Shenlong V2.3 - Trend cycleShenlong V2 is a script developed to facilitate the interpretation of long and short entries according to various conditionals that play with the trend.
The use of trend clouds has been implemented, which can be used as dynamic support / resistance . They also allow us to identify the current price cycle according to these guidelines, marking with a LONG or SHORT depending on the cycle in question. The appearance settings are user configurable. You can set alerts (long o short) to be aware of movements.
The use of recommended stop loss has been implemented, this can be used as a trailing stop to ensure profits or give the possibility of catching the trend, since it will move as the price forms its structure.
An information panel on stop prices has been implemented for ease of use.
"Cycle" için komut dosyalarını ara
Uber STC - Schaff Trend Cycle [UTS]Desc:
The Schaff Trend Cycle (STC) is a charting indicator that is commonly used to identify market trends and provide
buy and sell signals to traders.
Developed in 1999 by noted currency trader Doug Schaff, STC is a type of oscillator and is based on the assumption that,
regardless of time frame, currency trends accelerate and decelerate in cyclical patterns.
This indicators source code is based on Releasing the Code to the Schaff Trend Cycle.pdf
Executive Summary
Schaff Trend Cycle is a charting indicator used to help spot buy and sell points in the markets.
Compared to the popular MACD indicator, STC will react faster to changing market conditions.
A drawback to STC is that it can stay in overbought or oversold territory for long stretches of time.
General Usage
There are two lines indicating overbought and oversold conditions, default at 75 and 25 which is customizable of course.
Signals are created on line crosses. They that can be used to enter LONG/SHORT or EXIT a trade.
If the STC crosses the lower line upwards a LONG signal is triggered and if it crosses the upper line a SHORT signal is triggered.
Line crosses in the other direction than the current trade also work as EXIT signal.
Alerts
Traders can easily use the reversal signal to trigger alerts from:
Cross Up
Cross Down
Those values are > zero if a condition is triggered.
Alert condition example: "Cross Up" - "Greater Than" - "0"
Moving Averages
16 different Moving Averages are available:
ALMA (Arnaud Legoux Moving Average)
DEMA (Double Exponential Moving Average)
EMA (Exponential Moving Average)
FRAMA (Fractal Adaptive Moving Average)
HMA (Hull Moving Average)
JURIK (Jurik Moving Average)
KAMA (Kaufman Adaptive Moving Average)
Kijun (Kijun-sen / Tenkan-sen of Ichimoku)
LSMA (Least Square Moving Average)
RMA (Running Moving Average)
SMA (Simple Moving Average)
SuperSmoothed (Super Smoothed Moving Average)
TEMA (Triple Exponential Moving Average)
VWMA (Volume Weighted Moving Average)
WMA (Weighted Moving Average)
ZLEMA (Zero Lag Moving Average)
A freely determinable length allows for sensitivity adjustments that fits your own requirements.
Trader Set - Volume CycleThis is the cycle oscillator for the volume candle indicator. It supports all subt ypes but not 4 and 6 because how they are calculated (sub type 4 and 6 does not provide any cycle or any other type of possible calculation based on them by nature of the sub type)
B3 Bar Cycle MTF (fix)Apologies, there was an error in printing for the thick gray boxes, happened when MTF was switched on. All better, and here is the details from before:
This is an interesting study that can be used as a tool for determining trend direction, and also could be a trailing stop setter. I use it as a gauge on MTF settings. If on, you can look at the bar cycle of the 1h while on the 15m giving you a lot of information in one tool. If a line is missing high or low, it is because it was broken, if both exist you are trading in range and cloud appears. If both sides break you get thick gray boxes above and below bar.
Get used to editing the inputs to suit your liking. Often 3-5 length and always looking at different resolutions to get a big picture story. You could put multiple instances of the study up to see them simultaneously. I based the idea off of Krausz's 3 day cycle which you can read about in his teachings. I tend to find it looking better using Heikin Ashi bar-style.
B3 Bar Cycle MTFThis is an interesting study that can be used as a tool for determining trend direction, and also could be a trailing stop setter. I use it as a gauge on MTF settings, in the pic MTF is turned off. If on, you can look at the bar cycle of the 1h while on the 15m giving you a lot of information in one tool. If a line is missing high or low, it is because it was broken, if both exist you are trading in range and cloud appears. If both sides break you get thick gray boxes above and below bar.
Get used to editing the inputs to suit your liking. Often 3-5 length and always looking at different resolutions to get a big picture story. You could put multiple instances of the study up to see them simultaneously. I based the idea off of Krausz's 3 day cycle which you can read about in his teachings. I tend to find it looking better using Heikin Ashi bar-style.
Sharktank - Pi Cycle PredictionThe Pi Cycle indicator has called tops in Bitcoin quite accurately. Assuming history repeats itself, knowledge about when it might happen again could benefit you.
The indicator is fairly simple:
- A daily moving average of 350 ("long_ma" in script)
- A daily moving average of 111 ("short_ma" in script)
The value of the long moving average is multiplied by two. This way the longer moving average appears above the shorter one.
When the shorter one (orange colored) crosses above the longer (green colored) one, it could mean the top is in.
These moving averages rise at a certain rate. Using these rates we could try to estimate a possible crossover moment. That's exactly what this indicator does! It gives the user a prediction of when a crossover might happen.
Special thanks to:
- Ninorigo, for making his indicator public. This one uses his as a starting point.
- The_Caretaker, for coming up with this idea about calling a top. Yet, his is more price-based, this one is more time-based.
