Parabolic Hull MA [wm]
Based on Everget's Parabolic WMA and Mladen MT5 Hull MA.
Power = 1 behaves the same as a standard HMA , > 1 speeds it up, < 1 slows it down
Komut dosyalarını "hull+ma通达信源码" için ara
Professional MSTI+ Trading Indicator"Professional MSTI+ Trading Indicator" is a comprehensive technical analysis tool that combines over 20 indicators to generate high-quality trading signals and assess market sentiment. The script integrates standard indicators (MACD, RSI, Bollinger Bands, Stochastic, Simple Moving Averages, and Volume Analysis) with advanced components (Squeeze Momentum, Fisher Transform, True Strength Index, Heikin-Ashi, Laguerre RSI, Hull MA) and further includes metrics such as ADX, Chaikin Money Flow, Williams %R, VWAP, and EMA for in-depth market analysis.
Key Features:
Multiple Presets for Different Trading Styles:
Choose from optimal configurations like Professional, Swing Trading, Day Trading, Scalping, or Reversal Hunter. Note that the presets may not work perfectly on all pairs, and manual calibration might be required. This flexibility allows you to fine-tune the settings to align with your unique strategies and signals.
Multi-Layered Signal Filtering:
Filters based on trend, volume, and volatility help eliminate false signals, enhancing the accuracy of market entries.
Comprehensive Fear & Greed Index:
The indicator aggregates data from RSI, volatility, momentum, trend, and volume to gauge overall market sentiment, providing an additional layer of market context.
Dynamic Information Panel:
Displays detailed status updates for each component (e.g., MACD, RSI, Laguerre RSI, TSI, Fisher Transform, Squeeze, Hull MA, etc.) along with a visual strength bar that represents the intensity of the trading signal.
Signal Generation:
Buy and sell signals are generated when a predefined number of conditions are met and confirmed over multiple bars. These signals are clearly displayed on the chart with arrows, making it easier to spot potential entry and exit points.
Alert Setup:
Built-in alert conditions allow you to receive real-time notifications when trading signals are generated, helping you stay on top of market movements.
"Professional MSTI+ Trading Indicator" is designed to enhance your trading strategy by providing a multi-faceted market analysis and an intuitive visual interface. While the presets offer a robust starting point, they may require manual calibration on certain pairs, giving you the flexibility to configure your own unique strategies and signals.
Dynamic Market ScannerDynamic Market Scanner is a powerful tool for analyzing financial markets, combining a variety of indicators to provide clear and understandable signals.
Key Features:
- Signal Generation:
The main signals "Buy", "Sell", and "Hold" are formed based on the analysis of indicators:
- MACD
- RSI
- SMA
- EMA
- WMA
- Hull MA
Additional Analytical Tools:
- ATR is used to assess volatility and helps to understand the risk of the current market situation.
- SMA Ichimoku does not generate signals but is used to assess their accuracy.
- If the price is above the SMA, "Buy" signals are more likely, as this confirms the strength of the upward movement.
- If the price is below the SMA, "Buy" signals require additional confirmations.
Dashboard:
Displays the current price position relative to the indicators, helping the trader understand how strong or weak the current signals are.
Advantages of Using:
1. Signal Filtering:
The price position relative to the SMA Ichimoku helps to assess the likelihood of successful trades.
2. Volatility Analysis:
ATR provides additional information about risks and market fluctuations.
3. Comprehensive Approach:
Signal generation is based on a combination of key indicators, offering a multifaceted view of the market.
Explanation of Percent Calculation in the Table:
- The table shows the values of indicators such as MACD, ATR, EMA, SMA, WMA, and Hull MA in percentages. Percentages are calculated based on the current value of the indicator relative to its maximum and minimum.
- Percentages are displayed for each indicator, allowing traders to assess market conditions based on their current values.
Dynamic Market Scanner will become a reliable assistant in your technical analysis toolkit, providing a comprehensive overview of market conditions and helping to make informed trading decisions.
+ Bollinger Bands WidthHere is my rendition of Bollinger Bands Width. If you are unfamiliar, Bollinger Bands Width is a measure of the distance between the top and bottom bands of Bollinger Bands. Bollinger Bands themselves being a measure of market volatility, BB Width is a simpler, cleaner way of determining the amount of volatility in the market. Myself, I found the original, basic version of BB Width a bit too basic, and I thought that by adding to it it might make for an improvement for traders over the original.
Simple things that I've done are adding a signal line; adding a 'baseline' using Donchian Channels (such as that which is in my Average Candle Bodies Range indicator); adding bar and background coloring; and adding alerts for increasing volatility, and baseline and signal line crosses. It really ends up making for a much improved version of the basic indicator.
