Patreon Moving AverageThe Patreon moving average (PMA) is an adaptive moving average specifically designed to provide an optimal fit with the price while having a minimum amount of lag. The PMA can act as a fast-moving average for moving averages crossover system, detect trends, and filter out noisy variations from the price. The PMA is simple to use and interpret, and can be a really nice addition to your strategies, especially if they are based on moving averages.
The PMA integrates alerts based on the trend direction detected by the PMA.
Settings
Length: Determine the degree of filtering of the PMA.
Factor: Determine the sensitivity of the PMA to price variations, with higher values making the PMA less sensitive to price variations.
Decay: When higher than 0, introduce progressive smoothing, values closer to 0 return a faster progressive smoothing.
Src: Source input of the indicator.
Detect Trends With The PMA
The color of the PMA is related to the detected trend, with a blue color associated with an up-trend and a red color associated with a down-trend.
Higher values of Factor allows us to spot longer-term trends as well as filtering retracement in a trend.
Lower values of Length can also be used with higher values of Factor , this combination allows the PMA to actually be way less sensitive to price variations, thus returning less false signals while keeping a good fit with the price.
PMA As A Fast Moving Average
The PMA tries to provide crosses with a slow-moving average at the exact moment price cross the slow MA while minimizing the number of false signals.
PMA (In blue), EMA (in green), and SMA as a slow-moving average (in red), the PMA provide faster crosses while returning less false signals.
Progressive Smoothing
Progressive smoothing is obtained by using the Decay setting and allows the PMA to fit the price during extremely volatile markets and allows to preserve the structure of higher high's and lower low's.
Progressive smoothing can also minimize false signals.
In green/orange the PMA without progressive smoothing, in blue/red the PMA with progressive smoothing.
Finally progressive smoothing can give predictive and accurate estimates of the price central tendency
In green the mean of the price with a window size equal to the period the PMA is red, we can see that the PMA converges toward it extremely fast.
How To Access
The indicator is one of the "Patreon trend following indicators", and can only be used by my Patreons, you can become a Patreon by using the link on my signature.
Cari dalam skrip untuk "moving average crossover"
4K+ Candlestacks/ColumnCandles Plus PerksFor all candle analysis enthusiasts out there, this is my cutting edge "4K+ Candlestacks/ColumnCandles Plus Perks" that I spontaneously invented long ago. Just when you may have thought it was the end of the evolutionary line for candle technology, it's not! There are candlesticks and now "candlestacks". Your eyes are presently gazing upon a NEW candle type intended for destiny well into the 21st century and onward to support much higher graphics resolutions including 4K, 8K, 16K+ yielding enhanced chart analytics. With extremely high resolution display technologies arriving within the affordable range, having thin 1 pixel wide traditional candle wicks are going to become more and more visually apprehensible. Particularly for folks with a visual acuity that is not par at 20/20 or have some degree of color blindness, the candlestacks have a "large" amount of different color schemes to select from.
"Candlestick charts" are suspected to have been invented by Munehisa Homma well over 200 years ago. We have been using technology that is older than the age of distributed electricity and the modern car combined with billions at stake, hour to hour of each day. While candlesticks are effective, by having an abundance of computing power, the old candlestick wick width is becoming indistinguishably lost in the fog of a plenitude of plots. After a short time of contemplating about it linguistically in Pine Script, I arrived at a eureka moment having an actual working candle that was entirely novel. However, I didn't want to stop there. It required color finesse for diagnosed visual impairments combined with methods such as Heikin Ashi variants. My intention while inventing this was to provide the ultimate experience in candle technology that could potentially exist.
"Candlestacks" are just like the original OHLC candlesticks, however the "wick" portion is more like a column displaying visually increased situational awareness. Immediately at first sight, I originally conceived of the name "ColumnCandles" upon initial inspection of the plot, being it was remarkably similar to overlapping column charts I have been seeing for years with data metrics. In my attempt to formulate a worthier name, I noticed their appearance looks like stacks of blocks. Stacks, sticks, it sounded rhythmically sweet. I decided candlestacks would be a more appropriate name for this candle type distinguishable from candlesticks, but all to similarly sounding. I am hopeful I chose candlestacks as a fitting name that the rest of the world may come to appreciate one day when the planet is powered by nuclear "compact fusion" reactors and everyone has personal aerial transportation availability. "Candlestacks" vs "ColumnCandles", leave your opinion below in the comments if you are compelled to do so, providing a consensus. I respect your opinion either way...
Heikin Ashi, with it's advantages of identifying current short term trends, seemed worthy of inclusion, so I decided to expand on candlestacks with three different formulations to select from, including a fourth OHLC basic type. There are two distinct methods of Hieken Ashi employing pre-smoothing and post-smoothing techniques, each of which having capabilities of using different smoothing filters that are selectable.
Other features include a brightening option for the first descending candle which is best suited while using Heikin Ashi. The candlestacks wick transparency is independently controllable. Descending candlestacks have a darker wick than the ascending kind. With the Heikin Ashi smoothing techniques, I included a selection to see traditional candlestick wicks in a supplementary fashion. Also, there is an option to control the amount of candlestacks that are displayable. This is also a multicator including my "SWIFT Moving Average Crossover", which is complimentary to the candlestacks, especially in one of the Heikin Ashi modes. This moving average crossover(MAC), having multiple color schemes, limits the divergences between the leading and lagging lines. Of notable mention, the crossover dots on the SWIFT MAC you see, are actually one bar late. Lastly, with this flagship indicator, I included a multi-color "neon source" line to view close, hl2, etc... in combination with the candlestacks yielding the best of both worlds selectively. Any one of the individual indicators may actually be enabled/disabled independently. Being this is an overlay chart, I "may" include other overlay indicators in the future where they provide an added benefit to what is already included.
