30m: Shows the levels of the 1g-30m EMAs.
- EMA Levels Highest TF: Provides the option to select additional EMA levels from the major timeframes, customizable via the drop-down menu.
- "Hammer Detector: Marks hammers with a green triangle and inverted hammers with a red triangle on the chart
- "Azzeramento" signal on TF > 30m: Indicates a small candlestick on the EMA after a dump.
- "No Fomo" signal on TF < 30m: Indicates a hyperextended movement.
Trigger Points:
- Today's highs and lows: Shows the opening price of the day's candlestick, along with the day's highs and lows (high in purple, low in red, open in green).
- Yesterday's highs and lows: Displays the opening price of the daily candlestick, along with the previous day's highs and lows (high in yellow, low in red).
You can customize the colors in "Settings" > "Style".
It is best used with the Scalping The Bull indicator on the main panel.
Credits:
@tumiza999: for tests and suggestions.
Thanks for your attention, happy to support the TradingView community.
TradeTale ScalperThis script explains how "Supertrend" along with ALMA & Simple Moving Average can be used to catch "HH-HL-LH-LL" with linear regression Candles.
Simple Moving Average (MA):-
A simple moving average (SMA) is used in technical analysis, used to help smooth out price data by creating a constantly updated average price. A rising moving average indicates that the security is in an uptrend, while a declining moving average indicates a downtrend.
Supertrend :-
A Super Trend is a trend following indicator similar to moving averages. It is comprise of just two parameters - period and multiplier. Average True Range (ATR) plays a key role in ‘Supertrend’ as the indicator uses ATR to compute its value and it signals the degree of price volatility.
Supertrend Calculations:-
Up = (high + low / 2 + multiplier x ATR
Down = (high + low) / 2 – multiplier x ATR
Calc of Average True Range = / 14
14 is period.
ATR is derived by multiplying the previous ATR with 13.
Add the latest TR and divide it by period.
ATR is important in supertrend.
ALMA:-
Arnaud Legoux Moving Average (ALMA) is a technical analysis indicator that calculates the average price of an asset over a specific period using Gaussian distribution function. It aims to provide a responsive and smooth moving average (MA) while reducing lag and noise.ALMA can be used for trend identification, trend reversal or dynamic support and resistance.
ALMA Calculations:-
ALMA = (Weighted Sum of Prices) / (Sum of Weight).
Weighted Sum of Prices:
- Each price within the selected period is multiplied by a specific weight.
- Weight is determined using a Gaussian function.
- Which assign higher weights to more recent prices and lower weights to older prices.
- That is why its more responsive to price changes
Sum of Weight:
- Add up all the weights using Gaussian function for each price within selected period.
Linear Regression Candles:-
open, high, low, and close values of Linear Regression Candles are adjusted as per Smoothed moving average. This adjustment not only highlights the trend more clearly but also colors the candles in green (for bullish) or red (for bearish) based on whether the close is above or below the open. The advantage of the Linear Regression Indicator over a normal moving average is that it has less lag than the moving average, responding quicker to changes in direction. The downside is that it is more prone to whipsaws.
HH-HL-LH-LL:-
Charts provide traders with a visual representation of the price action over a given period of time. To analyse these charts and make informed trading decisions, traders use various technical indicators, one of which is the concept of Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL). HH, HL, LH, and LL are terms used to describe the price action. They identify the direction of the trend and the potential reversal points. HH and HL are used to identify an uptrend, while LH and LL are used to identify a downtrend.
Logic of this indicator:-
HH & HL are used as Long signals when Supertrend is in Uptrend and is above ALMA & SMA. (also other calculations are used)
LL & LH are used as Short signals when Supertrend is in Downtrend and is below ALMA & SMA. (also other calculations are used)
How to Use:-
Long: when Long appears + Green Candles + price above White SMA Line. (Bullish Entry/ Bear Exit)
Short: when Short appears + Red Candles + price below White SMA Line. (Bearish Entry/ Bull Exit)
Chart Timeframe:-
This Indicator works on all timeframes.
Traders should set stop loss and take profit levels as per risk reward ratio.
Note:
- Hide the actual candles for better view from chart setting.
- you may select "Repaint" from indicator settings in which Long & Short signals will repaint as per the conditions/calculations or you may select "NonRepaint" from indicator settings in which the Long & Short signals will not be repainted.
Like other technical indicators, This indicator also is not a holy grail. It can only assist you in building a good strategy. You can only succeed with proper position sizing, risk management and following correct trading Psychology (No overtrade, No greed, No revenge trade etc).
THIS INDICATOR IS FOR EDUCATIONAL PURPOSE AND PAPER TRADING ONLY. YOU MAY PAPER TRADE TO GAIN CONFIDENCE AND BUILD FURTHER ON THESE. PLEASE CONSULT YOUR FINANCIAL ADVISOR BEFORE INVESTING. WE ARE NOT SEBI REGISTERED.
Hope you all like it
happy learning.
Brilliance Academy Secret StrategyThe Brilliance Academy Secret Strategy is a powerful trading strategy designed to identify potential trend reversals and optimize entry and exit points in the market. This strategy incorporates a combination of technical indicators, including Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), Pivot Points, and Bollinger Bands.
Key Features:
MACD Indicator: A momentum oscillator that helps identify changes in trend strength and direction.
RSI Indicator: A momentum oscillator that measures the speed and change of price movements, indicating potential overbought or oversold conditions.
Pivot Points: Key levels used by traders to identify potential support and resistance levels in the market, aiding in trend reversal identification.
Bollinger Bands: Volatility bands placed above and below a moving average, indicating potential market volatility and overbought or oversold conditions.
How to Use:
Long Signals: Look for long signals when the market price is above the 200-period moving average, MACD line crosses below the signal line, RSI is above 30, and price is above the lower Bollinger Band or at a pivot low.
Short Signals: Look for short signals when the market price is below the 200-period moving average, MACD line crosses above the signal line, RSI is below 70, and price is below the upper Bollinger Band or at a pivot high.
Exit Strategy: Long trades are closed when the next short signal occurs or when the profit reaches a fixed take profit percentage (3% above entry price). Short trades are closed when the next long signal occurs or when the profit reaches a fixed take profit percentage (3% below entry price).
Fibonacci Adaptive Timeframe EMA (FAT EMA)The "Fibonacci Adaptive Timeframe EMA" is a sophisticated trading indicator designed for the TradingView platform, leveraging the power of Exponential Moving Averages (EMAs) determined by Fibonacci sequence lengths to provide traders with dynamic market insights. This indicator overlays directly on the price chart, offering a unique blend of trend analysis, smoothing techniques, and timeframe adaptability, making it an invaluable tool for traders looking to enhance their technical analysis strategy.
Key Features
1. Fibonacci-Based EMA Lengths: Utilizes the Fibonacci sequence to select EMA lengths, incorporating natural mathematical ratios believed to be significant in financial markets. The available lengths range from 1 to 987, allowing for detailed trend analysis over various periods.
2. Multiple Smoothing Methods: Offers the choice between several smoothing techniques, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA or RMA), Weighted Moving Average (WMA), and Volume Weighted Moving Average (VWMA). This versatility ensures that users can tailor the indicator to suit their analytical preferences.
3. Timeframe Adaptability: Features the ability to fetch and calculate EMAs from different timeframes, providing a multi-timeframe analysis within a single chart view. This adaptability gives traders a broader perspective on market trends, enabling more informed decision-making.
4. Dynamic Visualization Options: Traders can customize the display to suit their analysis needs, including toggling the visibility of Fibonacci EMA lines, EMA prices, and smoothed EMA lines. Additionally, forecast lines can be projected into the future, offering speculative insights based on current trends.
5. Ema Tail Visualization: An innovative feature allowing for the visualization of the 'tail' or the continuation of EMA lines, which can be particularly useful for identifying trend persistence or reversal points.