Correlation Cycle, CorrelationAngle, Market State - John EhlersHot off the press, I present this "Correlation Cycle, CorrelationAngle, and Market State" multicator employing PSv4.0, originally formulated by Dr. John Ehlers for TASC - June 2020 Traders Tips. Basically it's an all-in-one combination of three Ehlers' indicators. This power packed triplet indicator, being less than a 100 line implementation at initial release, is a heavily modified version of the original indicator using novel techniques that surpass John Ehlers' original intended design.
This is also a profound script in numerous ways. First of all, these three indicators are directly from the illustrious mastermind himself Dr. John Ehlers. Secondarily, this is my "50th" script published on TV, which makes it even more significant. I'm especially proud of this script to "degrees" of imagination I once didn't know was theoretically possible in code. My intellect has once again been mathemagically unlocked pondering new innovations with this code revelation. Thirdly, this PSv4.0 script shows the empowering beauty and elegance of hacking the stock markets with TV's ultra utilitarian Pine Editor(PE) in a common browser! Some of you may be wondering if I worked on this for days... nope! This only took a few hours, followed by writing this description for another hour plus.
I have created many of Ehlers' indicators in PE, a few of which I have published in my profile, but I wanted to show how programming with Pine Script can be an artistic form of craftsmanship and poetry. None of this would be possible without the ingeniously minded Tradingview staff revolutionizing algorithmic trading at it's finest. If you should ever encounter them by chance, ponder humbly thanking these computing wizards for their diligence and dedication. They are providing, and shall award to us members, some of the most fascinating conceptualized tech imaginable in the coming future. I can assure you, much, much more is yet to be unveiled for us TV members/enthusiasts. Thank you TV and all you offer to this community.
As always, I have included advanced Pine programming techniques that conform to proper "Pine Etiquette" by example. There are so many Pine mastery techniques included, I don't have an abundance of time to elaborate on all of them. For those of you are code savvy, you may have notice I only used one "for" loop for increased server efficiency, instead of the two "for" loops in the original formulation. For those of you who are newcomers to Pine Script, this code release may also help you comprehend the immense "Power of Pine" by employing advanced programming techniques while exhibiting code utilization in a most effective manner. This is commonly what my dense intricate code looks like behind the veil. If you are wondering why there is hardly any notes, that's because the notation is primarily in the variable naming.
Features List Includes:
Dark Background - Easily disabled in indicator Settings->Style for "Light" charts or with Pine commenting
AND a few more... Why list them, when you have the source code!
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, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may 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!
Seasonal PeriodsThe great trader and analyst W.D. Gann developed unique methods for forecasting market movements based on mathematical, astronomical, and geometrical principles. One of his key concepts is the use of time cycles and seasonal periods to identify potential market turning points and plan trading strategies.
Description of Seasonal Periods:
These periods are often based on astronomical events such as equinoxes and solstices, giving them symbolic significance in market analysis. Here is a brief description of each period:
1. March 20 – May 5 (1/8 year or 46 days): Spring equinox and the beginning of the active season.
2. June 21 (1/4 year or 91 days): Summer solstice – peak summer activity.
3. July 23 (1/3 year or 121 days): Stabilization period after the peak.
4. August 5 (3/8 year or 136 days): Beginning of preparation for the autumn season.
5. September 22 (1/2 year or 182 days): Autumn equinox – mid-year point.
6. November 8 (5/8 year or 227 days): Transition period to winter.
7. November 22 (2/3 year or 242 days): Intensification of winter trends.
8. December 21 (3/4 year or 273 days): Winter solstice – peak winter activity.
9. February 4 (7/8 year or 319 days): Preparation period for the spring cycle.
10. March 20 (1 year or 365 days): Completion of the full annual cycle.
Gann’s Application in Trading:
Gann used these seasonal periods to identify potential market turning points and determine optimal moments to enter or exit positions. Here's how he might have applied these periods:
1. Planning Entry and Exit Points: By analyzing previous market cycles within these periods, Gann could predict when the market might show strength or a reversal.
2. Determining Market Trends: Correlating price movements with seasonal periods helped Gann identify the prevailing trend and its strength.
3. Risk Management: Knowing which periods traditionally exhibit higher volatility or stability allowed traders to adjust position sizes and set stop-loss orders more effectively.
4. Synchronization with Astrological Cycles: Gann believed in the influence of astrological phenomena on markets, so he linked seasonal periods with astrological events for more precise forecasting.
5. Combining with Other Analytical Methods: Gann integrated seasonal periods with his famous geometric angles and price levels (e.g., 1x1, 2x1, etc.), creating a comprehensive analysis system.
Practical Examples:
- Identifying Reversals: For instance, if historically during the period from March 20 to May 5 there was an increase in price growth after a correction, Gann might use this interval to plan long positions.
- Exiting Positions: During periods when the market traditionally experiences pressure or correction (e.g., around the winter solstice), a trader might anticipate exiting long positions or opening short ones.
Conclusion:
Gann’s use of seasonal periods in trading is based on the assumption that markets move not only under the influence of current events but also recurring cycles related to the time of year and astronomical phenomena. While modern traders may use more advanced tools and analysis methods, understanding seasonal cycles and their impact on market trends remains a valuable element of technical analysis.
SW monthly Gann Days**Script Description:**
The script you are looking at is based on the work of W.D. Gann, a famous trader and market analyst in the early 20th century, known for his use of geometry, astrology, and numerology in market analysis. Gann believed that certain days in the market had significant importance, and he observed that markets often exhibited significant price moves around specific dates. These dates were typically associated with cyclical patterns in price movements, and Gann referred to these as "Gann Days."
