Possible RSI [Loxx]Possible RSI is a normalized, variety second-pass normalized, Variety RSI with Dynamic Zones and optionl High-Pass IIR digital filtering of source price input. This indicator includes 7 types of RSI.
High-Pass Fitler (optional)
The Ehlers Highpass Filter is a technical analysis tool developed by John F. Ehlers. Based on aerospace analog filters, this filter aims at reducing noise from price data. Ehlers Highpass Filter eliminates wave components with periods longer than a certain value. This reduces lag and makes the oscialltor zero mean. This turns the RSI output into something more similar to Stochasitc RSI where it repsonds to price very quickly.
First Normalization Pass
RSI (Relative Strength Index) is already normalized. Hence, making a normalized RSI seems like a nonsense... if it was not for the "flattening" property of RSI. RSI tends to be flatter and flatter as we increase the calculating period--to the extent that it becomes unusable for levels trading if we increase calculating periods anywhere over the broadly recommended period 8 for RSI. In order to make that (calculating period) have less impact to significant levels usage of RSI trading style in this version a sort of a "raw stochastic" (min/max) normalization is applied.
Second-Pass Variety Normalization Pass
There are three options to choose from:
1. Gaussian (Fisher Transform), this is the default: The Fisher Transform is a function created by John F. Ehlers that converts prices into a Gaussian normal distribution. The normaliztion helps 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.
2. Softmax: The softmax function, also known as softargmax: or normalized exponential function, converts a vector of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and used in multinomial logistic regression. The softmax function is often used as the last activation function of a neural network to normalize the output of a network to a probability distribution over predicted output classes, based on Luce's choice axiom.
3. Regular Normalization (devaitions about the mean): Converts a vector of K real numbers into a probability distribution of K possible outcomes without using log sigmoidal transformation as is done with Softmax. This is basically Softmax without the last step.
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.
7 Types of RSI
See here to understand which RSI types are included:
Included:
Bar coloring
4 signal types
Alerts
Loxx's Expanded Source Types
Loxx's Variety RSI
Loxx's Dynamic Zones
Normalized
Leavitt Convolution Slope [CC]The Leavitt Convolution Slope indicator was created by Jay Leavitt (Stocks and Commodities Oct 2019, page 11), who is most well known for creating the Volume-Weighted Average Price indicator. This indicator is very similar to the Leavitt Convolution indicator but the big difference is that it is getting the slope instead of predicting the next Convolution value. I changed quite a few things from the original source code so let me know if you like these changes. I added a normalization function using code from a good friend @loxx that I recommend to leave on but feel free to experiment with it. Last but not least, the unsure levels are essentially acting as a buy or sell threshold. I personally recommend to buy or sell for zero crossovers but another option would be to buy or sell for crossovers using the unsure levels. I have color coded the lines to turn light green for a normal buy signal or dark green for a strong buy signal and light red for a normal sell signal, and dark red for a strong sell signal.
This is another indicator in a series that I'm publishing to fulfill a special request from @ashok1961 so let me know if you ever have any special requests for me.
Gaussian Filter MACD [Loxx]Gaussian Filter MACD is a MACD that uses an 1-4 Pole Ehlers Gaussian Filter for its calculations. Compare this with Ehlers Fisher Transform.
What is Ehlers Gaussian filter?
This filter can be used for smoothing. It rejects high frequencies (fast movements) better than an EMA and has lower lag. published by John F. Ehlers in "Rocket Science For Traders". First implemented in Wealth-Lab by Dr René Koch.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve. In the case of low-pass filters, only the upper half of the curve describes the filter. The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
A gaussian filter with...
one pole is equivalent to an EMA filter.
two poles is equivalent to EMA ( EMA ())
three poles is equivalent to EMA ( EMA ( EMA ()))
and so on...
For an equivalent number of poles the lag of a Gaussian is about half the lag of a Butterworth filters: Lag = N * P / (2 * ¶2), where,
N is the number of poles, and
P is the critical period
Special initialization of filter stages ensures proper working in scans with as few bars as possible.
From Ehlers Book: "The first objective of using smoothers is to eliminate or reduce the undesired high-frequency components in the eprice data. Therefore these smoothers are called low-pass filters, and they all work by some form of averaging. Butterworth low-pass filtters can do this job, but nothing comes for free. A higher degree of filtering is necessarily accompanied by a larger amount of lag. We have come to see that is a fact of life."