6. User-friendly Customization: Through a series of input options, traders can easily adjust the source data, Fibonacci lengths, smoothing method, and visual aspects such as line colors and transparency, ensuring a seamless integration into any trading strategy.
Application and Use Cases
The "Fibonacci Adaptive Timeframe EMA" indicator is designed for traders who appreciate the significance of Fibonacci numbers in market analysis and seek a flexible tool to analyze trends across different timeframes. Whether it's for scalping, day trading, or long-term investing, this indicator can provide valuable insights into price dynamics, trend strengths, and potential reversal points. Its adaptability makes it suitable for various asset classes, including stocks, forex, commodities, and cryptocurrencies.
Trend, Momentum, Volume Delta Ratings Emoji RatingsThis indicator provides a visual summary of three key market conditions - Trend, Momentum, and Volume Delta - to help traders quickly assess the current state of the market. The goal is to offer a concise, at-a-glance view of these important technical factors.
Trend (HMA): The indicator uses a Hull Moving Average (HMA) to assess the overall trend direction. If the current price is above the HMA, the trend is considered "Good" or bullish (represented by a 😀 emoji). If the price is below the HMA, the trend is "Bad" or bearish (🤮). If the price is equal to the HMA, the trend is considered "Neutral" (😐).
Momentum (ROC): The Rate of Change (ROC) is used to measure the momentum of the market. A positive ROC indicates "Good" or bullish momentum (😀), a negative ROC indicates "Bad" or bearish momentum (🤮), and a zero ROC is considered "Neutral" (😐).
Volume Delta: The indicator calculates the difference between the current trading volume and a simple moving average of the volume (Volume Delta). If the Volume Delta is above a user-defined threshold, it is considered "Good" or bullish (😀). If the Volume Delta is below the negative of the threshold, it is "Bad" or bearish (🤮). Values within the threshold are considered "Neutral" (😐).
The indicator displays these three ratings in a compact table format in the top-right corner of the chart. The table uses color-coding to quickly convey the overall market conditions - green for "Good", red for "Bad", and gray for "Neutral".
This indicator can be useful for traders who want a concise, at-a-glance view of the current market trend, momentum, and volume activity. By combining these three technical factors, traders can get a more well-rounded understanding of the market conditions and potentially identify opportunities or areas of concern more easily.
The user can customize the indicator by adjusting the lengths of the HMA, ROC, and Volume moving average, as well as the Volume Delta threshold. The colors used in the table can also be customized to suit the trader's preferences.
Luxmi AI Smart Sentimeter (Index) "Performance or the direction of indices depend on the performance or direction of its constituents"
The above statement succinctly highlights the fundamental relationship between the movements of stock indices and the individual stocks that comprise them. Essentially, the statement underscores the fact that the overall performance and direction of an index are directly influenced by the collective performance and direction of its constituent stocks.
In essence, when the majority of stocks within an index experience positive movements, such as price increases or upward trends, the index itself tends to rise. Conversely, if a significant number of constituent stocks exhibit negative movements, such as price decreases or downward trends, the index is likely to decline.
This interdependence between indices and their constituents reflects the broader market sentiment and economic conditions. Individual stock movements contribute to the overall market sentiment, which is reflected in the movements of the index. Therefore, investors and traders often analyze the performance of underlying constituents to gain insights into market trends, sentiment shifts, and potential trading opportunities.
In summary, the statement emphasizes the integral role that individual stocks play in shaping the performance and direction of stock indices, highlighting the importance of monitoring constituent stocks when analyzing and trading in the financial markets.
Analyzing the performance of underlying constituents is crucial when trading index futures and options due to several reasons:
Index Composition Impact: Index futures and options derive their value from the performance of the underlying index, which, in turn, is determined by the constituent stocks. Understanding how individual stocks within the index are performing provides insights into the broader market sentiment and direction.
Diversification Assessment: Indices typically consist of a diverse range of stocks across various sectors. Analyzing the performance of these constituent stocks allows traders to assess the overall health of the market and identify sector-specific trends or weaknesses. This information is vital for constructing a well-diversified portfolio and managing risk effectively.
Sector Rotation Strategies: Different sectors perform differently under various market conditions. Analyzing the performance of underlying constituents enables traders to identify sectors that are outperforming or underperforming relative to the broader market. This insight can be utilized to implement sector rotation strategies, where traders adjust their portfolio allocations based on the expected performance of different sectors.
Options Pricing and Hedging: In options trading, the performance of underlying constituents directly affects the pricing of options contracts. Volatility, correlation among stocks, and individual stock movements all influence options prices. By analyzing the performance of underlying constituents, traders can better understand the factors driving options pricing and implement more effective hedging strategies.
Technical Analysis Confirmation: Technical analysis techniques often rely on price movements and patterns observed in individual stocks. Analyzing the performance of underlying constituents can confirm or invalidate technical signals generated by the index itself, providing additional conviction for trading decisions.
In summary, analyzing the performance of underlying constituents when trading index futures and options is essential for understanding market dynamics, identifying trading opportunities, managing risk, and making informed trading decisions. By staying informed about individual stock movements within an index, traders can gain a deeper understanding of market trends and position themselves for success in the ever-changing financial markets.
Workng Principle of Luxmi AI Smart Sentimeter:
The Luxmi AI Smart Sentimeter indicator is a powerful tool designed for traders to gain insights into market sentiment and trend strength. This indicator amalgamates data from multiple stocks to provide a comprehensive overview of market conditions. Let's delve into its components, functionalities, and potential applications.
Firstly, the indicator allows users to input symbols for up to ten different stocks. These symbols serve as the basis for retrieving closing prices, which are essential for conducting technical analysis. The flexibility to choose symbols empowers traders to tailor their analysis according to their preferences and market focus.
The indicator's core functionality revolves around the calculation of a combined Moving Averages of various lenghts, which aggregates the closing prices of the selected stocks. This combined combined analysis serves as a pivotal metric for assessing overall market trends and sentiment. By incorporating data from multiple stocks, the indicator offers a holistic view of market dynamics, reducing the impact of individual stock fluctuations.
To further refine the analysis, the combined Moving Average Data undergoes a smoothing process using another additional Moving Average (SMA). This smoothing mechanism helps filter out noise and provides a clearer depiction of underlying trends, thereby enhancing the indicator's effectiveness.
Moreover, the indicator computes an oscillator by measuring the difference between the combined MA and the smoothed MA. This oscillator serves as a valuable tool for gauging trend strength and identifying potential reversal points in the market, offering further insights into market momentum and directionality.
The indicator's graphical representation includes plots of the oscillator and its MA, facilitating visual interpretation of trend dynamics and momentum shifts. Furthermore, the script generates visual signals, such as UP and DOWN triangles, to highlight crossover and crossunder events on the oscillator, aiding traders in making timely and informed trading decisions.
In practice, the Luxmi AI Smart Sentimeter indicator offers a myriad of applications for traders across various trading styles and timeframes. Traders can utilize it to assess market sentiment, identify trend reversals, and confirm trade signals generated by other technical indicators. Additionally, the indicator can serve as a valuable tool for conducting market analysis, formulating trading strategies, and managing risk effectively.
In conclusion, the Luxmi AI Smart Sentimeter indicator represents a sophisticated yet accessible tool for traders seeking to navigate the complexities of the financial markets. With its robust features, customizable parameters, and insightful analysis, this indicator stands as a testament to the potential of data-driven approaches in trading and investment.
Settings:
The Index Constituent Analysis setting empowers users to input the constituents of a specific index, facilitating the analysis of market sentiments based on the performance of these individual components. An index serves as a statistical measure of changes in a portfolio of securities representing a particular market or sector, with constituents representing the individual assets or securities comprising the index.