A note on how I created the baseline:
First, what do I mean by 'baseline?' I think of it as an area of the indicator where if the BB Width is below you will not want to enter into any trades, and if the BB Width is above then you are free to enter trades based on your system. It's basically a volatility measure of the volatility indicator. Waddah Attar Explosion is a popular indicator that implements something similar. The baseline is calculated thus: make a Donchian Channel of the BB Width, and then use the basis as the baseline while not plotting the actual highs and lows of the Donchian Channel. Now, the basis of a Donchian Channel is the average of the highs and the lows. If we did that here we would have a baseline much too high, however, by making the basis adjustable with a divisor input it no longer must be plotted in the center of the channel, but may be moved much lower (unless you set the divisor to 2, but you wouldn't do that). This divisor is essentially a sensitivity adjustment for the indicator. Of course you don't have to use the baseline. You could ignore it and only use the signal line, or just use the rising and falling of the BB Width by itself as your volatility measure.
I should make note: the main image above at default settings is an 8 period lookback (so, yes, that is quite fast), and the signal line is a Hull MA set to 13. The background and bar coloring are simply set to the rising and falling of the BB Width. Images below will show some different settings, but definitely play with it yourself to determine if it might be a good fit for your system.
Above, settings are background and bar coloring tuned to BB Width being above the baseline, and also requiring that the BB Width be rising. Background coloring only highlights increasing volatility or volatility above a certain threshold. Grey candles are because the BB Width is above the baseline but falling. We'll see an example without the requirement of BB Width rising, below.
Here, we see that background highlights and aqua candles are more prevalent because I've checked off the requirement that BB Width be rising. The idea is that BB Width is above the baseline therefor there is sufficient volatility to enter trades if our indicators give us the go-ahead.
This here is set to BB Width being above the signal line and also requiring a rising BB Width. Keep in mind the signal line is a Hull MA.
And this fourth and final image uses a volume-weighted MA as the signal line. Bar coloring is turned off, and instead the checkboxes for volatility advancing and declining are turned on under the signal line options. BB Width crosses up the signal line is advancing volatility, while falling below it is declining volatility. Background highlights are set to baseline and not requiring a rising BB Width. This way, with a quick glance you can see if the rising volatility is legitimate, i.e., is the cross up of the signal line coupled with it being above the baseline.
Please enjoy.
Hull MACDMACD constructed using Hull MA and triangular MA.
HMA overshoots while TMA lags, producing an interesting MACD even when the two MAs have the same period.
Coloring shows tops, bots, and inflections.
Legoux_MA<>Hull_MAArnaud Legoux MA > Hull MA
Long Hull period default, for use with low timeframe
probably not as good if a trading commision is applied etc
script open, help yourself :)
Well Rounded Moving AverageIntroduction
There are tons of filters, way to many, and some of them are redundant in the sense they produce the same results as others. The task to find an optimal filter is still a big challenge among technical analysis and engineering, a good filter is the Kalman filter who is one of the more precise filters out there. The optimal filter theorem state that : The optimal estimator has the form of a linear observer , this in short mean that an optimal filter must use measurements of the inputs and outputs, and this is what does the Kalman filter. I have tried myself to Kalman filters with more or less success as well as understanding optimality by studying Linear–quadratic–Gaussian control, i failed to get a complete understanding of those subjects but today i present a moving average filter (WRMA) constructed with all the knowledge i have in control theory and who aim to provide a very well response to market price, this mean low lag for fast decision timing and low overshoots for better precision.
Construction
An good filter must use information about its output, this is what exponential smoothing is about, simple exponential smoothing (EMA) is close to a simple moving average and can be defined as :
output = output(1) + α(input - output(1))
where α (alpha) is a smoothing constant, typically equal to 2/(Period+1) for the EMA.
This approach can be further developed by introducing more smoothing constants and output control (See double/triple exponential smoothing - alpha-beta filter) .
The moving average i propose will use only one smoothing constant, and is described as follow :
a = nz(a ) + alpha*nz(A )
b = nz(b ) + alpha*nz(B )
y = ema(a + b,p1)
A = src - y
B = src - ema(y,p2)
The filter is divided into two components a and b (more terms can add more control/effects if chosen well) , a adjust itself to the output error and is responsive while b is independent of the output and is mainly smoother, adding those components together create an output y , A is the output error and B is the error of an exponential moving average.
Comparison
There are a lot of low-lag filters out there, but the overshoots they induce in order to reduce lag is not a great effect. The first comparison is with a least square moving average, a moving average who fit a line in a price window of period length .