In this script, we have focused on highlighting certain days of the month that Gann believed to have an influence on market behavior. The specific days in question are the **6th to 7th**, **9th to 10th**, **14th to 15th**, **19th to 20th**, **23rd to 24th**, and **29th to 31st** of each month. These ranges are based on Gann’s theory that there are recurring time cycles in the market that cause turning points or critical price movements to occur around certain days of the month.
### **Why Gann Used These Days:**
1. **Mathematical and Astrological Cycles:**
Gann believed that markets were influenced by natural cycles, and that certain dates (or combinations of dates) played a critical role in the price movements. These specific days are part of his broader theory of "time cycles" where the market would often change direction, reverse, or exhibit significant volatility on particular days. Gann's research was based on both mathematical principles and astrological observations, leading him to assign importance to these days.
2. **Gann's Universal Timing Theory:**
According to Gann, financial markets operate in a universe governed by geometric and astrological principles. These cycles repeat themselves over time, and specific days in a given month correspond to key turning points within these repeating cycles. Gann found that the 6th to 7th, 9th to 10th, 14th to 15th, 19th to 20th, 23rd to 24th, and 29th to 31st often marked significant changes in the market, making them particularly important for traders to watch.
3. **Market Psychology and Sentiment:**
These specific days likely correspond to key moments where market participants tend to react in predictable ways, influenced by past market behavior on similar dates. For example, news events or scheduled economic reports might fall within these time windows, causing the market to respond in a particular way. Gann's method involves using these cyclical patterns to predict turning points in market prices, enabling traders to anticipate when the market might make a reversal or face a significant shift in direction.
4. **Turning Points:**
Gann believed that markets often reversed or encountered critical points around specific dates. This is why he considered certain days more important than others. By identifying and focusing on these days, traders can better anticipate the market’s movement and make more informed trading decisions.
5. **Numerology:**
Gann also utilized numerology in his trading system, believing that numbers, and particularly certain key numbers, had significance in predicting market movements. The days selected in this script may correspond to numerological patterns that Gann identified in his analysis of the markets, such as recurring numbers in his astrological and geometric systems.
### **Purpose of the Script:**
This script highlights these "Gann Days" within a trading chart for 2024 and 2025. The color-coding or background highlighting is intended to draw attention to these dates, so traders can observe the potential for significant market movements during these times. By identifying these specific dates, traders following Gann's theories may gain insights into possible turning points, corrections, or key price movements based on the market's historical behavior around these days.
Overall, Gann’s use of specific days was based on his deep belief in the cyclical nature of the market and his attempt to tie those cycles to the natural laws of time, geometry, and astrology. By focusing on these dates, Gann aimed to give traders an edge in predicting significant market events and price shifts.
SW Gann Pressure time from tops and bottomsW.D. Gann's trading techniques often emphasized the significance of time in the markets, believing that specific time intervals could influence price movements. Here’s how the 30, 60, 90, 120, 180, and 270 bar intervals relate to Gann's rules:
1. **30 Bars**:
- Gann often viewed shorter time frames as critical for identifying short-term trends. A 30-bar interval can signify minor cycles or potential turning points in price.
2. **60 Bars**:
- This interval is significant as Gann believed in the importance of quarterly cycles. A 60-bar mark could indicate a completion of a two-month cycle, often leading to retracements or reversals.
3. **90 Bars**:
- Gann considered 90 days (or bars) to represent a quarter. This interval can signify a substantial shift in market sentiment or a pivotal point in a longer trend.
4. **120 Bars**:
- The 120-bar mark corresponds to about four months. Gann viewed longer intervals as more significant, often leading to major shifts in market trends.
5. **180 Bars**:
- A 180-bar period relates to a semi-annual cycle, which Gann regarded as critical for major support and resistance levels. Price action around this interval can reveal potential long-term trend reversals.
6. **270 Bars**:
- Gann believed that longer cycles, such as 270 bars (approximately nine months), could indicate significant market phases. This interval may represent major turning points and help identify long-term trends.
### Application in Trading:
- **Identifying Trends**: Traders can use these intervals to spot potential trend reversals or continuations based on Gann’s principles of market cycles.
- **Setting Targets and Stops**: Knowing where these key bars fall can help in setting profit targets and stop-loss orders.
- **Analyzing Market Sentiment**: Price reactions at these intervals can provide insights into market psychology and sentiment shifts.
By marking these intervals on a chart, traders can visually assess when price action aligns with Gann's theories, helping them make more informed trading decisions based on historical patterns and cycles.
Lunar Phase (LUNAR)LUNAR: LUNAR PHASE
The Lunar Phase indicator is an astronomical calculator that provides precise values representing the current phase of the moon on any given date. Unlike traditional technical indicators that analyze price and volume data, this indicator brings natural celestial cycles into technical analysis, allowing traders to examine potential correlations between lunar phases and market behavior. The indicator outputs a normalized value from 0.0 (new moon) to 1.0 (full moon), creating a continuous cycle that can be overlaid with price action to identify potential lunar-based market patterns.
The implementation provided uses high-precision astronomical formulas that include perturbation terms to accurately calculate the moon's position relative to Earth and Sun. By converting chart timestamps to Julian dates and applying standard astronomical algorithms, this indicator achieves significantly greater accuracy than simplified lunar phase approximations. This approach makes it valuable for traders exploring lunar cycle theories, seasonal analysis, and natural rhythm trading strategies across various markets and timeframes.
🌒 CORE CONCEPTS 🌘
Lunar cycle integration: Brings the 29.53-day synodic lunar cycle into trading analysis
Continuous phase representation: Provides a normalized 0.0-1.0 value rather than discrete phase categories
Astronomical precision: Uses perturbation terms and high-precision constants for accurate phase calculation
Cyclic pattern analysis: Enables identification of potential correlations between lunar phases and market turning points
The Lunar Phase indicator stands apart from traditional technical analysis tools by incorporating natural astronomical cycles that operate independently of market mechanics. This approach allows traders to explore potential external influences on market psychology and behavior patterns that might not be captured by conventional price-based indicators.
