MTM - Momentum IndicatorMTM - Momentum
Description
The Momentum indicator is a speed of movement indicator that is designed to identify the speed (or strength) of price movement. This indicator compares the current close price to the close price N bars ago and also displays a moving average of this difference.
Category
Momentum Indicators
Parameters
N ( Default: 6 Min: 1 Max: 100 )
N1 ( Default: 6 Min: 1 Max: 100 )
Chart Script
MTM : CLOSE-REF(CLOSE,N);
MTMMA : MA(MTM,N1)
www.edgerater.com
Trend
Generalized Bollinger Bands %B And Bandwidth (Tartigradia)Bollinger Band is simply a representation of the rolling average of price and its standard deviation around the average (called the "basis").
This indicator generalizes the Bollinger Band by implementing many different equations to calculate the Bollinger Bands beyond the standard deviation and sma, and then plot the %B (where the current price falls inside the Bollinger Band), Bandwidth (size of the Bollinger Band) as well as the Bollinger Band itself and a reproduction of the OHLC price candles in a separate pane.
Whereas other Bollinger Bands indicators often just change the basis but not the stdev calculation, the correct way to change the basis is to also change it inside the stdev calculation.
Advanced features such as temporal discounting (ie, newer bars can have more weights), median absolute deviation and multiple sigma bands (eg, 3-sigma) are available.
Up to 3 different Bollinger Bands can be displayed, and the background can be highlighted when price is overbought/oversold (beyond the Bollinger Band of choice). Tip: BB3, which is the bollinger band with standard deviation of 3, which represents 99% of observed values in the lookback period, is a good choice to highlight overbought/oversold conditions.
Three "Sentiment Bars" are provided to see at a glance the sentiments on the price action relative to the Bollinger Bands as reflected by the %B value.
Usage:
Use the %B as a measure of sentiment: bullish if > 0.5, bearish if < 0.5. You can use the Sentiment Bars at the bottom for a quick reference: aqua if bullish, red if bearish, gray if undefined (too close to the middle line).
Use the bandwidth as a measure of volatility: higher is more volatile, lower is less.
When overbought, it can be a good time to sell/short. Use a higher Bollinger Band Multiplier such as 3 or more to reduce false positives.
When oversold, it can be a good time to buy/long. Use a higher Bollinger Band Multiplier such as 3 or more to reduce false positives.
Consider setting a much tighter lookback period of 4 as recommended in backtested works (en.wikipedia.org), use zlma instead of sma, and finally set a higher timeframe for the Bollinger Bands than the one you are currently studying. Then, the Bollinger Bands can help in detecting overbought and oversold regions (price going "out of bands").
Note that I tried to automate the setting of a higher timeframe, but for some reason the output is different when I manually do it using request.security() than when it's in indicator(timeframe=""). If someone has any suggestion as to why it happens, please let me know! (You can try it for yourself by uncommenting the auto_timeframe parameter line).
Change of VolatilityOVERVIEW
The Change of Volatility indicator is a technical indicator that gauges the amount of volatility currently present in the market. The purpose of this indicator is to filter out with-trend signals during ranging/non-trending/consolidating conditions.
CONCEPTS
This indicator assists traders in capitalizing on the assumption that trends are more likely to start during periods of high volatility compared to periods of low volatility . This is because high volatility indicates that there are bigger players currently in the market, which is necessary to begin a sustained trending move.
So, to determine whether the current volatility in the market is low, the indicator will grey out all the areas on the chart whose short term standard deviation of volatility is lower than the long term standard deviation of volatility.
If the short term standard deviation of volatility is above the long term standard deviation of volatility, the current volatility in the market is considered high. This would the ideal time to enter a trending trade due to the assumption that trends are more likely to start during these high-volatility periods.
HOW DO I READ THIS INDICATOR
When the histogram is grey, don't take any trend trades since the current volatility is less than the usual volatility experienced in the market.
When the histogram is green, take all valid with-trend trades since the current volatility is greater than the usual volatility experienced in the market.
Q-TrendQ-Trend is an multipurpose indicatorm that can be used for swing- and trend-trading equally on any timeframe (non-volatile markets are better for this thing).