References John F. Ehlers: "Rocket Science For Traders, Digital Signal Processing Applications", Chapter 15: "Infinite Impulse Response Filters"
Included
Loxx's Expanded Source Types
Signals, zero or signal crossing, signal crossing is very noisy
Alerts
Bar coloring
Parabolic SAR Oscillator [LuxAlgo]This indicator is a detrended price series using the Parabolic Stop and Reverse (SAR) trailing stop, resulting in a bounded oscillator in the range (-100, 100). The SAR output is also normalized to obtain a noiseless oscillator which can complement the detrended price.
Settings
Start: Initial value of the convergence factor used when a new trend is detected by the SAR
Increment: Increment value of the convergence factor
Maximum: Maximum value of the convergence factor
Usage
The price is detrended by subtracting the closing price to the SAR, this result is then normalized.
An up-trending market is indicated once the normalized SAR reaches -100, while a value of 100 indicates a down-trending market. One can anticipate trends when the normalized SAR crosses above/under 0.
The converging nature of the SAR trailing stop allows for the trader to obtain a very apparent leading oscillator.
ESTOCÁSTICO + NORMALIZED MACD=== INTRO ===
This is a 2 in 1 indicator, STOCHASTIC + NORMALIZED MACD.
I release this script as public because both stochastic and normalized macd are public, so I cannot find any reason to post it as private :)
=== USAGE ===
You can use any of the indicators by itself as usual, stochastic as a oversold/overbought indicator as a momentum/trend indicator.
Usually, crossovers are used for LONG/SHORT entries.
I added dots for crossovers as well as background colors to show movement direction when both indicators agree: green = bullish, red = bearish and orange = range/consolidation.
=== SETTINGS ===
Default settings for both indicators have been changed (but they're of course configurable), to make them work better together.
You can also change NMACD moving average time to SMA or WMA instead of SMA, SMA is really slow for me but give it a try, WMA is more aggressive.
=== RECOMMENDATIONS ===
Always look for higher timeframes, for example, if you're trading 1h, don't try to catch a 1H "ALL GREEN" LONG while 4H is "ALL RED" because otherwise you're just "trying" to catch a bounce in the 1H chart that could never happen, always trade with the main trend.
Try to catch both crossovers in the opposite area, ex: try to LONG when both indicators are below 50 and SHORT above.
I did not test divergences on this indicator, as the MACD is normalized i prefer to use a standard MACD for that, but you can use the stochastic for sure.
Circular Barplot - Oscillators Sentiment [LuxAlgo]This indicator is an implementation of a circular barplot aiming to return the market sentiment given by multiple normalized oscillators. These include the relative strength index (RSI), Stochastic %K (%K), Linear Correlation Oscillator (ROSC), William Percent Range (WPR), Percent Rank (%R), and money flow index (MFI).
The length period of each of these oscillators can be adjusted in the indicator settings.
The label in the center of the circular plot returns the average market sentiment constructed from all the previously mentioned oscillators.
Settings
Width: Circle width.
Spacing: Determines how close each circle is to the other.
Thickness: Width of the colored lines.
Offset: Controls how far the circular barplot left extremity is from the most recent candles.
Src: Input source of the indicators.
Usage
Unlike regular bar charts, circular bar plots display the bars as circle arcs and have the advantage of preserving horizontal and vertical space. A higher arc length would indicate a value closer to the maximal value of the oscillator. Other variations of the circular barplots exist but this variation using the circle arc is particularly appropriate for normalized data.
The indicator can be used as a simple widget giving a quick method to obtain the overall market sentiment of a certain ticker. A dashboard is displayed on the top left of the chart in the event the user wants to see the actual value of the oscillators.
Note that low width or high spacing settings might return unwanted results.
Normalized Quantitative Qualitative Estimation nQQENormalized version of Quantitative Qualitative Estimation QQE:
Normalized QQE tries to overcome the problems of false signals due to RSI divergences on the original QQE indicator.
The main purpose is to determine and ride the trend as far as possible.
