Regression Envelope MTFThe Regression Envelope MTF indicator is a technical analysis tool that uses linear regression to identify potential price reversal points in the market. The indicator plots a linear regression line based on the selected price source over a specified length, and adds and subtracts a multiple of the standard deviation to create upper and lower bands around the line.
One advantage of using linear regression over the traditional envelope indicator is that it takes into account the slope of the trend, rather than assuming that the trend is linear. This means that the bands will adapt to the slope of the trend, which can provide more accurate signals in trending markets.
Another advantage of using linear regression over a simple moving average (SMA) is that it is less sensitive to outliers. SMAs can be heavily influenced by extreme values in the data, which can result in false signals. Linear regression, on the other hand, is more robust to outliers, which can lead to more reliable signals.
Overall, the Regression Envelope MTF indicator can be a useful tool for traders and investors looking to identify potential price reversal points and generate trading signals. However, it should be used in conjunction with other technical analysis tools and with proper risk management strategies in place.
Linear
Autoregressive Covariance Oscillator by TenozenWell to be honest I don't know what to name this indicator lol. But anyway, here is my another original work! Gonna give some background of why I create this indicator, it's all pretty much a coincidence when I'm learning about time series analysis.
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Well, the formula of Auto-covariance is:
E{(X(t)-(t) * (X(t-s)-(t-s))}= Y_s
But I don't multiply both values but rather subtract them:
E{(X(t)-(t) - (X(t-s)-(t-s))}= Y_s?
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For arm_vald, the equation is as follows:
arm_vald = val_mu + mu_plus_lsm + et
val_mu --> mean of time series
mu_plus_lsm --> val_mu + LSM
et --> error term
As you can see, val_mu^2. I did this so the oscillator is much smoother.
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After I get the value, I normalize them:
aco = Y_s? / arm_vald
So by this calculation, I get something like an oscillator!
(more details in the code)
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So how to use this indicator? It's so easy! If the value is above 0, we gonna expect a bullish response, if the value is below 0, we gonna expect a bearish response; that simple. Be aware that you should wait for the price to be closed before executing a trade.
Well, try it out! So far this is the most powerful indicator that I've created, hope it's useful. Ciao.
(more updates for the indicator if needed)
Linear Regression Volume ProfileLinear Regression Volume Profile plots the volume profile fixated on the linear regression of the lookback period rather than statically across y = 0. This helps identify potential support and resistance inside of the price channel.
Settings
Linear Regression
Linear Regression Source: the price source in which to sample when calculating the linear regression
Length: the number of bars to sample when calculating the linear regression
Deviation: the number of standard deviations away from the linear regression line to draw the upper and lower bounds
Linear Regression
Rows: the number of rows to divide the linear regression channel into when calculating the volume profile
Show Point of Control: toggle whether or not to plot the level with highest amount of volume
Usage
Similar to the traditional Linear Regression and Volume Profile this indicator is mainly to determine levels of support and resistance. One may interpret a level with high volume (i.e. point of control) to be a potential reversal point.
Details
This indicator first calculates the linear regression of the specified lookback period and, subsequently, the upper and lower bound of the linear regression channel. It then divides this channel by the specified number of rows and sums the volume that occurs in each row. The volume profile is scaled to the min and max volume.
Linear Regress on Price And VolumeLinear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. It assumes a linear relationship between the dependent variable and the independent variable(s) and attempts to fit a straight line that best describes the relationship.
In the context of predicting the price of a stock based on the volume, we can use linear regression to build a model that relates the price of the stock (dependent variable) to the volume (independent variable). The idea is to use lookback period to predict future prices based on the volume.
To build this indicator, we start by collecting data on the price of the stock and the volume over a selected of time or by default 21 days. We then plot the data on a scatter plot with the volume on the x-axis and the price on the y-axis. If there is a clear pattern in the data, we can fit a straight line to the data using a method called least squares regression. The line represents the best linear approximation of the relationship between the price and the volume.
