Swing Highs and Lows predictorHighs and Lows Predictor
Description:
The "Swing Highs and Lows Predictor" is a comprehensive Pine Script indicator designed to help traders identify potential swing highs and lows in the market. This indicator combines moving averages, RSI, Fibonacci retracement levels, and volume analysis to provide a holistic view of market trends and reversals.
Features:
Moving Averages (SMA and EMA): These are used to determine the overall trend direction. The Simple Moving Average (SMA) smooths out price data to identify the direction of the trend over a specified period. The Exponential Moving Average (EMA) reacts more quickly to recent price changes, providing a more sensitive trend indicator.
Relative Strength Index (RSI): This oscillator measures the speed and change of price movements. Values above 70 indicate overbought conditions, while values below 30 indicate oversold conditions. This helps in identifying potential reversal points.
Fibonacci Retracement Levels: These levels are calculated based on the recent significant high and low. They help in identifying potential support and resistance levels where the price might reverse.
Volume Spike Detection: Volume spikes often precede significant price movements. This feature highlights unusual volume activity, indicating potential trend changes.
Swing Highs and Lows: The script identifies and marks significant swing highs and lows based on historical price action. This is useful for traders to spot potential entry and exit points.
How It Works:
Trend Analysis with Moving Averages: The script plots both SMA and EMA on the chart to help identify the current trend. When the EMA is above the SMA, it indicates an uptrend, and vice versa for a downtrend.
Momentum Analysis with RSI: The RSI is plotted to identify overbought and oversold conditions. Traders can look for entries when the RSI exits these zones.
Support and Resistance with Fibonacci Retracements: Fibonacci levels are drawn based on the highest high and lowest low over the specified period. These levels indicate potential areas of support and resistance.
Volume Analysis: The script highlights bars with significant volume spikes, providing additional confirmation for potential reversals.
Identifying Swings: The script uses a combination of high and low price points over a defined period to mark swing highs and lows, helping traders spot potential turning points.
How to Use:
Entry Points: Look for swing low markers combined with oversold RSI levels and support from Fibonacci retracement levels for potential buy entries.
Exit Points: Look for swing high markers combined with overbought RSI levels and resistance from Fibonacci retracement levels for potential sell entries.
Volume Confirmation: Use volume spikes as an additional confirmation for the strength of the identified swings.
Trend Confirmation: Use SMA and EMA to confirm the overall trend direction before making trade decisions.
This script aims to provide a comprehensive tool for traders to analyze market trends, momentum, support, and resistance levels, enhancing their decision-making process. By combining multiple indicators into a single script, it offers a streamlined approach to technical analysis.
Example Usage:
Long Trade Setup: Enter a long position when a swing low is identified, RSI exits the oversold zone, and the price finds support at a Fibonacci retracement level, with a volume spike confirming the move.
Short Trade Setup: Enter a short position when a swing high is identified, RSI exits the overbought zone, and the price faces resistance at a Fibonacci retracement level, with a volume spike confirming the move.
Forecasting
Dinapoli Objective Points (OPs)The DiNapoli Objective Points (OPs) is a drawing tool that computes potential exit targets to a market. It does so by drawing Fibonacci ABC Extensions which form Areas that might condition future market moves. This is a Leading Indicator created by Joe DiNapoli.
Let’s dive into what this tool does.
HOW TO READ THE DINAPOLI OPs
First, let’s review the basic concepts. In the chart below you’ll see a market Up Swing and a Down Swing. Both charts show a significant Retracement within the scope of a larger Swing, and therefore are suitable for this tool.
A Point : That’s the base Reaction Point. In up swings, it’s usually a significant pivot low, while in down swings it’s a pivot high.
B Point : That’s the Focus Point that will define the extent of the extensions. In up swings, it’s usually a significant pivot high, while in down swings it’s a pivot low.
C Point : That’s the Retracement Point from where the extensions will be drawn. The C Point is contained within the A-B Price Range, and often coincides with a Fibonacci Node.
On adding the tool to the chart, it will pop up a message asking the user to click for the 3 Points: A, B and C. Then, the tool will compute the Objective Points. Let’s review them:
COP : It’s the 61.8% Fibonacci Extension. It’s called COP as an acronym for Contracted Objective Point. It’s commonly used as an early Take Profit level or also as a point at which to enable a Trailing Stop Loss.
OP : It’s the 100% Fibonacci Extension. It’s called OP as an acronym for the main Objective Point. It’s usually used as a level where to Take Profit.
XOP : It’s the 161.8% Fibonacci Extension. It’s called XOP as an acronym for Extended Objective Point. It’s usually employed as a Take Profit target in which to close the position or significantly reduce the position weight.
By combining Objective Points with Dinapoli Levels, one can define Areas of Interest that might act as reinforced Support or Resistance levels. The Agreement Area happens where there’s a convergence between a Fibonacci Node and an Objective Point.
WHY WOULD YOU BE INTERESTED IN THIS INDICATOR?
This version of Dinapoli Levels has been designed to address the needs of dedicated traders. Let’s review its main features.
Combine Objective Points with D-Levels!
This tool allows you to quickly compute the Objective Points and display them in a minimalistic non-intrusive fashion.
The fact that the Objective Points get drawn on the right hand side of the chart combines perfectly with the Dinapoli Levels tools.
Keep your Chart Clean!
Disciplined traders keep their charts clean and visually appealing. One needs proper focus to trade in the zone.
Please check how the chart on the left looks compared to the one on the right. Both display exactly the same information. On the right it uses the DiNapoli Objective Points to print the Extensions, whilst on the right it uses the standard Fibonacci Extension tool.
The DiNapoli Objective Points use a view concentrated into the empty right side of the chart, which contributes to a more comprehensive display of information. There are no lines crossing over the price candles. It’s just a better tool. It keeps your charts free of messy lines.
EACH MARKET IN ITS OWN CHART
This tool somehow enhances the functionality of a Fibonacci Extension Drawing Tool. Being in nature a drawing tool, it has been developed as an indicator because that’s the only way it can be done at the present moment in this platform.
Therefore it’s recommended to structure Each Market in its Own Chart . Being coded as an indicator, this tool benefits by displaying over a chart dedicated to a single market.
If you trade on multiple markets, then it’s convenient to set up separate charts for each one. Otherwise, you would need to apply, delete and reapply the tool every time you shift markets.
SETTINGS
Now let’s dive into the settings of this indicator.
ABC Points : This section contains the ABC price points selected and its label visualization controls.
A-Point, B-Point and C-Point : These fields contain the prices that were selected when clicking on the chart. One can change their value by hand, and the indicator will do its best to accommodate the drawing.
Highlight ABC Points : This conditions whether the A-B-C labels should display on screen.
Back Color : Select the color that will be used to highlight the A-B-C labels.
Text Color : Select the color that will be used to print the characters in the A-B-C labels.
Levels : This section allows you to customize the look of the Dinapoli Objective Points.
Enable/Disable Level : Each Level (COP, OP and XOP) can be enabled or disabled.
Level Color : Select the line color for that specific level. Please beware that the default color is 100% transparent. You might need to change the transparency setting in the color picker for the color you’ve selected to appear.
Id : Shows the label identifying the Objective Point.
Price : Shows the price value of the Objective Point.
Offset : Determines how far to the right will the group of DiNapoli Objective Points be located.
Width : Sets the width of the horizontal lines that represent the Objective Points.
Thickness : Sets the line thickness of the lines.
Median Analyst ConsensusThe Median Analyst Consensus Indicator provides an unbiased, easy-to-interpret view of market sentiment by leveraging TradingView's comprehensive financial data library. This tool displays the median 12-month price target and the percentage difference from the current price directly on your charts.
Key Features
1. Accurate Market Sentiment: By consolidating analyst ratings and price targets from multiple reputable sources like Bloomberg, Refinitiv (formerly Thomson Reuters), S&P Capital IQ, and Morningstar, this indicator displays the median analyst consensus. Using the median ensures outlier ratings don't skew the overall sentiment, providing a more robust representation.
2. Simplicity at a Glance: View the median 12-month price target and percentage difference from the current price directly on your chart. No need to juggle multiple reports - key insights are surfaced within your normal trading workflow.
3. Data-Driven Transparency: If no analyst data is available for a particular asset, the indicator will not display, ensuring you only see reliable information. The number of contributing analysts is also shown for context.
Why the Median?
The median is favored over the mean to minimize the impact of outlier ratings that could distort the consensus view. By taking the middle value across all analyst projections, the median provides a more stable, outlier-resistant measure of market sentiment.
Powered by TradingView Data
This indicator taps into TradingView's financial data library, which aggregates analyst ratings, estimates, and recommendations from leading institutional data providers. TradingView sources this data from firms like FactSet, Bloomberg, Refinitiv, S&P Capital IQ, and Morningstar, ensuring a comprehensive and trusted view of analyst sentiment.