By providing the constituent list, users gain insights into market sentiments by observing how each constituent performs within the broader index. This analysis aids traders and investors in understanding the underlying dynamics driving the index's movements, identifying trends or anomalies, and making informed decisions regarding their investment strategies.
This setting empowers users to customize their analysis based on specific indexes relevant to their trading or investment objectives, whether tracking a benchmark index, sector-specific index, or custom index. Analyzing constituent performance offers a valuable tool for market assessment and decision-making.
Example: BankNifty Index and Its Constituents
Illustratively, the BankNifty index represents the performance of the banking sector in India and includes major banks and financial institutions listed on the National Stock Exchange of India (NSE). Prominent constituents of the BankNifty index include:
State Bank of India (SBIN)
HDFC Bank
ICICI Bank
Kotak Mahindra Bank
Axis Bank
IndusInd Bank
Punjab National Bank (PNB)
Yes Bank
Federal Bank
IDFC First Bank
By utilizing the Index Constituent Analysis setting and inputting these constituent stocks of the BankNifty index, traders and investors can assess the individual performance of these banking stocks within the broader banking sector index. This analysis enables them to gauge market sentiments, identify trends, and make well-informed decisions regarding their trading or investment strategies in the banking sector.
Example: NAS100 Index and Its Constituents
Similarly, the NAS100 index, known as the NASDAQ-100, tracks the performance of the largest non-financial companies listed on the NASDAQ stock exchange. Prominent constituents of the NAS100 index include technology and consumer discretionary stocks such as:
Apple Inc. (AAPL)
Microsoft Corporation (MSFT)
Amazon.com Inc. (AMZN)
Alphabet Inc. (GOOGL)
Facebook Inc. (FB)
Tesla Inc. (TSLA)
NVIDIA Corporation (NVDA)
PayPal Holdings Inc. (PYPL)
Netflix Inc. (NFLX)
Adobe Inc. (ADBE)
By inputting these constituent stocks of the NAS100 index into the Index Constituent Analysis setting, traders and investors can analyze the individual performance of these technology and consumer discretionary stocks within the broader NASDAQ-100 index. This analysis facilitates the evaluation of market sentiments, identification of trends, and informed decision-making regarding trading or investment strategies in the technology and consumer sectors.
Example: FTSE 100 Index and Its Constituents
The FTSE 100 index represents the performance of the 100 largest companies listed on the London Stock Exchange (LSE) by market capitalization. Some notable constituents of the FTSE 100 index include:
HSBC Holdings plc
BP plc
GlaxoSmithKline plc
Unilever plc
Royal Dutch Shell plc
AstraZeneca plc
Diageo plc
Rio Tinto plc
British American Tobacco plc
Reckitt Benckiser Group plc
Timeframe Selection:
If a traders wshes to analyze the constituent in a higher timeframe they can simply switch to HTF from the dropdown without changing the chart timeframe.
Weight:
Weight needs to be a positive number when applied on the index future or call option charts.
Weight must be configured to a negative number when this indicator is applied on a put option chart (Put options move in the opposite direction compared to it's stock or index).
Happy Trading,
VCBBDOVWAPSMA By Anil ChawraHow Users Can Make Profit Using This Script:
1. Volume Representation : Each candle on the chart represents a specific time period (e.g., 1 minute, 1 hour, 1 day) and includes information about both price movement and trading volume during that period.
2. Candlestick Anatomy : A volume candle has the same components as a regular candlestick: the body (which represents the opening and closing prices) and the wicks or shadows (which indicate the highest and lowest prices reached during the period).
3. Volume Bars : Instead of just the candlestick itself, volume candles also include a bar or histogram representing the trading volume during that period. The height or length of the volume bar indicates the amount of trading activity.
4. Interpreting Volume : High volume candles typically indicate increased market interest or activity during that period. This could be due to significant buying or selling pressure.
5. Confirmation : Traders often look for confirmation from other technical indicators or price action to validate the significance of a high volume candle. For example, a high volume candle breaking through a key support or resistance level may signal a strong market move.
6. Trend Strength : Volume candles can provide insights into the strength of a trend. A series of high volume candles in the direction of the trend suggests strong momentum, while decreasing volume may indicate weakening momentum or a potential reversal.
7. Volume Patterns : Traders also analyze volume patterns, such as volume spikes or divergences, to identify potential trading opportunities or reversals.
8. Combination with Price Action: Volume analysis is often used in conjunction with price action analysis and other technical indicators to make more informed trading decisions.
9. Confirmation and Validation: It's important to confirm the significance of volume candles with other indicators or price action signals to avoid false signals.
10. Risk Management : As with any trading strategy, proper risk management is crucial when using volume candles to make trading decisions. Set stop-loss orders and adhere to risk management principles to protect your capital.
How to script works :
1.Identify High Volume Candles: Look for candles with significantly higher volume compared to the surrounding candles. These can indicate increased market interest or activity.
2.Wait for Confirmation: Once you identify a high volume candle, wait for confirmation from subsequent candles to ensure the momentum is sustained.
3.Enter the Trade: After confirmation, consider entering a trade in the direction indicated by the high volume candle. For example, if it's a bullish candle, consider buying.
4.Set Stop Loss: Always set a stop loss to limit potential losses in case the trade goes against you.
5.Take Profit: Set a target for taking profits. This could be based on technical analysis, such as a resistance level or a certain percentage gain.
6.Monitor Volume: Continuously monitor volume to gauge the strength of the trend. Decreasing volume may signal weakening momentum and could be a sign to exit the trade.
7.Risk Management: Manage risk carefully by adjusting position sizes according to your risk tolerance and the size of your trading account.
8.Review and Adapt: Regularly review your trades and adapt your strategy based on what's working and what's not.
Remember, no trading strategy guarantees profits, and it's essential to practice proper risk management and have realistic expectations. Additionally, consider combining volume analysis with other technical indicators for a more comprehensive approach to trading.
**How Users Can Make Profit Using This Script:
**
DAYS OPEN LINE:
1.Purpose: Publishing a "Days Open Line" indicator serves to inform customers about the operational schedule of a business or service.
2.Visibility: It ensures that the information regarding the days of operation is easily accessible to current and potential customers.
3.Transparency: By making the operational schedule public, businesses demonstrate transparency and reliability to their customers.
4.Accessibility: The indicator should be published on various platforms such as the business website, social media channels, and physical locations to ensure accessibility to a wide audience.
5.Clarity: The information should be presented in a clear and concise manner, specifying the days of the week the business is open and the corresponding operating hours.
6.Updates: It's important to regularly update the "Days Open Line" indicator to reflect any changes in the operational schedule, such as holidays or special events.
7.Customer Convenience: Providing this information helps customers plan their visits accordingly, reducing inconvenience and frustration due to unexpected closures.
8.Expectation Management: Setting clear expectations regarding the business hours helps manage customer expectations and reduces the likelihood of disappointment or complaints.
9.Customer Service: Publishing the "Days Open Line" indicator demonstrates a commitment to customer service by ensuring that customers have the information they need to engage with the business.
10.Brand Image: Consistently .maintaining and updating the indicator contributes to a positive brand image, as it reflects professionalism, reliability, and a customer-centric approach.
SMA CROSS:
1.This indicator generates buy and sell signals based on the crossover of two Simple Moving Averages (SMA): a shorter 3-day SMA and a longer 8-day SMA.
When the 3-day SMA crosses above the 8-day SMA, it generates a buy signal indicating a potential upward trend.
Conversely, when the 3-day SMA crosses below the 8-day SMA, it generates a sell signal indicating a potential downward trend.
Signal Interpretation:
2.Buy Signal: Generated when the 3-day SMA crosses above the 8-day SMA.
Sell Signal: Generated when the 3-day SMA crosses below the 8-day SMA.
Usage:
3.Traders can use this indicator to identify potential entry and exit points in the market.
