Trend Condition [TradersPro]
OVERVIEW
The Trend Condition Indicator measures the strength of the bullish or bearish trend by using a ribbon pattern of exponential moving averages and scoring system. Trend cycles naturally expand and contract as a normal part of the cycle. It is the rhythm of the market. Perpetual expansion and contraction of trend.
As trend cycles develop the indicator shows a compression of the averages. These compression zones are key locations as trends typically expand from there. The expansion of trend can be up or down.
As the trend advances the ribbon effect of the indicator can be seen as each average expands with the price action. Once they have “fanned” the probability of the current trend slowing is high.
This can be used to recognize a powerful trend may be concluding. Traders can tighten stops, exit positions or utilize other prudent strategies.
CONCEPTS
Each line will display green if it is higher than the prior period and red if it is lower than the prior period. If the average is green it is considered bullish and will score one point in the bullish display. Red lines are considered bearish and will score one point in the bearish display.
The indicator can then be used at a quick glance to see the number of averages that are bullish and the number that are bearish.
A trader may use these on any tradable instrument. They can be helpful in stock portfolio management when used with an index like the S&P 500 to determine the strength of the current market trend. This may affect trade decisions like possession size, stop location and other risk factors.
Cerca negli script per "Cycle"
Triad QT - BetaQT Profiler is the ultimate tool for Quarterly Theory traders. It's great both for trading and backtesting purposes.
The indicator includes the following features:
- accurate plotting of quarters for cycles from micro to quadrennial, consistent across different markets
- plotting previous quarter high and previous quarter low with possibility of projecting it into next quarters
- plotting DFR for each cycle in convenient, clear way
- plotting True Opens with possibility of looking up higher cycle quarters on lower timeframe charts (you can look up even TYO on micro cycle!) in consistent manner
- plotting SSMTs both for present, as well as historical charts in vey fast fashion - priceless for backtesting and trading purposes
- 3 SSMT detection ways : wick above previous quarter high, close above previous quarter's high, close above previous quarter's highest close (vice versa for lows)
- possibility of choosing the triad you're using from drop down list, as well as setting up your custom triad
- fast performance due to unique coding solutions
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Brought to you by Triad Trading Community
EmKa
Phase-Accumulation Adaptive EMA w/ Expanded Source Types [Loxx]Phase-Accumulation Adaptive EMA w/ Expanded Source Types is a Phase Accumulation Adaptive Exponential Moving Average with Loxx's Expanded Source Types. This indicator is meant to better capture trend movements using dominant cycle inputs. Alerts are included.
What is Phase Accumulation?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
Included:
-Toggle on/off bar coloring
-Alerts
Take Profit ScreenerI'm going to introduce you to the Take Profit Screener tool.
It allows you to manually scan your watchlist to determine at a glance the assets that have the best profitability potential.
It is a 2 in 1 tool that allows you to :
identify where your Take Profit ratios are located whether you are in SHAD or Cycle Strategy
identify the potential reward percentages when approaching the key Fibonacci levels
Before you start using it, you need to:
sort your watchlist according to the price (Last) in order to have price ranges more or less close to each other when jumping from a symbol to another
disable the Auto Scale and Magnet feature
select your first symbol
display the tool (the indicator more exactly)
The settings dialog box is organised in 3 sections:
Strategy : By setting this section, you will answer the question " Where do my Take Profit ratios stand in relation to my entry price, and according to Risk Management Strategy adopted (SHAD or Cycle)? "
Fibonacci : By setting this section, you will answer the question " What percentage gain can I expect as I approach one of the key Fibonacci levels? "
Layout : This is the settings for the look and feel
Strategy Section
Active : This part of the indicator won't display on your chart if unchecked
Type : Choose between SHAD or Cycle Strategy. When choosing SHAD, you can select 2, 4, 8 or 16 SHAD Levels. When choosing Cycle, you can enter whatever ratio value you wish in the Strategy Ratio (Cycle only) input.
SHAD xNN : When choosing SHAD Strategy, you should select at least one level and more if need be.
Strategy Ratio (Cycle only) : When choosing Strategy Type Cycle, you can enter whatever ratio value you wish there.
Freeze Entry Price & Value : Leave it unchecked whenever the current price of the asset is located within your desired area (i.e. Reload Zone) while attempting to estimate its potential reward. Conversely, keep it checked whenever the current price of the asset is outside your desired area, but you need to anticipate the potential reward of this asset if its price reaches a certain level, your Entry price. Enter this price there and check the box.
Show price : If checked, both Take Profit ratio and Price are displayed. If unchecked, then price is hidden.
Extend Line : If checked, then lines showing Take Profit levels extend to the left.
Label Offset : If checked, then the label that displays Take Profit ratio and price shift to the right by a value that ranges from 0 to 100 candles.
Label Style : You can choose between Right or Top. This will determine the orientation of the label.
Fibonacci Section
Active : This part of the indicator won't display on your chart if unchecked
Type : Choose between SHAD or Cycle Strategy. When choosing SHAD, you can select 2, 4, 8 or 16 SHAD Levels. When choosing Cycle, you can enter whatever ratio value you wish in the Strategy Ratio (Cycle only) input.
SHAD xNN : When choosing SHAD Strategy, you should select at least one level and more if need be.
Strategy Ratio (Cycle only) : When choosing Strategy Type Cycle, you can enter whatever ratio value you wish there.
Freeze Entry Price : Leave it unchecked whenever the current price of the asset is located within your desired area (i.e. Reload Zone) while attempting to estimate its potential reward. Conversely, keep it checked whenever the current price of the asset is outside your desired area, but you need to anticipate the potential reward of this asset if its price reaches a certain level, your Entry price. Enter this price there and check the box.
Color : You can define the color of Fibonacci line levels
even_better_sinewave_mod
Description:
Even better sinewave was an indicator developed by John F. Ehlers (see Cycle Analytics for Trader, pg. 159), in which improvement to cycle measurements completely relies on strong normalization of the waveform. The indicator aims to create an artificially predictive indicator by transferring the cyclic data swings into a sine wave. In this indicator, the modified is on the weighted moving average as a smoothing function, instead of using the super smoother, aim to be more adaptive, and the default length is set to 55 bars.
