Auto Signal Buy/SellAuto Signal Buy/Sell with Time Filter and Dynamic ZLEMA (GMT+2) 🌟
Are you looking for an indicator that combines efficiency and simplicity while integrating advanced elements like SuperTrend, ZLEMA (Zero Lag EMA), and a MACD DEMA for clear and precise buy/sell signals? 📈 Introducing Auto Signal Buy/Sell, the ultimate indicator designed for intraday and swing traders, optimized for market hours in GMT+2.
🛠️ Key Features:
- **Advanced SuperTrend**: Follow the dominant trend with a robust SuperTrend, adjustable to your preferences (customizable multiplier and period).
- **Dynamic ZLEMA**: Get a zero-lag EMA curve with a visual signal. Additionally, the ZLEMA turns blue when it’s nearly flat, helping you easily spot market consolidation phases.
- **MACD DEMA**: An enhanced version of the traditional MACD, using the Double EMA to capture more responsive buy/sell cross signals. 📊
- **Buy/Sell Signals**: Visual arrows clearly indicate potential entry and exit points on your chart, filtered by MACD crossovers and the SuperTrend trend.
- **Smart Time Filter (GMT+2)**: This script adapts to trading hours (customizable) and only displays signals during trading hours. The background turns light blue when the market is closed, preventing confusion during inactivity periods. 🕒
⚙️ Full Customization:
- Adjustable trading hours (default 9 AM to 5 PM in GMT+2) with dynamic background indicating when markets are closed.
- Flexible settings for SuperTrend, ZLEMA, and MACD DEMA to suit any strategy.
🎯 Why Choose This Indicator?
- Optimized for maximum precision with advanced algorithms like ZLEMA and DEMA.
- Easy to use: it provides clear, visual signals directly on the chart—no need to decipher complex indicators.
- A complete intraday and swing indicator that combines trend analysis and signal filtering with precise market hours.
🚀 Boost Your Trading!
Add this indicator to your toolkit and enhance your decision-making. Thanks to its intuitive interface and clear visual signals, you can trade with confidence. 💡
Don't forget to like 👍 and comment if you find this indicator useful! Your feedback helps us continue improving such tools. 🚀
📌 How to Use:
1. Add the indicator to your chart.
2. Adjust the SuperTrend and ZLEMA settings to suit your needs.
3. Follow the buy/sell signals and watch for the light blue background outside of trading hours.
4. Trade effectively and stay in control, even during consolidation phases.
Cari dalam skrip untuk "curve"
Dynamic Volume RSI (DVRSI) [QuantAlgo]Introducing the Dynamic Volume RSI (DVRSI) by QuantAlgo 📈✨
Elevate your trading and investing strategies with the Dynamic Volume RSI (DVRSI) , a powerful tool designed to provide clear insights into market momentum and trend shifts. This indicator is ideal for traders and investors who want to stay ahead of the curve by using volume-responsive calculations and adaptive smoothing techniques to enhance signal clarity and reliability.
🌟 Key Features:
🛠 Customizable RSI Settings: Tailor the indicator to your strategy by adjusting the RSI length and price source. Whether you’re focused on short-term trades or long-term investments, DVRSI adapts to your needs.
🌊 Adaptive Smoothing: Enable adaptive smoothing to filter out market noise and ensure cleaner signals in volatile or choppy market conditions.
🎨 Dynamic Color-Coding: Easily identify bullish and bearish trends with color-coded candles and RSI plots, offering clear visual cues to track market direction.
⚖️ Volume-Responsive Adjustments: The DVRSI reacts to volume changes, giving greater significance to high-volume price moves and improving the accuracy of trend detection.
🔔 Custom Alerts: Stay informed with alerts for key RSI crossovers and trend changes, allowing you to act quickly on emerging opportunities.
📈 How to Use:
✅ Add the Indicator: Set up the DVRSI by adding it to your chart and customizing the RSI length, price source, and smoothing options to fit your specific strategy.
👀 Monitor Visual Cues: Watch for trend shifts through the color-coded plot and candles, signaling changes in momentum as the RSI crosses key levels.
🔔 Set Alerts: Configure alerts for critical RSI crossovers, such as the 50 line, ensuring you stay on top of potential market reversals and opportunities.
🔍 How It Works:
The Dynamic Volume RSI (DVRSI) is a unique indicator designed to provide more accurate and responsive signals by incorporating both price movement and volume sensitivity into the RSI framework. It begins by calculating the traditional RSI values based on a user-defined length and price source, but unlike standard RSI tools, the DVRSI applies volume-weighted adjustments to reflect the strength of market participation.
The indicator dynamically adjusts its sensitivity by factoring in volume to the RSI calculation, which means that price moves backed by higher volumes carry more weight, making the signal more reliable. This method helps identify stronger trends and reduces the risk of false signals in low-volume environments. To further enhance accuracy, the DVRSI offers an adaptive smoothing option that allows users to reduce noise during periods of market volatility. This adaptive smoothing function responds to market conditions, providing a cleaner signal by reducing erratic movements or price spikes that could lead to misleading signals.
Additionally, the DVRSI uses dynamic color-coding to visually represent the strength of bullish or bearish trends. The candles and RSI plots change color based on the RSI values crossing critical thresholds, such as the 50 level, offering an intuitive way to recognize trend shifts. Traders can also configure alerts for specific RSI crossovers (e.g., above 50 or below 40), ensuring that they stay informed of potential trend reversals and significant market shifts in real-time.
The combination of volume sensitivity, adaptive smoothing, and dynamic trend visualization makes the DVRSI a robust and versatile tool for traders and investors looking to fine-tune their market analysis. By incorporating both price and volume data, this indicator delivers more precise signals, helping users make informed decisions with greater confidence.
Disclaimer:
The Dynamic Volume RSI is designed to enhance your market analysis but should not be used as a sole decision-making tool. Always consider multiple factors before making any trading or investment decisions. Past performance is not indicative of future results.
Dynamic Jurik RSX w/ Fisher Transform█ Introduction
The Dynamic Jurik RSX with Fisher Transform is a powerful and adaptive momentum indicator designed for traders who seek a non-laggy view of price movements. This script is based on the classic Jurik RSX (Relative Strength Index). It also includes features such as the dynamic overbought and oversold limits, the Inverse Fisher Transform, trend display, slope calculations, and the ability to color extremes for better clarity.
█ Key Features:
• RSX: The Relative Strength Index (RSX) in this script is based on Jurik’s RSX, which is smoother than the traditional RSI and aims to reduce noise and lag. This script calculates the RSX using an exponential smoothing technique and adaptive adjustments.