Buy signals suggest a bullish trend, indicating a favorable time to enter or hold a long position.
4.Sell signals suggest a bearish trend, indicating a potential opportunity to exit or take a short position.
Parameters:
5.Periods: 3-day SMA and 8-day SMA.
Price: Closing price is commonly used, but users can choose other price types (open, high, low) for calculation.
Confirmation:
6.It's recommended to use additional technical analysis tools or confirmatory indicators to validate signals and minimize false signals.
Risk Management:
7.Implement proper risk management strategies, such as setting stop-loss orders, to mitigate losses in case of adverse price movements.
Backtesting:
8.Before using the indicator in live trading, conduct thorough backtesting to evaluate its effectiveness under various market conditions.
Considerations:
9.While SMA crossovers can provide valuable insights, they may generate false signals during ranging or choppy markets.
Combine this indicator with other technical analysis techniques for comprehensive market analysis.
Continuous Optimization:
10.Monitor the performance of the indicator and adjust parameters or incorporate additional filters as needed to enhance accuracy over time.
BOLLINGER BAND:
1.Definition: A Bollinger Band indicator is a technical analysis tool that consists of a centerline (typically a moving average) and two bands plotted above and below it. These bands represent volatility around the moving average.
2.Purpose: Publishing a Bollinger Band indicator serves to provide traders and investors with insights into the volatility and potential price movements of a financial instrument.
3.Visualization: The indicator is typically displayed on price charts, allowing users to visualize the relationship between price movements and volatility levels.
4.Interpretation: Traders use Bollinger Bands to identify overbought and oversold conditions, potential trend reversals, and volatility breakouts.
5.Components: The indicator consists of three main components: the upper band, lower band, and centerline (usually a simple moving average). These components are calculated based on standard deviations from the moving average.
6.Parameters: Traders can adjust the parameters of the Bollinger Bands, such as the period length and standard deviation multiplier, to customize the indicator based on their trading strategy and preferences.
7.Signals: Bollinger Bands generate signals when prices move outside the bands, indicating potential trading opportunities. For example, a price breakout above the upper band may signal a bullish trend continuation, while a breakout below the lower band may indicate a bearish trend continuation.
8.Confirmation: Traders often use other technical indicators or price action analysis to confirm signals generated by Bollinger Bands, enhancing the reliability of their trading decisions.
9.Education: Publishing Bollinger Band indicators can serve an educational purpose, helping traders learn about technical analysis concepts and how to apply them in real-world trading scenarios.
10.Risk Management: Traders should exercise proper risk management when using Bollinger Bands, as false signals and market volatility can lead to losses. Publishing educational content alongside the indicator can help users understand the importance of risk management in trading.
VWAP:
1.Calculation: VWAP is calculated by dividing the cumulative sum of price times volume traded for every transaction (price * volume) by the total volume traded.
2.Time Frame: VWAP is typically calculated for a specific time frame, such as a trading day or a session.
3.Intraday Trading: It's commonly used by intraday traders to assess the fair value of a security and to determine if the current price is above or below the average price traded during the day.
4.Execution: Institutional traders often use VWAP as a benchmark for executing large orders, aiming to buy at prices below VWAP and sell at prices above VWAP.
5.Benchmark: It serves as a benchmark for traders to evaluate their trading performance. Trades executed below VWAP are considered good buys, while those above are considered less favorable.
6.Sensitivity: VWAP is more sensitive to price and volume changes during periods of high trading activity and less sensitive during periods of low trading activity.
7.Day's End: VWAP resets at the end of each trading day, providing a new reference point for the following trading session.
8.Volume Weighting: The weighting by volume means that prices with higher trading volumes have a greater impact on VWAP than those with lower volumes.
9.Popular with Algorithmic Traders: Algorithmic trading systems often incorporate VWAP strategies to execute trades efficiently and minimize market impact.
10.Limitations: While VWAP is a useful indicator, it's not foolproof. It may lag behind rapidly changing market conditions and may not be suitable for all trading strategies or market conditions. Additionally, it's more effective in liquid markets where there is significant trading volume.
On Chart Reverse PMARPIntroducing the On Chart Reverse PMARP
Concept
The PMAR/PMARP is an indicator which calculates :
The ratio between a chosen source price and a user defined moving average ( Price Moving Average Ratio ).
The percentile of the PMAR over an adjustable lookback period ( Price Moving Average Ratio Percentile ).
Here I have 'reverse engineered' the PMAR / PMARP formulas to derive several functions.
These functions calculate the chart price at which the PMARP will cross a particular PMARP level.
I have employed those functions here to give the "crossover" price levels for :
Scale high level
High alert level
High test level
Mid-Line
Low test level
Low alert level
Scale low level
Knowing the price at which these various user defined PMARP levels will be crossed can be useful in setting price levels that trigger components of various strategies.
For example: A trader can use the reverse engineered upper high alert price level, to set a take profit limit order on a long trade, which was entered when PMARP was low.
This 'On Chart' RPMARP indicator displays these 'reverse engineered' price levels as plotted lines on the chart.
This allows the user to see directly on the chart the interplay between the various crossover levels and price action.
This allows for more intuitive Technical Analysis, and allows traders to precisely plan entries, exits and stops for their PMARP based trades.
It optionally plots the user defined moving average from which the PMARP is derived.
It also optionally plots the 'Reverse engineered' midline, test level lines, visual alert level lines, scale max. and min. level lines, and background alert signal bars.
Main Properties :
Price Source :- Choice of price values or external value from another indicator ( default *Close ).
PMAR Length :- User defined time period to be used in calculating the Moving Average for the Price Moving Average Ratio and the PMAR component of the PMARP ( default *21 ).
MA Type :- User defined type of Moving Average which creates the MA for the Price Moving Average Ratio and the PMAR component of the PMARP ( default *EMA ).
Checkbox and color selection box for the optionally plotted Moving Average line.
Price Moving Average Ratio Percentile Properties :
PMARP Length :- The lookback period to be used in calculating the Price Moving Average Ratio Percentile ( default *350 ).
PMARP Level Settings :
Scale High :- Scale high level ( Locked at 100 ).
Hi Alert :- High alert level ( default *99 ).
Hi Test :- High test level ( default *70 ).
Lid Line :- Mid line level ( Locked at 50 ).
Lo Test :- Low test level ( default *30 ).
Lo Alert :- Low alert level ( default *1 ).
Scale Low :- Scale low level ( Locked at 0 ).
Checkboxes and color selection boxes for each of the optionally plotted lines.
PMARP MA Settings :
Checkbox to optionally plot 'reverse engineered' PMARP MA line.
PMARP MA Length :- The time period to be used in calculating the signal Moving Average for the Line Plot ( default *20 ).
PMARP MA Type :- The type of Moving Average which creates the signal Moving Average for the Line Plot ( default *EMA ).
Color Type :- User choice from dropdown between "single" or "dual" line color ( default *dual ).
Single Color :- Color selection box.
Dual Color :- Color selection box. Note: Defines the color of the signal MA when the MA is falling in "dual" line coloring mode.
Signal Bar Settings :
Signal Bars Transparency :- Sets the transparency of the vertical signal bars ( default *70 ).
Checkboxes and color selection boxes for Upper/Lower alert signal bars.
Volume Candle bollinger band By Anil ChawraHow Users Can Make Profit Using This Script:
1.Volume Representation: Each candle on the chart represents a specific time period (e.g., 1 minute, 1 hour, 1 day) and includes information about both price movement and trading volume during that period.
2.Candlestick Anatomy: A volume candle has the same components as a regular candlestick: the body (which represents the opening and closing prices) and the wicks or shadows (which indicate the highest and lowest prices reached during the period).
3.Volume Bars: Instead of just the candlestick itself, volume candles also include a bar or histogram representing the trading volume during that period. The height or length of the volume bar indicates the amount of trading activity.