The library provides variables like:
syminfo.recommendations_buy
syminfo.recommendations_sell
syminfo.target_price_median
syminfo.recommendations_buy_strong
syminfo.recommendations_sell_strong
The indicator calculates and displays the median of these analyst inputs.
Usage
The indicator displays:
The median 12-month price target across analysts
The percentage difference between the price target and current price
The number of contributing analyst estimates
If no analyst data is available, the indicator does not display, ensuring full transparency.
The Median Analyst Consensus Indicator provides an unbiased, easy-to-interpret view of market sentiment by leveraging TradingView's comprehensive financial data library. This tool offers a new perspective on potential trade opportunities directly on your charts.
Disclaimer
While the data is sourced from reputable providers, analyst forecasts should not be construed as investment recommendations. This indicator aims to synthesize market opinions, but investment decisions are solely your responsibility. As with any analytical tool, you should conduct your own research and risk assessments before executing any trades.
ΔYoY(Economics)Year over year indicator which will benchmark the most recent data vs 1 year lookback; Will automate the lookback for quarterly and monthly data based on timeframe selected (3M for quarterly, 1M for monthly). Tradingview will aggregate weekly data into a monthly data point. SMA applied to get the average over some x period.
Ln(close)Natural log indicator for normalizing data. SMA applied so you can take the average of that normalization factor. Personally use it for US economic data where the value is very large (GDI, Fed Balance Sheet, USM2 etc.) and the year over year delta is not pertinent (USM2) or not available (GDI.. although I did make an indicator to get YoY :D). Any additional ideas leave a comment and I'll take a look.
Nasan Moving Average with ForecastThe "Nasan Moving Average with Forecast" indicator is a technical analysis forecasting tool that combines the principles of historical data analysis and random walk theory. It calculates a customized moving average (Nasan Moving Average) by integrating price data and statistical measures and projects future price points by generating forecast values within calculated volatility bounds, creating a dynamic and insightful visualization of potential market movements. This indicator to blend past market behavior with probabilistic future trends to enhance forecasting.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
forecast_points: Number of points to forecast (default 30).
m: Multiplier for standard deviation (default 2.5).
bl: Block length for calculating max/min values (default 100).
use_calculated_max_min: Boolean to decide whether to use calculated max/min values.
Nasan Moving Average Calculation:
Calculates the simple moving average (mean) and standard deviation (sd) of the typical price (hlc3).
Computes intermediate variables (a, b, c, etc.) based on log transformation and cumulative sum.
Applies weighted moving averages (wma) to these intermediate variables to smooth them and derive the final value c6.
Plots c6 as the Nasan Moving Average if the bar is confirmed. To learn more see Nasan Moving Average.
Forecast Points Calculation:
Calculates maximum (max_val) and minimum (min_val) values for the forecast, either using a fixed value or based on standard deviation and a multiplier.
Initializes an array to store forecast values and creates polyline objects for plotting.
If the current bar is one of the last three bars and confirmed:
Clears and reinitializes the polyline.
Initializes the first forecast value from the cumulative sum c.
Generates subsequent forecast values using a random value within the range .
Updates the forecast array and plots the forecast points as an orange curved polyline.
Plotting Max/Min Values:
Plots max_val and min_val as green and red lines, respectively, to indicate the bounds of the forecast range.
Components of the Forecasting Model
Historical Dependence:
Nasan Moving Average Calculation: The script calculates a custom moving average (c6) that incorporates historical price data (hlc3), standard deviations (sd), and weighted moving averages (wma). This part of the code processes historical data to create a smoothed representation of the price trend.
Max/Min Value Calculation: The maximum (max_val) and minimum (min_val) values for the forecast can be calculated based on the historical standard deviation of a transformed variable b over a block length (bl). This introduces historical volatility into the bounds for the forecast.
Random Walk Model:
Random Value Generation: Within the forecast points calculation, a random value (random_val) is generated for each forecast point within the range . This random value introduces stochasticity into the model, characteristic of a random walk process.
Cumulative Sum for Forecasting: The script uses a cumulative sum (prev_f + random_val) to generate the next forecast point (next_f). This is a typical approach in random walk models where each new point is based on the previous point plus some random noise.
Explanation of the Forecast Model
Random Walk Characteristics: Each new forecast point is generated by adding a random value to the previous point, making the model a random walk with drift, where the drift is influenced by historical correction factors (c1, c4).
Historical and Statistical Dependence: The bounds of the random values and the initial conditions are derived from historical data, ensuring that the forecast respects historical volatility and trends.
The forecasting model in the script is a hybrid approach: It uses a random walk to generate future points, characterized by adding random values to the previous forecasted value.
The historical and statistical dependence is incorporated through initial conditions, scaling factors, and bounds derived from historical price data and its statistical properties.
This combination ensures that the forecasts are not purely stochastic but are grounded in historical price behavior, making the model more robust and potentially more accurate in reflecting market conditions.
Introducing the Markov Chain Model IndicatorThis powerful tool leverages Markov chain theory to help traders predict stock price movements by analyzing historical price data and calculating transition probabilities between different states: "Up by >1%", "Stable", and "Down by <1%". This post will provide a comprehensive overview of the indicator, its advantages and disadvantages, and how it can be used effectively in trading decisions.
How It Works
The Markov Chain Model indicator calculates the daily percentage changes in stock prices and categorizes them into three states:
Up by >1%
Stable (between -1% and +1%)
Down by <1%
By analyzing these transitions, the script constructs a transition matrix that shows the probability of moving from one state to another. This matrix is then displayed on the chart, providing traders with valuable insights into potential future price movements.
Advantages of the Markov Chain Model Indicator
Data-Driven Predictions : Utilizes historical price data to calculate probabilities, offering a statistical foundation for predictions.
Visual Representation : Displays the transition matrix directly on the chart, making it easy to interpret and use in trading decisions.
Adaptability : Allows users to customize the percentage threshold, enabling fine-tuning based on different market conditions.
Comprehensive Analysis : Considers multiple states (up, stable, down), providing a more nuanced view of price movements.
Disadvantages of the Markov Chain Model Indicator
Historical Dependence : The model relies on historical data, which may not always accurately predict future movements, especially in volatile markets.
Simplified States : The use of only three states might oversimplify complex market behaviors, potentially missing out on subtler trends.
Limited Scope : Designed for short-term predictions and may not be as effective for long-term investment strategies.
Example Interpretation
Transition Matrix:
From/To | Up >1% | Stable | Down <1% |
---------------------------------------
Up >1% | 0.30 | 0.40 | 0.30 |
Stable | 0.33 | 0.44 | 0.23 |
Down <1% | 0.34 | 0.36 | 0.30 |
Latest 3 States: S2 -> S1 -> S1
Total Bars: 2523
Decision Making Based on the Transition Matrix:
Current State: Up >1%
Next State Probabilities : 30% Up >1%, 40% Stable, 30% Down <1%
Decision : Given the balanced probabilities, a trader might decide to hold the position but set a trailing stop-loss to protect against sudden downturns. If other technical indicators also suggest continued upward momentum, they might increase their position cautiously.
Current State : Stable
Next State Probabilities : 33% Up >1%, 44% Stable, 23% Down <1%
Decision : With a high probability of stability, a cautious approach might be to hold or make small incremental trades, keeping an eye on other market indicators for confirmation.
Conclusion
The Markov Chain Model indicator is a powerful tool for traders looking to leverage statistical models to predict stock price movements. By understanding the transition probabilities between different states, traders can make more informed decisions and better manage their risk. We hope this tool helps enhance your trading strategy and provides you with a deeper understanding of market behaviors.
Try It Out
Copy the script above into TradingView and start exploring the potential of the Markov Chain Model indicator. Happy trading!
Feel free to share your feedback and let us know how this indicator works for you. Your insights can help us improve and develop even more effective trading tools.
ALT Trend DetectionALT Trend Detection Indicator
Overview:
The "ALT Trend Detection" indicator is designed to help traders analyze the relationship between Bitcoin's dominance, Bitcoin's price, and the potential impact on altcoin prices. This indicator uses various time frames and average true range (ATR) calculations to detect trends and provide insights into the altcoin market conditions based on Bitcoin's movements.
How It Works:
BTC Dominance and Price Data:
The indicator fetches Bitcoin dominance data (percentage of the total cryptocurrency market cap that Bitcoin represents) and Bitcoin price data using the selected time frame.
It calculates whether Bitcoin dominance and price are trending up, down, or remaining stable based on ATR calculations.
Altcoin Trend Detection:
The indicator then evaluates different scenarios based on the combination of Bitcoin dominance and price movements. These scenarios help predict the potential impact on altcoin prices.
For instance, if Bitcoin dominance is up and Bitcoin price is up, it might indicate a bearish trend for altcoins. Conversely, if Bitcoin dominance is down and Bitcoin price is up, it might indicate a bullish trend for altcoins (altseason).