So users can identify:
UPTREND : when nQQE Histogram is GREEN (nQQE is above 10)
DOWNTREND : when nQQE Histogram is RED (nQQE is below -10)
SIDEWAYS: when nQQE Histogram is YELLOW (nQQE is between -10 and 10)
Calculation is very simple;
RSI based QQE oscillates between 0-100
nQQE is simply calculated as:
nQQE=QQE-50
to make the indicator fluctuate around 0 level to get more accurate signals.
Various alarms added.
Kıvanç Özbilgiç
Closing Price NormalizationIndicator title : Price Normalized
Description : The indicator is a variation of %k Stochastic where it use highest/lowest closing price to define the range instead of highest high/lowest low,
the range also excluded current bar so that break above 100 or below 0 means current bar closing price breaks above highest/below lowest the closing price in the past 200 bars (default setting)
Simplest way to interpret the indicator is that as price retraced downward while indicator still above 50 value, it means the closing price still traded on the upper side of last 200 bars range
Warning: While the indicator assume similar characteristic as Stochastic Indicator, its is not meant to be used to determnine ovebought/oversold zone.
Disclaimer:
I always felt Pinescript is a very fast to type language with excellent visualization capabilities, so I've been using it as code-testing platform prior to actual coding in other platform.
Having said that, these study scripts was built only to test/visualize an idea to see its viability and if it can be used to optimize existing strategy.
While some of it are useful and most are useless, none of it should be use as main decision maker.
© fareidzulkifli
Percentage Price Over SMAReturn the percentage of closing prices greater than SMA's with periods within a user-selected range. An exponential moving average applied to these results is also displayed (in orange).
Settings
Min : Minimum period of the SMA in the range
Max : Maximum period of the SMA in the range
Smooth : Period of the EMA
Src : Input series of the indicator
Usage
The indicator is a normalized oscillator. A value of 100 indicates that 100% of the current closing price is over SMA's with periods ranging from min to max , this indicates a bullish market, while a value of 0 would indicate a bearish market.
In this image the indicator use min = 50 and max = 200, here AMD has been strongly bullish at the start, and ended being strongly bearish at the end, during this bullish period the indicator is over its overbought level, while it is under its oversold level during the bearish period.
In case the market is ranging we can expect the indicator to be around 50%, using the smoothed result might be more useful to detect ranging markets with this indicator.
If the smoothed result is within the overbought/oversold levels, then we can say that the market is either ranging or transitioning from a bullish/bearish market to an opposite one.
UCS_Price Action Normalized VolatilityFor Stock, Futures and Forex traders this may not be a replacement for MACD . But for an Option Trader, this would make sense 1000 times.
So, What is this?
This is the MACD for OPTIONS traders, remove the smoothness and adjust for volatility . Thats all it is.
Why is it important?
No one, ABSOLUTELY no one should be buying options in high volatility period for a long haul. So, this indicator takes that out of your guess work and only spits out price movement with relation to volatility .
You can use this exactly like a MACD for any options ( aka , volatility driven market).
Few things I have added, since I created and used it privately.
1. Chop Zone - Trade the Extremes of any Product
2. Buyers Zone - Shorts reconsider
3. Sellers Zone - Longs reconsider
Why did I create this?
Volatility dictates the market movement. That is an indepth conversation. If you are curious you can research on how shorts are squeezed, what are market makers obligations, how they maintain profitability. How NITE got burned, are some starting point for your own research.
So, if you are an options trader, I highly recommend to use this/test it and share your thoughts and how you use it.
- Good Luck Everyone.
ATR _NormalizedThis script is good to use with Williams %R indicator, to find out when price has bottomed out.
ATR has to be over 90 and Williams %R ( lenght 52 ) has to be over 95 to find out level around which one is good to buy.
You can check back, to see that this worked very well over history. Best way to use this 2 indicators is with DCA ( dollar cost average ), as area where to buy can go a little bit down and up for as long as few months. So dont just jump in, use DCA .
Celasor Normalized ATR with Williams %RNormalized Average True Range combined with Williams %R - Celasor 04/2020.
Indicator can be used for identifying potential market bottoms with the following criteria: Normalized ATR is above 80% and Williams %R is below -80.
This script combines both indicators and displays bars to mark where conditions are met. Future updates may include selectable smoothing.