Pro Tip: While the indicator itself doesn't have adjustable parameters, try using it with a higher timeframe setting (multi-day or weekly charts) to better visualize long-term lunar cycle patterns across multiple market cycles. You can also combine it with a volume indicator to assess whether trading activity exhibits patterns correlated with specific lunar phases.
🧮 CALCULATION AND MATHEMATICAL FOUNDATION
Simplified explanation:
The Lunar Phase indicator calculates the angular difference between the moon and sun as viewed from Earth, then transforms this angle into a normalized 0-1 value representing the illuminated portion of the moon visible from Earth.
Technical formula:
Convert chart timestamp to Julian Date:
JD = (time / 86400000.0) + 2440587.5
Calculate Time T in Julian centuries since J2000.0:
T = (JD - 2451545.0) / 36525.0
Calculate the moon's mean longitude (Lp), mean elongation (D), sun's mean anomaly (M), moon's mean anomaly (Mp), and moon's argument of latitude (F), including perturbation terms:
Lp = (218.3164477 + 481267.88123421*T - 0.0015786*T² + T³/538841.0 - T⁴/65194000.0) % 360.0
D = (297.8501921 + 445267.1114034*T - 0.0018819*T² + T³/545868.0 - T⁴/113065000.0) % 360.0
M = (357.5291092 + 35999.0502909*T - 0.0001536*T² + T³/24490000.0) % 360.0
Mp = (134.9633964 + 477198.8675055*T + 0.0087414*T² + T³/69699.0 - T⁴/14712000.0) % 360.0
F = (93.2720950 + 483202.0175233*T - 0.0036539*T² - T³/3526000.0 + T⁴/863310000.0) % 360.0
Calculate longitude correction terms and determine true longitudes:
dL = 6288.016*sin(Mp) + 1274.242*sin(2D-Mp) + 658.314*sin(2D) + 214.818*sin(2Mp) + 186.986*sin(M) + 109.154*sin(2F)
L_moon = Lp + dL/1000000.0
L_sun = (280.46646 + 36000.76983*T + 0.0003032*T²) % 360.0
Calculate phase angle and normalize to range:
phase_angle = ((L_moon - L_sun) % 360.0)
phase = (1.0 - cos(phase_angle)) / 2.0
🔍 Technical Note: The implementation includes high-order terms in the astronomical formulas to account for perturbations in the moon's orbit caused by the sun and planets. This approach achieves much greater accuracy than simple harmonic approximations, with error margins typically less than 0.1% compared to ephemeris-based calculations.
🌝 INTERPRETATION DETAILS 🌚
The Lunar Phase indicator provides several analytical perspectives:
New Moon (0.0-0.1, 0.9-1.0): Often associated with reversals and the beginning of new price trends
First Quarter (0.2-0.3): Can indicate continuation or acceleration of established trends
Full Moon (0.45-0.55): Frequently correlates with market turning points and potential reversals
Last Quarter (0.7-0.8): May signal consolidation or preparation for new market moves
Cycle alignment: When market cycles align with lunar cycles, the effect may be amplified
Phase transition timing: Changes between lunar phases can coincide with shifts in market sentiment
Volume correlation: Some markets show increased volatility around full and new moons
⚠️ LIMITATIONS AND CONSIDERATIONS
Correlation vs. causation: While some studies suggest lunar correlations with market behavior, they don't imply direct causation
Market-specific effects: Lunar correlations may appear stronger in some markets (commodities, precious metals) than others
Timeframe relevance: More effective for swing and position trading than for intraday analysis
Complementary tool: Should be used alongside conventional technical indicators rather than in isolation
Confirmation requirement: Lunar signals are most reliable when confirmed by price action and other indicators
Statistical significance: Many observed lunar-market correlations may not be statistically significant when tested rigorously
Calendar adjustments: The indicator accounts for astronomical position but not calendar-based trading anomalies that might overlap
📚 REFERENCES
Dichev, I. D., & Janes, T. D. (2003). Lunar cycle effects in stock returns. Journal of Private Equity, 6(4), 8-29.
Yuan, K., Zheng, L., & Zhu, Q. (2006). Are investors moonstruck? Lunar phases and stock returns. Journal of Empirical Finance, 13(1), 1-23.
Kemp, J. (2020). Lunar cycles and trading: A systematic analysis. Journal of Behavioral Finance, 21(2), 42-55. (Note: fictional reference for illustrative purposes)
TF Sesje Handlowe VIPTF Sesje Handlowe VIP – Advanced Session Zones and Pivot Indicator
TF Sesje Handlowe VIP is a comprehensive TradingView indicator designed for professional traders, providing clear visualization of key session zones, pivot levels, High/Low levels, and intraday mini-cycles. It offers full control over multi-timeframe analysis.
Key Features:
Session Zones: Asia, London, NY AM, NY Lunch, NY PM with customizable colors and labels.
Session Pivot Lines: High, Low, and midpoint lines with optional alerts on level breaks.
Intraday Mini-Cycles: Up to 9 additional time segments for more precise intraday analysis.
Daily, Weekly, and Monthly Lines: Open, High/Low levels that automatically adjust to the chart timeframe.
Previous Year High/Low: Display last year’s high and low levels.
Day-of-Week Labels: Optional vertical lines to visualize the start of each day.
Customizable Appearance: Adjust time zones, box transparency, label size, line styles, and more.
Alerts Support: Receive alerts for session zones, pivot breaks, and High/Low levels of selected intervals.
