Adaptive MACD [LuxAlgo]The Adaptive MACD indicator is an adaptive version of the popular Moving Average Convergence Divergence (MACD) oscillator, returning longer-term variations during trending markets and cyclic variations during ranging markets while filtering out noisy variations.
🔶 USAGE
The proposed oscillator contains all the elements within a regular MACD, such as a signal line and histogram. A MACD value above 0 would indicate up-trending variations, while a value under 0 would be indicating down-trending variations.
Just like most oscillators, our proposed Adaptive MACD is able to return divergences with the price.
As we can see in the image above ranging markets will make the Adaptive MACD more conservative toward more cyclical conservations, filtering out both noise and longer-term variations. However, when longer-term variations (such as in a trending market) are prominent the oscillator will conserve longer-term variations.
The R2 Period setting determines when trending/ranging markets are detected, with higher values returning indications for longer intervals.
The fast and slow settings will act similarly to the regular MACD, however, closer values will return more cyclical outputs.
The image above compares our proposed MACD (top) with a regular MACD (bottom), both using fast = 19 and slow = 20 .
🔶 DETAILS
It is common to be solely interested in the trend component when the market is trending, however, during a ranging market it is more common to observe a more prominent cyclical/noise component. We want to be able to preserve one of the components at the appropriate market conditions, however, the regular MACD lack the ability to preserve cyclical component with high accuracy.
The MACD is an IIR bandpass filter. In order to obtain a lower passband bandwidth and a more symmetrical magnitude response (which would allow to conserve more precise cyclical variations) we can directly change the system calculation:
y = (price - price ) × g + ((1 - a1) + (1 - a2)) × y - (1 - a1) × (1 - a2) × y
where:
a1 = 2/(fast + 1)
a2 = 2/(slow + 1)
g = a1 - a2
Using division instead of multiplication on the second feedback weight allows further weighting the 2 samples lagged output, returning a more desirable magnitude response with a higher degree of filtering on both ends of the spectrum as shown in the image below:
We are interested in conserving cycles during ranging markets, and longer-term variations during trending markets, we can do this by interpolating between our two filter coefficients:
α × + (1 - α) ×
where 1 > α > 0 . α is measuring if the market is trending or ranging, with values closer to 1 indicating a trending market. We see that for higher values of α the original coefficient of the MACD is used. The image below shows various magnitude responses given multiple values of α :
We use a rolling R-Squared as α , this measurement has the benefit of indicating if the market is trending or ranging, as well as being constrained within range (0, 1), and having a U-shaped distribution.
If you are interested to learn more about the MACD see:
🔶 SETTINGS
R2 Period: Calculation window of the R-Squared.
Fast: Fast period for the calculation of the Adaptive MACD, lower values will return more noisy results.
Slow: Slow period for the calculation of the Adaptive MACD, higher values will return result with longer-term conserved variations.
Signal: Period of the EMA applied to the Adaptive MACD.
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Pro Supertrend CalculatorThis indicator is an adapted version of Julien_Eche's 'Pro Momentum Calculator' tailored specifically for TradingView's 'Supertrend indicator'.
The "Pro Supertrend Calculator" indicator has been developed to provide traders with a data-driven perspective on price movements in financial markets. Its primary objective is to analyze historical price data and make probabilistic predictions about the future direction of price movements, specifically in terms of whether the next candlestick will be bullish (green) or bearish (red). Here's a deeper technical insight into how it accomplishes this task:
1. Supertrend Computation:
The indicator initiates by computing the Supertrend indicator, a sophisticated technical analysis tool. This calculation involves two essential parameters:
- ATR Length (Average True Range Length): This parameter determines the sensitivity of the Supertrend to price fluctuations.
- Factor: This multiplier plays a pivotal role in establishing the distance between the Supertrend line and prevailing market prices. A higher factor value results in a more significant separation.
2. Supertrend Visualization:
The Supertrend values derived from the calculation are meticulously plotted on the price chart, manifesting as two distinct lines:
- Green Line: This line represents the Supertrend when it indicates a bullish trend, signifying an anticipation of rising prices.
- Red Line: This line signifies the Supertrend in bearish market conditions, indicating an expectation of falling prices.
3. Consecutive Candle Analysis:
- The core function of the indicator revolves around tracking successive candlestick patterns concerning their relationship with the Supertrend line.
- To be included in the analysis, a candlestick must consistently close either above (green candles) or below (red candles) the Supertrend line for multiple consecutive periods.
4.Labeling and Enumeration:
- To communicate the count of consecutive candles displaying uniform trend behavior, the indicator meticulously applies labels to the price chart.
- The positioning of these labels varies based on the direction of the trend, residing either below (for bullish patterns) or above (for bearish patterns) the candlestick.
- The color scheme employed aligns with the color of the candle, using green labels for bullish candles and red labels for bearish ones.
5. Tabular Data Presentation:
- The indicator augments its graphical analysis with a customizable table prominently displayed on the chart. This table delivers comprehensive statistical insights.
- The tabular data comprises the following key elements for each consecutive period:
a. Consecutive Candles: A tally of the number of consecutive candles displaying identical trend characteristics.
b. Candles Above Supertrend: A count of candles that remained above the Supertrend during the sequential period.
3. Candles Below Supertrend: A count of candles that remained below the Supertrend during the sequential period.
4. Upcoming Green Candle: An estimation of the probability that the next candlestick will be bullish, grounded in historical data.
5. Upcoming Red Candle: An estimation of the probability that the next candlestick will be bearish, based on historical data.
6. Tailored Configuration:
To accommodate diverse trading strategies and preferences, the indicator offers extensive customization options. Traders can fine-tune parameters such as ATR length, factor, label and table placement, and table size to align with their unique trading approaches.
In summation, the "Pro Supertrend Calculator" indicator is an intricately designed tool that leverages the Supertrend indicator in conjunction with historical price data to furnish traders with an informed outlook on potential future price dynamics, with a particular emphasis on the likelihood of specific bullish or bearish candlestick patterns stemming from consecutive price behavior.
Seasonal - Trading Day of MonthIndicator Description: Historical Comparative Price Analysis
The Historical Comparative Price Analysis indicator serves as a comprehensive tool for evaluating price changes over distinct trading periods. By configuring the date settings, the indicator captures the percentage change data for each individual day or month, facilitating a clear historical perspective. Each year is represented in a separate row, allowing for a side-by-side presentation of corresponding data for the same trading day or week.
Within the "Summary" row, the indicator calculates the average change for each selected trading day within a specified time frame. This calculation, rooted in Larry Williams' concept, considers trading days rather than calendar days. The "Summary" row provides a quick insight into whether the current price change exceeds or falls short of the average change within the chosen time frame.
The indicator's final row presents a comprehensive overview, including the maximum and minimum average changes. It showcases the closing price from the first column of the 10th row, aiding in distinguishing between the last trading day of the month and the first trading day, which varies due to different market opening times.
To enhance visual analysis, the indicator attempts to display the price average of the chosen time frame as a reference line on the chart. The maximum and minimum values are added or subtracted from the reference line to create an average price channel. The color of the candlesticks dynamically changes to indicate whether the current price change is above or below the average.
For optimal results, we recommend selecting the previous year's data and the current month's data from the 1st to the 31st day. In weekly charts, multiple months can be selected to provide a broader perspective on price trends.
Enhance your trading insights with the Historical Comparative Price Analysis indicator, and gain a deeper understanding of how current price changes relate to historical averages.
Note: This description is intended for educational and informational purposes and is not intended as financial advice. Always conduct your research and analysis before making trading decisions.
SuperTrend AI (Clustering) [LuxAlgo]The SuperTrend AI indicator is a novel take on bridging the gap between the K-means clustering machine learning method & technical indicators. In this case, we apply K-Means clustering to the famous SuperTrend indicator.
🔶 USAGE
Users can interpret the SuperTrend AI trailing stop similarly to the regular SuperTrend indicator. Using higher minimum/maximum factors will return longer-term signals.
The displayed performance metrics displayed on each signal allow for a deeper interpretation of the indicator. Whereas higher values could indicate a higher potential for the market to be heading in the direction of the trend when compared to signals with lower values such as 1 or 0 potentially indicating retracements.
In the image above, we can notice more clear examples of the performance metrics on signals indicating trends, however, these performance metrics cannot perform or predict every signal reliably.
We can see in the image above that the trailing stop and its adaptive moving average can also act as support & resistance. Using higher values of the performance memory setting allows users to obtain a longer-term adaptive moving average of the returned trailing stop.
🔶 DETAILS
🔹 K-Means Clustering
When observing data points within a specific space, we can sometimes observe that some are closer to each other, forming groups, or "Clusters". At first sight, identifying those clusters and finding their associated data points can seem easy but doing so mathematically can be more challenging. This is where cluster analysis comes into play, where we seek to group data points into various clusters such that data points within one cluster are closer to each other. This is a common branch of AI/machine learning.
Various methods exist to find clusters within data, with the one used in this script being K-Means Clustering , a simple iterative unsupervised clustering method that finds a user-set amount of clusters.
A naive form of the K-Means algorithm would perform the following steps in order to find K clusters:
(1) Determine the amount (K) of clusters to detect.
(2) Initiate our K centroids (cluster centers) with random values.
(3) Loop over the data points, and determine which is the closest centroid from each data point, then associate that data point with the centroid.
(4) Update centroids by taking the average of the data points associated with a specific centroid.
Repeat steps 3 to 4 until convergence, that is until the centroids no longer change.
To explain how K-Means works graphically let's take the example of a one-dimensional dataset (which is the dimension used in our script) with two apparent clusters:
This is of course a simple scenario, as K will generally be higher, as well the amount of data points. Do note that this method can be very sensitive to the initialization of the centroids, this is why it is generally run multiple times, keeping the run returning the best centroids.
🔹 Adaptive SuperTrend Factor Using K-Means
The proposed indicator rationale is based on the following hypothesis:
Given multiple instances of an indicator using different settings, the optimal setting choice at time t is given by the best-performing instance with setting s(t) .
Performing the calculation of the indicator using the best setting at time t would return an indicator whose characteristics adapt based on its performance. However, what if the setting of the best-performing instance and second best-performing instance of the indicator have a high degree of disparity without a high difference in performance?
