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.
스크립트에서 "Cycle"에 대해 찾기
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
CME Quarterly ShiftsCME Quarterly Shifts - Institutional Quarter Levels
Overview:
The CME Quarterly Shifts indicator tracks price action based on actual CME futures contract rollover dates, not calendar quarters. This indicator plots the Open, High, Low, and Close (OHLC) for each quarter, with quarters defined by the third Friday of March, June, September, and December - the exact dates when CME quarterly futures contracts expire and roll over.
Why CME Contract Dates Matter:
Institutional traders, hedge funds, and large market participants typically structure their positions around futures contract expiration cycles. By tracking quarters based on CME rollover dates rather than calendar months, this indicator aligns with how major institutional players view quarterly timeframes and position their capital.
Key Features:
✓ Automatic CME contract rollover date calculation (3rd Friday of Mar/Jun/Sep/Dec)
✓ Displays Quarter Open, High, Low, and Close levels
✓ Vertical break lines marking the start of each new quarter
✓ Quarter labels (Q1, Q2, Q3, Q4) for easy identification
✓ Adjustable history - show up to 20 previous quarters
✓ Fully customizable colors and line widths
✓ Works on any instrument and timeframe
✓ Toggle individual OHLC levels on/off
How to Use:
Quarter Open: The opening price when the new quarter begins (at CME rollover)
Quarter High: The highest price reached during the current quarter
Quarter Low: The lowest price reached during the current quarter
Quarter Close: The closing price from the previous quarter
These levels often act as key support/resistance zones as institutions reference them for quarterly performance, rebalancing, and position management.
Settings:
Display Options: Toggle quarterly break lines, OHLC levels, and labels
Max Quarters: Control how many historical quarters to display (1-20)
Colors: Customize colors for each level and break lines
Styles: Adjust line widths for OHLC levels and quarterly breaks
Best Practices:
Combine with other Smart Money Concepts (liquidity, order blocks, FVGs)
Watch for price reactions at quarterly Open levels
Monitor quarterly highs/lows as potential targets or stop levels
Use on higher timeframes (4H, Daily, Weekly) for clearer institutional perspective
Pairs well with monthly and yearly levels for multi-timeframe confluence
Perfect For:
ICT (Inner Circle Trader) methodology followers
Smart Money Concepts traders
Swing and position traders
Institutional-focused technical analysis
Traders tracking quarterly performance levels
Works on all markets: Forex, Indices, Commodities, Crypto, Stocks
Vertical Timelines Pro |MC|Vertical Timelines Pro |MC|
Credits go to lucemanb for the great work 👍
This indicator has been further developed and enhanced with additional features.
Vertical Timelines Pro is a customizable time-based indicator designed to mark important intraday timestamps directly on the chart. It helps traders visualize recurring market moments such as True Day Open, session opens, macro events, or personal timing models with precise vertical reference lines.
The indicator allows you to define multiple custom times, each with its own color and on/off toggle. All timestamps are calculated using a selectable timezone, ensuring consistent and accurate alignment across different markets and chart settings.
Optional labels can be displayed at each timeline to clearly identify the corresponding time. To keep the chart clean and readable, the number of visible labels can be limited retroactively. Due to Pine Script limitations, this setting only affects labels—plotted lines are not impacted.
💎 Key Features 💎
Multiple configurable intraday time markers
Timezone-aware calculations
Individual color and visibility control per line
Optional time labels with customizable size and colors
Historical label limiting to reduce chart clutter
Lightweight and suitable for all intraday timeframes
This indicator is ideal for traders who rely on time-based market behavior, session structure, or repeatable intraday cycles.
Happy Trading!
Macro Valuation Oscillator (MVO)Macro Valuation Oscillator (MVO) is a macro-relative-strength indicator that compares the current valuation of an asset against three key benchmarks: Gold, USD, and Bond. It helps visualize how the asset performs in relative macro terms over time.
When the MVO line for Gold (yellow) moves below the neutral zone (0), it reflects relative weakness against gold. When it rises above +80, it indicates relative strength or potential overheating compared to gold. The same concept applies to USD (blue) and Bond (purple) lines.
The indicator highlights macro-rotation behavior, showing periods when assets outperform (green) or underperform (red) in relative value. It is mainly intended for daily charts, providing a clear visual framework for assessing long-term macro relationships and timing within broader market cycles.
Hurst‑Millard FLD Normalized 2.0 – Signals "Hurst-Millard FLD Normalized 2.0 – Signals" indicator. It analyzes price data using a combination of moving averages (MAs) and the Hurst exponent to decompose price movements into trend, swing, and noise components, generating buy and sell signals. Here's a brief overview of its functionality:Inputs and Modes:Offers Auto Mode (cycle-based) and Manual Mode for configuring three moving averages: Long-Term (LT), Mid-Term (MT), and Short-Term (ST).