I provided multiple color schemes for those of you who may have color blindness vision impairments. You may contact me in private, if these color schemes are not suitable for your diagnosed visual impairment, and you wish to contribute to seeing the color schemes improved along with other future indicators I shall release.
I.P.O.C.S.: "Initial Public Offering Clean Start" proprietary technology. Firstly, many of my other indicators already possess this capability. It allows suitable plotting from day one, minute one of IPO, remedying visually delayed signal analysis. It's basically accurate plotting from the very first bar (bar_index==0) on Tradingview. If you don't know what this is, most people don't, go back to the VERY beginning of any stock on the "All" chart and compare it to other similar indicators. What's so special about this? It is extremely difficult to get a healthy plot from bar_index==0 on any platform. However, I have become exceedingly talented performing this feat in most cases, but not all depending on the algorithm. This indicator is a successful accomplishment implementing IPOCS. It's inherent value is predominantly for IPO traders who in the past have had to wait 20, 50, and 150 bars before they obtain a precise indicator measurement for the simplest of algorithms in order to make a properly informed decision to potentially invest in an asset. How is this achieved? It's a highly protected secret of mine... but I will say I rarely use Pine built-in functions at all. When I do, I use them scarcely due to currently existing Pine language limitations.
Features List Includes:
I.P.O.C.S.(Initial Public Offering Clean Start) Technology
Enable/disable dark background for enhanced visibility
Color schemes for individual indicators
Controls for Heikin Ashi candlestacks smoothing
Historical bar controls
"Neon Source" options
Many, many more previously described...
This is not a freely available indicator, FYI. To witness my Pine poetry in action, properly negotiated requests for unlimited access, per indicator, may ONLY be obtained by direct contact with me using TV's "Private Chats" or by "Message" hidden in my member name above. The comments section below is solely just for commenting and other remarks, ideas, compliments, etc... regarding only this indicator, not others. When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section if you do have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I will implement more ideas when they present themselves as worthy additions. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
Predictive EMAFrom the MQL5 Indicator database, here is what the author said about the script,
"Goal of this indicator:
Given three EMA's of varying lengths, use their values
for a estimator of "where we are now" or will be in the near future.
This is a very simplistic method, better ones are probably found
in the signal processing and target tracking literature.
A Kalman filter has been known since the 1950's 1960's and there
is better still. Nevertheless this is easily programmable in the
typical environments of a retail trading application like Metatrader4.
Method:
An an exponential moving average (EMA) or a simple moving average (SMA), for that
matter, have a bandwidth parameter 'L', the effective length of the window. This
is in units of time or, really, inverse of frequency. Higher L means a lower
frequency effect.
With a parameter L, the weighted time index of the EMA and SMA is (L-1)/2. Example:
take an SMA of the previous 5 values: -5 -4 -3 -2 -1 now. The average "amount of time"
back in the past of the data which go in to the SMA is hence -3, or (L-1)/2. Same applies
for an EMA. The standard parameterization makes this correspondence between EMA
and SMA.
Therefore the idea here is to take two different EMA's, a longer, and
a shorter of lengths L1 and L2 (L2 <L1). Now take the pairs:
which defines a line.
Extrapolate to , solve for y and that is the predictive EMA estimate.
Application:
Traditional moving averages, as simple-minded linear filters, have significant group delay.
In engineering that isn't so important as nobody cares if your sound from your iPod is delayed
a few milliseconds after it is first processed. But in markets, you can't
trade on the smoothed price, only the actual noisy, market price now. Hence you
ought to estimate better.
This statistic (what math/science people call what technical analysts call an 'indicator')
may be useful as the "fast" moving average in a moving average crossover trading system.
It could also be useful for the slow moving average as well.
For instance, on a 5 minute chart:
try for the fast: (will be very wiggly, note)
LongPeriod 25.0
ShortPeriod 8.0
ExtraTimeForward 1.0
and for the slow:
LongPeriod 500.0
ShortPeriod 50.0 to 200.0
ExtraTimeForward 0.0
But often a regular MA for the slow can work as well or better, it appears from visual inspection.
Enjoy.
In chaos there is order, and in that order there is chaos and order inside again.
Then, surrounding everything, pointy haired bosses. "
I may have done it incorrectly, feel free to revise
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI)
What is Lyapunov Market Instability?
Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes.
Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth.
Theoretical Foundation (Chaos Theory & Lyapunov Exponents)
In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories:
λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect)
λ < 0: System is stable—trajectories converge, perturbations die out
λ ≈ 0: Edge of chaos—transition between regimes
Phase Space Reconstruction
Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions:
Time-delay embedding: Create vectors from price at different lags
Nearest neighbor search: Find historically similar market states
Trajectory evolution: Track how these similar states diverged over time
Divergence rate: Calculate average exponential separation
Market Application
Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies
Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work
Transition zones: Market regime about to change, reduce position size, wait for confirmation
How LMI Works
1. Phase Space Construction
Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure.