Price/Volume Normalized OscillatorIt can be interesting to have an indicator displaying two rescaled measures, thus ending with an indicator that allow the creation of more complex trading rules (conditions), this is what is intended with the price/volume normalized oscillator (PVNO) who normalize both volume and price in order to display them together.
Volume is considered an important factor as it show the trading activity of a security, securities with higher volume are more attractive to trade as higher volume is in general present with larger price variations, higher volume can also indicate a better trade execution.
THE INDICATOR
In the PVNO, the rescaled volume is represented by the blue plot while the rescaled price is represented by the (green/red) plot. The rescaling method used here is simply based on the sum of the current and past momentum output of a series of observations divided by the sum of the current and past absolute value of this momentum, this allow to have a smooth output with values reaching 1 and -1 instead of converging toward 0.
The indicator has two settings, Volume Length who control the length of the sum of the rescaled volume, while Price Length control the sum length of the rescaled price. When the rescaled volume is positive it means that the sum of the current and past Volume Length - 1 positive volume momentum values is greater than the sum of negative ones, this indicate a more active market. The same apply to the rescaled price, with a positive rescaled price value indicating an uptrend and negative values indicating a downtrend.
Because of the stationary and periodic nature of volume, low values for Volume Length are recommended.
INTERPRETATIONS AND USAGES
As you can see the rescaled price plot can have two colors, and the area between the rescaled volume and price plot is filled with two possible colors as well, the color depend on the following simple condition:
green: once rescaled price > 0 and rescaled volume > 0 until condition for red don't happen
red: once rescaled price < 0 and rescaled volume > 0 until condition for green don't happen
Therefore no signals are triggered if the rescaled price is greater/lower then 0 but the rescaled volume is lower than 0, this could allow to filter various false signals (at the cost of reactivity). A more interesting use-case of the indicator can be based on the upper and lower constant levels displayed in order to spot points where volume will fall or rise.
Volume can also be used to spot potential reversals, therefore the levels can also be used to this end as well.
SUMMARY
A normalized oscillator plotting rescaled price and volume values has been presented, the indicator posses its own trading rules but can easily modified. This is not an indicator i'am super proud of, even after passing some time on it lol. You can use the code freely without asking for permission, mention is appreciated.
Next indicators should be more pertinent and interesting, thanks for reading !
Normalized Smoothed MACDMACD normalized with its highest and lowest values over the last “Normalization period”
- includes alerts
Normailzed CandleThis indicator normalizes Day's candle with Open. Idea is to see the daily movement in the context of the Open of the Day.
Larry Williams talks about Open being the most important price of the day. Hence, this indicator.
The Green line is average Open-to-High for occurrences of Red days. The Red line is average Open-to-Low for occurrences of Green days.
Average are not perfect calculations since occurrences(of Red or Green) will vary within the time-span used for averages.
These can used to gauge likelihood of the intra-day price reversal. If the price exceeds green/red line, there is higher likelihood of the price closing above/below open.
The blue lines are average Open-to-close for Green and Red occurrences.
Be careful on days where consecutive 3rd Highest High or Lowest Low day is made and also on the next day after such day. Prices may turn direction at least for a short while.
The precursor to this script of the Candle Infopanel script. That script was just numbers in panel and this is a graphical representation. I
Some of the calculations from original script are commented here because it would make visuals clutters (and probably the left-out calculation are not critical to making trade decisions!)
(5) Volume Price Projection VS-93Volume Price Projection, displays only the differences the current volume represents above or below the current moving average of volume. This isolates only significant volume events for the trader. When utilized in combination with a simple volume/price matrix chart, traders are provided with a powerful tool-set, alerting traders of potential opportunities while providing strong conformations of your trading decisions.
Volume is a direct reflection of the current level of interest in this equity. What is important about interest levels, regardless of sentiment (positive or negative,) produced by any event, is if the event or news is to have an impact on share price, the volume will increase as a result. This volume increase provides the liquidity required to allow market dynamics to fuel changes in price. This makes significant volume increases the hallmark of any meaningful changes, first in interest, which results in higher volume, and second, in influencing sentiment with the end result being a change in price.
We consider volume increases over the moving average of volume (significant volume increases) to be such an important trading principal that the blue background flag it triggers is built into all other Genie Indicators.