Auto Mode calculates MA lengths and offsets based on user-defined target cycle lengths (e.g., LT: 400 bars, MT: 100 bars, ST: 25 bars) with predefined offset ratios (0.2, 0.333, 0.5 respectively).
Manual Mode allows direct input of MA lengths and offsets.
Moving Averages:Computes Simple Moving Averages (SMAs) for LT, MT, and ST based on the closing price.
Applies forward-shifting to simulate future price behavior (e.g., maLongFwd shifts the LT MA by the specified offset).
Decomposition:Trend: Derived from the forward-shifted LT MA (maLongFwd).
Swing: Calculated as the difference between MT and LT MAs, scaled as a percentage of the closing price and amplified (using ATR or a manual factor).
Noise: Calculated as the difference between ST and MT MAs, similarly scaled and amplified.
Hurst Exponent:Estimates the Hurst exponent to measure the persistence or mean-reversion of the noise component.
Uses a 50-bar lookback period, smoothed with a 5-period SMA.
Signal Generation:Generates buy signals when the noise component is less than the swing component and their difference is within a user-defined proximity threshold (default: 25% of swing).
Generates sell signals when noise exceeds swing within the same threshold.
Signals are plotted as diamond shapes at the calculated proximity price level.
Visualization:Plots the trend, swing, and noise components as lines with customizable colors and gradient intensity based on their relative strength.
Optional debugging plots for raw forward-shifted MAs and proximity thresholds.
Displays a periodic debug table (every 100 bars) showing key metrics like close price, MAs, trend, swing, noise, Hurst exponent, and more.
Additional Features:Supports ATR-based amplification for scaling swing and noise.
Allows customization of signal colors, diamond offsets, and proximity thresholds.
Includes debugging options to visualize raw MAs and proximity bands.
In summary, this indicator uses cycle-based or manually configured MAs to break down price action into trend, swing, and noise, calculates the Hurst exponent for noise analysis, and generates buy/sell signals based on the relationship between swing and noise within a proximity threshold. It’s designed for traders to identify potential trend reversals or continuations.
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.
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
Simple Parallel Channel TrackerThis script will automatically draw price channels with two parallel trends lines, the upper trendline and lower trendline. These lines can be changed in terms of appearance at any time.
The Script takes in fractals from local and historic price action points and connects them over a certain period or amount of candles as inputted by the user. It tracks the most recent highs and lows formed and uses this data to determine where the channel begins.
The Script will decide whether to use the most recent high, or low, depending on what comes first.
Why is this useful?
Often, Traders either have no trend lines on their charts, or they draw them incorrectly. Whichever category a trader falls into, there can only be benefits from having Trend lines and Parallel Channels drawn automatically.
Trends naturally occur in all Markets, all the time. These oscillations when tracked allow for a more reliable following of Markets and management of Market cycles.
Abdozo - Highlight First DaysAbdozo - Highlight First Days Indicator
This Pine Script indicator helps traders easily identify key timeframes by highlighting the first trading day of the week and the first day of the month. It provides visual markers directly on your chart, helping you stay aware of potential market trends and turning points.
Features:
- Highlight First Day of the Week (Monday): Automatically marks Mondays to help you track weekly market cycles.
- Highlight First Day of the Month: Spot the start of each month with ease to analyze monthly performance and trends.
Market Health MonitorThe Market Health Monitor is a comprehensive tool designed to assess and visualize the economic health of a market, providing traders with vital insights into both current and future market conditions. This script integrates a range of critical economic indicators, including unemployment rates, inflation, Federal Reserve funds rates, consumer confidence, and housing market indices, to form a robust understanding of the overall economic landscape.
Drawing on a variety of data sources, the Market Health Monitor employs moving averages over periods of 3, 12, 36, and 120 months, corresponding to quarterly, annual, three-year, and ten-year economic cycles. This selection of timeframes is specifically chosen to capture the nuances of economic movements across different phases, providing a balanced view that is sensitive to both immediate changes and long-term trends.
Key Features:
Economic Indicators Integration: The script synthesizes crucial economic data such as unemployment rates, inflation levels, and housing market trends, offering a multi-dimensional perspective on market health.
Adaptability to Market Conditions: The inclusion of both short-term and long-term moving averages allows the Market Health Monitor to adapt to varying market conditions, making it a versatile tool for different trading strategies.