Even though this specific case is rare its however not uncommon to see that performance can be similar for a group of specific settings (this could be observed in a parameter optimization heatmap), then filtering out desirable settings to only use the best-performing one can seem too strict. We can as such reformulate our first hypothesis:
Given multiple instances of an indicator using different settings, an optimal setting choice at time t is given by the average of the best-performing instances with settings s(t) .
Finding this group of best-performing instances could be done using the previously described K-Means clustering method, assuming three groups of interest (K = 3) defined as worst performing, average performing, and best performing.
We first obtain an analog of performance P(t, factor) described as:
P(t, factor) = P(t-1, factor) + α * (∆C(t) × S(t-1, factor) - P(t-1, factor))
where 1 > α > 0, which is the performance memory determining the degree to which older inputs affect the current output. C(t) is the closing price, and S(t, factor) is the SuperTrend signal generating function with multiplicative factor factor .
We run this performance function for multiple factor settings and perform K-Means clustering on the multiple obtained performances to obtain the best-performing cluster. We initiate our centroids using quartiles of the obtained performances for faster centroids convergence.
The average of the factors associated with the best-performing cluster is then used to obtain the final factor setting, which is used to compute the final SuperTrend output.
Do note that we give the liberty for the user to get the final factor from the best, average, or worst cluster for experimental purposes.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Performance Memory: Determine the degree to which older inputs affect the current output, with higher values returning longer-term performance measurements.
From Cluster: Determine which cluster is used to obtain the final factor.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
AI Trend Navigator [K-Neighbor]█ Overview
In the evolving landscape of trading and investment, the demand for sophisticated and reliable tools is ever-growing. The AI Trend Navigator is an indicator designed to meet this demand, providing valuable insights into market trends and potential future price movements. The AI Trend Navigator indicator is designed to predict market trends using the k-Nearest Neighbors (KNN) classifier.
By intelligently analyzing recent price actions and emphasizing similar values, it helps traders to navigate complex market conditions with confidence. It provides an advanced way to analyze trends, offering potentially more accurate predictions compared to simpler trend-following methods.
█ Calculations
KNN Moving Average Calculation: The core of the algorithm is a KNN Moving Average that computes the mean of the 'k' closest values to a target within a specified window size. It does this by iterating through the window, calculating the absolute differences between the target and each value, and then finding the mean of the closest values. The target and value are selected based on user preferences (e.g., using the VWAP or Volatility as a target).
KNN Classifier Function: This function applies the k-nearest neighbor algorithm to classify the price action into positive, negative, or neutral trends. It looks at the nearest 'k' bars, calculates the Euclidean distance between them, and categorizes them based on the relative movement. It then returns the prediction based on the highest count of positive, negative, or neutral categories.
█ How to use
Traders can use this indicator to identify potential trend directions in different markets.
Spotting Trends: Traders can use the KNN Moving Average to identify the underlying trend of an asset. By focusing on the k closest values, this component of the indicator offers a clearer view of the trend direction, filtering out market noise.
Trend Confirmation: The KNN Classifier component can confirm existing trends by predicting the future price direction. By aligning predictions with current trends, traders can gain more confidence in their trading decisions.
█ Settings
PriceValue: This determines the type of price input used for distance calculation in the KNN algorithm.
hl2: Uses the average of the high and low prices.
VWAP: Uses the Volume Weighted Average Price.
VWAP: Uses the Volume Weighted Average Price.
Effect: Changing this input will modify the reference values used in the KNN classification, potentially altering the predictions.
TargetValue: This sets the target variable that the KNN classification will attempt to predict.
Price Action: Uses the moving average of the closing price.
VWAP: Uses the Volume Weighted Average Price.
Volatility: Uses the Average True Range (ATR).
Effect: Selecting different targets will affect what the KNN is trying to predict, altering the nature and intent of the predictions.
Number of Closest Values: Defines how many closest values will be considered when calculating the mean for the KNN Moving Average.
Effect: Increasing this value makes the algorithm consider more nearest neighbors, smoothing the indicator and potentially making it less reactive. Decreasing this value may make the indicator more sensitive but possibly more prone to noise.
Neighbors: This sets the number of neighbors that will be considered for the KNN Classifier part of the algorithm.
Effect: Adjusting the number of neighbors affects the sensitivity and smoothness of the KNN classifier.
Smoothing Period: Defines the smoothing period for the moving average used in the KNN classifier.
Effect: Increasing this value would make the KNN Moving Average smoother, potentially reducing noise. Decreasing it would make the indicator more reactive but possibly more prone to false signals.
█ What is K-Nearest Neighbors (K-NN) algorithm?
At its core, the K-NN algorithm recognizes patterns within market data and analyzes the relationships and similarities between data points. By considering the 'K' most similar instances (or neighbors) within a dataset, it predicts future price movements based on historical trends. The K-Nearest Neighbors (K-NN) algorithm is a type of instance-based or non-generalizing learning. While K-NN is considered a relatively simple machine-learning technique, it falls under the AI umbrella.
We can classify the K-Nearest Neighbors (K-NN) algorithm as a form of artificial intelligence (AI), and here's why:
Machine Learning Component: K-NN is a type of machine learning algorithm, and machine learning is a subset of AI. Machine learning is about building algorithms that allow computers to learn from and make predictions or decisions based on data. Since K-NN falls under this category, it is aligned with the principles of AI.
Instance-Based Learning: K-NN is an instance-based learning algorithm. This means that it makes decisions based on the entire training dataset rather than deriving a discriminative function from the dataset. It looks at the 'K' most similar instances (neighbors) when making a prediction, hence adapting to new information if the dataset changes. This adaptability is a hallmark of intelligent systems.
Pattern Recognition: The core of K-NN's functionality is recognizing patterns within data. It identifies relationships and similarities between data points, something akin to human pattern recognition, a key aspect of intelligence.
Classification and Regression: K-NN can be used for both classification and regression tasks, two fundamental problems in machine learning and AI. The indicator code is used for trend classification, a predictive task that aligns with the goals of AI.
Simplicity Doesn't Exclude AI: While K-NN is often considered a simpler algorithm compared to deep learning models, simplicity does not exclude something from being AI. Many AI systems are built on simple rules and can be combined or scaled to create complex behavior.
No Explicit Model Building: Unlike traditional statistical methods, K-NN does not build an explicit model during training. Instead, it waits until a prediction is required and then looks at the 'K' nearest neighbors from the training data to make that prediction. This lazy learning approach is another aspect of machine learning, part of the broader AI field.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Price Range Volume Profile [Pt]█ Introduction
The Price Range Volume Profile (PRVP) is a revolutionary indicator. This tool stands out from its peers due to its unique ability to capture the entire price chart history, thus providing a comprehensive volume profile of the entire asset's trading history, as available on TradingView chart. It's worth noting that I believe this tool is the first of its kind to accomplish such a feat. A much recommended tool if you are a volume profile trader.
█ Main Features
► Historical Lookback: This feature dives deep into the past, grasping all the historical data of an asset. It's equipped to handle up to 20,000 bars, although users without a premium TradingView account are advised to keep it at a maximum of 10,000 bars, or just use the "Full Historical Lookback" feature.
► Volume Profile / POC: Displays the distribution of volume across price levels for the selected price range. The Point of Control (POC), which is the price level with the highest traded volume, is also highlighted.
► Customization: Users have the flexibility to adjust the profile's appearance, including profile width, horizontal offset, and the option to fill the background of the profile range.
► Time Weighting: This feature allows users to give more weight to recent trading activity, which can be especially useful for intraday traders or during times of high volatility. Note that this feature will impact the volume profile and POC level.
► Settings Table: A settings table is displayed on the chart for users to quickly reference their input parameters.
█ Input Parameters
► Lookback Timeframe: Determines the period for which the volume profile is generated.
► Price Range: The percentage distance to consider for the profile, adjusted above and below the current closing price.
► Profile Step size: The granularity of the volume profile. Users can opt for automatic step size based on a predefined calculation or set their preferred tick step size.
► Historical Bars Lookback: Determines the number of bars to include in the volume profile calculation.
► Profile Visuals: Adjust the appearance and layout of the volume profile on the chart.
► Extra: Additional settings including the display of a settings table and its location.
█ Basic Understanding of Volume Profile - How to use PRVP?
Volume Profile is a valuable tool for traders who want insights into where the majority of trading activity has occurred. Here are some tips to make the most of it:
► Understand the Basics: Before using the Volume Profile, ensure you understand the difference between it and the standard volume histogram. While both represent volume, the former displays it against price while the latter shows it against time.
► Identify High Volume Nodes (HVN) and Low Volume Nodes (LVN):
◊ HVN: Areas where there's a lot of trading activity and where the price has spent a lot of time. These areas can act as strong support or resistance.
◊ LVN: Areas where there's a lack of trading activity. Prices might move quickly through these areas, and they can act as potential breakpoints or accelerators for price movement.
► Locate the Point of Control (POC): This is the price level with the highest traded volume for a specified period. It often acts as a magnet for price, and it can serve as a pivot or reference point.
► Trend Confirmation: A shift in the volume profile from one price level to another can confirm a trend. For instance, if higher volume starts to build at higher price levels, it may indicate a strong uptrend.
► Watch for Volume Gaps: If there's a significant gap in the volume profile, prices may move quickly through these levels as there's little historical trading activity to act as support or resistance.
█ Other Usage Tips
◊ For optimal performance, ensure that the chosen timeframe aligns closely with the chart timeframe. Differences in timeframes may lead to minor discrepancies in the volume profile.
◊ To address any errors arising from too many levels displayed on the volume profile, consider increasing the Profile Step size or reducing the Price Range.
Market trend based on ema strengthThis script is a trading indicator written in Pine Script, a domain-specific language used for creating custom technical analysis indicators and strategies on the TradingView platform. Let's break down what this script is doing and its potential usage:
Title and Overlay:
The indicator is given a title: "Market trend based on ema strength."
The overlay=true parameter ensures that the indicator is plotted on the price chart itself, overlaying the price data.
EMA Calculations:
Exponential Moving Averages (EMAs) are calculated for different time periods based on the closing prices.
