True Adaptive-Lookback Phase Change Index [Loxx]Previously I posted a Phase Change Index using Ehlers Autocorrelation Periodogram Algorithm to tease out the adaptive periods. You can find the previous version here: . This new version is also adaptive but uses a different method to derive the adaptive length inputs. This adaptive method derives period inputs by counting pivots from past candles. This version also relies on Jurik Smoothing to generate the final signal. I named this one "true" because I should have specified in the previous PCI's title that it's powered by Ehlers Autocorrelation Periodogram. Additionally, you'll notice the ALB algorithm has changed from other indicators, This is restrict the range of possible ALB period outputs to a specific range so the indicator is usable.
And remember, this is an inverse indicator. This means that small values on the oscillator indicate bullish sentiment and higher values on the oscillator indicate bearish sentiment.
What is the Phase Change Index?
Based on the M.H. Pee's TASC article "Phase Change Index".
Prices at any time can be up, down, or unchanged. A period where market prices remain relatively unchanged is referred to as a consolidation. A period that witnesses relatively higher prices is referred to as an uptrend, while a period of relatively lower prices is called a downtrend.
The Phase Change Index ( PCI ) is an indicator designed specifically to detect changes in market phases.
This indicator is made as he describes it with one deviation: if we follow his formula to the letter then the "trend" is inverted to the actual market trend. Because of that an option to display inverted (and more logical) values is added.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
Included:
Bar coloring
2 signal variations w/ alerts
Wyszukaj w skryptach "one一季度财报"
Multiple Moving Avg MTF TableThis script replaces the other script that was just the SMAs that where in a Multi Time Frame Table as this was a redo of that one and this one is SO MUCH MORE!!!!
Not only does this one do the Simple Moving Avg 5, 10, 20, 50, 120, 200 into a table that shows Current/Hourly/Daily/Weekly/Monthly/Quarterly ( 3M )/ Yearly. It now does Exponential Moving Avg , Weighted Moving Avg , and Volume Weight Moving Avg along with Simple Moving Avg.
I still use this script so that you can quickly capture the values so that short-term, and long-term resistance and support can be determined during market hours. Even better now you can select between SMA / EMA / WMA /or VWMA .
imgur.com
The table will change to the values based on the Choice of the type of Moving Avg and if you change the default values.
Now it will take a little bit for the table to show up, so please be patient. I have tested it with stocks, forex, and crypto.
Key Performance IndicatorWe are happy to introduce the Key Performance Indicator by Detlev Matthes. This is an amazing tool to quantify the efficiency of a trading system and identify potential spots of improvement.
Abstract
A key performance indicator with high explanatory value for the quality of trading systems is introduced. Quality is expressed as an indicator and comprises the individual values of qualitative aspects. The work developing the KPI was submitted for the 2017 VTAD Award and won first prize.
Introduction
Imagine that you have a variety of stock trading systems from which to select. During backtesting, each trading system will deliver different results with regard to its indicators (depending on, inter alia, its parameters and the stock used). You will also get different forms of progression for profit development. It requires great experience to select the “best” trading system from this variety of information (provided by several indicators) and significantly varying equity progression forms. In this paper, an indicator will be introduced that expresses the quality of a trading system in just one figure. With such an indicator, you can view the results of one backtest at a glance and also more easily compare a variety of backtesting results with one another.
If you are interested in learning more about the calculations behind this indicator then I have included a link to the english version of his research paper.
Along with this, we now offer indicator development services. If you are interested in learning more then feel free to reach out to get a quote for your project.
**Please note that we have NOT inputted any real strategy into the code and therefore it is not producing any real value. Feel free to change the code as desired to test any strategy!**
drive.google.com
Double CCIWith this variant of the CCI indicator you have 2 CCIs. I call it convenience the fast and the slow.
The slow one has the default period of 20. The fast one has a lower value and will therefore also change his direction much faster.
I don't use this as a decisive indicator, but the fast one does indicate where the standard CCI might go and so you are already prepared for the decisive moment.
I've added a zero line so you can visually track whether the buyers or the sellers are predominant.
Between 0 and +100, as well as between 0 and -100 there is still a battle between buyers and sellers and it is better to wait a little longer before entering a trade.
From +100 to +250 I have colored the zone green; here the buyers are winning and it is a confirmation that you can safer enter the BUY.
From -100 to -250 it's colored red; here the sellers are firmly winning and it is a confirmation to go into a SELL.
Most values are adjustable via the settings and can be switched on or off.
This indicator is not intended to be used as the sole decision element, but rather to fine-tune your entry and exit points . Maybe wait a little longer than you normally would, but then be able to step in at the right time that there is enough volume in your desired direction.
Good luck with it and I would love feedback.
Thank you Tradingview-community.
R-sqrd Adapt. Fisher Transform w/ D. Zones & Divs. [Loxx]The full name of this indicator is R-Squared Adaptive Fisher Transform w/ Dynamic Zones and Divergences. This is an R-squared adaptive Fisher transform with adjustable dynamic zones, signals, alerts, and divergences.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
What is R-squared Adaptive?
One tool available in forecasting the trendiness of the breakout is the coefficient of determination ( R-squared ), a statistical measurement.
The R-squared indicates linear strength between the security's price (the Y - axis) and time (the X - axis). The R-squared is the percentage of squared error that the linear regression can eliminate if it were used as the predictor instead of the mean value. If the R-squared were 0.99, then the linear regression would eliminate 99% of the error for prediction versus predicting closing prices using a simple moving average .