Oscillator Thresholds for Recession and Growth: The script sets specific thresholds that, when crossed, indicate either potential economic downturns (recessions) or periods of growth (expansions), allowing traders to anticipate and react to changing market conditions proactively.
Color-Coded Visualization: The Market Health Monitor employs a color-coding system for ease of interpretation:
-- A red background signals unhealthy economic conditions, cautioning traders about potential risks.
-- A bright red background indicates a confirmed recession, as declared by the NBER, signaling a critical time for traders to reassess risk exposure.
-- A green background suggests a healthy market with expected economic expansion, pointing towards growth-oriented opportunities.
Comprehensive Market Analysis: By combining various economic indicators, the script offers a holistic view of the market, enabling traders to make well-informed decisions based on a thorough understanding of the economic environment.
Key Criteria and Parameters:
Economic Indicators:
Labor Market: The unemployment rate is a critical indicator of economic health.
High or rising unemployment indicates reduced consumer spending and economic stress.
Inflation: Key for understanding monetary policy and consumer purchasing power.
Persistent high inflation can lead to economic instability, while deflation can signal weak
demand.
Monetary Policy: Reflected by the Federal Reserve funds rate.
Changes in the rate can influence economic activity, borrowing costs, and investor
sentiment.
Consumer Confidence: A predictor of consumer spending and economic activity.
Reflects the public’s perception of the economy
Housing Market: The housing market often leads the economy into recession and recovery.
Weakness here can signal broader economic problems.
Market Data:
Stock Market Indices: Reflect overall investor sentiment and economic
expectations. No gains in a stock market could potentially indicate that economy is
slowing down.
Credit Conditions: Indicated by the tightness of bank lending, signaling risk
perception.
Commodity Insight:
Crude Oil Prices: A proxy for global economic activity.
Indicator Timeframe:
A default monthly timeframe is chosen to align with the release frequency of many economic indicators, offering a balanced view between timely data and avoiding too much noise from short-term fluctuations. Surely, it can be chosen by trader / analyst.
The Market Health Monitor is more than just a trading tool—it's a comprehensive economic guide. It's designed for traders who value an in-depth understanding of the economic climate. By offering insights into both current conditions and future trends, it encourages traders to navigate the markets with confidence, whether through turbulent times or in periods of growth. This tool doesn't just help you follow the market—it helps you understand it.
Dark Energy Divergence OscillatorThe Dark Energy Divergence Oscillator (DEDO)
What makes The Universe grow at an accelerating pace?
Dark Energy.
What makes The Economy grow at an accelerating pace?
Debt.
Debt is the Dark Energy of The Economy.
I pronounce DEDO "Deed-oh", but variations are fine with me.
Note: The Pine Script version of DEDO is improved from the original formula, which used a constant all-time high calculation in the normalization factor. This was technically not as accurate for calculating liquidity pressure in historical data because it meant that historical prices were being tested against future liquidity factors. Now using Pine, the functions can be normalized for the bar at the time of calculation, so the liquidity factors are normalized per candle, not across the entire series, which feels like an improvement to me.
Thought Process:
It's all about the liquidity. What I started with is a correlation between major stock indices such as SPX and WRESBAL , a balance sheet metric on FRED
After September 2008, when QE was initiated, many asset valuations started to follow more closely with liquidity factors. This led me to create a function that could combine asset prices and liquidity in WRESBAL , in order to calculate their divergence and chart the signal in TradingView.
The original formula:
First, we don't want "non-QE" data. we only want data for the market affected by QE .
So, find SPX on the day of pre-QE: 1255.08 and subtract that from the 2022 top 4818.62 = 3563.54
With this post-QE SPX range, now you can normalize the price level simply by dividing by the range = ( SPX -1255.08)/3563.54)
Normalization produces values from 0 to 1 so that they can be compared with other normalized figures.
In order to test the 0 to 1 normalized SPX range measure against the liquidity number, WRESBAL , it's the same idea: normalize it using the max as the denominator and you get a 0 to 1 liquidity index:
( WRESBAL /4276000000000)
Subtract one from the other to get the divergence:
(( WRESBAL /4276000000000)-(( SPX -1255.08)/3563.54))*10
x10 to reduce decimal places, but this option is configurable in DEDO's input settings tab.
Positive values indicate there's ample liquidity to hold up price or even create bullish momentum in some cases. Negative values mean price levels are potentially extended beyond what liquidity levels can support.
Note: many viewers of the charts on social media wanted the values to go down in alignment with price moving down, so inverting the chart is what I do with Option + I. I like the fact that negative values represent a deficit in liquidity to hold up price but that's just me.