Sinewave
smoothing = (7*hp + 6*hp_1 + 5*hp_2+ 4*hp_3 + 3*hp_4 + 2*hp5 + hp_6) /28
normalize = wave/sqrt(power)
Notes:
sinewave indicator crossing over -0.9 is considered to beginning of the cycle while crossing under 0.9 is considered as an end of the cycle
line color turns to green considered as a confirmation of an uptrend, while turns red as a confirmation of a downtrend
confidence of using indicator will be much in confirmation paired with another indicator such dynamic trendline e.g. moving average
as cited within Ehlers book Cycle Analytic for Traders, the indicator will be useful if the satisfied market cycle mode and the period of the dominant cycle must be estimated with reasonable accuracy
Other Example
Transfer Function Filter [theUltimator5]The Transfer Function Filter is an engineering style approach to transform the price action on a chart into a frequency, then filter out unwanted signals using Butterworth-style filter approach.
This indicator allows you to analyze market structure by isolating or removing different frequency components of price movement—similar to how engineers filter signals in control systems and electrical circuits.
🔎 Features
Four Filter Types
1) Low Pass Filter – Smooths price data, highlighting long-term trends while filtering out short-term noise. This filter acts similar to an EMA, removing noisy signals, resulting in a smooth curve that follows the price of the stock relative to the filter cutoff settings.
Real world application for low pass filter - Used in power supplies to provide a clean, stable power level.
2) High Pass Filter – Removes slow-moving trends to emphasize short-term volatility and rapid fluctuations. The high pass filter removes the "DC" level of the chart, removing the average price moves and only outputting volatility.
Real world application for high pass filter - Used in audio equalizers to remove low-frequency noise (like rumble) while allowing higher frequencies to pass through, improving sound clarity.
3) Band Pass Filter – Allows signals to plot only within a band of bar ranges. This filter removes the low pass "DC" level and the high pass "high frequency noise spikes" and shows a signal that is effectively a smoothed volatility curve. This acts like a moving average for volatility.
Real world application for band pass filter - Radio stations only allow certain frequency bands so you can change your radio channel by switching which frequency band your filter is set to.
4) Band Stop Filter – Suppresses specific frequency bands (cycles between two cutoffs). This filter allows through the base price moving average, but keeps the high frequency volatility spikes. It allows you to filter out specific time interval price action.
Real world application for band stop filter - If there is prominent frequency signal in the area which can cause unnecessary noise in your system, a band stop filter can cancel out just that frequency so you get everything else
Configurable Parameters
• Cutoff Periods – Define the cycle lengths (in bars) to filter. This is a bit counter-intuitive with the numbering since the higher the bar count on the low-pass filter, the lower the frequency cutoff is. The opposite holds true for the high pass filter.
• Filter Order – Adjust steepness and responsiveness (higher order = sharper filtering, but with more delay).
• Overlay Option – Display Low Pass & Band Stop outputs directly on the price chart, or in a separate pane. This is enabled by default, plotting the filters that mimic moving averages directly onto the chart.
• Source Selection – Apply filters to close, open, high, low, or custom sources.
Histograms for Comparison
• BS–LP Histogram – Shows distance between Band Stop and Low Pass filters.
• BP–HP Histogram – Highlights differences between Band Pass and High Pass filters.
Histograms give the visualization of a pseudo-MACD style indicator
Visual & Informational Aids
• Customizable colors for each filter line.
• Optional zero-line for histogram reference.
• On-chart info table summarizing active filters, cutoff settings, histograms, and filter order.
📊 Use Cases
Trend Detection – Use the Low Pass filter to smooth noise and follow underlying market direction.
Volatility & Cycle Analysis – Apply High Pass or Band Pass to capture shorter-term patterns.
Noise Suppression – Deploy Band Stop to remove specific choppy frequencies.
Momentum Insight – Watch the histograms to spot divergences and relative filter strength.
BigNuts MacroScript that overlays key events that are coming up as the US economy shifts into fiscal dominance and global liquidity may peak. The specified dates were cross referenced from many cycle theories including Benner and Kondratieff key cycle dates as well work of Michel Howell for Global liquidity cycles and Luke Gromen analysis for Marco. The script also then cross references all these dates with any key celestial events that have had previous historical significance for market timing. The celestial events are key dates to watch but can be toggled on and off.
Fourier Oscillator Suite [SeerQuant]| Fourier Oscillator Suite |
WHY THE FOURIER TRANSFORM?
The Discrete Fourier Transform (DFT) extracts dominant cyclical patterns from market price data. Fourier analysis allows for the decomposition of price movements into frequency components, distinguishing trend-driven behaviour from noise and identifying oscillatory cycles within the market. This approach is effective in detecting dominant cycles in data, filtering out random fluctuations, and providing insights into price behaviour beyond conventional indicators.
This indicator applies a Fourier transform to the selected price source, converting it into a frequency-based signal. Instead of directly working with raw price data, the transformed signal acts as a smoothed and cycle-adjusted input for multiple technical indicators, enhancing their ability to adapt to market conditions dynamically.
Once the Fourier transform is applied, the extracted signal is processed through a suite of technical indicators, which are then normalized and aggregated into a single, actionable metric.
FEATURES AND BENEFITS
✅ Multi-Factor Aggregation:
By blending volatility, momentum, and volume-based oscillators, this indicator provides a comprehensive view of market conditions.
✅ Enhanced Signal Clarity:
Fourier transformation filters noise, revealing more reliable trading signals.
✅ Adaptive Market Sensitivity:
Unlike static oscillators, the Fourier-enhanced input dynamically adjusts to price shifts.
INDICATOR COMPONENTS
The Fourier Oscillator Suite aggregates the output of the transformed signal into three primary market components:
1. Volatility-Based Metrics
Commodity Channel Index (CCI) – Measures price deviation from a moving average.