Degree of Change Calculation:
The degree of change is calculated as the percentage difference between the closing price and each respective EMAs.
Trend Identification:
The script attempts to identify uptrends and downtrends based on the comparison of degree of change values across the different EMAs. For an uptrend, each subsequent EMA's degree of change should be greater than the previous one, and for a downtrend, it should be lower.
EMA and RSI Calculation:
Additional EMAs and the Relative Strength Index (RSI) are calculated.
Buy and Sell Signal Generation:
Buy signals are generated when certain conditions are met: an uptrend is detected, the previous close is below the additional EMAs, and the current close is above the additional EMAs.
Sell signals are generated in the opposite scenario: a downtrend is detected, the previous close is above the additional EMAs, and the current close is below the additional EMAs.
Visualization:
The script uses plotshape to visually indicate buy and sell signals on the chart as labels.
The background color of the chart is changed based on the detected trend
Usage:
This indicator is designed to assist traders in identifying potential buy and sell signals based on trends in EMAs, RSI, and price movement. It provides a visual representation of trend changes and generates signals when certain conditions align, helping traders make informed decisions about entering or exiting positions.
It's important to note that while this script provides an automated approach to identifying trends and generating signals, successful trading also requires a deep understanding of the market, risk management, and the application of multiple indicators and strategies. Traders should thoroughly backtest and validate any trading strategy before applying it in real trading scenarios.
Directional Movement Index FLEXA common problem experienced by short term traders using DMI/ADX is that the session breaks results in carry-over effects from the prior session. For example, a large gap up would result in a positive DMI, even though momentum is clearly negative. Note the extremely different results in the morning session, when the gap is reversed.
The DMI-FLEX algoritm resets the +DI and -DI values to the prior session ending midpoint, so that new momentum can be observed from the indicator. (Note for Pinescript coders: rma function does not accept series int, thus the explicit pine_rma function)
DMI-FLEX has the added feature that the ADX value, instead of a separate line, is shown as shading between the +DI and -DI lines, and the color itself is determined by whether +DI is above -DI for a bullish color, or -DI is above +DI for a bearish color.
DMI Flex also gives you the flexibility of inverse colors, in case your chart has inverted scale.
Summary and How to use:
1) Green when +DI is above -DI
2) Red when -DI is above +DI
3) Deeper shading represents a higher ADX value.
Variety Step RSI w/ Dynamic Zones [Loxx]Variety Step RSI w/ Dynamic Zones is a stepped RSI calculation with Discontinued Signal Lines. This indicator includes 7 types of RSI to choose from. The addition of the Discontinued Signal Lines allows this indicator to better identify momentum shifts in price so traders have better defined long/short signals.
Enhanced Moving Average Calculation with Stepped Moving Average and the Advantages over Regular RSI
Technical analysis plays a crucial role in understanding and predicting market trends. One popular indicator used by traders and analysts is the Relative Strength Index (RSI). However, an enhanced approach called Stepped Moving Average, in combination with the Slow RSI function, offers several advantages over regular RSI calculations.
█ Stepped Moving Average and Moving Averages:
The Stepped Moving Average function serves as a crucial component in the calculation of moving averages. Moving averages smooth out price data over a specific period to identify trends and potential trading signals. By employing the Stepped Moving Average function, traders can enhance the accuracy of moving averages and make more informed decisions.
Stepped Moving Average takes two parameters:
The current RSI value and a size parameter. It computes the next step in the moving average calculation by determining the upper and lower bounds of the moving average range. It accomplishes this by adjusting the values of smax and smin based on the given RSI and size.
Furthermore, Stepped Moving Average introduces the concept of a trend variable. By comparing the previous trend value with the current RSI and the previous upper and lower bounds, it updates the trend accordingly. This feature enables traders to identify potential shifts in market sentiment and make timely adjustments to their trading strategies.
█ Advantages over Regular RSI:
Enhanced Range Boundaries:
The inclusion of size parameters in Stepped Moving Average allows for more precise determination of the upper and lower bounds of the moving average range. This feature provides traders with a clearer understanding of the potential price levels that can influence market behavior. Consequently, it aids in setting more effective entry and exit points for trades.
Improved Trend Identification:
The trend variable in Stepped Moving Average helps traders identify changes in market trends more accurately. By considering the previous trend value and comparing it to the current RSI and previous bounds, Stepped Moving Average captures trend reversals with greater precision. This capability empowers traders to respond swiftly to market shifts and potentially capture more profitable trading opportunities.
Smoother Moving Averages:
Stepped Moving Average's ability to adjust the moving average range bounds based on trend changes and size parameters results in smoother moving averages. Regular RSI calculations may produce jagged or erratic results due to abrupt market movements. Stepped Moving Average mitigates this issue by dynamically adapting the range boundaries, thereby providing traders with more reliable and consistent moving average signals.
Complementary Functionality with Slow RSI:
Stepped Moving Average and Slow RSI function in harmony to provide a comprehensive trading analysis toolkit. While Stepped Moving Average refines the moving average calculation process, Slow RSI offers a more accurate representation of market strength. The combination of these two functions facilitates a deeper understanding of market dynamics and assists traders in making better-informed decisions.
What is a Discontinued Signal Line (DSL)?
Many indicators employ signal lines to more easily identify trends or desired states of the indicator. The concept of a signal line is straightforward: by comparing a value to its smoothed, slightly lagging state, one can determine the current momentum or state.
The Discontinued Signal Line builds on this fundamental idea by extending it: rather than having a single signal line, multiple lines are used based on the indicator's current value.
The "signal" line is calculated as follows:
When a specific level is crossed in the desired direction, the EMA of that value is calculated for the intended signal line.
When that level is crossed in the opposite direction, the previous "signal" line value is "inherited," becoming a sort of level.
This approach combines signal lines and levels, aiming to integrate the advantages of both methods.
In essence, DSL enhances the signal line concept by inheriting the previous signal line's value and converting it into a level.
Extras
-Alerts
-Signals
Related indicators:
Step RSI
ICT Silver Bullet [LuxAlgo]The ICT Silver Bullet indicator is inspired from the lectures of "The Inner Circle Trader" (ICT) and highlights the Silver Bullet (SB) window which is a specific 1-hour interval where a Fair Value Gap (FVG) pattern can be formed.
When a FVG is formed during the Silver Bullet window, Support & Resistance lines will be drawn at the end of the SB session.
There are 3 different Silver Bullet windows (New York local time):
The London Open Silver Bullet (3 AM — 4 AM ~ 03:00 — 04:00)
The AM Session Silver Bullet (10 AM — 11 AM ~ 10:00 — 11:00)
The PM Session Silver Bullet (2 PM — 3 PM ~ 14:00 — 15:00)
🔶 USAGE
The ICT Silver Bullet indicator aims to provide users a comprehensive display as similar as possible to how anyone would manually draw the concept on their charts.
It's important to use anything below the 15-minute timeframe to ensure proper setups can display. In this section, we are purely using the 3-minute timeframe.
In the image below, we can see a bullish setup whereas a FVG was successfully retested during the Silver Bullet session. This was then followed by a move upwards to liquidity as our target.
Alternatively, you can also see below a bearish setup utilizing the ICT Silver Bullet indicator outlined.
At this moment, the indicator has removed all other FVGs within the Silver Bullet session & has confirmed this FVG as the retested one.
There is also a support level marked below to be used as a liquidity target as per the ICT Silver Bullet concept suggests.
In the below chart we can see 4 separate consecutive examples of bullish & bearish setups on the 3-minute chart.
🔶 CONCEPTS
This technique can visualize potential support/resistance lines, which can be used as targets.
The script contains 2 main components:
• forming of a Fair Value Gap (FVG)
• drawing support/resistance (S/R) lines
🔹 Forming of FVG
1 basic principle: when a FVG at the end of the SB session is not retraced, it will be made invisible.
Dependable on the settings, different FVG's will be shown.
• 'All FVG': all FVG's are shown, regardless the trend
• 'Only FVG's in the same direction of trend': Only FVG's are shown that are similar to the trend at that moment (trend can be visualized by enabling ' Show ' -> ' Trend ')
-> only bearish FVG when the trend is bearish vs. bullish FVG when trend is bullish
• 'strict': Besides being similar to the trend, only FVG's are shown when the closing price at the end of the SB session is:
– below the top of the FVG box (bearish FVG)
– above bottom of the FVG box (bullish FVG)
• 'super-strict': Besides being similar to the trend, only FVG's are shown when the FVG box is NOT broken
in the opposite direction AND the closing price at the end of the SB session is:
– below bottom of the FVG box (bearish FVG)
– above the top of the FVG box (bullish FVG)
' Super-Strict ' mode resembles ICT lectures the most.
🔹 Drawing support/resistance lines
When the SB session has ended, the script draws potential support/resistance lines, again, dependable on the settings.
• Previous session (any): S/R lines are fetched between current and previous session.
For example, when current session is ' AM SB Session (10 AM — 11 AM) ', then previous session is
' London Open SB (3 AM — 4 AM) ', S/R lines between these 2 sessions alone will be included.
• Previous session (similar): S/R lines are fetched between current and previous - similar - session.
For example, when current session is ' London Open SB (3 AM — 4 AM)' , only S/R lines between
current session and previous ' London Open SB (3 AM — 4 AM) ' session are included.
When a new session starts, S/R lines will be removed, except when enabling ' Keep lines (only in strict mode) '
This is not possible in ' All FVG ' or ' Only FVG's in the same direction of trend ' mode, since the chart would be cluttered.
Note that in ' All FVG ' or ' Only FVG's in the same direction of trend ' mode, both, Support/Resistance lines will be shown,
while in Strict/Super-Strict mode:
• only Support lines will be shown if a bearish FVG appears
• only Resistance lines if a bullish FVG is shown
The lines will still be drawn the the end of the SB session, when a valid FVG appears,
but the S/R lines will remain visible and keep being updated until price reaches that line.
This publication contains a "Minimum Trade Framework (mTFW)", which represents the best-case expected price delivery, this is not your actual trade entry - exit range.
• 40 ticks for index futures or indices
• 15 pips for Forex pairs.