Table Display:
The indicator displays a table on the chart that summarizes the current conditions for Bitcoin dominance, Bitcoin price, and the expected impact on altcoins. Each cell in the table is color-coded to provide a quick visual representation of the trends.
Usage:
Add the indicator to your TradingView chart.
Customize the time frame, ATR multiplier, table position, table size, and background color as per your preference.
Observe the table displayed on the chart. It shows the current state of Bitcoin dominance, Bitcoin price, and the potential trend for altcoin prices based on predefined scenarios.
Use this information to make informed trading decisions about altcoins. For example, if the table shows "ALT SEASON" in green, it might be a good time to consider investing in altcoins.
By analyzing the interaction between Bitcoin dominance and price, this indicator helps traders identify potential opportunities and risks in the altcoin market.
FaikValThe "FaikVal" indicator is a powerful tool designed to help traders analyze relative price movements between a base asset and up to three comparison assets. This indicator uses exponential moving averages (EMA) and normalization techniques to identify potential overbought and oversold situations.
Functions and Applications:
Comparison of Price Ratios: The indicator calculates the ratio of the closing price of the base asset to the closing prices of three user-defined comparison assets. This allows for direct comparative analysis and helps identify relative strengths and weaknesses.
EMA Calculations: Two EMAs are calculated for each price ratio (with configurable periods). The difference between these two EMAs serves as the basis for further calculations.
Normalization: The calculated values are normalized over a defined period, helping to smooth out extreme values and facilitate analysis. This normalization transforms the values onto a scale from -100 to 100.
Optional Smoothing: Optional smoothing of the normalized values can be enabled to further reduce short-term fluctuations and generate clearer signals.
Visual Signals: The indicator plots three lines (one for each comparison ratio), representing the normalized values. Additionally, horizontal lines are displayed at +60, -60, and 0 to mark overbought and oversold zones as well as neutral areas.
Customizability: Users can adjust the periods of the EMAs, the length of the normalization period, and the smoothing period. They can also specify which of the three indicators should be displayed.
Applications:
Relative Strength Analysis: Identify whether the base asset is performing stronger or weaker compared to other markets or instruments.
Trend Confirmation: Confirm existing trends by analyzing the movements of the base asset relative to the comparison assets.
Overbought and Oversold Signals: Use the displayed values and horizontal lines to identify potential market turning points and determine entry or exit points.
!!! It works best on the weekly and daily chart for swing trading. It is a set up tool, to determin weather you should go long or short and not a market timing tool. For timing you could use concepts like trend and supply and demand!!!
The "FaikVal" indicator offers versatile and detailed analysis, making it particularly useful for traders seeking deeper insights into relative price strength and weakness.
Anchored Monte Carlo Shuffled Projection [LuxAlgo]The Anchored Monte Carlo Shuffled Projection tool randomly simulates future price points based on historical bar movements made before a user-anchored point in time.
By anchoring our data and projections to a single point in time, users can better understand and reflect on how the price played out while taking into consideration our random simulations.
🔶 USAGE
After selecting the indicator to apply to the chart, you will be prompted to "Set the Anchor Point". Do so by clicking on the desired location on your chart, only time is used as the anchor point.
Note: To select a new anchor point when applied to the chart, click on the 'More' dropdown next to the indicator status bar (○○○), then select "Reset points...".
Alternate Method: You are also able to click and drag the vertical line that displays on the anchor point bar when the indicator is highlighted.
By randomly simulating bar movements, a range is developed of potential price action which could be utilized to locate future price development as well as potential support/resistance levels.
Performing numerous simulations and taking the average at each step will converge toward the result highlighted by the "Average Line", and can point out where the price might develop, assuming the trend and amount of volatility persist.
Current closing price + Sum of changes in the calculation window
This constraint will cause the simulations always to display an endpoint consistent with the current lookback's slope.
While this may be helpful to some traders, this indicator includes an option to produce a less biased range, as seen below:
🔶 DETAILS
The Anchored Monte Carlo Shuffled Projection tool creates simulations based on prices within a user-set lookback window originating at the specified anchor point. Simulations are done as follows:
Collect each bar's price changes in the user-set window.
Randomize the order of each change in the window.
Project the cumulative sum of the shuffled changes from the current closing price.
Collect data on each point along the way.
This is the process for the Default calculation; for the 'Randomize Direction' calculation, when added onto the front for every other change, the value is inverted, creating the randomized endpoints for each simulation.
The script contains each simulation's data for that bar, with a maximum of 1000 simulations.
To get a glimpse behind the scenes, each simulation (up to 99) can be viewed using the 'Visualize Simulations' Options, as seen below.
Because the script holds the full simulation data, the script can also calculate this data, such as standard deviations.
In this script the Standard deviation lines are the average of all standard deviations across the vertical data groups, this provides a singular value that can be displayed a distance away from the simulation center line.
🔶 SETTINGS
Lookback: Sets the number of Bars to include in calculations.
Simulation Count: Sets the number of randomized simulations to calculate. (Max 1000)
Randomize Direction: See Details Above. Creates a more 'Normalized' Distribution
Visualize Simulations: See Details Above. Turns on Visualizations, and colors are randomly generated. Visualized max does not cap the calculated max. If 1000 simulations are used, the data will be from 1000 simulations, however, only the last 99 simulations will be visualized.
🔹 Standard Deviations
Standard Deviation Multiplier: Sets the multiplier to use for the Standard Deviation distance away from the center line.
🔹 Style
Extend Lines: Extends the Simulated Value Lines into the future for further reference and analysis.
Velocity And Acceleration with Strategy: Traders Magazine◙ OVERVIEW
Hi, Ivestors and Traders... This Indicator, the focus is Scott Cong's article in the Stocks & Commodities September issue, “VAcc: A Momentum Indicator Based On Velocity And Acceleration”. I have also added a trading strategy for you to benefit from this indicator. First of all, let's look at what the indicator offers us and what its logic is. First, let's focus on the logic of the strategy.
◙ CONCEPTS
Here is a new indicator based on some simple physics concepts that is easy to use, responsive and precise. Learn how to calculate and use it.
The field of physics gives us some important principles that are highly applicable to analyzing the markets. In this indicator, I will present a momentum indicator. Scott Cong developed based on the concepts of velocity and acceleration this indicator. Of the many characteristics of price that traders and analysts often study, rate and rate of change are useful ones. In other words, it’s helpful to know: How fast is price moving, and is it speeding up or slowing down? How is price changing from one period to the next? The indicator I’m introducing here is calculated using the current bar (C) and every bar of a lookback period from the current bar. He named the indicator the VAcc since it’s based on the average of velocity line (av) and acceleration line (Acc) over the lookback period. For longer periods, the VAcc behaves the same way as the MACD, only it’s simpler, more responsive, and more precise. Interestingly, for shorter periods, VAcc exhibits characteristics of an oscillator, such as the stochastics oscillator.
◙ CALCULATION
The calculation of VAcc involves the following steps:
1. Relatively weighted average where the nearer price has the largest influence.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. The Velocity Average is smoothed with an exponential moving average. Now it get:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Similarly, accelerations for each bar within the lookback period and scale factor are calculated as:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEGY
In fact, Scott probably preferred to use it in periods 9 and 26 because it was similar to Macd and used the ratio of 0.5. However, I preferred to use the 8 and 21 periods to provide signals closer to the stochastic oscillator in the short term and used the 0.382 ratio. The logic of the strategy is this
Long Strategy → acc(Acceleration Line) > 0.1 and av(Velocity Average Line) > 0.1(Long Factor)
Short strategy → acc(Acceleration Line) < -0.1 and av(Velocity Average Line) < -0.1(Long Factor)
Here, you can change the Short Factor and Long Factor as you wish and produce more meaningful results that are closer to your own strategy.
I hope you benefits...
◙ GENEL BAKIŞ
Merhaba Yatırımcılar ve Yatırımcılar... Bu Gösterge, Scott Cong'un Stocks & Emtia Eylül sayısındaki “VAcc: Hız ve İvmeye Dayalı Bir Momentum Göstergesi” başlıklı makalesine odaklanmaktadır. Bu göstergeden faydalanabilmeniz için bir ticaret stratejisi de ekledim. Öncelikle göstergenin bize neler sunduğuna ve mantığının ne olduğuna bakalım. Öncelikle stratejinin mantığına odaklanalım.
◙ KAVRAMLAR
İşte kullanımı kolay, duyarlı ve kesin bazı basit fizik kavramlarına dayanan yeni bir gösterge. Nasıl hesaplanacağını ve kullanılacağını öğrenin.