Once we have the line, we can use it to make predictions. For example, if we observe a certain volume, we can use the line to estimate the corresponding price.
It's worth noting that linear regression assumes a linear relationship between the variables. In reality, the relationship between the price and the volume may be more complex, and other factors may also influence the price of the stock. Therefore, while linear regression can be a useful tool, it should be used in conjunction with other methods and should be interpreted with caution.
Premium Linear Regression - The Quant ScienceThis script calculates the average deviation of the source data from the linear regression. When used with the indicator, it can plot the data line and display various pieces of information, including the maximum average dispersion around the linear regression.
The code includes various user configurations, allowing for the specification of the start and end dates of the period for which to calculate linear regression, the length of the period to use for the calculation, and the data source to use.
The indicator is designed for multi-timeframe use and to facilitate analysis for traders who use regression models in their analysis. It displays a green linear regression line when the price is above the line and a red line when the price is below. The indicator also highlights areas of dispersion around the regression using circles, with bullish areas shown in green and bearish areas shown in red.
VHF Adaptive Linear Regression KAMAIntroduction
Heyo, in this indicator I decided to add VHF adaptivness, linear regression and smoothing to a KAMA in order to squeeze all out of it.
KAMA:
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low. KAMA will adjust when the price swings widen and follow prices from a greater distance. This trend-following indicator can be used to identify the overall trend, time turning points and filter price movements.
VHF:
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
Linear Regression Curve:
A line that best fits the prices specified over a user-defined time period.
This is very good to eliminate bad crosses of KAMA and the pric.
Usage
You can use this indicator on every timeframe I think. I mostly tested it on 1 min, 5 min and 15 min.
Signals
Enter Long -> crossover(close, kama) and crossover(kama, kama )
Enter Short -> crossunder(close, kama) and crossunder(kama, kama )
Thanks for checking this out!
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Credits to
▪️@cheatcountry – Hann Window Smoohing
▪️@loxx – VHF and T3
▪️@LucF – Gradient
Dynamic Linear Regression Oscillator | AdulariDescription:
This dynamic linear regression oscillator visualizes the general price trend of specific ranges in the chart based on the linear regression calculation, it automatically determines these ranges with pivot detection. The central line of the indicator is the baseline of the linear regression itself. This is a good tool to use to determine when a price is unusually far away from its baseline. The lines above or below it are overbought and oversold zones. These zones are based on the high or low of the range, in combination with the set multipliers.
The overbought and oversold lines indicate support and resistance; when the prices stay outside these levels for a significant period of time, a reversal can be expected soon. When the oscillator's value crosses above the signal or smoothed line the trend may become bullish. When it crosses below, the trend may become bearish.
This indicator is quite special, as it first determines price ranges using pivot detection. It then uses the middle of the range to determine how far the current price is from the baseline. This value is then rescaled compared to a set amount of bars back, putting it into relevant proportions with the current price action.
How do I use it?
Never use this indicator as standalone trading signal, it should be used as confluence.
When the value crosses above the signal this indicates the current bearish trend is getting weak and may reverse upwards.
When the value crosses below the signal this indicates the current bullish trend is getting weak and may reverse downwards.
When the value is above the middle line this shows the bullish trend is strong.
When the value is below the middle line this shows the bearish trend is strong.
When the value crosses above the upper line this indicates the trend may reverse downwards.
When the value crosses below the lower line this indicates the trend may reverse upwards.
Features:
Oscillator value indicating how far the price has currently deviated from the middle of the range. Proportioned to data from a set amount of bars ago.
Signal value to indicate whether or not the price is abnormally far from the middle of the range.
Horizontal lines such as oversold, overbought and middle lines, indicating possible reversal zones.
Automatic range detection using pivots.
Built-in rescaling functionality to ensure values are proportionate with the latest data.
How does it work? (simplified)
1 — Calculate the middle of the range.
2 — Define whether the current price is above the middle of the range or below.
3 — If above the middle of the range, calculate the difference of the current high and the middle line. If below, calculate the difference of the current low and the middle line.