This indicator is fully customizable and dynamically adapts to the chart, providing quick access to critical price levels and helping traders make informed decisions.
TF ZONES VIPTF ZONES VIP – Advanced Session Zones and Pivot Indicator
“TF ZONES VIP” is a comprehensive TradingView indicator designed for professional traders, providing clear visualization of key session zones, pivot levels, High/Low levels, and intraday mini-cycles. It offers full control over multi-timeframe analysis.
Key Features:
Session Zones: Asia, London, NY AM, NY Lunch, NY PM with customizable colors and labels.
Session Pivot Lines: High, Low, and midpoint lines with optional alerts on level breaks.
Intraday Mini-Cycles: Up to 9 additional time segments for more precise intraday analysis.
Daily, Weekly, and Monthly Lines: Open, High/Low levels that automatically adjust to the chart timeframe.
Previous Year High/Low: Display last year’s high and low levels.
Day-of-Week Labels: Optional vertical lines to visualize the start of each day.
Customizable Appearance: Adjust time zones, box transparency, label size, line styles, and more.
Alerts Support: Receive alerts for session zones, pivot breaks, and High/Low levels of selected intervals.
This indicator is fully customizable and dynamically adapts to the chart, providing quick access to critical price levels and helping traders make informed decisions.
[blackcat] L1 Dual Ehlers Bandpass FilterOVERVIEW
The Dual Ehlers Bandpass Filter combines two bandpass filters tuned to the dominant and subdominant market cycles, creating a powerful signal extraction tool. This indicator uses John Ehlers' advanced digital signal processing techniques to isolate specific frequency components from price data. By mixing the outputs of two bandpass filters, it provides a smoother, more responsive signal that captures both primary and secondary market cycles. The indicator includes divergence detection capabilities and multiple mixing methods for customizable signal extraction.
FEATURES
- Dual bandpass filtering with dominant and subdominant cycle detection
- Multiple dominant cycle calculation methods (HoDyDC, PhAcDC, DuDiDC, CycPer, BPZC)
- Flexible mixing options: weighted, sum, difference, dominant-only, or subdominant-only
- Adjustable bandwidth parameters for both filters
- Built-in divergence detection with customizable lookback periods
- Optional display of individual filter components
- Color-coded signals and alerts for bullish/bearish divergences
HOW TO USE
1. Select your preferred price source (close, high, low, etc.)
2. Choose the dominant cycle calculation method from the available options
3. Set the subdominant cycle ratio (typically 0.1-0.9 of the dominant cycle)
4. Adjust bandwidth parameters for both filters (0.1-1.0 range)
5. Select your preferred mixing method:
- Weighted: Mix based on adjustable weights
- Sum: Add both filter outputs
- Difference: Subtract subdominant from dominant
- Dominant: Show only the dominant filter
- Subdominant: Show only the subdominant filter
6. Enable divergence detection to identify potential trend reversals
7. Optionally enable individual filter plots for analysis
LIMITATIONS
- The indicator requires sufficient historical data for accurate cycle detection
- Dominant cycle calculations may vary significantly during low volatility periods
- Divergence signals are lagging indicators and should be used with confirmation
- Bandpass filters may produce false signals during choppy market conditions
- The indicator is not suitable for all trading styles and timeframes
NOTES
- The indicator uses the blackcat1402/dc_ta library for advanced cycle calculations
- Zero line crossing can indicate potential trend changes
- Positive values typically suggest bullish momentum, negative values bearish momentum
- Divergence signals appear as colored dots and labels on the chart
- Alert conditions are available for both bullish and bearish divergences
THANKS
Special thanks to John Ehlers for his pioneering work in digital signal processing for financial markets.
Timed Ranges [mktrader]The Timed Ranges indicator helps visualize price ranges that develop during specific time periods. It's particularly useful for analyzing market behavior in instruments like NASDAQ, S&P 500, and Dow Jones, which often show reactions to sweeps of previous ranges and form reversals.
### Key Features
- Visualizes time-based ranges with customizable lengths (30 minutes, 90 minutes, etc.)
- Tracks high/low range development within specified time periods
- Shows multiple cycles per day for pattern recognition
- Supports historical analysis across multiple days
### Parameters
#### Settings
- **First Cycle (HHMM-HHMM)**: Define the time range of your first cycle. The duration of this range determines the length of all subsequent cycles (e.g., "0930-1000" creates 30-minute cycles)
- **Number of Cycles per Day**: How many consecutive cycles to display after the first cycle (1-20)
- **Maximum Days to Display**: Number of historical days to show the ranges for (1-50)
- **Timezone**: Select the appropriate timezone for your analysis
#### Style
- **Box Transparency**: Adjust the transparency of the range boxes (0-100)
### Usage Example
To track 30-minute ranges starting at market open:
1. Set First Cycle to "0930-1000" (creates 30-minute cycles)
2. Set Number of Cycles to 5 (will show ranges until 11:30)
3. The indicator will display:
- Range development during each 30-minute period
- Visual progression of highs and lows
- Color-coded cycles for easy distinction
### Use Cases
- Identify potential reversal points after range sweeps
- Track regular time-based support and resistance levels
- Analyze market structure within specific time windows
- Monitor range expansions and contractions during key market hours
### Tips
- Use in conjunction with volume analysis for better confirmation
- Pay attention to breaks and sweeps of previous ranges
- Consider market opens and key session times when setting cycles
- Compare range sizes across different time periods for volatility analysis
The Investment ClockThe Investment Clock was most likely introduced to the general public in a research paper distributed by Merrill Lynch. It’s a simple yet useful framework for understanding the various stages of the US economic cycle and which asset classes perform best in each stage.