Lsma in blue and WRMA in red with both length = 100 . The lsma is a bit smoother but induce terrible overshoots
ZLMA in blue and WRMA in red with both length = 100 . The lag difference between each moving average is really low while VWRMA is way more precise.
Hull MA in blue and WRMA in red with both length = 100 . The Hull MA have similar overshoots than the LSMA.
Reduced overshoots moving average (ROMA) in blue and WRMA in red with both length = 100 . ROMA is an indicator i have made to reduce the overshoots of a LSMA, but at the end WRMA still reduce way more the overshoots while being smoother and having similar lag.
I have added a smoother version, just activate the extra smooth option in the indicator settings window. Here the result with length = 200 :
This result is a little bit similar to a 2 order Butterworth filter. Our filter have more overshoots which in this case could be useful to reduce the error with edges since other low pass filters tend to smooth their amplitude thus reducing edge estimation precision.
Conclusions
I have presented a well rounded filter in term of smoothness/stability and reactivity. Try to add more terms to have different results, you could maybe end up with interesting results, if its the case share them with the community :)
As for control theory i have seen neural networks integrated to Kalman flters which leaded to great accuracy, AI is everywhere and promise to be a game a changer in real time data smoothing. So i asked myself if it was possible for a neural networks to develop pinescript indicators, if yes then i could be replaced by AI ? Brrr how frightening.
Thanks for reading :)
Adaptive Multi-MA OptimizerAdaptive Multi-MA Optimizer
This indicator provides a powerful, customizable solution for traders seeking dynamically optimized moving averages with precision and control. It integrates multiple custom-built moving average types, applies real-time volatility-based optimization, and includes an optional composite smoothing engine.
🧠 Key Features
Dynamic Optimization:
Automatically selects the optimal lookback length based on market volatility stability using a custom standard deviation differential model.
Multiple Custom MA Types:
Includes fully custom implementations of:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume Weighted MA)
DEMA (Double EMA)
TEMA (Triple EMA)
Hull MA
ALMA (Arnaud Legoux MA)
Composite MA Option:
A unique "Composite" mode blends all supported MAs into a single average, then applies optional smoothing for enhanced signal clarity.
Dynamic Smoothing:
The composite mode supports volatility-adjusted smoothing (based on optimized lookback), making it adaptable to different market regimes.
Fully Custom Logic:
No built-in MA functions are used — every moving average is hand-coded for transparency and educational value.
⚙️ How It Works
Optimization:
The script evaluates a range of lengths (minLen to maxLen) using the standard deviation of price returns. It selects the length with the most stable recent volatility profile.
Calculation:
The selected MA type is calculated using that optimized length. If "Composite" is chosen, all MA types are averaged and smoothed dynamically.
Visualization:
The adaptive MA is plotted on the chart, changing color based on its position relative to price.
📌 Use Cases
Trend-following strategies that adapt to different market conditions.
Traders wanting a high-fidelity composite of multiple MAs.
Analysts interested in visualizing market smoothness without lag-heavy signals.
Coders looking to learn how to build custom indicators from scratch.
🧪 Inputs
MA Type: Choose from 8 MA types or a blended Composite.
Lookback Range: Control min/max and step size for optimization.
Source: Choose any price series (e.g., close, hl2).
⚠️ Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice, trading advice, or investment recommendations. Use of this script is at your own risk. Past performance does not guarantee future results. Always perform your own analysis and consult with a qualified financial advisor before making trading decisions.
Multi-timeframe Moving Average Overlay w/ Sentiment Table🔍 Overview
This indicator overlays selected moving averages (MA) from multiple timeframes directly onto the chart and provides a dynamic sentiment table that summarizes the relative bullish or bearish alignment of short-, mid-, and long-term moving averages.
It supports seven moving average types — including traditional and advanced options like DEMA, TEMA, and HMA — and provides visual feedback via table highlights and alerts when strong momentum alignment is detected.
This tool is designed to support traders who rely on multi-timeframe analysis for trend confirmation, momentum filtering, and high-probability entry timing.
⚙️ Core Features
Multi-Timeframe MA Overlay:
Plot moving averages from 1-minute, 5-minute, 1-hour, 1-day, 1-week, and 1-month timeframes on the same chart for visual trend alignment.
Customizable MA Type:
Choose from:
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
DEMA (Double EMA)
TEMA (Triple EMA)
WMA (Weighted MA)
VWMA (Volume-Weighted MA)
HMA (Hull MA)
Adjustable MA Length:
Change the length of all moving averages globally to suit your strategy (e.g. 9, 21, 50, etc.).