• Inverse Fisher Transform: This script can optionally apply the Inverse Fisher Transform to the RSX, which helps to normalize the RSX values, compressing them between -1 and 1. The inverse transformation makes it easier to spot extreme values (overbought and oversold conditions) by enhancing the visual clarity of those extremes. It also smooths the curve over a user-defined period in hopes of providing a more consistent signal.
• Dynamic Limits: The dynamic overbought and oversold limits are calculated based on the RSX's recent high and low values. The limits adjust dynamically depending on market conditions, making them more relevant to current price action.
• Slope Display: The slope of the RSX is calculated as the rate of change between the current and previous RSX value. The slope is displayed as dots when the slope exceeds the threshold designated by the user, providing visual cues for momentum shifts.
• Trend Coloring: Optionally, the user can also enable a trend-based display. It is simply based on current value of RSX versus the previous one. If RSX is rising then the trend is bullish, if not, then the trend is bearish.
• Coloring Extremes: Users can configure the RSX to color the chart when prices enter extreme conditions, such as overbought or oversold zones, providing visual cues for market reversals.
█ Attached Chart Notes:
• Top Panel: Enabled dynamic limits, Trend display, standard Jurik RSX with 20 lookback period, and Slope display.
• Middle Panel: Enabled dynamic limits, Extremes display, and standard Jurik RSX with 20 lookback period.
• Bottom Panel: Enabled dynamic limits, Trend display, Inverse Fisher Transform with 14 lookback period and 9 smoothing period. and Slope display.
█ Credits:
Special thanks to Everget for providing the original script. The script was also slightly modified based on updates from outside sources.
█ Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always conduct your own research and consult a professional before making any trading decisions.
Gaussian Acceleration ArrayIndicators play a role in analyzing price action, trends, and potential reversals. Among many of these, velocity and acceleration have held a significant place due to their ability to provide insight into momentum and rate of change. This indicator takes the old calculation and tweaks it with gaussian smoothing and logarithmic function to ensure proper scaling.
A Brief on Velocity and Acceleration: The concept of velocity in trading refers to the speed at which price changes over time, while acceleration is the rate of change(ROC) of velocity. Early momentum indicators like the RSI and MACD laid foundation for understanding price velocity. However, as markets evolve so do we as technical analysts, we seek the most advanced tools.
The Acceleration/Deceleration Oscillator, introduced by Bill Williams, was one of the early attempts to measure acceleration. It helped gauge whether the market was gaining or losing momentum. Over time more specific tools like the "Awesome Oscillator"(AO) emerged, which has a set length on the datasets measured.
Gaussian Functions: Named after the mathematician Carl Friedrich Gauss, the Gaussian function describes a bell-shaped curve, often referred to as the "normal distribution." In trading these functions are applied to smooth data and reduce noise, focusing on underlying patterns.
The Gaussian Acceleration Array leverages this function to create a smoothed representation of market acceleration.
How does it work?
This indicator calculates acceleration based the highs and lows of each dataset
Once the weighted average for velocity is determined, its rate of change essentially becomes the acceleration
It then plots multiple lines with customizable variance from the primary selected length
Practical Tips:
The Gaussian Acceleration Array offers various customizable parameters, including the sample period, smoothing function, and array variance. Experiment with these settings to tailor it to preferred timeframes and styles.
The color-coded lines and background zones make it easier to interpret the indicator at a glance. The backgrounds indicate increasing or decreasing momentum simply as a visual aid while the lines state how the velocity average is performing. Combining this with other tools can signal shifts in market dynamics.
Gaussian Kernel Smoothing EMAGaussian Kernel Smoothing EMA
The Gaussian Kernel Smoothing EMA integrates the exponential moving average with kernel smoothing techniques to refine the trend tool. Kernel smoothing is a non-parametric technique used to estimate a smooth curve from a set of data points. It is particularly useful in reducing noise and capturing the underlying structure of data. The smoothed value at each point is calculated as a weighted average of neighboring points, with the weights determined by a kernel function.
The Gaussian kernel is a popular choice in kernel smoothing due to its properties of being smooth, symmetric, and having infinite support. This function gives higher weights to data points closer to the target point and lower weights to those further away, resulting in a smooth and continuous estimate. Since price isn't normally distributed a logarithmic transformation is performed to remove most of its skewness to be able to fit the Gaussian kernel.
This indicator also has a bandwidth, which in kernel smoothing controls the width of the window over which the smoothing is performed. It determines how much influence nearby data points have on the smoothed value. In this indicator, the bandwidth is dynamically adjusted based on the standard deviation of the log-transformed prices so that the smoothing adapts to the underlying variability and potential volatility.
Bandwidth Factor: The bandwidth factor in this indicator is used to adjust the degree of the smoothing applied to the MA. In kernel smoothing, Bandwidth controls the width of the window over which the smoothing is applied. It determines how many data points around a central point are considered when calculating a smooth value. A smaller bandwidth results in less smoothing, while a larger bandwidth smooths out more noise, leading to a broader, more general trend.
Moving Average Z-Score Suite [BackQuant]Moving Average Z-Score Suite
1. What is this indicator
The Moving Average Z-Score Suite is a versatile indicator designed to help traders identify and capitalize on market trends by utilizing a variety of moving averages. This indicator transforms selected moving averages into a Z-Score oscillator, providing clear signals for potential buy and sell opportunities. The indicator includes options to choose from eleven different moving average types, each offering unique benefits and characteristics. It also provides additional features such as standard deviation levels, extreme levels, and divergence detection, enhancing its utility in various market conditions.
2. What is a Z-Score
A Z-Score is a statistical measurement that describes a value's relationship to the mean of a group of values. It is measured in terms of standard deviations from the mean. For instance, a Z-Score of 1.0 means the value is one standard deviation above the mean, while a Z-Score of -1.0 indicates it is one standard deviation below the mean. In the context of financial markets, Z-Scores can be used to identify overbought or oversold conditions by determining how far a particular value (such as a moving average) deviates from its historical mean.
3. What moving averages can be used
The Moving Average Z-Score Suite allows users to select from the following eleven moving averages:
Simple Moving Average (SMA)
Hull Moving Average (HMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Double Exponential Moving Average (DEMA)
Running Moving Average (RMA)
Linear Regression Curve (LINREG) (This script can be found standalone )
Triple Exponential Moving Average (TEMA)
Arnaud Legoux Moving Average (ALMA)
Kalman Hull Moving Average (KHMA)
T3 Moving Average
Each of these moving averages has distinct properties and reacts differently to price changes, allowing traders to select the one that best fits their trading style and market conditions.
4. Why Turning a Moving Average into a Z-Score is Innovative and Its Benefits
Transforming a moving average into a Z-Score is an innovative approach because it normalizes the moving average values, making them more comparable across different periods and instruments. This normalization process helps in identifying extreme price movements and mean-reversion opportunities more effectively. By converting the moving average into a Z-Score, traders can better gauge the relative strength or weakness of a trend and detect potential reversals. This method enhances the traditional moving average analysis by adding a statistical perspective, providing clearer and more objective trading signals.