Fizik alanı bize piyasaları analiz etmede son derece uygulanabilir bazı önemli ilkeler verir. Bu göstergede bir momentum göstergesi sunacağım. Scott Cong bu göstergeyi hız ve ivme kavramlarına dayanarak geliştirdi. Yatırımcıların ve analistlerin sıklıkla incelediği fiyatın pek çok özelliği arasında değişim oranı ve oranı yararlı olanlardır. Başka bir deyişle şunu bilmek faydalı olacaktır: Fiyat ne kadar hızlı hareket ediyor ve hızlanıyor mu, yavaşlıyor mu? Fiyatlar bir dönemden diğerine nasıl değişiyor? Burada tanıtacağım gösterge, mevcut çubuk (C) ve mevcut çubuktan bir yeniden inceleme döneminin her çubuğu kullanılarak hesaplanır. Göstergeye, yeniden inceleme dönemi boyunca hız çizgisinin (av) ve ivme çizgisinin (Acc) ortalamasına dayandığı için VAcc adını verdi. Daha uzun süreler boyunca VACc, MACD ile aynı şekilde davranır, yalnızca daha basit, daha duyarlı ve daha hassastır. İlginç bir şekilde, daha kısa süreler için VAcc, stokastik osilatör gibi bir osilatörün özelliklerini sergiliyor.
◙ HESAPLAMA
VAcc'nin hesaplanması aşağıdaki adımları içerir:
1. Yakın zamandaki fiyatın en büyük etkiye sahip olduğu göreceli ağırlıklı ortalamayı hesaplatıyoruz.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. Hız Ortalamasına üstel hareketli ortalamayla düzleştirme uygulanır. Şimdi bu şekilde aşağıdaki kod ile bunu şöyle elde ediyoruz:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Benzer şekilde, yeniden inceleme süresi ve ölçek faktörü içindeki her bir çubuk için fiyattaki ivmelenler yada momentum şu şekilde hesaplanır:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEJİ
Aslında Scott muhtemelen Macd'e benzediği ve 0,5 oranını kullandığı için 9. ve 26. periyotlarda kullanmayı tercih etmişti. Ancak kısa vadede stokastik osilatöre daha yakın sinyaller sağlamak için 8 ve 21 periyotlarını kullanmayı tercih ettim ve 0,382 oranını kullandım. Stratejinin mantığı şu
Uzun Strateji → acc(İvme Çizgisi) > 0,1 ve av(Hız Ortalama Çizgisi) > 0,1(Uzun Faktör)
Kısa strateji → acc(İvme Çizgisi) < -0,1 ve av(Hız Ortalama Çizgisi) < -0,1(Uzun Faktör)
Burada Kısa Faktör ve Uzun Faktör' ü dilediğiniz gibi değiştirip, kendi stratejinize daha yakın, daha anlamlı sonuçlar üretebilirsiniz.
umarım faydasını görürsün...
Leading MACDThe Moving Average Convergence Divergence (MACD) indicator is one of the most popular and versatile tools used by traders to identify potential buy and sell signals. It helps traders determine the strength and direction of a trend by comparing different moving averages of a security's price. The traditional MACD uses two exponential moving averages (EMAs), a fast EMA (typically 12 periods) and a slow EMA (typically 26 periods), along with a signal line (typically a 9-period EMA of the MACD line) to generate trading signals.
Our "Custom MACD with Leading Length" script for TradingView enhances the traditional MACD by introducing an additional smoothing factor called the "leading length." This customization aims to reduce noise and provide a potentially earlier indication of trend changes, making it a valuable tool for traders seeking to optimize their trading strategies.
- **Purpose:** This additional smoothing factor is designed to reduce noise and provide a potentially leading signal, enhancing the accuracy of trend identification.
## How It Works
1. **Calculate the MACD Line:**
The MACD line is calculated by subtracting the slow EMA from the fast EMA. This difference represents the convergence or divergence between the two EMAs.
2. **Calculate the Signal Line:**
The signal line is an EMA of the MACD line. This additional smoothing helps to generate clearer buy and sell signals based on crossovers with the MACD line.
3. **Calculate the Histogram:**
The histogram represents the difference between the MACD line and the signal line. It visually indicates the strength and direction of the trend. A positive histogram suggests a bullish trend, while a negative histogram indicates a bearish trend.
4. **Apply Leading Length Smoothing:**
To incorporate the leading length, the script applies a simple moving average (SMA) to both the MACD and signal lines using the leading length parameter. This additional smoothing helps to further reduce noise and potentially provides earlier signals of trend changes.
## Benefits of the Leading MACD
### Reduced Noise
The leading length parameter adds an extra layer of smoothing to the MACD and signal lines, helping to filter out market noise. This can be particularly beneficial in volatile markets, where frequent price fluctuations can generate false signals.
### Potential Early Signals
By smoothing the MACD and signal lines, the leading length can help to provide earlier indications of trend changes. This can give traders a potential edge in entering or exiting trades before the broader market reacts.
### Enhanced Trend Identification
The combination of the traditional MACD with the leading length smoothing can enhance the accuracy of trend identification. Traders can use this tool to confirm the strength and direction of trends, making it easier to make informed trading decisions.
### Versatility
The Custom MACD with Leading Length can be applied to various timeframes and asset classes, including stocks, forex, commodities, and cryptocurrencies. Its adaptability makes it a valuable tool for traders with different strategies and preferences.
## Practical Applications
### Buy Signal
A typical buy signal occurs when the MACD line crosses above the signal line. With the additional smoothing provided by the leading length, traders might receive this signal slightly earlier, allowing them to enter a long position sooner. This can be particularly advantageous in capturing the beginning of a bullish trend.
### Sell Signal
Conversely, a sell signal is generated when the MACD line crosses below the signal line. The leading length smoothing can help to provide this signal earlier, enabling traders to exit a long position or enter a short position before the trend reversal is fully recognized by the market.
### Divergence Analysis
Traders can also use the Custom MACD with Leading Length for divergence analysis. Bullish divergence occurs when the price makes a new low, but the MACD line forms a higher low. This suggests that the downward momentum is weakening, potentially leading to a bullish reversal. Bearish divergence is the opposite, where the price makes a new high, but the MACD line forms a lower high, indicating a potential bearish reversal.
### Confirmation Tool
The Custom MACD with Leading Length can be used in conjunction with other technical indicators to confirm trading signals. For example, traders might use it alongside support and resistance levels, trendlines, or other momentum indicators to validate their trade entries and exits.
## Conclusion
The Custom MACD with Leading Length is a powerful enhancement of the traditional MACD indicator. By introducing an additional smoothing factor, it aims to reduce noise and provide earlier signals of trend changes. This makes it a valuable tool for traders seeking to improve their market analysis and trading strategies.
Whether you are a day trader, swing trader, or long-term investor, the Custom MACD with Leading Length can help you make more informed decisions by offering clearer insights into market trends. Its adaptability to different timeframes and asset classes further enhances its utility, making it a versatile addition to any trader's toolkit.
Experiment with the parameters to find the optimal settings that suit your trading style and preferences. Use the Custom MACD with Leading Length to gain a deeper understanding of market dynamics and enhance your trading performance.
VolCorrBeta [NariCapitalTrading]Indicator Overview: VolCorrBeta
The VolCorrBeta indicator is designed to analyze and interpret intermarket relationships. This indicator combines volatility, correlation, and beta calculations to provide a comprehensive view of how certain assets (BTC, DXY, CL) influence the ES futures contract (I tailored this indicator to the ES contract, but it will work for any symbol).
Functionality
Input Symbols
BTCUSD : Bitcoin to USD
DXY : US Dollar Index
CL1! : Crude Oil Futures
ES1! : S&P 500 Futures
These symbols can be customized according to user preferences. The main focus of the indicator is to analyze how the price movements of these assets correlate with and lead the price movements of the ES futures contract.
Parameters for Calculation
Correlation Length : Number of periods for calculating the correlation.
Standard Deviation Length : Number of periods for calculating the standard deviation.
Lookback Period for Beta : Number of periods for calculating beta.
Volatility Filter Length : Length of the volatility filter.
Volatility Threshold : Threshold for adjusting the lookback period based on volatility.
Key Calculations
Returns Calculation : Computes the daily returns for each input symbol.
Correlation Calculation : Computes the correlation between each input symbol's returns and the ES futures contract returns over the specified correlation length.
Standard Deviation Calculation : Computes the standard deviation for each input symbol's returns and the ES futures contract returns.
Beta Calculation : Computes the beta for each input symbol relative to the ES futures contract.
Weighted Returns Calculation : Computes the weighted returns based on the calculated betas.
Lead-Lag Indicator : Calculates a lead-lag indicator by averaging the weighted returns.
Volatility Filter : Smooths the lead-lag indicator using a simple moving average.
Price Target Estimation : Estimates the ES price target based on the lead-lag indicator (the yellow line on the chart).
Dynamic Stop Loss (SL) and Take Profit (TP) Levels : Calculates dynamic SL and TP levels using volatility bands.
Signal Generation
The indicator generates buy and sell signals based on the filtered lead-lag indicator and confirms them using higher timeframe analysis. Signals are debounced to reduce frequency, ensuring that only significant signals are considered.