Volume Price Projection was originally published in the Journal of Technical Analysis of Stocks and Commodities; Oct., 2017. by Michael Slattery.
Access this Genie indicator for your Tradingview account, through our web site. (Links Below) This will provide you with additional educational information and reference articles, videos, input and setting options and trading strategies this indicator excels in.
(4) Early Warning System VS-606The early warning system is constructed by converting a short alpha-length Laguerre filter into a normalized, horizontal line. This line is then placed into a chart on the zero axis. The calculation underpinning this line is identical to that produced by a moving filter or traditional moving average. Each current bar’s succeeding data is incorporated into the indicator’s updated calculation, but the visual output is plotted on a horizontal centerline that remains static. The current close is then subtracted from the normalized Laguerre filter, allowing the trader to visualize exactly what the difference is between the most current Laguerre filter’s value and the close of the most recent candle or bar. To put this in another way, the columns indicate how far away the close of the day is from the most current value the Laguerre moving filter calculation is producing. This enables the trader to immediately visualize and gauge the beginning, middle, and end of each parabolic swing, clearly exposing diversion/reversion overreactions in both directions, creating insightful entry/exit opportunities.
The Early Warning Indicator produces a foundation, enabling the production of an extremely effective swing trading system, effectively generating meaningful signals when a stock is loosely tracking, or swinging above and below a short-term Laguerre filter or moving average. The greater the volatility of these swings, the more precise the indicator becomes, increasing both accuracy and profit opportunities. The added implementation of the standard deviation of root mean square to the EWS flags, signals, that have a very high likelihood or reversing. The Early Warning System was first published in the journal of Technical Analysis of Stocks and Commodities: Aug 2017 by Michael slattery.
Access this Genie indicator for your Tradingview account, through our web site. (Links Below) This will provide you with additional educational information and reference articles, videos, input and setting options and trading strategies this indicator excels in.
Normalized XAUUSD VolumeNormalized XAUUSD Volume
Volume points to the amount of a financial instrument that was traded over a specified period of time. It can refer to shares, contracts or lots. The data is tracked and provided by market exchanges. It is one of the oldest and most popular indicators and is usually plotted in colored columns, green for up volume and red for down volume, with a moving average. It is one of the few indicators that is not based on price. High volume points to a high interest in an instrument at its current price and vice versa.
A sudden increase in trading volume points to a increased probability of the price changing. News events are typical moments when volume can increase. Strong trending moves go hand in hand with an increased trading volume. It can therefore be seen as a measure of strength. One would expect high buying volume at a support level and high selling volume at a resistance level. There are several ways to use volume in a trading strategy and most traders use it in combination with other analysis techniques.
Scaled Normalized Vector Strategy, ver.4.1This modification of the Scaled Normalized Vector Strategy uses trailing stops and is optimized for lower TFs.
Scaled Normalized Vector Strategy, ver.4This is a modification of my Scaled Normalized Vector Strategy.
This mod features some activation functions. Performance remains high. The repainting problem should be tested out.
Scaled Normalized Vector StrategyThis is a scaled Normalized Vector Strategy with a Karobein Oscillator
Original: Drkhodakarami (www.tradingview.com)
Repainting: in general there two types of repainting:
* when the last candle is constantly being redrawn
* when the indicator draws a different configuration after it has been deactivated/reactivated, i.e. refreshed.
The former is a natural behaviour, which presents a constant source of frustration, when a signal directly depends on the current market situation and can be overcome with various indirect techniques like divergence.
The latter suggests a flaw in the indicator design.
Unfortunately, the Normalized Vector Strategy is repainting in the latter sense, although being really promising. Would be nice if our community suggests a solution to this problem ))
As it is this strat should be refreshed each time a decision is being taken.
This strat consistently performs with high accuracy, showing up to 96% scores. Here are some of the best parameters:
TF Lookback Performance (ca.)
1m 13 92%
3m 34 92%
5m 85 92%
15m 210 90%
30m 360 89%
1H 1440, 720 94%, 87%
The Karobein Oscillator has an intrinsic sinusoidal behaviour that helps in determining direction and timing. It does not repaint.
Original: alexgrover (www.tradingview.com)