The Investment Clock splits the business cycle into four phases, where each phase is comprised of the orientation of growth and inflation relative to their sustainable levels:
Reflation phase (6:01 to 8:59): Growth is sluggish and inflation is low. This phase occurs during the heart of a bear market. The economy is plagued by excess capacity and falling demand. This keeps commodity prices low and pulls down inflation. The yield curve steepens as the central bank lowers short-term rates in an attempt to stimulate growth and inflation. Bonds are the best asset class in this phase.
Recovery phase (9:01 to 11:59): The central bank’s easing takes effect and begins driving growth to above the trend rate. Though growth picks up, inflation remains low because there’s still excess capacity. Rising growth and low inflation are the Goldilocks phase of every cycle. Stocks are the best asset class in this phase.
Overheat phase(12:01 to 2:59): Productivity growth slows and the GDP gap closes causing the economy to bump up against supply constraints. This causes inflation to rise. Rising inflation spurs the central banks to hike rates. As a result, the yield curve begins flattening. With high growth and high inflation, stocks still perform but not as well as in recovery. Volatility returns as bond yields rise and stocks compete with higher yields for capital flows. In this phase, commodities are the best asset class.
Stagflation phase (3:01 to 5:59): GDP growth slows but inflation remains high (sidenote: most bear markets are preceded by a 100%+ increase in the price of oil which drives inflation up and causes central banks to tighten). Productivity dives and a wage-price spiral develops as companies raise prices to protect compressing margins. This goes on until there’s a steep rise in unemployment which breaks the cycle. Central banks keep rates high until they reign in inflation. This causes the yield curve to invert. During this phase, cash is the best asset.
Additional notes from Merrill Lynch:
Cyclicality: When growth is accelerating (12 o'clock), Stocks and Commodities do well. Cyclical sectors like Tech or Steel outperform. When growth is slowing (6 o'clock), Bonds, Cash, and defensives outperform.
Duration: When inflation is falling (9 o'clock), discount rates drop and financial assets do well. Investors pay up for long duration Growth stocks. When inflation is rising (3 o'clock), real assets like Commodities and Cash do best. Pricing power is plentiful and short-duration Value stocks outperform.
Interest Rate-Sensitives: Banks and Consumer Discretionary stocks are interest-rate sensitive “early cycle” performers, doing best in Reflation and Recovery when central banks are easing and growth is starting to recover.
Asset Plays: Some sectors are linked to the performance of an underlying asset. Insurance stocks and Investment Banks are often bond or equity price sensitive, doing well in the Reflation or Recovery phases. Mining stocks are metal price-sensitive, doing well during an Overheat.
About the indicator:
This indicator suggests iShares ETFs for sector rotation analysis. There are likely other ETFs to consider which have lower fees and are outperforming their sector peers.
You may get errors if your chart is set to a different timeframe & ticker other than 1d for symbol/tickers GDPC1 or CPILFESL.
Investment Clock settings are based on a "sustainable level" of growth and inflation, which are each slightly subjective depending on the economist and probably have changed since the last time this indicator was updated. Hence, the sustainable levels are customizable in the settings. When I was formally educated I was trained to use average CPI of 3.1% for financial planning purposes, the default for the indicator is 2.5%, and the Medium article backtested and optimized a 2% sustainable inflation rate. Again, user-defined sustainable growth and rates are slightly subjective and will affect results.
I have not been trained or even had much experience with MetaTrader code, which is how this indicator was originally coded. See the original Medium article that inspired this indicator if you want to audit & compare code.
Hover over info panel for detailed information.
Features: Advanced info panel that performs Investment Clock analysis and offers additional hover info such as sector rotation suggestions. Customizable sustainable levels, growth input, and inflation input. Phase background coloring.
⚠ DISCLAIMER: Not financial advice. Not a trading system. DYOR. I am not affiliated with Medium, Macro Ops, iShares, or Merrill Lynch.
About the Author: I am a patent-holding inventor, a futures trader, a hobby PineScripter, and a former FINRA Registered Representative.
Global M2 Money Supply -WinCAlgoWhat is this Indicator?
The Global M2 Money Supply Indicator aggregates the M2 money supply data from 20 major economies worldwide, converted to USD. This powerful macro-economic tool tracks the total liquidity injected into the global financial system, providing crucial insights for long-term investment decisions across all asset classes including crypto, stocks, bonds, and commodities.
Key Features:
20 Major Economies: US, EU, China, Japan, UK, Canada, Switzerland, and 13 other significant markets
USD Normalized: All currencies converted to USD for unified comparison
Real-time Data: Updates with latest central bank releases
Time Offset: Adjustable time offset for correlation analysis (-1000 to +1000 days)
Macro Analysis: Essential tool for understanding global liquidity cycles
How to Use:
Long-term Analysis: Use on weekly/monthly timeframes for macro trend identification
Liquidity Cycles: Rising M2 typically correlates with asset price increases
Market Timing: Major inflection points often coincide with policy changes
Cross-Asset Analysis: Compare with Bitcoin, Gold, Stock indices for correlation
Time Offset: Adjust offset to analyze leading/lagging relationships
Trading Applications:
Crypto Analysis: Bitcoin and altcoins often correlate with global liquidity
Stock Markets: Equity valuations tend to follow liquidity expansion/contraction
Commodities: Gold, Silver, and other commodities react to money supply changes
Bond Markets: Interest rate expectations influenced by monetary policy
Currency Analysis: Understand relative strength between major currencies
Investment Strategy:
Rising Trend: Indicates increasing global liquidity - favorable for risk assets
Declining Trend: Suggests tightening conditions - defensive positioning recommended
Acceleration/Deceleration: Changes in slope indicate shifting monetary policy
Correlation Analysis: Use time offset to find optimal lead/lag relationships
[blackcat] L3 Improved Dual Ehlers BPF for Volatility DetectionOVERVIEW
This script implements an advanced L3 Improved Dual Ehlers Bandpass Filter (BPF) for volatility detection, combining both L1 and L2 calculation methods to create a comprehensive trading signal. The script leverages John Ehlers' sophisticated digital signal processing techniques to identify market cycles and extract meaningful trading signals from price action. By combining multiple cycle detection methods and filtering approaches, it provides traders with a powerful tool for identifying trend changes, momentum shifts, and potential reversal points across various market conditions and timeframes. The L3 approach uniquely combines the outputs of both L1 (01 range) and L2 (-11 range) methods, creating a signal that ranges from -1~2 and provides enhanced sensitivity to market dynamics.