R-squared is used here to derive an r-squared value that is then modified by a user input "factor"
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included:
Bar coloring
4 signal variations w/ alerts
Divergences w/ alerts
Loxx's Expanded Source Types
Dynamic Zones Polychromatic Momentum Candles [Loxx]Dynamic Zones Polychromatic Momentum Candles is a candle coloring, momentum indicator that uses Jurik Filtering and Dynamic Zones to calculate the monochromatic color between two colors.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
Loxx's Expanded Source Types
Double Dynamic Zone RSX [Loxx]Double Dynamic Zone RSX is a Juirk RSX RSI indicator using Leo Zamansky and David Stendahl's Dynamic Zones to determine breakouts, breakdowns, and reversals.
What is RSX?
RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurik RSX retains all the useful features of RSI , but with one important exception: the noise is gone with no added lag.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph.D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
VWAP + EMA Analysis [Joshlo]Overview and Use Case
VWAP Analysis gives the possibility to combine multiple time frames of VWAP along with a triplet of exponential moving averages. This can provide insight into potential scalp, swing and longer term trades, depending on your time frame. The use of this indicator with it's setup is based off the the Scalp Setup Alerts provided by Roensch Capital.
The primary use for this script is to help with intraday scalp set ups. Using the Daily VWAP, turned on by default, we can look for price to respect and bounce from one of the VWAP lines (support or resistance) back toward equilibrium, we can also look for price to bounce off of equilibrium and move back toward VWAP support or resistance.
The chart attached shows AMD bouncing off of the Daily time frame VWAP Resistance level multiple times (see yellow boxes), often with confirmation given by an increase in volume which is often far higher than the average volume. In many of these cases a short position could've been opened or put option could have been placed with a profitable outcome.
Every line projected onto the chart via this indicator has the potential to create support or resistance as well as causing 'hang ups', meaning price loses it's momentum, slows down and hangs out in the particular area. This is shown on the chart within the green box.
Chart walkthrough - See attached chart
After a rejection off of the Daily VWAP Resistance line (depicted by the white circle), price starts to move back toward Daily VWAP Equilibrium. In order to reach this line, price needs to move through the 20EMA (white) and 50EMA (purple), the Weekly VWAP Resistance (red circles) and the 200EMA (orange). All of these lines are a part of this single indicator.
The 20EMA seems to offer little resistance but follows the price on it's move, offering some resistance to a volatile move upward. Initially upon contact with the 50EMA, price hangs up and bounces above and below the line whilst finding support on the Weekly VWAP Resistance at the same time. This causes a 'hang up' or sideways movement for around 20 minutes of trading. A potential trade may have entered at the white circle with a VWAP Resistance rejection and exited upon contact with the 50EMA in anticipation of multiple EMAs and support / resistance lines converging which is known to cause price movement to slow.
Eventually with an increase in volume, price breaks below the 20EMA (white), 50EMA (purple) and the Weekly VWAP Resistance level (red circles). Price then finds support on the 200EMA (orange), although there was potential for the price to fall to the Daily VWAP Equilibrium (solid blue). As the Red VWAP lines tend to act more often as resistance as opposed to support (price is rarely above these lines for extended periods), the trade from earlier may have profited more by awaiting contact with the 200EMA before exiting, taking the assumption that the Weekly VWAP Resistance was more likely to act as resistance than support.
A period of consolidation in the green box, around the Weekly VWAP Resistance, 20EMA, 50EMA and with support from the 200EMA eventually resulted in another break out where the price came back up to the Daily VWAP Resistance. Prior to the end of this trading day, there were two more opportunities for scalp setups based off of the price showing consistent rejections off the Daily VWAP Resistance back down to the 50EMA.
In the final example, price breaks above the Daily VWAP Resistance but quickly rejects off of the Monthly VWAP Resistance. For examples where the VWAP Resistance or Support or broken, it can help to look at an indicator such as the RSI to look for bullish divergence or bearish divergence.
Just as this example shows bounces and rejection off of VWAP Resistance, the same applies around the Equilibrium and Support VWAP lines.
The perfect scenario would be to find a ticker where there has already been two or three bounces off of one of these levels, with the goal of taking the trade on the next bounce and either using a percentage price target or technical price target based off of the EMAs or VWAP lines. If there are EMAs close in the direction you want to take the trade, there is a higher chance of hang ups and reversals, so a clear run is the more desired trade set up.
You can also look for these indicator lines to stack up in order to form a stronger support and resistance. For example the 200EMA and Daily VWAP Equilibrium being close to each other may suggest it would take more of an effort to break both of these levels, but one by itself may break more easily.
Indicator Setup
In the settings for the indicator, almost everything you might want to change can be done from the Input tab.
The three options for VWAP (daily, weekly and monthly) allow for analysis on multiple time frames. Daily is turned on as standard.
Standard Deviation Multiplier is set to 2 as standard, this effects the distance of the VWAP support and resistance from the equilibrium line. This seems to be a level that works well with finding support and resistance lines, however if there is excessively high or low volume, occasionally the lines can be thrown off. You can adjust this level if required to find a 'sweet spot' where price likes to reject or find support.
The colors for all VWAPs can be adjusted via the Inputs tab, however if you'd like to change the type of line these are depicted as, this can be done from the Styles tab.
The 3 EMAs (20, 50 and 200) can be toggled on or off and also have their color changed. The style of the lines can be adjusted from with the Styles tab if required.