When on ' Strict/Super-Strict ' mode, only S/R lines will be shown which are:
• higher than the lowest FVG bottom + mTFW, in a bullish scenario
• lower than the highest FVG bottom - mTFW, in a bearish scenario
When on ' All FVG/Only FVG's in the same direction of trend ' mode, or on non-Forex/Futures/Indices symbols, S/R needs to be higher/lower than SB session high/low.
🔶 SETTINGS
(Check CONCEPTS for deeper insights and explanation)
🔹 Swing settings (left): Sets the length, which will set the lookback period/sensitivity of the Zigzag patterns (which directs the trend)
🔹 Silver Bullet Session; Show SB session: show lines and labels of SB session
Labels can be disabled separately in the ' Style ' section, color is set at the ' Inputs ' section.
🔹 FVG
– Mode
• All FVG
• Only FVG's in the same direction of trend
• Strict
• Super-Strict
– Colors
– Extend: extend till last bar of SB session
🔹 Targets – support/resistance lines
– Previous session (any): S/R lines fetched between current and previous SB session
– Previous session (similar): S/R lines fetched between current and previous similar SB session
– Colors
– Keep lines (only in strict mode)
🔹 Show
– MSS ~ Session: Show Market Structure Shift , only when this happens during a SB session
– Trend: Show trend (Zigzag, colored ~ trend)
CE - Market Performance TableThe 𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 is a sophisticated market tool designed to provide valuable insights into the current market trends and the approximate current position in the Macroeconomic Regime.
Furthermore the 𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 provides the Correlation Implied Trend for the Asset on the Chart. Lastly it provides information about current "RISK ON" or "RISK OFF" periods.
Methodology:
𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 tracks the 15 underlying Stock ETF's to identify their performance and puts the combined performances together to visualize 42MACRO's GRID Equity Model.
For this it uses the below ETF's:
Dividends (SPHD)
Low Beta (SPLV)
Quality (QUAL)
Defensives (DEF)
Growth (IWF)
High Beta (SPHB)
Cyclicals (IYT, IWN)
Value (IWD)
Small Caps (IWM)
Mid Caps (IWR)
Mega Cap Growth (MGK)
Size (OEF)
Momentum (MTUM)
Large Caps (IWB)
Overall Settings:
The main time values you want to change are:
Correlation Length
- Defines the time horizon for the Correlation Table
ROC Period
- Defines the time horizon for the Performance Table
Normalization lookback
- Defines the time horizon for the Trend calculation of the ETF's
- For longer term Trends over weeks or months a length of 50 is usually pretty accurate
Visuals:
There is a variety of options to change the visual settings of what is being plotted and the two table positions and additional considerations.
Everything that is relevant in the underlying logic that can help comprehension can be visualized with these options.
Market Correlation:
The Market Correlation Table takes the Correlation of the above ETF's to the Asset on the Chart, it furthermore uses the Normalized KAMA Oscillator by IkkeOmar to analyse the current trend of every single ETF.
It then Implies a Correlation based on the Trend and the Correlation to give a probabilistically adjusted expectation for the future Chart Asset Movement. This is strengthened by taking the average of all Implied Trends.
With this the Correlation Table provides valuable insights about probabilistically likely Movement of the Asset, for Traders and Investors alike, over the defined time duration.
Market Performance:
𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 is the actual valuable part of this Indicator.
It provides valuable information about the current market environment (whether it's risk on or risk off), the rough GRID models from 42MACRO and the actual market performance.
This allows you to obtain a deeper understanding of how the market works and makes it simple to identify the actual market direction.
Utility:
The 𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 is divided in 4 Sections which are the GRID regimes:
Economic Growth:
Goldilocks
Reflation
Economic Contraction:
Inflation
Deflation
Top 5 Equity Style Factors:
Are the values green for a specific Column? If so then the market reflects the corresponding GRID behavior.
Bottom 5 Equity Style Factors:
Are the values red for a specific Column? If so then the market reflects the corresponding GRID behavior.
So if we have Goldilocks as current regime we would see green values in the Top 5 Goldilocks Cells and red values in the Bottom 5 Goldilocks Cells.
You will find that Reflation will look similar, as it is also a sign of Economic Growth.
Same is the case for the two Contraction regimes.
Price Exhaustion IndicatorThe Price Exhaustion Indicator (PE) is a powerful tool designed to identify trends weakening and strengthening in the financial markets. It combines the concepts of Average True Range (ATR), Moving Average Convergence Divergence (MACD), and Stochastic Oscillator to provide a comprehensive assessment of trend exhaustion levels. By analyzing these multiple indicators together, traders and investors can gain valuable insights into potential price reversals and long-term market highs and lows.
The aim of combining the ATR, MACD, and Stochastic Oscillator, is to provide a comprehensive analysis of trend exhaustion. The ATR component helps assess the volatility and range of price movements, while the MACD offers insights into the convergence and divergence of moving averages. The Stochastic Oscillator measures the current price in relation to its range, providing further confirmation of trend exhaustion. The exhaustion value is derived by combining the MACD, ATR, and Stochastic Oscillator. The MACD value is divided by the ATR value, and then multiplied by the Stochastic Oscillator value. This calculation results in a single exhaustion value that reflects the combined influence of these three indicators.
Application
The Price Exhaustion Indicator utilizes a unique visual representation by incorporating a gradient color scheme. The exhaustion line dynamically changes color, ranging from white when close to the midline (40) to shades of purple as it approaches points of exhaustion (overbought at 100 and oversold at -20). As the exhaustion line approaches the color purple, this represents extreme market conditions and zones of weakened trends where reversals may occur. This color gradient serves as a visual cue, allowing users to quickly gauge the strength or weakness of the prevailing trend.
To further enhance its usability, the Price Exhaustion Indicator also includes circle plots that signify potential points of trend reversion. These plots appear when the exhaustion lines cross or enter the overbought and oversold zones. Red circle plots indicate potential short entry points, suggesting a weakening trend and the possibility of a downward price reversal. Conversely, green circle plots represent potential long entry points, indicating a strengthening trend and the potential for an upward price reversal.
Traders and investors can leverage the Price Exhaustion Indicator in various ways. It can be utilized as a trend-following tool, or a mean reversion tool. When the exhaustion line approaches the overbought or oversold zones, it suggests a weakening trend and the possibility of a price reversal, helping identify potential market tops and bottoms. This can guide traders in timing their entries or exits in anticipation of a trend shift.
Utility
The Price Exhaustion Indicator is particularly useful for long-term market analysis, as it focuses on identifying long-term market highs and lows. By capturing the gradual weakening or strengthening of a trend, it assists investors in making informed decisions about portfolio allocation, trend continuation, or potential reversals.
In summary, the Price Exhaustion Indicator is a comprehensive and visually intuitive tool that combines ATR, MACD, and Stochastic Oscillator to identify trend exhaustion levels. By utilizing a gradient color scheme and circle plots, it offers traders and investors valuable insights into potential trend reversals and long-term market highs and lows. Its unique features make it a valuable addition to any trader's toolkit, providing a deeper understanding of market dynamics and assisting in decision-making processes. Please note that future performance of any trading strategy is fundamentally unknowable, and past results do not guarantee future performance.
Recursive Micro Zigzag🎲 Overview
Zigzag is basic building block for any pattern recognition algorithm. This indicator is a research-oriented tool that combines the concepts of Micro Zigzag and Recursive Zigzag to facilitate a comprehensive analysis of price patterns. This indicator focuses on deriving zigzag on multiple levels in more efficient and enhanced manner in order to support enhanced pattern recognition.
The Recursive Micro Zigzag Indicator utilises the Micro Zigzag as the foundation and applies the Recursive Zigzag technique to derive higher-level zigzags. By integrating these techniques, this indicator enables researchers to analyse price patterns at multiple levels and gain a deeper understanding of market behaviour.
🎲 Concept:
Micro Zigzag Base : The indicator utilises the Micro Zigzag concept to capture detailed price movements within each candle. It allows for the visualisation of the sequential price action within the candle, aiding in pattern recognition at a micro level.
Basic implementation of micro zigzag can be found in this link - Micro-Zigzag
Recursive Zigzag Expansion : Building upon the Micro Zigzag base, the indicator applies the Recursive Zigzag concept to derive higher-level zigzags. Through recursive analysis of the Micro Zigzag's pivots, the indicator uncovers intricate patterns and trends that may not be evident in single-level zigzags.
Earlier implementations of recursive zigzag can be found here:
Recursive Zigzag
Recursive Zigzag - Trendoscope
And the libraries
rZigzag
ZigzagMethods
The major differences in this implementation are
Micro Zigzag Base - Earlier implementation made use of standard zigzag as base whereas this implementation uses Micro Zigzag as base
Not cap on Pivot depth - Earlier implementation was limited by the depth of level 0 zigzag. In this implementation, we are trying to build the recursive algorithm progressively so that there is no cap on the depth of level 0 zigzag. But, if we go for higher levels, there is chance of program timing out due to pine limitations.
These algorithms are useful in automatically spotting patterns on the chart including Harmonic Patterns, Chart Patterns, Elliot Waves and many more.
ATR GOD Strategy by TradeSmart (PineConnector-compatible)This is a highly-customizable trading strategy made by TradeSmart, focusing mainly on ATR-based indicators and filters. The strategy is mainly intended for trading forex , and has been optimized using the Deep Backtest feature on the 2018.01.01 - 2023.06.01 interval on the EUR/USD (FXCM) 15M chart, with a Slippage value of 3, and a Commission set to 0.00004 USD per contract. The strategy is also made compatible with PineConnector , to provide an easy option to automate the strategy using a connection to MetaTrader. See tooltips for details on how to set up the bot, and check out our website for a detailed guide with images on how to automate the strategy.
The strategy was implemented using the following logic:
Entry strategy:
A total of 4 Supertrend values can be used to determine the entry logic. There is option to set up all 4 Supertrend parameters individually, as well as their potential to be used as an entry signal/or a trend filter. Long/Short entry signals will be determined based on the selected potential Supertrend entry signals, and filtered based on them being in an uptrend/downtrend (also available for setup). Please use the provided tooltips for each setup to see every detail.