4 — Smooth the value using a set moving average type.
5 — Rescale the value to proportionate it with the latest data.
Three Linear Regression ChannelsPlot three linear regression channels using alexgrover 's Computing The Linear Regression Using The WMA And SMA indicator for the linear regression calculations.
Settings
Length : Number of inputs to be used
Source : Source input of the indicator
Midline Colour : The colour of the midline
Channel One, Two, and Three Multiplicative Factor : Multiplication factor for the RMSE, determine the distance between the upper and lower level
Channel One, Two, and Three Colour : The channel's lines colour
Usage
For usage details, please refer to alexgrover 's Computing The Linear Regression Using The WMA And SMA indicator.
Multi-Optimized Linear Regression ChannelA take on alexgrover 's Optimized Linear Regression Channel script which allows users to apply multiple linear regression channel with unique multiplicative factors.
Multiplicative Factors
Adjust the amount of channels and multiplicative factors of existing or additional channels using the "Mults" input.
An input of "1" creates a single linear regression channel with the multiplicative factor of one.
An input of "4" creates a single linear regression channel with the multiplicative factor of four.
An input of "1,4" creates two linear regression channels with multiplicative factors of one and four.
An input of "1,2,3" creates three linear regression channels with multiplicative factors of one, two, and three.
DB Change Forecast ProDB Change Forecast Pro
What does the indicator do?
The DB Change Forecast Pro is a unique indicator that uses price change on HLC3 to detect buy and sell periods along with plotting a linear regression price channel with oversold and undersold zones. It also has a linear regression change forecast mode to optionally project market direction.
Change is calculated by taking a two-bar change of HLC3 and dividing that by the price or, optionally, a fixed divisor.
A fast-moving change cloud is then calculated and displayed as the "regular version" plot (shown in light gray). When the cloud bottom is above low, a buy zone is detected. When the cloud top is below the high, a sell zone is detected.
The linear regression price channel is calculated similarly but using a much slower change rate. The linear regression price channel shows reasonable high, low and HLC3 ranges. At the bar's opening, the channel will be more compact and come fairly accurate about 1/4 into the bar timeframe.
The change forecasted price is projected on the right side of the current bar to indicate the current timeframe direction. Please note this forecasting feature is shown in orange when it's early in the timeframe and gray when the timeframe is more likely to produce an accurate direction forecast for the upcoming bar.
You can use these projected dashed lines to see possible market movements for the Current bar and possible market direction for the next bar. Kindly note these projects change; they should be used to understand possible extreme highs/lows for the current bar or market direction.
The indicator includes an optional change forecast projection feature hidden by default. It will project the market forecast channel with an offset of 1. The forecast is defaulted to an offset of 1 to show market direction. However, you can modify to zero the offset to show the current bar forecast and forecast history.
How should this indicator be used?
First, very important,
1. Settings > Set Symbol to Desired
2. Settings > Set High Timeframe to "Chart"
3. Settings > Ensure "Use price as divisor" is checked.
It's recommended to use this indicator in higher timeframes. Buy and sell signals are displayed in real-time. However, waiting until 1/4 to 1/2 into the current bar is recommended before taking action, and change can happen.
The buy/sell signals (zones) provide recommendations on playing a long vs. a short. When in a buy sone, only play longs. When in a sell zone, only play shorts.
Then use the linear regression price channel oversold and undersold zones to optionally open and close positions within the buy/sell zones.
For example, consider opening a long in a buy zone when the linear regression price channel shows undersold. Then consider closing the long when the price moves into the linear regression oversold or higher. Then repeat as long as it's in the buy zone. Then vice versa for sell zones and shorting.
At basic design, buy in the buy zone, sell or short in the sell zone. If you are up for higher trading frequencies, use the linear regression price channel as described in the example above.
Please note, as, with all indicators, you may need to adjust to fit the indicator to your symbol and desired timeframe.
This is only an example of use. Please use this indicator as your own risk and after doing your due diligence.
Does the indicator include any alerts?