.srb suiteThe essential suite Indicator.
that are well integrated to ensure visibility of essential items for trading.
it is very cumbersome to put symbol in the Tradingview chart and combine essential individual indicators one by one.
Moreover even with such a combination, the chart is messy and visibility is not good.
This is because each indicator is not designed with the others in mind.
This suite was developed as a composite-solution to that situation, and will make you happy.
designed to work in the same pane with open-source indicator by default.
Recommended visual order ; Back = .srb suite, Front = .srb suite vol & info
individually turn on/off only what you need on the screen.
BTC-agg. Volume
4 BTC-spot & 4 BTC-PERP volume aggregated.
It might helps you don't miss out on important volume flows.
Weighted to spot trading volume when using PERP+spot volume .
If enabled, BTC-agg.Vol automatically applied when selecting BTC-pair.
--> This is used in calculations involving volumes, such as VWAP.
Moving Average
1 x JMA trend ribbon ; Accurately follow short-term trend changes.
3 x EMA ribbon ; zone , not the line.
MA extension line ; It provide high visibility to recognize the direction of the MA.
SPECIAL TOOLS
VWAP with Standard Deviation Bands
VWAP ruler
BB regular (Dev. 2.0, 2.5)
BB Extented (Dev. 2.5, 3.0, 3.5)
Fixed Range Volume Profile ; steamlined one, performace tuned & update.
SPECIAL TOOLS - Auto Fibonacci Retracement - New GUI
'built-in auto FBR ' has been re-born
It shows - retracement Max top/ min bottom ; for higher visibility
It shows - current retracement position ; for higher visibility
The display of the Fib position that exceeds the regular range is auto-determined according to the price.
tradingview | chart setting > Appearance > Top margin 0%, Bottom margin 0% for optimized screen usage
tradingview | chart setting > Appearance > Right margin 57
.srb suite vol & info --> Visual Order > Bring to Front
.srb suite vol & info --> Pin to scale > No scale (Full-screen)
Visual order ; Back = .srb suite, Front = .srb suite vol & info
1. Fib.Retracement core is from tradingview built-in FBR ---> upgrade new-type GUI, and performance tuned.
2. Fixed-range volume-profile core is from the open-source one ---> some update & perf.tuned.
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if you have any questions freely contact to me by message on tradingview.
but please understand that responses may be quite late.
Special thanks to all of contributors of community.
The script may be freely distributed under the MIT license.
Genesis Matrix [Loxx]Over a decade ago, the Genesis Matrix system was one of best strategies for new traders looking to learn how to really trade trends. Fast forward to 2022, a new version of Genesis Matrix has emerged using TVI, CCI, HL Channel & T3
What is T3?
The T3 moving average is an indicator of an indicator since it includes several EMAs of another EMA. Unlike any other moving average, it adds the so-called volume factor, a value between 0 and 1. Like the SMA, traders typically use this indicator to spot trends and trend reversals.
What is CCI?
The Commodity Channel Index ( CCI ) measures the current price level relative to an average price level over a given period of time. CCI is relatively high when prices are far above their average. CCI is relatively low when prices are far below their average. Using this method, CCI can be used to identify overbought and oversold levels.
Genesis matrix uses Jurik-Smoothed CCI w/ MA Deviation--a spin on regular CCI .Usually CCI is calculated as using average ( Simple Moving Average ) and mean deviation. In this version, average is replaced with well known JMA (Jurik Moving Average) instead for the smoothing phase and the deviation is replaced with variety moving average deviation. The result in this one is responsive and fast (as expected) and also it is smoother than the original CCI (as expected).
What is SSL?
Known as the SSL, the Semaphore Signal Level channel chart alert is an indicator that combines moving averages to provide you with a clear visual signal of price movement dynamics. In short, it's designed to show you when a price trend is forming. For our purposes here, SSL has been modified to allow for different moving average selection and different closing price look back periods.
What is William Blau Ergodic Tick Volume?
This is one of the techniques described by William Blau in his book "Momentum, Direction and Divergence" (1995). If you like to learn more, we advise you to read this book. His book focuses on three key aspects of trading: momentum, direction and divergence. Blau, who was an electrical engineer before becoming a trader, thoroughly examines the relationship between price and momentum in step-by-step examples. From this grounding, he then looks at the deficiencies in other oscillators and introduces some innovative techniques, including a fresh twist on Stochastics. On directional issues, he analyzes the intricacies of ADX and offers a unique approach to help define trending and non-trending periods.
William Blau's definition of TVI ergodicity is that the indictor is ergodic when periods are set to 32, 5, 1, and the signal is set to 5. Other combinations are not ergodic, according to Blau.
How to use
Long signal: All 4 indicators turn green
Short signal: All 4 indicators turn red
Included
Bar coloring
Phase-Accumulation Adaptive RSX w/ Expanded Source Types [Loxx]Phase-Accumulation Adaptive RSX w/ Expanded Source Types is a Phase Accumulation Adaptive Jurik RSX.
What is RSX?
RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI , but with one important exception: the noise is gone with no added lag.
What is Phase Accumulation?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
Included:
-Toggle on/off bar coloring
Polynomial Regression Extrapolation [LuxAlgo]This indicator fits a polynomial with a user set degree to the price using least squares and then extrapolates the result.
Settings
Length: Number of most recent price observations used to fit the model.
Extrapolate: Extrapolation horizon
Degree: Degree of the fitted polynomial
Src: Input source
Lock Fit: By default the fit and extrapolated result will readjust to any new price observation, enabling this setting allow the model to ignore new price observations, and extend the extrapolation to the most recent bar.