5. How It Can Be Used in the Context of a Trading System
In a trading system, it can be used to generate buy and sell signals based on the Z-Score values. When the Z-Score crosses above zero, it indicates a potential buying opportunity, suggesting that the price is above its mean and possibly trending upward. Conversely, a Z-Score crossing below zero signals a potential selling opportunity, indicating that the price is below its mean and might be trending downward. Additionally, the indicator's ability to show standard deviation levels and extreme levels helps traders set profit targets and stop-loss levels, improving risk management and trade planning.
6. How It Can Be Used for Trend Following
For trend-following strategies, it can be particularly useful. The Z-Score oscillator helps traders identify the strength and direction of a trend. By monitoring the Z-Score and its rate of change, traders can confirm the persistence of a trend and make informed decisions to enter or exit trades. The indicator's divergence detection feature further enhances trend-following by identifying potential reversals before they occur, allowing traders to capitalize on trend shifts. By providing a clear and quantifiable measure of trend strength, this indicator supports disciplined and systematic trend-following strategies.
No backtests for this indicator due to the many options and ways it can be used,
Enjoy
FX Index Curve Oscillator (FICO)We can approximate the TVC:DXY with simple multiplication, rather than using geometric weighted averages; the values will be different, but the charts will look almost the same. Because we can make a "good enough" version of DXY, we can also extend this concept to the other major currencies:
AUD - Yellow
CAD - Red
CHF - Orange
EUR - Purple
GBP - Green
JPY - White
NZD - Lime green
USD - Blue
This indicator works by constructing an "index" for each currency, performing a lookback to figure out the rate of change, and then smoothing the values. These values are fed through an oscillator to normalize them between -1.00 and +1.00, before finally being smoothed again. Interestingly, using HMA to smooth them the second time will cause the values to leak past 1.00, which we can also use as a signal.
If you want to change the values, I find that the biggest difference comes from the lookback and oscillator settings; the MA/smoothing is probably good enough. The default settings are for doing forex trades on the daily chart. Other timeframes are possible, but I could not find any settings that work. It might also be possible to use a similar approach on other assets (crypto, metals, indexes, etc) but I have not tried yet.
In my own testing, what I found to be a good approach is to look for a currency to be above +1 and another to be below -1, and then look for color changes; ideally this will happen on the same bar/candle.
You can also consider two line crosses, breaking above or below 1, etc as other entry signals. I find that price will either move immediately, or take a candle or two to retrace and then start moving.
Happy trading!
Unfortunately, the indicator pane can get quite crowded; if you're testing for a single currency pair, you may want to disable some of the plotted lines:
MarketcapDefinition
This indicator was designed to reveal the relationship between the price of the product and its market value. The red average marketcap line that appears on the chart is the line. And the further up this line moves from the chart, the more it shows that there is a mismatch between the price and the market value. So what does this incompatibility mean? There are purchases of the product, but since the supply of the product into circulation is constantly increasing, it means that these purchases are not reflected in the price, which means there is inflation.
The main purpose of our indicator is to calculate inflation of the product. It is the understanding of whether or not the amount of supply put into circulation in response to the investment is reflected in the product price while increasing the market value.
Attention: Transactions are made based on the data received via CRYPTOCAP. In cases where this data cannot be received, the "UNSUPPORTED SOURCE" warning is displayed. You can use Settings to change the source from which data can be retrieved.
Labels
The labels are explained one by one below.
MARKETCAP: Shows the current market value.
ATH MARKETCAP: Shows the highest market value of all time.
MARKETCAP RATIO: It gives the ratio between the highest level and the lowest level of the market value.
PRICE RATIO: Gives the ratio between the highest level and the lowest level of the crypto price.
ALL INFLATION PERCENT: It refers to the percentage of all inflation that has developed so far. It is also the percentage difference between market value and price.
MONTHLY INFLATION PERCENT: It refers to the monthly estimated inflation percentage.
CIRCULATING SUPPLY: It refers to the estimated circulation supply of the product.
Best Use
It should bring to mind the idea that the further the indicator curve moves away from the price, the higher the inflation will be. In order for a product to reach its previous peak, its market value must normally increase by the "MARKETCAP RATIO" value and the "PRICE RATIO" value. This should make you think that this product needs more investment to reach its former peak. And it is necessary to be careful when purchasing such products.
Disclaimer
This indicator is for informational purposes only and should be used for educational purposes only. You may lose money if you rely on this to trade without additional information. Use at your own risk.
Version
v1.0
MathTransformLibrary "MathTransform"
Auxiliary functions for transforming data using mathematical and statistical methods
scaler_zscore(x, lookback_window)
Calculates Z-Score normalization of a series.
Parameters:
x (float) : : floating point series to normalize
lookback_window (int) : : lookback period for calculating mean and standard deviation
Returns: Z-Score normalized series
scaler_min_max(x, lookback_window, min_val, max_val, empiric_min, empiric_max, empiric_mid)
Performs Min-Max scaling of a series within a given window, user-defined bounds, and optional midpoint
Parameters:
x (float) : : floating point series to transform
lookback_window (int) : : int : optional lookback window size to consider for scaling.
min_val (float) : : float : minimum value of the scaled range. Default is 0.0.
max_val (float) : : float : maximum value of the scaled range. Default is 1.0.
empiric_min (float) : : float : user-defined minimum value of the input data. This means that the output could exceed the `min_val` bound if there is data in `x` lesser than `empiric_min`. If na, it's calculated from `x` and `lookback_window`.
empiric_max (float) : : float : user-defined maximum value of the input data. This means that the output could exceed the `max_val` bound if there is data in `x` greater than `empiric_max`. If na, it's calculated from `x` and `lookback_window`.
empiric_mid (float) : : float : user-defined midpoint value of the input data. If na, it's calculated from `empiric_min` and `empiric_max`.
Returns: rescaled series
log(x, base)
Applies logarithmic transformation to a value, base can be user-defined.
Parameters:
x (float) : : floating point value to transform
base (float) : : logarithmic base, must be greater than 0
Returns: logarithm of the value to the given base, if x <= 0, returns logarithm of 1 to the given base
exp(x, base)
Applies exponential transformation to a value, base can be user-defined.
Parameters:
x (float) : : floating point value to transform
base (float) : : base of the exponentiation, must be greater than 0
Returns: the result of raising the base to the power of the value
power(x, exponent)
Applies power transformation to a value, exponent can be user-defined.