Settings:
Trend period - used to calculate trend line in the special moments(will explain below);
ATR Multiplier - changes sensitivity. The higher the multiplier = the more sensitive it is.
Also option to smooth source data (helps get cleaner signals, as always).
How to use?
Signals are given on the chart. Also ou can use trend line as S/R line.
The idea behind:
Terms:
SRС = Source
TL = trend line;
MP = ATR multiplier;
ATR = ATR :)
TL = (highest of source P-bars back + lowest of source P-bars back) / 2
Epsilon = MP * ATR
I was thinking for a week about combining volatility and relation between highest and lowest price point. That why I called indicator Q-Trend = Quantitative Trend , as I was trying to think about price in a mathematical way.
Okay, time to go philosophical:
1) TL is shows good price trend, but as it is slow enough and not enough informative, we need add additional conditions to produce signals.
2) Okay, so what can we add as conditions? We need to take volatility into account, as it is crucial in the moments of market uncertainty. So let's use ATR (Average True Range) somehow. My idea is that if SRC breaks TL + ATR , then it means that there will be upmove and we update our TL . Analogically for SRC breaking TL - ATR (breaks are crosses of TL +- ATR lines) .
Conclusion:
- if SRC breaks TL + ATR , it is a BUY signal and update of trend line;
- if SRC breaks TL - ATR , it is a SELL signal and update of trend line;
I think that such indicator already exisits on TradingView, as I've already saw something similar, but long ago, so please don't report, if such thing already exists.
But if not, then I hope, that you will gain some profits with Q-Trend :)
I will continue my work on this thing, so stay tuned.
Trade with your own risks and have your profits!
Wish you all the best!
- Tarasenko Fyodor
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
Relative Bi-Directional Volatility RangeThe basic math behind this Indicator is very similar to the math behind the Relative Strength Index without using a standard deviation as used for the Relative Volatility Index. The Volatility Range is calculated by utilizing the highs and lows. However not in the same way as in the Relative Volatility Index. This approach leads to different values, but the overall result clearly reveals the intrinsic Volatility of the chart, so the user can be aware, when something fundamentally is going on behind the scenes. If the Volatility rises on positive and negative range (-100 to 100) it implies that something fundamental is changing.
An advantage of using this kind of calculation is the possibility of separating the data into positive (buy pressure) and negative (sell pressure) components. The bi-directional character shows a slightly overhang in one of the directions, which can be used to detect a trend. A Moving Average of the users choice shell smoothen the overhang of the Relative Bi-Directional Volatility and show a trend direction. Similar to the math of the Relative Strength Index as standard a Relative Moving Average is preferred. If the Moving Average is in the positive range (0 to 100) it indicates a bullish trend, else if the Moving Average is in the negative range (0 to -100) it indicates a bearish trend. External Indicators can use a provided Trend Shift Signal which switches from 0 to 1, if the trend becomes bullish or from 0 to -1, if the trend becomes bearish.
The user should know, that in this Indicator the starting point of the Moving Averages always begins at the first bar, because the starting progress is approximated appropriately. Most Moving Averages require a minimum number of bars to be calculated, which is chosen with the Moving Average Length. In this cases the length used will be automatically reduced in the background until the number of bars is sufficient to match the chosen length. So if data history is very short, the Indicator can be used never the less as good as possible.
It is feasible to switch the Indicator on a higher timeframe, while staying in a lower timeframe on the chart. This can be useful for making the indication cleaner, if the Moving Average is to choppy and shows too many false signals. On the other hand the benefit of a higher timeframe (or a higher Moving Average Length) is paid with higher latency of the signaling. So the user has to decide what the best setting in his case is.
This Indicator can be used with all kinds of charts. Even charts with percentage or negative values should work fine.
Support & Resistance Trendlines with PP + Fib. Channel█ Support & Resistance Trendlines with Pivot Points + Fibonacci Channel
This script automatically draw support and resistance trend lines based on pivot points and add a fibonacci channel.
It will show potential patterns with the help of support and resistance lines as well as breakout target and pullback entry with the fibonacci extension and retracement levels.
It is based on atolelole's script, I only made it more configurable so please check out his script.
I added the possibility to change values and add additional retracement and extension levels.