Usage
Polynomial regression is commonly used when a relationship between two variables can be described by a polynomial.
In technical analysis polynomial regression is commonly used to estimate underlying trends in the price as well as obtaining support/resistances. One common example being the linear regression which can be described as polynomial regression of degree 1.
Using polynomial regression for extrapolation can be considered when we assume that the underlying trend of a certain asset follows polynomial of a certain degree and that this assumption hold true for time t+1...,t+n . This is rarely the case but it can be of interest to certain users performing longer term analysis of assets such as Bitcoin.
The selection of the polynomial degree can be done considering the underlying trend of the observations we are trying to fit. In practice, it is rare to go over a degree of 3, as higher degree would tend to highlight more noisy variations.
Using a polynomial of degree 1 will return a line, and as such can be considered when the underlying trend is linear, but one could improve the fit by using an higher degree.
The chart above fits a polynomial of degree 2, this can be used to model more parabolic observations. We can see in the chart above that this improves the fit.
In the chart above a polynomial of degree 6 is used, we can see how more variations are highlighted. The extrapolation of higher degree polynomials can eventually highlight future turning points due to the nature of the polynomial, however there are no guarantee that these will reflect exact future reversals.
Details
A polynomial regression model y(t) of degree p is described by:
y(t) = β(0) + β(1)x(t) + β(2)x(t)^2 + ... + β(p)x(t)^p
The vector coefficients β are obtained such that the sum of squared error between the observations and y(t) is minimized. This can be achieved through specific iterative algorithms or directly by solving the system of equations:
β(0) + β(1)x(0) + β(2)x(0)^2 + ... + β(p)x(0)^p = y(0)
β(0) + β(1)x(1) + β(2)x(1)^2 + ... + β(p)x(1)^p = y(1)
...
β(0) + β(1)x(t-1) + β(2)x(t-1)^2 + ... + β(p)x(t-1)^p = y(t-1)
Note that solving this system of equations for higher degrees p with high x values can drastically affect the accuracy of the results. One method to circumvent this can be to subtract x by its mean.
Jurik CFB Adaptive, Elder Force Index w/ ATR Channels [Loxx]Jurik CFB Adaptive, Elder Force Index w/ ATR Channels is a variation of Elder Force Index that better adapts to trends by calculating dynamic lengths for the traditional Elder Force Index calculation. ATR channels are added to show levels of price extremes or exhaustion of price either up or down. Elder Force Index is typically used for spotting reversals on the weekly timeframe.
What is the Elder Force Index?
Dr. Alexander Elder is one of the contributors to a newer generation of technical indicators. His force index is an oscillator that measures the force, or power, of bulls behind particular market rallies and of bears behind every decline.1
The three key components of the force index are the direction of price change, the extent of the price change, and the trading volume. When the force index is used in conjunction with a moving average, the resulting figure can accurately measure significant changes in the power of bulls and bears.1 In this way, Elder has taken an extremely useful solitary indicator, the moving average, and combined it with his force index for even greater predictive success.
What is Composite Fractal Behavior ( CFB )?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
Buy/Sell on the levelsThis script is generally
My describe is:
There are a lot of levels we would like to buy some crypto.
When the price has crossed the level-line - we buy, but only if we have the permission in array(2)
When we have bought the crypto - we lose the permission for buy for now(till we will sell it on the next higher level)
When we sell some crypto(on the buying level + 1) we have the permission again.
There also are 2 protect indicators. We can buy if these indicators both green only(super trend and PIVOT )
Jun 12
Release Notes: Hello there,
Uncomment this section before use for real trade:
if array.get(price_to_sellBue, i) >= open and array.get(price_to_sellBue, i) <= close// and
//direction < 0 and permission_for_buy != 0
Here is my script.
In general - this is incredible simple script to use and understand.
First of all You can see this script working with only long orders, it means we going to get money if crypto grows only. Short orders we need to close the position on time.
In this script we buy crypto and sell with step 1% upper.
You can simply change the step by changing the price arrays.
Please note, if You want to see where the levels of this script is You Have to copy the next my indicator called LEVEL 1%
In general - if the price has across the price-level we buy some crypto and loose permission for buying for this level till we sell some crypto. There is ''count_of_orders" array field with value 2. When we bought some crypto the value turns to 0. 0 means not allowed to by on this level!!! The script buy if the bar is green only(last tick).
The script check every level(those we can see in "price_to_sellBue" array).
If the price across one of them - full script runs. After buying(if it possible) we check is there any crypto for sell on the level.
We check all levels below actual level( of actual level - ''i'' than we check all levels from 0 to i-1).
If there is any order that has value 0 in count of orders and index <= i-1 - we count it to var SELL amount and in the end of loop sell all of it.
Pay attention - it sells only if price across the level with red bar AND HAS ORDERS TO SELL WHICH WAS BOUGHT BELOW!!!
In Strategy tester it shows not-profitables orders sometimes, because if You have old Long position - it sells it first. First in - first out.
If the price goes down for a long time and You sell after 5 buys You sell the first of it with the highest value.
There is 2 protection from horrible buying in this strategy. The first one - Supertrend. If the supertrend is red - there is no permission for buy.
The second one - something between PIVOT and supertrend but with switcher.
If the price across last minimum - switcher is red - no permission for buy and the actual price becomes last minimum . The last maximum calculated for last 100 bars.
When the price across last maximum - switcher is green, we can buy. The last minimum calculation for last 100 bars, last maximum is actual price.
This two protections will save You from buying if price get crash down.