Parameters:
x (float) : : floating point value to transform
exponent (float) : : exponent for the transformation
Returns: the value raised to the given exponent, preserving the sign of the original value
tanh(x, scale)
The hyperbolic tangent is the ratio of the hyperbolic sine and hyperbolic cosine. It limits an output to a range of −1 to 1.
Parameters:
x (float) : : floating point series
scale (float)
sigmoid(x, scale, offset)
Applies the sigmoid function to a series.
Parameters:
x (float) : : floating point series to transform
scale (float) : : scaling factor for the sigmoid function
offset (float) : : offset for the sigmoid function
Returns: transformed series using the sigmoid function
sigmoid_double(x, scale, offset)
Applies a double sigmoid function to a series, handling positive and negative values differently.
Parameters:
x (float) : : floating point series to transform
scale (float) : : scaling factor for the sigmoid function
offset (float) : : offset for the sigmoid function
Returns: transformed series using the double sigmoid function
logistic_decay(a, b, c, t)
Calculates logistic decay based on given parameters.
Parameters:
a (float) : : parameter affecting the steepness of the curve
b (float) : : parameter affecting the direction of the decay
c (float) : : the upper bound of the function's output
t (float) : : time variable
Returns: value of the logistic decay function at time t
Linear Regression Channel Slow And Fast (Multi time frame)Linear Regression Channels are useful measure for technical and quantitative analysis in financial markets that help identifying trends and trend direction. The use of standard deviation gives traders ideas as to when prices are becoming overbought or oversold relative to the long term trend
The basis of a linear regression channel
Linear Regression Line – is a line drawn according to the least-squares statistical technique which produces a best-fit line that cuts through the middle of price action, a line that best fits all the data points of interest. The resulting fitted model can be used to summarize the data, to predict unobserved values from the same system. Linear Regression Line then present basis for the channel calculations
The linear regression channel
2. Upper Channel Line – A line that runs parallel to the Linear Regression Line and is usually one to two standard deviations above the Linear Regression Line.
3. Lower Channel Line – This line runs parallel to the Linear Regression Line and is usually one to two standard deviations below the Linear Regression Line.
Unlike Fibonacci Channels and Andrew’s Pitchfork, Linear Regression Channels are calculated using statistical methods, both for the regression line (as expressed above) and deviation channels. Upper and Lower channel lines are presenting the idea of bell curve method, also known as a normal distribution and are calculated using standard deviation function.
A standard deviation include 68% of the data points, two standard deviations include approximately 95% of the data points and any data point that appears outside two standard deviations is very rare.
It is often assumed that the data points will move back toward the average, or regress and channels would allow us to see when a security is overbought or oversold and ready to revert to the mean
please note : Over time, the price will move up and down, and the linear regression channel will experience changes as old prices fall off and new prices appear
Papercuts Recency CandlesPapercuts Recency Candles
V0.8 by Joel Eckert @PapercutsTrading
***This is currently an experimental visual exploratory concept.***
*** Experimental tools should only be explored by fellow coders and experienced traders.***
DESCRIPTION:
As coders, how can we seamlessly transition between actual and smoothed price data sets as data ages?
This is a visual experiment to see if and how data can be smoothly transitioned from one value to another over a set number of candles. If we visualize a chart in 3 zones, a head, a body, and a tail we can start to understand how this could work. The head zone would represent the first data set of actual asset prices. The body zone would represent the transition period from the first to the to the second data set. Last, the tail zone would represent the second data set made of a Hull Moving Average of the asset.
CONCEPT:
It is conceived that data and position precision constantly shift as they decay or age, therefore making older price levels act more like price regions or zones vs exact price points. This is what I am calling Recency.
This indicator utilizes the concept of "Recency" to explore the possibility of a new style of candle. It aims to maintain accurately on recent prices action but loosen up accuracy on older price action. The very nature of this requires ALTERING HISTORICAL DATA within the body zone or transition candles to achieve the effect. It is similar to trying to merge a line chart type with a candle chart type.
This experiment of using recency for candles was to create candles that stay more accurate near current price but fade away into a simple line as they age out, resulting in a simplified view of the big picture which consists of older price action.
This experimental design theoretically will help you stay focused only on what is currently unfolding and to minimize distractions from older price nuances.
USAGE:
WHO:
This is not recommended for new traders or novices that are unfamiliar with standard tools. Standardized tools should always be used to get grounded and build a foundation.
Active traders who are familiar with trading comfortably should experiment with this to see if they find it interesting or usable.
Pine coders may find this concept interesting enough, and may adapt the idea to other elements of their own scripts if they find it interesting… I just ask they give credit where credit is due.
HOW:
The best way to visualize how this works is to do the following:
Load it on a chart.
Turn off Standard candles in Chart Setting of the current window. I actually just turn off the bodies and borders, and dim the old wicks as I like the way the old wicks look when left alone with these new candles.
Enable chart replay at a faster speed, like 3x, and play back the chart to watch the behavior of the candles.
You’ll be able to see how the head of the candle type preserves OHLC, and indicates direction but as the candle starts to age it progressively flowers into the HMA
While it plays back try adjusting settings to see how they affect behavior.
You can see the data average in real-time which often reveals how unstable actual price noise really is.
The head candle diagonals indicate the candle body direction.
SETTINGS:
Coloring: You can choose your own bullish or bearish colors to match your scheme.
Price Line: The price line is colored according to the trend and
Head Length: These candles are true to the source high and low. They remain slightly brighter than transition candles. We have a max of 50 to keep things responsive.
Time Decay Length: This is the amount of candles it takes to transition to the tail. Max is 300 to keep things responsive.
Decay Continuity: This forces transition candles to complete the HMA curve instead of creating gaps when conforming to it. The best way to visualize this feature is to run a 3x replay of an asset, and toggle the result on and off. On is preferred.
Tail HMA Length: This is the smoothing amount for the resulting HMA stepline that calculates every close, but has a delayed draw until after the transition candles. You can optionally turn off the delayed visibility to help with comprehension.
Tail HMA Weight: This is simply an option to make the tail thicker or thinner. This also adjusts the border on the head candles to help them stand out.
Show Side Bias Dots: Default true: Draws a dot when bias to one side changes to help keep you on the right side of trade. Side bias is simply the alignment of 3 moving averages in one direction.
IMPORTANT NOTES:
You'll have to turn off or dim the standard candles in your view "Chart Settings" to see this properly.
Be aware that since the candles are based on boxes and utilize the “recency concept”, which means their data decays and changes as it ages. This results in a cleaner chart overall, but exact highs and lows will be averaged out as the data decays, forming a Hull Moving Average stepline of your defined length once decay has finished.
SUMMARY OF HOW IT WORKS:
First it takes candle information and creates unique boxes that represent each candle based on the high and low. It utilizes boxes because standard candles once written, cannot be later altered or removed… which is a key element for this effect to work.