Bollinger Band %B (BB%) – Evaluates price positioning within the Bollinger Bands.
Relative Volatility Index (RVI) – Identifies periods of heightened or subdued volatility.
2. Momentum Indicators
Relative Strength Index (RSI) – Gauges trend momentum and overbought/oversold levels.
Coppock Curve – A long-term momentum oscillator, often used for detecting major trend shifts.
Momentum (MOM), TRIX, and Stochastic Momentum Index (SMI) – Further refine momentum analysis.
3. Volume-Based Oscillators
Money Flow Index (MFI) – Measures price strength relative to volume.
Volume Zone Oscillator (VZO) – Detects accumulation and distribution phases.
Elder's Force Index (EFI) & Klinger Volume Oscillator (KVO) – Assess money flow strength.
These individual metrics are first normalized within a defined period and then smoothed using the selected moving average type. The final composite signal is derived from a weighted combination of the volatility, momentum, and volume components, each of which can be customized by the user.
SETTINGS
The indicator includes an extensive set of options for users to tailor its performance:
📌 Fourier Transform Parameters
Source Selection – Choose which price input (e.g., HLC3) is used for Fourier analysis.
Fourier Period – Defines the number of cycles analyzed for signal extraction.
📌 Aggregation Settings
Normalization Period – Controls how indicator values are scaled.
Smoothing Length – Adjusts the sensitivity of moving averages applied to oscillators.
Weight Adjustments – Fine-tune the impact of volatility, momentum, and volume-based inputs on the final signal.
📌 White Noise Control
White Noise Amplitude & Period – Filters out excessive market noise to improve signal clarity.
Enable/Disable White Noise Overlay – Provides optional visualization of filtered noise levels.
📌 Custom Styling & Visual Enhancements
Selectable Color Schemes – Choose from Default, Modern, Cool, or Monochrome.
Bull & Bear Color Customization – Define custom colors for positive/negative momentum shifts.
Adaptive Gradient Fills – Highlights market conditions dynamically based on oscillator movements.
The Fourier Oscillator Suite is designed for advanced traders seeking a noise-reduced, multi-dimensional view of market dynamics. By incorporating Fourier-transformed signals into a broad range of oscillators, this tool offers a highly adaptive, filter-enhanced, and customizable approach to momentum and trend analysis. Whether you are a trend follower, mean reversion trader, or volume analyst, this suite provides actionable insights with enhanced clarity.
Detrended Price Oscillator [NexusSignals]Detrended Price Oscillator (DPO) is a detrended price oscillator, used in technical analysis, strips out price trends in an effort to estimate the length of price cycles from peak to peak or trough to trough.
DPO is not a momentum indicator, instead highlights peaks and troughs in price, which are used to estimate buy and sell points in line with the historical cycle. (cf. to investopedia)
DPO indicator made by NexusSignals components :
a filled area that allow users to see easy the trend of an asset;
a sma moving average on chart (default length is 20)
a 20 sma on oscillator, both ma's are color coded to show uptrend / downtrend
a donchian channel applied to the dpo to show breakouts, breakdowns and resistances/support, reversals
few alerts for price crossing above ma, cross above the 0 dpo line, and for cross above and below the donchian channels top and bottom
How you can use DPO indicator ?
The detrended price oscillator (DPO) can be used for measuring the distance between peaks and troughs in the indicator that may help traders to make future decisions as they can locate the most recent trough and determine when the next one may occur in the meassured distance on oscillator between peaks and troughs.
You can use the indicator to find the potential price reversals, for example when the price of an asset is in a bearish trend and the dpo is bouncing from the donchian channel bottom, that may be a potential swing low for that asset, same thing in a bullish trend when the dpo rejecting at top of donchian channel may be a trend reversal, a pullback or swing high.
When DPO is above the 0 trend is in an uptrend and when dpo is below the zero the asset is possible to move into a downtrend.
Also crosses of DPO above and below the DPO moving average may signalising a trend change.
Next Moon Phases 2025Next Moon Phases 2025
This custom indicator marks both past and future moon phases with vertical lines on your chart, providing a unique way to incorporate lunar cycles into your trading strategy.
This indicator is best used on the Daily timeframe. The lunar cycle is most effective when viewed in daily bars, providing the clearest correlation between moon phases and market trends.
Key Features:
Past Moon Phases (2016–2024): Marks the key lunar phases—New Moon, First Quarter, Full Moon, and Last Quarter—with vertical lines on the chart. Perfect for backtesting and analyzing the historical relationship between moon phases and market movements.
Future Moon Phases (2025): Unlike most indicators, this tool also projects upcoming moon phases for 2025, allowing you to plan ahead and anticipate potential market reactions based on future lunar events.
Adjustable Visibility: Customize which moon phases are displayed by toggling the visibility of each phase (New Moon, First Quarter, Full Moon, Last Quarter) with a simple control.
Why Moon Phases Matter in Trading:
Many traders believe that the lunar cycle can influence market sentiment and behavior. For example:
New Moon is often associated with new beginnings and potential market reversals.
Full Moon is thought to bring increased volatility and market climaxes.
First Quarter and Last Quarter may indicate periods of consolidation or momentum shifts.
By including both past and future moon phases, this indicator allows you to examine historical data while also planning for upcoming lunar events, giving you a strategic edge for both short-term and long-term trading decisions.
E9 PLRRThe E9 PLRR (Power Law Residual Ratio) is a custom-built indicator designed to evaluate the overvaluation or undervaluation of an asset, specifically by utilizing logarithmic price data and a power law-based model. It leverages a dynamic regression technique to assess the deviation of the current price from its expected value, giving insights into how much the price deviates from its long-term trend.
This indicator is primarily used to detect market extremes and cycles, often used in the analysis of long-term price movements in assets like Bitcoin, where cyclical behavior and significant price deviations are common.