Visualization
Background Coloring : The background color changes based on the buy and sell signals for easy visualization (user can toggle this on/off).
Signal Labels : Labels with arrows are plotted on the chart, showing the signal type (buy/sell), the entry price, TP, and SL levels.
Estimated ES Price Target : The estimated price target for ES futures is plotted on the chart.
Correlation and Beta Dashboard : A table displayed in the top right corner shows the current correlation and beta values for relative to the ES futures contract.
Customization
Traders can customize the following parameters to tailor the indicator to their specific needs:
Input Symbols : Change the symbols for BTC, DXY, CL, and ES.
Correlation Length : Adjust the number of periods used for calculating correlation.
Standard Deviation Length : Adjust the number of periods used for calculating standard deviation.
Lookback Period for Beta : Change the lookback period for calculating beta.
Volatility Filter Length : Modify the length of the volatility filter.
Volatility Threshold : Set a threshold for adjusting the lookback period based on volatility.
Plotting Options : Customize the colors and line widths of the plotted elements.
Funding Rate [CryptoSea]The Funding Rate Indicator by is a comprehensive tool designed to analyze funding rates across multiple cryptocurrency exchanges. This indicator is essential for traders who want to monitor funding rates and their impact on market trends.
Key Features
Exchange Coverage: Includes data from major exchanges such as Binance, Bitmex, Bybit, HTX, Kraken, OKX, Bitstamp, and Coinbase.
Perpetual Futures and Spot Markets: Fetches and analyzes pricing data from both perpetual futures and spot markets to provide a holistic view.
Smoothing and Customization: Allows users to smooth funding rates using a moving average, with customizable MA lengths for tailored analysis.
Dynamic Candle Coloring: Option to color candles based on trading conditions, enhancing visual analysis.
In the example below, the indicator shows how the funding rate shifts with market conditions, providing clear visual cues for bullish and bearish trends.
How it Works
Data Integration: Uses a secure security fetching function to retrieve pricing data while preventing look-ahead bias, ensuring accurate and reliable information.
TWAP Calculation: Computes Time-Weighted Average Prices (TWAP) for both perpetual futures and spot prices, forming the basis for funding rate calculations.
Funding Rate Calculation: Determines the raw funding rate by comparing TWAPs of perpetual futures and spot prices, then applies smoothing to highlight significant trends.
Color Coding: Highlights the funding rate with distinct colors (bullish and bearish), making it easier to interpret market conditions at a glance.
In the example below, the indicator effectively differentiates between bullish and bearish funding rates, aiding traders in making informed decisions based on current market dynamics.
Application
Market Analysis: Enables traders to analyze the impact of funding rates on market trends, facilitating more strategic decision-making.
Trend Identification: Assists in identifying potential market reversals by monitoring shifts in funding rates.
Customizable Settings: Provides extensive input settings for exchange selection, MA length, and candle coloring, allowing for personalized analysis.
The Funding Rate Indicator by is a powerful addition to any trader's toolkit, offering detailed insights into funding rates across multiple exchanges to navigate the cryptocurrency market effectively.
VP demo(Rolling period)Introduction
In the native VP (Volume Profile), the commonly referenced parameters are POC (Point of Control), VAH (Value Area High), and VAL (Value Area Low). However, since VAH and VAL are calculated by extending outward from the POC, their values heavily depend on the shape of the VP and the parameter settings of the value area ratio. This means their significance in identifying support and resistance in the market is limited. Based on VP, my algorithm is designed with two additional methods to identify low-volume points within a rolling time period, using them as reference points for support and resistance.
Current Algorithm Issues
When the candles update, you might notice overlapping support and resistance lines on the chart, or multiple lines appearing near the same location. This is due to TradingView's rendering issue, where old support and resistance lines that have been deleted in the code are not promptly removed from the chart. You only need to refer to the support and resistance lines that extend to the latest candle. If some lines remain at previous candles, it indicates that these points are outdated. As new candles continue to form, these lagging support and resistance lines will automatically disappear once the number of new candles reaches a certain threshold. Additionally, during significant market movements, you may see a large number of red lines. This is because the algorithm does not yet fully recognize abnormal market conditions. Future versions will gradually improve this aspect.
Volume Profile cheap copyIn the absence of TradingView's open-source Volume Profile (hereinafter referred to as VP) indicator code, I have replicated it. However, because this code is classified as an "indicator" rather than a "tool," it cannot allow users to define the range according to their preferences. In the code, I have set different periods, and users can input 0, 1, or 2 to let the indicator calculate the volume distribution from the earliest candle to the latest candle within the daily, weekly, or monthly range, respectively.
How can we prove that this code is consistent with TradingView's algorithm?
Firstly, the calculation or drawing process of VP starts from the earliest candle in the selected range. After calling TradingView's built-in "Fixed Range Volume Profile" (FRVP) tool, you can enter the settings interface of the tool and check both "developing POC" and "Value Area (VA)." The paths of POC, VAH, and VAL will appear in the chart. These paths are the changes in the values of POC, VAH, and VAL as the number of candles increases. If the paths shown by my indicator are the same as those shown by TradingView's VP indicator, then it proves the algorithms are consistent. Since VP itself is calculated based on volume, the high and low points of candles, and the opening and closing prices, if the data sources are consistent, the calculation results (the paths of POC, VAH, and VAL) will remain consistent over time. This can be used to infer that the algorithms are consistent. Additionally, the parameters of the two indicators (number of rows and value area ratio) must be the same to verify consistency. The number of rows in the indicator is usually set to 100 by default, and the value area ratio is 70. Therefore, the parameters in FRVP should also be set to 100 rows and a value area volume of 70.
Why is there a noticeable discrepancy?
When the start and end points of the VP remain unchanged, reducing the chart's time frame can improve accuracy. For example, when calculating the weekly VP, switching from a 1-hour time frame to a 5-minute time frame can make the indicator more closely match TradingView's native VP. Tests have shown that TradingView's native VP may not use the data displayed on the current chart for its calculations. For instance, the VP may use data from the 5-minute time frame even if the chart is displayed in the 1-hour time frame. However, my replicated VP calculates based on the chart's data, so differences in time frames will affect accuracy.
Current algorithm deficiencies
This replicated VP code is merely a demo and does not handle data updates. In other words, after the latest candle closes, the VP needs to be recalculated, but this recalculation step is not handled, which will cause errors. To resolve this issue, you only need to switch the time frame or delete the indicator and re-add it.
MetaFOX DCA (ASAP-RSI-BB%B-TV)Welcome To ' MetaFOX DCA (ASAP-RSI-BB%B-TV) ' Indicator.
This is not a Buy/Sell signals indicator, this is an indicator to help you create your own strategy using a variety of technical analyzing options within the indicator settings with the ability to do DCA (Dollar Cost Average) with up to 100 safety orders.
It is important when backtesting to get a real results, but this is impossible, especially when the time frame is large, because we don't know the real price action inside each candle, as we don't know whether the price reached the high or low first. but what I can say is that I present to you a backtest results in the worst possible case, meaning that if the same chart is repeated during the next period and you traded for the same period and with the same settings, the real results will be either identical to the results in the indicator or better (not worst). There will be no other factors except the slippage in the price when executing orders in the real trading, So I created a feature for that to increase the accuracy rate of the results. For more information, read this description.
Below I will explain all the properties and settings of the indicator:
A) 'Buy Strategies' Section: Your choices of strategies to Start a new trade: (All the conditions works as (And) not (OR), You have to choose one at least and you can choose more than one).
- 'ASAP (New Candle)': Start a trade as soon as possible at the opening of a new candle after exiting the previous trade.
- 'RSI': Using RSI as a technical analysis condition to start a trade.
- 'BB %B': Using BB %B as a technical analysis condition to start a trade.
- 'TV': Using tradingview crypto screener as a technical analysis condition to start a trade.
B) 'Exit Strategies' Section: Your choices of strategies to Exit the trades: (All the conditions works as (And) not (OR), You can choose more than one, But if you don't want to use any of them you have to activate the 'Use TP:' at least).
- 'ASAP (New Candle)': Exit a trade as soon as possible at the opening of a new candle after opening the previous trade.
- 'RSI': Using RSI as a technical analysis condition to exit a trade.
- 'BB %B': Using BB %B as a technical analysis condition to exit a trade.
- 'TV': Using tradingview crypto screener as a technical analysis condition to exit a trade.
C) 'Main Settings' Section:
- 'Trading Fees %': The Exchange trading fees in percentage (trading Commission).
- 'Entry Price Slippage %': Since real trading differs from backtest calculations, while in backtest results are calculated based on the open price of the candle, but in real trading there is a slippage from the open price of the candle resulting from the supply and demand in the real time trading, so this feature is to determine the slippage Which you think it is appropriate, then the entry prices of the trades will calculated higher than the open price of the start candle by the percentage of slippage that you set. If you don't want to calculate any slippage, just set it to zero, but I don't recommend that if you want the most realistic results.