Yes,
"DB CFHLC3: Signal BUY" - Is triggered when a buy signal is fired.
"DB CFHLC3: Signal SELL" - Is triggered when a sell signal is fired.
"DB CFHLC3: Zone BUY" - Is triggered when a buy zone is detected.
"DB CFHLC3: Zeon SELL" - Is triggered when a sell zone is detected.
"DB CFHLC3: Oversold SELL" - Is triggered when the price exceeds the oversold level.
"DB CFHLC3: Undersold BUY" - Is triggered when the price goes below the undersold level.
Any other tips?
Once you have configured the indicator for your symbol and chart timeframe. Meaning the plots are displayed over the price. Check out larger timeframes such as W, 2W, 3W, 4W, M, and 4M. It works wonderfully for showing market lows and highs for long-term investing too!
Another, tip is to combine it with your favorite indicator, such as TTM Squeeze or MACD for confirmation purposes. You may be surprised how fast the indicator shows market direction changes on higher timeframes.
You can just as easily use a high timeframe such as D, 2D, or 3D for day trading due to how the linear price channel works.
Why am I not selling this indicator?
I would like to bless the TradingView community, and I enjoy publishing custom indicators.
If you enjoy this indicator, please consider leaving a thumbs up or a comment for others to know about your experience or recommendations.
Enjoy!
Leavitt Convolution [CC]The Leavitt Convolution 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 my Leavitt Projection script and I forgot to mention that both of these indicators are actually predictive moving averages. The Leavitt Convolution indicator doubles down on this idea by creating a prediction of the Leavitt Projection which is another prediction for the next bar. Obviously this means that it isn't always correct in its predictions but it does a very good job at predicting big trend changes before they happen. The recommended strategy for how to trade with these indicators is to plot a fast version and a slow version and go long when the fast version crosses over the slow version or to go short when the fast version crosses under the slow version. 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.
Regression Channel, Candles and Candlestick Patterns by MontyRegression Candles by ugurvu
Regression Channel by Tradingview
All Candlestick Patterns By Tradingview
This script was combined for a friend of mine who needed this.
This Script has regression candles by ugurvu, Regression channel and Candlestick patterns by tradingview.
The intention was to fuse these together so more information can be processed on the cost of a single indicator.
Leavitt Projection [CC]The Leavitt Projection 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 simple but is also the building block of many other indicators, so I'm starting with the publication of this one. Since this is the first in a series I will be publishing, keep in mind that the concepts introduced in this script will be the same across the entire series. The recommended strategy for how to trade with these indicators is to plot a fast version and a slow version and go long when the fast version crosses over the slow version or to go short when the fast version crosses under the slow version. 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.
I know many of you have wondered where I have been, and my personal life has become super hectic. I was recently hired full-time by TradingView, and my wife is pregnant with twins, and she is due in a few months. I will do my absolute best to get back to posting scripts regularly, but I will post a bunch today in the meantime to fulfill a special request from one of my loyal followers (@ashok1961).
Standard Deviation Channel V.1Standard Deviation channel For TradingView V.1
Many thanks to and Made with help from @rumpypumpydumpy
█ - How to add the indicator-
You can “Boost” the tool if you like it, then scroll down on this page to "Add to favorite indicators" so it will be saved in your favorites. Easiest way to add to chart past that is simply copy the indicators name, Navigate to a chart, then paste the indicators name into your chart's "Indicators" tab. It should then be immediately added to the current chart. If your display is not large enough, when you first add your channel,, you may realize that you see labels appear, but no channel. Simply scroll backwards in time until the chart loads. TradingView needs to be able to see the data you would like the channel to read in order to plot and display correctly. This is a simple one or two mouse wheel scroll and it will appear.
You may notice a compression of price scale. IF this happens simply right click your right price axis, a menu will appear, select “Scale price chart only”, and "Auto (fits data to screen) This will release the scale compression and let you view the channel and price normally. Once your Channel is added, loaded, and ready to go, you can proceed to settings. In the top left corner of your main chart there will be a Indicator title, hover that and click on the gear icon to access the channels custom settings. You can also double click any of the active plots from the channel or averages on the chart, and gain access to the settings panel through that.