Sentiment Table:
Visually track trend sentiment across four key zones (Hourly, Daily, Weekly, Monthly). Each is based on the relative positioning of short-term and long-term MAs.
Sentiment Symbols Explained:
↑↑↑: Strong bullish momentum (short-term MAs stacked above longer-term MAs)
↑↑ / ↑: Moderate bullish bias
↓↓↓: Strong bearish momentum
↓↓ / ↓: Moderate bearish bias
Table Customization:
Choose the table’s position on the chart (bottom right, top right, bottom left, top left).
Style Customization:
Display MA lines as standard Line or Stepline format.
Color Customization:
Individual colors for each timeframe MA line for visual clarity.
Built-in Alerts:
Receive alerts when strong bullish (↑↑↑) or bearish (↓↓↓) sentiment is detected on any timeframe block.
📈 Use Cases
1. Trend Confirmation:
Use sentiment alignment across multiple timeframes to confirm the overall trend direction before entering a trade.
2. Entry Timing:
Wait for a shift from neutral to strong bullish or bearish sentiment to time entries during pullbacks or breakouts.
3. Momentum Filtering:
Only trade in the direction of the dominant multi-timeframe trend. For example, ignore long setups when all sentiment blocks show bearish alignment.
4. Swing & Intraday Scalping:
Use hourly and daily sentiment zones for swing trades, or rely on 1m/5m MAs for precise scalping decisions in fast-moving markets.
5. Strategy Layering:
Combine this overlay with support/resistance, RSI, or volume-based signals to enhance decision-making with multi-timeframe context.
⚠️ Important Notes
Lower-timeframe values (1m, 5m) may appear static on higher-timeframe charts due to resolution limits in TradingView. This is expected behavior.
The indicator uses MA stacking, not crossover events, to determine sentiment.
+ BB %B: MA selection, bar coloring, multi-timeframe, and alerts+ %B is, at its simplest, the classic Bollinger Bands %B indicator with a few added bells and whistles.
However, the right combination of bells and whistles will often improve and make a more adaptable indicator.
Classically, Bollinger Bands %B is an indicator that measures volatility, and the momentum and strength of a trend, and/or price movements.
It shows "overbought" and "oversold" spots on a chart, and is also useful for identifying divergences between price and trend (similar to RSI).
With + %B I've added the options to select one or two moving averages, candle coloring, and a host of others.
Let's start with the moving averages:
There are options for two: one faster and one slower. Or combine them how you will, or omit one or both of them entirely.
Here you will find options for SMA, EMA (as well as double and triple), Hull MA, Jurik MA, Least Squares MA, Triangular MA, Volatility Adjusted MA, and Weighted MA.
A moving average essentially helps to define trend by smoothing the noise of movements of the underlying asset, or, in this case, the output of the indicator.
All of these MAs available track this in a different way, and it's up to the trader to figure out which makes most sense to him/her.
MA's, in my opinion, improve the basic %B by providing a clearer picture of what the indicator is actually "seeing", and may be useful for providing entries and exits.
Next up is candle coloring:
I've added the option for this indicator to color candles on the chart based on where the %B is in relation to its upper and lower bounds, and median line.
If the %B is above the median but below the upper bound, candles will be green (showing bullish market structure). If %B is below the median but above the lower bound, candles will be red (denoting bearish market structure).
Overbought and oversold candles will also be colored on the chart, so that a quick glance will tell you whether price action is bullish/bearish or "oversold"/"overbought".
I've also added functionality that enables candles to be colored based on if the %B has crossed up or crossed down the primary moving average.
One example as a way to potentially use these features is if the candles are showing oversold coloration followed by the %B crossing up your moving average coloration. You might consider a long there (or exit a short position if you are short).
And the last couple of tweaks:
You may set the timeframe to whatever you wish, so maybe you're trading on the hourly, but you want to know where the %B is on the 4h chart. You can do that.
The background fill for the indicator is split into bullish and bearish halves. Obviously you may turn the background off, or make it all one color as well.
I've also added alerts, so you may set alerts for "overbought" and "oversold" conditions.
You may also set alerts for %B crossing over or under the primary moving average, or for crossing the median line.
All of these things may be turned on and off. You can pretty much customize this to your heart's delight. I see no reason why anyone would use the standard %B after playing with this.
I am no coder. I had this idea in my head, though, and I made it happen through referencing another indicator I was familiar with, and watching tutorials on YouTube.
Credits:
Firstly, thanks to www.tradingview.com for his brilliant, free tutorials on YouTube.