Enjoy my script.
Should You need the code or explanation, You have any ideas how to improve this crypt, contact me.
Vladyslav.
Jun 12
Release Notes: Here has been uncommented the protection for buy in case of price get down.
5 hours ago
Release Notes: Changed rages up to actual price to make it work
Cipher Twister - Long and ShortINTRO / NOTES:
This script is based on Market Cipher B Oscillator by Falcon
The difference in this script is that only the useful points are printed on the indicator, namely Long and Short Trade Execution signals to be used by a bot, namely the PT Bot.
The script also differs from the original that it has been upgraded to Pinescript v4
This oscillator can be used with ALL time frames, but generally works the best on 15 minute and 1 hour charts on ANY market, no matter, stock, forex, crypto, spot, futures, derivatives, Nasdaq etc...
DEFINITIONS:
This oscillator forms the foundation of Buy and Exit of Long and Short Trades.
There are 2 'Red' Lines at the top of the channel and 2 Green Lines at the bottom of the channel.
These two channels are set at default to be +53 / -53 and +60 / -60 respectively. These two lines will serve as the threshold point if one is to make cautious trades only.
There is a center line which divides the Oscillator into two parts. Above the center line, the market is in over bought territory and Below the center line is in over sold territory.
'Red' dots are drawn by the indicator to represent a potential Short (or a signal to exit from a Long position)
'Green' dots are drawn by the indicator to represent a potential Long (or a signal to exit from a Short position)
The 'Red' and 'Green' dots are draw when a Cross between both wt1 & wt2 cross, thus providing a fantastic indication of potential trend reversal and entry/exit of a position.
STRATEGY NOTES:
The strategy to use this indicator with for realistic and proper results would be to use it with an automated Trading Bot such as Profit Trailer (PT-BOT)
You could use this strategy manually, however it would mean you would need to sit in front of the screen all day and night long and activate the trades immediately after the 'red'/'green' dots are drawn. Usually this will result in non-optimal entries and exits as well as loss on various instances when a 'red' and 'green' dot are printed close together (which is usually when the market goes into correction/consolidation) and slow entries/exits will result in a loss rather than a small profit or exit at BE (Break Even)
ACTUAL STRATEGY (For use with automated bot)
To be used in conjunction with Heikin Ashi Candles for added cautionary measures
For LONGs ONLY
--------------------
1/ When 'Green' dot is drawn, ACTIVATE Long Position
(Use 1.5% Risk Management for each trade)
(Use Lot size based on 1.5% risk management and xLeverage (if any))
2/ Make sure bot Opens an SL (Stop Loss) value based on 1.5% Risk Management
3/ When 'Red' dot is drawn, CLOSE Long Position.
*If you want to add extra caution to your trade, only activate the trade if the 'Green' dot is BELOW the 'Green' Markers
*For added caution, use color coded Heikin Ashi candles to 'confirm' Activation and Closing of a trade in the bot configuration
---------------------------------------------------------------------------------------------------
For SHORTs ONLY
--------------------
1/ When 'Red' dot is drawn, ACTIVATE Short Position
(Use 1.5% Risk Management for each trade)
(Use Lot size based on 1.5% risk management and xLeverage (if any))
2/ Make sure bot Opens an SL (Stop Loss) value based on 1.5% Risk Management
3/ When 'Green' dot is drawn, CLOSE Short Position
*If you want to add extra caution to your trade, only activate the trade if the 'Red' dot is Above the Red Markers
*For added caution, use color coded Heikin Ashi candles to 'confirm' Activation and Closing of a trade in the bot configuration
---------------------------------------------------------------------------------------------------
Supplementary Notes:
Make sure that your bot configuration will only activate ONE TRADE when the 'Green'/'Red' dot appears.
Occasionally during high volatility , 'red'/'green' dots will appear intermittently before remaining drawn, thus the oscillator 'redraws' the dots during market movement.
There will be times where occasionally a 'green' dot or a 'red' dot will appear, the trade will be opened, but the trade will fail due to the market manipulation (algorithm/market maker bots/fake volume etc), to wipe out those trading on derivatives and futures markets using leverage. Do not worry about this, no bot can make 100% wins, no strategy will achieve 100% win ratio and one necessarily doesn't need a high win ratio when using strict money management practices with your trading for SL and lot size.
If you use this method, you will see great results, but again I must stress, using this method with a fully automated bot is the only way to achieve proper results.
Traling.SL.TargetTrailing SL and Target
I have seen few requests in PineScripters telegram group asking questions about implementation of trailing stop-loss (SL) and targets. This script is one of the way to implement the same.
This script is developed based on dark color theme and is best viewed using dark color theme.
How and where can this script be used:
The script is built to demonstrate how one can implement the trailing SL and target, so by referring the script one can mimic the approach and add trailing SL and target implementation in their own strategy.
How it works:
To demonstrate the SL and target implementation, i have considered simple EMA crossover strategy.
Key Input Parameters
Method to use for SL/Target trailing:
1. % Based Target and SL - Used to calculate trailing based on parameters defined under group '% Based Target SL'
2. Fixed point Based Target and SL - Used to calculate trailing based on parameters defined under group 'Fixed point Based Target and SL'
% Based Target and SL:
Initial profit % - This is used to calculate target when trade is initiated
Initial SL % - This is used to calculate SL when trade is initiated
Initiate trailing % - This parameter determines, when to start trailing SL and target.
Trail profit by % - Target would be trailed by % specified as this parameter
Trail SL by % - SL would be trailed by % specified as this parameter
e.g.