Note: If (open price + slippage) is higher than the high of the candle then don't worry, I've kept this in consideration.
- 'Use SL': Activate to use stop loss percentage.
- 'SL %': Stop loss percentage.
- 'SL settings options box':
'SL From Base Price': Calculate the SL from the base order price (from the trade first entry price).
'SL From Avg. Price': Calculate the SL from the average price in case you use safety orders.
'SL From Last SO.': Calculate the SL from the last (lowest) safety order deviation.
ex: If you choose 'SL From Avg. Price' and SL% is 5, then the SL will be lower than the average price by 5% (in this case your SL will be dynamic until the price reaches all the safety orders unlike the other two SL options).
Note: This indicator programmed to be compatible with '3COMMAS' platform, but I added more options that came to my mind.
'3COMMAS' DCA bots uses 'SL From Base Price'.
- 'Use TP': Activate to use take profit percentage.
- 'TP %': Take profit percentage.
- 'Pure TP,SL': This feature was created due to the differences in the method of calculations between API tools trading platforms:
If the feature is not activated and (for example) the TP is 5%, this means that the price must move upward by only 5%, but you will not achieve a net profit of 5% due to the trading fees. but If the feature is activated, this means that you will get a net profit of 5%, and this means that the price must move upward by (5% for the TP + the equivalent of trading fees). The same idea is applied to the SL.
Note: '3COMMAS' DCA bots uses activated 'Pure TP,SL'.
- 'SO. Price Deviation %': Determines the decline percentage for the first safety order from the trade start entry price.
- 'SO. Step Scale': Determines the deviation multiplier for the safety orders.
Note: I'm using the same method of calculations for SO. (safety orders) levels that '3COMMAS' platform is using. If there is any difference between the '3COMMAS' calculations and the platform that you are using, please let me know.
'3COMMAS' DCA bots minimum 'SO. Price Deviation %' is (0.21)
'3COMMAS' DCA bots minimum 'SO. Step Scale' is (0.1)
- 'SO. Volume Scale': Determines the base order size multiplier for the safety orders sizes.
ex: If you used 10$ to buy at the trade start (base order size) and your 'SO. Volume Scale' is 2, then the 1st SO. size will be 20, the 2nd SO. size will be 40 and so on.
- 'SO. Count': Determines the number of safety orders that you want. If you want to trade without safety orders set it to zero.
'3COMMAS' DCA bots minimum 'SO. Volume Scale' is (0.1)
- 'Exchange Min. Size': The exchange minimum size per trade, It's important to prevent you from setting the base order Size less than the exchange limit. It's also important for the backtest results calculations.
ex: If you setup your strategy settings and it led to a loss to the point that you can't trade any more due to insufficient funds and your base order size share from the strategy becomes less than the exchange minimum trade size, then the indicator will show you a warning and will show you the point where you stopped the trading (It works in compatible with the initial capital). I recommend to set it a little bit higher than the real exchange minimum trade size especially if you trade without safety orders to not stuck in the trade if you hit the stop loss
- 'BO. Size': The base order size (funds you use at the trade entry).
- 'Initial Capital': The total funds allocated for trading using your strategy settings, It can be more than what is required in the strategy to cover the deficit in case of a loss, but it should not exceed the funds that you actually have for trading using this strategy settings, It's important to prevent you from setting up a strategy which requires funds more than what you have. It's also has other important benefits (refer to 'Exchange Min. Size' for more information).
- 'Accumulative Results': This feature is also called re-invest profits & risk reduction. If it's not activated then you will use the same funds size in each new trade whether you are in profit or loss till the (initial capitals + net results) turns insufficient. If it's activated then you will reuse your profits and losses in each new trade.
ex: The feature is active and your first trade ended with a net profit of 1000$, the next trade will add the 1000$ to the trade funds size and it will be distributed as a percentage to the BO. & SO.s according to your strategy settings. The same idea in case of a loss, the trade funds size will be reduced.
D) 'RSI Strategy' Section:
- 'Buy': RSI technical condition to start a trade. Has no effect if you don't choose 'RSI' option in 'Buy Strategies'.
- 'Exit': RSI technical condition to exit a trade. Has no effect if you don't choose 'RSI' option in 'Exit Strategies'.
E) 'TV Strategy' Section:
- 'Buy': TradingView Crypto Screener technical condition to start a trade. Has no effect if you don't choose 'TV' option in 'Buy Strategies'.
- 'Exit': TradingView Crypto Screener technical condition to exit a trade. Has no effect if you don't choose 'TV' option in 'Exit Strategies'.
F) 'BB %B Strategy' Section:
- 'Buy': BB %B technical condition to start a trade. Has no effect if you don't choose 'BB %B' option in 'Buy Strategies'.
- 'Exit': BB %B technical condition to exit a trade. Has no effect if you don't choose 'BB %B' option in 'Exit Strategies'.
G) 'Plot' Section:
- 'Signals': Plots buy and exit signals.
- 'BO': Plots the trade entry price (base order price).
- 'AVG': Plots the trade average price.
- 'AVG options box': Your choice to plot the trade average price type:
'Avg. With Fees': The trade average price including the trading fees, If you exit the trade at this price the trade net profit will be 0.00
'Avg. Without Fees': The trade average price but not including the trading fees, If you exit the trade at this price the trade net profit will be a loss equivalent to the trading fees.
- 'TP': Plots the trade take profit price.
- 'SL': Plots the trade stop loss price.
- 'Last SO': Plots the trade last safety order that the price reached.
- 'Exit Price': Plots a mark on the trade exit price, It plots in 3 colors as below:
Red (Default): Trade exit at a loss.
Green (Default): Trade exit at a profit.
Yellow (Default): Trade exit at a profit but this is a special case where we have to calculate the profits before reaching the safety orders (if any) on that candle (compatible with the idea of getting strategy results at the worst case).
- 'Result Table': Plots your strategy result table. The net profit percentage shown is a percentage of the 'initial capital'.
- 'TA Values': Plots your used strategies Technical analysis values. (Green cells means valid condition).
- 'Help Table': Plots a table to help you discover 100 safety orders with its deviations and the total funds needed for your strategy settings. Deviations shown in red is impossible to use because its price is <= 0.00
- 'Portfolio Chart': Plots your Portfolio status during the entire trading period in addition to the highest and lowest level reached. It's important when evaluating any strategy not only to look at the final result, but also to look at the change in results over the entire trading period. Perhaps the results were worryingly negative at some point before they rose again and made a profit. This feature helps you to see the whole picture.
- 'Welcome Message': Plots a welcome message and showing you the idea behind this indicator.
- 'Green Net Profit %': It plots the 'Net Profit %' in the result table in green color if the result is equal to or above the value that you entered.
- 'Green Win Rate %': It plots the 'Win Rate %' in the result table in green color if the result is equal to or above the value that you entered.
- 'User Notes Area': An empty text area, Feel free to use this area to write your notes so you don't forget them.
The indicator will take care of you. In some cases, warning messages will appear for you. Read them carefully, as they mean that you have done an illogical error in the indicator settings. Also, the indicator will sometimes stop working for the same reason mentioned above. If that happens then click on the red (!) next to the indicator name and read the message to find out what illogical error you have done.
Please enjoy the indicator and let me know your thoughts in the comments below.
Liquidity Dependent Price Stability AlgorithmThe Liquidity Dependent Price Stability (LDPS) indicator is designed to measure liquidity levels on an equity and, from those measurements, provide Bullish or Bearish outlooks for future price action. These outlooks are given via reporting the equity's Liquidity Condition and Liquidity Flow.
Interpretation
Liquidity Condition (LC) and Liquidity Flow (LF) measurements are displayed with color-specific chart colors and/or with text output.
LC can be reported as "Weak Bullish", "Bullish", or "Strong Bullish" for Bullish outlooks and "Weak Bearish", "Bearish" or "Strong Bearish" for Bearish outlooks. LC can also just be reported as "Bullish" or "Bearish".
Bullish LCs have a statistical correlation with future price appreciation, and Bearish LCs have a statistical correlation with price depreciation. When LC is “Bullish”, the price is likely to go up, and if LC is “Bearish”, the price is likely to go down.
Liquidity Flow (LF) is a measure of how LC is changing. When LC is becoming more bullish, LF is reported as “Improving”. When LC is becoming more bearish, LF is reported as “Worsening”. LF is only displayed via text output.
Settings and Configurations
LDPS Sensitivity and Reactivity: Determines if you want LDPS to be more sensitive to changing conditions or less sensitive. This choice affects how certain LDPS is when forming its future outlooks. LDPS achieves this increase in sensitivity and reactivity by lowering the bar for what LDPS considers a significant change.
Aggressive : LDPS will optimize reporting early changes in LC and LF at the expensive of accuracy. Aggressive is good for low-risk trading styles that prefer to exit a position early rather than deal with increased risk of oppositional movement.