Secondly, thanks to www.tradingview.com for his beautiful SSL Hybrid indicator (and his clean code) from which I obtained the MAs.
Please enjoy this indicator, and I hope that it serves you well. :)
[CS] NWMA Moving Average 3.0PineScript Implementation of Moving Average 3.0 first referenced by Manfred G. Dürschner as New wma or Nwma.
See amazing original paper Moving Averages 3.0 at page 27:
ifta.org
As shown in the picture Nwma is performing better than DEMA, TEMA, EMA, and other common used moving averages such as Hull MA that is prone to overshooting. With NWMA lag is extremely reduced.
As already implemented in NinjaTrader C# Nwma plugin by sumana.m:
ninjatrader.com
(from the original paper)
Nyquist Criterion
In signal processing theory, the application of a MA to itself can be seen as a Sampling procedure. The sampled signal is the MA (referred to as MA1) and the sampling signal is the MA as well (referred to as MA2). If additional periodic cycles which are not included in the price series are to be avoided sampling must obey the Nyquist Criterion . With the cycle period as parameter, the usual one in Technical Analysis, the Nyquist Criterion reads as follows: n1 = λ*n2 , with λ ≥ 2. n1 is the cycle period of the sampled signal to which a sampling signal with cycle period n2 is applied. n1 must at least be twice as large as n2. In Mulloy´s and Ehlers´ approaches (referred to as Moving Averages 2.0) both cycle periods are equal. Moving Averages 3.0 Using the Nyquist Criterion there is a relation by which the application of a MA to itself can be described more precisely. In figure 2 a price series C (black line), one MA (MA1, red line) with lag L1 to the price series and another MA with lag L2 to MA1 (MA2, blue line) are illustrated. Based on the approximation and the relations described in figure 2 the following equation holds: (1) D1/D2 = (C – MA1)/(MA1 – MA2) = L1/L2 According to the lag formulas in the introduction L1/L2 can be written as follows:
α := L1/L2 = (n1 – 1)/(n2 – 1).
In this expression denominator 2 for the SMA and EMA as well as denominator 3 for the WMA are missing. α is therefore valid for all three MAs.
Using the Nyquist Criterion one gets for α the following result:
(2) α = λ* (n1 – 1)/(n1 – λ).
α put in (1) and C replaced by the approximation term NMA, the notation for the new MA, one gets:
NMA = (1 +α) MA1 – α MA2.
In detail, equation (2) reads as follows:
(3) NMA = (1 + α) MA1 – α
MA2 ,
(4) α = λ* (n1 – 1)/(n1 – λ), with λ ≥ 2.
(3) and (4) are equations for a group of MAs (notation: Moving Averages 3.0). They are independent of the choice of an MA. As the WMA shows the smallest lag (see introduction), it should generally be the first choice for the NMA. n1 = n2 results in the value 1 for α and λ, respectively. Then equation (3) passes into Ehlers´ formula. Thus Ehlers´ formula is included in the NMA formula as limiting value. It follows from a short calculation that the lag for NMA results in a theoretical value zero.
Please enjoy,
CryptoStatistical
Trend Strength Confidence Gauge LiteMost traders don’t fail from bad charts — they fail from bad timing. Jumping in too early, bailing too soon, or freezing when the move finally comes.
The Trend Strength Confidence Meter strips away the noise and highlights the three factors that matter most:
Trend → The confirmed direction of the market
Confidence → Concise tool clarity providing quick entries
Strength → Strength Score shows the underlying battle between buyers and sellers
How to Use It:
Watch the Moving Average Ribbon (Hull MA) for a flip: green = uptrend, red = downtrend.
Act only when ribbon color matches the Confidence thumbs-up.
Confirm with Strength 3+ before entry.
When trend, confidence, and strength align, you reduce risk and step in at tighter entry points — giving clarity for entries and conviction to hold through stronger moves.
Advanced Indicators Made Simple — Provided by The AI Trading Desk
End-of-Session ProbabilityThis indicator estimates the probability that the market will finish the session above a specified target price. It blends a statistical probability model with directional bias and optional morning momentum weighting to help traders gauge end-of-day market expectations.
Key Features:
• Statistical Probability Model:
Uses a normal distribution (with a custom normal CDF approximation) scaled by the square-root-of-time rule. The indicator dynamically adjusts the standard deviation for the remaining session time to compute a z‑score and ultimately the probability that the session close exceeds the target.