This chart is back from 2019 and shows (From left to right) 2018 Bear market bottom at $3.5k (Dark Blue) , following a peak at 12k (dark red) before the Covid crash back down to EUROTLX:4K (Dark blue)
Key Components
Logarithmic Price Data:
The indicator works with logarithmic price data (ohlc4), which represents the average of open, high, low, and close prices. The logarithmic transformation is crucial in financial modeling, especially when analyzing long-term price data, as it normalizes exponential price growth patterns.
Dynamic Exponent 𝑘:
The model calculates a dynamic exponent k using regression, which defines the power law relationship between time and price. This exponent is essential in determining the expected power law price return and how far the current price deviates from that expected trend.
Power Law Price Return:
The power law price return is computed using the dynamic exponent
k over a defined period, such as 365 days (1 year). It represents the theoretical price return based on a power law relationship, which is used to compare against the actual logarithmic price data.
Risk-Free Rate:
The indicator incorporates an adjustable risk-free rate, allowing users to model the opportunity cost of holding an asset compared to risk-free alternatives. By default, the risk-free rate is set to 0%, but this can be modified depending on the user's requirements.
Volatility Adjustment:
A key feature of the PLRR is its ability to adjust for price volatility. The indicator smooths out short-term price fluctuations using a moving average, helping to detect longer-term cycles and trends.
PLRR Calculation:
The core of the indicator is the calculation of the Power Law Residual Ratio (PLRR). This is derived by subtracting the expected power law price return and risk-free rate from the logarithmic price return, then multiplying the result by a user-defined multiplier.
Color Gradient:
The PLRR values are represented visually using a color gradient. This gradient helps the user quickly identify whether the asset is in an undervalued, fair value, or overvalued state:
Dark Blue to Light Blue: Indicates undervaluation, with increasing blue tones representing a higher degree of undervaluation.
Green to Yellow: Represents fair value, where the price is aligned with the expected power law return.
Orange to Dark Red: Indicates overvaluation, with increasing red tones representing a higher degree of overvaluation.
Zero Line:
A zero line is plotted on the indicator chart, serving as a reference point. Values above the zero line suggest potential overvaluation, while values below indicate potential undervaluation.
Dots Visualization:
The PLRR is plotted using dots, with each dot color-coded based on the PLRR value. This dot-based visualization makes it easier to spot significant changes or reversals in market sentiment without overwhelming the user with continuous lines.
Bar Coloring:
The chart’s bars are colored in accordance with the PLRR value at each point in time, making it visually clear when an asset is potentially overvalued or undervalued.
Indicator Functionality
Cycle Identification : The E9 PLRR is especially useful for identifying cyclical market behavior. In assets like Bitcoin, which are known for their boom-bust cycles, the PLRR can help pinpoint when the market is likely entering a peak (overvaluation) or a trough (undervaluation).
Overvaluation and Undervaluation Detection: By comparing the current price to its expected power law return, the PLRR helps traders assess whether an asset is trading above or below its fair value. This is critical for long-term investors seeking to enter the market at undervalued levels and exit during periods of overvaluation.
Trend Following: The indicator helps users identify the broader trend by smoothing out short-term volatility. This makes it useful for both momentum traders looking to ride trends and contrarian traders seeking to capitalize on market extremes.
Customization
The E9 PLRR allows users to fine-tune several parameters based on their preferences or specific market conditions:
Lookback Period:
The user can adjust the lookback period (default: 100) to modify how the moving average and regression are calculated.
Risk-Free Rate:
Adjusting the risk-free rate allows for more realistic modeling of the opportunity cost of holding the asset.
Multiplier:
The multiplier (default: 5.688) amplifies the sensitivity of the PLRR, allowing users to adjust how aggressively the indicator responds to price movements.
This indicator was inspired by the works of Ashwin & PlanG and their work around powerLaw. Thank you. I hall be working on the calculation of this indicator moving forward to make improvements and optomisations.
Ehlers Stochastic Center Of Gravity [CC]The Stochastic Center Of Gravity Indicator was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pgs 79-80), and this is one of the many cycle scripts that I have created but not published yet because, to be honest, I don't use cycle indicators in my everyday trading. Many of you probably do, so I will start publishing my big backlog of cycle-based indicators. These indicators work best with a trend confirmation or some other confirmation indicator to pair with it. The current cycle is the length of the trend, and since most stocks generally change their underlying trend quite often, especially during the day, it makes sense to adjust the length of this indicator to match the stock you are using it on. As you can see, the indicator gives constant buy and sell signals during a trend which is why I recommend using a confirmation indicator.
I have color-coded it to use lighter colors for normal signals and darker colors for strong signals. Buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts you would like to see me publish!
Fractal Wave MarkerFractal Wave Marker is an indicator that processes relative extremes of fluctuating prices within 2 periodical aspects. The special labeling system detects and visually marks multi-scale turning points, letting you visualize fractal echoes within unfolding cycles dynamically.
What This Indicator Does
Identifies major and minor swing highs/lows based on adjustable period.
Uses Phi in power exponent to compute a higher-degree swing filter.
Labels of higher degree appear only after confirmed base swings — no phantom levels, no hindsight bias. What you see is what the market has validated.
Swing points unfold in a structured, alternating rhythm . No two consecutive pivots share the same hierarchical degree!
Inspired by the Fractal Market Hypothesis, this script visualizes the principle that market behavior repeats across time scales, revealing structured narrative of "random walk". This inherent sequencing ensures fractal consistency across timeframes. "Fractal echoes" demonstrate how smaller price swings can proportionally mirror larger ones in both structure and timing, allowing traders to anticipate movements by recursive patterns. Cycle Transitions highlight critical inflection points where minor pivots flip polarity such as a series of lower highs progress into higher highs—signaling the birth of a new macro trend. A dense dense clusters of swing points can indicate Liquidity Zones, acting as footprints of institutional accumulation or distribution where price action validates supply and demand imbalances.
Visualization of nested cycles within macro trend anchors - a main feature specifically designed for the chartists who prioritize working with complex wave oscillations their analysis.
111D SMA / (350D SMA * 2)Indicator: Pi Cycle Ratio
This custom technical indicator calculates a ratio between two moving averages that are used for the PI Cycle Top indicator. The PI Cycle Top indicator triggers when the 111-day simple moving average (111D SMA) crosses up with the 350-day simple moving average (350D SMA *2).
