Entry helperHello traders,
This is a script I use daily as a scalper and it helps me a lot, maybe it can help you, this is why I am sharing it!
PART 1 - DESCRIPTION
This program is specifically designed to help scalpers but can be used for all types of trading but won't be as useful.
This script is what I call an entry helper as it calculates dynamically the position size, stop loss and take profit levels and more.
When scalping and placing market entry orders, the price can move significantely while you are calculating your position size according to your stop loss, capital, risk and especially close price that changes very quickly, this results in a risk that is not ideally controlled and personally was a source of frustration and stress. I wanted to enter my quantity and stop loss values as fast as possible and make the process easier.
This script automates the calculation of the position size, stop loss and take profit levels according the the users input and prints the data visibly on the screen so it is easy to copy by the trader. It allows the trader to be confident that his risk is as controlled as possible.
The script is easy to use and set up, this guide will help you if you have any difficulies or questions.
PART 2 - HOW TO USE THE SCRIPT
- SET THE CAPITAL SETTINGS
1 - Set your capital value in $
- SET THE TRADE SETTINGS
2 - Set your trade side (BUY or SELL)
3 - Set you desired risk in % of your capital
- ENTRY SETTINGS
4 - Set your entry from 2 different options
|MARKET| (default option)
This option will place the entry level at the last available price
|LIMIT|
This option allows you to input a fixed price level for the entry
- STOP LOSS SETTINGS
5 - Select your stop loss placement from 4 different options
|EXTREMA STOP LOSS| (default option)
This option will place the stop loss at the highest/lowest (extrema) price level within the last N candles
|ATR EXTREMA|
This option uses the same price level as the EXTREMA STOP LOSS but will add/soustract the last ATR value (calculated on the N last candles) multiplied by a coefficient that you input
|TICKS EXTREMA|
This option uses the same price level as the EXTREMA STOP LOSS but will add/soustract a number of ticks that you input
|PRICE LEVEL|
This option allows you to input a fixed price level for the stop loss
- TAKE PROFIT SETTINGS
6 - Select your take profit from 3 different options
|NONE| (default option)
This option will not display any take profit level, I have added this option as I don't have take profit targets
|RR|
This option uses a risk to reward ratio (reward/risk) that you input, it will automatically calculate the take profit level that corresponds
|PRICE LEVEL|
This option allows you to input a fixed price level for the take profit
- QUANTITY AND FEE SETTINGS
7 - Set the quantity settings, it represents the quantity in a lot (usually 100 000 in forex, 100 in stocks 1 for crypto currencies)
8 - Set the fee per quantity (turning lot)
- VISUAL SETTINGS
9 - Show or remove the tab
- TAB SETTINGS
10 - Select the data that you want to display in the tab (the tab will adapt automatically)
NOTES:
The vertical dashed line shows what candle has been used for the calculation of the stop loss, it allows you to visualize what candle the script has selected in case of an EXTREMA stop loss option.
I hope this helps you out! Any suggestions are welcome and I hope that the guide is clear enough.
Happy trading!
Dynamic
Dynamic Highest Lowest Moving AverageSimilar to my last script, although this one uses the RSI value of
(highest high - price) / (price - lowest low)
to feed into the the logic creating the dynamic length. Choose how the length curve works by selecting either Incline, Decline, Peak or Trough.
Lastly select the moving average type to filter the result through to smoothen things out a bit
to find something that works for your strategy. This is useful as an entry/exit indicator along with other moving averages, or even just a standalone if you play with the settings enough.
TwV Multi-timeframe Dynamic VRVPMulti-timeframe Dynamic Visible Range Volume Profile
The volume profile is an indicator that displays trading activity over a specified period and plots a histogram on the chart which reveals dominant and significant price levels based on volume and in essence gives a clear indication of Supply or demand at a certain price rather than volume in a certain period.
What makes this VRVP indicator different from other is that it is multi-timeframe and dynamic, meaning that it has the ability to show the POC for a higher timeframe and that it also recalculates the main POC every single time traders adjust the chart.
Most VRVP need to be adjusted to a fixed position for the Main POC, I made an improvement by giving the indicator the ability to identify the bars that are being look at in the screen, this really gives traders the possibility and agility to identify potential support and resistance areas without the need to be changing any settings on the indicator.