4.Interpreting Volume: High volume candles typically indicate increased market interest or activity during that period. This could be due to significant buying or selling pressure.
5.Confirmation: Traders often look for confirmation from other technical indicators or price action to validate the significance of a high volume candle. For example, a high volume candle breaking through a key support or resistance level may signal a strong market move.
6.Trend Strength: Volume candles can provide insights into the strength of a trend. A series of high volume candles in the direction of the trend suggests strong momentum, while decreasing volume may indicate weakening momentum or a potential reversal.
7.Volume Patterns: Traders also analyze volume patterns, such as volume spikes or divergences, to identify potential trading opportunities or reversals.
8.Combination with Price Action: Volume analysis is often used in conjunction with price action analysis and other technical indicators to make more informed trading decisions.
9.Confirmation and Validation: It's important to confirm the significance of volume candles with other indicators or price action signals to avoid false signals.
10.Risk Management: As with any trading strategy, proper risk management is crucial when using volume candles to make trading decisions. Set stop-loss orders and adhere to risk management principles to protect your capital.
How the Script Works:
1.Identify High Volume Candles: Look for candles with significantly higher volume compared to the surrounding candles. These can indicate increased market interest or activity.
2.Wait for Confirmation: Once you identify a high volume candle, wait for confirmation from subsequent candles to ensure the momentum is sustained.
3.Enter the Trade: After confirmation, consider entering a trade in the direction indicated by the high volume candle. For example, if it's a bullish candle, consider buying.
4.Set Stop Loss: Always set a stop loss to limit potential losses in case the trade goes against you.
5.Take Profit: Set a target for taking profits. This could be based on technical analysis, such as a resistance level or a certain percentage gain.
6.Monitor Volume: Continuously monitor volume to gauge the strength of the trend. Decreasing volume may signal weakening momentum and could be a sign to exit the trade.
7.Risk Management: Manage risk carefully by adjusting position sizes according to your risk tolerance and the size of your trading account.
8.Review and Adapt: Regularly review your trades and adapt your strategy based on what's working and what's not.
Remember, no trading strategy guarantees profits, and it's essential to practice proper risk management and have realistic expectations. Additionally, consider combining volume analysis with other technical indicators for a more comprehensive approach to trading.
How Users Can Make Profit Using this script :
Bollinger Bands are a technical analysis tool that helps traders identify potential trends and volatility in the market. Here's a simple strategy using Bollinger Bands with a 10-point range:
1. *Understanding Bollinger Bands*: Bollinger Bands consist of a simple moving average (typically 20 periods) and two standard deviations plotted above and below the moving average. The bands widen during periods of high volatility and contract during periods of low volatility.
2. *Identify Price Range*: Look for a stock or asset that has been trading within a relatively narrow range (around 10 points) for some time. This indicates low volatility.
3. *Wait for Squeeze*: When the Bollinger Bands contract, it suggests that volatility is low and a breakout may be imminent. This is often referred to as a "squeeze."
4. *Plan Entry and Exit Points*: When the price breaks out of the narrow range and closes above the upper Bollinger Band, consider entering a long position. Conversely, if the price breaks below the lower band, consider entering a short position.
5. *Set Stop-Loss and Take-Profit*: Set stop-loss orders to limit potential losses if the trade goes against you. Take-profit orders can be set at a predetermined level or based on the width of the Bollinger Bands.
6. *Monitor and Adjust*: Continuously monitor the trade and adjust your stop-loss and take-profit levels as the price moves.
7. *Risk Management*: Only risk a small percentage of your trading capital on each trade. This helps to mitigate potential losses.
8. *Practice and Refinement*: Practice this strategy on a demo account or with small position sizes until you are comfortable with it. Refine your approach based on your experience and market conditions.
Remember, no trading strategy guarantees profits, and it's essential to combine technical analysis with fundamental analysis and risk management principles for successful trading. Additionally, always stay informed about market news and events that could impact your trades.
How does script works:
Bollinger Bands work by providing a visual representation of the volatility and potential price movements of a financial instrument. Here's how they work with a 10-point range:
1. *Calculation of Bollinger Bands*: The bands consist of three lines: the middle line is a simple moving average (SMA) of the asset's price (typically calculated over 20 periods), and the upper and lower bands are calculated by adding and subtracting a multiple of the standard deviation (usually 2) from the SMA.
2. *Interpretation of the Bands*: The upper and lower bands represent the potential extremes of price movements. In a 10-point range scenario, these bands are positioned 10 points above and below the SMA.
3. *Volatility Measurement*: When the price is experiencing high volatility, the bands widen, indicating a wider potential range of price movement. Conversely, during periods of low volatility, the bands contract, suggesting a narrower potential range.
4. *Mean Reversion and Breakout Signals*: Traders often use Bollinger Bands to identify potential mean reversion or breakout opportunities. When the price touches or crosses the upper band, it may indicate overbought conditions, suggesting a potential reversal to the downside. Conversely, when the price touches or crosses the lower band, it may indicate oversold conditions and a potential reversal to the upside.
5. *10-Point Range Application*: In a scenario where the price range is limited to 10 points, traders can look for opportunities when the price approaches either the upper or lower band. If the price consistently bounces between the bands, traders may consider buying near the lower band and selling near the upper band.
6. *Confirmation and Risk Management*: Traders often use other technical indicators or price action patterns to confirm signals generated by Bollinger Bands. Additionally, it's crucial to implement proper risk management techniques, such as setting stop-loss orders, to protect against adverse price movements.
Overall, Bollinger Bands provide traders with valuable insights into market volatility and potential price movements, helping them make informed trading decisions. However, like any technical indicator, they are not foolproof and should be used in conjunction with other analysis methods.
[FXAN] 71 Cygni Algorithm (Scalping)⚜️ FXAN CYGNI INDICATORS ORIGINALITY
Originality comes from proprietary formula we use to measure the relationship between Volume and Price Volatility in relation to overall current market positioning in developing Volume Profile and multiple custom period Volume Profiles. We combine that with our own approach to measure price velocity in correlation to average daily/weekly/monthly ranges of the given market.
The relationship between current volume and price volatility gives us information about how much the volume that is currently coming into the market affects the price movement (volatility) and which side is more dominant/involved in the market (Buyers/Sellers). We call this the "Volume Impact" factor.
This information is then compared in relation to the overall current market positioning in developing Volume Profile and Multiple custom period Volume Profiles. We have created a rating system based on current price positioning in relation to the Volume Profile. Volume profile consists of different volume nodes, high volume nodes where we consider market interest to be high (a lot of transactions - High Volume) and low volume nodes where we consider market interest to be low (not a lot of transactions - Low Volume). We call this the current "Market Interest" factor.
We combine this information with our own approach to measure price velocity in correlation to the higher-timeframe price ranges. Calculation is done by measuring current ranges of market movement in correlation to average daily/weekly/monthly ranges. We call this "Price Velocity" factor.
This approach was applied to develop key components of our Tradingview Indicators, we've simplified some of the calculations and made them easy to use by programming them to display buying/selling volume pressure with colors.
In addition to our own proprietary formulas and criterias to measure volume impact on price, we've also used an array of indicators that measure the percentage change in volume over custom specified periods of time, including custom period ranged Volume Profile, Developing VA, Accumulation/Distribution (A/D Line), Volume Rate of Change (VROC), Volume Price Trend (VPT) - all of them with of course fine-tuned settings to fit the purpose in the overall calculation.
Reasons for multiple indicator use:
Custom period ranged Volume Profiles: To determine current interest of market participants. Used for "Market Interest"
Developing VA: To determine current fair price of the market (value area). Used for "Market Interest".