Now with Pine Script and some help from other liquidity focused accounts on TradingView , I was able to derive a script that includes central bank liquidity and Reverse Repo liquidity drain, all in one algorithm, with adjustable settings.
Central bank assets included in this version:
-JPY (Japan)
-CNY (China)
-UK (British Pound)
-SNB (Swiss National Bank)
-ECB (European Central Bank )
Central Bank assets can be adjusted to an allocation % so that the formula is adjusted for the market cap of the asset.
A handy table in the lower right corner displays useful information about the asset market cap, and percentage it represents in the liquidity pool.
Reverse repo soak is also an optional addition in the Input settings using the RRPONTSYD value from FRED. This value is subtracted from global liquidity used to determine divergence since it is swept away from markets when residing in the Fed's reverse repo facility.
There is an option to draw a line at the Zero bound. This provides a convenience so that the line doesn't keep having to be redrawn on every chart. The normalized equation produces a value that should oscillate around zero, as price/valuation grows past liquidity support, falls under it, and repeats in cycles.
S&P 500 Quandl Data & RatiosTradingView has a little-known integration that allows you to pull in 3rd party data-sets from Nasdaq Data Link, also known as Quandl. Today, I am open-sourcing for the community an indicator that uses the Quandl integration to pull in historical data and ratios on the S&P500. I originally coded this to study macro P/E ratios during peaks and troughs of boom/bust cycles.
The indicator pulls in each of the following datasets, as defined and provided by Quandl. The user can select which datasets to pull in using the indicator settings:
Dividend Yield : S&P 500 dividend yield (12 month dividend per share)/price. Yields following June 2022 (including the current yield) are estimated based on 12 month dividends through June 2022, as reported by S&P. Sources: Standard & Poor's for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.
Price Earning Ratio : Price to earnings ratio, based on trailing twelve month as reported earnings. Current PE is estimated from latest reported earnings and current market price. Source: Robert Shiller and his book Irrational Exuberance for historic S&P 500 PE Ratio.
CAPE/Shiller PE Ratio : Shiller PE ratio for the S&P 500. Price earnings ratio is based on average inflation-adjusted earnings from the previous 10 years, known as the Cyclically Adjusted PE Ratio (CAPE Ratio), Shiller PE Ratio, or PE 10 FAQ. Data courtesy of Robert Shiller from his book, Irrational Exuberance.
Earnings Yield : S&P 500 Earnings Yield. Earnings Yield = trailing 12 month earnings divided by index price (or inverse PE) Yields following March, 2022 (including current yield) are estimated based on 12 month earnings through March, 2022 the latest reported by S&P. Source: Standard & Poor's
Price Book Ratio : S&P 500 price to book value ratio. Current price to book ratio is estimated based on current market price and S&P 500 book value as of March, 2022 the latest reported by S&P. Source: Standard & Poor's
Price Sales Ratio : S&P 500 Price to Sales Ratio (P/S or Price to Revenue). Current price to sales ratio is estimated based on current market price and 12 month sales ending March, 2022 the latest reported by S&P. Source: Standard & Poor's
Inflation Adjusted SP500 : Inflation adjusted SP500. Other than the current price, all prices are monthly average closing prices. Sources: Standard & Poor's Robert Shiller and his book Irrational Exuberance for historic S&P 500 prices, and historic CPIs.
Revenue Per Share : Trailing twelve month S&P 500 Sales Per Share (S&P 500 Revenue Per Share) non-inflation adjusted current dollars. Source: Standard & Poor's
Earnings Per Share : S&P 500 Earnings Per Share. 12-month real earnings per share inflation adjusted, constant August, 2022 dollars. Sources: Standard & Poor's for current S&P 500 Earnings. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Earnings.
Disclaimer: This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
ln(close/20 sma) adjusted for time (BTC)(This indicator was designed for the BTC index chart)
Designed for Bitcoin. Plots the log of the close/20W SMA with a linear offset m*t, where m is the gradient I've chosen and t is the candle index. Anything above 1 is a mania phase/market cycle top. If it peaks around 0.92 and rolls over, it could be a local/market cycle top.
This will obviously not work at all in the long term as Bitcoin will not continue following the trend line on the log plot (you can even see it start to deviate in the Jan-Feb 2021 peaks where the indicator went to 1.15).
It identifies the 2011, 2013 (both of them), 2017 tops as being just above 1. It also identifies the 2019 local peak and 2021 market cycle top at ~0.94.
Feel free to change the gradient or even add a function to curve the straight line eventually. I made this for fun, feel free to use it as you wish.