Next it creates a second box and line from open to close for the body of the Head candles. This indicates direction at a glance.
As candles age beyond the defined distance of the “Head” they enter the "Body" aka "Time Decay" zone. Here the accuracy of the high and low will be averaged down using an incremental factor of the HMA, defined by "Time Decay Length" amount of candles.
The resulting tail is an HMA of Tail HMA Length. This tail is always calculate at close, but is not drawn instantly. The draw is delayed so that there is not overlapping data, and this makes the effect look more elegant.
There are also two EMAs within the script that do nothing but help candle coloring and help provide a trade side bias. When both EMA's and the HMA align, a side bias is defined. Only when the side bias changes will a new dot is formed.
Head candles have been simplified from previous versions to be easier to read at a a glance.
Turn of the Month Strategy [Honestcowboy]The end of month effect is a well known trading strategy in the stock market. Quite simply, most stocks go up at the end of the month. What's even better is that this effect spills over to the next phew days of the next month.
In this script we backtest this theory which should work especially well on SP500 pair.
By default the strategy buys 2 days before the end of each month and exits the position 3 days into the next month.
The strategy is a long only strategy and is extremely simple. The SP500 is one of the #1 assets people use for long term investing due to it's "9.8%" annualised return. However as a trader you want the best deal possible. This strategy is only inside the market for about 25% of the time while delivering a similar return per exposure with a lower drawdown.
Here are some hypothesis why turn of the month effect happens in the stock markets:
Increased inflow from savings accounts to stocks at end of month
Rebalancing of portfolios by fund managers at end of month
The timing of monthly cash flows received by pension funds, which are reinvested in the stock market.
The script also has some inputs to define how many days before end of the month you want to buy the asset and how long you want to hold it into the next month.
It is not possible to buy the asset exactly on this day every month as the market closes on the weekend. I've added some logic where it will check if that day is a friday, saturdady or sunday. If that is the case it will send the buy signal on the end of thursday, this way we enter on the friday and don't lose that months trading opportunity.
The backtest below uses 4% exposure per trade as to show the equity curve more clearly and because of publishing rules. However, most fund managers and investors use 100% exposure. This way you actually risk money to earn money. Feel free to adjust the settings to your risk profile to get a clearer picture of risks and rewards before implementing in your portfolio.
Crypto Realized Profits/Losses Extremes [AlgoAlpha]🌟🚀 Introducing the Crypto Realized Profits/Losses Extremes Indicator by AlgoAlpha 🚀🌟
Unlock the potential of cryptocurrency markets with our cutting-edge On-Chain Pine Script™ indicator, designed to highlight extreme realized profit and loss zones! 🎯📈
Key Features:
✨ Realized Profits/Losses Calculation: Uses real-time data from the blockchain to monitor profit and loss realization events.
📊 Multi-Crypto Compatibility: The Indicator is compatible on other Crypto tickers besides Bitcoin.
⚙️ Customizable Sensitivity: Adjust the look-back period, normalization period, and deviation thresholds to tailor the indicator to your trading style.
🎨 Visual Enhancements: Choose from a variety of colors for up and down trends, and toggle extreme profit/loss overlay for easy viewing.
🔔 Integrated Alerts: Set up alerts for high and extreme profit or loss conditions, helping you stay ahead of significant market movements.
🔍 How to Use:
🛠 Add the Indicator: Add the indicator to favorites. Customize settings like period lengths and deviation thresholds according to your needs.
📊 Market Analysis: Monitor the main oscillator and the bands to understand current profit and loss extremes in the market. When the oscillator is at the upper band, this means that the market is doing really well and traders/investors will be likely to take profit and cause a reversal. The opposite is true when the oscillator reaches the lower band. The main oscillator can also be used for trend analysis.
🔔 Set Alerts: Configure alerts to notify you when the market enters a zone of high profit or loss, or during trend changes, enabling timely decisions without constant monitoring.
How It Works:
The indicator calculates a normalized area under the RSI curve applied on on-chain data regarding the number of wallets in profit. It employs a custom "src" variable that aggregates data from the blockchain about profit and loss addresses, adapting to intraday or longer timeframes as needed. The main oscillator plots this normalized area, while the upper and lower bands are plotted based on a deviation metric to identify extreme conditions. Colored fills between these bands visually denote these zones. For interaction, the indicator plots bubbles for extreme profits or losses and provides optional bar coloring to reflect the current market trend.
🚀💹 Enjoy a comprehensive, customizable, and visually engaging tool that helps you stay ahead in the fast-paced crypto market!
price action reversion bands - [SigmaStreet]█ OVERVIEW
The "Price Action Reversion Bands" is designed to help traders identify potential reversal zones through the integration of polynomial regression, fractal analysis, and pinbar detection. This tool overlays directly onto the price chart, providing dynamic visual cues and signals for market reversals. Its unique synthesis of these methodologies offers traders a powerful, multifaceted approach to market analysis.
█ CONCEPTS
Polynomial Regression Bands:
What It Does:
Models the main trend using a polynomial equation to create a middle trend line with dynamic support and resistance bands.
How It Works:
Calculates polynomial coefficients to plot a regression line and adjusts the bands according to market volatility and conditions.
Fibonacci Retracement Levels:
What It Does:
Provides additional lines inside the regression bands at key Fibonacci ratios to identify potential support and resistance areas.
How It Works:
Calculates retracement levels by identifying high and low points over the same period used to calculate the regression bands, applying Fibonacci ratios to these points.
Fractal Analysis:
What It Does: Identifies natural resistance and support levels, indicating potential reversal zones.
How It Works: Detects fractals based on a specific pattern of price action, using Williams Fractal methodology.
Pinbar Detection:
What It Does: Signals potential price reversals through pinbar candlestick patterns.
How It Works: Analyzes
candlesticks to identify pinbars which show a rejection of prices, suggesting possible reversals.
█ ORIGINALITY AND USEFULNESS
The price action reversion bands distinguishes itself through its innovative integration of several advanced analytical methods, providing traders with a holistic view of potential market reversals:
Unique Combination:
While many tools use these techniques in isolation, this indicator synergistically combines polynomial regression, Fibonacci retracement levels, fractal analysis, and pinbar detection. This multi-faceted approach allows traders to assess strength, potential reversal zones, and price rejection more effectively than using traditional single-method indicators.
Advanced Polynomial Regression Application:
Unlike standard regression tools that offer static insights, this indicator dynamically adjusts its regression bands based on real-time market volatility, providing a more accurate reflection of market conditions.
Enhanced Signal Reliability:
By using fractals and pinbars in conjunction to validate each other, the indicator significantly increases the reliability of its reversal signals. This dual-validation method filters out less probable signals, focusing on high-probability trading opportunities.