Balanced : LDPS will try to balance reporting changes in LC and LF with maintaining accuracy. Balanced style is a good setting to start out with and is applicable across the widest range of equity’s and timeframes.
Conservative : LDPS will optimize accuracy over being sensitive to changes in LC or LF. Conservative is a good choice for lower timeframes and traders who only want to change or exit positions with the greatest confidence.
LDPS Reporting Style: Determines how you want LC to be reported.
Simplified : LDPS will only report LC as “Bullish” or “Bearish”.
Full : LDPS will increase its reporting details and include the “Strong” and “Weak” pre-fixes, when appropriate.
LDPS Candle Coloring: There are three different ways that LC can be reported on the chart via coloring.
LDPS Candle Replacement: This will replace the chart’s default candles with those created by LDPS. Note: In order to see LDPS’ candles and not the chart’s, you have to disable to chart’s candles. This can be done in Settings -> Symbol and unchecking “Body”, “Borders” and “Wick” boxes.
LDPS Candle Coloring: This will just color the bodies of the chart’s default candles. Note: This setting should not have the chart’s candle’s disabled.
LDPS Background Coloring: This will color the chart’s background rather than any candles.
LDPS Text Output: LC and LF are reported via a text box that can be moved several places on the chart, or the text box can be removed.
LDPS Measurements – Display: When selected, LC and LF will be reported via the text box.
LDPS Measurement – Text Location: Determines where the text box with LC and LF are located.
LDPS Measurement – Text Size: Determines the size of LC and LF within the text box.
LDPS Measurement – Background Color: Determines the background color of the text box with LC and LF.
LDPS Condition Color Selection – Bullish / Bearish: Color selection for each type of LC. Note: If the Simplified reporting style is selected, the “Full Bullish” and “Full Bearish” are the bullish and bearish color choices, respectively.
Frequently Asked Questions:
Where can I get additional Information?
Please check the “Author’s Instructions” section below.
Where can I find the results of the LDPS research?
Please check the “Author’s Instructions” section below.
Help! Something’s not working!
Apologies. Please see the email listed in “Author’s Instructions” below and let’s get started on solving the issue.
Which Sensitivity setting should I use?
The author’s preference is Conservative in most cases, but the answer for you depends on your preferred style.
An analogy might help: the aggressive setting will ensure LDPS is early to the party – every party. Of the parties that really kick off, you can be certain LDPS is there, but they had to visit a several of parties before finding the right one.
The Conservative setting won’t bring LDPS to every party – it will gladly stay at the one it’s at but when it detects the next real big hit, LDPS will move to that party instead. It won’t be the first one there, but it is definitely earlier than most.
Should I use the Full or Simplified reporting style?
Depending on how engaged you are with the particular equity or position, either choice can be beneficial. The Full reporting style will let you detect changes in LC before they might show with the Simplified reporting style. Some enjoy the additional data, some (like the Author) enjoy keeping things simple.
I can see LDPS’ colors in the chart’s candlesticks when the settings are open, but not when the settings are closed. How come?
If you are using the “LDPS Candle Replacement” setting, be sure to turn off the Chart’s default candles by right-clicking on the chart, going to Settings, then Symbol and then un-checking “Body”, “Border” and “Wick”. This should fix the issue.
I think there’s a bug – where do I report it?
Thank you for reaching out about a potential bug or issue! Please see the email below in “Author’s Instructions” to report the issue.
HilalimSBHilalimSB A Wedding Gift 🌙
HilalimSB - Revealing the Secrets of the Trend
HilalimSB is a powerful indicator designed to help investors analyze market trends and optimize trading strategies. Designed to uncover the secrets at the heart of the trend, HilalimSB stands out with its unique features and impressive algorithm.
Hilalim Algorithm and Fixed ATR Value:
HilalimSB is equipped with a special algorithm called "Hilalim" to detect market trends. This algorithm can delve into the depths of price movements to determine the direction of the trend and provide users with the ability to predict future price movements. Additionally, HilalimSB uses its own fixed Average True Range (ATR) value. ATR is an indicator that measures price movement volatility and is often used to determine the strength of a trend. The fixed ATR value of HilalimSB has been tested over long periods and its reliability has been proven. This allows users to interpret the signals provided by the indicator more reliably.
ATR Calculation Steps
1.True Range Calculation:
+ The True Range (TR) is the greatest of the following three values:
1. Current high minus current low
2. Current high minus previous close (absolute value)
3. Current low minus previous close (absolute value)
2.Average True Range (ATR) Calculation:
-The initial ATR value is calculated as the average of the TR values over a specified period
(typically 14 periods).
-For subsequent periods, the ATR is calculated using the following formula:
ATRt=(ATRt−1×(n−1)+TRt)/n
Where:
+ ATRt is the ATR for the current period,
+ ATRt−1 is the ATR for the previous period,
+ TRt is the True Range for the current period,
+ n is the number of periods.
Pine Script to Calculate ATR with User-Defined Length and Multiplier
Here is the Pine Script code for calculating the ATR with user-defined X length and Y multiplier:
//@version=5
indicator("Custom ATR", overlay=false)
// User-defined inputs
X = input.int(14, minval=1, title="ATR Period (X)")
Y = input.float(1.0, title="ATR Multiplier (Y)")
// True Range calculation
TR1 = high - low
TR2 = math.abs(high - close )
TR3 = math.abs(low - close )
TR = math.max(TR1, math.max(TR2, TR3))
// ATR calculation
ATR = ta.rma(TR, X)
// Apply multiplier
customATR = ATR * Y
// Plot the ATR value
plot(customATR, title="Custom ATR", color=color.blue, linewidth=2)
This code can be added as a new Pine Script indicator in TradingView, allowing users to calculate and display the ATR on the chart according to their specified parameters.
HilalimSB's Distinction from Other ATR Indicators
HilalimSB emerges with its unique Average True Range (ATR) value, presenting itself to users. Equipped with a proprietary ATR algorithm, this indicator is released in a non-editable form for users. After meticulous testing across various instruments with predetermined period and multiplier values, it is made available for use.
ATR is acknowledged as a critical calculation tool in the financial sector. The ATR calculation process of HilalimSB is conducted as a result of various research efforts and concrete data-based computations. Therefore, the HilalimSB indicator is published with its proprietary ATR values, unavailable for modification.
The ATR period and multiplier values provided by HilalimSB constitute the fundamental logic of a trading strategy. This unique feature aids investors in making informed decisions.
Visual Aesthetics and Clear Charts:
HilalimSB provides a user-friendly interface with clear and impressive graphics. Trend changes are highlighted with vibrant colors and are visually easy to understand. You can choose colors based on eye comfort, allowing you to personalize your trading screen for a more enjoyable experience. While offering a flexible approach tailored to users' needs, HilalimSB also promises an aesthetic and professional experience.
Strong Signals and Buy/Sell Indicators:
After completing test operations, HilalimSB produces data at various time intervals. However, we would like to emphasize to users that based on our studies, it provides the best signals in 1-hour chart data. HilalimSB produces strong signals to identify trend reversals. Buy or sell points are clearly indicated, allowing users to develop and implement trading strategies based on these signals.
For example, let's imagine you wanted to open a position on BTC on 2023.11.02. You are aware that you need to calculate which of the buying or selling transactions would be more profitable. You need support from various indicators to open a position. Based on the analysis and calculations it has made from the data it contains, HilalimSB would have detected that the graph is more suitable for a selling position, and by producing a sell signal at the most ideal selling point at 08:00 on 2023.11.02 (UTC+3 Istanbul), it would have informed you of the direction the graph would follow, allowing you to benefit positively from a 2.56% decline.
Technology and Innovation:
HilalimSB aims to enhance the trading experience using the latest technology. With its innovative approach, it enables users to discover market opportunities and support their decisions. Thus, investors can make more informed and successful trades. Real-Time Data Analysis: HilalimSB analyzes market data in real-time and identifies updated trends instantly. This allows users to make more informed trading decisions by staying informed of the latest market developments. Continuous Update and Improvement: HilalimSB is constantly updated and improved. New features are added and existing ones are enhanced based on user feedback and market changes. Thus, HilalimSB always aims to provide the latest technology and the best user experience.
Social Order and Intrinsic Motivation:
Negative trends such as widespread illegal gambling and uncontrolled risk-taking can have adverse financial effects on society. The primary goal of HilalimSB is to counteract these negative trends by guiding and encouraging users with data-driven analysis and calculable investment systems. This allows investors to trade more consciously and safely.
Ocs Ai TraderThis script perform predictive analytics from a virtual trader perspective!
It acts as an AI Trade Assistant that helps you decide the optimal times to buy or sell securities, providing you with precise target prices and stop-loss level to optimise your gains and manage risk effectively.