Furthermore, giving the ability to the indicator to be multi-timeframe allows traders not only to work with a point of control in one timeframe, but also have a dashed line plotting the Point of Control of a HIGHER timeframe, which could potentially be a strongest support or resistance. The multi-timeframe point of control is fixed only.
This VRVP is completely similar to the official Trading View paid subscription one.
Fundamentals
Point of Control (POC): The price level for the time period with the highest traded volume. The POC is represented by an amber line within the indicator.
Profile High: The highest reached price level during the specified time period
Profile Low: The lowest reached price level during the specified time period.
Value Area (VA): The range of price levels in which a specified percentage of all volume was traded during the time period. Typically, this percentage is set to 70% however it is up to the trader’s discretion.
Value Area High (VAH): The highest price level within the value area.
Value Area Low (VAL): The lowest price level within the value area.
Usage
The Resistance and Support levels can be provided by the Volume profile using a reactive method so they constantly change with price action and give a clearer picture to predict future price movements. The Reactive method relies on past price movements at certain price levels and applies a more significant understanding of price reaction at certain meaningful levels
Support levels will be areas where price will be supported on the way down.
Resistance levels will be areas that resist price on the way up.
A basic understanding of this is that Buyers will enter the market at the bottom of a profile and sellers will enter the market at the top of the profile.
Configuration
By the default the indicator has enabled plotting the charts timeframe Volume Profile.
Multi-timeframe option needs to be enabled and desired timeframe chosen from selector menu.
Bars back value for fixed calculation of the multi-timeframe point of control.
Traders can adjust default settings as follows:
Charts timeframe VRVP
Main POC color – Yellow
Positive Volume – Green
Negative Volume – Red
VRVP Width – 100 (Refers to the plotting width for better suiting on small screens)
Multi timeframe VRVP
Enable or disable calculations
Bars back - Fixed numbers of bars for calculation (Consider that max bars back limit is 5000, but it considers 5000 bars on the current charts timeframe, therefore traders need to take into consideration converting number of bars in higher timeframe to charts timeframe)
e.g.
Charts timeframe 15m – MTF desired 1H
1H = 60 min 15m = 15 min – 100 bars back equivalent to (60 min * 100) / 15 = 400
Lower than 5000 then calculations takes place, otherwise calculations will be disabled.
Multi-timeframe POC color = Light blue DASHED
Timeframe desired – 1H by default
Summary box
Enable or disable box
Box shows information regarding the exact price where Main POC and MTF POC reside
Table Size for better fitting on mobile devices
able Position for adjusting to each trader’s preference or use in combination with other indicators
Dynamic Array Table (versatile display methods)Library "datTable"
Dynamic Array Table.... Configurable Shape/Size Table from Arrays
Allows for any data in any size combination of arrays to join together
with:
all possible orientations!
filling all cells contiguously and/or flipping at boundaries
vertical or horizontal rotation
x/y axis direction swapping
all types array inputs for data.
please notify of any bugs. thanks
init(_posit)
Get Table (otional gapping cells)
Parameters:
_posit : String or Int (1-9 3x3 grid L to R)
Returns: Table
coords()
Req'd coords Seperate for VARIP table, non-varip coords
add
Add arrays to display table. coords reset each calc
uses displaytable object, string titles, and color optional array, and second line optional data array.
Papercuts Dynamic EMA - Relative Parameter FunctionThe goal of this is to link two parameters of different known low and high values so one affects the other.
In this case, I want to link Relative Volume to the length of an EMA, so it responds faster in times of high volume.
As an animator I am used to linking values in this way with Maya using a set driven key, took some work to figure it out in pine.
Looking up this concept, it has a few names, Relative values, linear interpolation, or rescale values.
Thanks to pinecoders for writing the EMA funciton that can accept length variables!
Here's a quick look at the root function to link the two values.
f_relativeVal(_source, in_bot, in_top, out_bot, out_top) =>
// float _source: input signal
// float in_bot : minimum range of input signal.
// float in_top : maximum range of input signal.
// float out_bot : minimum range of output signal.