Customization and Flexibility:
It offers unprecedented customization options, allowing traders to fine-tune the tool according to their trading style and market conditions. Traders can adjust the polynomial degree, the sensitivity of the Fibonacci retracements, and even the definition of what constitutes a significant pinbar, making it highly adaptable to various trading scenarios.
Educational Value:
The indicator not only aids in trading but also serves as an educational tool that helps traders understand the interaction between different types of market analysis techniques. This contributes to a deeper knowledge base and better trading decisions over time.
These distinctive features make the "Price Action Reversion Bands - " not just another indicator but a comprehensive trading tool that enhances decision-making through a well-rounded analysis of market dynamics.
█ HOW TO USE
Installation and Setup:
Apply the indicator to your TradingView chart from the "Indicators" menu.
Select either polynomial regression or Fibonacci retracement as the basis for the bands through the indicator settings.
Reading the Indicator:
Monitor the approach of price to the upper and lower bands which indicate potential reversal zones.
Look for fractal and pinbar formations near these bands for additional signal confirmation.
Customization:
Adjust settings such as the polynomial degree, data window length, and engagement zones to tailor the bands to your trading style.
Modify visual aspects like color and line type for better clarity and personal preference.
█ FEATURES
Dynamic Adjustment:
Bands adjust in real-time based on incoming price data and selected settings.
Multiple Analysis Techniques: Combines several analytical techniques to provide a comprehensive view of potential market movements. The integration of polynomial regression with Fibonacci levels, supplemented by fractal and pinbar analysis, marks this tool as particularly innovative, offering a level of synthesis that enhances predictive accuracy and usability.
User-Friendly Customization: Allows for extensive customization to suit individual trading strategies and preferences.
█ LIMITATIONS
Market Dependency:
Performance may vary significantly across different markets and conditions.
Parameter Sensitivity: Requires fine-tuning of parameters to ensure optimal performance, which might demand a steep learning curve for new users.
█ NOTES
For best results, combine this tool with other forms of analysis, such as fundamental analysis and other technical indicators, to confirm signals and enhance decision-making.
█ THANKS
Special thanks to the PineCoders community the Pine Coders themselves for their foundational contributions to the concepts used in this script. Their pioneering work in the fields of technical analysis and Pine Script development has been invaluable. This script is a testament to the collaborative spirit of the TradingView developer community, integrating analytical techniques with innovative approaches to offer a tool that is both modern and cutting-edge.
Yield Curve SpaghettiDisplays the difference in yield between multiple bond pairs for a given country.
Currently supports US, DE, and GB bonds
[Wiseplat Sideways] v.04The Sideway indicator for TradingView is a powerful tool designed to identify periods of sideways or ranging price action in the market. With its intuitive interface and customizable parameters, traders can easily spot when an asset is consolidating, providing valuable insights for both trend-following and range-bound strategies.
This indicator utilizes really simple algorithm to analyze price movement and volatility, effectively filtering out noise and false signals. By plotting clear visual cues on the chart.
Traders can adjust the sensitivity parameters to tailor the indicator to their specific trading style and preferences. Whether used in isolation or in conjunction with other technical analysis tools, the Sideway indicator empowers traders to make informed decisions in dynamic market conditions.
Its user-friendly design and simple settings of parameters makes it accessible to traders of all levels, from beginners seeking clarity in choppy markets to seasoned professionals looking for confirmation of their analysis. With the Sideway indicator, traders can confidently navigate sideways price action and stay ahead of the curve in their trading endeavors.
Developer: Oleg Shpagin
Bitcoin Regression Price BoundariesTLDR
DCA into BTC at or below the blue line. DCA out of BTC when price approaches the red line. There's a setting to toggle the future extrapolation off/on.
INTRODUCTION
Regression analysis is a fundamental and powerful data science tool, when applied CORRECTLY . All Bitcoin regressions I've seen (Rainbow Log, Stock-to-flow, and non-linear models), have glaring flaws ... Namely, that they have huge drift from one cycle to the next.
Presented here, is a canonical application of this statistical tool. "Canonical" meaning that any trained analyst applying the established methodology, would arrive at the same result. We model 3 lines:
Upper price boundary (red) - Predicted the April 2021 top to within 1%
Lower price boundary (green)- Predicted the Dec 2022 bottom within 10%
Non-bubble best fit line (blue) - Last update was performed on Feb 28 2024.
NOTE: The red/green lines were calculated using solely data from BEFORE 2021.
"I'M INTRUIGED, BUT WHAT EXACTLY IS REGRESSION ANALYSIS?"
Quite simply, it attempts to draw a best-fit line over some set of data. As you can imagine, there are endless forms of equations that we might try. So we need objective means of determining which equations are better than others. This is where statistical rigor is crucial.
We check p-values to ensure that a proposed model is better than chance. When comparing two different equations, we check R-squared and Residual Standard Error, to determine which equation is modeling the data better. We check residuals to ensure the equation is sufficiently complex to model all the available signal. We check adjusted R-squared to ensure the equation is not *overly* complex and merely modeling random noise.
While most people probably won't entirely understand the above paragraph, there's enough key terminology in for the intellectually curious to research.
DIVING DEEPER INTO THE 3 REGRESSION LINES ABOVE
WARNING! THIS IS TECHNICAL, AND VERY ABBREVIATED
We prefer a linear regression, as the statistical checks it allows are convenient and powerful. However, the BTCUSD dataset is decidedly non-linear. Thus, we must log transform both the x-axis and y-axis. At the end of this process, we'll use e^ to transform back to natural scale.
Plotting the log transformed data reveals a crucial visual insight. The best fit line for the blowoff tops is different than for the lower price boundary. This is why other models have failed. They attempt to model ALL the data with just one equation. This causes drift in both the upper and lower boundaries. Here we calculate these boundaries as separate equations.
Upper Boundary (in red) = e^(3.24*ln(x)-15.8)
Lower Boundary (green) = e^(0.602*ln^2(x) - 4.78*ln(x) + 7.17)
Non-Bubble best fit (blue) = e^(0.633*ln^2(x) - 5.09*ln(x) +8.12)
* (x) = The number of days since July 18 2010
Anyone familiar with Bitcoin, knows it goes in cycles where price goes stratospheric, typically measured in months; and then a lengthy cool-off period measured in years. The non-bubble best fit line methodically removes the extreme upward deviations until the residuals have the closest statistical semblance to normal data (bell curve shaped data).
Whereas the upper/lower boundary only gets re-calculated in hindsight (well after a blowoff or capitulation occur), the Non-Bubble line changes ever so slightly with each new datapoint. The last update to this line was made on Feb 28, 2024.
ENOUGH NERD TALK! HOW CAN I APPLY THIS?