█ OVERVIEW
Settings explained -
Inputs and color choices
You can think of the settings panel as 3 separate sections.
First - Look and feel- You will have your Channels visual inputs, Simple Yes or No check boxes on whether you would like to display the visual items listed. You can choose to display the channel in a multitude of ways, with or without half deviations, with no 2nd, 3rd, or 4th deviations. This first section is your quick access control panel to the visual feel and display of the channel and its items.
Then below that you will see quick access color presets for each deviation and half deviations. You can choose to leave these as is, or you can choose custom colors per your preference.
The positive and negative Second deviations (+/-2std) are colored by positive and negative slope of channel. This will help to show overall trend, whether up or down, positive or negative. User can change the positive and negative slope colors if they would like.
Second, - Time and Regression - Next as you scroll down the settings panel you will encounter the Time and regression settings. In order for the channel to match the channel used widely in TOS, we had to Preset the look back lengths into the code because on Tradingview we have an “Continuous left edge of the chart”. We needed to tell the channel how far to look back and start calculating. The frame work for this time logic came initially from the channel that was developed years back by @corgalicious, We then took that time logic and re-worked it in order to fit the parameters that the widely used and popular TOS channel has.
Above the time frame length back inputs you will find a dropdown menu "Regression method type". This will offer different methods of regression and calculating the standard deviation from the center linear regression line. It is preset to “Population standard deviation” which will mimic the widely used TOS channel. There is also a choice for “Regression method standard error, or RMSE. This is a similar regression style, but will result in a tighter fitting, smaller deviation measurement and channel all around. As well as a multitude of other regression styles thanks to the genius of @rumpypumpydumpy
All the time presets were carefully chosen based off Pre set time frames TOS offers for their widely used Standard deviation channel, and time frames I had noted as widely used. You as the user can change those look back windows if you prefer through the input length settings. I recommend using the stock settings in most scenarios. Trading view has a 5000 bar look back limit, so we have implemented “Max lookbacks” inside the code to avoid any user error or confusion. The standard error of the sample mean is an estimate of how far the sample mean is likely to be from the population mean, whereas the standard deviation of the sample is the degree to which individuals within the sample differ from the sample mean. For longer time frames and sample sets I tend to use Population Standard Dev setting. For smaller sample sets I will go with Linreg RMSE setting. This is a personal preference. It is encouraged to try all of them and see what fits your trading style the best.
If the user would like to use a "Max bar lookback and plot the maximum allowed length on the current time frame, Simply select, "Use the full range of data allowed in max bars back for calculation?" This will automatically search back on the current time frame and plot the channel 4999 bars back. User will have to SCROLL BACK in order to fully load the channel into view. Again, Tradingview needs to see the candles you would like to plot on.
Third, - Finally at the bottom of the settings I have included Exponential moving average clouds. These are NOT enabled by default. If the user would like them enabled simply check "show momentum average clouds" and "Show Candle EMA". These are Multiple time frame moving average clouds consisting of 72/89 length 3, and 5min exponential moving averages. I use these to simply show the front or back side of a move and to find if trend is strong or weakening. These are not always needed so they are turned off by default.
█ CONCEPTS
Reversion and Repulsion-
You will find that the channel linear regression trend line has two characteristic's, Reversion to the mean, and Repulsion away from the mean. Price either seeks to aggressively return to the mean when it has exited a normal distribution, or price seeks to aggressively move away from the mean in times of momentum. Most seek to participate in the move through MAJOR WHOLE deviation levels in one scenario or the other.
The idea behind using a Standard deviation channel is to see extension and find where in the move we are. Are you extended out to 3 or 4 deviation's up or down? If so, you could start to think about reversion back to the mean. Have you had a violent move down to -3 or -4 deviations in a sell off? Maybe look at reversion back up toward the mean off a whole deviation break. Have you broken out of a normal distribution at +1 deviation and are building trend? maybe seek to join trend.