• Directional Bias via Daily HullMA (Exponential):
A daily Hull Moving Average (calculated using an exponential method) is used as a big-picture trend indicator. The model allows you to select your bias method—either by comparing the current price to the daily HullMA (Price method) or by using the HullMA’s slope (Slope method). A drift multiplier scales this bias, which then shifts the mean used in the probability calculations.
• Optional Morning Momentum Weight:
For traders who believe that early session moves provide useful clues about the day’s momentum, you can enable an optional weighting. The indicator captures the percentage change from the morning open (within a user-defined time window) and adjusts the expected move accordingly. A multiplier lets you control the strength of this adjustment.
• Visual Outputs:
The indicator plots quantile lines (approximately the 25%, 50%, and 75% levels) for the expected price distribution at session end. An abbreviated on-chart label displays key information:
• Target: The target price (current price plus a user-defined offset)
• Prob Above: The probability (in percentage) that the session close will exceed the target price
• Time: The time remaining in the session (in minutes)
How to Use:
1. Set Your Parameters:
• Expected Session Move: Input your estimated standard deviation for the full-session move in price units.
• Daily Hull MA Settings: Adjust the period for the daily HullMA and choose the bias method (Price or Slope). Modify the drift multiplier to tune the strength of the directional bias.
• Target Offset: Specify an offset from the current price to set your target level.
• Morning Momentum (Optional): Enable the morning momentum weight if you want the indicator to adjust the expected move based on early session price changes. Define the morning session window and set the momentum multiplier.
2. Interpret the Output:
• Quantile Lines: These represent the range of possible end-of-session prices based on your model.
• Abbreviated Label: Provides a quick snapshot of the target price, probability of finishing above that target, and time remaining in the session.
3. Trading Application:
Use the probability output as a guide to assess if the market is likely to continue in the current direction or reverse by session close. The indicator can help you decide on trade entries, exits, or adjustments based on your overall strategy and risk management approach.
This tool is designed to offer a dynamic, statistically driven snapshot of the market’s expected end-of-day behavior, combining both longer-term trend bias and short-term momentum cues.
Mean Reversion Indictor, Based on Standard Deviations Description:
The Reversal Candle Mean Reversion Indicator is designed for traders seeking to identify potential reversal points in the market based on key price action and volatility. This indicator combines price action analysis (sweeping prior highs or lows) with mean reversion theory, highlighting opportunities where the price tests or touches a moving average's standard deviation bands.
By focusing on these moments of price extremes, the indicator helps traders spot bullish and bearish reversal signals when the price retraces from volatile movements. These conditions often signal a return to the mean—an ideal setup for reversal traders who thrive on fading exaggerated price moves.
How It Works:
1. Price Action Reversal Signal:
* Bullish Reversal: The indicator flags a bullish signal when the current candle's low sweeps the prior candle's low, and the candle closes higher than the prior candle's close.
* Bearish Reversal: The indicator flags a bearish signal when the current candle's high sweeps the prior candle's high, and the candle closes lower than the prior candle's close.
2. Mean Reversion Confirmation:
* Mean Reversion Signal is triggered when the price touches or tests the upper or lower bands, calculated using a user-selected moving average (SMA, EMA, WMA, VWMA, or Hull MA) and standard deviation.
* The indicator combines price action and volatility, providing stronger reversal signals when the price reaches an extreme distance from the moving average.
3. Customization Options:
* Moving Average Type: Choose from SMA, EMA, WMA, VWMA, or Hull MA.
* Moving Average Length: Adjust the length of the moving average (default: 20).
* Standard Deviation Multiplier: Set the number of standard deviations for the volatility bands (default: 2.0).
* Custom Candle Colors: Choose custom colors for bullish and bearish reversal candles to easily spot signals.
How to Use for Trading Reversals:
1. Identify Extremes:
* Watch for candles where the price tests or touches the standard deviation bands. These are key moments when the price has moved significantly from the moving average, indicating a potential overbought or oversold condition.
2. Look for Reversals:
* When the price tests a band and simultaneously forms a bullish reversal pattern (sweeping the prior low and closing higher), it signals a potential mean reversion to the upside.
* When the price tests a band and forms a bearish reversal pattern (sweeping the prior high and closing lower), it signals a potential mean reversion to the downside.
3. Entry Points:
* Long Trades: Enter a long trade after a bullish signal appears (green candle) near the lower band, indicating a likely price reversal back towards the mean.
* Short Trades: Enter a short trade after a bearish signal appears (red candle) near the upper band, indicating a likely price pullback.
4. Exit Strategy:
* Set a profit target at the moving average (the mean) or a specific price level based on your strategy.
* Consider using a trailing stop to capture additional profit in case of a stronger reversal beyond the mean.