2. Lyapunov Calculation
For each current state, we:
- Find similar historical states within epsilon (ε) distance
- Track how these initially similar states evolved
- Measure exponential divergence rate
- Average across multiple trajectories for robustness
3. Signal Generation
Chaos signals: When λ crosses above threshold, market enters trending regime
Stability signals: When λ crosses below threshold, market enters ranging regime
Divergence detection: Price/Lyapunov divergences signal potential reversals
4. Rothko Visualization
Color fields: Background zones represent market states with Rothko-inspired palettes
Glowing line: Lyapunov exponent with intensity reflecting market state
Minimalist design: Focus on essential information without clutter
Inputs:
📐 Lyapunov Parameters
Embedding Dimension (default: 3)
Dimensions for phase space reconstruction
2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns
4-5: Complex dynamics (stocks/indices) - captures intricate market structures
Higher dimensions need exponentially more data but reveal deeper patterns
Time Delay τ (default: 1)
Lag between phase space coordinates
1: High-frequency (1m-15m charts) - captures rapid market shifts
2-3: Medium frequency (1H-4H) - balances noise and signal
4-5: Low frequency (Daily+) - focuses on major regime changes
Match to your timeframe's natural cycle
Initial Separation ε (default: 0.001)
Neighborhood size for finding similar states
0.0001-0.0005: Highly liquid markets (major forex pairs)
0.0005-0.002: Normal markets (large-cap stocks)
0.002-0.01: Volatile markets (crypto, small-caps)
Smaller = more sensitive to chaos onset
Evolution Steps (default: 10)
How far to track trajectory divergence
5-10: Fast signals for scalping - quick regime detection
10-20: Balanced for day trading - reliable signals
20-30: Slow signals for swing trading - major regime shifts only
Nearest Neighbors (default: 5)
Phase space points for averaging
3-4: Noisy/fast markets - adapts quickly
5-6: Balanced (recommended) - smooth yet responsive
7-10: Smooth/slow markets - very stable signals
📊 Signal Parameters
Chaos Threshold (default: 0.05)
Lyapunov value above which market is chaotic
0.01-0.03: Sensitive - more chaos signals, earlier detection
0.05: Balanced - optimal for most markets
0.1-0.2: Conservative - only strong trends trigger
Stability Threshold (default: -0.05)
Lyapunov value below which market is stable
-0.01 to -0.03: Sensitive - quick stability detection
-0.05: Balanced - reliable ranging signals
-0.1 to -0.2: Conservative - only deep stability
Signal Smoothing (default: 3)
EMA period for noise reduction
1-2: Raw signals for experienced traders
3-5: Balanced - recommended for most
6-10: Very smooth for position traders
🎨 Rothko Visualization
Rothko Classic: Deep reds for chaos, midnight blues for stability
Orange/Red: Warm sunset tones throughout
Blue/Black: Cool, meditative ocean depths
Purple/Grey: Subtle, sophisticated palette
Visual Options:
Market Zones : Background fields showing regime areas
Transitions: Arrows marking regime changes
Divergences: Labels for price/Lyapunov divergences
Dashboard: Real-time state and trading signals
Guide: Educational panel explaining the theory
Visual Logic & Interpretation
Main Elements
Lyapunov Line: The heart of the indicator
Above chaos threshold: Market is trending, follow momentum
Below stability threshold: Market is ranging, fade extremes
Between thresholds: Transition zone, reduce risk
Background Zones: Rothko-inspired color fields
Red zone: Chaotic regime (trending)
Gray zone: Transition (uncertain)
Blue zone: Stable regime (ranging)
Transition Markers:
Up triangle: Entering chaos - start trend following
Down triangle: Entering stability - start mean reversion
Divergence Signals:
Bullish: Price makes low but Lyapunov rising (stability breaking down)
Bearish: Price makes high but Lyapunov falling (chaos dissipating)
Dashboard Information
Market State: Current regime (Chaotic/Stable/Transitioning)
Trading Bias: Specific strategy recommendation
Lyapunov λ: Raw value for precision
Signal Strength: Confidence in current regime
Last Change: Bars since last regime shift
Action: Clear trading directive
Trading Strategies
In Chaotic Regime (λ > threshold)
Follow trends aggressively: Breakouts have high success rate
Use momentum strategies: Moving average crossovers work well
Wider stops: Expect larger swings
Pyramid into winners: Trends tend to persist
In Stable Regime (λ < threshold)
Fade extremes: Mean reversion dominates
Use oscillators: RSI, Stochastic work well
Tighter stops: Smaller expected moves
Scale out at targets: Trends don't persist
In Transition Zone
Reduce position size: Uncertainty is high
Wait for confirmation: Let regime establish
Use options: Volatility strategies may work
Monitor closely: Quick changes possible
Advanced Techniques
- Multi-Timeframe Analysis
- Higher timeframe LMI for regime context
- Lower timeframe for entry timing
- Alignment = highest probability trades
- Divergence Trading
- Most powerful at regime boundaries
- Combine with support/resistance
- Use for early reversal detection
- Volatility Correlation
- Chaos often precedes volatility expansion
- Stability often precedes volatility contraction
- Use for options strategies
Originality & Innovation
LMI represents a genuine breakthrough in applying chaos theory to markets:
True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement
Rothko Aesthetic: Transforms complex math into meditative visual experience
Regime Detection: Identifies market state changes before price makes them obvious
Practical Application: Clear, actionable signals from theoretical physics
This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics.
Best Practices
Start with defaults: Parameters are optimized for broad market conditions
Match to your timeframe: Adjust tau and evolution steps
Confirm with price action: LMI shows regime, not direction
Use appropriate strategies: Chaos = trend, Stability = reversion
Respect transitions: Reduce risk during regime changes
Alerts Available
Chaos Entry: Market entering chaotic regime - prepare for trends
Stability Entry: Market entering stable regime - prepare for ranges
Bullish Divergence: Potential bottom forming
Bearish Divergence: Potential top forming
Chart Information
Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes
Academic References
Takens, F. (1981). "Detecting strange attractors in turbulence"
Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series"
Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents"
Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering.
Disclaimer
This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of chaos. Trade the regime, not the noise.
Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Liquidity Market Seeking SwiftEdgeThis indicator is designed to identify potential liquidity levels on the chart by detecting swing highs and lows, which are often areas where stop-loss orders or significant orders accumulate. It visualizes these levels with horizontal lines and labels on the right side of the chart, color-coded based on volume to help traders understand where the market might seek liquidity.
How It Works
Swing Highs and Lows: The indicator uses the ta.pivothigh and ta.pivotlow functions to identify significant swing points over a user-defined lookback period (Swing Length). These points are considered potential liquidity levels where stop-loss orders might be placed.
Volume Analysis: The indicator compares the volume at each swing point to the average volume over a specified period (Volume Average Length). Levels with above-average volume are colored red, indicating higher liquidity, while levels with below-average volume are colored green.
