SQueezeVergenceThis is my SQueezeVergence indicator. It fires Buy and Sell signals based on squeeze momentum and trend. **It also creates Bull and Bear signals based on MACD divergence which should only be used as areas of support and resistance being as these signals repaint based on a 5 candle look back of pivots.** All settings are editable for better use. The default settings are what I use on the 1 Minute chart of ES to scalp. This is a simple indicator to help me get alerts on when I need to scalp. The divergence signals work well for areas of significance. I like to watch for breaks of these levels along with support and resistance. I hope this helps.
Trend
Unified Composite Index [UCI] [KuraiBlu] [LazyBear]The purpose of this indicator is to combine the four basic types of indicators (Trend, Volatility, Momentum and Volume) to create a singular, composite index in order to provide a more holistic means of observing potential changes within the market, known as the Unified Composite Index . The indicators used in this index are as follows:
Trend - Trend Composite Index
Volatility - Bollinger Bands %b
Momentum - Relative Strength Index
Volume - Money Flow Index
The average price source can’t be altered as I’ve made it an average between ((open + close) / 2) and ((high + low) / 2).
The best way to use this is by observing several of the indicators at once in conjunction with the average, rather than simply using the average produced to determine the right moment to enter, or exit a trade by itself. I've found when one indicator goes way out of bounds relative to the other three (and subsequently, the average array), then it presents a good buying, or selling opportunity.
Some adjustments were made to several of the indicators in order to standardize them on a scale of 1-100 so that they could better accommodate the average array that was finally produced. Thanks to LazyBear for letting me strip down the WaveTrend Oscillator.
Bayesian BBSMA + nQQE Oscillator + Bank funds (whales detector)Three trend indicators in one. Fork of Gunslinger2005 indicator, with a fix to display the nQQE oscillator correctly and clearly, and converted to pinescript v5 (allowing to set a different timeframe and gaps).
How to use: Essentially, nQQE is a long term trend indicator which is more adequate in daily or weekly timeframe to indicate the current market cycle. Banker Fund seems better suited to indicate current local trend, although it is sensitive to relief rallies. Bayesian BBSMA is an awesome tool to visualize the buildup in bullish/bearish sentiment, and when it is more likely to get released, however it is unreliable, so it needs to be combined with other indicators.
Please show the original indicators some love:
Bayesian BBSMA:
nQQE:
L3 Banker Fund Flow Trend:
Originally mixed together by Gunslinger2005:
Linear Average PriceWhat is "Linear Average Price"?
"Linear Average Price" is both a trend and an overbought oversold indicator .
What it does?
it creates a trendline and trading zones.
How it does it?
To create the trend line, it averages the difference between each data and chooses it as the slope of the line it creates. then it positions this line so that it passes right through the middle of the data at hand. It uses standard deviation to create trading zones.
How to use it?
It can be used both to have an idea about the trend direction and to determine buy-sell zones. You can choose how many candles the indicator will calculate from the "lenght" section. The "range" part is the coefficient of the standard deviation and can be used to expand or collapse zones.
Trend Dominance Multi Timeframe [Misu]█ This indicator shows the repartition of bullish and bearish trends over a certain period in multiple timeframes. It's also showing the trending direction at the time.
█ Usages:
Trend dominance is expressed with two percentages: left is downtrend and right is uptrend. Cell colors turn green if dominance is up and red if it is down.
Knowing the trend dominance allows you to have a better overview of the market conditions.
You can use it to your advantage to favor long or short trades, reversal or breakout strategies, etc.
█ Features:
> Table colors
> Instant Trend Multitimeframe
> Trend Dominance Multitimeframe
█ Parameters:
> Length: Length is used to calculate ATR.
> Atr Multiplier: A factor used to balance the impact of the ATR on the Trend Bands calculation.
> UI Settings
Performance Tablethis scrip is modified of Performance Table () of TradingView user @BeeHolder = Thank u very much.
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@BeeHolder formula is based on daily basis,
but my calculation is based on respective day, week and month.