The line value is ratio is calculated as:
Line Value = 111DSMA / (350D SMA × 2)
When the 111D SMA crosses with the 350D SMA triggering the PI Cycle Top, the value of the ratio between the two lines is 1.
This visualizes the ratio between the two moving averages into a single line. This indicator can be used for technical analysis for historical and future moves.
The Investment Clock Orbital GraphThe Investment Clock Orbital Graph is an advanced visualization tool designed to help traders and investors track economic cycles using a dynamic scatter plot of GDP growth vs. CPI inflation rates.
This indicator is a fusion of two powerful TradingView indicators:
LuxAlgo ’s Relative Strength Scatter Plot – A robust scatter plot for tracking relative strength.
The Investment Clock Indicator – A cycle-based approach to market rotation. This indicator contains more information regarding The Investment Clock.
By combining these approaches, the Investment Clock Orbital Graph enables traders to visualize economic momentum and inflationary trends in a unique, orbital-style scatter plot.
Key Features & Improvements
Orbital Graph Representation – Displays GDP growth and CPI inflation as a dynamic, evolving scatter plot, showing how the economy moves through different phases.
Quadrant-Based Market Regimes – Identifies four key economic phases:
1)🔥 Overheating (High Growth, High Inflation)
2)📉 Stagflation (Low Growth, High Inflation)
3)🤒 Recovery (High Growth, Low Inflation)
4)🎈 Reflation (Low Growth, Low Inflation)
Data-Driven Analysis – Utilizes FRED (Federal Reserve Economic Data) for accurate real-world GDP & CPI data.
Trailing Path of Economic Evolution – Tracks historical economic cycles over time to show momentum and cyclical movements.
Customizable Parameters – Set sustainable GDP growth and inflation thresholds, adjust trail length, and fine-tune scatter plot resolution.
Auto-Labeled Quadrants & Revised Accurate Market Guidance – Each quadrant includes newly updated tooltips and annotations (like ETF suggestions) to help traders make informed decisions.
Live Macro Forecasting Tool – Helps traders anticipate future market conditions, rate hikes/cuts, and sector rotations.
How to Use for Trading Decisions
The Investment Clock Orbital Graph helps traders and macro investors by identifying market phases and providing insights into asset class performance during different economic conditions.
📌 Step 1: Identify the Current Quadrant
Locate the most recent point on the orbital graph to see if the economy is in Overheating, Stagflation, Recovery, or Reflation.
📌 Step 2: Forecast Market Trends
The trajectory of the points can predict upcoming economic shifts:
Overheating → Stagflation ➡️ Expect economic slowdowns, bearish stock markets.
Stagflation → Reflation ➡️ Interest rate cuts likely, bonds and defensive stocks perform well.
Reflation → Recovery ➡️ Risk-on rally, technology and cyclicals perform best.
Recovery → Overheating ➡️ Commodities surge, inflation rises, and central banks intervene.
📌 Step 3: Align Trading & Investing Strategies
🔥 Overheating – Favor commodities & energy (Oil, Industrial Stocks, Materials).
📉 Stagflation – Favor defensive assets (Cash, Utilities, Healthcare).
🤒 Recovery – Favor growth stocks (Technology, Consumer Discretionary).
🎈 Reflation – Favor bonds, value stocks, and financials.
📌 Step 4: Monitor Trends Over Time
The indicator visualizes economic movement over multiple months, allowing traders to confirm long-term trends vs. short-term noise.
The Investment Clock Orbital Graph is an essential macro trading tool, providing a real-time visualization of economic conditions. By tracking GDP growth vs. CPI inflation, traders and investors can align their portfolios with major macroeconomic shifts, predict sector rotations, and anticipate central bank policy changes.
Bitcoin Reversal PredictorOverview
This indicator displays two lines that, when they cross, signal a potential reversal in Bitcoin's price trend. Historically, the high or low of a bull market cycle often occurs near the moment these lines intersect. The lines consist of an Exponential Moving Average (EMA) and a logarithmic regression line fitted to all of Bitcoin's historical data.
Inspiration
The inspiration for this indicator came from the PI Cycle Top indicator, which has accurately predicted past bull market peaks. However, I believe the PI Cycle Top indicator may not be as effective in the future. In that indicator, two lines cross to mark the top, but the extent of the cross has been diminishing over time. This was especially noticeable in the 2021 cycle, where the lines barely crossed. Because of this, I created a new indicator that I think will continue to provide reliable reversal signals in the future.
How It Works
The logarithmic regression line is fitted to the Bitcoin (BTCUSD) chart using two key factors: the 'a' factor (slope) and the 'b' factor (intercept). This results in a steadily decreasing line. The EMA oscillates above and below this regression line. Each time the two lines cross, a vertical colored bar appears, indicating that Bitcoin's price momentum is likely to reverse.
Use Cases
- Price Bottoming:
Bitcoin often bottoms out when the EMA crosses below the logarithmic regression line.
- Price Topping:
In contrast, Bitcoin often peaks when the EMA crosses above the logarithmic regression line.
- Profitable Strategy:
Trading at the crossovers of these lines can be a profitable strategy, as these moments often signal significant price reversals.
Fourier For Loop [BackQuant]Fourier For Loop
PLEASE Read the following, as understanding an indicator's functionality is essential before integrating it into a trading strategy. Knowing the core logic behind each tool allows for a sound and strategic approach to trading.
Introducing BackQuant's Fourier For Loop (FFL) — a cutting-edge trading indicator that combines Fourier transforms with a for-loop scoring mechanism. This innovative approach leverages mathematical precision to extract trends and reversals in the market, helping traders make informed decisions. Let's break down the components, rationale, and potential use-cases of this indicator.
Understanding Fourier Transform in Trading
The Fourier Transform decomposes price movements into their frequency components, allowing for a detailed analysis of cyclical behavior in the market. By transforming the price data from the time domain into the frequency domain, this indicator identifies underlying patterns that traditional methods may overlook.