I have found most success by using a Split screen style layout. On the left chart most will have a 1min intraday channel showing, and on the left chart a 4hr channel showing. The idea is to mark your longer time frame deviations onto your intraday time frame, and use the intraday Channel to guide you through the higher time framed move. The move through +/- 1 deviation is a high momentum area in most names as price either seeks to return to the mean, or move strongly away from the mean.
█ Time periods
The channel has pre determined lookback presets for each major time frame. These have been preset in the code to mimic the widely used channel in TOS to the best of our ability.
Preset timeframe lookbacks include.
//intraday shorter time frames. 1/2min with 2day lookbacks
'1D-1Min' - Default= 2D, minval=1, maxval=5
'1D-2Min' - Default= 2D, minval=1, maxval=7
//intraday shorter time frames. 3/5min with 5day lookbacks. User can set shorter or longer if they choose, up to a 5000k bar look back depending on their Data tier level, Basic, Pro, Pro+, Premium etc.
'5D-3Min' - Default= 5D, minval=1, maxval=7
'5D-5Min' - Default= 5D, minval=1, maxval=20
// larger intraday time frames, 10/15min with 5day look backs.
'5D-10Min' - Default= 5D, minval=1, maxval=20
'5D-15Min' - Default= 5D, minval=1, maxval=60
// "Swing style time frames" 30/60 min with 10 and 20 day look back.
'10D-30Min' - Default= 10D, minval=1, maxval=60
'20D-1Hr' - Default= 20D, minval=1, maxval=90
//longer lookbacks for larger time frames using day lookback with the exception of week/month
'90D-2Hr' - Default = 90D, minval=1, maxval=180
'4h ' - Default = 180D,minval=1, maxval=4999
'6h' - Default = 36D, minval=1, maxval=252
'5Yr-W' - Default = 260W,minval=1, maxval=260
'1Yr-1D' - Default = 252D,minval=1, maxval=4999
'1Yr-1W' - Default = 52W, minval=1, maxval=480
'5Yr-1M' - Default = 60W, minval=1, maxval=480
█ Minimum Window Size
Note that on each time frame you MUST quickly scroll out to the first bar that the channel should start calculating on in order for the channel to populate on longer time frame series. This is under construction and as soon as there is a fix or other way around this, it will be addressed.
█ NOTES
Enjoy!
In the end I encourage any who tries the Channel to really sit down and spend some time playing around with the settings in order to find out how they like the Channel set up. I usually run the default settings on a intraday 5min chart, and then another instance of the study on a 4 hour chart. That way I can see granular intraday levels, and macro long term levels in the same view. See what fit's you the best, and how you like to trade. Most of all ENJOY!
Good luck -
JMF.
IMPORTANT INFO-
As always, the creator of this code is NOT a licensed investment advisor. No output of this tool is to be taken as investment advice or a recommendation to buy or sell any security.
Trading is risky, any one using this tool acknowledges they CAN LOSE some if not all of their initial investment even with this tool enabled.
User assumes ALL RESPONSIBILITY when using this tool in their technical analysis. There is NO GUARANTEE THAT THE USE OF THIS TOOL WILL RESULT IN PROFIT Use at your own risk.
Auto Linear Trend Target x16Experienced traders always tell us that “Never trade against the trend.” or “Trend is our friend.”. Yes sure, no one wants to trade against the trend. However, there are a lot of trends with different types and cycles, then which trend to follow, which trend they are mentioning? This tool (also known as ALTT x16, Laser Net x16) will support us in identifying different linear trends with different cycles. Nearest history-based targets are also added for our convenience of completeness.
Markets: All.
Timeframes: All. Recommendation: 30m and above.
Periods: Up to 16.
Usage: The higher period of a trend, the more strength it has. Enter when price breakouts a trend line and exit at the nearest trend line and target.