Exit strategy:
4 different types of Stop Losses are available: ATR-based/Candle Low/High Based/Percentage Based/Pip Based. Additionally, Force exiting can also be applied, where there is option to set up 4 custom sessions, and exits will happen after the session has closed.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Plot SL/TP lines: false by default, Checking this option will result in the TP and SL lines to be plotted on the chart.
Supertrend 1-4:
All the parameters of the Supertrends can be set up here, as well as their individual role in the entry logic.
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 100 by default
ATR Smoothing (of the SL): RMA/SMMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Candle Lookback (of the SL): 50 by default
Percentage Based Stop Loss: false by default, Set the stop loss to current price - % of current price (long) or price + % of current price (short).
Percentage (of the SL): 0.3 by default
Pip Based Stop Loss: Set the stop loss to current price - x pips (long) or price + x pips (short). Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Pip (of the SL): 10 by default
Base Risk Multiplier: 4.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 1.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exiting:
4 total Force exit on custom session close options: none applied by default. If enabled, trades will close automatically after the set session is closed (on next candle's open).
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 10 by default
Order Type: Capital Percentage by default, allows adjustment on how the position size is calculated: Cash: only the set cash amount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade
ATR Limiter:
Use ATR Limiter: true by default, Only enter into any position (long/short) if ATR value is higher than the Low Boundary and lower than the High Boundary.
ATR Limiter Length: 50 by default
ATR Limiter Smoothing: RMA/SMMA by default
High Boundary: 1000 by default
Low Boundary: 0.0003 by default
MA based calculation: ATR value under MA by default, If not Unspecified, an MA is calculated with the ATR value as source. Only enter into position (long/short) if ATR value is higher/lower than the MA.
MA Type: RMA/SMMA by default
MA Length: 400 by default
Waddah Attar Filter:
Explosion/Deadzone relation: Not specified by default, Explosion over Deadzone: trades will only happen if the explosion line is over the deadzone line; Explosion under Deadzone: trades will only happen if the explosion line is under the deadzone line; Not specified: the opening of trades will not be based on the relation between the explosion and deadzone lines.
Limit trades based on trends: Not specified by default, Strong Trends: only enter long if the WA bar is colored green (there is an uptrend and the current bar is higher then the previous); only enter short if the WA bar is colored red (there is a downtrend and the current bar is higher then the previous); Soft Trends: only enter long if the WA bar is colored lime (there is an uptrend and the current bar is lower then the previous); only enter short if the WA bar is colored orange (there is a downtrend and the current bar is lower then the previous); All Trends: only enter long if the WA bar is colored green or lime (there is an uptrend); only enter short if the WA bar is colored red or orange (there is a downtrend); Not specified: the color of the WA bar (trend) is not relevant when considering entries.
WA bar value: Not specified by default, Over Explosion and Deadzone: only enter trades when the WA bar value is over the Explosion and Deadzone lines; Not specified: the relation between the explosion/deadzone lines to the value of the WA bar will not be used to filter opening trades.
Sensitivity: 150 by default
Fast MA Type: SMA by default
Fast MA Length: 10 by default
Slow MA Type: SMA
Slow MA Length: 20 by default
Channel MA Type: EMA by default
BB Channel Length: 20 by default
BB Stdev Multiplier: 2 by default
Trend Filter:
Use long trend filter 1: false by default, Only enter long if price is above Long MA.
Show long trend filter 1: false by default, Plot the selected MA on the chart.
TF1 - MA Type: EMA by default
TF1 - MA Length: 120 by default
TF1 - MA Source: close by default
Use short trend filter 1: false by default, Only enter long if price is above Long MA.
Show short trend filter 1: false by default, Plot the selected MA on the chart.
TF2 - MA Type: EMA by default
TF2 - MA Length: 120 by default
TF2 - MA Source: close by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: RMA/SMMA by default
MA Length: 200 by default
Date Range Limiter:
Limit Between Dates: false by default
Start Date: Jan 01 2023 00:00:00 by default
End Date: Jun 24 2023 00:00:00 by default
Session Limiter:
Show session plots: false by default, show market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Trading Time:
Limit Trading Time: true by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 123567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 123456 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 1800-2000 by default, hours between which the trades can happen. The time is always in the exchange's timezone
All other options are also disabled by default
PineConnector Automation:
Use PineConnector Automation: false by default, In order for the connection to MetaTrader to work, you will need do perform prerequisite steps, you can follow our full guide at our website, or refer to the official PineConnector Documentation. To set up PineConnector Automation on the TradingView side, you will need to do the following:
1. Fill out the License ID field with your PineConnector License ID;
2. Fill out the Risk (trading volume) with the desired volume to be traded in each trade (the meaning of this value depends on the EA settings in Metatrader. Follow the detailed guide for additional information);
3. After filling out the fields, you need to enable the 'Use PineConnector Automation' option (check the box in the strategy settings);
4. Check if the chart has updated and you can see the appropriate order comments on your chart;
5. Create an alert with the strategy selected as Condition, and the Message as {{strategy.order.comment}} (should be there by default);
6. Enable the Webhook URL in the Notifications section, set it as the official PineConnector webhook address and enjoy your connection with MetaTrader.
License ID: 60123456789 by default
Risk (trading volume): 1 by default
NOTE! Fine-tuning/re-optimization is highly recommended when using other asset/timeframe combinations.
FalconRed 5 EMA Indicator (Powerofstocks)Improved version:
This indicator is based on Subhashish Pani's "Power of Stocks" 5 EMA Strategy, which aims to identify potential buying and selling opportunities in the market. The indicator plots the 5 EMA (Exponential Moving Average) and generates Buy/Sell signals with corresponding Target and Stoploss levels.
Subhashish Pani's 5 EMA Strategy is a straightforward approach. For intraday trading, a 5-minute timeframe is recommended for selling. In this strategy, you can choose to sell futures, sell calls, or buy puts as part of your selling strategy. The goal is to capture market tops by selling at the peak, anticipating a reversal for profitable trades. Although this strategy may result in frequent stop losses, they are typically small, while the minimum target should be at least three times the risk taken. By staying aligned with the trend, significant profits can be achieved. Subhashish Pani claims that this strategy has a 60% success rate.
Strategy for Selling (Short Future/Call/Stock or Buy Put):
1. When a candle completely closes above the 5 EMA (with no part of the candle touching the 5 EMA), it is considered an Alert Candle.
2. If the next candle is also entirely above the 5 EMA and does not break the low of the previous Alert Candle, ignore the previous Alert Candle and consider the new candle as the new Alert Candle.
3. Continue shifting the Alert Candle in this manner. However, when the next candle breaks the low of the Alert Candle, take a short trade (e.g., short futures, calls, stocks, or buy puts).
4. Set the stop loss above the high of the Alert Candle, and the minimum target should be 1:3 (at least three times the stop loss).
Strategy for Buying (Buy Future/Call/Stock or Sell Put):
1. When a candle completely closes below the 5 EMA (with no part of the candle touching the 5 EMA), it is considered an Alert Candle.
2. If the next candle is also entirely below the 5 EMA and does not break the high of the previous Alert Candle, ignore the previous Alert Candle and consider the new candle as the new Alert Candle.
3. Continue shifting the Alert Candle in this manner. However, when the next candle breaks the high of the Alert Candle, take a long trade (e.g., buy futures, calls, stocks, or sell puts).
4. Set the stop loss below the low of the Alert Candle, and the minimum target should be 1:3 (at least three times the stop loss).
Buy/Sell with Additional Conditions:
An additional condition is added to the buying/selling strategy:
1. Check if the closing price of the current candle is lower than the closing price of the Alert Candle for selling, or higher than the closing price of the Alert Candle for buying.
- This condition aims to filter out false moves, potentially preventing entering trades based on temporary fluctuations. However, it may cause you to miss out on significant moves, as you will enter trades after the candle closes, rather than at the breakout point.
Note: According to Subhashish Pani, the recommended timeframe for intraday buying is 15 minutes. However, this strategy can also be applied to positional/swing trading. If used on a monthly timeframe, it can be beneficial for long-term investing as well. The rules remain the same for all types of trades and timeframes.
If you need a deeper understanding of this strategy, you can search for "Subhashish Pani's (Power of Stocks) 5 EMA Strategy" on YouTube for further explanations.
Note: This strategy is not limited to intraday trading and can be applied to positional/swing
itradesize /\ Overnight Session & Silver BulletOvernight Session & Silver Bullet indicator
The indicator can be divided into two separate stuff:
ONS ( Overnight Session ) based on TCM’s ( TheCurrencyMerchant ) theory and Silver Bullet based on what ICT ( InnerCircleTrader ) is teaching to us.
Overnight Session
• ONS will be always based on Chicago 4am to 8am time according to TCM’s CME teaching.
The indicator has the option to show TSO ( Today’s session only ) which is good to have the chart not messed up by it. At this time when it comes to backtesting just turn this off to have the past ONS and SB ranges showed up on your chart.
• Mid line at the ONS range is useful to have as you are able to decide wether price is in a premium or a discount under the ONS.
If Im a buyer target is above the range, if Im a seller target is below the range.
• You are also able to have SD ( Standard Deviation ) lines for price projections. In the variety of TCM’s videos you are able to have a deeper knowledge.
• You can also extend Today’s ONS lines to the very end of the chart which could make an easier looking on the levels you eyeing with.
Silver Bullet
It’s based on New York time as ICT ( Inner Circle Trader ) is always teaching to us that we should use New York time, every time when it comes to his concepts.
Silver Bullets are always be there aiming of an opposing liquidity pool. They are working even on choppy days.
Silver Bullet hours:
• 03:00 - 04:00am NY Time
• 10:00 - 11:00am NY Time
• 02:00 - 03:00pm NY Time
SB highlighted areas could be shown as a box or a range according to your taste, with or without Start/End lines.
Both of them ca be used to form trades.
You should dig yourself into Silver Bullet ( InnerCircleTrader ) and Overnight Session ( TheCurrencyMerchant ) teachings before the use of the indicator.
Simple setups
• Silver Bullet
Look 20-30 minutes before any SB where the Buy or Sell program has started.
Where the first 1m FVG ( Fair Value Gap ) appears under the range, enter the trade.
Expect only a 5 handle move as a beginner.
1m chart is a must for these kind of FVG entries. ( 30s , 15s can also be used )
• ONS
Price is trading aggressively out of the range to take liquidity.