Liquidity Visualization: Horizontal dashed lines are drawn at each identified level, extending across the chart. Labels on the right side display the estimated liquidity amount (simulated based on volume and a multiplier, Volume Multiplier for Liquidity).
Sell Signal: A "SELL NOW" label appears when the price approaches a liquidity level after an uptrend (detected using a simple moving average crossover). This suggests a potential reversal as the market may target liquidity at that level.
Strategy Concept: Market Seeking Liquidity
The indicator is based on the concept that markets often move toward areas of high liquidity, such as clusters of stop-loss orders or significant order accumulations. These liquidity pools are typically found around swing highs and lows, where traders place their stop-losses or large orders. By identifying these levels and highlighting those with higher volume (red lines), the indicator aims to show where the market might move to "grab" this liquidity. For example, after an uptrend, the market may reverse at a swing high to take out stop-losses above that level, providing liquidity for larger players to enter or exit positions.
Settings
Swing Length: The number of bars to look back for detecting swing highs and lows. Default is 20.
Liquidity Threshold: The price threshold for merging nearby levels to avoid duplicates. Default is 0.001.
Volume Average Length: The period for calculating the average volume to compare against. Default is 20.
Volume Multiplier for Liquidity: A multiplier to scale the volume into a simulated liquidity amount (displayed as "K"). Default is 1000.
Usage Notes
Use this indicator on any timeframe, though it may be more effective on higher timeframes (e.g., 1H, 4H) where swing points are more significant.
Red lines indicate levels with higher volume, suggesting stronger liquidity pools that the market might target.
Green lines indicate levels with lower volume, which may be less significant.
The "SELL NOW" signal is a basic example of how to use liquidity levels for trading decisions. It appears when the price approaches a liquidity level after an uptrend, but it should be used in conjunction with other analysis.
Adjust the Volume Multiplier for Liquidity to scale the displayed liquidity amounts based on your instrument (e.g., forex pairs may need a higher multiplier than indices).
MA Win RateMoving Average Cross Win Rate
This simple yet useful script calculates the percentage of times a moving average crossover successfully predicts price movement.
Win Conditions:
1] A Golden Cross (fast MA crossing above slow MA) where the price moves up afterward.
2] A Death Cross (fast MA crossing below slow MA) where the price moves down afterward.
In this script, I have used a Simple Moving Average (SMA) for illustration.
You can modify the code to apply any type of moving average and test its accuracy.
TWAP + MA crossover Study [Dynamic Signal Lab]Dear TV'ers,
Hereby the study for the TWAP/moving average crossover, with taking profit options.
moving averages include: EMA , WMA , DEMA , TEMA , VAR, WWMA, ZLEMA , TSF , HULL, TILL
It is also possible to gradually take profit, using:
* minimum consecutive green/red candles
* minimum amount of green/red candles in the last 2-8 candles
* both of the above criteria
The slightly transparent green fill shows how much you are in profit from your entry point
The current default properties should be modified to make this strategy cost-effective, but typically 15 minutes and higher timeframes (up to 6hr) seem to work well for larger (top10 cap) crypto projects. Don't use this script for small-caps as it will get you rekt, due to wild volatility.
Additionally, you'll also be able to continuously take profit, making sure you lock in all those sweet profits. For backtesting: use the strategy version of this script
Trend-Quality IndicatorBINANCE:BTCUSDT
Open source version of the Trend-Quality Indicator as described by David Sepiashvili in [ Stocks & Commodities V. 22:4 (14-20) ]
Q-Indicator and B-Indicator are available both separately or together
█ OVERVIEW
The Trend-Quality indicator is a trend detection and estimation tool that is based on a two-step filtering technique. It measures cumulative price changes over term-oriented semicycles and relates them to “noise”. The approach reveals congestion and trending periods of the price movement and focuses on the most important trends, evaluating their strength in the process. The indicator is presented in a centered oscillator (Q-Indicator) and banded oscillator format (B-Indicator).
Semicycles are determined by using a short term and a longer term EMAs. The starting points for the cycles are determined by the moving averages crossover.
Cumulative price change (CPC) indicator measures the amount that the price has changed from a fixed starting point within a given semicycle. The CPC indicator is calculated as a cumulative sum of differences between the current and previous prices over the period from the fixed starting point.
The trend within the given semicycle can be found by calculating the moving average of the cumulative price change.
The noise can be defined as the average deviation of the cumulative price change from the trend. To determine linear noise, we calculate the absolute value of the difference between CPC and trend, and then smooth it over the n-point period. The root mean square noise, similar to the conventional standard deviation, can be derived by summing the squares of the difference between CPC and trend over each of the preceding n-point periods, dividing the sum by n, and calculating the square root of the result.
█ Q-INDICATOR
The Q-Indicator is a centered oscillator that fluctuates around a zero line with no upper or lower limits, is calculated by dividing trend by noise.
The Q-Indicator is intended to measure trend activity. The further the Q is from 0, the less the risk of trading with a trend, and the more reliable the trading opportunity. Values exceeding +2 or -2 can be qualified as promising
Values:
in the -1 to +1 range (GRAY) indicate that the trend is buried beneath noise. It is preferable to stay out of this zone
in the +1 to +2 or -1 to -2 range (YELLOW) indicate weak trending
in the +2 to +5 range (BLUE) or -2 to -5 range (ORANGE) indicate moderate trending
above +5 range (GREEN) or below -5 (RED) indicate strong trending
Readings exceeding strong trending levels can indicate overbought or oversold conditions and signal that price action should be monitored closely.
█ B-INDICATOR
The B-Indicator is a banded oscillator that fluctuates between 0 and 100, is calculated by dividing the absolute value of trend by noise added to absolute value of trend, and scaling the result appropriately.