RSI + MA, LinReg, ZZ (HH HL LH LL), Div, Ichi, MACD and TSI HistRelative Strength Index with Moving Average, Linear Regression, Zig Zag (Highs and Lows), Divergence, Ichimoku Cloud, Moving Average Convergence Divergence and True Strength Index Histogram
This script is based on zdmre's RSI script, I revamped a lot of things and added a few indicators from ParkF's RSI script.
Disable Labels in the Style tab and the histogram if you don't enlarge the indicator and it seems too small.
Look to buy in the oversold area and bounce of the support of the linear regression.
Look to sell in the overbought area and bounce of the resistance of the linear regression.
Look for retracement to the moving average or horizontal lines, and divergences for potential reversal.
RSI
The Relative Strength Index (RSI) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements.
Moving Average
Moving Average (MA) is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
Linear Regression
The Linear Regression indicator visualizes the general price trend of a specific part of the chart based on the Linear Regression calculation.
Zig Zag (Highs and Lows)
The Zig Zag indicator is used to identify price trends, and in doing so plots points on the chart to mark whenever prices reverse by a larger percentage point than a predetermined variable or marker.
Divergence
The divergence indicator warns traders and technical analysts of changes in a price trend, oftentimes that it is weakening or changing direction.
Ichimoku Cloud
The Ichimoku Cloud is a package of multiple technical indicators that signal support, resistance, market trend, and market momentum.
MACD and TSI Histogram
MACD can be used to identify aspects of a security's overall trend.
The True Strength Index indicator is a momentum oscillator designed to detect, confirm or visualize the strength of a trend.
Itakura-Saito Autoregressive Extrapolation of Price [Loxx]Itakura-Saito Autoregressive Extrapolation of Price is an indicator that uses an autoregressive analysis to predict future prices. This is a linear technique that was originally derived or speech analysis algorithms.
What is Itakura-Saito Autoregressive Analysis?
The technique of linear prediction has been available for speech analysis since the late 1960s (Itakura & Saito, 1973a, 1970; Atal & Hanauer, 1971), although the basic principles were established long before this by Wiener (1947). Linear predictive coding, which is also known as autoregressive analysis, is a time-series algorithm that has applications in many fields other than speech analysis (see, e.g., Chatfield, 1989).
Itakura and Saito developed a formulation for linear prediction analysis using a lattice form for the inverse filter. The Itakura–Saito distance (or Itakura–Saito divergence) is a measure of the difference between an original spectrum and an approximation of that spectrum. Although it is not a perceptual measure it is intended to reflect perceptual (dis)similarity. It was proposed by Fumitada Itakura and Shuzo Saito in the 1960s while they were with NTT. The distance is defined as: The Itakura–Saito distance is a Bregman divergence, but is not a true metric since it is not symmetric and it does not fulfil triangle inequality.
read more: Selected Methods for Improving Synthesis Speech Quality Using Linear Predictive Coding: System Description, Coefficient Smoothing and Streak
Data inputs
Source Settings: -Loxx's Expanded Source Types. You typically use "open" since open has already closed on the current active bar
LastBar - bar where to start the prediction
PastBars - how many bars back to model
LPOrder - order of linear prediction model; 0 to 1
FutBars - how many bars you want to forward predict
Things to know
Normally, a simple moving average is calculated on source data. I've expanded this to 38 different averaging methods using Loxx's Moving Avreages.
This indicator repaints
Related Indicators (linear extrapolation of price)
Levinson-Durbin Autocorrelation Extrapolation of Price
Weighted Burg AR Spectral Estimate Extrapolation of Price
Helme-Nikias Weighted Burg AR-SE Extra. of Price
Relative Andean ScalpingThis is an experimental signal providing script for scalper that uses 2 of open source indicators.
First one provides the signals for us called Andean Oscillator by @alexgrover . We use it to create long signals when bull line crosses over signal line while being above the bear line. And reverse is true for shorts where bear line crosses over signal line while being above bull line.
Second one is used for filtering out low volatility areas thanks to great idea by @HeWhoMustNotBeNamed called Relative Bandwidth Filter . We use it to filter out signals and create signals only when the Relative Bandwith Line below middle line.