System Components
The trading system is built on 4 fundamental layers :
Time series Processing layer
Signal Processing layer
Machine Learning
Virtual Trade Emulator
Time series Processing layer
This is first component responsible for handling and processing real-time and historical time series data.
In this layer Signals are extracted from
averages such as : volume price mean, adaptive moving average
Estimates such as : relative strength stochastics estimates on supertrend
Signal Processing layer
This second layer processes signals from previous layer using sensitivity filter comprising of an Probability Distribution Confidence Filter
The main purpose here is to predict the trend of the underlying, by converging price, volume signals and deltas over a dominant cycle as dimensions and generate signals of action.
Key terms
Dominant cycle is a time cycle that has a greater influence on the overall behaviour of a system than other cycles.
The system uses Ehlers method to calculate Dominant Cycle/ Period.
Dominant cycle is used to determine the influencing period for the underlying.
Once the dominant cycle/ period is identified, it is treated as a dynamic length for considering further calculations
Predictive Adaptive Filter to generate Signals and define Targets and Stops
An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimisation algorithm. Because of the complexity of the optimisation algorithms, almost all adaptive filters are digital filters. Thus Helping us classify our intent either long side or short side
The indicator use Adaptive Least mean square algorithm, for convergence of the filtered signals into a category of intents, (either buy or sell)
Machine Learning
The third layer of the System performs classifications using KNN K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique.
K-NN algorithm assumes the similarity between the new case/data and available cases and put the new case into the category that is most similar to the available categories.
K-NN algorithm stores all the available data and classifies a new data point based on the similarity. This means when new data appears then it can be easily classified into a well suite category by using K- NN algorithm. K-NN algorithm can be used for Regression as well as for Classification but mostly it is used for the Classification problems.
Virtual Trade Emulator
In this last and fourth layer a trade assistant is coded using trade emulation techniques and the Lines and Labels for Buy / Sell Signals, Targets and Stop are forecasted!
How to use
The system generates Buy and Sell alerts and plots it on charts
Buy signal
Buy signal constitutes of three targets {namely T1, T2, T3} and one stop level
Sell signal
Sell signal constitutes of three targets {namely T1, T2, T3} and one stop level
What Securities will it work upon ?
Volume Informations must be present for the applied security
The indicator works on every liquid security : stocks, future, forex, crypto, options, commodities
What TimeFrames To Use ?
You can use any Timeframe, The indicator is Adaptive in Nature,
I personally use timeframes such as : 1m, 5m 10m, 15m, ..... 1D, 1W
This Script Uses Tradingview Premium features for working on lower timeframes
In case if you are not a Tradingview premium subscriber you should tell the script that after applying on chart, this can be done by going to settings and unchecking "Is your Tradingview Subscription Premium or Above " Option
How To Get Access ?
You will need to privately message me for access mentioning you want access to "Ocs Ai Trader" Use comment box only for constructive comments. Thanks !
Total Cross CalculatorThe Indicator calculates the total number of the death and golden crosses in the total chart which can help the moving average user to compare the number of signals generated by the moving average pair in the given timeframe.
If Indicator is not plotting anything then right click on the indicator's scale and click on "Auto(data fits the screen)" option.
Please visit it's previous version if you want to use the indicator on the moving averages created by yourself. Link is here
CPR by MTThe CPR indicator, or Central Pivot Range indicator, is a technical analysis tool used in trading to identify potential support and resistance levels based on the price action of a security. Developed by pivot point theory, it is particularly popular among day traders and swing traders. The CPR indicator consists of three lines:
1. **Pivot Point (PP):** This is the central line and is calculated as the average of the high, low, and closing prices from the previous trading period.
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2. **Top Central Pivot (TC):** This is calculated by subtracting the low from the PP and then adding the result to the PP.
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3. **Bottom Central Pivot (BC):** This is calculated by subtracting the high from the PP and then adding the result to the PP.
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### How to Use the CPR Indicator
- **Trend Identification:** A wide CPR range indicates low volatility and a potential sideways or consolidation phase. A narrow CPR range indicates high volatility and a potential strong trending move.
- **Support and Resistance:** The top and bottom central pivots act as immediate resistance and support levels. If the price is above the TC, it indicates a bullish sentiment, while if it is below the BC, it indicates a bearish sentiment.
- **Entry and Exit Points:** Traders use the CPR lines to determine optimal entry and exit points. For example, if the price breaks above the TC and sustains, it may signal a buy opportunity, whereas a drop below the BC may signal a sell opportunity.
### Practical Example
Suppose a stock had a high of $105, a low of $95, and a closing price of $100 on the previous day. The CPR levels for the next day would be calculated as follows:
1. **Pivot Point (PP):**
\
2. **Top Central Pivot (TC):**
\
3. **Bottom Central Pivot (BC):**
\
The levels for the next day would be PP = $100, TC = $110, and BC = $90. Traders would then use these levels to assess potential trading strategies based on where the price moves relative to these levels.
### Conclusion
The CPR indicator is a useful tool for traders looking to understand market conditions and make informed decisions about entry and exit points. Its effectiveness comes from its ability to highlight key price levels derived from historical price data, helping traders predict potential market movements.
Buffett Quality Score [Communication Services]Buffett Quality Score "Communication Services": Analyzing Communication Companies with Precision
The communication services sector encompasses a diverse range of companies involved in telecommunications, media, and entertainment. To assess the financial strength and performance of companies within this sector, the Buffett Quality Score employs a tailored set of financial metrics. This scoring system, inspired by the Piotroski F-Score methodology, assigns points based on specific financial criteria to provide a comprehensive quality assessment.
Scoring Methodology
The Buffett Quality Score is designed to evaluate the overall financial health and quality of companies operating within the communication services sector. Each selected financial metric is chosen for its relevance and importance in evaluating a company's performance and potential for sustainable growth. The score is computed by assigning points based on the achievement of specific thresholds for each indicator, with the total points determining the final score. This methodology ensures a nuanced analysis that captures the unique dynamics of the communication services industry.
Selected Financial Metrics and Criteria
1. Return on Invested Capital (ROIC) > 10.0%
Relevance: ROIC measures a company's efficiency in allocating capital to profitable investments. For communication companies, a ROIC above 10.0% indicates effective capital utilization, crucial for sustaining growth and innovation.
2. Return on Equity (ROE) > 15.0%
Relevance: ROE evaluates the return generated on shareholders' equity. A ROE exceeding 15.0% signifies robust profitability and effective management of shareholder funds, essential for investor confidence in communication companies.
3. Revenue One-Year Growth > 10.0%
Relevance: High revenue growth indicates strong market demand and successful business strategies. For communication services, where innovation and content delivery are paramount, growth exceeding 10.0% reflects market leadership and competitive positioning.
4. Gross Margin > 40.0%
Relevance: Gross margin measures profitability after accounting for production costs. In the communication services sector, a gross margin above 40.0% demonstrates efficient operations and high-value content offerings, critical for maintaining competitive advantage.
5. Net Margin > 10.0%
Relevance: Net margin assesses overall profitability after all expenses. A net margin exceeding 10.0% indicates effective cost management and operational efficiency, fundamental for sustained profitability in communication companies.
6. EPS One-Year Growth > 10.0%
Relevance: EPS growth reflects the company's ability to increase earnings per share. For communication firms, where content monetization and subscription models are prevalent, EPS growth above 10.0% signals successful business expansion and value creation.
7. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score evaluates fundamental strength across various financial metrics. A score above 6.0 suggests strong financial health and operational efficiency, crucial for navigating competitive pressures in the communication services industry.
8. Price/Earnings Ratio (Forward) < 25.0
Relevance: The forward P/E ratio compares current share price to expected future earnings. A ratio below 25.0 indicates reasonable valuation relative to growth prospects, important for investors seeking value opportunities in communication stocks.
9. Current Ratio > 1.5
Relevance: The current ratio assesses short-term liquidity by comparing current assets to current liabilities. In communication companies, a ratio above 1.5 ensures financial flexibility and the ability to meet short-term obligations, vital for operational stability.
10. Debt to Equity Ratio < 1.0
Relevance: A lower debt to equity ratio indicates prudent financial management and reduced reliance on debt financing. For communication firms, maintaining a ratio below 1.0 signifies a healthy balance sheet and lower financial risk.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, suggesting higher risk.
5 Points: Represents average performance, warranting further analysis to understand underlying factors.
6-10 Points: Reflects strong financial health and quality, positioning the company favorably within the competitive communication services industry.
Conclusion
The Buffett Quality Score provides a robust framework for evaluating communication companies, emphasizing critical financial indicators tailored to industry dynamics. By leveraging these insights, investors and analysts can make informed decisions, identifying companies poised for sustainable growth and performance in the ever-evolving communication services landscape.
Disclaimer: The Buffett Quality Score serves as a tool for financial analysis and should not replace professional advice or comprehensive due diligence. Investors should conduct thorough research and consult with financial experts based on individual investment objectives.