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The formula of the calculation is (Current Close - Previous Close) * 100 / Previous Close, where Past value is:
1D = close 1 day before
5D = close 5 day before
1W - close 1 week before
4W = close 4 week before
1M - close 1 month before
3M - close 3 month before
6M - close 6 month before
12M - close 12 month before
52W - close 52 week before
Also table position cane be set.
thank you all
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[fpemehd] SSL Baseline StrategyHello Guys! Nice to meet you all!
This is my third script!
This Logic is trend following logic, This detects long & short trends based on SSL Hybrid Baseline.
This fits to the longer time frame like 4hr and 1d.
### Long Condition
1. close > SSL Hybrid baseline upper k
- Baseline is the ma of close price. (You can choose ma type and length)
- Upper k is the upper Keltner Channel.
### Short Condition
1. close < SSL Hybrid baseline lower k
- Baseline is the ma of close price. (You can choose ma type and length)
- Lower k is the lower Keltner Channel.
### Etc
1. Added Stoploss based on highest high or lowest low with lookback.
2. Strategy Template is based on @kevinmck100 template. Thank you!
Symbols at Highs & LowsFor the chosen symbols (Defaults to XLV, XLF, IWM, QQQ), this displays a table that indicates (by color) if each symbol is at the high or low of day. When used with the main indexes, If all symbols are at highs or lows together, this can be a great indicator that a trend day is occurring in the market. You can customize the indicator to use up to 8 symbols of your choice. You can also customize the appearance so that it only displays an "All symbols are at the Lows/Highs" message. Finally, you can customize the % threshold to use when measuring how close to the high/low of day price needs to be in order to be considered "at high/low of day".
Strategy Myth-Busting #8 - TrendSurfers+TrendOsc - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our 8th one is an automated version of the " 653% Gain Magical 1 Minute Scalping Strategy Tested 100 Times | Become Consistently Huge Profit " strategy from " Fxaccurate US " who claims to have achieved 653% profit scalping GOLD on the 5 minute timeframe. As you can see from the backtest results below, I was unable to substantiate anything close to that that claim on any timeframe or symbol. Myth 10000% busted.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
Trend Surfers - Premium Breakout + Alerts by TrendSurfersSignals
Mawreez' Trend Oscillator Indicator by Mawreez
Trading Rules:
1 min - 15 min candles
Stop loss middle between high and low Risk 1:2
Long Condition
Trend Surfers Trailing stop line goes below (Crosses) lowest low
Bullish Candle (red)
Mawreeze Trend Oscilator Indicator is green
Short Condition
Trend Surfers Trailing stop line goes above (Crosses) highest high
Bearish Candle (red)
Mawreeze Trend Oscilator Indicator is red
MA Simple Strategy with SL & TP & ATR FiltersHello Guys! Nice to meet you all!
This is my second script!
This Logic is trend following logic, This detects long & short trends by comparing the value of MAs.
This fits to the longer time frame.
### Long Condition
1. Compare 4 MAs (you can chose MA Type)
- Shortest MA (MA 1)
- Shorter MA (MA 2)
- Normal MA (MA 3)
- Longer MA (MA 4)
2. If MA 1 > MA 2 > MA 3 > MA 4, then Enter Long Position
- ‘The arrangement of MAs in descending orders’ is the proxy of the long trend.
### Short Condition
1. Compare 4 MAs (you can chose MA Type)
- Shortest MA (MA 1)
- Shorter MA (MA 2)
- Normal MA (MA 3)
- Longer MA (MA 4)
2. If MA 1 < MA 2 < MA 3 < MA 4, then Enter Short Position
- ‘The arrangement of MAs in ascending orders’ is the proxy of the short trend.
### Close Condition
1. When trend Changes
- When (MA 1 > MA 2 > MA 3 > MA 4) breaks or (MA 1 < MA 2 < MA 3 < MA 4) breaks.
2. When the price hits the stoploss
3. When the price hits the take profit level (basically 50% of qty will be closed)
### Etc
1. Trend filter (ATR should be bigger than SMA of ATR)
- If the volatility of price is to small (ATR), then there could be false signal. To filter this out, I used the condition ‘ATR should be larger than SMA of ATR’.