Multi-Metric Market Regime Detector - [KK]This indicator identifies current market behavioral regimes by synthesizing six complementary analytical methodologies. Rather than generating trading signals, it provides contextual analysis to help traders understand market conditions and adapt their strategies accordingly.
Markets cycle through distinct behavioral states - trending efficiently, consolidating in ranges, compressing before breakouts, or transitioning between states. This tool quantifies these conditions using only price action data (OHLC), enabling traders to filter strategies based on current market structure.
Core Methodology
The indicator combines six independent metrics into a weighted composite classification system:
Efficiency Ratio (30% weight)
Measures the signal-to-noise ratio of price movement by comparing net price displacement to total path traveled. High efficiency indicates clean directional movement; low efficiency indicates choppy, noisy conditions.
Choppiness Index (25% weight)
Quantifies whether the market is trending or consolidating by comparing cumulative True Range to actual price range. Values below 38.2 suggest trending behavior; values above 61.8 suggest range-bound consolidation.
Volatility Analysis (20% weight)
Detects compression and expansion cycles using the relationship between Bollinger Bands and Keltner Channels. Compression phases (squeeze conditions) often precede significant directional moves.
Fractal Efficiency Proxy (10% weight)
Analyzes path complexity by comparing net displacement to cumulative range, providing insight into the smoothness versus randomness of price action.
Market Structure (15% weight)
Examines pivot point sequences to identify structural trends. Higher Highs and Higher Lows indicate bullish structure; Lower Lows and Lower Highs indicate bearish structure.
Wick-to-Body Ratio Analysis (qualitative)
Identifies rejection and indecision patterns by measuring the proportion of candle wicks to bodies, highlighting potential reversal zones or liquidity events.
Regime Classifications
The composite scoring system produces four distinct regime states:
TRENDING : High efficiency, low choppiness, clear directional structure. Favorable conditions for momentum and trend-following strategies.
CHOPPY/RANGE : Low efficiency, high choppiness, mean-reverting behavior. Favorable conditions for range trading and counter-trend setups.
COMPRESSION : Volatility squeeze detected, market coiling. Anticipate expansion; reduce position size until breakout confirmation.
TRANSITION : Mixed signals, conflicting metrics, unclear direction. Recommended to reduce exposure and wait for regime clarity.
Visual Features
Regime-Colored Candles (enabled by default)
Candles are colored according to the current regime state for immediate visual identification. Green indicates trending, gray indicates choppy, orange indicates compression, and yellow indicates transition.
Comprehensive Metrics Table (top right)
Displays real-time values for all six metrics along with individual regime assessments and the final composite classification with score.
Regime Guide Table (middle right)
Quick reference guide showing recommended strategies and actions to avoid for each regime state.
Chart Label ( optional)
Summary label displaying current regime and key metric values.
Background Coloring (optional)
Alternative visualization using background colors instead of candle coloring.
Indicator Plots (optional)
Displays Efficiency Ratio and Choppiness Index with threshold reference lines.
Customization Options
All calculation parameters are adjustable:
- Efficiency Ratio lookback period and thresholds
- Choppiness Index length and classification thresholds
- Volatility analysis parameters (BB/KC multipliers and lengths)
- Pivot detection sensitivity (left/right bars)
- Text size controls for both tables (Tiny to Huge)
- Visual element toggles (candles, background, label, tables, plots)
The indicator automatically detects chart theme (dark/light) and adjusts text colors for optimal readability.
Practical Application
This is a context tool, not a signal generator. Use it to:
- Filter trend-following strategies to trending regimes only
- Identify range-bound conditions for mean-reversion setups
- Anticipate breakout opportunities during compression phases
- Reduce exposure during transitional periods with mixed signals
- Improve risk management by matching position size to regime clarity
The indicator works on all timeframes and instruments using only OHLC data. Higher timeframes generally provide more stable regime classifications.
Alert Conditions
Four alert types are available:
- Efficiency Ratio crosses trend threshold
- Choppiness Index enters range territory
- Volatility squeeze released
- Regime state change detected
Technical Notes
Built with Pine Script v5. Uses up to 500 bars of historical data for stable calculations. All metrics are calculated in real-time with no repainting on confirmed pivots. Compatible with all chart themes through adaptive text coloring.
Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice or trading recommendations. Past performance and theoretical analysis do not guarantee future results. Always conduct independent research and implement appropriate risk management. Trading financial instruments involves substantial risk of loss.
Usage Philosophy
The goal is not to trade more frequently, but to think more clearly about market conditions. Use this tool to develop deeper intuition about market structure and to enforce discipline by avoiding low-probability setups during unfavorable regime conditions.