Accumulation/Distribution (A/D Line): Helping to gauge the strength of buying and selling pressure. Used for "Volume Impact"
Volume Rate of Change (VROC): To give us information about percentage change in volume. Used for "Volume Impact"
Volume Price Trend (VPT): To help identify potential trends. Used for "Volume Impact".
Average True Range (ATR): Used for measuring volatility. Used for "Volume Impact" and "Price Velocity".
Average Daily Range (ADR): Used for measuring average market price movement. Used for "Price Velocity".
How it all works together:
"Volume Impact" factor tells us the influence of incoming market volume on price movement. This information alongside the overall market positioning information derived from "Market Interest" factor combined with information about speed and direction relative to higher-timeframe price ranges frin "Price Velocity.
This is the basis of our proprietary developed Volume Dynamics analysis approach
"Volume Impact" x "Market Interest" x "Price Velocity"
Combining this factors together gives a good overall understanding of which side is currently more involved in the market to gauge the direction ("Volume Impact"), where the market is currently positioned to gauge the context ("Market Interest") and what the current market's momentum to improve the timing of our trades ("Price Velocity"). This increases our probabilities for successful trades, executed with good timing.
To simplify - our indicators will always analyze the volume behind every price movement and rate those movements based on the relationship between movement distance and volume behind it through an array of criterias and rate them.
Colors displayed by the indicators will be a result of that, suggesting which side of the market (Buyers or sellers) is currently more involved in the market, aiming to increase the probabilities for profitable trades. With the help of our indicators you have deep volume analysis behind price movements done without looking at anything else then indicator components.
🔷 OVERVIEW
Cygni 71 Algorithm is a TradingView indicator designed for short-term trading (scalping) and enhancing the precision of your entries/exits based on a higher timeframe market context. It analyzes the underlying volume behind market movements and colors the candles with the help of the Heiken-Ashi methodology to provide a clearer perspective on the market's potential direction and intentions.
🔷 KEY FEATURES
▊ Candle Coloring
▊ Upper Colored Bar
▊ Lower Colored Bar
🔷 HOW DOES IT WORK?
□ Candles will color in reference to the Heiken ashi "average bar" methodology, which uses a modified formula based on two-period averages. This way, you can observe the normal candlesticks with less noise as colors will suggest the most likely direction where the market might be heading.
□ Upper Colored Bar analyzes daily volume dynamics in the market's price action by referencing the daily average price weighted by volume. If the market is bullish, you’ll see the green bars, and if the market is bearish, the bars will color red.
□ Lower Colored Bar analyzes volume dynamics and the market's price action every few second and minute intervals by referencing average price weighted by volume. This makes it much more sensitive than the Upper Colored Bar. If the market is bullish, you’ll see the green bars, and if the market is bearish, the bars will color red.
🔷 HOW TO USE IT?
□ In general, we look for areas where all components are in sync. These are valid trading signals (refer to the usage example below).
□ If all components are not in sync, we should look for at least two of them to be in sync while one of them must be Upper Colored Bar.
□ Candle Colors: Looking for longs when the candles are green and looking for shorts when the colors are red
□ Upper Colored Bar: The most important component of this indicator is that we favor trading in the direction suggested by this component. Additional confirmation of other components is a bonus. The green color suggests a bullish market, trading long. Red color suggests bearish market, trading short.
□ Lower Colored Bar: This should not be used on its own but always combined with at least one of the other components due to its sensitivity. Colors are indicating longs when green and shorts when red.
🔷 COMBINING THE COMPONENTS
Each component of the indicator serves it's own purpose and analyzes the market from it's own perspective and with its own custom settings and formulas. The calculation of the individual component is done independently from other components. Once all of them align, we're able to execute trades with an edge as it signals that different aspects of volume and price analysis line up for the trading opportunity.
- Candle Colors are used for improving the timing of your entries/exits based on market structure
- Upper Colored Bar is used for determining the favorable direction of the market based on Daily Volume Dynamics.
- Lower Colored Bar used for determining the favorable direction of the market based on Second/Minute/3-minute Volume Dynamics.
It's important to combine the components to increase the probability of success - here's how you should look for a trade:
1. Assess the current most favorable market direction by referencing the Upper Colored bar, look for longs if it’s green and for shorts if it’s red
2. Look for the Candle Colors to align with the Upper Colored bar, look for longs if it’s green and for shorts if it’s red
3. Look for short-time frame volume dynamics to align with your entries, by referencing the Lower Colored Bar - look for longs if it’s green and for shorts if it’s red.
A valid example of the trade would be:
- Upper Colored Bar is green, indicating the favorable trading directions is long
- Lower Colored Bar is green, indicating the favorable trading directions is long
- Candle Colors are green, indicating the market structure is favorable to enter your positions
📊 USAGE EXAMPLE
RSI EMA WMA (hieuhn)Indicator: RSI & EMA & WMA (14-9-45)
This indicator, named "RSI & EMA & WMA", is a versatile tool designed to provide insights into market momentum and trend strength by combining multiple technical indicators.
The Relative Strength Index (RSI) is a popular momentum oscillator used to measure the speed and change of price movements. In this indicator, RSI is plotted alongside its Exponential Moving Average (EMA) and Weighted Moving Average (WMA). EMA and WMA are smoothing techniques applied to RSI to help identify trends more clearly.
Key features of this indicator include:
RSI: The main RSI line is plotted on the chart, offering insights into overbought and oversold conditions.
EMA of RSI: The Exponential Moving Average of RSI smooths out short-term fluctuations, aiding in trend identification.
WMA of RSI: The Weighted Moving Average of RSI gives more weight to recent data points, providing a faster response to price changes.
Additionally, this indicator marks specific RSI levels considered as bullish and bearish trends, helping traders identify potential entry or exit points based on market sentiment.
By combining these technical indicators, traders can gain a comprehensive understanding of market dynamics, helping them make more informed trading decisions.
Fibonacci Timeframe Adaptive EMAThe "Fibonacci Timeframe Adaptive EMA" is a sophisticated trading indicator designed for the TradingView platform, leveraging the power of Exponential Moving Averages (EMAs) determined by Fibonacci sequence lengths to provide traders with dynamic market insights. This indicator overlays directly on the price chart, offering a unique blend of trend analysis, smoothing techniques, and timeframe adaptability, making it an invaluable tool for traders looking to enhance their technical analysis strategy.
Key Features
1. Fibonacci-Based EMA Lengths: Utilizes the Fibonacci sequence to select EMA lengths, incorporating natural mathematical ratios believed to be significant in financial markets. The available lengths range from 1 to 987, allowing for detailed trend analysis over various periods.
2. Multiple Smoothing Methods: Offers the choice between several smoothing techniques, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA or RMA), Weighted Moving Average (WMA), and Volume Weighted Moving Average (VWMA). This versatility ensures that users can tailor the indicator to suit their analytical preferences.
3. Timeframe Adaptability: Features the ability to fetch and calculate EMAs from different timeframes, providing a multi-timeframe analysis within a single chart view. This adaptability gives traders a broader perspective on market trends, enabling more informed decision-making.
4. Dynamic Visualization Options: Traders can customize the display to suit their analysis needs, including toggling the visibility of Fibonacci EMA lines, EMA prices, and smoothed EMA lines. Additionally, forecast lines can be projected into the future, offering speculative insights based on current trends.
5. Ema Tail Visualization: An innovative feature allowing for the visualization of the 'tail' or the continuation of EMA lines, which can be particularly useful for identifying trend persistence or reversal points.
6. User-friendly Customization: Through a series of input options, traders can easily adjust the source data, Fibonacci lengths, smoothing method, and visual aspects such as line colors and transparency, ensuring a seamless integration into any trading strategy.