2. Stoploss
- Enabled Stoploss based on ATR, Percent, Risk-Reward Ratio,
- Enabled Trailing Stoploss.
3. Choose MA Type
- You can choose MA Type
+ Thanks for the stoploss template @jason5480
Bollinger BandsThis strategy is inspired from Power of Stock aka Subhasish Panni.
Target is minimum 1:3 when you get this setup right.
Buy when:
1) Low is greater than upper band of BB and next candle breaks high of that candle, SL is Low of previous candle which is has low above upper band.
2) High is lower than lower band of BB and next candle breaks high of that candle, SL is low of previous candle which has high lower than lower band.
Sell when:
1) Low is greater than upper band of BB and next candle breaks low of that candle, SL is high of previous candle which is has low above upper band.
2) High is lower than lower band of BB and next candle breaks high of that candle, SL is high of previous candle which has high lower than lower band.
Disclaimer: this setup will cause many small stoploss hit, you have to accept that loss but you will be profitable because of R:R.
Tradesharpe Session BiasThis script is designed for traders who want help defining their session bias it is for people who trade in sessions which will most likely be 1 4h candle. The way I trade using Price action to get my daily bias, to either look for sells or buys or both I look at the previous daily candle close and previous 4hr candle close before analyzing the structure on the lower time frames to get my session bias of bullish/bearish. so this indicator compares the daily and 4hr candles to develop a bias for example
previous daily bullish + Previous 4hr Bullish = BULLISH BIAS
previous daily Bearish + Previous 4hr Bearish = BEARISH BIAS
if Daily bullish 4hr bearish = MIXED SESSION
if daily bearish 4hr bullish = MIXED SESSION
MIXED SESSION = Can argue both buys and sells
BEARISH SESSION = Best to look for Sells only based on my trading style
BULLISH SESSION = Best to look for Buys only based on my trading style
NSDT MA+ADXThis script combines Moving Averages with ADX Strength, but with an added bonus. Rather than having the Moving Average line always plot on the chart, it will reference the ADX strength based on the settings by the trader.
This way, the Moving Average will not show on the chart unless there is also a strong direction in the trend. This may potentially be used to help with entries when trend trading due to adding the ADX for trend strength.
In the examples below, the ADX settings in the MA+ADX indicator are matched with the settings of a standalone ADX indicator at the bottom of the chart (not included, just for reference).
MA+ADX
prnt.sc
ADX Only
prnt.sc
You will see how the MA only plots when the ADX is over the threshold, currently set at 25. (arrows drawn to indicate confluence)
Volatility Stop with Vwap StrategyFirst the credits goes to @TradingView for their release of the volatility stop mtf indicator.
I have took it, and inside I have added a weekly vwap for a better trend direction and at the same time I have added a dynamic risk managment which is calculated from the distance between the volatility line to the close of the candle.
The rules for entry are simple:
For long:We enter when our close of the candle is above the volatility stop line and at the same time the close of the candle is above weekly vwap
For short we enter when our close of the candle is below the volatility stop line and at the same time the close of the candle is below weekly vwap.
We exit when we either have a reverse signal than the one we enterred, or based on the TP/SL which is calculated with the distance from vwap to the close of the candle.
If you have any questions please let me know !
MACD strategy + Trailstop indicatorWelcome traveler !
Here is my first indicator I made after 3 days of hardlearning pine code (beginner in coding).
I hope it will please you, if you have any suggestion to enhance this indicator, do not hesitate to give me your thoughts in the comments section or by Private message on trading View !
How does it works ?
It's a simple MACD strategy as describe here :
Uses of EMA 200 as a trend confirmer,
For sells :
When above Zero line (MACD) and under EMA200, we go on sell (background color is red)
For buys:
When under Zero line (MACD) and above EMA 200, we go on Buy (back ground color is green)
FILTERS !