TZ - India VIX Volatility ZonesTZ – India VIX Volatility Zones is a long-term volatility analysis indicator designed to visually map important India VIX regimes using clearly defined horizontal zones and labels.
The indicator highlights how market volatility cycles between complacency, normal conditions, elevated risk, and panic phases. These zones are based on historical behavior of India VIX and help traders understand when risk is underpriced or overstretched.
This tool is especially useful for:
Index traders
Options sellers and buyers
Risk management and regime filtering
Long-term volatility study
How It Works
The script plots static, historically significant volatility zones on the India VIX chart and visually separates them using shaded bands and labels.
Volatility Zones Explained
1.Extreme Low Volatility (VIX 8–10)
Indicates market complacency and underpriced risk. Often precedes volatility expansion.
2.Low Volatility (VIX 10–13)
Stable market conditions with controlled movement.
3.Normal Volatility (VIX 13–18)
Healthy market behavior and balanced risk.
4.High Volatility (VIX 18–25)
Rising uncertainty and increased intraday swings.
5.Panic Zone (VIX 25–35+)
High fear environment, usually during major events or crises.
How Traders Can Use This Indicator
Identify volatility regimes before choosing option strategies
Avoid aggressive short-volatility trades during extreme zones
Prepare for volatility expansion during low-VIX phases
Use as a market risk context tool alongside price action
This indicator does not provide buy/sell signals. It is designed for contextual analysis and decision support.
Best Usage
Apply on India VIX (NSE:INDIAVIX)
Works best on Weekly and Monthly timeframes
Can be combined with index charts for volatility-based risk assessment
Disclaimer
This indicator is for educational and analytical purposes only.
It does not constitute financial advice or trade recommendations.
Users should apply proper risk management and confirm signals using additional analysis.
FOMC Federal Fund Rate Tracker [MHA Finverse]The FOMC Rate Tracker is a comprehensive indicator that visualizes Federal Reserve interest rate decisions and tracks market behavior during FOMC meeting periods. This tool helps traders analyze historical rate changes and anticipate market movements around Federal Open Market Committee announcements.
Key Features:
• Visual FOMC Periods - Automatically highlights each FOMC meeting period with colored boxes spanning from announcement to the next meeting
• Complete Rate Data - Displays actual rates, forecasts, previous rates, and rate differences for every meeting from 2021-2026
• Multiple Color Modes - Choose between cycle colors for visual distinction or rate difference colors (green for hikes, red for cuts, gray for holds)
• Smart Filtering - Filter periods by rate hikes only, cuts only, no change, or surprise moves to focus on specific market conditions
• Performance Metrics - Track average returns during rate hikes, cuts, and holds to identify historical patterns
• Volatility Analysis - Measure and compare price volatility across different FOMC periods
• Statistical Dashboard - View total hikes, cuts, holds, surprises, and longest hold streaks at a glance
• Built-in Alerts - Get notified 1 day before FOMC meetings, on meeting day, or when rates change
How It Works:
The indicator divides your chart into distinct periods between FOMC meetings, with each period showing a labeled box containing the meeting date, actual rate, forecast, previous rate, and rate difference. Future meetings are marked as "UPCOMING" to help you prepare for scheduled announcements.
Use Cases:
- Analyze how markets typically react to rate hikes vs. cuts
- Identify volatility patterns around FOMC announcements
- Backtest strategies based on monetary policy cycles
- Plan trades around upcoming Federal Reserve meetings
- Study the impact of surprise rate decisions on price action
Customization Options:
- Adjustable box transparency and outlines
- Customizable label sizes and colors
- Toggle individual dashboards on/off
- Filter specific types of rate decisions
- Configure alert preferences
This indicator is ideal for traders who incorporate fundamental analysis and monetary policy into their trading decisions. The historical data provides context for understanding market reactions to Federal Reserve actions.
Intraday Key OpensIntraday Key Opens plots the key session and cycle opening prices: 90-minute cycles opens, New York open, Asia open, and 9:30 US market open. Each line is labeled, color-coded, and can be toggled on/off independently. Designed for intraday traders to quickly identify important price levels and session pivots.
Dani u nedelji + midnight open @mladja123This indicator breaks the weekly timeframe into cycles and marks the midnight open for each day. It helps traders visualize weekly structure, identify key daily openings, and track market rhythm within the week. Perfect for analyzing trend patterns, swing setups, and session-based strategies.
Modern Economic Eras DashboardOverview
This script provides a historical macroeconomic visualization of U.S. markets, highlighting long-term structural "eras" such as the Bretton Woods period, the inflationary 1970s, and the post-2020 "Age of Disorder." It overlays key economic indicators sourced from FRED (Federal Reserve Economic Data) and displays notable market crashes, all in a clean and rescaled format for easy comparison.