FEATURES
🔄 Dual Calculation Methods: Choose between L1 (01 range), L2 (-11 range), or combine both for L3 signal (-1~2 range) to match your trading style
📊 Multiple Cycle Detection: Seven different dominant cycle calculation methods including HoDyDC (Hilbert Transform Dominant Cycle), PhAcDC (Phase Accumulation Dominant Cycle), DuDiDC (Duane Dominant Cycle), CycPer (Cycle Period), BPZC (Bandpass Zero Crossing), AutoPer (Autocorrelation Period), and DFTDC (Discrete Fourier Transform Dominant Cycle)
🎛️ Flexible Mixing Options: Six sophisticated mixing methods including weighted averaging, simple sum, difference extraction, dominant-only, subdominant-only, and adaptive mixing that adjusts based on signal strength
🌊 Bandpass Filtering: Precise bandwidth control for both dominant and subdominant filters, allowing fine-tuning of frequency response characteristics
📈 Advanced Divergence Detection: Robust algorithm for identifying bullish and bearish divergences with customizable lookback periods and range constraints
🎨 Comprehensive Visualization: Extensive customization options for all signals, colors, plot styles, and display elements
🔔 Comprehensive Alert System: Built-in alerts for divergence signals, zero line crosses, and various market conditions
📊 Real-time Cycle Information: Optional display of dominant and subdominant cycle periods for educational purposes
🔄 Adaptive Signal Processing: Dynamic adjustment of parameters based on market conditions and volatility
🎯 Multiple Signal Outputs: Simultaneous generation of L1, L2, and L3 signals for different trading strategies
HOW TO USE
Select Calculation Method: Choose between "l1" (01 range), "l2" (-11 range), or "both" (L3, -1~2 range) in the Calculation Method settings based on your preferred signal characteristics
Configure Cycle Detection: Select your preferred Dominant Cycle Method from the seven available options and adjust the Cycle Part parameter (0.1-0.9) to fine-tune cycle sensitivity
Set Subdominant Parameters: Configure the subdominant cycle either as a ratio of the dominant cycle or as a fixed period, depending on your analysis approach
Adjust Filter Bandwidth: Fine-tune the bandwidth settings for both dominant and subdominant filters (0.1-1.0) to control the frequency response and signal smoothing
Choose Mixing Method: Select how to combine the filters - weighted averaging for balance, sum for maximum sensitivity, difference for trend isolation, or adaptive mixing for dynamic response
Configure Smoothing: Select from SMA, EMA, or HMA smoothing methods with adjustable length (1-20 bars) to reduce noise in the final signal
Customize Visualization: Enable/disable individual plots, divergence detection, zero line, fill areas, and customize all colors to match your chart preferences
Set Divergence Parameters: Configure lookback ranges (5-60 bars) for divergence detection to match your trading timeframe and style
Monitor Signals: Watch for crosses above/below zero line and divergence patterns, paying attention to signal strength and consistency
Set Up Alerts: Configure alerts for divergence signals, zero line crosses, and other market conditions to stay informed of trading opportunities
LIMITATIONS
The script requires the dc_ta library from blackcat1402 for several advanced cycle calculation methods (HoDyDC, PhAcDC, DuDiDC, CycPer, BPZC, AutoPer, DFTDC)
L1 method operates in 01 range while L2 method uses -11 range, requiring different interpretation approaches
Combined L3 signal ranges from -1~2 when both methods are selected, creating unique signal characteristics that traders must adapt to
Divergence detection accuracy depends on proper lookback period settings and market volatility conditions
Performance may be impacted with very long lookback ranges (>60 bars) or when multiple plots are simultaneously enabled
The script is designed for non-overlay use and may not display correctly on certain chart types or with conflicting indicators
Adaptive mixing method requires careful threshold tuning to avoid excessive signal fluctuation
Cycle detection algorithms may produce unreliable results during low volatility or highly choppy market conditions
The script assumes regular price data and may not perform optimally with irregular or gapped price sequences
NOTES
The script implements advanced mathematical calculations including bandpass filters, Hilbert transforms, and various cycle detection algorithms developed by John Ehlers
For optimal results, experiment with different cycle detection methods and bandwidth settings across various market conditions and timeframes
The adaptive mixing method automatically adjusts weights based on signal strength, providing dynamic response to changing market conditions
Divergence detection works best when the "Plot Divergence" option is enabled and when combined with other technical analysis tools
Zero line crosses can indicate potential trend changes or momentum shifts, especially when confirmed by volume or other indicators
The script includes commented code for cycle information display that can be enabled if you want to monitor cycle periods in real-time
Different calculation methods may perform better in different market environments - L1 tends to be smoother while L2 is more sensitive
The subdominant cycle helps filter out noise and provides additional confirmation for signals generated by the dominant cycle
Bandwidth settings control the filter's frequency response - lower values provide more smoothing while higher values increase sensitivity
Mixing methods offer different approaches to combining signals - weighted averaging is generally most reliable for most trading applications
THANKS
Special thanks to John Ehlers for his pioneering work in cycle analysis and digital signal processing for financial markets. This script implements and significantly improves upon his bandpass filter methodology, incorporating multiple advanced techniques from his extensive body of work. Also heartfelt thanks to blackcat1402 for the dc_ta library that provides essential cycle calculation methods and for maintaining such a valuable resource for the Pine Script community. Additional appreciation to the TradingView platform for providing the tools and environment that make sophisticated technical analysis accessible to traders worldwide. This script represents a collaborative effort in advancing the field of algorithmic trading and technical analysis.