I haded one filter to reduce noise on the indicator :
Signals aren't taken if one of the 14 last candles closed on the other side of the EMA 14.
What are the green and red lines ?
The green line is equivalent of a potential stop loss as a buyer side, same for the red one on seller side !
To make the space with the price bigger, please use "ATR multiplier" in the input options of the indicator while on your chart !
Is it timeframe specific ?
Hell no it is not timeframe specific ! You can try to use it on every timeframe !
As usual, I like to remind you that the best way to test an indicator is to go backtest it or to paper trade before using it on real market conditions !
If you find an idea of filter for a specific timeframe, do not hesitate to contact me ! I'll try to do my best to enhance this indicator as the time goes !
Is there repainting ?
There is no repainting on confirmation !
There's only a movement that I don't know how to ignore on the current open candle for the trail stop indicator I built, it should not be a problem if you place alerts to automatise your trading on the close of the candle, and not the high or low !
If you know how to resolve this problem with my code, I would be glad to get your tips to enhance the script ! :)
Example of the indicator in market (backtest, as said, no repaint on confirmation) :
ATR Trend FollowingThe script filters stocks on the basis of ATR. If the stock has moved above 7 times the ATR from the lows, the system generates buy signal and continues till the stock drops by 2 ATR. It is a good system in trending markets however in sideways consolidating markets, the system must be avoided. In trending markets it can generate good returns with significant Risk to Reward Ratio. Use it in confirmation with other trend depicting indicators is expected to generate better results.
FDI-Adaptive Non-Lag Moving Average [Loxx]FDI-Adaptive Non-Lag Moving Average is a Fractal Dimension Index adaptive Non-Lag moving Average. This acts more like a trend coloring indictor with gradient coloring.
What is the Fractal Dimension Index?
The goal of the fractal dimension index is to determine whether the market is trending or in a trading range. It does not measure the direction of the trend. A value less than 1.5 indicates that the price series is persistent or that the market is trending. Lower values of the FDI indicate a stronger trend. A value greater than 1.5 indicates that the market is in a trading range and is acting in a more random fashion.
Included
Bar coloring
Loxx's Expanded Source Types
STD-Adaptive T3 [Loxx]STD-Adaptive T3 is a standard deviation adaptive T3 moving average filter. This indicator acts more like a trend overlay indicator with gradient coloring.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included
Bar coloring
Loxx's Expanded Source Types
KERPD Noise Filter - Kaufman Efficiency Ratio and Price DensityThis indicator combines Kaufman Efficiency Ratio (KER) and Price Density theories to create a unique market noise filter that is 'right on time' compared to using KER or Price Density alone. All data is normalized and merged into a single output. Additionally, this indicator provides the ability to consider background noise and background noise buoyancy to allow dynamic observation of noise level and asset specific calibration of the indicator (if desired).
The basic theory surrounding usage is that: higher values = lower noise, while lower values = higher noise in market.
Notes: NON-DIRECTIONAL Kaufman Efficiency Ratio used. Threshold period of 30 to 40 applies to Kaufman Efficiency Ratio systems if standard length of 20 is applied; maintained despite incorporation of Price Density normalized data.
TRADING USES:
-Trend strategies, mean reversion/reversal/contrarian strategies, and identification/avoidance of ranging market conditions.
-Trend strategy where KERPD is above a certain value; generally a trend is forming/continuing as noise levels fall in the market.
-Mean reversion/reversal/contrarian strategies when KERPD exits a trending condition and falls below a certain value (additional signal confluence confirming for a strong reversal in price required); generally a reversal is forming as noise levels increase in the market.
-A filter to screen out ranging/choppy conditions where breakouts are frequently fake-outs and or price fails to move significantly; noise level is high, in addition to the background buoyancy level.
-In an adaptive trading systems to assist in determining whether to apply a trend following algorithm or a mean reversion algorithm.
THEORY / THOUGHT SPACE:
The market is a jungle. When apex predators are present it often goes quiet (institutions moving price), when absent the jungle is loud.