The B-indicator doesn’t show the direction of price movement, but only the existence of the trend and its strength. It requires additional tools for reversal manifestations.
The indicator’s interpretation is simple. The central line suggests that the trend and noise are in equilibrium (trend is equal to noise).
Values:
below 50 (GRAY) indicate ranging market
in the 50 to 65 range (YELLOW) indicate weak trending
in the 65 to 80 range (BLUE) indicate moderate trending
above 80 (GREEN) indicate strong trending
The 65 level can be thought of as the demarcation line of trending and ranging markets and can help determine which type of technical analysis indicator (lagging or leading) is better suited to current market conditions. Readings exceeding strong trending levels can indicate overbought or oversold conditions.
Buff Averages [CC]The Buff Averages were created by Buff Dormeier (Stocks and Commodities Feb 2001) and this is another hidden gem that is a combo of a volume weighted indicator and a moving average crossover system. It uses a special method to calculate the weighting based on volume. The colored line (fast buff) will follow the price closely and you use the other line to act as a trend confirmation. I have included strong buy and sell signals in addition to normal ones so strong signals are darker in color and normal signals are lighter in color. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish!
Trend Analysis Index [CC]The Trend Analysis Index was created by Adam White and not to be confused with the Trend Analysis Indicator that I also published. This indicator operates under the same idea but using a completely different calculation to achieve similar results. The idea behind this indicator is for a combination of volatility and trend confirmation. If the indicator is above it's signal line then the stock is very volatile and vice versa. If the stock is currently trending as in above a chosen moving average for example and the indicator falls below the signal line then there is a pretty good chance in a trend reversal. The recommended buy and sell system to use is to pair this indicator with a moving average crossover system which I have included in the script. Buy when the indicator is above it's signal and the shorter moving average crosses above the longer moving average. For selling you would do the same and sell when the indicator is above it's signal and the shorter moving average crosses below the longer moving average. I have included strong buy and sell signals in addition to the normal ones so stronger signals are darker in color and normal signals are lighter in color.
Let me know what other indicators or scripts you would like to see me publish!
[blackcat] L1 Stick-Line Merged MACDLevel: 1
Background
The MACD is a superior derivative of moving average crossovers and was developed by Gerald Appel in 1979 as a market timing tool. MACD uses two exponential moving averages with different bar periods, which are then subtracted to form what Mr. Appel calls the Fast Line. A 9-period moving average of the fast line creates the slow line.
Function
L1 Stick-Line Merged MACD merges dif and dea lines with macd sticks by the same color candles. The generation of candles help to confirm the trend contiuation. E.g. yellow candles indicate up trend continuation while blue candles indicate down trend continuation
Key Signal
dif --> classic MACD diff fast line in yellow
dea --> classic MACD dea slow line in fuchsia
macd --> classic difference histogram
upslmerge --> up trend continuation yellow candle merge condition
dnslmerge --> down trend continuation blue candle merge condition
Pros and Cons
Pros:
1. merged line and stick with candles help confirm trend reversal
2. long entry signal is indicated.
Cons:
1. need sophisticated knowledge of MACD to use this well
2. this still requires a lot of MACD experience to obtain reliable trading signals
Remarks
Merge lines and sticks of MACD into candles. Better view of the trend
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
[blackcat] L1 Another Improved MACD IndicatorLevel: 1
Background
The MACD is a superior derivative of moving average crossovers and was developed by Gerald Appel in 1979 as a market timing tool. MACD uses two exponential moving averages with different bar periods, which are then subtracted to form what Mr. Appel calls the Fast Line. A 9-period moving average of the fast line creates the slow line.
Function
L1 Another Improved MACD Indicator improves MACD histogram by customized an algorithm and add three levels of long entry alerts derived from ema ().
Key Signal
diff --> classic MACD diff fast line in white
dea --> classic MACD dea slow line in yellow
macd --> classic difference histogram,but I did not use it directly in the plot.
macd1 --> ema3 of macd
Pros and Cons
Pros:
1. more clear sub level trend change with new histograms
Cons:
1. need sophisticated knowledge of MACD to use this well
2. this still requires a lot of MACD experience to obtain reliable trading signals
Remarks
Another improved MACD on histogram
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
[blackcat] L1 Improved MACD IndicatorLevel: 1
Background
The MACD is a superior derivative of moving average crossovers and was developed by Gerald Appel in 1979 as a market timing tool. MACD uses two exponential moving averages with different bar periods, which are then subtracted to form what Mr. Appel calls the Fast Line. A 9-period moving average of the fast line creates the slow line.
Function
L1 Improved MACD Indicator mainly improves MACD histogram by customized an algorithm and add three levels of long entry alerts derived from ema().
Key Signal
buy1 --> the 1st level of buy alert in green
buy2 --> the 2nd level of buy alert in lime
buy3 --> the 3rd level of buy alert in yellow
diff --> classic MACD diff fast line in white
dea --> classic MACD dea slow line in yellow
macd --> classic difference histogram,but I did not use it directly in the plot.
Pros and Cons
Pros:
1. more clear sub level trend change with new histograms
2. three levels of buy alerts
Cons:
1. need sophisticated knowledge of MACD to use this well
2. this still requires a lot of MACD experience to obtain reliable trading signals
Remarks
I am a fan of MACD. Even the most classic MACD can have in-depth usage. I think MACD is the king of indicators.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Vertical Horizontal Moving Average [AneoPsy & alexgrover] Moving average adapting to the strength of the trend, this is made possible by using the square of the vertical-horizontal filter as a smoothing factor. Alerts are included with two different types of conditions available to the user.
Settings
Length : Period of the moving average
Src : Input data for the indicator
Alerts : Types of conditions to be used in the alerts, when set to "VHMA Direction Change" alerts are triggered once the VHMA is either rising or declining, else the alerts are based on the crosses between Src and the VHMA
Usage
The VHMA can be used as a fast or slow-moving average in a moving average crossover system, or as input for other indicators.