Application and Use Cases
The "Fibonacci Timeframe Adaptive EMA" indicator is designed for traders who appreciate the significance of Fibonacci numbers in market analysis and seek a flexible tool to analyze trends across different timeframes. Whether it's for scalping, day trading, or long-term investing, this indicator can provide valuable insights into price dynamics, trend strengths, and potential reversal points. Its adaptability makes it suitable for various asset classes, including stocks, forex, commodities, and cryptocurrencies.
Day Open Line + SMA 8/3 Crossover + BollingerHow Users Can Make Profit Using This Script:
DAYS OPEN LINE:
1.Purpose: Publishing a "Days Open Line" indicator serves to inform customers about the operational schedule of a business or service.
2.Visibility: It ensures that the information regarding the days of operation is easily accessible to current and potential customers.
3.Transparency: By making the operational schedule public, businesses demonstrate transparency and reliability to their customers.
4.Accessibility: The indicator should be published on various platforms such as the business website, social media channels, and physical locations to ensure accessibility to a wide audience.
5.Clarity: The information should be presented in a clear and concise manner, specifying the days of the week the business is open and the corresponding operating hours.
6.Updates: It's important to regularly update the "Days Open Line" indicator to reflect any changes in the operational schedule, such as holidays or special events.
7.Customer Convenience: Providing this information helps customers plan their visits accordingly, reducing inconvenience and frustration due to unexpected closures.
8.Expectation Management: Setting clear expectations regarding the business hours helps manage customer expectations and reduces the likelihood of disappointment or complaints.
9.Customer Service: Publishing the "Days Open Line" indicator demonstrates a commitment to customer service by ensuring that customers have the information they need to engage with the business.
10.Brand Image: Consistently .maintaining and updating the indicator contributes to a positive brand image, as it reflects professionalism, reliability, and a customer-centric approach.
SMA CROSS:
1.This indicator generates buy and sell signals based on the crossover of two Simple Moving Averages (SMA): a shorter 3-day SMA and a longer 8-day SMA.
When the 3-day SMA crosses above the 8-day SMA, it generates a buy signal indicating a potential upward trend.
Conversely, when the 3-day SMA crosses below the 8-day SMA, it generates a sell signal indicating a potential downward trend.
Signal Interpretation:
2.Buy Signal: Generated when the 3-day SMA crosses above the 8-day SMA.
Sell Signal: Generated when the 3-day SMA crosses below the 8-day SMA.
Usage:
3.Traders can use this indicator to identify potential entry and exit points in the market.
Buy signals suggest a bullish trend, indicating a favorable time to enter or hold a long position.
4.Sell signals suggest a bearish trend, indicating a potential opportunity to exit or take a short position.
Parameters:
5.Periods: 3-day SMA and 8-day SMA.
Price: Closing price is commonly used, but users can choose other price types (open, high, low) for calculation.
Confirmation:
6.It's recommended to use additional technical analysis tools or confirmatory indicators to validate signals and minimize false signals.
Risk Management:
7.Implement proper risk management strategies, such as setting stop-loss orders, to mitigate losses in case of adverse price movements.
Backtesting:
8.Before using the indicator in live trading, conduct thorough backtesting to evaluate its effectiveness under various market conditions.
Considerations:
9.While SMA crossovers can provide valuable insights, they may generate false signals during ranging or choppy markets.
Combine this indicator with other technical analysis techniques for comprehensive market analysis.
Continuous Optimization:
10.Monitor the performance of the indicator and adjust parameters or incorporate additional filters as needed to enhance accuracy over time.
BOLLINGER BAND:
1.Definition: A Bollinger Band indicator is a technical analysis tool that consists of a centerline (typically a moving average) and two bands plotted above and below it. These bands represent volatility around the moving average.
2.Purpose: Publishing a Bollinger Band indicator serves to provide traders and investors with insights into the volatility and potential price movements of a financial instrument.
3.Visualization: The indicator is typically displayed on price charts, allowing users to visualize the relationship between price movements and volatility levels.
4.Interpretation: Traders use Bollinger Bands to identify overbought and oversold conditions, potential trend reversals, and volatility breakouts.
5.Components: The indicator consists of three main components: the upper band, lower band, and centerline (usually a simple moving average). These components are calculated based on standard deviations from the moving average.
6.Parameters: Traders can adjust the parameters of the Bollinger Bands, such as the period length and standard deviation multiplier, to customize the indicator based on their trading strategy and preferences.
7.Signals: Bollinger Bands generate signals when prices move outside the bands, indicating potential trading opportunities. For example, a price breakout above the upper band may signal a bullish trend continuation, while a breakout below the lower band may indicate a bearish trend continuation.
8.Confirmation: Traders often use other technical indicators or price action analysis to confirm signals generated by Bollinger Bands, enhancing the reliability of their trading decisions.
9.Education: Publishing Bollinger Band indicators can serve an educational purpose, helping traders learn about technical analysis concepts and how to apply them in real-world trading scenarios.
10.Risk Management: Traders should exercise proper risk management when using Bollinger Bands, as false signals and market volatility can lead to losses. Publishing educational content alongside the indicator can help users understand the importance of risk management in trading.
VWAP:
1.Calculation: VWAP is calculated by dividing the cumulative sum of price times volume traded for every transaction (price * volume) by the total volume traded.
2.Time Frame: VWAP is typically calculated for a specific time frame, such as a trading day or a session.
3.Intraday Trading: It's commonly used by intraday traders to assess the fair value of a security and to determine if the current price is above or below the average price traded during the day.
4.Execution: Institutional traders often use VWAP as a benchmark for executing large orders, aiming to buy at prices below VWAP and sell at prices above VWAP.
5.Benchmark: It serves as a benchmark for traders to evaluate their trading performance. Trades executed below VWAP are considered good buys, while those above are considered less favorable.
6.Sensitivity: VWAP is more sensitive to price and volume changes during periods of high trading activity and less sensitive during periods of low trading activity.
7.Day's End: VWAP resets at the end of each trading day, providing a new reference point for the following trading session.
8.Volume Weighting: The weighting by volume means that prices with higher trading volumes have a greater impact on VWAP than those with lower volumes.
9.Popular with Algorithmic Traders: Algorithmic trading systems often incorporate VWAP strategies to execute trades efficiently and minimize market impact.
10.Limitations: While VWAP is a useful indicator, it's not foolproof. It may lag behind rapidly changing market conditions and may not be suitable for all trading strategies or market conditions. Additionally, it's more effective in liquid markets where there is significant trading volume.
How the Script Works:
1.Utilizes Day Open Line for accurate market entry points.
2.Identifies bullish trends with SMA 3 crossover SMA 8.
3.Signals potential sell opportunities with SMA 8 crossunder SMA 3.
4.Bollinger Bands indicate overbought and oversold conditions.
5.VWAP offers insights into average price levels weighted by volume.
6.Combination of indicators enhances trade confirmation.
7.Facilitates precise timing for buy and sell decisions.
8.Enables traders to capitalize on market volatility.
9.Empowers users to navigate dynamic market conditions.
10.Supports profitable trading strategies with comprehensive analysis.
11.It is known when the market is sideways.
Red Light, Green Light Red Light, Green Light" is a comprehensive trading indicator designed for traders who need a clear, visual representation of market trends, applicable to any financial instrument and timeframe. It combines the analytical depth of three customizable moving averages with the visual simplicity of traffic lights. Users can adjust the length, MA type (including options like Donchian/Ichimoku baseline), source, and utilize multi-timeframe analysis, all enhanced with an offset feature for precise market alignment.
This indicator is ideal for users of Ichimoku Clouds, Donchian Channels, Price Action Scanners, Bollinger Bands, and moving average strategies, offering a new perspective in technical analysis.
The color system of the indicator simplifies trend identification:
Green indicates a strong bullish trend, suggesting traders consider long positions. This occurs when the short MA is above both the medium and long MAs, and the medium is also above the long MA.
Yellow signals caution in a bullish trend, pointing to potential consolidation or distribution phases. It appears when the short MA crosses below the medium MA while the medium remains above the long MA.