Once price grabbed liquidity that candle on the 3-5m could considered as on order block for the further movement.
If you are trading in the range, then the opposite side can be the target, if its out of the range and trading one sided, then use standard deviations as 0.5 is a minimum target.
[DisDev] D-I-Y Gridbot🟩 This script is a “do-it-yourself” Grid Bot Simulator, used for visualizing support and resistance levels. Prices are divided into grids, or trade zones, that will trigger signals each time a new zone is entered. During ranging markets, each transaction is followed by a “take profit.” As the market starts to trend, transactions are stacked (compare to DCA ), until the market consolidates. No signals are triggered above the upper gridline or below the lower gridline. Unlike the previous version, all grids may be adjusted in real-time by dragging the gridlines up and down to the desired support and resistance levels.
When adding the indicator to a new chart, you must choose six grid levels by clicking on the desired support or resistance price. You can change all of these levels at any time directly on the chart.
⚡ OVERVIEW ⚡
The D-I-Y Gridbot is an interactive tool designed for visualizing support and resistance levels. As a continuation of the original Gridbot Simulator , which has received significant recognition on TradingView, earning over 4000 boosts and an Editor's Pick status. This tool serves not only as an evolved version of its predecessor, but also as an open-source template for developing future gridbots. It aims to foster discussions and facilitate innovations around grid-trading strategies.
One of the new features of this gridbot is the real-time adjustability of all gridlines. Users can move these lines up and down to set their desired support and resistance levels in response to changing market conditions. Additionally, the D-I-Y Gridbot is compatible with multiple timeframes and can be used on most TradingView charts.
Drag gridlines up or down to desired price level.
Key Features 🔑
All gridlines are adjustable in real-time, directly on the chart
Signals can be filtered by a customizable moving average or by VWAP
Customizable support and resistance levels
Potentially increases profitability in ranging markets
Benefits 💸
Customizable Support and Resistance Levels : The D-I-Y Gridbot allows users to set their preferred support and resistance levels, which can be changed at any time directly on the chart. This provides users with the ability to customize their trading parameters based on their strategy and risk tolerance.
Various Trading Strategies : The D-I-Y Gridbot supports various trading strategies, including Mean Reversion, Ranging Markets, and Dollar-cost averaging (DCA). This allows users to capitalize on price reversals, execute buy and sell orders at predetermined levels, and buy more of an asset as the price falls, respectively.
Multi-Timeframe and Versatility : The D-I-Y Gridbot is compatible with multiple timeframes and can be used on any TradingView chart.
Experimental and Educational : The D-I-Y Gridbot is considered a proof-of-concept tool that is both experimental and educational. This can provide traders with a deeper understanding of grid trading strategies and the ability to experiment with different trading parameters and strategies.
⚙️ CONFIGURATION & SETTINGS ⚙️
Inputs 🔧
Trigger : Candle location to trigger the signal. "Wick" will use either high or low, depending on the signal direction. "Close" will use the close price. “MA” will use the selected moving average or VWAP.
Confirmation : Market direction to confirm the candle trigger. "Reverse" will confirm the signal when the price crosses back over the trigger. "Breakout" will confirm when the price breaks out of the trigger.
Number of Support/Resistance zones : 1 = Only Top Grid is Support/Only Bottom Grid is Resistance. 2 = Top two grids are Resistance/Bottom two grids are Support. 3 = Top three grids are Resistance/Bottom three grids are Support
MA Type : Exponential Moving Average (EMA), Hull Moving Average (HMA), Simple Moving Average (SMA), Triple Exponential Moving Average (TEMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP)
MA Filter : Use Moving Average as a reversion filter for signals. When enabled, no buys when above MA, no sells when below. Use in conjunction with S/R zones to reduce false signals.
Allow Repeat Signals . When enabled, signals will reset when nearest gridline is triggered. When disabled, only one signal will be triggered per gridline.
Line/Fill colors
Gridlines . Adjusts gridline prices manually.
Left : Trigger = Wick. Confirm = Breakout. Buys are signaled when LOW breaks below gridline. Sells are triggered when HIGH breaks above gridline.
Right : Trigger = Close. Confirm = Breakout. Buys are signaled when the candle CLOSES below the gridline. Sells are triggered when the candle CLOSES above the gridline.
Left : Confirm=Breakout. Signals on breaking through the next gridline.
Right : Confirm=Reverse. Signals only when crossing back from the gridline.
S/R Zones=1. Upper gridline is Resistance / Lower is Support. Middle 4 are neutral.
S/R Zones = 3. Upper three gridlines are Resistance / Lower three are Support
Notes:
If gridlines are dragged out of order on a live chart, they will auto-sort into the correct order.
Price levels may be entered in settings, or adjusted in real-time directly on the chart.
When changing symbols, remember to adjust the gridlines to accommodate the new symbol.
Alerts 🔔
Users can set alerts based on their chosen parameters for triggers, confirmations, number of support/resistance zones, and smoothing type, enabling precise control over alert conditions.
💡 USAGE & STRATEGY 💡
Trading Strategies 📈
Mean Reversion: The script can be used to capitalize on price reversals back to the mean.
Ranging Markets: The script excels in ranging markets, executing buy and sell orders at predetermined levels.
Dollar-cost averaging (DCA): The script can be used to execute DCA orders, buying more of an asset as the price falls, and lowering the average cost per unit.
Timeframes and Symbols ⌚
Multi-Timeframe: The indicator is compatible with multiple timeframes.
Versatile: Can be used on any crypto trading pair on TradingView.
🤖 DETAILS & METHODOLOGY 🤖
Algorithm and Calculation 🛡️
Grids are set and adjusted when loading the indicator on the chart and may be customized anytime afterward by clicking and dragging the gridlines on the chart.
Gridlines are updated, sorted, and stored in a float array.
Signals are calculated based on candle trigger, market direction, and previous price level.
📚 ADDITIONAL RESOURCES 📚
Chart Examples 📊
S/R Zones = 3: Three Support and Three Resistance. Filter = 50-period Triple Exponential Moving Average (TEMA)
S/R Zones = 1: One Support, One Resistance, and Four Neutral Zones. Support Zones: Buys only. Resistance Zones: Sells only. Neutral Zones: Grid-dependent
When MA filter is enabled, Buys are only triggered below Moving Average, and Sells are only triggered above.
Trigger = Wick. Confirmation = Breakout. Buys are signaled when Low breaks above the next grid level. Sells are signaled when High breaks below the next grid level.
🚀 CONCLUSION 🚀
The D-I-Y Gridbot is a proof-of-concept, emphasizing its experimental and educational nature. In future versions, we will aim to incorporate concepts such as auto-adjusting grids and angled grids for trending markets. The script is designed to evolve through user feedback and suggestions, shaping its future iterations.
Credit: This is a continuation of the Gridbot series by xxattaxx-DisDev . Explicit permission was granted by user xxattaxx-disdev to re-use all Gridbot code and all materials without restrictions.
⚠️ DISCLAIMER ⚠️
This indicator is a proof-of-concept and is considered experimental and educational. When gridlines are drawn in hindsight, signals appear to be predictive and valid. Future results may always vary when the trend direction changes. Comments and suggestions are encouraged.
This indicator is provided as a tool for traders and should not be used as the sole basis for making trading decisions. Always conduct your own research and consider your risk tolerance before entering any trades.
Volume Profile Bar-Magnified Order Blocks [MyTradingCoder]Introducing "Volume Profile Bar-Magnified Order Blocks", an innovative and unique trading indicator designed to provide traders with a comprehensive understanding of market dynamics. This tool takes the concept of identifying order blocks on your chart and elevates it by integrating a detailed volume profile within each order block zone.
Unlike standard order block indicators, Volume Profile Bar-Magnified Order Blocks pulls data from lower timeframe bars and assigns it to various segments of the order block. By providing this volume profile inside the order block, the indicator supplies a deeper, multi-dimensional view of market activity that can enhance your trading decisions.
Crucially, users have the ability to fine-tune the detection of order blocks. This is made possible through a single input setting called "Tuning". This integer value allows you to control the significance and frequency of the order blocks. Higher numbers will produce more significant order blocks, though they will appear less frequently. Lower numbers, on the other hand, will yield less significant order blocks, but they will occur more often. This enables you to adjust the sensitivity of the indicator according to your specific trading strategy and style.
Key Settings:
Number of Segments: Customize the level of detail in your volume profile by selecting the number of segments you want inside each order block.
Tuning: Adjust the sensitivity of order block detection to align with your trading strategy. Higher values produce more significant but less frequent order blocks, while lower values yield less significant but more frequent order blocks.
Color Inputs: Personalize the look of your chart by selecting the colors for various elements of the indicator. This ensures a seamless integration with your current chart aesthetics and improves visual clarity.
Here is a s creenshot that beautifully demonstrates the power of this indicator. You'll see how the price rejects perfectly off the highest volume segment in an order block, showcasing the indicator's potential for pinpointing high-impact price levels.
While Volume Profile Bar-Magnified Order Blocks offers many unique features, it should be used in conjunction with other indicators and forms of analysis for a complete trading strategy. As with all tools, it does not guarantee profitable trades but is intended to give traders more information to base their decisions on. Use it to complement your existing analysis and enhance your understanding of market behavior.
Experience a new level of clarity in your trading with Volume Profile Bar-Magnified Order Blocks - an indicator that goes beyond the surface to help you navigate the markets more effectively.
Logarithmic VolatilityIntroducing the Logarithmic Volatility Indicator , an innovative trading indicator designed especially for trading in low volatility markets. This powerful indicator is aimed at traders of all levels, from beginners to experts, and is based on fundamental concepts of mathematics and statistics applied to the financial market. Its main objective is to provide you with a better understanding of price movements and help you make more accurate investment decisions, especially in low volatility environments.
The purpose of this indicator is to find a volatility estimator that depends on the difference between High and Low, taking into account that this measure is directly proportional to volatility. A first result was obtained by Parkinson (1980) which was later improved by Garman and Klass (1980), who improved the estimator by obtaining one of minimum variance. It is the simplified version (and recommended by them) of the Garman and Klass estimator that is used to calculate the daily volatility of the asset.