In the simplest terms, anything below the blue line is a statistical buying opportunity. The closer you approach the green line (the lower boundary) the more statistically strong that opportunity is. As price approaches the red line, is a growing statistical likelyhood/danger of an imminent blowoff top.
So a wise trader would DCA (dollar cost average) into Bitcoin below the blue line; and would DCA out of Bitcoin as it approaches the red line. Historically, you may or may not have a large time-window during points of maximum opportunity. So be vigilant! Anything within 10-20% of the boundary should be regarded as extreme opportunity.
Note: You can toggle the future extrapolation of these lines in the settings (default on).
CLOSING REMARKS
Keep in mind this is a pure statistical analysis. It's likely that this model is probing a complex, real economic process underlying the Bitcoin price. Statistical models like this are most accurate during steady state conditions, where the prevailing fundamentals are stable. (The astute observer will note, that the regression boundaries held despite the economic disruption of 2020).
Thus, it cannot be understated: Should some drastic fundamental change occur in the underlying economic landscape of cryptocurrency, Bitcoin itself, or the broader economy, this model could drastically deviate, and become significantly less accurate.
Furthermore, the upper/lower boundaries cross in the year 2037. THIS MODEL WILL EVENTUALLY BREAK DOWN. But for now, given that Bitcoin price moves on the order of 2000% from bottom to top, it's truly remarkable that, using SOLELY pre-2021 data, this model was able to nail the top/bottom within 10%.
HSI - Halving Seasonality Index for Bitcoin (BTC) [Logue]Halving Seasonality Index (HSI) for Bitcoin (BTC) - The HSI takes advantage of the consistency of BTC cycles. Past cycles have formed macro tops around 538 days after each halving. Past cycles have formed macro bottoms every 948 days after each halving. Therefore, a linear "risk" curve can be created between the bottom and top dates to measure how close BTC might be to a bottom or a top. The default triggers are set at 98% risk for tops and 5% risk for bottoms. Extensions are also added as defaults to allow easy identification of the dates of the next top or bottom according to the HSI.
CSI - Calendar Seasonality Index for Bitcoin (BTC) [Logue]Calendar Seasonality Index (CSI) for Bitcoin (BTC) - The CSI takes advantage of the consistency of BTC cycles. Past cycles have formed macro tops every four years near November 21st, starting from in 2013. Past cycles have formed macro bottoms every four years near January 15th, starting from 2011. Therefore, a linear "risk" curve can be created between the bottom and top dates to measure how close BTC might be to a bottom or a top. The default triggers are at 98% risk for tops and 5% risk for bottoms. Extensions are also added as defaults to allow easy identification of the dates of the next top or bottom according to the CSI.
Greenblatts Magic Formula - A multiple approachThis indicator is supposed to help find undervalued stocks. Inspired by Joel Greenblatt's strategy where he ranks stocks with the lowest EV/EBIT and the highest ROC. Inspired by the ERP5 strategy I have added Earnings Yield together with ROC.
My approach and how I use the indicator is to see Magic Formula score as a multiple, rather than ranking the numbers between different stocks. Like P/E for comparison. Different kinds of companies trades at different multiples so you have to compare the current MF Score in relation to historical MF Score to get an idea if it truly is undervalued. You also want to see that price actually reacts to a low MF Score.
As i general rule for myself I stay away from companies with EV/EBIT above 13 and generally want to see MF Score below 6-7. A company trading at a negative MF Score indicates that the company may be heavily undervalued.
Red line = EV/EBIT
Green line = ROC + EY / 2
Yellow line = "MF Score" EVEBIT - (ROC+EY/2)
Blue line = The 50 EMA of MF score
The strategy is simple. Look for companies which might be undervalued. Compare the current MF score to it's history. If it's trading near a previous bottom it indicates that the company might be undervalued. You can also use the MF EMA to see a more smooth curve to interpret the multiple.
Trending RSI [ChartPrime]Trending RSI takes a new approach to RSI intended to provide all of the missing information that traditional RSI lacks. Questions such as "why does the price continue to decline even during an oversold period?" can be aided using the Trending RSI.
These types of movements are due to the market still trending and traditional RSI can not tell traders this. Trending RSI fixes this by introducing trend information back into the oscillator. By reverse engineering RSI we have been able to make a new indicator that is no longer bound between 0 and 100. Instead it provides the traditional 70 and 30 zones as bands, and 50 as a center line that still represent these zones perfectly. This transforms RSI into a centered oscillator instead of a normalized oscillator. When the market is trending our indicator represents this as the center line being below or above 0. Just like MACD the center line is colored to represent the market phases. This helps in identifying reversals more clearly by adding a layer of confluence to the already renowned RSI. We have also included a novel filtering technique that has a low lag to smoothing ratio. This is primarily used to smooth the bands by default but you can also utilize this on the RSI. Several alerts have been included to provide users with easy to configure signals.
You can use the center line as a directional filter for your trades by only picking trades in the direction of the center line. When the center line is above 0, the market is trending up. Conversely, when the center line is below 0 the market is trending down trend. Use the polarity of the center line to estimate the strength of retracements from the oversold and overbought zones. We have also included a special moving average to help you find the momentum of a move. The Binomial MA filter approximates a normal curve making it similar to a gaussian filter. We have also included standard divergences which are fully configurable in the settings. Finally, we have built this indicator to be compatible with the built in multi time frame option to allow users to freely pick the time frame they wish to use. It is worth noting that due to the limitations of the standard MTF implementation divergences will not plot as expected when using time frames outside of the charts time frame. This is standard and also affects the built in RSI.
All of the colors are fully adjustable with the option to enable or disable the glow effect. We have also designed this indicator to only display the information for plots that are enabled to reduce clutter and provide a cleaner charting experience. All alerts are built to work with the standard alert builder and do not have to be enabled or disabled inside of the indicator.
Included Alerts:
RSI Cross Over Center
RSI Cross Under Center
RSI Cross Under Upper Range
RSI Cross Over Upper Range
RSI Cross Over Lower Range
RSI Cross Under Lower Range
RSI Cross Over MA
RSI Cross Under MA
RSI Cross Over 0
RSI Cross Under 0
Center Cross Over 0
Center Cross Under 0
Center Bullish
Center Bearish
Bullish Divergence
Bearish Divergence
In wrapping up, the Trending RSI aims to enhance the conventional RSI by adding trend insights directly into the oscillator, addressing the gap that traditional RSI leaves regarding market trends. This version of RSI breaks away from the 0 to 100 range, offering bands and a center line that better represent market conditions. It includes a set of features like the Binomial MA for momentum analysis, configurable settings for divergence detection, and compatibility with multi-time frame analysis. The color customization and glow effects aim to improve visual clarity, and the inclusion of alerts is designed to streamline alert configuration. Overall, this indicator is designed to provide a more view of the markets, suitable for traders looking to incorporate trend analysis into their RSI-based strategies.