VHMA of with length = 25 and sma with length = 200.
VHMA with length = 25 used as input for the RSI with length = 14.
Details
The vertical-horizontal filter is a measure of the strength of the trend and lay in a (0,1) range, to calculate it you just need to divide the rolling range over with the rolling sum of the absolute price changes, squaring the result allow to get lower results with higher values of length .
Squared vertical horizontal filter with length = 50, the value is low when the market is ranging and high when trending.
To set the alerts go in the alert panel, click on create alert, and select VHMA in "condition", choose between the buy or sell alert. If Src = closing price or another indicator dependant on the closing price select in options "once per bar close", if the indicator using the opening or lagged closing prices values as input select "One per bar" instead.
Thanks
Thanks to AneoPsy for adding the color change, the idea to use two kinds of conditions for the alert, and for its feedback, you can follow him
www.tradingview.com
and finally thanks to you for reading and for your support, only one last script left for the month, then we'll start July with some pretty interesting indicators, I hope you'll like them ^^/
MATRIX Flow Chart V.3DepthHouse Volume Flow indicator is used to help determine trend direction strictly based on Negative and Positive volume data.
How to Read:
- Moving Average crossovers are used to help determine a possible trend change or retracement.
- The area cloud on the bottom is calculated by the difference of the moving averages. This could be used to help determine the trending volume strength.
- Bright colored volume bars are large volume spikes calculated by the x factor in the options.
Other changes:
- DepthHouse is going open source with numerous of its indicators. This is only one of many!
- Volume is now displayed without being altered for calculations.
O indicador de fluxo de volume DepthHouse é usado para ajudar a determinar a direção da tendência estritamente com base nos dados de volume negativo e positivo.
Como ler:
- Média móvel crossovers são usados para ajudar a determinar uma possível mudança ou retração de tendência.
- A nuvem da área na parte inferior é calculada pela diferença das médias móveis. Isso pode ser usado para ajudar a determinar a força do volume de tendências.
- Barras de volume coloridas brilhantes são grandes picos de volume calculados pelo fator x nas opções.
Scripting Tutorial 5 - Triple Many Moving Averages CrossoversThis script is for a triple moving average indicator where the user can select from different types of moving averages and periods. This script improves upon tutorial 3 by adding source selection for MAs and another option for an MA that is not built-in, the HMA . It is meant as an educational script with well formatted styling, and references for specific functions.
Simple TrenderOriginates from:
I was reading some Impulse Trading literature by A. Elder.. In it, someone named Kerry Lovvorn proposed "An End of Day Trend Following System" for someone lazy.
Originally it is just price closing above an 8 ema (low) for long. Exit when price closes below an 8 ema (low). The opposite for a short position.
Conditions: Buy when price closed below ema (low) for two bars or more, then closes above. Opposite for a short position. I do not follow this condition. Though it may help with whipsaw.
My condition is when price closes above the 26 ema (low) (works the best for me) I place orders above the initial crossing bars high. Opposite for lows.
I look for stocks that are low in price to go long on. I want the run from 2's to 15's
I look for stocks that are mid-teens/20's in price to go short on. I want the run from 20's to 2's
I look for stock with news and earnings that are already running (up or down) to play the pullback.
These conditions can easily be scanned for on thinkorswim
From first glance, the system looks like CMsling shotsystem. Although, I plagiarized some parts of the codes, because I am inept when it comes to that shit, it differs as it is not a moving average crossover system.
It is a price crossing over concept. A moving average VWAP is used for best entries on pullbacks.
Purpose:
--To catch the majority of a trend/wave/run.
--To identify pullback areas to go long or short while in midst of trend. To catch pullbacks off news and earning runners.
--To catch the initial start of trend with clear rules to enter
--Clear rules to exit
Issues
--possibilities of getting ninja sliced the fuck up. Can be mitigated by entering stocks with decent average volume. And also only going long above 200 ema and short below it. ADX won't work, at the initial start of the trend it will show not trending. Can look at blow off volume at the bottom followed by increase in buying for long and vice versa for short.
--Can give some huge gains away through gap ups or gap downs from news or earnings during trend. However, can get huge gain on gaps from news or earning. Nature of the game.
--Need some brass balls and a supply of pepto to stomach through some of the pullbacks. Gut wrenching seeing big gains dwindle. But they all even out at the end, you hope. (see NBEV and IGC, and CRON and others. shit don't go in straight lines, homie)
Pros
--It's simple and easy. Overall, you profit
--works with any security
Cons
--It can be stressful.
--does not work well on lower time frames. Do not recommend going below 15 minutes
--Possibility of working on 5 minutes with a time frame breakout strategy (15,30 min).
Couple it with LazyBear "Weis Wave Volume" indicator. Works well for pullback entries.
Enjoy. Ride some waves.
MultiTradingSystemThis is example to show how you can combine two and more strategies for get
a cumulative signal. Result signal will return 1 if two (or more) strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
Chaikin's Volatility indicator compares the spread between a security's
high and low prices. It quantifies volatility as a widening of the range
between the high and the low price.
You can use in the xPrice1 and xPrice2 any series: Open, High, Low, Close, HL2,
HLC3, OHLC4 and ect...
Secon strategy
The Moving Average Crossover trading strategy is possibly the most popular
trading strategy in the world of trading. First of them were written in the
middle of XX century, when commodities trading strategies became popular.
This strategy is a good example of so-called traditional strategies.
Traditional strategies are always long or short. That means they are never
out of the market. The concept of having a strategy that is always long or
short may be scary, particularly in today’s market where you don’t know what
is going to happen as far as risk on any one market. But a lot of traders
believe that the concept is still valid, especially for those of traders who
do their own research or their own discretionary trading.
This version uses crossover of moving average and its exponential moving average.