Trade type: - Long
Trade price: 10000
initial profit %: 1
Initial SL %: 1
Initiate trailing %: 0.5
Trail profit by %: 0.3
Trail SL by %: 0.4
Calculations based on above:
initial profit %: 10100 (trade price + 1%)
Initial SL %: 9900 (trade price - 1%)
Initiate trailing %: 10049.5 (initial profit - 0.5%)
Trail profit by %: 10130 (initial profit + 0.3%)
Trail SL by %: 9939.6 (initial SL + 0.4%)
For next iteration of Trailing SL and target above calculated values will be taken as a base and next set of values will be calculated. these calculations will continue till the trade is exited either on price reaching profit or SL point.
Fixed point Based Target and SL:
Initial profit target points - To derive initial target, parameter value is added to trade price in case of long trade.
Initial SL points - To derive SL point, parameter value is subtracted from trade price
Initiate trailing points - To derive start of trailing logic, parameter value is subtracted from initial profit point.
Trail profit by points - In case of long trade, parameter value is added to the profit target to derive new trailed profit target.
Trail SL by % - In case of long trade, parameter value is added to the SL initial point to derive new trailed SL.
Calculation of Trailing SL and target will continue till the trade is exited either on price reaching profit or SL point.
Plots displayed on the chart:
Apart from default trade markings i have added 3 shapes on the chart to describe working of Trailing SL and targets.
Diamond shape marks - These are added on the chart when trade is initiated. These shapes gives additional trade information by way of 'tooltip'. This information can be viewed by placing mouse pointer on the shape.
Circle shape marks - These are added on the chart whenever Trailing SL and targets are calculated. These shapes gives additional trade information by way of 'tooltip'. This information can be viewed by placing mouse pointer on the shape. You will also notice a number displayed just above or below circle denoting Trailing iteration.
Labels up and label down shapes - These are dynamically placed on the chart whenever trade is in progress. These labels will display ongoing trades, Target and SL points.
LNL Squeeze ArrowsIf you struggle with the entries, low % win rate or trading the squeeze setup overall, this indicator is for you!
If you look closely at your losing trades, chances are the losers have one thing in common = inverse momentum. I created this tool after I found out that Stacked EMAs and picture perfect trend is not the only thing you need for a squeeze setup. Squeeze arrows pinpoint the exact moment where the squeeze momentum change happens (momentum change is absolutely crucial for the squeeze setup). These arrows will help you stay out of "everything was aligned but still failed" type of setups.
Squeeze Arrows:
1. Momentum Arrows (cyan blue/red) - Showing the best possible moment for an entry during the squeeze (after you see one, you can expect the squeeze to fire soon).
2. Slingshot Arrows (yellow) - Even though you can trade off of them, these arrows work mostly as a confirmation & caution tool. If an inverse slingshot arrow is plotted during a squeeze that means caution = you should wait because momentum is not on your side thus there there is a quite high probability that the squeeze can fire the other direction.
Squeeze Dots Trigger:
Represents the number of red dots (squeeze) after which the arrows should plot. Default = 5 (only after 5 red dots, arrows will appear), some traders like to set it on 3 or even 1.
Tips & Tricks:
1.Breakout or Bailout Mentality
- The big advantage of the arrows is the fact that they either work straight away or they don't. This is where you can apply the breakout or bailout mentality and really focus exclusively on the breakout part of the whole squeeze move. You can minimize the risk by putting mental stops just a few points below the last low of the candle where the arrows appeared. That way you can be stopped out even during the squeeze = won't hurt as much as when the squeeze fire the opposite direction. Reward may be the same but the risk is lower.
2. Yellow Flags
- Use the slingshot arrows as a caution tool. Even if all your squeeze criteria are met. Yellow inverse arrow = caution (wait for the true momentum change). Once the slingshot arrow appears in the conext of the trend, you are good to go.
3. Last Arrow Rule
- Sometimes you will see a lot of arrows during the longer squeezes. This is where the last arrow rule come in handy. The last arrow you see on chart can be canceled anytime by a new one. The last arrow is the valid one!
Hope you can squeeze from these squeeze arrows as much as there is to squeeze so you can finally trade the squeeze with ease.
Hope it helps.
Input Source█ OVERVIEW
This script demonstrates how your script can provide multiple input source selections while still allowing the use of an external indicator input.
█ CONCEPTS
There are occasions when one needs to provide script users with multiple input source selections while still allowing the selection of an external input. This is usually impossible because for external indicators to appear in an input widget's dropdown menu, only one input.source() call must be used in the script. If multiple calls are used, then no external indicator can be selected in any of the script's input widgets.
This script demonstrates how you can provide input sources offering a selection among the usual source built-ins ( open , high , low , close , hl2 , hlc3 , ohlc4 , hlcc4 ), but without the ability for users to select an external indicator. This allows your script to use multiple source inputs while still using one source input allowing the selection of an external input.
Look first. Then leap.
Z-Score DeltaHeavily modified from Z Score by jwammo12
Compares the z-score of two assets, the onscreen one and the reference one configured. If you're familiar, you can think of it as Bollinger Band Percent of Onscreen Asset minus the Bollinger Band Percent of Reference Asset.
It's compared off a simple moving average, due to how standard deviation is calculated.
I view this a more literal meaning of relative strength.
Has the ability to offset or delay in time one to another.
TODO: add MAD and MAD/STD.DEV views
Not my greatest work, but it's functional.