// float out_top : maximum range of output signal.
clampSrc = _source > in_top ? in_top : _source < in_bot ? in_bot : _source //claps source to create a controlled range
//relInput = (clampSrc - in_bot) / (in_top - in_bot) * 100
inDiffIncrement = (in_top - in_bot)
outDiffIncrement = (out_top - out_bot)
out_bot + (clampSrc - in_bot) * outDiffIncrement / inDiffIncrement // rescale input range to output range
Pair Prowler [CR]Pair Prowler by Cryptorhythms
Intro
Members needed a new scalping indicator, so of course I listened and delivered. Pair prowler is not crypto specific and can be applied to a variety of timeframes, markets, and tickers. Its meant to be a general purpose scalping aid providing actionable signals that help you time the market.
Description
This indicator relies upon various methods relataed to probabilities, statistics and data science to predict optimal times to buy or sell any given time series data. The goal was to create a tool that isolated short form trades, making it easier to follow a noisy market. With built in safety features to help trades make smart decision real time when it matters. The focus is making high hit rate uncorrelated returns to your base market.
There are still a large list of features to implement on the indicator. Most of the parameters will be made dynamic needed no changing or interaction from the user. This will also help prevent potential overfits from over-enthusiastic optimization =)
Private
This indicator is reserved for our members only to prevent decay as long as possible. You can view my signature at the bottom of this post for more information on membership. Membership seats are also capped!
Dont worry, there are 2 new free public scripts coming as well in the near future!
Cosmic GravityCosmic Gravity draws dynamic non-repainting trendlines and helps
⭐ know when to scalp
⭐ predict the position and timing of the next major reversal
⭐ predict sudden changes in volatility
⭐ recognize if the trend is bearish or bullish
👀 HOW IT WORKS
Cosmic Gravity draws a dynamic channel consisting of a basis line and several support and resistance levels for low/medium/high volatility situations, as defined by the Inner Channel and 2 Outer Channel plots respectively. The script achieves this by reducing a large number of select moving averages, their multiples, and other trend levels into a single basis line and deriving the remaining plots off of it using ATR and probability-constant multiples. The basis line color is determined by its smoothed vector similar to how our Cosmic Vector indicator paints its plot. The aim of this indicator is to provide a consistent and generic price context that works out-of-the-box; accordingly a single static average period is used throughout and the settings have been stripped to the bare minimum with no need to ever update them.
📗 HOW TO USE IT
Cosmic Gravity's channel levels are meant to be used as a guide for entering and exiting positions and setting stop-loss and take profit levels. The indicator is deemed effective for any particular timeframe as long as the price stays within the maximum bounds of the indicator's plots. For this reason it is recommended to use Cosmic Gravity in a multi-chart layout where each chart has a different timeframe. The 5 primary strategies are:
long when the price reverses off of an Outer Channel support level and short when the price reverses off of an Outer Channel resistance level
long when the price crosses above the basis line after being below it for a prolonged period and vice-versa (short when the price trend moves below the basis line)
long when the basis line color turns blue after being pink for a prolonged period and visa-versa (short when the basis line color turns pink)
long/short in the direction the price takes when it goes outside the Magnetic Gravity channel when this channel is in a tight squeeze
scalp as the price bounces between the Inner Channel levels (do this only while the price is contained inside the Inner Channel )
🔔 SMART ALERTS
Get notified at the most critical times with a single alert. Simply select Cosmic Gravity - Any alert() function call as the condition when creating an alert and you will be tipped-off on bar-close as follows:
RR↘ (price close crossed below Outer Channel R6 plot)
RR↗ (price high crossed above Outer Channel R6 plot)
R└ (price low entered R channel from above)
R┘ (price high exited R channel from above)
R┐ (price high exited R channel from below)
R┌ (price high entered R channel from below)
B↘ (price high crossed below Basis plot)
B↗ (price low crossed above Basis plot)
B╮ ( Basis vector turned negative)
B╯ ( Basis vector turned positive)
S└ (price low entered S channel from above)
S┘ (price low exited S channel from above)
S┐ (price low exited S channel from below)
S┌ (price high entered S channel from below)
SS↘ (price low crossed below Outer Channel S6 plot)
SS↗ (price close crossed above Outer Channel S6 plot)
For example, an alert such as Cosmic Gravity 6H R┐ B↘ means that during the last 6-hour bar the price exited the R channel from below and also crossed below the basis line.