Data Sources & Indicators
All data is loaded monthly from official FRED series and rescaled to improve readability:
🔵 Real GDP (FRED:GDP): Total output of the U.S. economy.
🔴 Inflation Index (FRED:CPIAUCSL): Consumer price index as a proxy for inflation.
⚪ Debt to GDP (FRED:GFDGDPA188S): Federal debt as % of GDP.
🟣 Labor Force Participation (FRED:CIVPART): % of population in the labor force.
🟠 Oil Prices (FRED:DCOILWTICO): Monthly WTI crude oil prices.
🟡 10Y Real Yield (FRED:DFII10): Inflation-adjusted yield on 10-year Treasuries.
🔵 Symbol Price: Optionally overlays the charted asset’s price, rescaled.
Historical Crashes
The dashboard highlights 10 major U.S. market crashes, including 1929, 2000, and 2008, with labeled time spans for quick context.
Era Classification
Six macroeconomic eras based on Deutsche Bank’s Long-Term Asset Return Study (2020) are shaded with background color. Each era reflects dominant economic regimes—globalization, wars, monetary systems, inflationary cycles, and current geopolitical disorder.
Best Use Cases
✅ Long-term macro investors studying structural market behavior
✅ Educators and analysts explaining economic transitions
✅ Portfolio managers aligning strategy with macroeconomic phases
✅ Traders using history for cycle timing and risk assessment
Technical Notes
Designed for monthly timeframe, though it works on weekly.
Uses close price and standard request.security calls for consistency.
Max labels/lines configured for broader history (from 1860s to present).
All plotted series are rescaled manually for better visibility.
Originality
This indicator is original and not derived from built-in or boilerplate code. It combines multiple economic dimensions and market history into one interactive chart, helping users frame today's markets in a broader structural context.
Log Regression OscillatorThe Log Regression Oscillator transforms the logarithmic regression curves into an easy-to-interpret oscillator that displays potential cycle tops/bottoms.
🔶 USAGE
Calculating the logarithmic regression of long-term swings can help show future tops/bottoms. The relationship between previous swing points is calculated and projected further. The calculated levels are directly associated with swing points, which means every swing point will change the calculation. Importantly, all levels will be updated through all bars when a new swing is detected.
The "Log Regression Oscillator" transforms the calculated levels, where the top level is regarded as 100 and the bottom level as 0. The price values are displayed in between and calculated as a ratio between the top and bottom, resulting in a clear view of where the price is situated.
The main picture contains the Logarithmic Regression Alternative on the chart to compare with this published script.
Included are the levels 30 and 70. In the example of Bitcoin, previous cycles showed a similar pattern: the bullish parabolic was halfway when the oscillator passed the 30-level, and the top was very near when passing the 70-level.
🔹 Proactive
A "Proactive" option is included, which ensures immediate calculations of tentative unconfirmed swings.
Instead of waiting 300 bars for confirmation, the "Proactive" mode will display a gray-white dot (not confirmed swing) and add the unconfirmed Swing value to the calculation.
The above example shows that the "Calculated Values" of the potential future top and bottom are adjusted, including the provisional swing.
When the swing is confirmed, the calculations are again adjusted, showing a red dot (confirmed top swing) or a green dot (confirmed bottom swing).
🔹 Dashboard
When less than two swings are available (top/bottom), this will be shown in the dashboard.
The user can lower the "Threshold" value or switch to a lower timeframe.
🔹 Notes
Logarithmic regression is typically used to model situations where growth or decay accelerates rapidly at first and then slows over time, meaning some symbols/tickers will fit better than others.
Since the logarithmic regression depends on swing values, each new value will change the calculation. A well-fitted model could not fit anymore in the future.
Users have to check the validity of swings; for example, if the direction of swings is downwards, then the dataset is not fitted for logarithmic regression.
In the example above, the "Threshold" is lowered. However, the calculated levels are unreliable due to the swings, which do not fit the model well.
Here, the combination of downward bottom swings and price accelerates slower at first and faster recently, resulting in a non-fit for the logarithmic regression model.
Note the price value (white line) is bound to a limit of 150 (upwards) and -150 (down)
In short, logarithmic regression is best used when there are enough tops/bottoms, and all tops are around 100, and all bottoms around 0.
Also, note that this indicator has been developed for a daily (or higher) timeframe chart.
🔶 DETAILS
In mathematics, the dot product or scalar product is an algebraic operation that takes two equal-length sequences of numbers (arrays) and returns a single number, the sum of the products of the corresponding entries of the two sequences of numbers.