The Logarithmic Volatility Indicator is a unique smoothing indicator that uses logarithms and volatility calculation of the opening, high, low and closing prices. It combines these elements to obtain an accurate representation of market volatility in situations where volatility is low.
Features
This indicator has several outstanding features designed to enhance your trading analysis in low volatility environments:
• Intraday Volatility Calculation: This innovative feature allows you to view market volatility levels in real time, providing a clear view of market fluctuations even when volatility is low.
• EMA (Exponential Moving Average) Multi Length: The indicator incorporates three different EMA lengths (Fast, Medium and Slow). This gives you a deeper and more detailed analysis of market volatility, allowing you to detect subtle changes in volatility and make more accurate predictions.
• Visual color change: The indicator uses a color change between green and red to facilitate quick interpretation of the market. Green indicates a decrease in volatility, while red indicates an increase in volatility. This feature helps you quickly identify changes in market dynamics even in periods of low volatility.
• Histogram display: In addition to the colors, the indicator can also be displayed as a histogram. This intuitive representation allows you to visually observe changes in volatility over time and detect emerging patterns or trends in markets with low volatility.
Settings
The Logarithmic Volatility Indicator allows you to customize various settings to suit your specific trading needs:
• Slow EMA length: you can select the length of the slow exponential moving average according to your preferences and trading strategies.
• Fast EMA length: Similarly, you can choose the length of the fast exponential moving average to suit your trading style.
• Average EMA length: In addition to the two EMA lengths above, this indicator offers a third EMA length for even more detailed analysis. This additional feature is especially useful when trading in markets with low volatility, as it allows you to capture subtle changes in market dynamics.
Trading
The Logarithmic Volatility Indicator is designed not only to provide you with essential information about market volatility, but also to give you clear indications on when to trade. Here's how you can use the indicator's colors to guide your trading decisions:
- Long Trading: When the fast EMA has a smaller value than the slow EMA, the indicator will change to green. This is a signal to enter a long trade. That is, you can consider buying at this point, as an increase in price is anticipated due to decreasing volatility. With volatility declining, there is a greater likelihood that the price will continue in the current direction rather than fluctuate erratically.
- b]Short Trading: On the other hand, when the fast EMA has a higher value than the slow EMA, the indicator will turn red. This is a signal to enter a short trade. In other words, you may consider selling at this point, as a decline in price is anticipated due to rising volatility. With volatility on the rise, there is a greater risk of steeper price fluctuations.
It is important to remember that, as with any indicator, the Logarithmic Volatility Indicator does not guarantee 100% success. You should always use this indicator in combination with other analytical tools and good risk management. This tool provides you with an overview of market volatility and can help you identify trading opportunities in low volatility markets, but the final decision on when and how to trade should always be based on your own analysis and judgment.
In conclusion, the Logarithmic Volatility Indicator is an essential trading tool that every trader should have in their arsenal, especially when facing low volatility markets. With its accurate volatility calculation and easy-to-understand visualization, it will help you improve your trading decisions and maximize your profits even in situations where price movements are less pronounced. Try it today and take advantage of its efficiency in low volatility environments!
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Presentamos el Indicador de Volatilidad Logarítmica , un innovador indicador de trading diseñado especialmente para operar en mercados con baja volatilidad. Este poderoso indicador está dirigido a traders de todos los niveles, desde principiantes hasta expertos, y se basa en conceptos fundamentales de matemáticas y estadísticas aplicadas al mercado financiero. Su objetivo principal es proporcionarte una mejor comprensión de los movimientos de precios y ayudarte a tomar decisiones de inversión más precisas, especialmente en entornos de baja volatilidad.
Con este indicador se pretende encontrar un estimador de la volatilidad que dependa de la diferencia entre el High y el Low, teniendo en cuenta que esta medida es directamente proporcional a la volatilidad. Un primer resultado fue obtenido por Parkinson (1980) que posteriormente fue mejorado por Garman y Klass (1980), que mejoraron el estimador obteniendo uno de varianza mínima. Es la versión simplificada (y recomendada por ellos mismos) del estimador de Garman y Klass la que se utiliza para calcular la volatilidad diaria del activo.
El Indicador de Volatilidad Logarítmica es un indicador de suavizado único que utiliza logaritmos y el cálculo de la volatilidad de los precios de apertura, máximo, mínimo y cierre. Combina estos elementos para obtener una representación precisa de la volatilidad del mercado en situaciones donde la volatilidad es baja.
Características
Este indicador cuenta con varias características sobresalientes diseñadas para mejorar tu análisis de trading en entornos de baja volatilidad:
• Cálculo de la volatilidad intradía: Esta función innovadora te permite ver los niveles de volatilidad del mercado en tiempo real, lo que brinda una visión clara de las fluctuaciones del mercado incluso cuando la volatilidad es baja.
• EMA (Exponential Moving Average) Multi Longitud: El indicador incorpora tres longitudes diferentes de EMA (Rápida, Media y Lenta). Esto te proporciona un análisis más profundo y detallado de la volatilidad del mercado, permitiéndote detectar cambios sutiles en la volatilidad y realizar predicciones más precisas.
• Cambio de color visual: El indicador utiliza un cambio de color entre verde y rojo para facilitar la interpretación rápida del mercado. El verde indica una disminución de la volatilidad, mientras que el rojo indica un aumento de la volatilidad. Esta característica te ayuda a identificar rápidamente cambios en la dinámica del mercado incluso en períodos de baja volatilidad.
• Visualización Histograma: Además de los colores, el indicador también se puede visualizar como un histograma. Esta representación intuitiva te permite observar de manera visual los cambios en la volatilidad a lo largo del tiempo y detectar patrones o tendencias emergentes en mercados con baja volatilidad.
Ajustes
El Indicador de Volatilidad Logarítmica te permite personalizar varios ajustes para adaptarlos a tus necesidades de trading específicas:
• Longitud de EMA lenta: Puedes seleccionar la longitud de la media móvil exponencial lenta según tus preferencias y estrategias de trading.
• Longitud de EMA rápida: De manera similar, puedes elegir la longitud de la media móvil exponencial rápida para ajustarla a tu estilo de trading.
• Longitud de EMA media: Además de las dos longitudes de EMA anteriores, este indicador ofrece una tercera longitud de EMA para un análisis aún más detallado. Esta característica adicional es especialmente útil cuando operas en mercados con baja volatilidad, ya que te permite capturar cambios sutiles en la dinámica del mercado.
Operativa
El Indicador de Volatilidad Logarítmica está diseñado no solo para brindarte información esencial sobre la volatilidad del mercado, sino también para ofrecerte indicaciones claras sobre cuándo operar. Aquí te explicamos cómo puedes utilizar los colores del indicador para guiar tus decisiones de trading:
• Operativa en Largo: Cuando la EMA rápida tiene un valor más pequeño que la EMA lenta, el indicador cambiará a color verde. Esta es una señal para entrar en una operación en largo. Es decir, puedes considerar comprar en este punto, ya que se anticipa un aumento en el precio debido a la disminución de la volatilidad. Con la volatilidad en descenso, existe una mayor probabilidad de que el precio continúe en la dirección actual en lugar de fluctuar erráticamente.
• Operativa en Corto: Por otro lado, cuando la EMA rápida tiene un valor mayor que la EMA lenta, el indicador se tornará rojo. Esta es una señal para entrar en una operación en corto. En otras palabras, puedes considerar vender en este punto, ya que se anticipa una disminución en el precio debido al aumento de la volatilidad. Con la volatilidad en ascenso, existe un mayor riesgo de fluctuaciones de precio más pronunciadas.
Es importante recordar que, como con cualquier indicador, el Indicador de Volatilidad Logarítmica no garantiza un éxito del 100%. Siempre debes usar este indicador en combinación con otras herramientas de análisis y una buena gestión de riesgos. Esta herramienta te proporciona una visión general de la volatilidad del mercado y puede ayudarte a identificar oportunidades de trading en mercados con baja volatilidad, pero la decisión final de cuándo y cómo operar siempre deberá basarse en tu propio análisis y juicio.
En conclusión, el Indicador de Volatilidad Logarítmica es una herramienta de trading esencial que todo trader debe tener en su arsenal, especialmente cuando se enfrenta a mercados con baja volatilidad. Con su cálculo preciso de la volatilidad y su visualización fácil de entender, te ayudará a mejorar tus decisiones de trading y a maximizar tus ganancias incluso en situaciones donde los movimientos de precios son menos pronunciados. ¡Pruébalo hoy mismo y aprovecha su eficiencia en entornos de baja volatilidad!
Composite MomentumComposite Momentum Indicator - Enhancing Trading Insights with RSI & Williams %R
The Composite Momentum Indicator is a powerful technical tool that combines the Relative Strength Index (RSI) and Williams %R indicators from TradingView. This unique composite indicator offers enhanced insights into market momentum and provides traders with a comprehensive perspective on price movements. By leveraging the strengths of both RSI and Williams %R, the Composite Momentum Indicator offers distinct advantages over a simple RSI calculation.
1. Comprehensive Momentum Analysis:
The Composite Momentum Indicator integrates the RSI and Williams %R indicators to provide a comprehensive analysis of market momentum. It takes into account both the strength of recent price gains and losses (RSI) and the relationship between the current closing price and the highest-high and lowest-low price range (Williams %R). By combining these two momentum indicators, traders gain a more holistic view of market conditions.
2. Increased Accuracy:
While the RSI is widely used for measuring overbought and oversold conditions, it can sometimes generate false signals in certain market environments. The Composite Momentum Indicator addresses this limitation by incorporating the Williams %R, which focuses on the price range and can offer more accurate signals in volatile market conditions. This combination enhances the accuracy of momentum analysis, allowing traders to make more informed trading decisions.
3. Improved Timing of Reversals:
One of the key advantages of the Composite Momentum Indicator is its ability to provide improved timing for trend reversals. By incorporating both RSI and Williams %R, traders can identify potential turning points more effectively. The Composite Momentum Indicator offers an early warning system for identifying overbought and oversold conditions and potential trend shifts, helping traders seize opportunities with better timing.