5. Risk Management:
* Place stops just below the low of the bullish reversal candle or just above the high of the bearish reversal candle to manage risk efficiently.
RedK_Momentum-based Step MA (MoStep_MA)Summary
==========
This script plots a "momentum based" stepping Moving Average of various types - the idea is to visualize price moves in levels (or steps) to reduce "chart noise" - avoid getting caught in sideway moves - and enable better trade entry and exit decision.
How does the MoStep_MA Work:
=============================
- we first choose a "base MA" of our preferred type: WMA, EMA, SMA and Hull MA are available - this base MA will be visible in light gray on the chart and can be completely hidden (although it is useful - see chart below)
- The steps are then created when a "momentum change" - expressed by a "relatively significant price move" - has been detected - either up or down
A "Significant price move" is defined as a price move that is relatively large compared to the "recent" average (absolute) price moves within a certain period
The "strength average" period can be adjusted - in terms of how the average is calculated (WMA, EMA, SMA), the number of bars (length) taken into consideration, as well as to include a "significance factor" of the price move relative to that average
using a significance factor of 1.5 is like saying: i want a new step only when the price move is 1.5 times the average price moves within the last (x) bars
the move has to be in the direction of the underlying MA trend - this is an additional condition i added, when i found that some moves will be significant but in the opposite direction and will cause a new step to be created - adding unnecessary "noise"
Default settings and other tweaks
===============================
By default, we use WMA for both the base MA and for calculating the average price change - other moving average types are available -
the significance factor is set to 1 by default.
feel free to experiment with other values and settings.
here's a chart with some additional notes - the significance factor here is set to 1.5 times the average price move.
- code is commented with further notes
- this indicator should not be used in isolation - as usual, it should be supported by other trend and momentum indicators to get proper confirmation of signals
RMI + Triple HMRSI + Double EVWRSI + TERSI + CMO StrategyThis is a strange experimental strategy WIP that I decided to upload an early version to share some of what I am working on. Just one script of a few.
It combines Chande Momentum with RMI and some weird ones I am experimenting with - Triple Hull MA RSI, Double Exponential + Volume Weighted RSI, Triple Exponential RSI. And to top it off, a final oscillator that combines the THMRSI with the RMI.
The main intention here, currently, is to test the usefulness of each on different timeframes and values. Currently it is considered to buy when all are below their threshold and sell when all are above, with the chande momentum crossing its line as the final confirmation.
For now there is no individual for each of the unique elements included. I am going to likely use this is a working house project to test other experimental indicators in the future.
It may be some of these are better suited for long term but I do think they have valid uses in checking short and long term momentum at the very least.
I copied the RMI from Everget.
Donchian Fibonacci Trading ToolDONCHIAN FIBONACCI TRADING TOOL
This indicator is based on a Donchian Channel with Fibonacci zones I published before. Features are added which enable trading decisions, it suggests when to open either a long or a short position, it provides suggestions for a stop loss level and suggests a take profit level, the calculation of the take profit suggestion can be altered in the inputs. The user should devise a trading strategy on his own, several strategies are possible, but as a Donchian Channel is used, these must come down to refinements in the classical Turtle Trading system.
NO LAGGING
Donchian Channels have no lagging, this tool being based on these, has none as well. The only added feature with a little lagging is the Hull MA, all other features work at once and report right now the historical context of the present bar or candle even while it is developping.
ANY TIME FRAME
This indicator works in any time frame. However, when the user sets the prediction calculation to percent, then in small intraday time frames the result will be relatively huge.
FALSE SIGNALS
Fibonacci retracement levels are based on inclinations which exist in nature and which also exist in the financial markets. The expectations, labeled ‘DFT: expect’, based on these levels, are usually correct. The take profit levels otoh, labeled ‘DFT: predict’, are usually incorrect. The trader should take care and needs proper ‘gut feeling’ in using these
FEATURES TRIGGERED BY THE MARKET ENTERING OR LEAVING ZONES
1. REACTIVE COLORS
The zone in which the close is, is brighter coloured.
2. ENTRY AND EXIT MARKERS NEAR UP- OR DOWN TREND ZONES
If the close enters the Up Trend or Down Trend zone, coming from another zone, a triangle is placed just outside the channel border. If it leaves the zone, an X cross is placed.
3. MARKET SITUATION EXPECTATION LEVELS (OFFSET)
The indicator can report four market situations which may be valid for the last candle:
3.1. Market is in up trend: a blue dot is placed in an offset (=future) position of the High Border,
expect levels are placed offset of High Border and the Highest Fibonacci line,
3.2. Market is in down trend: a red dot is placed offset the Low Border, also expect levels offset the Low Border and the Lowest Fibonacci line.