🚩 DISCLAIMER
The information we create and publish here is not prohibited, doesn't constitute investment advice, and isn't created solely for qualified investors.
Strategy PnL LibraryLibrary "Strategy_PnL_Library"
TODO: This is a library that helps you learn current pnl of open position and use it to create your own dynamic take profit or stop loss rules based on current level of your profit. It should only be used with strategies.
inTrade()
inTrade: Checks if a position is currently open.
Returns: bool: true for yes, false for no.
notInTrade()
inTrade: Checks if a position is currently open. Interchangeable with inTrade but just here for simple semantics.
Returns: bool: true for yes, false for no.
pnl()
pnl: Calculates current profit or loss of position after the commission. If the strategy is not in trade it will always return na.
Returns: float: Current Profit or Loss of position, positive values for profit, negative values for loss.
entryBars()
entryBars: Checks how many bars it's been since the entry of the position.
Returns: int: Returns a int of strategy entry bars back. Minimum value is always corrected to 1 to avoid lookback errors.
pnlvelocity()
pnlvelocity: Calculates the velocity of pnl by following the change in open profit compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl velocity.
pnlacc()
pnlacc: Calculates the acceleration of pnl by following the change in profit velocity compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl acceleration.
pnljerk()
pnljerk: Calculates the jerk of pnl by following the change in profit acceleration compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl jerk.
pnlhigh()
pnlhigh: Calculates the highest value the pnl has reached since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float highest value the pnl has reached.
pnllow()
pnllow: Calculates the lowest value the pnl has reached since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float lowest value the pnl has reached.
pnldev()
pnldev: Calculates the deviance of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float deviance value of the pnl.
pnlvar()
pnlvar: Calculates the variance value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float variance value of the pnl.
pnlstdev()
pnlstdev: Calculates the stdev value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float stdev value of the pnl.
pnlmedian()
pnlmedian: Calculates the median value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float median value of the pnl.
SUPER RSI [Gabbo]this indicator serves to differentiate the classic source of RSI
with these inputs you can modify the inputs of the different Bar's, you can choose between:
Candles = classic Candles
Heikin Hashi
Kagi
Line break
Pointfigure
Renko
Selecting the input: "Use Different Source ???" you can use a source with multiple elements of your choice
2 = (Source 1 + Source 2) / 2
3 = (Source 1 + Source 2 + Source 3) / 3
4 = (Source 1 + Source 2 + Source 3 + Source 4) / 4
5 = (Source 1 + Source 2 + Source 3 + Source 4 + Source 5) / 5
Variety RSI w/ Dynamic Zones [Loxx]Variety RSI w/ Dynamic Zones is an indicator with 7 different RSI types with Dynamic Zones. This indicator has signal crossing options for signal, middle, and all Dynamic Zone levels.
What is RSI?
The relative strength index ( RSI ) is a momentum indicator used in technical analysis . RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security.
The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The indicator was developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, New Concepts in Technical Trading Systems.
The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
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
RSI source pre-smoothing options
Bar coloring
4 types of signal crossing options
Alerts
Loxx's Expanded Source Types
Loxx's RSI Variety RSI types
Dynamic Zone of Bollinger Band Stops Line [Loxx]Dynamic Zone of Bollinger Band Stops Line is a Bollinger Band indicator with Dynamic Zones. This indicator serves as both a trend indicator and a dynamic stop-loss indicator.
What are Bollinger Bands?
A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a security's price, but which can be adjusted to user preferences.
Bollinger Bands were developed and copyrighted by famous technical trader John Bollinger, designed to discover opportunities that give investors a higher probability of properly identifying when an asset is oversold or overbought.
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
Signals
Alerts
3 types of signal smoothing
EchoMorphicAverageLibrary "EchoMorphicAverage"
Original Self Referencing Moving Average which references
it's own output agsainst itself and the incoming source to dynamically
alter smoothness and length internally per calculation cycle.
@kaigouthro
Inputs are float length series.