[CP]Pivot Boss Multi Timeframe CPR Inception with MACD and EMAINTRODUCTION:
This indicator combines multi-timeframe CPR bands with MACD Momentum and EMA trend, all projected on the candlestick chart through a novel visualization.
If you have seen my other indicators on TradingView, you would know that I use floor pivots a lot and “Secrets of a Pivot Boss” is my favorite book. While using floor pivots, time and again I have noticed an interesting price behavior,
Trending moves in price typically start from around the Central Pivot Range (CPR). The CPR could be from ANY timeframe. These moves can easily be caught using simple momentum and trend indicators like MACD and EMA crossovers.
Yes, it is that simple. Follow along to understand how to use this indicator.
INDICATOR SETTINGS:
RANGEBOUND MACD AND EMA MARKINGS:
TradingView limits the max number of labels that can be shown on a chart to 500. Therefore, if you go far back enough, you won't see any markings for the MACD or EMA setups. If you are looking to test the efficacy of this indicator in the past, change the start and end dates to your desired timeframe and then select the ‘Mark MACD and EMA Setups in Range?’ option.
MULTI TIMEFRAME CENTRAL PIVOT RANGE:
Here you can select CPRs and their bands from which timeframes are shown on the chart. I will share my favorite settings later in this description.
CPR CONFIGURATION:
Show CPR Labels: CPRs markings can carry labels, so that you don’t confuse between which line is what. Use this setting to toggle them On/Off.
Show Next Time Period Pivots: Check this option if you want to see the CPR of the next time period. This is typically done to figure out the ’Two Day CPR Relationship’ . Read the book, “Secrets of a Pivot Boss”, to understand more.
EMA TREND:
Show EMA on the Chart: EMAs will be plotted on the chart. Standard stuff.
Mark EMA Crossovers on Chart: EMA crossovers will be marked on the chart in diamond shapes. If you are using EMA crossovers, I recommend setting this option to True.
Rest of the EMA settings are fairly obvious.
MACD MOMENTUM:
Projecting MACD parameters directly on the candlesticks is surely going to give you a new perspective about price action and MACD.
Also, in order to better understand the MACD projections on the chart, you can add a standard MACD indicator on the chart with default settings to figure out what my indicator is actually showing you.
Marking MACD Crossovers on Chart: Marks the MACD signal crossovers on the chart. This visualization was a game changer for me.
Show MACD Histogram on Chart: Projects the complete MACD Histogram in a novel fashion (Try it!). You will be able to visually see the ebbs and flow of momentum in the charts.
Mark MACD Histogram Peaks on Chart: Marks only the MACD peaks instead of the complete histogram. Peaks are a great way to enter an ongoing trend and to play an intraday rangebound market.
Rest of the settings are just the standard settings that you will find in a typical MACD indicator.
ALERTS:
Not shown in the settings panel, but I have added alerts for EMA and MACD Crossovers so that you don’t have to sit in front of the charts or constantly check the price all day long.
If you don’t know how to set alerts in TradingView, then please Google it.
INDICATOR USAGE EXAMPLES:
This indicator can be used in intraday as well as in higher timeframes.
There are quite a few variations possible, I personally prefer to use the EMA crossovers in intraday (5m) and MACD on Daily timeframes.
This is just a matter of personal preference, some people might prefer using EMAs only or MACD only in all timeframes.
Here are my personal settings for the intraday 5-minute timeframe:
Turn on all the CPR pivots starting from Yearly all the way to Daily. You can turn on 6 hourly and 4 hourly as well if you want.
Hourly CPR is mostly used when the price is in a strong trend and you missed the entry and don’t know when to enter. Price will typically experience pullbacks towards the Hourly CPR, before resuming in the direction of the trend. That is your chance to hop onto the bandwagon.
For Intraday, I keep the Bands off. Just a personal preference here.
You can turn ON the Show CPR Labels , if you want.
Turn ON both the options in the EMA TREND section. You would want to see the EMA crossovers marked on the chart as well as the EMAs themselves, as the distance between the two EMAs will give you an idea about the strength of the trend.
Keep rest of the settings in the EMA section as default (you can change the colors if you wish). I keep the same EMAs as the ones kept in the MACD indicator. I like to keep things simple.
In the MACD MOMENTUM section, turn ON Mark MACD Histogram Peaks on Chart and all the other options turned OFF. Leave the other settings as default. By the way, these are the default settings of the standard MACD Indicator.
You can set up EMA Bullcross and Bearcross alarms if you like.
Before checking out the examples, remember one super simple rule:
SOME OF THE BEST TRENDING MOVES IN THE MARKET, BE IT INTRADAY OR OTHERWISE, ORIGINATE IN THE VICINITY OF A LARGER TIMEFRAME PIVOT/CPR.
Look for price settling above/below a pivot, and then a move away from the pivot in any direction is typically a trending move.
You can use hourly pivots or MACD Histogram peaks marked on the chart to enter an existing trend, or add to your positions.
Let’s have a look at a few recent intraday examples from the Crypto, Indian, and US equity markets.
I have added my comments in the charts to make you easily understand what is going on.
Understand that both, moving average crossover and MACD, will give out a lot of signals (chop) every day. But almost 70% of them are going to be fake signals. It is the signals that you get when the price is near a Pivot, that tend to convert into gorgeous trending moves that last.
BTC 5m Charts
NIFTY Futures 5m Charts (good intraday trends are hard to find here, as the market is very efficient)
TSLA 5m Charts
Some important points for using this indicator in higher timeframes:
For higher timeframes, my personal preference is to go with the MACD indicator. I personally find MACD to be lethal on daily and weekly timeframes, if you know how to use it well.