3.3. Market is high ranging, i.e. last break out was at High Border and market is not in up- or down trend. A green dot is placed offset the Center High Fibonacci line and expect levels offset the Highest and Center Low Fibonacci lines.
3.4. Market is low ranging, i.e. last break out was at Low Border and market is not in up- or down trend. A brown dot is placed offset the Center Low Fibonacci line and expect levels offset the Center High and Lowest Fibonacci lines.
FEATURES TRIGGERED BY AN ATTEMPT TO BREAK OUT OF THE CHANNEL BORDERS
4. SWING LINE
When the High Border is touched, the Swing Line changes its level to the Highest Fibonacci line and changes its color to blue. When the Low Border is touched, the Swing Line changes its level to the Lowest Fibonacci line and changes its color to red. This way you can see whether the general trend is up- or down and also if and when the line has been crossed.
5. DIAMOND MARKERS (OFFSET)
These markers flash when the last bar or candle or the one before that, touches a channel border, the offset is equal to the expect levels.
6. PREDICTION LEVEL (OFFSET)
The prediction level flashes in the same situation as the diamond marker. The default level is 1 Average True Range. Most are in fact false signals. One can switch the prediction level off by setting the added amount to 0, then only the Diamond Markers will flash
OTHER FEATURES
7. HULL MOVING AVERAGE
Its direction provides an indication of the price dynamics.
8. SUPPRESSION OF PLOTTING SOME LAST VALUES
Quite a few lines stop before the last bar or candle. This way the last candle seem free loating and the chart reports only the values the user needs.
Enjoy, Eykpunter.
MA Study: Different Types and More [NeoButane]A study of moving averages that utilizes different tricks I've learned to optimize them. Included is Bollinger Bands, Guppy (GMMA) and Super Guppy.
The method used to make it MtF should be more precise and smoother than regular MtF methods that use the security function. For intraday timeframes, each number represents each hour, with 24 equal to 1 day. For daily, 3 is 3 day, for weekly, 4 is the 4 weekly, etc. If you're on a higher timeframe than the one selected, the length will not change.
Log-space is used to make calculations work on many cryptos. The rules for color changing Guppy is changed to make it not as choppy on MAs other than EMA. Note that length does not affect SWMA and VWAP and source does not affect VWAP.
A short summary of each moving average can be found here: medium.com
List of included MAs:
ALMA: Arnaud Legoux
Double EMA
EMA: Exponential
Hull MA
KAMA: Kaufman Adaptive
Linear Regression Curve
LSMA: Least Squares
SMA: Simple
SMMA/RMA: Smoothed/Running
SWMA: Symm. Weighted
TMA: Triangular
Triple EMA
VWMA: Volume Weighted
WMA: Weighted
ZLEMA: Zero Lag
VWAP: Vol Weighted Average
Welles Wilder MA
Multi Time Frame Moving Averages [Anan]Hello friends,
All your popular moving average now in one indicator, also no need to open a lot of tabs to see where is that moving average at that time frame,
with multi time frame feature, now u can see up to six multi time frame MA in the same chart with option to show/hide it
list of moving averages:
SMA
Smooth SMA
SuperSmooth MA
EMA
DEMA
TEMA
Triangular MA
QEMA
RMA
Hull MA
KAMA
WMA
VWMA
VWAP
CTI
LSMA
VIDYA
Blackman Filter
Adaptive RSI
also there is an option to see the Average of four lengths, i backtest this and found it super great !
MMI SignalTrend trading strategies filtered by the Market Meanness Index.
This is a port of the experiment described at
www.financial-hacker.com
www.financial-hacker.com
www.financial-hacker.com
www.financial-hacker.com
The Market Meanness Index tells whether the market is currently moving in or out of a "trending" regime. It can this way prevent losses by false signals of trend indicators. It is a purely statistical algorithm and not based on volatility, trends, or cycles of the price curve.
The indicator measures the meanness of the market - its tendency to revert to the mean after pretending to start a trend. If that happens too often, all trend following systems will bite the dust.
Inputs
Price Source: Either open, high, low, close, hl2, hlc3, or ohlc4. The default value is hlc3.
Trend MA Type: Either SMA, EMA, LowPass, Hull MA, Zero-Lag MA, ALMA, Laguerre, Smooth, Decycle. The default value is LowPass.
Trend MA Period: Sets the lookback period of trend MA. The default value is 200.
MMI Period: Sets the lookback period of the Market Meanness Index. The default value is 300.