The default values for both indicators changed a bit, especially used linreg values to create relatively better signals. These can be changed in settings. Please be aware that i did not do extensive testing with this indicator in different market conditions so it should be used with caution.
Linear Regression ChannelsThese channels are generated from the current values of the linear regression channel indicator, the standard deviation is calculated based off of the RSI . This indicator gives an idea of when the linear regression model predicts a change in direction.
You are able to change the length of the linear regression model, as well as the size of the zone. A negative zone size will make the zone stretch away from the center, and a positive zone size will make it stretch towards the centerline.
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.
Standard deviation channel of linear regression distance [AbAh]The indicator calculates the distance between linear regression line and the data point (price) as a percentage , then calculates the standard deviation for the linear regression distance , then draw the channel of two lines depending on the values of standard deviation .
///////// How to use ////////////////
1 - for Best result , indicator should be used on 2H frame Time of less : like 1H or 30 min
2 - The upper line and the lower line, both play a role as a support and resistance area, when the price bounces from the upper zone or lower zone, there is a high probability that it will move to the other line.
3 - The price breakout of one of the lower or upper lines may indicate a major price movement coming in the direction of the breakout
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MarketVision Screener█ OVERVIEW
• Screens 36 Assets at Once
• This Screener is Unique in that it turns my MarketVision series of Indicators Into a Complete Trading System
• To help you Automatically find Possible Turning Points in the Market the Following MarketVision Parameters are Displayed
o Linear Regression Direction and whether Price can be considered Over Bought / Sold according to the Linear Regression Channel (This works exceptionally well if used in confluence with manually drawn Fibonacci retracements)
o RSI value and Over / Very Over Bought / Sold condition
o Trend Meter – Shows Condition of the Trend Meter and its associated Trend / Money Flow Bar
o Wave Trend Crossing Condition taken from MarketVision B or Cipher B
o Wave Trend Divergences
o Super Trend Direction – Not a usual MarketVision parameter but it helps
• Furthermore you can choose where abouts on your chart you want the Screener displayed – this allows for multiple Screeners on one chart
█ HOW TO USE IT
• Look for Confluence between different parameters,
• For example Linear Regression Pointing Down and Price Over Bought according to both RSI and Linear Regression Channel, this is where you can look for maybe a Wave Trend cross down or a specific Candle Stick Pattern on you Chart with a Divergence
• Other confluences that work well are Trend Meter cross at the same time as a Wave Trend cross – Look for This Symbol "⯅ ⬱🡅⇶" or "⬱🡇⇶ ⯆"
• There are many possibilities the rest is up to you and your Trading Style / System
• Feel the Power
█ LIMITATIONS
• Can Not Set Alerts at This Stage – This is for a future Update or Script
• Slow Loading Time – As this is a rather long script Loading time is dependent on Internet Speed and your Computer Hardware
█ CREDITS
• Tradingview for the Pine Script Engine found under the hood of these amazing scripts
• QuantNomad and Others for their pioneering work making it possible to bring these sorts of advanced scripts to life
█ DISCLAIMER
• Not Financial Advice BUT
• Always use Proper Risk / Money Management – Never Risk more than you can Afford to Lose, Preferably not more than 1% - 2% of your Account
• Do Not FOMO or Revenge Trade
• Please remember that Past Performance may not be indicative of future results
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical Back Testing
Regression Channel with projectionEXPERIMENTAL:
Auto adjusting regressive channel with projection.
Linear regression is a linear approach to modeling the relationship between a dependent variable and one or more independent variables.
In linear regression , the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data.
Disclaimer :
Success in trading is all about following your trading strategy and indicators should fit into your own strategy, and not be traded purely on.
This script is for informational and educational purposes only. Use of the script does not constitute professional and / or financial advice. You are solely responsible for evaluating the outcome of the script and the risks associated with using the script. In exchange for the use of the script, you agree not to hold monpotejulien TradingView user responsible for any possible claims for damages arising out of any decisions you make based on the use of the script.