Enjoy
Kernel Regression RibbonKernel Regression Ribbon is a flexible, visually pleasing trend identification tool. Plotting 8 different kernel regressions of different types and parameters allows the user to see where levels of support and resistance are being tested, retested and broken.
What’s Kernel Regression?
A statistical method for estimating the best fitting curve for a dataset, in this case, a time/price chart.
How’s Kernel Regression different from a Moving Average?
A Moving Average is basically a simple form of Kernel Regression, in that it uses a fixed (Retangular) Kernel function. In an MA, all data points are weighted equally over its length. However, a Kernel function reacts more to data points that are closer to the current point. This means it will adapt more quickly to changes in data than an MA. Due to this adaptability, Kernel functions often form part of Machine Learning.
Using this indicator:
Explore the default Regular mode first to get a feel for the inputs, which are more numerous than for MAs. Try out different settings, filters and intervals to get the best out of each kernel. Not all parameters are available for each KR. There are info tips to explain this in the menu, but I’ve also included handy, optional labels on the chart for each KR as a more accessible guide.
Once you know your way round the Regular mode, check out the Presets and start changing the parameters of each kernel to your liking in the “User KR1, KR2, … “ mode. Each kernel type has its strong and weak points. Blending different kernels is where this indicator comes into its own. Give your charts a funky shine!
This indicator does NOT repaint.
This script acknowledges, and hopefully showcases, the great work of @veryfid Kernel Regression Toolkit.
Targets For Many Indicators [LuxAlgo]The Targets For Many Indicators is a useful utility tool able to display targets for many built-in indicators as well as external indicators. Targets can be set for specific user-set conditions between two series of values, with the script being able to display targets for two different user-set conditions.
Alerts are included for the occurrence of a new target as well as for reached targets.
🔶 USAGE
Targets can help users determine the price limit where the price might start deviating from an indication given by one or multiple indicators. In the context of trading, targets can help secure profits/reduce losses of a trade, as such this tool can be useful to evaluate/determine user take profits/stop losses.
Due to these essentially being horizontal levels, they can also serve as potential support/resistances, with breakouts potentially confirming new trends.
In the above example, we set targets 3 ATR's away from the closing price when the price crosses over the script built-in SuperTrend indicator using ATR period 10 and factor 3. Using "Long Position Target" allows setting a target above the price, disabling this setting will place targets below the price.
Users might be interested in obtaining new targets once one is reached, this can be done by enabling "New Target When Reached" in the target logic setting section, resulting in more frequent targets.
Lastly, users can restrict new target creation until current ones are reached. This can result in fewer and longer-term targets, with a higher reach rate.
🔹 Dashboard
A dashboard is displayed on the top right of the chart, displaying the amount, reach rate of targets 1/2, and total amount.
This dashboard can be useful to evaluate the selected target distances relative to the selected conditions, with a higher reach rate suggesting the distance of the targets from the price allows them to be reached.
🔶 DETAILS
🔹 Indicators
Besides 'External' sources, each source can be set at 1 of the following Build-In Indicators :
ACCDIST : Accumulation/distribution index
ATR : Average True Range
BB (Middle, Upper or Lower): Bollinger Bands
CCI : Commodity Channel Index
CMO : Chande Momentum Oscillator
COG : Center Of Gravity
DC (High, Mid or Low): Donchian Channels
DEMA : Double Exponential Moving Average
EMA : Exponentially weighted Moving Average
HMA : Hull Moving Average
III : Intraday Intensity Index
KC (Middle, Upper or Lower): Keltner Channels
LINREG : Linear regression curve
MACD (macd, signal or histogram): Moving Average Convergence/Divergence
MEDIAN : median of the series
MFI : Money Flow Index
MODE : the mode of the series
MOM : Momentum
NVI : Negative Volume Index
OBV : On Balance Volume
PVI : Positive Volume Index
PVT : Price-Volume Trend
RMA : Relative Moving Average
ROC : Rate Of Change
RSI : Relative Strength Index
SMA : Simple Moving Average
STOCH : Stochastic
Supertrend
TEMA : Triple EMA or Triple Exponential Moving Average
VWAP : Volume Weighted Average Price
VWMA : Volume-Weighted Moving Average
WAD : Williams Accumulation/Distribution
WMA : Weighted Moving Average
WVAD : Williams Variable Accumulation/Distribution
%R : Williams %R
Each indicator is provided with a link to the Reference Manual or to the Build-In Indicators page.
The latter contains more information about each indicator.
Note that when "Show Source Values" is enabled, only values that can be logically found around the price will be shown. For example, Supertrend , SMA , EMA , BB , ... will be made visible. Values like RSI , OBV , %R , ... will not be visible since they will deviate too much from the price.
🔹 Interaction with settings
This publication contains input fields, where you can enter the necessary inputs per indicator.
Some indicators need only 1 value, others 2 or 3.
When several input values are needed, you need to separate them with a comma.
You can use 0 to 4 spaces between without a problem. Even an extra comma doesn't give issues.
The red colored help text will guide you further along (Only when Target is enabled)
Some examples that work without issues:
Some examples that work with issues:
As mentioned, the errors won't be visible when the concerning target is disabled
🔶 SETTINGS
Show Target Labels: Display target labels on the chart.
Candle Coloring: Apply candle coloring based on the most recent active target.
Target 1 and Target 2 use the same settings below:
Enable Target: Display the targets on the chart.
Long Position Target: Display targets above the price a user selected condition is true. If disabled will display the targets below the price.
New Target Condition: Conditional operator used to compare "Source A" and "Source B", options include CrossOver, CrossUnder, Cross, and Equal.
🔹 Sources
Source A: Source A input series, can be an indicator or external source.
External: External source if 'External" is selected in "Source A".
Settings: Settings of the selected indicator in "Source A", entered settings of indicators requiring multiple ones must be comma separated, for example, "10, 3".
Source B: Source B input series, can be an indicator or external source.
External: External source if 'External" is selected in "Source B".
Settings: Settings of the selected indicator in "Source B", entered settings of indicators requiring multiple ones must be comma separated, for example, "10, 3".
Source B Value: User-defined numerical value if "value" is selected in "Source B".
Show Source Values: Display "Source A" and "Source B" on the chart.
🔹 Logic
Wait Until Reached: When enabled will not create a new target until an existing one is reached.
New Target When Reached: Will create a new target when an existing one is reached.
Evaluate Wicks: Will use high/low prices to determine if a target is reached. Unselecting this setting will use the closing price.
Target Distance From Price: Controls the distance of a target from the price. Can be determined in currencies/points, percentages, ATR multiples, ticks, or using multiple of external values.
External Distance Value: External distance value when "External Value" is selected in "Target Distance From Price".