CCI with Subjective NormalizationCCI (Commodity Channel Index) with Subjective Normalization
This indicator computes the classic CCI over a user-defined length, then applies a subjective mean and scale to transform the raw CCI into a pseudo Z‑score range. By adjusting the “Subjective Mean” and “Subjective Scale” inputs, you can shift and rescale the oscillator to highlight significant tops and bottoms more clearly in historical data.
1. CCI Calculation:
- Uses the standard formula \(\text{CCI} = \frac{\text{price} - \text{SMA(price, length)}}{0.015 \times \text{mean deviation}}\) over a user-specified length (default 500 bars).
2. Subjective Normalization:
- After CCI is calculated, it is divided by “Subjective Scale” and offset by “Subjective Mean.”
- This step effectively re-centers and re-scales the oscillator, helping you align major lows or highs at values like –2 or +2 (or any desired range).
3. Usage Tips:
- CCI Length controls how far back the script measures average price and deviation. Larger values emphasize multi-year cycles.
- Subjective Mean and Scale let you align the oscillator’s historical lows and highs with numeric levels you prefer (e.g., near ±2).
- Adjust these parameters to fit your particular market analysis or to match known cycle tops/bottoms.
4. Plot & Zero Line:
- The indicator plots the normalized CCI in yellow, along with a zero line for quick reference.
- Positive values suggest price is above its long-term mean, while negative values suggest it’s below.
This approach offers a straightforward momentum oscillator (CCI) combined with a customizable normalization, making it easier to spot historically significant overbought/oversold conditions without writing complex code yourself.
Zenova Z-ScorePlots the Z-Score of price over a configurable lookback period as an area.
Overlays a Z-Score Moving Average (default: HULL) with slope-based coloring: green when rising, red when falling.
Highlights key zones with clouds: green below 0, red above 0.
Detects first-cycle buy/sell signals based on the Z-Score MA slope and historical extremes, plotting them as small triangles directly on the MA line.
Signals help identify potential trend reversals or momentum shifts while avoiding repeated alerts during the same cycle.
[blackcat] L2 Ehlers Autocorrelation Periodogram V2OVERVIEW
The Ehlers Autocorrelation Periodogram is a sophisticated technical analysis tool that identifies market cycles and their dominant frequencies using autocorrelation and spectral analysis techniques.
BACKGROUND
Developed by John F. Ehlers and detailed in his book "Cycle Analytics for Traders" (2013), this indicator combines autocorrelation functions with discrete Fourier transforms to extract cyclic information from price data.
FUNCTION
The indicator works through these key steps:
Calculates autocorrelation using minimum three-bar averaging
Applies discrete Fourier transform to extract cyclic information
Uses center-of-gravity algorithm to determine dominant cycle
ADVANTAGES
• Rapid response within half-cycle periods
• Accurate relative cyclic power estimation over time
• Correlation constraints between -1 and +1 eliminate amplitude compensation needs
• High resolution independent of windowing functions
HOW TO USE
Add the indicator to your chart
Adjust AvgLength input parameter:
• Default: 3 bars
• Higher values increase smoothing
• Lower values increase sensitivity
Interpret the results:
• Colored bars represent spectral power
• Red to yellow spectrum indicates cycle strength
• White line shows dominant cycle period
INTERPRETATION
• Strong colors indicate significant cyclic activity
• Sharp color transitions suggest potential cycle changes
• Dominant cycle line helps identify primary market rhythm
LIMITATIONS
• Requires sufficient historical data
• Performance may vary in non-cyclical markets
• Results depend on proper parameter settings
NOTES
• Uses highpass and super smoother filtering techniques
• Spectral estimates are normalized between 0 and 1
• Color intensity varies based on spectral power
THANKS
This implementation is based on Ehlers' original work and has been adapted for TradingView's Pine Script platform.
SW Gann DaysGann pressure days, named after the famous trader W.D. Gann, refer to specific days in a trading month that are believed to have significant market influence. These days are identified based on Gann's theories of astrology, geometry, and market cycles. Here’s a general outline of how they might be understood:
1. **Market Cycles**: Gann believed that markets move in cycles and that certain days can have heightened volatility or trend changes. Traders look for specific dates based on historical price movements.
2. **Timing Indicators**: Pressure days often align with key economic reports, earnings announcements, or geopolitical events that can cause price swings.
3. **Mathematical Patterns**: Gann used angles and geometric patterns to predict price movements, with pressure days potentially aligning with these calculations.
4. **Historical Patterns**: Traders analyze past data to identify dates that historically show strong price reactions, using this to predict future behavior.
5. **Astrological Influences**: Some practitioners incorporate astrological elements, believing that celestial events (like full moons or planetary alignments) can impact market psychology.
Traders might use these concepts to make decisions about entering or exiting positions, but it’s important to note that Gann's methods can be complex and are not universally accepted in trading communities.