Contact Me for More Dynamic Float Length Indicators.
wema(src, mod, len)
Waited Echo-Morphic Average
Parameters:
src : (float) input value
mod : (float) modifier(0-1) mix of current value
len : (float) length
Returns: output processed smoothed value
wemaStack(src, mod, len)
Stacked Multipass Waited Echo-Morphic Average
Parameters:
src : (float) input value
mod : (float) modifier(0-1) mix of current value
len : (float) length
Returns: output processed smoothed value
Dynamic Zones of On Chart Stochastic [Loxx]Dynamic Zones of On Chart Stochastic is a Stochastic indicator that sits on top of the chart instead of below as an oscillator. Dynamic zone levels are included to find breakouts/breakdowns and reversals.
What is the Stochastic Oscillator?
A stochastic oscillator is a momentum indicator comparing a particular closing price of a security to a range of its prices over a certain period of time. The sensitivity of the oscillator to market movements is reducible by adjusting that time period or by taking a moving average of the result. It is used to generate overbought and oversold trading signals, utilizing a 0–100 bounded range of values.
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
Signals
Alerts
4 types of signal smoothing
Fisher Transform of MACD w/ Quantile Bands [Loxx]Fisher Transform of MACD w/ Quantile Bands is a Fisher Transform indicator with Quantile Bands that takes as it's source a MACD. The MACD has two different source inputs for fast and slow moving averages.
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 Quantile Bands?
In statistics and the theory of probability, quantiles are cutpoints dividing the range of a probability distribution into contiguous intervals with equal probabilities, or dividing the observations in a sample in the same way. There is one less quantile than the number of groups created. Thus quartiles are the three cut points that will divide a dataset into four equal-size groups (cf. depicted example). Common quantiles have special names: for instance quartile, decile (creating 10 groups: see below for more). The groups created are termed halves, thirds, quarters, etc., though sometimes the terms for the quantile are used for the groups created, rather than for the cut points.
q-Quantiles are values that partition a finite set of values into q subsets of (nearly) equal sizes. There are q − 1 of the q-quantiles, one for each integer k satisfying 0 < k < q. In some cases the value of a quantile may not be uniquely determined, as can be the case for the median (2-quantile) of a uniform probability distribution on a set of even size. Quantiles can also be applied to continuous distributions, providing a way to generalize rank statistics to continuous variables. When the cumulative distribution function of a random variable is known, the q-quantiles are the application of the quantile function (the inverse function of the cumulative distribution function) to the values {1/q, 2/q, …, (q − 1)/q}.
What is MACD?
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
Included:
Zero-line and signal cross options for bar coloring, signals, and alerts
Alerts
Signals
Loxx's Expanded Source Types
35+ moving average types
Fisher Transform w/ Dynamic Zones [Loxx]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 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
3 signal types
Bar coloring
Alerts
Channels fill
Loxx's Expanded Source Types
Dynamic Zone Range on PDFMA [Loxx]Dynamic Zone Range on PDFMA is a Probability Density Function Moving Average oscillator with Dynamic Zones.
What is Probability Density Function?
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights.
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
4 signal types
Bar coloring
Alerts
Channels fill
Reversal scoreDynamic divergence indicator on 3 indicators, without delays or repaints
Technological choices have been made so as not to lie to you about the signals, and so that the backtesting is perfectly faithful to reality. The market is analyzed and looks for a dynamic status of divergence on the Fisher transformation, the Money Flow Index and the MACD: if the status is "divergence", it is quantified by a divergence score to assess its potential and whose parameters are multiple (including market structure during divergence status).
At the top Reversal score, at the bottom the divergence indicator integrated in Tradingview. On this last candle, there will indeed be an RSI divergence but which will only be displayed 5 candles later, where ASTRE displays it to you in real time:
You will notice how certain spikes trigger sharp divergence – an anomaly between the movement of the price and that of the indicators is a good sign of an instant reversal, and in m2, a way to take a 2:1 TP in seconds:
Usage tip: Follow the signals in the direction of the main trend! They are much less numerous but very effective! :
Adaptive EnvelopeI bring to your attention a dynamic indicator Adaptive Envelope .
The main qualitative characteristic of the technical indicator is adaptability. This means that it does not need to be adjusted for each tool. The adaptive envelope itself dynamically adjusts to the volatility of each individual instrument, or even timeframe.