There is always background noise that scales with the anticipation of the silence, which has features of buoyancy that act to calibrate the beginning of the silence and return to background noise conditions.
Trend traders hunt in low noise conditions. Reversion traders hunt in the onset of low noise into static conditions. Ranges can be avoided during high noise and buoyant background noise conditions.
Distance between the noise line and background noise can help inform decision making.
CALIBRATION:
- Set the Noise Threshold % color change line so that the color cut off is where your trend/reversion should begin.
- Set the Background Noise Buoyancy Calibration Decimal % to match the beginning/end of the color change Noise Threshold % line. Match the Background Noise Baseline Decimal %' to the number set for buoyancy.
- Additionally, create your own custom settings; 33/34 and 50 length also provides interesting results.
- A color change tape option can be enabled by un-commenting the lines at the bottom of this script.
Market Usage:
Stock, Crypto, Forex, and Others
Excellent for: NDQ, J225, US30, SPX
Market Conditions:
Trend, Reversal, Ranging
Squeeze Index [LuxAlgo]The Squeeze Index aims to measure the action of price being squeezed, and is expressed as a percentage, with higher values suggesting prices are subject to a higher degree of compression.
Settings
Convergence Factor: Convergence factor of exponential envelopes.
Length: Period of the indicator.
Src: Source input of the indicator.
Usage
Prices being squeezed refer to the action of price being compressed within a tightening area. Prices in a tight area logically indicate a period of stationarity, price breaking out of this area will generally indicate the trader whether to buy or sell depending on the breakout direction.
The convergence factor and length settings both play an important role in the returned indicator values. A convergence factor greater than the period value will detect more squeezed prices area, while a period greater than the convergence will return fewer detected squeezed areas.
We recommend using a convergence factor equal to the period setting or a convergence factor twice as high.
The above chart makes use of a convergence factor of 100 and a period of 10.
Due to the calculation method, it is possible to see retracements being interpreted as price squeezing. This effect can be emphasized with higher convergence factor values.
Details
In order to measure the effect of price being squeezed in a tighter area we refer to damping, where the oscillations amplitude of a system decrease over time. If the envelopes of a damped system can be estimated, then getting the difference between the upper and lower extremity of these envelopes would return a decreasing series of values.
This approach is used here. First the difference between the exponential envelopes extremities is obtained, the logarithm of this difference if obtained due to the extremities converging exponentially toward their input.
We then use the correlation oscillator to get a scaled measurement.
SuperTrend Support & Resistance(My goal creating this indicator) : Provide a way to categorize and label key structures on multiple time frames so I can create a plan based on those observable facts.
The Underlying Concept / What is Momentum?
The Momentum shown is derived from a Mathematical Formula, SUPERTREND. When price closes above Supertrend Its bullish Momentum when its below Supertrend its Bearish Momentum. On the first bar bearish momentum is detected a resistance Level is made at the highest point of the previous bullish condition. On the first bar bullish momentum is detected a support Level is made at the lowest point of the previous bearish condition. As I become a better analyst I will find better techniques and this source code may become open-source, but as of now it remains protected. This indicator scans for bullish & bearish Momentum on the Timeframes selected by the user and when there is a shift in momentum on any of those time frames (price closes below or above SUPERTREND ) it notifies the trader with a Supply or Demand level with a unique color and Size to signify the severity of said level.
What is Severity?
Severity is How we differentiate the importance of different Highs and Lows. If Momentum is detected on a higher timeframe the Supply or Demand Level is updated. The Color and Size representing that higher timeframe will be shown. Demand and Supply Levels made by higher Timeframes are more SEVERE then a demand level made by a lower Timeframe.
Technical Inputs
- If you want to optimize the rate of signals to better fit your trading plan you would change the Factor input and ATR Length input. Increase factor and ATR Length to decrease the frequency of signals and decrease the Factor and ATR Length to increase the frequency of signals.