Regime Scope | mad_tiger_slayerRegimeScope by mad_tiger_slayer
Adapt to the Market’s Mood. Trade in Sync with Regime Scope.
Overview
Regime Scope is an advanced multi-factor market regime identifier meticulously engineered to determine whether an asset is exhibiting trending behavior (Markup/Markdown phases) or mean-reverting dynamics (Sideways - Accumulation/Distribution). By integrating and synthesizing outputs from nine rigorously chosen statistical and volatility-based models, this tool offers a unified framework for assessing regime conditions with precision.
This indicator is best used in conjunction with other tools in your trading arsenal—serving not as a standalone signal generator, but as a high-value filter for confluence and strategic alignment. Whether you're trading breakouts, reversals, or mean-reversion setups, Regime Scope can elevate your system’s contextual awareness and execution timing.
How It Works – Part 1
Regime Scope calculates a composite "regime score" by normalizing and averaging a range of volatility and statistical measures. This score, which ranges between -1 and +1, indicates the likelihood of the market being in a trending versus mean-reverting state.
Values near +1 suggest a strong trending environment.
Values near -1 suggest strong mean-reversion (sideways, volatile) conditions.
Values between -0.30 and +0.30 are considered neutral and indicate choppy or range-bound market behavior.
When the average regime score crosses above the upper threshold, the asset likely enters a trending state.
When it crosses below the lower threshold, the market likely shifts to a volatile, mean-reverting state.
The histogram and dynamic background color provide an intuitive visual guide to the current regime.
How It Works – Part 2: Components
Each of the following sub-models has been carefully selected for its contribution to understanding price behavior. All components are normalized to create a consistent, unified score:
Phillips-Perron Test: Detects the presence of a unit root to infer stationarity and mean-reverting characteristics.
Hurst Exponent: Measures long-term memory in a time series to identify persistence or anti-persistence.
KPSS Test: Tests for level stationarity to contrast against unit-root behavior and validate trending assumptions.
GARCH Volatility: Captures volatility clustering and regime shifts in conditional variance.
Wavelet Transform: Decomposes price action into time-frequency space to extract non-linear and localized dynamics.
Half-Life of Mean Reversion: Estimates the speed at which price returns to its mean, enhancing the timing of reversion plays.
Augmented Dickey-Fuller (ADF) Test: Statistically verifies whether a series exhibits mean-reverting tendencies.
Garman-Klass-Yang-Zhang Volatility: A robust historical volatility measure using open-high-low-close data.
ADX (Average Directional Index): A classic technical tool for quantifying the strength of trend directionality.
How It Works – Part 3: Output Interpretation
All sub-models are normalized and synthesized into a single histogram plot shown in the lower chart panel.
+1.0 to +0.30: Indicates high probability of a directional, trending market.
-1.0 to -0.30: Indicates high probability of a sideways, mean-reverting regime.
-0.30 to +0.30: Suggests a neutral, uncertain market condition.
Transitions above or below these thresholds signal regime shifts.
Background shading adapts in real-time to visually reflect regime classification.
Features
Customizable thresholds to fine-tune sensitivity for regime classification.
Visual overlay positioning (choose from top-left, bottom-right, etc.).
Toggleable reference lines for regime thresholds.
Cross-timeframe consistency through dynamic normalization.
Each sub-model includes adjustable settings for personalized optimization.
Use Cases
Dynamically switch between trend-following and mean-reversion strategies.
Filter out choppy, low-probability zones by avoiding neutral regime periods.
Use regime score as confluence with entry/exit signals from other indicators.
Adapt strategies across timeframes—works well from scalping to swing trading.
Best used on timeframes ≥12H for macro regime context, but scalpers can benefit by using it on shorter windows with tuned parameters.
Scalping Use Case
Overlay the regime score on low timeframes (e.g., 1m–15m) and use it to avoid high chop zones or confirm breakout volume spikes during trending periods.
Long-Term Use Case
On 1D–1W charts, Regime Scope can filter false breakouts and confirm macro trend alignment for position trades or swing setups.
Tip
Combine Regime Scope with traditional technical tools like RSI, MACD, Bollinger Bands, or moving average crossovers to enhance strategic coherence.
For example, only act on breakout or trend-following signals when the regime score exceeds the upper threshold, confirming a high-trend environment.
Conversely, mean-reversion strategies like fading RSI extremes or trading Bollinger Band bounces work best when the regime score is in the lower range.
Aligning your tactical entries with the broader regime can significantly reduce false signals, enhance trade probability, and improve overall system robustness.
Price Lag Factor (PLF)📊 Price Lag Factor (PLF) for Crypto Traders: A Comprehensive Breakdown
The Price Lag Factor (PLF) is a momentum indicator designed to identify overextended price movements and gauge market momentum. It is particularly optimized for the crypto market, which is known for its high volatility and rapid trend shifts.
🔎 What is the Price Lag Factor (PLF)?
The PLF measures the difference between long-term and short-term price momentum and scales it dynamically based on recent volatility. This helps traders identify when the market might be overbought or oversold while filtering out noise.
The formula used in the PLF calculation is:
PLF = (Z-Long - Z-Short) / Stdev(PLF)
Where:
Z-long: Z-score of the long-term moving average (50-period by default).
Z-short: Z-score of the short-term moving average (14-period by default).
Stdev(PLF): Standard deviation of the PLF over a longer period (50-period by default).
🧠 How to Interpret the PLF:
1. Trend Direction:
Positive PLF (Green Bars): Indicates bullish momentum. The long-term trend is up, and short-term movements are confirming it.
Negative PLF (Red Bars): Indicates bearish momentum. The long-term trend is down, and short-term movements are consistent with it.
2. Momentum Strength:
PLF near Zero (±0.5): Low momentum; trend direction is not strong.
PLF between ±1 and ±2: Moderate momentum, indicating that the market is moving with strength but not in an overextended state.