The default settings of the indicator are the settings I use for both, Daily and Weekly, timeframes. Additionally, I turn off the CPR labels.
In theory large trending moves still have a big probability to start near an important pivot level, however, in larger timeframes, trending moves can start from anywhere. They need not start in the vicinity of any important pivot (but they often do!).
Weekly pivots can act as great pullback levels when the price is in strong momentum, when trading on the daily timeframe.
Quarterly Pivots act as great pullback levels when the price is in strong momentum, when trading on the weekly timeframe.
BTC Weekly Chart
BTC Daily Chart
Nifty Weekly Chart
Nifty Daily Chart
NASDAQ Weekly Chart
NASDAQ Daily Chart
FINAL WORDS:
Please understand that I have Cherry Picked the examples to showcase the capability of the indicator and its usage.
DO NOT conflate the accuracy of examples with the accuracy of this indicator.
Biggest catch is the fact that this indicator, like every other indicator out there, will have whipsaws. Some I have also marked in the example charts.
You need to come up with your own technique to avoid whipsaws, one technique I have shared here…… big moves typically start near pivots.
Work on avoiding whipsaws and finding you own edge in the markets.
If you really want to learn how to use Pivots, read the book ’Secrets of a Pivot Boss’ . This book can change your life.
Volume CompressorTurns volume into a more informative representation, ready to be further analyzed
...
Rationale
Volume
Back in the "before the quant" days I was a big fan of market & volume profile. Thing is J. Steidlmayer had lotta different ideas & works aside of profiling, it's just most of them ain't got to mainstream, one of them was "Hot / Cold volume" (yes, you can't really google it). From my interpretation, the idea was that in a given asset there is a usual constant volume that stays there no matter what, and if it ever changes it changes very slow and gradually; and there's another kind of, so to say, 'active' volume that actually influences price dynamics and very volatile by its nature. So I've met concept lately, and decided to quantify & model it one day when I'll have an idea how. That day was yesterday.
Compression
When we do music we always use different kinds of filters (low-pass, high pass, etc) for equalization and filtering itself. That stuff we use in finance as well. What we also always use in music are compressors, there dynamic processors that automatically adjust volume so it will be more consistent. Almost all the cool music you hear is compressed (both individual instruments (especially vocals) and the whole track afterwards), otherwise stuff will be too quite and too weak to flex on it, and also DJing it would be a nightmare. I am a big adept of loudness war. So I was like, how can I use compression in finance, when ima get an idea? That day was yesterday as well.
Volume structure
Being inspired by Steidlmayer's idea, I decided to distinguish volume this way:
1) Passive / static volume. The ~ volume that's always there no matter what (hedges, arbitrages, spread legs, portfolio parts etc etc), doesn't affect things;
2) Active / dynamic volume. The volume that flows from one asset to another, really matters and affects things;
3) Excess volume. The last portion of number 2 volume, that doesn't represent any powerful value to affect things.
Now it's clear that we can get rid of number 1 and number 3, the components that don't really matter, and concentrate on number 2 in order to improve information gain, both for ourselves and for the models we feed this data. How?
Model
I don't wanna explain it all in statistical / DSP way for once.
First of all, I think the population of volumes is log-normally distributed, so let's take logs of volumes, now we have a ~ normally distributed data. We take linearly weighted mean, add and subtract linearly weighted standard deviation from it, these would be our thresholds, the borders between different kinds of volumes explained before.
The upper threshold is for downward compression, that will not let volume pass it higher.
The lower threshold is for upward compression, all the volumes lower than this threshold will be brought up to the threshold's level.
Then we apply multipliers to the thresholds in order to adjust em and find the sweet spots. We do it the same way as in sound engineering when we don't aim for overcompression, we adjust the thresholds until they start to touch the signal and all good.
Afterwards, we delete all the number 1 and number 3 volume, leaving us exclusively with the clear main component, ready to be processed further.
We return the volumes to dem real scale.
About the parameters, based on testing I don't recommend changing the thresholds from dem default values, first of all they make sense statistically and second they work as intended.
Window length can and should be adjusted, find your own way, or leave the default value. ML (moving location) length is up to you as well.
So yeah, you can see now we can smooth the data and make it visually appealing not only by applying a smooth filter over it.
All good TV?
MTF Ichimoku Cross MonitorIchimoku Kinko Hyo is a technical analysis method that builds on candlestick charting to improve the accuracy of forecast price moves and Crossing TenkanSen ((HH + LL)/2 for the last 9 periods) & KijunSen (HH + LL)/2 for the last 26 periods) is One of major strategies on Ichimoku.
This Indicator build for Monitor Tenkansen & Kijunsen Lines status and you can watch 3 Time Frames Status on one bar and in one timeframe.
You can select timeframe and set Inputs for lines from Indicator setting.
Good trading to all ...
intraday_bondsStatistics for assisting with intraday bond trading, using five minute periods and one hour ranges. There are two tables, a volatility table and a correlation table. The correlation table shows the correlation of five minute returns (absolute) between the four different bond contracts that trade on the CME. The volatility table shows for each contract:
- The current realized volatility, based on the previous one hour of realized volatility. This figure is annualized for easy comparison with options contracts.
- The current realized volatility's z-score, based on all available data.
- The tick range of an "N" standard deviation move over one hour. Choose "N" using the stdevs input.
- The previous hour's true range (high - low).
The ranges are expressed in ticks.