Orange reflects caution in a bearish trend, functioning similarly to yellow but under bearish conditions.
Red signifies a strong bearish trend, recommending short selling opportunities. It manifests when all MAs align in descending order, with the short MA at the lowest.
The 'cloud' feature, between the first two MAs, provides trend context akin to the Ichimoku Cloud but with a unique approach. While the Ichimoku system uses price position relative to the cloud to dictate trade bias, "Red Light, Green Light" relies on the color transitions of the MAs to guide trading decisions, with green and yellow for bullish scenarios and red and orange for bearish conditions.
Optimal use of "Red Light, Green Light" involves setting the moving average to the Donchian Baseline with default lengths of 20, 50, and 200, adjusting line thickness for visibility, and moderating cloud opacity as preferred.
Additionally, I developed this indicator primarily as a price action scanner to aid in identifying the most ideal financial instruments for trading based on their directional trends. It’s particularly useful for scanning through multiple timeframes of top-performing or bottom-performing stocks to discern which ones present the best trading opportunities. For instance, a stock that is consistently green from longer timeframes like 12M to 1D but shows yellow, orange, or red in shorter timeframes like 4H or 1H may be experiencing a minor pullback in an overall strong bullish trend, potentially signaling a buying opportunity. Conversely, in a bear market, consistent red in larger timeframes with green or yellow in shorter timeframes could indicate short-selling opportunities.
I recommend using this tool in conjunction with other indicators like Chris Moody’s Williams Vix Fix to enhance your market analysis and decision-making process.
I'm keen to receive feedback and learn about other tools on TradingView that can augment this price action scanning approach.
Volatility Adjusted Weighted DEMA [BackQuant]Volatility Adjusted Weighted DEMA
The Volatility Adjusted Weighted Double Exponential Moving Average (VAWDEMA) by BackQuant is a sophisticated technical analysis tool designed for traders seeking to integrate volatility into their moving average calculations. This innovative indicator adjusts the weighting of the Double Exponential Moving Average (DEMA) according to recent volatility levels, offering a more dynamic and responsive measure of market trends.
Primarily, the single Moving average is very noisy, but can be used in the context of strategy development, where as the crossover, is best used in the context of defining a trading zone/ macro uptrend on higher timeframes.
Why Volatility Adjustment is Beneficial
Volatility is a fundamental aspect of financial markets, reflecting the intensity of price changes. A volatility adjustment in moving averages is beneficial because it allows the indicator to adapt more quickly during periods of high volatility, providing signals that are more aligned with the current market conditions. This makes the VAWDEMA a versatile tool for identifying trend strength and potential reversal points in more volatile markets.
Understanding DEMA and Its Advantages
DEMA is an indicator that aims to reduce the lag associated with traditional moving averages by applying a double smoothing process. The primary benefit of DEMA is its sensitivity and quicker response to price changes, making it an excellent tool for trend following and momentum trading. Incorporating DEMA into your analysis can help capture trends earlier than with simple moving averages.
The Power of Combining Volatility Adjustment with DEMA
By adjusting the weight of the DEMA based on volatility, the VAWDEMA becomes a powerful hybrid indicator. This combination leverages the quick responsiveness of DEMA while dynamically adjusting its sensitivity based on current market volatility. This results in a moving average that is both swift and adaptive, capable of providing more relevant signals for entering and exiting trades.
Core Logic Behind VAWDEMA
The core logic of the VAWDEMA involves calculating the DEMA for a specified period and then adjusting its weighting based on a volatility measure, such as the average true range (ATR) or standard deviation of price changes. This results in a weighted DEMA that reflects both the direction and the volatility of the market, offering insights into potential trend continuations or reversals.
Utilizing the Crossover in a Trading System
The VAWDEMA crossover occurs when two VAWDEMAs of different lengths cross, signaling potential bullish or bearish market conditions. In a trading system, a crossover can be used as a trigger for entry or exit points:
Bullish Signal: When a shorter-period VAWDEMA crosses above a longer-period VAWDEMA, it may indicate an uptrend, suggesting a potential entry point for a long position.
Bearish Signal: Conversely, when a shorter-period VAWDEMA crosses below a longer-period VAWDEMA, it might signal a downtrend, indicating a possible exit point or a short entry.
Incorporating VAWDEMA crossovers into a trading strategy can enhance decision-making by providing timely and adaptive signals that account for both trend direction and market volatility. Traders should combine these signals with other forms of analysis and risk management techniques to develop a well-rounded trading strategy.
Alert Conditions For Trading
alertcondition(vwdema>vwdema , title="VWDEMA Long", message="VWDEMA Long - {{ticker}} - {{interval}}")
alertcondition(vwdema<vwdema , title="VWDEMA Short", message="VWDEMA Short - {{ticker}} - {{interval}}")
alertcondition(ta.crossover(crossover, 0), title="VWDEMA Crossover Long", message="VWDEMA Crossover Long - {{ticker}} - {{interval}}")
alertcondition(ta.crossunder(crossover, 0), title="VWDEMA Crossover Short", message="VWDEMA Crossover Short - {{ticker}} - {{interval}}")
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
EMA Cross Dashboard | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Exponential Moving Average (EMA) Cross Dashboard! This dashboard let's you select a source for the calculation of the EMA of it, then let's you enter 2 lengths for up to 5 timeframes, plotting their crosses in the chart.
Features of the new EMA Cross Dashboard :
Shows EMA Crosses Across Up To 5 Different Timeframes.
Select Any Source, Including Other Indicators.
Customizable Dashboard.
📌 HOW DOES IT WORK ?
EMA is a widely used indicator within trading community, it is similar to a Simple Moving Average (SMA) but places more weight on recent prices, making it more reactive to current trends. Crosses of EMA lines can be helpful to determine strong bullish & bearish movements of an asset. This indicator shows finds crosses across 5 different timeframes in a dashboard and plots them in your chart for ease of use.
🚩UNIQUENESS
This dashboard cuts through the hassle of manual EMA cross calculations and plotting. It offers flexibility by allowing various data sources (even custom indicators) and customization through enabling / disabling individual timeframes. The clear visualization lets you see EMA crosses efficiently.
⚙️SETTINGS
1. Timeframes
You can set up to 5 timeframes & 2 lenghts to detect crosses for each timeframe here. You can also enable / disable them.
2. General Configuration
EMA Source -> You can select the source for the calculation of the EMA here. You can select sources from other indicators as well as more general sources like close, high and low price.
SMA Cross Dashboard | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Simple Moving Average (SMA) Cross Dashboard! This dashboard let's you select a source for the calculation of the SMA of it, then let's you enter 2 lengths for up to 5 timeframes, plotting their crosses in the chart.
Features of the new SMA Cross Dashboard :
Shows SMA Crosses Across Up To 5 Different Timeframes.
Select Any Source, Including Other Indicators.
Customizable Dashboard.
📌 HOW DOES IT WORK ?
SMA is a widely used indicator within trading community, it simply works by taking the mathematical average of a source by desired length. Crosses of SMA lines can be helpful to determine strong bullish & bearish movements of an asset. This indicator shows finds crosses across 5 different timeframes in a dashboard and plots them in your chart for ease of use.
🚩UNIQUENESS
This dashboard cuts through the hassle of manual SMA cross calculations and plotting. It offers flexibility by allowing various data sources (even custom indicators) and customization through enabling / disabling individual timeframes. The clear visualization lets you see SMA crosses efficiently.
⚙️SETTINGS
1. Timeframes
You can set up to 5 timeframes & 2 lenghts to detect crosses for each timeframe here. You can also enable / disable them.
2. General Configuration
SMA Source -> You can select the source for the calculation of the SMA here. You can select sources from other indicators as well as more general sources like close, high and low price.