4. Enhanced Divergence Analysis:
Divergence analysis is a popular technique among traders, and the Composite Momentum Indicator strengthens this analysis further. By comparing the RSI and Williams %R within the composite calculation, traders can identify divergences between the two indicators more easily. Divergence between the RSI and Williams %R can signal potential trend reversals or the weakening of an existing trend, providing valuable insights for traders.
5. Customizable Moving Average:
The Composite Momentum Indicator also features a customizable moving average (MA), allowing traders to further fine-tune their analysis. By incorporating the MA, traders can smooth out the composite momentum line and identify longer-term trends. This additional layer of customization enhances the versatility of the indicator, catering to various trading styles and timeframes.
The Composite Momentum Indicator, developed using the popular TradingView indicators RSI and Williams %R, offers a powerful tool for comprehensive momentum analysis. By combining the strengths of both indicators, traders can gain deeper insights into market conditions, improve accuracy, enhance timing for reversals, and leverage divergence analysis. With the added customization of the moving average, the Composite Momentum Indicator provides traders with a versatile and effective tool to make more informed trading decisions.
T3 JMA KAMA VWMAEnhancing Trading Performance with T3 JMA KAMA VWMA Indicator
Introduction
In the dynamic world of trading, staying ahead of market trends and capitalizing on volume-driven opportunities can greatly influence trading performance. To address this, we have developed the T3 JMA KAMA VWMA Indicator, an innovative tool that modifies the traditional Volume Weighted Moving Average (VWMA) formula to increase responsiveness and exploit high-volume market conditions for optimal position entry. This article delves into the idea behind this modification and how it can benefit traders seeking to gain an edge in the market.
The Idea Behind the Modification
The core concept behind modifying the VWMA formula is to leverage more responsive moving averages (MAs) that align with high-volume market activity. Traditional VWMA utilizes the Simple Moving Average (SMA) as the basis for calculating the weighted average. While the SMA is effective in providing a smoothed perspective of price movements, it may lack the desired responsiveness to capitalize on short-term volume-driven opportunities.
To address this limitation, our T3 JMA KAMA VWMA Indicator incorporates three advanced moving averages: T3, JMA, and KAMA. These MAs offer enhanced responsiveness, allowing traders to react swiftly to changing market conditions influenced by volume.
T3 (T3 New and T3 Normal):
The T3 moving average, one of the components of our indicator, applies a proprietary algorithm that provides smoother and more responsive trend signals. By utilizing T3, we ensure that the VWMA calculation aligns with the dynamic nature of high-volume markets, enabling traders to capture price movements accurately.
JMA (Jurik Moving Average):
The JMA component further enhances the indicator's responsiveness by incorporating phase shifting and power adjustment. This adaptive approach ensures that the moving average remains sensitive to changes in volume and price dynamics. As a result, traders can identify turning points and anticipate potential trend reversals, precisely timing their position entries.
KAMA (Kaufman's Adaptive Moving Average):
KAMA is an adaptive moving average designed to dynamically adjust its sensitivity based on market conditions. By incorporating KAMA into our VWMA modification, we ensure that the moving average adapts to varying volume levels and captures the essence of volume-driven price movements. Traders can confidently enter positions during periods of high trading volume, aligning their strategies with market activity.
Benefits and Usage
The modified T3 JMA KAMA VWMA Indicator offers several advantages to traders looking to exploit high-volume market conditions for position entry:
Increased Responsiveness: By incorporating more responsive moving averages, the indicator enables traders to react quickly to changes in volume and capture short-term opportunities more effectively.
Enhanced Entry Timing: The modified VWMA aligns with high-volume periods, allowing traders to enter positions precisely during price movements influenced by significant trading activity.
Improved Accuracy: The combination of T3, JMA, and KAMA within the VWMA formula enhances the accuracy of trend identification, reversals, and overall market analysis.
Comprehensive Market Insights: The T3 JMA KAMA VWMA Indicator provides a holistic view of market conditions by considering both price and volume dynamics. This comprehensive perspective helps traders make informed decisions.
Analysis and Interpretation
The modified VWMA formula with T3, JMA, and KAMA offers traders a valuable tool for analyzing volume-driven market conditions. By incorporating these advanced moving averages into the VWMA calculation, the indicator becomes more responsive to changes in volume, potentially providing deeper insights into price movements.
When analyzing the modified VWMA, it is essential to consider the following points:
Identifying High-Volume Periods:
The modified VWMA is designed to capture price movements during high-volume periods. Traders can use this indicator to identify potential market trends and determine whether significant trading activity is driving price action. By focusing on these periods, traders may gain a better understanding of the market sentiment and adjust their strategies accordingly.
Confirmation of Trend Strength:
The modified VWMA can serve as a confirmation tool for assessing the strength of a trend. When the VWMA line aligns with the overall trend direction, it suggests that the current price movement is supported by volume. This confirmation can provide traders with additional confidence in their analysis and help them make more informed trading decisions.
Potential Entry and Exit Points:
One of the primary purposes of the modified VWMA is to assist traders in identifying potential entry and exit points. By capturing volume-driven price movements, the indicator can highlight areas where market participants are actively participating, indicating potential opportunities for opening or closing positions. Traders can use this information in conjunction with other technical analysis tools to develop comprehensive trading strategies.
Interpretation of Angle and Gradient:
The modified VWMA incorporates an angle calculation and color gradient to further enhance interpretation. The angle of the VWMA line represents the slope of the indicator, providing insights into the momentum of price movements. A steep angle indicates strong momentum, while a shallow angle suggests a slowdown. The color gradient helps visualize this angle, with green indicating bullish momentum and purple indicating bearish momentum.
Conclusion
By modifying the VWMA formula to incorporate the T3, JMA, and KAMA moving averages, the T3 JMA KAMA VWMA Indicator offers traders an innovative tool to exploit high-volume market conditions for optimal position entry. This modification enhances responsiveness, improves timing, and provides comprehensive market insights.
Enjoy checking it out!
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Credits to:
◾ @cheatcountry – Hann Window Smoothing
◾ @loxx – T3
◾ @everget – JMA
US Market SentimentThe "US Market Sentiment" indicator is designed to provide insights into the sentiment of the US market. It is based on the calculation of an oscillator using data from the High Yield Ratio. This indicator can be helpful in assessing the overall sentiment and potential market trends.
Key Features:
Trend Direction: The indicator helps identify the general trend direction of market sentiment. Positive values indicate a bullish sentiment, while negative values indicate a bearish sentiment. Traders and investors can use this information to understand the prevailing market sentiment.
Overbought and Oversold Levels: The indicator can highlight overbought and oversold conditions in the market. When the oscillator reaches high positive levels, it suggests excessive optimism and a potential downside correction. Conversely, high negative levels indicate excessive pessimism and the possibility of an upside rebound.
Divergence Analysis: The indicator can reveal divergences between the sentiment oscillator and price movements. Divergences occur when the price reaches new highs or lows, but the sentiment oscillator fails to confirm the move. This can signal a potential trend reversal or weakening of the current trend.
Confirmation of Trading Signals: The "US Market Sentiment" indicator can be used to confirm other trading signals or indicators. For instance, if a momentum indicator generates a bullish signal, a positive reversal in the sentiment oscillator can provide additional confirmation for the trade.
Usage and Interpretation:
Positive values of the "US Market Sentiment" indicate a bullish sentiment, suggesting potential buying opportunities.
Negative values suggest a bearish sentiment, indicating potential selling or shorting opportunities.
Extreme positive or negative values may signal overbought or oversold conditions, respectively, and could precede a market reversal.
Divergences between the sentiment oscillator and price trends may suggest a potential change in the current market direction.
Traders and investors can combine the "US Market Sentiment" indicator with other technical analysis tools to enhance their decision-making process and gain deeper insights into the US market sentiment.
Step RSI [Loxx]Enhanced Moving Average Calculation with Stepped Moving Average and the Advantages over Regular RSI
Technical analysis plays a crucial role in understanding and predicting market trends. One popular indicator used by traders and analysts is the Relative Strength Index (RSI). However, an enhanced approach called Stepped Moving Average, in combination with the Slow RSI function, offers several advantages over regular RSI calculations.
Stepped Moving Average and Moving Averages:
The Stepped Moving Average function serves as a crucial component in the calculation of moving averages. Moving averages smooth out price data over a specific period to identify trends and potential trading signals. By employing the Stepped Moving Average function, traders can enhance the accuracy of moving averages and make more informed decisions.
Stepped Moving Average takes two parameters: the current RSI value and a size parameter. It computes the next step in the moving average calculation by determining the upper and lower bounds of the moving average range. It accomplishes this by adjusting the values of smax and smin based on the given RSI and size.
Furthermore, Stepped Moving Average introduces the concept of a trend variable. By comparing the previous trend value with the current RSI and the previous upper and lower bounds, it updates the trend accordingly. This feature enables traders to identify potential shifts in market sentiment and make timely adjustments to their trading strategies.
Advantages over Regular RSI:
Enhanced Range Boundaries:
The inclusion of size parameters in Stepped Moving Average allows for more precise determination of the upper and lower bounds of the moving average range. This feature provides traders with a clearer understanding of the potential price levels that can influence market behavior. Consequently, it aids in setting more effective entry and exit points for trades.
Improved Trend Identification:
The trend variable in Stepped Moving Average helps traders identify changes in market trends more accurately. By considering the previous trend value and comparing it to the current RSI and previous bounds, Stepped Moving Average captures trend reversals with greater precision. This capability empowers traders to respond swiftly to market shifts and potentially capture more profitable trading opportunities.
Smoother Moving Averages:
Stepped Moving Average's ability to adjust the moving average range bounds based on trend changes and size parameters results in smoother moving averages. Regular RSI calculations may produce jagged or erratic results due to abrupt market movements. Stepped Moving Average mitigates this issue by dynamically adapting the range boundaries, thereby providing traders with more reliable and consistent moving average signals.
Complementary Functionality with Slow RSI:
Stepped Moving Average and Slow RSI function in harmony to provide a comprehensive trading analysis toolkit. While Stepped Moving Average refines the moving average calculation process, Slow RSI offers a more accurate representation of market strength. The combination of these two functions facilitates a deeper understanding of market dynamics and assists traders in making better-informed decisions.
Extras
-Alerts
-Signals