I also made it customizable with the possibility to change lines color, width and style.
Keltner Channel Volatility FilterOVERVIEW
The Keltner Channel Volatility Filter indicator is a technical indicator that gauges the amount of volatility currently present in the market. The purpose of this indicator is to filter out with-trend signals during ranging/non-trending/consolidating conditions.
CONCEPTS
This indicator assists traders in capitalizing on the assumption that trends are more likely to start during periods of high volatility compared to periods of low volatility . This is because high volatility indicates that there are bigger players currently in the market, which is necessary to begin a sustained trending move.
So, to determine whether the current volatility in the market is low, the KCVF will grey out all bars whose average price is within the Keltner Channels.
If the average price breaks out of the Keltner Channels , it is reasonable to assume we are in a high-volatility period. Thus, this is the ideal time to enter a trending trade due to the assumption that trends are more likely to start during these high-volatility periods.
HOW DO I READ THIS INDICATOR
When the candles are greyed out, don't take any trend trades since the current volatility is less than the usual volatility experienced in the market.
When the candles aren't greyed out, take all valid with-trend trades since the current volatility is greater than the usual volatility experienced in the market.
Zig Zag+ (Macro + Internal Structure Tool)ZigZag+ (Macro + Internal Structure Tool)
ZigZag+ is a simple tool that helps traders to clearly identify and differentiate between macro and internal market structure, to help you keep your bearings of where you are currently in the overall picture.
It is especially difficult to keep your bearings within the larger structural trend when trading the lower timeframes, where for example, a bearish structural trend on a lower timeframe may simply be a retracement of an overall bullish structural trend on a higher timeframe. This indicator primarily aims to help traders maintain awareness of where they are in relationship to the higher timeframe / 'macro' structural trend, and their most significant swing point highs and lows.
The features of this indicator include:
- 2x Zig Zag lines drawn automatically onto your chart. One which has a longer length than the other, which can be used to help identify and differentiate the larger price swings from the smaller price swings found within it. Enabled by default.
- Customisable Zig Zag line color & width settings to help clearly differentiate the higher timeframe 'macro structure' apart from the lower timeframe 'internal structure' within it, enabling it to be tailored to suit your chart colour theme and personal preference.
- Customisable individual length settings for the 2x Zig Zag lines, to allow the fine tuning of each line to any timeframe and asset. By default one lines length is set to a higher value than the other, to illustrate a macro structure (higher length value) as well as the 'internal structure' (lower value length), seen within the larger macro structure.
- Up to a maximum of 500 lines can be drawn meaning you can zoom out considerably, and view historical price action with both Zig Zag lines continuing to print.
- Custom alerts for identifying candlesticks that can offer optimal entries where they are found within valid price markups or markdowns that are already underway. Further details can be found within the tooltips for these signals.
Note: The above list of features are accurate at the time of publishing, but may be updated or added to in future.
Structure
Understanding structure is arguably the foundation of all trading strategies, and therefore very important to understand where you are exactly in the bigger picture, since it can help identify levels at which there is a higher probability of price moving either upward or downward at a given point. Structural trend refers to the typical way that price tends to move in any given trending market, identified by the continuation of higher highs and higher lows in a typical bullish trending market, and lower highs and lower lows in a bearish trending market.
During other times price may not be trending in this way, for example when it is undergoing accumulation or distribution phases, where the consistent higher high & lower low / lower high and lower low patterns will not be evident.
What is Macro Structure?
Macro trend structure refers to the structural trend seen on higher timeframe charts.
What is Internal Structure?
Internal trend structure refers to the structural trend seen on lower timeframe charts, which is found within the higher timeframe structure.
Disclaimer: This indicator is adapted from an original script authored by Tr0sT . With special thanks.
Swing RibbonA configurable fast and slow moving average combined to help visualize the current trend and potential changes in trend.
Allows for specifying a fixed set of minutes or days instead of just bars so that the visualization is similar when changing time-frames.
Relatively Good Adviser This indicator uses the RSI as the backbone of an extremely sensitive two-indicator trend following system.
This indicator is unique in that it uses the RSI as an anchor to attempt to solve for color where there is divergence nearby.
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.
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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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".
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)
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