The usual way is to loop through both arrays and sum the products.
In this case, the two arrays are transformed into a matrix, wherein in one matrix, a single column is filled with the first array values, and in the second matrix, a single row is filled with the second array values.
After this, the function matrix.mult() returns a new matrix resulting from the product between the matrices m1 and m2.
Then, the matrix.eigenvalues() function transforms this matrix into an array, where the array.sum() function finally returns the sum of the array's elements, which is the dot product.
dot(x, y)=>
if x.size() > 1 and y.size() > 1
m1 = matrix.new()
m2 = matrix.new()
m1.add_col(m1.columns(), y)
m2.add_row(m2.rows (), x)
m1.mult (m2)
.eigenvalues()
.sum()
🔶 SETTINGS
Threshold: Period used for the swing detection, with higher values returning longer-term Swing Levels.
Proactive: Tentative Swings are included with this setting enabled.
Style: Color Settings
Dashboard: Toggle, "Location" and "Text Size"
Altcoin Relative Macro StrengthAltcoin Relative Macro Strength
Overview
The Altcoin Relative Macro Strength indicator measures the altcoin market's price performance relative to global macroeconomic conditions. By comparing TOTAL3ES (total altcoin market capitalization excluding Bitcoin, Ethereum and stable coins) against a composite macro trend, the indicator identifies periods of relative overvaluation and undervaluation.
Methodology
Global Macro Trend Calculation:
The macro trend synthesizes three primary components:
- ISM PMI – A proxy for the business cycle phase
- Global Liquidity – An aggregate measure of major central bank balance sheets and broad money supply
- IWM (Russell 2000) – Small-cap equity exposure, reflecting risk-on/risk-off market sentiment
Global Liquidity is calculated as:
Fed Balance Sheet - Reverse Repo - Treasury General Account + U.S. M2 + China M2
The final Global Macro Trend is:
ISM PMI × Global Liquidity × IWM
Theoretical Framework:
The global macro trend integrates liquidity expansion/contraction with business cycle dynamics and small-cap equity performance. The inclusion of IWM reflects altcoins' tendency to behave as high-beta risk assets, exhibiting sensitivity similar to small-cap equities. This composite exhibits strong directional correlation with altcoin market movements, capturing the risk-on/risk-off dynamics that drive altcoin performance.
Interpretation
Primary Signal:
The histogram displays the rolling percentage change of TOTAL3ES relative to the global macro trend (default: 21-period average). Positive divergence indicates altcoins are outperforming macro conditions; negative divergence suggests underperformance relative to the underlying economic and risk environment.
Data Tables:
Alts/Macro Change – Percentage deviation of the altcoin market's average value from the Global Macro Trend's average over the specified period
Macro Trend – Directional assessment of the macro trend based on slope and trend agreement:
🔵 BULLISH ▲ – Positive slope with upward trend
⚪ NEUTRAL → – Slope and trend direction disagree
🟣 BEARISH ▼ – Negative slope with downward trend
Macro Slope – Percentage rate of change in the global macro trend
Altcoin Valuation – Relative valuation category based on TOTAL3/Macro deviation:
🟢 Extreme Discount / Deep Discount / Discount
🟡 Fair Value
🔴 Premium / Large Premium / Extreme Premium
TOTAL3ES Mcap – Current total altcoin market capitalization (in billions)
Visual Components:
📊 Histogram: Alts/Macro Change
🟢 Green = Positive deviation (altcoins outperforming)
🔴 Red = Negative deviation (altcoins underperforming)
📈 Macro Slope Line
Color-coded to match trend assessment
Scaled for visibility (adjustable in settings)
Application
This indicator is designed to identify mean reversion opportunities by highlighting periods when the altcoin market materially diverges from fundamental macro and risk conditions. Extreme positive values may indicate overvaluation; extreme negative values may signal undervaluation relative to the prevailing economic and risk appetite backdrop.
Strategy Considerations:
- Identify extremes: Look for periods when the histogram reaches elevated positive or negative levels
- Assess valuation: Use the Altcoin Valuation reading to gauge relative over/undervaluation
Confirm with risk sentiment: Check whether macro conditions and risk appetite support or contradict current price levels
- Mean reversion: Consider that significant deviations from trend historically tend to revert
Note: This indicator identifies relative valuation based on macro conditions and risk sentiment—it does not predict price direction or timing.
Settings
Lookback Period – 21 bars (default) – Number of bars for calculating rolling averages
Macro Slope Scale – 3.0 (default) – Multiplier for macro slope line visibility