PLF beyond ±2: High momentum (overbought/oversold), indicating potential trend exhaustion and a possible reversal.
📈 Trading Strategies:
1. Trend Following:
Bullish Signal:
Enter long when PLF crosses above 0 and remains green.
Confirm with other indicators like RSI or MACD to reduce false signals.
Bearish Signal:
Enter short when PLF crosses below 0 and remains red.
Use trend confirmation (e.g., moving average crossover) for better accuracy.
2. Reversal Trading:
Overbought Signal:
If PLF rises above +2, look for signs of bearish divergence or a reversal pattern to consider a short entry.
Oversold Signal:
If PLF falls below -2, watch for bullish divergence or a support bounce to consider a long entry.
3. Momentum Divergence:
Bullish Divergence:
Price makes a lower low while PLF makes a higher low.
Indicates weakening bearish momentum and a potential bullish reversal.
Bearish Divergence:
Price makes a higher high while PLF makes a lower high.
Signals weakening bullish momentum and a potential bearish reversal.
💡 Best Practices:
Combine with Volume:
Volume spikes during high PLF readings can confirm trend continuation.
Low volume during PLF extremes may hint at false breakouts.
Watch for Extreme Levels:
PLF beyond ±2 suggests overextended price action. Use caution when entering new positions.
Confirm with Other Indicators:
Use with Relative Strength Index (RSI) or Bollinger Bands to get a better sense of overbought/oversold conditions.
Overlay with a moving average to gauge trend consistency.
🚀 Why the PLF Works for Crypto:
Crypto markets are highly volatile and prone to rapid trend changes. The PLF's adaptive scaling ensures it remains relevant regardless of market conditions.
It highlights momentum shifts more accurately than static indicators because it accounts for changing volatility in its calculation.
🚨 Disclaimer for Traders Using the Price Lag Factor (PLF) Indicator:
The Price Lag Factor (PLF) indicator is designed as a technical analysis tool to gauge momentum and identify potential overbought or oversold conditions. However, it should not be relied upon as a sole decision-making factor for trading or investing.
Important Points to Consider:
Market Risk: Trading cryptocurrencies and other financial assets involves significant risk. The PLF may not accurately predict future price movements, especially during unexpected market events.
Indicator Limitations: No technical indicator, including the PLF, is infallible. False signals can occur, particularly in low-volume or highly volatile conditions.
Supplementary Analysis: Always combine PLF insights with other technical indicators, fundamental analysis, and risk management strategies to make informed decisions.
Personal Judgment: Traders should use their own discretion when interpreting PLF signals and never trade based solely on this indicator.
No Guarantees: The PLF is designed for educational and informational purposes only. Past performance is not indicative of future results.
Always perform thorough research and consider consulting with a professional financial advisor before making any trading decisions.
Quad Rotation StochasticQuad Rotation Stochastic
The Quad Rotation Stochastic is a powerful and unique momentum oscillator that combines four different stochastic setups into one tool, providing an incredibly detailed view of market conditions. This multi-timeframe stochastic approach helps traders better anticipate trend continuations, reversals, and momentum shifts with greater precision than traditional single stochastic indicators.
Why this indicator is useful:
Multi-layered Momentum Analysis: Instead of relying on one stochastic, this script tracks four independent stochastic readings, smoothing out noise and confirming stronger signals.
Advanced Divergence Detection: It automatically identifies bullish and bearish divergences for each stochastic, helping traders spot potential reversals early.
Background Color Alerts: When a configurable number (e.g., 3 or 4) of the stochastics agree in direction and position (overbought/oversold), the background colors green (bullish) or red (bearish) to give instant visual cues.
ABCD Pattern Recognition: The script recognizes "shield" patterns when Stochastic 4 remains stuck at extreme levels (above 90 or below 10) for a set time, warning of potential trend continuation setups.
Super Signal Alerts: If all four stochastics align in extreme conditions and slope in the same direction, the indicator plots a special "Super Signal," offering high-confidence entry opportunities.
Why this indicator is unique:
Quad Confirmation Logic: Combining four different stochastics makes this tool much less prone to false signals compared to using a single stochastic.
Customizable Divergence Coloring: Traders can choose to have divergence lines automatically match the stochastic color for clear visual association.
Adaptive ABCD Shields: Innovative use of bar counting while a stochastic remains extreme acts as a "shield," offering a unique way to filter out minor fake-outs.
Flexible Configuration: Each stochastic's sensitivity, divergence settings, and visual styling can be fully customized, allowing traders to adapt it to their own strategy and asset.
Example Usage: Trading Bitcoin with Quad Rotation Stochastic
When trading Bitcoin (BTCUSD), you might set the minimum count (minCount) to 3, meaning three out of four stochastics must be in agreement to trigger a background color.
If the background turns green, and you notice an ABCD Bullish Shield (Green X), you might look for bullish candlestick patterns or moving average crossovers to enter a long trade.
Conversely, if the background turns red and a Super Down Signal appears, it suggests high probability for further downside, giving you strong confirmation to either short BTC or avoid entering new longs.
By combining divergence signals with background colors and the ABCD shields, the Quad Rotation Stochastic provides a layered confirmation system that gives traders greater confidence in their entries and exits — particularly in fast-moving, volatile markets like Bitcoin.
AutoFibGauge (TechnoBlooms) AutoFibGauge help users to understand Fibonacci retracement with auto-drawn levels from previous candes, dual moving average crossover for trend confirmation, and a thermometer for quick Fib level identification.
This indicator is designed to streamline your trading decisions. By automatically plotting the Fibonacci levels based on previous candles, it aids in identifying key support and resistance zones. User can choose the number of previous candles for which the Fibonacci is calculated.
Paired with a dual moving average crossover system for robust trend confirmation, this tools helps in aligning with the market's direction.
A dynamic thermometer display that instantly highlights critical Fib levels, making it easier than ever to spot opportunities at a glance.