And thanks to a wide range of settings, the indicator can be adjusted to your needs. Let's consider an example of the use of the indicator in trading.
Option #1. The envelope shows the "stretch" of the market - that is, the price of the asset beyond normal volatility. And it is at such moments that the probability of returning to the average is highest. That is, for such a signal, we wait for the exit to the moving average, and when returning with a stop order, we enter the averaging direction.
Option #2. Another option for trading is to buy at the lower level, as well as additional purchases along the lines of the envelope. Exit - on the middle line of the envelope (for shorts on the contrary) - so we have a full adaptability of the strategy. I repeat that due to adaptability, there will be no need to reconfigure when changing market characteristics.
Thank you for attention. Sincerely, Oleksandr Yanchak. Capitalizator.UA
Adaptive_LengthLibrary "Adaptive_Length"
This library contains functions to calculate Adaptive dynamic length which can be used in Moving Averages and other indicators.
Two Exponential Moving Averages (EMA) are plotted. Coloring in plot is derived from Chikou filter and Dynamic length of MA1 is adapted using Signal output from Chikou library.
dynamic(para, adapt_Pct, minLength, maxLength) Adaptive dynamic length based on boolean parameter
Parameters:
para : Boolean parameter; if true then length would decrease and would increase if its false
adapt_Pct : Percentage adaption based on parameter
minLength : Minimum allowable length
maxLength : Maximum allowable length
Returns: Adaptive Dynamic Length based on Boolean Parameter
auto_alpha(src, a) Adaptive length based on automatic alpha calculations from source input
Parameters:
src : Price source for alpha calculations
a : Input Alpha value
Returns: Adaptive Length calculated from input price Source and Alpha
TPTR_Dynamic_Ratio_CorrelatorThe script provides a way to compute ratio between two indexes (or stocks) of your choice, and paints a "up-arrow" below the first candle where and when the value of the ratio exceeds your threshold of choice.
It also creates a table summarizing the value of your securities, and the value of the ratio below.
The script will also alert you with a message (automatically) when the ratio of your security_1 and security_2 exceeds the ratio.
Moving Average with Dynamic Color Gradient (WaveTrend Momentum)Similar scripts exist but I haven't seen one using WaveTrend and I haven't seen one that hand picks evenly divided colors between GREEN-YELLOW-RED.
The green is exact green, the yellow is exact yellow, and the red is exact red.
Not complicated, just useful.
Green to Red Gradient for Dynamic / Color Changing IndicatorsI have evenly divided every color between green and red.
This gradient is useful for pine coders who are creating color changing, dynamic, or gradient indicators.
Bollinger bands dynamic alertsThis triple Bollinger script is very useful for options traders to determine the trend condition. When the trend stays within 1 sigma limits it is termed as "congestion", breakout of congestion starts the "trending" phase and the big breakout termed "Blowout" happens when the underlying crosses the 2sigma and reaches 3 sigma limits in very short time at steep trend angles. The script provides dynamic alerts as soon as the underlying breaks out of these zones and enables options traders to stay in the trade longer. www.tradingview.com
Dynamic Moving AveragesThis indicator uses what I call Dynamic Moving Averages to identify trends. The reason these moving averages are dynamic is that they track different sources based on the trend. Allow me to explain...
Low = identifies the least sellers were willing to sell for in a given period.
High = Identifies the most buyers were willing to buy for in a given period.
Avg Low = Shows the least sellers were willing to sell for over several periods.
Avg High = Shows the least buyers were willing to buy for over several periods.
If, in an uptrend, the closing price closes below the Avg Low, a trend change could be coming to the downside. If, in a downtrend, the closing price closes above the Avg high, a trend change could be coming to the upside.
This indicator uses a single moving average to identify the trend. If price is above this MA, we are in an uptrend. Below it, we are in a downtrend. I recommend using that 50 length as your trend. Any moving averages that are Dynamic, will track the low when above the Trend MA and track the High when below the trend MA.
When Price crosses a Dynamic Moving Average, the trend is likely changing. I recommend using 3 MAs at a time (trend + 2 shorter MAs), but I have provided 7 in total.