In this script, Fourier transforms are applied to the specified calculation source (defaulted to HLC3). The transformation yields magnitude values that can be used to score market movements over a defined range. This scoring process helps uncover long and short signals based on relative strength and trend direction.
Why Use Fourier Transforms?
Fourier Transforms excel in identifying recurring cycles and smoothing noisy data, making them ideal for fast-paced markets where price movements may be erratic. They also provide a unique perspective on market volatility, offering traders additional insights beyond standard indicators.
Calculation Logic: For-Loop Scoring Mechanism
The For Loop Scoring mechanism compares the magnitude of each transformed point in the series, summing the results to generate a score. This score forms the backbone of the signal generation system.
Long Signals: Generated when the score surpasses the defined long threshold (default set at 40). This indicates a strong bullish trend, signaling potential upward momentum.
Short Signals: Triggered when the score crosses under the short threshold (default set at -10). This suggests a bearish trend or potential downside risk.'
Thresholds & Customization
The indicator offers customizable settings to fit various trading styles:
Calculation Periods: Control how many periods the Fourier transform covers.
Long/Short Thresholds: Adjust the sensitivity of the signals to match different timeframes or risk preferences.
Visualization Options: Traders can visualize the thresholds, change the color of bars based on trend direction, and even color the background for enhanced clarity.
Trading Applications
This Fourier For Loop indicator is designed to be versatile across various market conditions and timeframes. Some of its key use-cases include:
Cycle Detection: Fourier transforms help identify recurring patterns or cycles, giving traders a head-start on market direction.
Trend Following: The for-loop scoring system helps confirm the strength of trends, allowing traders to enter positions with greater confidence.
Risk Management: With clearly defined long and short signals, traders can manage their positions effectively, minimizing exposure to false signals.
Final Note
Incorporating this indicator into your trading strategy adds a layer of mathematical precision to traditional technical analysis. Be sure to adjust the calculation start/end points and thresholds to match your specific trading style, and remember that no indicator guarantees success. Always backtest thoroughly and integrate the Fourier For Loop into a balanced trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future .
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Relative Performance vs BTC/ETH📊 Relative Performance vs BTC/ETH
This indicator allows you to compare the relative performance of any asset against BTC and ETH over the same timeframe. Instead of just looking at price movements in USDT, it shows whether the asset is outperforming or underperforming Bitcoin and Ethereum.
🔎 How It Works
Automatically detects the current chart’s symbol (e.g., BNBUSDT, SOLUSDT, etc.).
Fetches the closing prices of BTCUSDT and ETHUSDT from the same exchange.
Calculates relative ratios:
Coin vs BTC → coin price / BTC price
Coin vs ETH → coin price / ETH price
Normalizes both series to 1.0 at the first visible bar for easy comparison.
📈 What You’ll See
Orange Line → Performance of the current asset vs BTC
Purple Line → Performance of the current asset vs ETH
If the line is trending up, your coin is outperforming that benchmark.
If the line is trending down, your coin is underperforming.
🚀 Use Cases
Identify whether an altcoin is stronger than BTC or ETH during market moves.
Spot shifts in market strength (e.g., altcoin dominance phases).
Compare performance across different market cycles.
⚙️ Tips
Best used on higher timeframes (4H, 1D, 1W) to spot major trends.
Combine with price action or order flow to refine entries.
QLitCycle QuarterlyQLITCYCLE
QLitCycle is an intraday cycle visualization tool that divides each trading day into multiple segments, helping traders identify time-based patterns and recurring market behaviors. By splitting the day into distinct periods, this indicator allows for better analysis of intraday rhythms, cycle alignment, and time-specific market tendencies.
It can be applied to various markets and timeframes, but is most effective on intraday charts where precise time segmentation can reveal valuable insights.
Dividers Timeframe/Session/Calendar-Based [ARTech]Dividers Timeframe/Session/Calendar-Based
This indicator provides customizable visual dividers for multiple timeframes, trading sessions, and calendar-based periods (daily, weekly, monthly). It helps traders visually separate chart areas by key time boundaries without cluttering the chart with price lines.
Key Features:
Multi-Timeframe Dividers: Select up to 4 timeframes (e.g., 60 min, 4 hours, daily, weekly) to display customizable lines marking the start of each timeframe’s candle.
Session Dividers: Define up to 4 trading sessions with user-defined time zones, colors, and active weekdays. The indicator highlights the session’s highest and lowest price range using a box, and compares the session’s opening and closing prices. Based on this comparison, it displays a green or red emoji to indicate bullish or bearish sessions, making it easy to identify session momentum visually.
Calendar-Based Dividers: Enable daily, weekly, or monthly background color zones, with individual toggles and color settings for each day, week, or month. Perfect for visually distinguishing trading periods.
Why use this indicator?
Divider Indicator helps keep your chart organized by visually segmenting timeframes, sessions, and calendar periods, aiding in better analysis of price action relative to important time boundaries.
How to Use
███████ Timezone ███████
A valid timezone name exactly as it appears in the chart’s lower-right corner (e.g. New York, London).
A valid UTC offset in ±H:MM or ±HH:MM format. Hours: 0–14 (zero-padded or not, e.g. +1:30, +01:30, -0:00). Minutes: Must be 00, 15, 30, or 45.
Examples;
UTC → ✅ Valid
Exchange → ✅ Valid
New York → ✅ Valid
London → ✅ Valid
Berlin → ✅ Valid
America/New York → ❌ Invalid. (Use "New York" instead)
+1:30 → ✅ Valid offset with single-digit hour
+01:30 → ✅ Valid offset with zero-padded hour
-05:00 → ✅ Valid negative offset
-0:00 → ✅ Valid zero offset
+1:1 → ❌ Invalid (minute must be 00, 15, 30, or 45)
+2:50 → ❌ Invalid (minute must be 00, 15, 30, or 45)
+15:00 → ❌ Invalid (hour must be 14 or below)
███████ Timeframe ███████
Use this section to display vertical divider lines at the opening of higher timeframe candles (e.g., 1H, 4H, Daily, Weekly). This helps visually separate price action according to larger market structures.