- to ensure the correct calculation of Support and Resistance levels change BAR_INDEX. BAR_INDEX creates a buffer at the start of the chart. For example: If you set BAR_INDEX to 300. The script will wait for 300 bars to elapse on the current chart before running. This allows the script more time to gather data. Which is needed in order for our dynamic lookback length to never return an error(Dynamic lookback length cant be negative or zero). The lower the timeframe the greater the amount of bars need. For Example if I open up a 30 sec chart I would enter 5000 as my BAR_INDEX since that will provide enough data to ensure the correct calculation of Support and Resistance levels.
Time Frame Inputs
- The indicator has 3 Time Frame Displays where you can choose how SEVERE You want the Supply and Demand Levels. For Example: 1min, 3min, 5min, 15 min Levels, 60 min levels Weekly Levels, etc.....The higher the Timeframe Selected the more SEVERE the Level.
- Use the Amount of time Frames input to increase or limit the amount of time frames that will be displayed onto the chart.
Display Inputs
- The toggle (Trend or Basic) option Lets the trend determine the colors of the Support and Resistance Levels or Basic where the color is strictly based on if its a high or a low ( Trend = HH,HL,LL,LH)
- Toggle options (Close) and (High & Low) creates Support and Resistance Levels using the Lowest close and Highest close or using the Lowest low and Highest high.
Toggle on both or toggle off both in order to use both these values when determining the trend of your chart. For Example this would mean (Price has to close higher then the highest high. Not only make a higher high or a
higher close) and the inverse (Price has to close lower then the lowest low. Not only make a lower low or a lower close)
How Trend Is being Determined ?
(Previous Supply Level > Current Supply Level ) if this statement is true then its s LH so the trend is bearish if this statement is false then its a HH so the trend is bullish
(Previous Demand Level > Current Demand Level ) if this statement is true then its a LL so the trend is bearish if this statement is false then its a HL so the trend is bullish
(Close > Current Supply Level ) if this statement is true technically price made a HH so the trend is bullish
(Close < Current Demand Level ) if this statement is true technically price made a LL so the trend is bearish
- Fully customize how you display and label Market Structure in specific timeframes. Line Length, Line Width, Line Style, Label Distance, Label Size, Label Background Size, and Background Color can all be customized.
- Lastly Is the Trend Chart. To Easily verify the current trend of any timeframes displayed by this indicator toggle on Chart On/Off . You also get the option to change the Chart Position and the size of the Trend Chart
*****The Current charts timeframe has to lower then a month to ensure correct calculation of Supply and Demand Levels*****
How it can be used ?
(Examples of Different ways you can use this indicator) : Easily categorize the severity of each and every Supply or Demand Level in the market (The higher the time frame the stronger the level)
: Quickly Determine the trend of any Timeframe
: Get a consistent view of a market and how different time frames are behaving but just use one chart.
: Take the discretion from hand drawing support and resistance lines out of your trading
: Find and categorize strong levels for potential breakouts
: Trend Analysis, Use multiple time frames to create a narrative based on observable facts from these time frames
: Different Targets to take money off the table
: Use labels to differentiate between different trend line setups
: Find Great places to move your stop loss too.
HMA-Kahlman Trend & Trendlines (v.2)This is an upgrade to the HMA-Kahlman Trend & Trendlines script ().
This version gives more flexibility because you can play around with 2 parameters to Kalman function (Sharpness and K (aka. step size)).
Moving Average Directional IndexMADX is ADX-inspired indicator with moving averages that determines strength of a trend, as well as its direction. Indicator works following:
As the value of MADX increases, so does the strength of a trend
If MADX+ ( green line - bullish MADX ) crosses above MADX- ( red line - bearish MADX ) we consider trend as bullish and vice versa..
There will be situations where MADX- and MADX+ cross multiple times in a short period of time -> that will mean that market indecision is happening and big move will most likely happen after it.
For the calculation of MADX+ and MADX- we need Moving Averages or Exponential Moving Averages with three specific sources ( high, close, low ).
Now, the calculation of each MADX will differ
=> for MADX+: Moving Average (high) / Moving Average (close)
=> for MADX-: Moving Average (close) / Moving Average (low)
Length of Moving Average is editable.