1. Enable a Timeframe:
Turn on one or more timeframes (e.g., 60, 240, D, W) by checking their respective toggle boxes.
2. Lines Mark Candle Opens:
Each active timeframe will draw a vertical line at the start of its candle , making it easier to align intraday moves with larger timeframe shifts.
3. Customize Line Style:
For each timeframe, you can individually set:
Line Style: Solid, dashed, or dotted.
Line Width: From 1 to 10 pixels.
Line Color: Pick any color to match your chart theme.
Opacity: Use transparent colors to avoid overwhelming the chart.
4. Use Multiple Timeframes Together:
You can enable multiple timeframe dividers simultaneously. To maintain clarity:
Use distinct colors for each timeframe.
Use thinner or dotted lines for lower timeframes and bolder lines for higher ones.
Match line style and color intensity to reflect timeframe importance. (e.g., a thick green solid line for Weekly, a thin gray dotted line for 1H)
5. Visual Tip:
These dividers are especially useful for identifying higher timeframe candle opens during intraday trading, spotting breaks above/below previous candle ranges, or aligning session-based strategies with higher timeframe trends.
███████ Session ███████
Use this section to visually highlight specific trading sessions (e.g., London, New York, Tokyo, Sydney) on your chart using time zones, session ranges, and optional weekday filters. This helps focus your analysis on active market hours.
1. Enable a Session:
Activate up to 4 separate trading sessions. Each session can be named (e.g., "London") and customized independently.
2. Set Session Time and Days:
Define session time using the hhmm-hhmm format. (e.g., 0800-1700)
Select which days of the week the session applies to (Sunday through Saturday)
Set your preferred time zone (UTC, Exchange, etc.) from the global settings.
3. Session Box Drawing:
For each active session, the indicator will:
Draw a background-colored box from the session’s start to end time.
Stretch the box to fit the highest and lowest price within that time window.
Draw an outline using customizable border style and width.
4. Session Labels and Directional Hints:
Optionally display the session’s name as a label.
The indicator compares the session’s opening and closing prices . Based on the result:
📈 Green emoji shows a bullish session (close >= open)
📉 Red emoji shows a bearish session (close < open)
5. Display Options:
Show all sessions, only the last session, or a specific number of previous sessions.
Customize label size, location (top/bottom), and whether it appears inside or outside the box.
Adjust background opacity to blend the sessions neatly into your chart.
6. Visual Tip:
Session boxes are particularly useful for:
Spotting repeated highs/lows during active trading hours.
Recognizing session-based breakouts or consolidations.
Comparing performance across different markets and time zones.
███████ Calendar-Based ███████
This section helps you visually segment your chart based on calendar periods: daily, weekly, and monthly. You can enable background color highlighting for individual days, weeks, or months to better track price movements within these time frames.
1. Enable Daily, Weekly, or Monthly Highlighting:
Toggle on the options for Daily, Weekly, and/or Monthly highlighting according to your needs.
2. Select Specific Days, Weeks, or Months:
For Daily, enable any combination of days (up to 7) to color-code.
For Weekly, enable up to 5 weeks per month to cover partial weeks.
For Monthly, enable up to 12 months with individual toggles and colors.
3. Customize Colors for Each Period:
Assign distinct colors to each day, week, or month for easy differentiation. Choose hues that stand out but avoid colors that are too close in tone for adjacent periods.
4. Background Opacity:
Adjust the opacity level of the background coloring to ensure it complements your chart without obscuring price data.
5. Handling Partial Weeks and Overlaps:
The weekly highlighting accounts for months that span 4 to 6 weeks by allowing toggles up to 5 weeks, including weeks that may partially overlap with previous or next months.
6. Visual Tip:
Calendar-based backgrounds are excellent for:
Quickly identifying price behavior within specific calendar units.
Comparing price action across days, weeks, or months.
Spotting seasonal trends or recurring patterns tied to calendar cycles.
CirclesCircles - Support & Resistance Levels
Overview
This indicator plots horizontal support and resistance levels based on W.D. Gann's mathematical approach of dividing 360 degrees by 2 and by 3. These divisions create natural price magnetism points that have historically acted as significant support and resistance levels across all markets and timeframes.
How It Works
360÷2 Levels (Blue): 5.63, 11.25, 33.75, 56.25, 78.75, etc.
360÷3 Levels (Red): 7.5, 15, 30, 37.5, 52.5, 60, 75, etc.
Both Levels (Yellow): 22.5, 45, 67.5, 90, 112.5, 135, 157.5, 180 - These are "doubly strong" as they appear in both calculations
Key Features
Auto-Scaling: Automatically adjusts for any price range (from $0.001 altcoins to $100K+ Bitcoin)
Manual Scaling: Choose from 0.001x to 1000x multipliers or set custom values
Full Customization: Colors, line widths, styles (solid/dashed/dotted)
Historical View: Option to show all levels regardless of current price
Clean Display: Adjustable label positioning and line extensions
Use Cases
Identify potential reversal zones before price reaches them
Set profit targets and stop losses at key mathematical levels
Confirm breakouts when price decisively moves through major levels
Works on all timeframes and all markets (stocks, crypto, forex, commodities)
Gann Theory
W.D. Gann believed that markets move in mathematical harmony based on geometric angles and time cycles. These 360-degree divisions represent natural balance points where price often finds support or resistance, making them valuable for both short-term trading and long-term analysis.
Perfect for traders who use:
Support/Resistance trading
Fibonacci levels
Pivot points
Mathematical/geometric analysis
Multi-timeframe analysis
Bitcoin NUPL IndicatorThe Bitcoin NUPL (Net Unrealized Profit/Loss) Indicator is a powerful metric that shows the difference between Bitcoin's market cap and realized cap as a percentage of market cap. This indicator helps identify different market cycle phases, from capitulation to euphoria.
// How It Works
NUPL measures the aggregate profit or loss held by Bitcoin investors, calculated as:
```
NUPL = ((Market Cap - Realized Cap) / Market Cap) * 100
```
// Market Cycle Phases
The indicator automatically color-codes different market phases:
• **Deep Red (< 0%)**: Capitulation Phase - Most coins held at a loss, historically excellent buying opportunities
• **Orange (0-25%)**: Hope & Fear Phase - Early accumulation, price uncertainty and consolidation
• **Yellow (25-50%)**: Optimism & Anxiety Phase - Emerging bull market, increasing confidence
• **Light Green (50-75%)**: Belief & Denial Phase - Strong bull market, high conviction
• **Bright Green (> 75%)**: Euphoria & Greed Phase - Potential market top, historically good profit-taking zone
// Features
• Real-time NUPL calculation with customizable smoothing
• RSI indicator for additional momentum confirmation
• Color-coded background reflecting current market phase
• Reference lines marking key transition zones
• Detailed metrics table showing NUPL value, market sentiment, market cap, realized cap, and RSI
// Strategy Applications
• **Long-term investors**: Use extreme negative NUPL values (deep red) to identify potential bottoms for accumulation
• **Swing traders**: Look for transitions between phases for potential trend changes
• **Risk management**: Consider taking profits when entering the "Euphoria & Greed" phase (bright green)
• **Mean reversion**: Watch for overbought/oversold conditions when NUPL reaches historical extremes
// Settings
• **RSI Length**: Adjusts the period for RSI calculation
• **NUPL Smoothing Length**: Applies moving average smoothing to reduce noise
// Notes
• Premium TradingView subscription required for Glassnode and Coin Metrics data
• Best viewed on daily timeframes for macro analysis
• Historical NUPL extremes have often marked cycle bottoms and tops
• Use in conjunction with other indicators for confirmation
DTT Yearly Volatility Grid [Pro+] (NINE/ANARR)Introduction :
This tool is designed to automate the Digital Time Theory (DTT) framework created by Ivan and Anarr and applies the DTT Yearly Volatility Grid to uncover swing trading opportunities by analyzing Time-based statistical market behavior across the 4H to Daily chart.
Description:
Built upon the proprietary Digital Time Theory (DTT) , this advanced version is tailored for traders seeking multi-day to multi-week moves . It equips swing traders with an edge by analyzing macro Time intervals and volatility behavior across higher Timeframes. Applicable to all major asset classes, including stocks, crypto, forex, and futures , this script breaks down the entire yearly range into Higher-Time Frame Time Models and statistical zones .
This version uses daily intervals to track broader volatility waves, highlight the DTT framework, and pinpoint premium/discount areas across swing cycles. Powered by Time-driven data insights, this tool assists traders in anticipating expansions, understanding long-range Time distortions, and positioning around statistically significant zones in the higher-Time frame narrative.
Key Features:
Time-Based Models and Macro Volatility Awareness:
Automatically populates the chart with DTT Yearly Time Models (4H, Daily), engineered to spotlight macro volatility events across broader market sessions. Helps swing traders identify potential inflection points, reversals, or trend continuation zones.
Average Model Range Probability (AMRP):
Measure the average volatility expected over higher Time-based models. Use AMRP Levels and Projections to assess the range potential of each Yearly Model Time window—vital for monitoring reversals, breakouts, or continuation plays across several sessions or weeks.
Digital Root Candles and HTF Liquidity Draws:
For DTT Yearly Models, the Digital Root Candles are calculated as a specific Daily candle, and can be viewed on the Daily or 4H Timeframe. Analysts can frame premium and discount zones, based on where price is trading in relation to the current or previous model's Digital Roots. These areas also act as anchors for institutional price movement, often serving as bases for accumulation/distribution periods or large impulse moves.
Extended Visualization:
Track and project prior model ranges (high, low, equilibrium) into the current swing window. This helps visualize macro support/resistance , range expansion, failure zones, and price gravitation levels for longer-term trade planning.
Lookback Periods and Model Count
Utilize adjustable lookback periods to control the number of past DTT Yearly Models displayed—ideal for swing traders and quarterly outlooks. Whether you’re reviewing one yearly model to focus on the present range or several months’ worth of data for backtesting and confluence, this feature keeps charts clean, structured, and aligned with your preferred historical perspective.
By tailoring how many previous Time-based models appear on the chart, traders can better visualize and backtest repeated behaviors, major volatility clusters, and how key levels evolve over Time.
Detailed Data Table:
View statistical AMRP data for multiple DTT Yearly Models in real-Time. The data table helps confirm whether current price movement exceeds, respects, or fails to reach historical volatility ranges—key for analyzing market compression or expansion phases.
Customization Options:
Toggle inner Time interval, calculate AMRP utilizing a custom model lookback, and display styles (solid/dotted lines), including color coordination per drawing. Easily customize your charts and settings to fit your swing trading system or macro analysis.
How Swing Traders Can Use DTT Yearly Volatility Grid Effectively
Identify Swing Premium and Discount Zones:
Use Root Candles and Yearly Time Model AMRP Zones to evaluate where price is positioned in the current Time Model. Using this tool, traders can plan trades with a longer term horizon for a minimum of 1 to 2-weeks or manage entries/exits around market structure shifts and liquidity pools
Expect Macro Volatility Shifts:
Use the HTF models to forecast when and which volatility models are historically known to create larger market impulses . These tools help spot periods of potential exhaustion or breakout, especially near key economic releases, quarterly closes , or macro liquidity zones .
Avoid Low Volatility Consolidations:
AMRP helps you detect when the market is compressing or coiling within a DTT Yearly Model. If price is trading between Digital Root Candles or the AMRP zones, analysts are likely to notice periods of consolidation, and the inability to reach their historical volatility averages.
Usage Guidance:
Add DTT Yearly Volatility Grid (NINE/ANARR) to your TradingView chart.
Make sure to be on the 4H, or Daily Timeframes depending on your asset class and analysis.
Use the DTT Model elements and the Data Table to track expansion zones, premium/discount extremes, and model range behavior.
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